Identification and Inference for Econometric Models
NASA Astrophysics Data System (ADS)
Andrews, Donald W. K.; Stock, James H.
2005-07-01
This volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose new ones. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.
Nassios, Jason; Giesecke, James A
2018-04-01
Economic consequence analysis is one of many inputs to terrorism contingency planning. Computable general equilibrium (CGE) models are being used more frequently in these analyses, in part because of their capacity to accommodate high levels of event-specific detail. In modeling the potential economic effects of a hypothetical terrorist event, two broad sets of shocks are required: (1) physical impacts on observable variables (e.g., asset damage); (2) behavioral impacts on unobservable variables (e.g., investor uncertainty). Assembling shocks describing the physical impacts of a terrorist incident is relatively straightforward, since estimates are either readily available or plausibly inferred. However, assembling shocks describing behavioral impacts is more difficult. Values for behavioral variables (e.g., required rates of return) are typically inferred or estimated by indirect means. Generally, this has been achieved via reference to extraneous literature or ex ante surveys. This article explores a new method. We elucidate the magnitude of CGE-relevant structural shifts implicit in econometric evidence on terrorist incidents, with a view to informing future ex ante event assessments. Ex post econometric studies of terrorism by Blomberg et al. yield macro econometric equations that describe the response of observable economic variables (e.g., GDP growth) to terrorist incidents. We use these equations to determine estimates for relevant (unobservable) structural and policy variables impacted by terrorist incidents, using a CGE model of the United States. This allows us to: (i) compare values for these shifts with input assumptions in earlier ex ante CGE studies; and (ii) discuss how future ex ante studies can be informed by our analysis. © 2017 Society for Risk Analysis.
Bayesian Nonparametric Prediction and Statistical Inference
1989-09-07
Kadane, J. (1980), "Bayesian decision theory and the sim- plification of models," in Evaluation of Econometric Models, J. Kmenta and J. Ramsey , eds...the random model and weighted least squares regression," in Evaluation of Econometric Models, ed. by J. Kmenta and J. Ramsey , Academic Press, 197-217...likelihood function. On the other hand, H. Jeffreys’s theory of hypothesis testing covers the most important situations in which the prior is not diffuse. See
Scale Mixture Models with Applications to Bayesian Inference
NASA Astrophysics Data System (ADS)
Qin, Zhaohui S.; Damien, Paul; Walker, Stephen
2003-11-01
Scale mixtures of uniform distributions are used to model non-normal data in time series and econometrics in a Bayesian framework. Heteroscedastic and skewed data models are also tackled using scale mixture of uniform distributions.
Much ado about two: reconsidering retransformation and the two-part model in health econometrics.
Mullahy, J
1998-06-01
In health economics applications involving outcomes (y) and covariates (x), it is often the case that the central inferential problems of interest involve E[y/x] and its associated partial effects or elasticities. Many such outcomes have two fundamental statistical properties: y > or = 0; and the outcome y = 0 is observed with sufficient frequency that the zeros cannot be ignored econometrically. This paper (1) describes circumstances where the standard two-part model with homoskedastic retransformation will fail to provide consistent inferences about important policy parameters; and (2) demonstrates some alternative approaches that are likely to prove helpful in applications.
Attrition Bias in Panel Data: A Sheep in Wolf's Clothing? A Case Study Based on the Mabel Survey.
Cheng, Terence C; Trivedi, Pravin K
2015-09-01
This paper investigates the nature and consequences of sample attrition in a unique longitudinal survey of medical doctors. We describe the patterns of non-response and examine if attrition affects the econometric analysis of medical labour market outcomes using the estimation of physician earnings equations as a case study. We compare the econometric gestimates obtained from a number of different modelling strategies, which are as follows: balanced versus unbalanced samples; an attrition model for panel data based on the classic sample selection model; and a recently developed copula-based selection model. Descriptive evidence shows that doctors who work longer hours, have lower years of experience, are overseas trained and have changed their work location are more likely to drop out. Our analysis suggests that the impact of attrition on inference about the earnings of general practitioners is small. For specialists, there appears to be some evidence for an economically significant bias. Finally, we discuss how the top-up samples in the Medicine in Australia: Balancing Employment and Life survey can be used to address the problem of panel attrition. Copyright © 2015 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Barnett, William A.; Duzhak, Evgeniya Aleksandrovna
2008-06-01
Grandmont [J.M. Grandmont, On endogenous competitive business cycles, Econometrica 53 (1985) 995-1045] found that the parameter space of the most classical dynamic models is stratified into an infinite number of subsets supporting an infinite number of different kinds of dynamics, from monotonic stability at one extreme to chaos at the other extreme, and with many forms of multiperiodic dynamics in between. The econometric implications of Grandmont’s findings are particularly important, if bifurcation boundaries cross the confidence regions surrounding parameter estimates in policy-relevant models. Stratification of a confidence region into bifurcated subsets seriously damages robustness of dynamical inferences. Recently, interest in policy in some circles has moved to New-Keynesian models. As a result, in this paper we explore bifurcation within the class of New-Keynesian models. We develop the econometric theory needed to locate bifurcation boundaries in log-linearized New-Keynesian models with Taylor policy rules or inflation-targeting policy rules. Central results needed in this research are our theorems on the existence and location of Hopf bifurcation boundaries in each of the cases that we consider.
Multi-Year Revenue and Expenditure Forecasting for Small Municipal Governments.
1981-03-01
Management Audit Econometric Revenue Forecast Gap and Impact Analysis Deterministic Expenditure Forecast Municipal Forecasting Municipal Budget Formlto...together with a multi-year revenue and expenditure forecasting model for the City of Monterey, California. The Monterey model includes an econometric ...65 5 D. FORECAST BASED ON THE ECONOMETRIC MODEL ------- 67 E. FORECAST BASED ON EXPERT JUDGMENT AND TREND ANALYSIS
Estimating the Regional Economic Significance of Airports
1992-09-01
following three options for estimating induced impacts: the economic base model , an econometric model , and a regional input-output model . One approach to...limitations, however, the economic base model has been widely used for regional economic analysis. A second approach is to develop an econometric model of...analysis is the principal statistical tool used to estimate the economic relationships. Regional econometric models are capable of estimating a single
Peden, Al; Baker, Judith J
2002-01-01
Using the optimizing properties of econometric analysis, this study analyzes how physician overhead costs (OC) can be allocated to multiple activities to maximize precision in reimbursing the costs of services. Drawing on work by Leibenstein and Friedman, the analysis also shows that allocating OC to multiple activities unbiased by revenue requires controlling for revenue when making the estimates. Further econometric analysis shows that it is possible to save about 10 percent of OC by paying only for those that are necessary.
J Jeuck; F. Cubbage; R. Abt; R. Bardon; J. McCarter; J. Coulston; M. Renkow
2014-01-01
: We conducted a meta-analysis on 64 econometric models from 47 studies predicting forestland conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified from 21 F2A models, 21 F2D models, 12 F2NF models, and...
Appendix : airborne incidents : an econometric analysis of severity
DOT National Transportation Integrated Search
2014-12-19
This is the Appendix for Airborne Incidents: An Econometric Analysis of Severity Report. : Airborne loss of separation incidents occur when an aircraft breaches the defined separation limit (vertical and/or horizontal) with another aircraft or terrai...
State Labor Market Research Study: An Econometric Analysis of the Effects of Labor Subsidies.
ERIC Educational Resources Information Center
MacRae, C. Duncan; And Others
The report describes the construction, application, and theoretical implications of an econometric model depicting the effects of labor subsidies on the supply of workers in the U.S. Three papers deal with the following aspects of constructing the econometric model: (1) examination of equilibrium wages, employment, and earnings of primary and…
What is mLearning and How Can It Be Used to Support Learning and Teaching in Econometrics?
ERIC Educational Resources Information Center
Morales, Lucia
2013-01-01
The aim of case this study was to analyze the integration of mobile learning technologies in a postgraduate course in Finance (MSc in Finance) at Dublin Institute of Technology, where econometrics is an important course component. Previous experience with students undertaking econometrics modules supported this analysis, where the researcher…
Airborne incidents : an econometric analysis of severity, December 31, 2014 : technical summary
DOT National Transportation Integrated Search
2014-12-31
This is a technical summary of the Airborne Incidents: An Econometric Analysis of Severity main report. : Airborne loss of separation incidents occur when an aircraft breaches the defined separation limit (vertical and/or horizontal) with anoth...
The SRI-WEFA Soviet Econometric Model: Phase One Documentation
1975-03-01
established prices. We also have an estimated equation for an end-use residual category which conceptually includes state grain reserves, other undis...forecasting. An important virtue of the econometric discipline is that it requires one first to conceptualize and estimate regularities of behavior...any de- scriptive analysis. Within the framwork of an econometric model, the analyst is able to discriminate among these "special events
ERIC Educational Resources Information Center
Cruz, Luiz M.; Moreira, Marcelo J.
2005-01-01
The authors evaluate Angrist and Krueger (1991) and Bound, Jaeger, and Baker (1995) by constructing reliable confidence regions around the 2SLS and LIML estimators for returns-to-schooling regardless of the quality of the instruments. The results indicate that the returns-to-schooling were between 8 and 25 percent in 1970 and between 4 and 14…
Reflections on Heckman and Pinto’s Causal Analysis After Haavelmo
2013-11-01
Econometric Analysis , Cambridge University Press, 477–490, 1995. Halpern, J. (1998). Axiomatizing causal reasoning. In Uncertainty in Artificial...Models, Structural Models and Econometric Policy Evaluation. Elsevier B.V., Amsterdam, 4779–4874. Heckman, J. J. (1979). Sample selection bias as a...Reflections on Heckman and Pinto’s “Causal Analysis After Haavelmo” Judea Pearl University of California, Los Angeles Computer Science Department Los
ERIC Educational Resources Information Center
Sutton, Farah
2012-01-01
This study examines the spatial distribution of educational attainment and then builds upon current predictive frameworks for understanding patterns of educational attainment by applying a spatial econometric method of analysis. The research from this study enables a new approach to the policy discussion on how to improve educational attainment…
ERIC Educational Resources Information Center
Ibourk, Aomar
2013-01-01
Based on data from international surveys measuring learning (TIMSS), this article focuses on the analysis of the academic performance Moroccan students. The results of the econometric model show that the students' characteristics, their family environment and school context are key determinants of these performances. The study also shows that the…
Econometrics and Psychometrics: A Survey of Communalities
ERIC Educational Resources Information Center
Goldberger, Arthur S.
1971-01-01
Several themes which are common to both econometrics and psychometrics are surveyed. The themes are illustrated by reference to permanent income hypotheses, simultaneous equation models, adaptive expectations and partial adjustment schemes, and by reference to test score theory, factor analysis, and time-series models. (Author)
Application of econometric and ecology analysis methods in physics software
NASA Astrophysics Data System (ADS)
Han, Min Cheol; Hoff, Gabriela; Kim, Chan Hyeong; Kim, Sung Hun; Grazia Pia, Maria; Ronchieri, Elisabetta; Saracco, Paolo
2017-10-01
Some data analysis methods typically used in econometric studies and in ecology have been evaluated and applied in physics software environments. They concern the evolution of observables through objective identification of change points and trends, and measurements of inequality, diversity and evenness across a data set. Within each analysis area, various statistical tests and measures have been examined. This conference paper summarizes a brief overview of some of these methods.
ERIC Educational Resources Information Center
Angrist, Joshua; Pischke, Jorn-Steffen
2010-01-01
This essay reviews progress in empirical economics since Leamer'rs (1983) critique. Leamer highlighted the benefits of sensitivity analysis, a procedure in which researchers show how their results change with changes in specification or functional form. Sensitivity analysis has had a salutary but not a revolutionary effect on econometric practice.…
Kipiński, Lech; König, Reinhard; Sielużycki, Cezary; Kordecki, Wojciech
2011-10-01
Stationarity is a crucial yet rarely questioned assumption in the analysis of time series of magneto- (MEG) or electroencephalography (EEG). One key drawback of the commonly used tests for stationarity of encephalographic time series is the fact that conclusions on stationarity are only indirectly inferred either from the Gaussianity (e.g. the Shapiro-Wilk test or Kolmogorov-Smirnov test) or the randomness of the time series and the absence of trend using very simple time-series models (e.g. the sign and trend tests by Bendat and Piersol). We present a novel approach to the analysis of the stationarity of MEG and EEG time series by applying modern statistical methods which were specifically developed in econometrics to verify the hypothesis that a time series is stationary. We report our findings of the application of three different tests of stationarity--the Kwiatkowski-Phillips-Schmidt-Schin (KPSS) test for trend or mean stationarity, the Phillips-Perron (PP) test for the presence of a unit root and the White test for homoscedasticity--on an illustrative set of MEG data. For five stimulation sessions, we found already for short epochs of duration of 250 and 500 ms that, although the majority of the studied epochs of single MEG trials were usually mean-stationary (KPSS test and PP test), they were classified as nonstationary due to their heteroscedasticity (White test). We also observed that the presence of external auditory stimulation did not significantly affect the findings regarding the stationarity of the data. We conclude that the combination of these tests allows a refined analysis of the stationarity of MEG and EEG time series.
Time Series Econometrics for the 21st Century
ERIC Educational Resources Information Center
Hansen, Bruce E.
2017-01-01
The field of econometrics largely started with time series analysis because many early datasets were time-series macroeconomic data. As the field developed, more cross-sectional and longitudinal datasets were collected, which today dominate the majority of academic empirical research. In nonacademic (private sector, central bank, and governmental)…
ERIC Educational Resources Information Center
González Canché, Manuel S.
2018-01-01
This study measures the extent to which student outmigration outside the 4-year sector takes place and posits that the benefits from attracting non-resident students exist regardless of sector of enrollment. The study also provides empirical evidence about the relevance of employing geographical network analysis (GNA) and spatial econometrics in…
Time Series Modeling of Army Mission Command Communication Networks: An Event-Driven Analysis
2013-06-01
Lehmann, D. R. (1984). How advertising affects sales: Meta- analysis of econometric results. Journal of Marketing Research , 21, 65-74. Barabási, A. L...317-357. Leone, R. P. (1983). Modeling sales-advertising relationships: An integrated time series- econometric approach. Journal of Marketing ... Research , 20, 291-295. McGrath, J. E., & Kravitz, D. A. (1982). Group research. Annual Review of Psychology, 33, 195- 230. Monge, P. R., & Contractor
Managing heteroscedasticity in general linear models.
Rosopa, Patrick J; Schaffer, Meline M; Schroeder, Amber N
2013-09-01
Heteroscedasticity refers to a phenomenon where data violate a statistical assumption. This assumption is known as homoscedasticity. When the homoscedasticity assumption is violated, this can lead to increased Type I error rates or decreased statistical power. Because this can adversely affect substantive conclusions, the failure to detect and manage heteroscedasticity could have serious implications for theory, research, and practice. In addition, heteroscedasticity is not uncommon in the behavioral and social sciences. Thus, in the current article, we synthesize extant literature in applied psychology, econometrics, quantitative psychology, and statistics, and we offer recommendations for researchers and practitioners regarding available procedures for detecting heteroscedasticity and mitigating its effects. In addition to discussing the strengths and weaknesses of various procedures and comparing them in terms of existing simulation results, we describe a 3-step data-analytic process for detecting and managing heteroscedasticity: (a) fitting a model based on theory and saving residuals, (b) the analysis of residuals, and (c) statistical inferences (e.g., hypothesis tests and confidence intervals) involving parameter estimates. We also demonstrate this data-analytic process using an illustrative example. Overall, detecting violations of the homoscedasticity assumption and mitigating its biasing effects can strengthen the validity of inferences from behavioral and social science data.
Econometric Estimation of the Economic Impact of a University. AIR 1993 Annual Forum Paper.
ERIC Educational Resources Information Center
Gana, Rajaram
This study conducted an econometric analysis of the impact of the University of Delaware (UD), a public, doctoral level institution, on the Delaware economy, particularly the impact of nonresident students. To construct a model the study used historical institutional data from the Office of Institutional Research and Planning at UD and…
Hoch, Jeffrey S; Briggs, Andrew H; Willan, Andrew R
2002-07-01
Economic evaluation is often seen as a branch of health economics divorced from mainstream econometric techniques. Instead, it is perceived as relying on statistical methods for clinical trials. Furthermore, the statistic of interest in cost-effectiveness analysis, the incremental cost-effectiveness ratio is not amenable to regression-based methods, hence the traditional reliance on comparing aggregate measures across the arms of a clinical trial. In this paper, we explore the potential for health economists undertaking cost-effectiveness analysis to exploit the plethora of established econometric techniques through the use of the net-benefit framework - a recently suggested reformulation of the cost-effectiveness problem that avoids the reliance on cost-effectiveness ratios and their associated statistical problems. This allows the formulation of the cost-effectiveness problem within a standard regression type framework. We provide an example with empirical data to illustrate how a regression type framework can enhance the net-benefit method. We go on to suggest that practical advantages of the net-benefit regression approach include being able to use established econometric techniques, adjust for imperfect randomisation, and identify important subgroups in order to estimate the marginal cost-effectiveness of an intervention. Copyright 2002 John Wiley & Sons, Ltd.
The log-periodic-AR(1)-GARCH(1,1) model for financial crashes
NASA Astrophysics Data System (ADS)
Gazola, L.; Fernandes, C.; Pizzinga, A.; Riera, R.
2008-02-01
This paper intends to meet recent claims for the attainment of more rigorous statistical methodology within the econophysics literature. To this end, we consider an econometric approach to investigate the outcomes of the log-periodic model of price movements, which has been largely used to forecast financial crashes. In order to accomplish reliable statistical inference for unknown parameters, we incorporate an autoregressive dynamic and a conditional heteroskedasticity structure in the error term of the original model, yielding the log-periodic-AR(1)-GARCH(1,1) model. Both the original and the extended models are fitted to financial indices of U. S. market, namely S&P500 and NASDAQ. Our analysis reveal two main points: (i) the log-periodic-AR(1)-GARCH(1,1) model has residuals with better statistical properties and (ii) the estimation of the parameter concerning the time of the financial crash has been improved.
Simulating Quantile Models with Applications to Economics and Management
NASA Astrophysics Data System (ADS)
Machado, José A. F.
2010-05-01
The massive increase in the speed of computers over the past forty years changed the way that social scientists, applied economists and statisticians approach their trades and also the very nature of the problems that they could feasibly tackle. The new methods that use intensively computer power go by the names of "computer-intensive" or "simulation". My lecture will start with bird's eye view of the uses of simulation in Economics and Statistics. Then I will turn out to my own research on uses of computer- intensive methods. From a methodological point of view the question I address is how to infer marginal distributions having estimated a conditional quantile process, (Counterfactual Decomposition of Changes in Wage Distributions using Quantile Regression," Journal of Applied Econometrics 20, 2005). Illustrations will be provided of the use of the method to perform counterfactual analysis in several different areas of knowledge.
Econometric analysis of the factors influencing forest acreage trends in the southeast.
Ralph J. Alig
1986-01-01
Econometric models of changes in land use acreages in the Southeast by physiographic region have been developed by pooling cross-section and time series data. Separate acreage equations have been estimated for the three major private forestland owner classes and the three major classes of nonforest land use. Observations were drawn at three or four different points in...
Synthesizing Econometric Evidence: The Case of Demand Elasticity Estimates.
DeCicca, Philip; Kenkel, Don
2015-06-01
Econometric estimates of the responsiveness of health-related consumer demand to higher prices are often key ingredients for risk policy analysis. We review the potential advantages and challenges of synthesizing econometric evidence on the price-responsiveness of consumer demand. We draw on examples of research on consumer demand for health-related goods, especially cigarettes. We argue that the overarching goal of research synthesis in this context is to provide policy-relevant evidence for broad-brush conclusions. We propose three main criteria to select among research synthesis methods. We discuss how in principle and in current practice synthesis of research on the price-elasticity of smoking meets our proposed criteria. Our analysis of current practice also contributes to academic research on the specific policy question of the effectiveness of higher cigarette prices to reduce smoking. Although we point out challenges and limitations, we believe more work on research synthesis in this area will be productive and important. © 2015 Society for Risk Analysis.
Factors influencing crime rates: an econometric analysis approach
NASA Astrophysics Data System (ADS)
Bothos, John M. A.; Thomopoulos, Stelios C. A.
2016-05-01
The scope of the present study is to research the dynamics that determine the commission of crimes in the US society. Our study is part of a model we are developing to understand urban crime dynamics and to enhance citizens' "perception of security" in large urban environments. The main targets of our research are to highlight dependence of crime rates on certain social and economic factors and basic elements of state anticrime policies. In conducting our research, we use as guides previous relevant studies on crime dependence, that have been performed with similar quantitative analyses in mind, regarding the dependence of crime on certain social and economic factors using statistics and econometric modelling. Our first approach consists of conceptual state space dynamic cross-sectional econometric models that incorporate a feedback loop that describes crime as a feedback process. In order to define dynamically the model variables, we use statistical analysis on crime records and on records about social and economic conditions and policing characteristics (like police force and policing results - crime arrests), to determine their influence as independent variables on crime, as the dependent variable of our model. The econometric models we apply in this first approach are an exponential log linear model and a logit model. In a second approach, we try to study the evolvement of violent crime through time in the US, independently as an autonomous social phenomenon, using autoregressive and moving average time-series econometric models. Our findings show that there are certain social and economic characteristics that affect the formation of crime rates in the US, either positively or negatively. Furthermore, the results of our time-series econometric modelling show that violent crime, viewed solely and independently as a social phenomenon, correlates with previous years crime rates and depends on the social and economic environment's conditions during previous years.
Using directed information for influence discovery in interconnected dynamical systems
NASA Astrophysics Data System (ADS)
Rao, Arvind; Hero, Alfred O.; States, David J.; Engel, James Douglas
2008-08-01
Structure discovery in non-linear dynamical systems is an important and challenging problem that arises in various applications such as computational neuroscience, econometrics, and biological network discovery. Each of these systems have multiple interacting variables and the key problem is the inference of the underlying structure of the systems (which variables are connected to which others) based on the output observations (such as multiple time trajectories of the variables). Since such applications demand the inference of directed relationships among variables in these non-linear systems, current methods that have a linear assumption on structure or yield undirected variable dependencies are insufficient. Hence, in this work, we present a methodology for structure discovery using an information-theoretic metric called directed time information (DTI). Using both synthetic dynamical systems as well as true biological datasets (kidney development and T-cell data), we demonstrate the utility of DTI in such problems.
The Model Analyst’s Toolkit: Scientific Model Development, Analysis, and Validation
2015-02-20
being integrated within MAT, including Granger causality. Granger causality tests whether a data series helps when predicting future values of another...relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 424-438. Granger, C. W. (1980). Testing ... testing dataset. This effort is described in Section 3.2. 3.1. Improvements in Granger Causality User Interface Various metrics of causality are
David J. Lewis; Ralph J. Alig
2014-01-01
This paper develops a plot-level spatial econometric land-use model and estimates it with U.S. Geological Survey Land Cover Trends (LCT) geographic information system panel data for the western halves of the states of Oregon and Washington. The discrete-choice framework we use models plot-scale choices of the three dominant land uses in this region: forest, agriculture...
Crime Pattern Analysis: A Spatial Frequent Pattern Mining Approach
2012-05-10
econometrics. A companion to theoretical econometrics, pages 310-330, 1988. [5] L. Anselin, J. Cohen, D. Cook, W. Gorr, and G. Tita . Spatial analyses...52] G. Mohler, M. Short, P. Brantingham, F. Schoenberg, and G. Tita . Self-exciting point process modeling of crime. Journal of the American...Systems, 9:462, 2010. [69] M. Short, P. Brantingham, A. Bertozzi, and G. Tita . Dissipation and displacement of hotspots in reaction-diffusion models
Econometrics of exhaustible resource supply: a theory and an application. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Epple, D.; Hansen, L.P.
1981-12-01
An econometric model of US oil and natural gas discoveries is developed in this study. The econometric model is explicitly derived as the solution to the problem of maximizing the expected discounted after tax present value of revenues net of exploration, development, and production costs. The model contains equations representing producers' formation of price expectations and separate equations giving producers' optimal exploration decisions contingent on expected prices. A procedure is developed for imposing resource base constraints (e.g., ultimate recovery estimates based on geological analysis) when estimating the econometric model. The model is estimated using aggregate post-war data for the Unitedmore » States. Production from a given addition to proved reserves is assumed to follow a negative exponential path, and additions of proved reserves from a given discovery are assumed to follow a negative exponential path. Annual discoveries of oil and natural gas are estimated as latent variables. These latent variables are the endogenous variables in the econometric model of oil and natural gas discoveries. The model is estimated without resource base constraints. The model is also estimated imposing the mean oil and natural gas ultimate recovery estimates of the US Geological Survey. Simulations through the year 2020 are reported for various future price regimes.« less
Spatial Analysis of China Province-level Perinatal Mortality
XIANG, Kun; SONG, Deyong
2016-01-01
Background: Using spatial analysis tools to determine the spatial patterns of China province-level perinatal mortality and using spatial econometric model to examine the impacts of health care resources and different socio-economic factors on perinatal mortality. Methods: The Global Moran’s I index is used to examine whether the spatial autocorrelation exists in selected regions and Moran’s I scatter plot to examine the spatial clustering among regions. Spatial econometric models are used to investigate the spatial relationships between perinatal mortality and contributing factors. Results: The overall Moran’s I index indicates that perinatal mortality displays positive spatial autocorrelation. Moran’s I scatter plot analysis implies that there is a significant clustering of mortality in both high-rate regions and low-rate regions. The spatial econometric models analyses confirm the existence of a direct link between perinatal mortality and health care resources, socio-economic factors. Conclusions: Since a positive spatial autocorrelation has been detected in China province-level perinatal mortality, the upgrading of regional economic development and medical service level will affect the mortality not only in region itself but also its adjacent regions. PMID:27398334
A Theory of Bayesian Data Analysis
1989-10-10
and the sim- plification of models," in Evaluation of Econometric Models, J. Kmenta and J. 20 Ramsey , eds., Academic Press, 245-268. Edwards, W...Evaluation of Econometric Models, ed. by J. Kmenta and J. Ramsey , Academic Press, 197-217. Hill, Bruce M., (1980c), Review of Specification Searches, by E...also Hill (1970a, 1975a) for earlier thoughts the subject with regard to tests of significance, and Smith.(1986). The Baesi theory of tests of
NASA Astrophysics Data System (ADS)
Tsutsumi, Morito; Seya, Hajime
2009-12-01
This study discusses the theoretical foundation of the application of spatial hedonic approaches—the hedonic approach employing spatial econometrics or/and spatial statistics—to benefits evaluation. The study highlights the limitations of the spatial econometrics approach since it uses a spatial weight matrix that is not employed by the spatial statistics approach. Further, the study presents empirical analyses by applying the Spatial Autoregressive Error Model (SAEM), which is based on the spatial econometrics approach, and the Spatial Process Model (SPM), which is based on the spatial statistics approach. SPMs are conducted based on both isotropy and anisotropy and applied to different mesh sizes. The empirical analysis reveals that the estimated benefits are quite different, especially between isotropic and anisotropic SPM and between isotropic SPM and SAEM; the estimated benefits are similar for SAEM and anisotropic SPM. The study demonstrates that the mesh size does not affect the estimated amount of benefits. Finally, the study provides a confidence interval for the estimated benefits and raises an issue with regard to benefit evaluation.
Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables
NASA Astrophysics Data System (ADS)
Barnett, Lionel; Barrett, Adam B.; Seth, Anil K.
2009-12-01
Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. Developed originally in the field of econometrics, it has since found application in a broader arena, particularly in neuroscience. More recently transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes, has gained traction in a similarly wide field. While it has been recognized that the two concepts must be related, the exact relationship has until now not been formally described. Here we show that for Gaussian variables, Granger causality and transfer entropy are entirely equivalent, thus bridging autoregressive and information-theoretic approaches to data-driven causal inference.
Castiel, D; Herve, C
1992-01-01
In general, a large number of patients is needed to conclude whether the results of a therapeutic strategy are significant or not. One can lower this number with a logit. The method has been proposed in an article published recently (Cost-utility analysis of early thrombolytic therapy, Pharmaco Economics, 1992). The present article is an essay aimed at validating the method, both from the econometric and ethical points of view.
A comparative analysis of errors in long-term econometric forecasts
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tepel, R.
1986-04-01
The growing body of literature that documents forecast accuracy falls generally into two parts. The first is prescriptive and is carried out by modelers who use simulation analysis as a tool for model improvement. These studies are ex post, that is, they make use of known values for exogenous variables and generate an error measure wholly attributable to the model. The second type of analysis is descriptive and seeks to measure errors, identify patterns among errors and variables and compare forecasts from different sources. Most descriptive studies use an ex ante approach, that is, they evaluate model outputs based onmore » estimated (or forecasted) exogenous variables. In this case, it is the forecasting process, rather than the model, that is under scrutiny. This paper uses an ex ante approach to measure errors in forecast series prepared by Data Resources Incorporated (DRI), Wharton Econometric Forecasting Associates (Wharton), and Chase Econometrics (Chase) and to determine if systematic patterns of errors can be discerned between services, types of variables (by degree of aggregation), length of forecast and time at which the forecast is made. Errors are measured as the percent difference between actual and forecasted values for the historical period of 1971 to 1983.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Friesen, G.
Chase Econometrics summarizes the assumptions underlying long-term US energy forecasts. To illustrate the uncertainty involved in forecasting for the period to the year 2000, they compare Chase Econometrics forecasts with some recent projections prepared by the DOE Office of Policy, Planning and Analysis for the annual National Energy Policy Plan supplement. Scenario B, the mid-range reference case, is emphasized. The purpose of providing Scenario B as well as Scenarios A and C as alternate cases is to show the sensitivity of oil price projections to small swings in energy demand. 4 tables.
India's pulp and paper industry: Productivity and energy efficiency
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schumacher, Katja
1999-07-01
Historical estimates of productivity growth in India's pulp and paper sector vary from indicating an improvement to a decline in the sector's productivity. The variance may be traced to the time period of study, source of data for analysis, and type of indices and econometric specifications used for reporting productivity growth. The authors derive both statistical and econometric estimates of productivity growth for this sector. Their results show that productivity declined over the observed period from 1973-74 to 1993-94 by 1.1% p.a. Using a translog specification the econometric analysis reveals that technical progress in India's pulp and paper sector hasmore » been biased towards the use of energy and material, while it has been capital and labor saving. The decline in productivity was caused largely by the protection afforded by high tariffs on imported paper products and other policies, which allowed inefficient, small plants to enter the market and flourish. Will these trends continue into the future, particularly where energy use is concerned? The authors examine the current changes in structure and energy efficiency undergoing in the sector. Their analysis shows that with liberalization of the sector, and tighter environmental controls, the industry is moving towards higher efficiency and productivity. However, the analysis also shows that because these improvements are being hampered by significant financial and other barriers the industry might have a long way to go.« less
An Applied Physicist Does Econometrics
NASA Astrophysics Data System (ADS)
Taff, L. G.
2010-02-01
The biggest problem those attempting to understand econometric data, via modeling, have is that economics has no F = ma. Without a theoretical underpinning, econometricians have no way to build a good model to fit observations to. Physicists do, and when F = ma failed, we knew it. Still desiring to comprehend econometric data, applied economists turn to mis-applying probability theory---especially with regard to the assumptions concerning random errors---and choosing extremely simplistic analytical formulations of inter-relationships. This introduces model bias to an unknown degree. An applied physicist, used to having to match observations to a numerical or analytical model with a firm theoretical basis, modify the model, re-perform the analysis, and then know why, and when, to delete ``outliers'', is at a considerable advantage when quantitatively analyzing econometric data. I treat two cases. One is to determine the household density distribution of total assets, annual income, age, level of education, race, and marital status. Each of these ``independent'' variables is highly correlated with every other but only current annual income and level of education follow a linear relationship. The other is to discover the functional dependence of total assets on the distribution of assets: total assets has an amazingly tight power law dependence on a quadratic function of portfolio composition. Who knew? )
NASA Astrophysics Data System (ADS)
Gwozdz-Lason, Monika
2017-12-01
This paper attempts to answer some of the following questions: what is the main selling advantage of a plot of land on the areas with mining exploitation? which attributes influence on market value the most? and how calculate the mining influence in subsoil under future new building as market value of plot with commercial use? This focus is not accidental, as the paper sets out to prove that the subsoil load bearing capacity, as directly inferred from the local geotechnical properties with mining exploitation, considerably influences the market value of this type of real estate. Presented in this elaborate analysis and calculations, are part of the ongoing development works which aimed at suggesting a new technology and procedures for estimating the value of the land belonging to the third category geotechnical. Analysed the question was examined both in terms of the theoretical and empirical. On the basis of the analysed code calculations in residual method, numerical, statistical and econometric defined results and final conclusions. A market analysis yielded a group of subsoil stabilization costs which depend on the mining operations interaction, subsoil parameters, type of the contemplated structure, its foundations, selected stabilization method, its overall area and shape.
Bootstrapping Student Understanding of What Is Going on in Econometrics.
ERIC Educational Resources Information Center
Kennedy, Peter E.
2001-01-01
Explains that econometrics is an intellectual game played by rules based on the sampling distribution concept. Contains explanations for why many students are uncomfortable with econometrics. Encourages instructors to use explain-how-to-bootstrap exercises to promote student understanding. (RLH)
Crystal study and econometric model
NASA Technical Reports Server (NTRS)
1975-01-01
An econometric model was developed that can be used to predict demand and supply figures for crystals over a time horizon roughly concurrent with that of NASA's Space Shuttle Program - that is, 1975 through 1990. The model includes an equation to predict the impact on investment in the crystal-growing industry. Actually, two models are presented. The first is a theoretical model which follows rather strictly the standard theoretical economic concepts involved in supply and demand analysis, and a modified version of the model was developed which, though not quite as theoretically sound, was testable utilizing existing data sources.
Parameterized examination in econometrics
NASA Astrophysics Data System (ADS)
Malinova, Anna; Kyurkchiev, Vesselin; Spasov, Georgi
2018-01-01
The paper presents a parameterization of basic types of exam questions in Econometrics. This algorithm is used to automate and facilitate the process of examination, assessment and self-preparation of a large number of students. The proposed parameterization of testing questions reduces the time required to author tests and course assignments. It enables tutors to generate a large number of different but equivalent dynamic questions (with dynamic answers) on a certain topic, which are automatically assessed. The presented methods are implemented in DisPeL (Distributed Platform for e-Learning) and provide questions in the areas of filtering and smoothing of time-series data, forecasting, building and analysis of single-equation econometric models. Questions also cover elasticity, average and marginal characteristics, product and cost functions, measurement of monopoly power, supply, demand and equilibrium price, consumer and product surplus, etc. Several approaches are used to enable the required numerical computations in DisPeL - integration of third-party mathematical libraries, developing our own procedures from scratch, and wrapping our legacy math codes in order to modernize and reuse them.
ENVIRONMENTAL ECONOMICS FOR WATERSHED RESTORATION
This book overviews non-market valuation, input-output analysis, cost-benefit analysis, and presents case studies from the Mid Atlantic Highland region, with all but the bare minimum econometrics, statistics, and math excluded or relegated to an appendix. It is a non-market valu...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-11-08
... analysis, survey methodology, geospatial analysis, econometrics, cognitive psychology, and computer science... following disciplines: demography, economics, geography, psychology, statistics, survey methodology, social... expertise in such areas as demography, economics, geography, psychology, statistics, survey methodology...
77 FR 1454 - Request for Nominations of Members To Serve on the Census Scientific Advisory Committee
Federal Register 2010, 2011, 2012, 2013, 2014
2012-01-10
..., statistical analysis, survey methodology, geospatial analysis, econometrics, cognitive psychology, and... following disciplines: Demography, economics, geography, psychology, statistics, survey methodology, social... technical expertise in such areas as demography, economics, geography, psychology, statistics, survey...
Intrafirm planning and mathematical modeling of owner's equity in industrial enterprises
NASA Astrophysics Data System (ADS)
Ponomareva, S. V.; Zheleznova, I. V.
2018-05-01
The article aims to review the different approaches to intrafirm planning of owner's equity in industrial enterprises. Since charter capital, additional capital and reserve capital do not change in the process of enterprise activity, the main interest lies on the field of share repurchases from shareholders and retained earnings within the owner's equity of the enterprise. In order to study the effect of share repurchases on the activities of the enterprise, let us use such mathematical methods as event study and econometric modeling. This article describes the step-by-step algorithm of carrying out event study and justifies the choice of Logit model in econometric analysis. The article represents basic results of conducted regression analysis on the effect of share repurchases on the key financial indicators in industrial enterprises.
. Areas of Expertise Economic impact studies Time series analysis Analysis of labor and demographic data Research Interests Static and dynamic economic impact models Labor data estimation Econometric modeling and 2030: A Strategic Roadmap for American Energy Innovation, Economic Growth, and Competitiveness."
Williams, James W; Cook, Nikolai M
2016-10-01
One of the lasting legacies of the financial crisis of 2008, and the legislative energies that followed from it, is the growing reliance on econometrics as part of the rulemaking process. Financial regulators are increasingly expected to rationalize proposed rules using available econometric techniques, and the courts have vacated several key rules emanating from Dodd-Frank on the grounds of alleged deficiencies in this evidentiary effort. The turn toward such econometric tools is seen as a significant constraint on and challenge to regulators as they endeavor to engage with such essential policy questions as the impact of financial speculation on food security. Yet, outside of the specialized practitioner community, very little is known about these techniques. This article examines one such econometric test, Granger causality, and its role in a pivotal Dodd-Frank rulemaking. Through an examination of the test for Granger causality and its attempts to distill the causal connections between financial speculation and commodities prices, the article argues that econometrics is a blunt but useful tool, limited in its ability to provide decisive insights into commodities markets and yet yielding useful returns for those who are able to wield it.
Interrelation of GDP and pension capital: Mathematical and econometrical analysis
NASA Astrophysics Data System (ADS)
Nepp, A. N.; Dolgodvorov, A. D.
2016-12-01
This article is a mathematicalanalysis of the relationship between GDP and the development of funded pension systems. For this purpose, a mathematical formula was derived from the macro-economic GDP, proportional to the level of income and consumption for the dependence of GDP on the level of pension payments, the value of pension savings and the structure of compulsory contributions to the pension fund allocated to the distribution and accumulative pension system. A derivation of the equation proves the linear relationship of GDP and the share of pension contributions channeled to the funded pension system. Thus, the macroeconomic indicator with the larger negative impact on GDP was proven to be the elimination of the compulsory funded pension system. Based on the econometric analysis, the positive effect of the distributive pension system was proven on macroeconomic parameters.
Airfreight forecasting methodology and results
NASA Technical Reports Server (NTRS)
1978-01-01
A series of econometric behavioral equations was developed to explain and forecast the evolution of airfreight traffic demand for the total U.S. domestic airfreight system, the total U.S. international airfreight system, and the total scheduled international cargo traffic carried by the top 44 foreign airlines. The basic explanatory variables used in these macromodels were the real gross national products of the countries involved and a measure of relative transportation costs. The results of the econometric analysis reveal that the models explain more than 99 percent of the historical evolution of freight traffic. The long term traffic forecasts generated with these models are based on scenarios of the likely economic outlook in the United States and 31 major foreign countries.
Irrigation water demand: A meta-analysis of price elasticities
NASA Astrophysics Data System (ADS)
Scheierling, Susanne M.; Loomis, John B.; Young, Robert A.
2006-01-01
Metaregression models are estimated to investigate sources of variation in empirical estimates of the price elasticity of irrigation water demand. Elasticity estimates are drawn from 24 studies reported in the United States since 1963, including mathematical programming, field experiments, and econometric studies. The mean price elasticity is 0.48. Long-run elasticities, those that are most useful for policy purposes, are likely larger than the mean estimate. Empirical results suggest that estimates may be more elastic if they are derived from mathematical programming or econometric studies and calculated at a higher irrigation water price. Less elastic estimates are found to be derived from models based on field experiments and in the presence of high-valued crops.
Bildirici, Melike; Ersin, Özgür Ömer
2018-01-01
The study aims to combine the autoregressive distributed lag (ARDL) cointegration framework with smooth transition autoregressive (STAR)-type nonlinear econometric models for causal inference. Further, the proposed STAR distributed lag (STARDL) models offer new insights in terms of modeling nonlinearity in the long- and short-run relations between analyzed variables. The STARDL method allows modeling and testing nonlinearity in the short-run and long-run parameters or both in the short- and long-run relations. To this aim, the relation between CO 2 emissions and economic growth rates in the USA is investigated for the 1800-2014 period, which is one of the largest data sets available. The proposed hybrid models are the logistic, exponential, and second-order logistic smooth transition autoregressive distributed lag (LSTARDL, ESTARDL, and LSTAR2DL) models combine the STAR framework with nonlinear ARDL-type cointegration to augment the linear ARDL approach with smooth transitional nonlinearity. The proposed models provide a new approach to the relevant econometrics and environmental economics literature. Our results indicated the presence of asymmetric long-run and short-run relations between the analyzed variables that are from the GDP towards CO 2 emissions. By the use of newly proposed STARDL models, the results are in favor of important differences in terms of the response of CO 2 emissions in regimes 1 and 2 for the estimated LSTAR2DL and LSTARDL models.
Effectiveness of conservation easements in agricultural regions.
Braza, Mark
2017-08-01
Conservation easements are a standard technique for preventing habitat loss, particularly in agricultural regions with extensive cropland cultivation, yet little is known about their effectiveness. I developed a spatial econometric approach to propensity-score matching and used the approach to estimate the amount of habitat loss prevented by a grassland conservation easement program of the U.S. federal government. I used a spatial autoregressive probit model to predict tract enrollment in the easement program as of 2001 based on tract agricultural suitability, habitat quality, and spatial interactions among neighboring tracts. Using the predicted values from the model, I matched enrolled tracts with similar unenrolled tracts to form a treatment group and a control group. To measure the program's impact on subsequent grassland loss, I estimated cropland cultivation rates for both groups in 2014 with a second spatial probit model. Between 2001 and 2014, approximately 14.9% of control tracts were cultivated and 0.3% of treated tracts were cultivated. Therefore, approximately 14.6% of the protected land would have been cultivated in the absence of the program. My results demonstrate that conservation easements can significantly reduce habitat loss in agricultural regions; however, the enrollment of tracts with low cropland suitability may constrain the amount of habitat loss they prevent. My results also show that spatial econometric models can improve the validity of control groups and thereby strengthen causal inferences about program effectiveness in situations when spatial interactions influence conservation decisions. © 2017 Society for Conservation Biology.
Interpreting Bivariate Regression Coefficients: Going beyond the Average
ERIC Educational Resources Information Center
Halcoussis, Dennis; Phillips, G. Michael
2010-01-01
Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…
1981-01-01
explanatory variable has been ommitted. Ramsey (1974) has developed a rather interesting test for detecting specification errors using estimates of the...Peter. (1979) A Guide to Econometrics , Cambridge, MA: The MIT Press. Ramsey , J.B. (1974), "Classical Model Selection Through Specification Error... Tests ," in P. Zarembka, Ed. Frontiers in Econometrics , New York: Academia Press. Theil, Henri. (1971), Principles of Econometrics , New York: John Wiley
NASA Technical Reports Server (NTRS)
Seidel, A. D.
1974-01-01
The economic value of information produced by an assumed operational version of an earth resources survey satellite of the ERTS class is assessed. The theoretical capability of an ERTS system to provide improved agricultural forecasts is analyzed and this analysis is used as a reasonable input to the econometric methods derived by ECON. An econometric investigation into the markets for agricultural commodities is summarized. An overview of the effort including the objectives, scopes, and architecture of the analysis, and the estimation strategy employed is presented. The results and conclusions focus on the economic importance of improved crop forecasts, U.S. exports, and government policy operations. Several promising avenues of further investigation are suggested.
Panel data analysis of cardiotocograph (CTG) data.
Horio, Hiroyuki; Kikuchi, Hitomi; Ikeda, Tomoaki
2013-01-01
Panel data analysis is a statistical method, widely used in econometrics, which deals with two-dimensional panel data collected over time and over individuals. Cardiotocograph (CTG) which monitors fetal heart rate (FHR) using Doppler ultrasound and uterine contraction by strain gage is commonly used in intrapartum treatment of pregnant women. Although the relationship between FHR waveform pattern and the outcome such as umbilical blood gas data at delivery has long been analyzed, there exists no accumulated FHR patterns from large number of cases. As time-series economic fluctuations in econometrics such as consumption trend has been studied using panel data which consists of time-series and cross-sectional data, we tried to apply this method to CTG data. The panel data composed of a symbolized segment of FHR pattern can be easily handled, and a perinatologist can get the whole FHR pattern view from the microscopic level of time-series FHR data.
DOT National Transportation Integrated Search
1979-12-01
An econometric model is developed which provides long-run policy analysis and forecasting of annual trends, for U.S. auto stock, new sales, and their composition by auto size-class. The concept of "desired" (equilibrium) stock is introduced. "Desired...
A joint econometric analysis of seat belt use and crash-related injury severity.
Eluru, Naveen; Bhat, Chandra R
2007-09-01
This paper formulates a comprehensive econometric structure that recognizes two important issues in crash-related injury severity analysis. First, the impact of a factor on injury severity may be moderated by various observed and unobserved variables specific to an individual or to a crash. Second, seat belt use is likely to be endogenous to injury severity. That is, it is possible that intrinsically unsafe drivers do not wear seat belts and are the ones likely to be involved in high injury severity crashes because of their unsafe driving habits. The preceding issues are considered in the current research effort through the development of a comprehensive model of seat belt use and injury severity that takes the form of a joint correlated random coefficients binary-ordered response system. To our knowledge, this is the first instance of such a model formulation and application not only in the safety analysis literature, but in the econometrics literature in general. The empirical analysis is based on the 2003 General Estimates System (GES) data base. Several types of variables are considered to explain seat belt use and injury severity levels, including driver characteristics, vehicle characteristics, roadway design attributes, environmental factors, and crash characteristics. The results, in addition to confirming the effects of various explanatory variables, also highlight the importance of (a) considering the moderating effects of unobserved individual/crash-related factors on the determinants of injury severity and (b) seat belt use endogeneity. From a policy standpoint, the results suggest that seat belt non-users, when apprehended in the act, should perhaps be subjected to both a fine (to increase the chances that they wear seat belts) as well as mandatory enrollment in a defensive driving course (to attempt to change their aggressive driving behaviors).
The need for econometric research in laboratory animal operations.
Baker, David G; Kearney, Michael T
2015-06-01
The scarcity of research funding can affect animal facilities in various ways. These effects can be evaluated by examining the allocation of financial resources in animal facilities, which can be facilitated by the use of mathematical and statistical methods to analyze economic problems, a discipline known as econometrics. The authors applied econometrics to study whether increasing per diem charges had a negative effect on the number of days of animal care purchased by animal users. They surveyed animal numbers and per diem charges at 20 research institutions and found that demand for large animals decreased as per diem charges increased. The authors discuss some of the challenges involved in their study and encourage research institutions to carry out more robust econometric studies of this and other economic questions facing laboratory animal research.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Abercrombie, Robert K; Sheldon, Frederick T; Grimaila, Michael R
2010-01-01
In earlier works, we presented a computational infrastructure that allows an analyst to estimate the security of a system in terms of the loss that each stakeholder stands to sustain as a result of security breakdowns. In this paper, we discuss how this infrastructure can be used in the subject domain of mission assurance as defined as the full life-cycle engineering process to identify and mitigate design, production, test, and field support deficiencies of mission success. We address the opportunity to apply the Cyberspace Security Econometrics System (CSES) to Carnegie Mellon University and Software Engineering Institute s Mission Assurance Analysismore » Protocol (MAAP) in this context.« less
Identifying economics' place amongst academic disciplines: a science or a social science?
Hudson, John
2017-01-01
Different academic disciplines exhibit different styles, including styles in journal titles. Using data from the 2014 Research Excellence Framework (REF) in the UK we are able to identify the stylistic trends of different disciplines using 155,552 journal titles across all disciplines. Cluster analysis is then used to group the different disciplines together. The resulting identification fits the social sciences, the sciences and the arts and humanities reasonably well. Economics overall, fits best with philosophy, but the linkage is weak. When we divided economics into papers published in theory, econometrics and the remaining journals, the first two link with mathematics and computer science, particularly econometrics, and thence the sciences. The rest of economics then links with business and thence the social sciences.
Teaching Students with Visual Impairments in an Inclusive Educational Setting: A Case from Nepal
ERIC Educational Resources Information Center
Lamichhane, Kamal
2017-01-01
Using the data set from teachers and students and utilising both qualitative and quantitative techniques for analysis, I discuss teaching style considerations in Nepal's mainstream schools for students with visual impairments. Results of the econometric analysis show that teachers' years of schooling, teaching experience, and using blackboard were…
DOT National Transportation Integrated Search
1979-12-01
An econometric model is developed which provides long-run policy analysis and forecasting of annual trends, for U.S. auto stock, new sales, and their composition by auto size-class. The concept of "desired" (equilibrium) stock is introduced. "Desired...
Pedagogy and the PC: Trends in the AIS Curriculum
ERIC Educational Resources Information Center
Badua, Frank
2008-01-01
The author investigated the array of course topics in accounting information systems (AIS), as course syllabi embody. The author (a) used exploratory data analysis to determine the topics that AIS courses most frequently offered and (b) used descriptive statistics and econometric analysis to trace the diversity of course topics through time,…
Price of gasoline: forecasting comparisons. [Box-Jenkins, econometric, and regression methods
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bopp, A.E.; Neri, J.A.
Gasoline prices are simulated using three popular forecasting methodologies: A Box--Jenkins type method, an econometric method, and a regression method. One-period-ahead and 18-period-ahead comparisons are made. For the one-period-ahead method, a Box--Jenkins type time-series model simulated best, although all do well. However, for the 18-period simulation, the econometric and regression methods perform substantially better than the Box-Jenkins formulation. A rationale for and implications of these results ae discussed. 11 references.
FBST for Cointegration Problems
NASA Astrophysics Data System (ADS)
Diniz, M.; Pereira, C. A. B.; Stern, J. M.
2008-11-01
In order to estimate causal relations, the time series econometrics has to be aware of spurious correlation, a problem first mentioned by Yule [21]. To solve the problem, one can work with differenced series or use multivariate models like VAR or VEC models. In this case, the analysed series are going to present a long run relation i.e. a cointegration relation. Even though the Bayesian literature about inference on VAR/VEC models is quite advanced, Bauwens et al. [2] highlight that "the topic of selecting the cointegrating rank has not yet given very useful and convincing results." This paper presents the Full Bayesian Significance Test applied to cointegration rank selection tests in multivariate (VAR/VEC) time series models and shows how to implement it using available in the literature and simulated data sets. A standard non-informative prior is assumed.
The Child as Econometrician: A Rational Model of Preference Understanding in Children
Lucas, Christopher G.; Griffiths, Thomas L.; Xu, Fei; Fawcett, Christine; Gopnik, Alison; Kushnir, Tamar; Markson, Lori; Hu, Jane
2014-01-01
Recent work has shown that young children can learn about preferences by observing the choices and emotional reactions of other people, but there is no unified account of how this learning occurs. We show that a rational model, built on ideas from economics and computer science, explains the behavior of children in several experiments, and offers new predictions as well. First, we demonstrate that when children use statistical information to learn about preferences, their inferences match the predictions of a simple econometric model. Next, we show that this same model can explain children's ability to learn that other people have preferences similar to or different from their own and use that knowledge to reason about the desirability of hidden objects. Finally, we use the model to explain a developmental shift in preference understanding. PMID:24667309
Drichoutis, Andreas C.; Lusk, Jayson L.
2014-01-01
Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error) for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample. PMID:25029467
Drichoutis, Andreas C; Lusk, Jayson L
2014-01-01
Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error) for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample.
The child as econometrician: a rational model of preference understanding in children.
Lucas, Christopher G; Griffiths, Thomas L; Xu, Fei; Fawcett, Christine; Gopnik, Alison; Kushnir, Tamar; Markson, Lori; Hu, Jane
2014-01-01
Recent work has shown that young children can learn about preferences by observing the choices and emotional reactions of other people, but there is no unified account of how this learning occurs. We show that a rational model, built on ideas from economics and computer science, explains the behavior of children in several experiments, and offers new predictions as well. First, we demonstrate that when children use statistical information to learn about preferences, their inferences match the predictions of a simple econometric model. Next, we show that this same model can explain children's ability to learn that other people have preferences similar to or different from their own and use that knowledge to reason about the desirability of hidden objects. Finally, we use the model to explain a developmental shift in preference understanding.
Analytical-numerical solution of a nonlinear integrodifferential equation in econometrics
NASA Astrophysics Data System (ADS)
Kakhktsyan, V. M.; Khachatryan, A. Kh.
2013-07-01
A mixed problem for a nonlinear integrodifferential equation arising in econometrics is considered. An analytical-numerical method is proposed for solving the problem. Some numerical results are presented.
Granger causality for state-space models
NASA Astrophysics Data System (ADS)
Barnett, Lionel; Seth, Anil K.
2015-04-01
Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations—commonplace in application domains as diverse as climate science, econometrics, and the neurosciences—induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.
DOT National Transportation Integrated Search
1979-12-01
An econometric model is developed which provides long-run policy analysis and forecasting of annual trends, for U.S. auto stock, new sales, and their composition by auto size-class. The concept of "desired" (equilibrium) stock is introduced. "Desired...
A statistical analysis of the effects of a uniform minimum drinking age
DOT National Transportation Integrated Search
1987-04-01
This report examines the relationship between minimum drinking age (MDA) and : highway fatalities during the 1975-1985 period, when 35 states changed their : MDAs. An econometric model of fatalities involving the 18-20 year-old driver : normalized by...
ERIC Educational Resources Information Center
Chressanthis, George A.; Chressanthis, June D.
1994-01-01
Asserts that subscription price increases for academic journals have been the area of single greatest concern to librarians during the past decade. Finds that systematic variations in library prices across economics journals offer explainable reasons. (CFR)
Airborne incidents : an econometric analysis of severity, December 19, 2014 : Final report
DOT National Transportation Integrated Search
2014-12-19
Airborne loss of separation incidents occur when an aircraft breaches the defined separation limit (vertical and/or horizontal) with another aircraft or terrain imposed by Air Traffic Control. Identifying conditions that lead to more severe loss of s...
Cost Effectiveness Trade-Offs in Software Support Environment Standardization.
1986-09-30
IIIIIEEEIIIIIE MiII I U..2 2 ma MICROCOPY RESOLUTION TEST CHART 911C FILE C y, o FINAL REPORT - September 30, 1986 G- TECHNION INTERNATIONAL, INC. Cost...Summary description of econometric model B-I C. Causal chain used as basis for model C-I D. Excerpts from [Wer185) D-1 LIST OF FIGURES S-1 USAF MCCR...Productivity cost drivers D-4 LIST OF TASL3$ I-1 Summary of Tangible Benefits in Econometric Equations 1-9 1-2 Summary of Tangible Costs in Econometric
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bjoerner, T.B.; Togeby, M.
1999-07-01
An econometric panel data analysis of industrial demand for electricity and energy is presented. In the panel energy consumption, production and value added are observed at company level. The authors estimate price and production elasticities for electricity and total energy (i.e. measuring the X per cent change in demand of say electricity of a one per cent increase in the price of electricity). The estimated price and production elasticities are allowed to vary according to company characteristics such as industrial sub-sector, company size, energy intensity and type of ownership. Most previous econometric studies on industrial energy demand use aggregate data,more » while a couple of micro level studies mainly employ cross-section analysis. To the knowledge this is only the second econometric study on industrial energy demand based on a large micro panel database. More than 2,700 Danish industrial companies during the period 1983 to 1995 are included in the model (covering the majority of all Danish industrial energy consumption). One advantage of micro data is that these data can be used to estimate the effect of an instrument like voluntary energy agreements. By entering a voluntary energy agreement a Danish company avoids paying the usual CO{sub 2} tax. Preliminary analyses suggest that there is a large positive gross reduction of electricity and total energy consumption of companies with energy agreements. However, the authors also find that companies would have had about the same reduction in electricity consumption if they had not entered into an agreement, but instead paid the full CO{sub 2} tax. Thus, the analysis suggests that the net effect on electricity use of the voluntary energy agreements is very low (perhaps even negative).« less
NASA Astrophysics Data System (ADS)
Ye, N. J.; Li, W. J.; Li, Y.; Bai, Y. F.
2017-12-01
Based on spatial panel data from 2010 to 2016 in China, this paper makes an empirical analysis on the relationship between highway construction and regional economic growth by means of spatial econometric model. The results show that there is positive spatial correlation on regional economic growth in China, and strong spatial dependences between some provinces and cities appear, specifically, Hebei, Beijing, Tianjin, Shanghai, Zhejiang and other eastern coastal areas show high-high agglomeration trend, the Pearl River Delta region presents high-low agglomeration trend; In terms of nationwide provinces and municipalities, a province’s highway construction investment for their own province and the neighboring provinces has pulling effect on economic growth to a certain extent, and the direct effect is more obvious.
Incomes, Attitudes, and Occurrences of Invasive Species: An Application to Signal Crayfish in Sweden
NASA Astrophysics Data System (ADS)
Gren, Ing-Marie; Campos, Monica; Edsman, Lennart; Bohman, Patrik
2009-02-01
This article analyzes and carries out an econometric test of the explanatory power of economic and attitude variables for occurrences of the nonnative signal crayfish in Swedish waters. Signal crayfish are a carrier of plague which threatens the native noble crayfish with extinction. Crayfish are associated with recreational and cultural traditions in Sweden, which may run against environmental preferences for preserving native species. Econometric analysis is carried out using panel data at the municipality level with economic factors and attitudes as explanatory variables, which are derived from a simple dynamic harvesting model. A log-normal model is used for the regression analysis, and the results indicate significant impacts on occurrences of waters with signal crayfish of changes in both economic and attitude variables. Variables reflecting environmental and recreational preferences have unexpected signs, where the former variable has a positive and the latter a negative impact on occurrences of waters with signal crayfish. These effects are, however, counteracted by their respective interaction effect with income.
Econometric Models of U.S. Navy Career Petty Officer Retention.
1981-06-01
PF AD-AL04 076 NAVAL POSTGRADUATE SCHOOL MONTEREY CA F/6 5/9 ECONO ETRIC MODELS OF U.S. NAVY CAREER PETTY OFFICER RETENTION.(Ul JUN 81 J J B PKO...THESIS D . ECONOMETRIC MODELS OF U. S. NAVY CAREER PETTY OFFICER RETENTION SML Vby John Joseph Bepko III June 1981 Thesis Advisor: George W. Thomas...DOCUMENTATION PACE 33703 coTu~rwc oEm 0419PsR 01N1911VT*48~ &GM01 1. 411CIP1SIMYS CATALOG IulmSIS Econometric Models of U. S. Navy Career Petty 1’ t h s s j
Does Peer Ability Affect Student Achievement?
ERIC Educational Resources Information Center
Hanushek, Eric A.; Kain, John F.; Markman, Jacob M.; Rivkin, Steven G.
Empirical analysis of peer effects on student achievement has been open to question because of the difficulties of separating peer effects from other confounding influences. While most econometric attention has been directed at issues of simultaneous determination of peer interactions, this paper argues that issues of omitted and mismeasured…
Econometrics of exhaustible resource supply: a theory and an application
DOE Office of Scientific and Technical Information (OSTI.GOV)
Epple, D.
1983-01-01
This report takes a major step toward developing a fruitful approach to empirical analysis of resource supply. It is the first empirical application of resource theory that has successfully integrated the effects of depletion of nonrenewable resources with the effects of uncertainty about future costs and prices on supply behavior. Thus, the model is a major improvement over traditional engineering-optimization models that assume complete certainty, and over traditional econometrics models that are only implicitly related to the theory of resource supply. The model is used to test hypotheses about interdependence of oil and natural gas discoveries, depletion, ultimate recovery, andmore » the role of price expectations. This paper demonstrates the feasibility of using exhaustible resource theory in the development of empirically testable models. 19 refs., 1 fig., 5 tabs.« less
The impact of corruption on the sustainable development of human capital
NASA Astrophysics Data System (ADS)
Absalyamova, Svetlana; Absalyamov, Timur; Khusnullova, Asiya; Mukhametgalieva, Chulpan
2016-08-01
The article explains the use of the human capital sustainable development index (HCSDI) to assess the quality of the reproduction of human capital. The paper provides the algorithm for calculating HCSDI and its components. Authors estimated cross-country differences of HCSDI and developed econometric model of the impact of corruption on HCSDI. The use of this model has allowed to reveal the mechanism and assess the impact of corruption on HCSDI and its components. The results of econometric analysis revealed a negative multiplier effect: an increase in the corruption of the socio-economic system of the state by 1% caused HCSDI reduce by more than 1%. The results and conclusions may be proxy-assessments of the socio-economic consequences of violations of the stability of reproduction of human capital in the conditions of the growth of corruption in the country
The Cost-Effectiveness of Raising Teacher Quality
ERIC Educational Resources Information Center
Yeh, Stuart S.
2009-01-01
Econometric studies suggest that student achievement may be improved if high-performing teachers are substituted for low-performing teachers. Drawing upon a recent study linking teacher performance on licensure exams with gains in student achievement, an analysis was conducted to determine the cost-effectiveness of requiring teacher applicants to…
Schools and Labor Market Outcomes. EQW Working Papers WP33.
ERIC Educational Resources Information Center
Crawford, David L.; And Others
The relationship between school characteristics and labor market outcomes was examined through a literature review and an econometric analysis of the effects of various characteristics of the schooling experience on students' labor market performance after high school. Data from the National Center on Education Statistics' longitudinal survey of…
Energy Conservation for Low-Income Households: The Evaporative Cooler Experience.
ERIC Educational Resources Information Center
Ridge, Richard S.
1988-01-01
An econometric analysis, using a research design based on the nonequivalent control group (NECG), assessed the effectiveness of a program offering free evaporative coolers to low-income families owning air conditioners. The NECG controls for serious threats to internal validity, except for self-selection. The program successfully reduced energy…
Spatial analysis of rural land development
Seong-Hoon Cho; David H. Newman
2005-01-01
This article examines patterns of rural land development and density using spatial econometric models with the application of Geographical Information System (GIS). The cluster patterns of both development and high-density development indicate that the spatially continuous expansions of development and high-density development exist in relatively remote rural areas....
The Dynamics of Online User Behavior and IS Policy Implications
ERIC Educational Resources Information Center
Kim, Keehyung
2016-01-01
This dissertation, which comprises three independent essays, explores the dynamics of online user behavior and provides IS policy implications across three different applications. The first essay employs an econometric empirical analysis to examine the role of IT interventions on online users' gambling behavior, based on field data collected over…
DOT National Transportation Integrated Search
2011-11-01
This study analyzes the effect of impact fees in urban form and congestion through a combination of methods including econometric analysis, GIS techniques, and interviews with planning officials. The results show that there is some evidence that impa...
The Insulation Board Industry - An Economic Analysis
Albert T. Schuler
1978-01-01
An econometric model of the domestic insulation board industry was developed to identify and quantify the major factors affecting quantity consumed and price. The factors identified were housing starts, residential improvement activity, disposable personal income, productivity, pulpwood and residue prices, and power costs. Disposable personal income was the most...
An Econommetric Analysis of the U.S. Hardboard Market
Albert T. Schuler
1978-01-01
An econometric model of U.S. hardboard consumption was developed to identify the major variables affecting hardboard consumption and price. The variables identified were housing starts, residential improvement activity, disposable personal income, hardwood plywood price, productivity, pulpwood and residue price, hardboard tariff, and power cost, Disposable personal...
The Ph.D. Production Function: The Case at Berkeley.
ERIC Educational Resources Information Center
Breneman, David W.
This report analyzes departmental variations in time to degree and attrition in Ph.D. programs at Berkeley. An alternative hypothesis, the Ph.D. production function, is examined by cross-section econometric analysis of 28 departments. The inputs included in the production function were student variables--quality and percent males; faculty…
Household Schooling Decisions in Rural Pakistan. Working Paper.
ERIC Educational Resources Information Center
Sawada, Yasuyuki; Lokshin, Michael
A study of household schooling decisions in rural Pakistan found serious supply-side constraints on female primary education in the villages studied. Field surveys of 25 Pakistani villages were integrated with economic theory and econometric analysis to investigate the sequential nature of educational decisions. The full-information maximum…
Space-time modeling of timber prices
Mo Zhou; Joseph Buongriorno
2006-01-01
A space-time econometric model was developed for pine sawtimber timber prices of 21 geographically contiguous regions in the southern United States. The correlations between prices in neighboring regions helped predict future prices. The impulse response analysis showed that although southern pine sawtimber markets were not globally integrated, local supply and demand...
Estimating School Efficiency: A Comparison of Methods Using Simulated Data.
ERIC Educational Resources Information Center
Bifulco, Robert; Bretschneider, Stuart
2001-01-01
Uses simulated data to assess the adequacy of two econometric and linear-programming techniques (data-envelopment analysis and corrected ordinary least squares) for measuring performance-based school reform. In complex data sets (simulated to contain measurement error and endogeneity), these methods are inadequate efficiency measures. (Contains 40…
Measuring Systematic Long-Term Trajectories of School Effectiveness Improvement
ERIC Educational Resources Information Center
Valenzuela, Juan Pablo; Bellei, Cristián; Allende, Claudio
2016-01-01
The objective of this study was to identify trajectories of school improvement experienced by Chilean elementary schools over the last decade. Using econometric analysis and controlling for potential confounding factors, we created an index of school performance combining outcome indicators focused on different school dimensions, and estimated the…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Griffin, J.M.
1977-11-01
The pseudo data approach to the joint production of petroleum refining and chemicals is described as an alternative that avoids the multicollinearity of time series data and allows a complex technology to be characterized in a statistical price possibility frontier. Intended primarily for long-range analysis, the pseudo data method can be used as a source of elasticity estimate for policy analysis. 19 references.
ERIC Educational Resources Information Center
Bel, Germa; Fageda, Xavier; Warner, Mildred E.
2010-01-01
Privatization of local government services is assumed to deliver cost savings, but empirical evidence for this from around the world is mixed. We conduct a meta-regression analysis of all econometric studies examining privatization of water distribution and solid waste collection services and find no systematic support for lower costs with private…
Glossary for econometrics and epidemiology.
Gunasekara, F Imlach; Carter, K; Blakely, T
2008-10-01
Epidemiologists and econometricians are often interested in similar topics-socioeconomic position and health outcomes-but the different languages that epidemiologists and economists use to interpret and discuss their results can create a barrier to mutual communication. This glossary defines key terms used in econometrics and epidemiology to assist in bridging this gap.
DOT National Transportation Integrated Search
2011-09-21
Title: Transportation and Socioeconomic Impacts of Bypasses on Communities: An Integrated Synthesis of Panel Data, Multilevel, and Spatial Econometric Models with Case Studies. The title used at the start of this project was Transportation and Soc...
Grade Repetition in Honduran Primary Schools
ERIC Educational Resources Information Center
Marshall, Jeffery H.
2003-01-01
This paper looks at several dimensions of the grade failure issue in Honduras using a unique data set compiled by the UMCE evaluation project in 1998 and 1999. The analytical framework incorporates econometric analysis of standardized tests and teacher pass/fail decisions for roughly 13,000 second and fourth grade students. The results show that…
School District Leave Policies, Teacher Absenteeism, and Student Achievement.
ERIC Educational Resources Information Center
Ehrenberg, Ronald G.; And Others
1991-01-01
Econometric analysis of data from over 700 New York state school districts found that (1) policies governing use of teacher leave days clearly influence their use; (2) higher student absenteeism correlated with poorer test performance; and (3) teacher absence was not largely associated with student test performance. Changes in leave policy were…
The Effect of School Size on Exam Performance in Secondary Schools.
ERIC Educational Resources Information Center
Bradley, Steve; Taylor, Jim
1998-01-01
Examines the effects of school size on exam performance for pupils in their final year of compulsory education in England. Background information about English secondary schools and the determinants of exam performance are discussed along with a description of the variables used in the econometric analysis and their expected effects on exam…
School Cost Functions: A Meta-Regression Analysis
ERIC Educational Resources Information Center
Colegrave, Andrew D.; Giles, Margaret J.
2008-01-01
The education cost literature includes econometric studies attempting to determine economies of scale, or estimate an optimal school or district size. Not only do their results differ, but the studies use dissimilar data, techniques, and models. To derive value from these studies requires that the estimates be made comparable. One method to do…
Wage Determinants among Medical Doctors and Nurses in Spain
ERIC Educational Resources Information Center
Salas-Velasco, Manuel
2010-01-01
This paper examines the determination of wage rates for health professionals using three well known, and commonly used, econometric techniques: ordinary least squares, instrumental variables, and Heckman's method. The data come from a graduate survey and the analysis focuses on a regional labor market, due to nationwide information on salaries is…
Estimated Effects of Retirement Revision on Retention of Navy Tactical Pilots.
1986-12-01
detailed explanation of the procedure and proofs can be found in Hanushek and Jackson [Ref. 441. S511 ,V. VI. RESULTS AND ANALYSIS A. DESCRIPTIVE...Introduction to Econometrics, pp. 242-243, Prentice-Hall, 1978. 44. Hanushek Eric ard Jackson, John, Statistical .Mlethods for Social Scientists, p. S188
of residential solar PV markets. Eric leads the lab's solar data partnerships program. Eric's current green power market research. Research Interests Economic analysis, econometrics, distributed solar PV . Ardani, R. Margolis. 2018. Solar plus: Optimization of distributed solar PV through battery storage and
ERIC Educational Resources Information Center
Ng, Larson S. W. M.
2011-01-01
The following study attempted to ascertain the instructional cost-effectiveness of public high school teachers towards high school completion through a financially based econometric analysis. Essentially, public high school instruction expenditures and completer data were collected from 2000 to 2007 and bivariate interaction analyzed through a…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hanham, R.; Vogt, W.G.; Mickle, M.H.
1986-01-01
This book presents the papers given at a conference on computerized simulation. Topics considered at the conference included expert systems, modeling in electric power systems, power systems operating strategies, energy analysis, a linear programming approach to optimum load shedding in transmission systems, econometrics, simulation in natural gas engineering, solar energy studies, artificial intelligence, vision systems, hydrology, multiprocessors, and flow models.
Decisions That Affect Outcomes in the Distant Future.
1979-12-01
cost-he.n- efit analysis is a special case of the results lerived in this rvso arch . %; In Chapter 3, the assumptions underlying willingness to pay are...p°,m°,z°). This information would generally cone from ex- perts or econometric studies. 5.5 Consistency Conditions There are two ways in which we
The Costs and Benefits of Deferred Giving.
ERIC Educational Resources Information Center
Fink, Norman S.; Metzler, Howard C.
It is argued in this book that while there can be a significant payoff for deferred giving programs, it is important to determine their cost effectiveness. Modern business methods of cost accounting, benefits analysis, and actuarial and econometric forecasting are applied to the Pomona College plan, whose study was supported by Lilly Endowment,…
Resource Allocation in Public Research Universities
ERIC Educational Resources Information Center
Santos, Jose L.
2007-01-01
The purpose of this study was to conduct an econometric analysis of internal resource allocation. Two theories are used for this study of resource allocation in public research universities, and these are: (1) Theory of the Firm; and (2) Resource Dependence Theory. This study used the American Association of Universities Data Exchange (AAUDE)…
Li, Qian; Trivedi, Pravin K
2016-02-01
This paper develops an extended specification of the two-part model, which controls for unobservable self-selection and heterogeneity of health insurance, and analyzes the impact of Medicare supplemental plans on the prescription drug expenditure of the elderly, using a linked data set based on the Medicare Current Beneficiary Survey data for 2003-2004. The econometric analysis is conducted using a Bayesian econometric framework. We estimate the treatment effects for different counterfactuals and find significant evidence of endogeneity in plan choice and the presence of both adverse and advantageous selections in the supplemental insurance market. The average incentive effect is estimated to be $757 (2004 value) or 41% increase per person per year for the elderly enrolled in supplemental plans with drug coverage against the Medicare fee-for-service counterfactual and is $350 or 21% against the supplemental plans without drug coverage counterfactual. The incentive effect varies by different sources of drug coverage: highest for employer-sponsored insurance plans, followed by Medigap and managed medicare plans. Copyright © 2014 John Wiley & Sons, Ltd.
Ranking product aspects through sentiment analysis of online reviews
NASA Astrophysics Data System (ADS)
Wang, Wei; Wang, Hongwei; Song, Yuan
2017-03-01
The electronic word-of-mouth (e-WOM) is one of the most important among all the factors affecting consumers' behaviours. Opinions towards a product through online reviews will influence purchase decisions of other online consumers by changing their perceptions on the product quality. Furthermore, each product aspect may impact consumers' intentions differently. Thus, sentiment analysis and econometric models are incorporated to examine the relationship between purchase intentions and aspect-opinion pairs, which enable the weight estimation for each product aspect. We first identify product aspects and reduce dimensions to extract aspect-opinion pairs. Next the information gain is calculated for each aspect through entropy theory. Based on sentiment polarity and sentiment strength, we formulate an econometric model by integrating the information gain to measure the aspect's weight. In the experiment, we track 386 digital cameras on Amazon for 39 months, and results show that the aspect weight for digital cameras is detected more precisely than TF-ID and HAC algorithms. The results will bridge product aspects and consumption intention to facilitate e-WOM-based marketing.
NASA Astrophysics Data System (ADS)
Schu, Kathryn L.
Economy-energy-environment models are the mainstay of economic assessments of policies to reduce carbon dioxide (CO2) emissions, yet their empirical basis is often criticized as being weak. This thesis addresses these limitations by constructing econometrically calibrated models in two policy areas. The first is a 35-sector computable general equilibrium (CGE) model of the U.S. economy which analyzes the uncertain impacts of CO2 emission abatement. Econometric modeling of sectors' nested constant elasticity of substitution (CES) cost functions based on a 45-year price-quantity dataset yields estimates of capital-labor-energy-material input substitution elasticities and biases of technical change that are incorporated into the CGE model. I use the estimated standard errors and variance-covariance matrices to construct the joint distribution of the parameters of the economy's supply side, which I sample to perform Monte Carlo baseline and counterfactual runs of the model. The resulting probabilistic abatement cost estimates highlight the importance of the uncertainty in baseline emissions growth. The second model is an equilibrium simulation of the market for new vehicles which I use to assess the response of vehicle prices, sales and mileage to CO2 taxes and increased corporate average fuel economy (CAFE) standards. I specify an econometric model of a representative consumer's vehicle preferences using a nested CES expenditure function which incorporates mileage and other characteristics in addition to prices, and develop a novel calibration algorithm to link this structure to vehicle model supplies by manufacturers engaged in Bertrand competition. CO2 taxes' effects on gasoline prices reduce vehicle sales and manufacturers' profits if vehicles' mileage is fixed, but these losses shrink once mileage can be adjusted. Accelerated CAFE standards induce manufacturers to pay fines for noncompliance rather than incur the higher costs of radical mileage improvements. Neither policy induces major increases in fuel economy.
An Econometric Model for Forecasting Income and Employment in Hawaii.
ERIC Educational Resources Information Center
Chau, Laurence C.
This report presents the methodology for short-run forecasting of personal income and employment in Hawaii. The econometric model developed in the study is used to make actual forecasts through 1973 of income and employment, with major components forecasted separately. Several sets of forecasts are made, under different assumptions on external…
Outputs as Educator Effectiveness in the United States: Shifting towards Political Accountability
ERIC Educational Resources Information Center
Piro, Jody S.; Mullen, Laurie
2013-01-01
The definition of educator effectiveness is being redefined by econometric modeling to evidence student achievement on standardized tests. While the reasons that econometric frameworks are in vogue are many, it is clear that the strength of such models lie in the quantifiable evidence of student learning. Current accountability models frame…
Econometric Models for Forecasting of Macroeconomic Indices
ERIC Educational Resources Information Center
Sukhanova, Elena I.; Shirnaeva, Svetlana Y.; Mokronosov, Aleksandr G.
2016-01-01
The urgency of the research topic was stipulated by the necessity to carry out an effective controlled process by the economic system which can hardly be imagined without indices forecasting characteristic of this system. An econometric model is a safe tool of forecasting which makes it possible to take into consideration the trend of indices…
Technical Change in the North American Forestry Sector: A Review
Jeffery C. Stier; David N. Bengston
1992-01-01
Economists have examined the impact of technical change on the forest products sector using the historical, index number, and econometric approaches. This paper reviews econometric analyses of the rate and bias of technical change, examining functional form, factors included, and empirical results. Studies are classified as first- second-, or third-generation...
Econometric Methods for Causal Evaluation of Education Policies and Practices: A Non-Technical Guide
ERIC Educational Resources Information Center
Schlotter, Martin; Schwerdt, Guido; Woessmann, Ludger
2011-01-01
Education policy-makers and practitioners want to know which policies and practices can best achieve their goals. But research that can inform evidence-based policy often requires complex methods to distinguish causation from accidental association. Avoiding econometric jargon and technical detail, this paper explains the main idea and intuition…
An econometric model of the hardwood lumber market
William G. Luppold
1982-01-01
A recursive econometric model with causal flow originating from the demand relationship is used to analyze the effects of exogenous variables on quantity and price of hardwood lumber. Wage rates, interest rates, stumpage price, lumber exports, and price of lumber demanders' output were the major factors influencing quantities demanded and supplied and hardwood...
The Status of Econometrics in the Economics Major: A Survey
ERIC Educational Resources Information Center
Johnson, Bruce K.; Perry, John J.; Petkus, Marie
2012-01-01
In this article, the authors describe the place of econometrics in undergraduate economics curricula in all American colleges and universities that offer economics majors as listed in the "U.S. News & World Report" "Best Colleges 2010" guide ("U.S. News & World Report" 2009). Data come from online catalogs, departmental Web sites, and online…
Empirical methods for modeling landscape change, ecosystem services, and biodiversity
David Lewis; Ralph Alig
2009-01-01
The purpose of this paper is to synthesize recent economics research aimed at integrating discrete-choice econometric models of land-use change with spatially-explicit landscape simulations and quantitative ecology. This research explicitly models changes in the spatial pattern of landscapes in two steps: 1) econometric estimation of parcel-scale transition...
Lachaud, Jean-Pierre
2007-05-01
Based on the data of the Demographic and Health Survey, and of the Household Priority Survey, carried out in 2003, the present study, examining the factors of HIV prevalence in Burkina Faso, provides two conclusions. Firstly, the fight against poverty is not necessarily a means of reducing simultaneously and drastically HIV/AIDS prevalence, an assertion based on several elements of empirical analysis. First of all, the micro-econometric estimates of the probit models suggest a positive relationship between HIV prevalence in adult women and men, and living standards of individuals. Then, the macro-econometric approach reveals the existence of a positive (negative) relationship between, on the one hand, the level of regional HIV prevalence, and, on the other hand, the average monetary provincial standard of living (poverty) of households. At the same time, the relationship between HIV prevalence and poverty, apprehended at the regional level, is not linear. Secondly, and correlatively, the relationship between HIV prevalence and poverty is called into question. First of all, some structural factors may contribute to a distortion of the relationship between resources of households and the prevalence of HIV/AIDS. This may be due, on the one hand, to the persistence of cognitive and behavioural factors inherent in a traditional society, and in particular, to the fact that the social construction of female attributes and roles confers to men a statute of "decision-makers" with regard to sexual intercourse, while the persistence of secular beliefs contributes to minimizing the perception of HIV/AIDS in terms of risk, independently of standards of living. In addition, the enclavement of Burkina Faso required development of road and railway traffic with neighbouring countries, in particular Côte d'Ivoire. Therefore, it may be that the structural conditions of the process of development of Burkina Faso, concomitant with significant flows of the exchange of goods, services and labour with a country where the prevalence of the HIV is particularly high, constitute an element of an explanation of the positive relationship between the resources of households and HIV seroprevalence. Also, factors related to the economic situation probably contributed to reinforcing the opposite relationship between HIV seroprevalence and poverty, the macro-econometric analysis highlighting a direct relationship between the massive return of migrants of Côte d'Ivoire and the level of HIV prevalence in Burkina Faso.
Pulling Econometrics Students up by Their Bootstraps
ERIC Educational Resources Information Center
O'Hara, Michael E.
2014-01-01
Although the concept of the sampling distribution is at the core of much of what we do in econometrics, it is a concept that is often difficult for students to grasp. The thought process behind bootstrapping provides a way for students to conceptualize the sampling distribution in a way that is intuitive and visual. However, teaching students to…
DOT National Transportation Integrated Search
1999-11-01
Using a fairly large cross-section/time-series data base, covering all provinces of Norway and all months between January 1973 and December 1994, we estimate non-linear (Box-Cox) regression equations explaining aggregate car ownership, road use, seat...
Econometric Methods for Research in Education. NBER Working Paper No. 16003
ERIC Educational Resources Information Center
Meghir, Costas; Rivkin, Steven G.
2010-01-01
This paper reviews some of the econometric methods that have been used in the economics of education. The focus is on understanding how the assumptions made to justify and implement such methods relate to the underlying economic model and the interpretation of the results. We start by considering the estimation of the returns to education both…
ERIC Educational Resources Information Center
Arnold, Ivo J. M.; Rowaan, Wietske
2014-01-01
In this study, the authors investigate the relationships among gender, math skills, motivation, and study success in economics and econometrics. They find that female students have stronger intrinsic motivation, yet lower study confidence than their male counterparts. They also find weak evidence for a gender gap over the entire first-year…
An Initial Econometric Consideration of Supply and Demand in the Guaranteed Student Loan Program.
ERIC Educational Resources Information Center
Bayus, Barry; Kendis, Kurt
1982-01-01
In this econometric model of the Guaranteed Student Loan Program (GSLP), supply is related to banks' liquidity and yield curves, all lenders' economic costs and returns, and Student Loan Marketing Association activity. GSLP demand is based on loan costs, family debt position, and net student need for financial aid. (RW)
Federal Register 2010, 2011, 2012, 2013, 2014
2013-07-09
... behavior is included in the econometric models underlying STANS, time series of proportional changes in... included in the econometric models underlying STANS, time series of proportional changes in implied... calculate daily margin requirements. OCC has proposed at this time to clear only OTC Options on the S&P 500...
ERIC Educational Resources Information Center
Binder, Martin; Coad, Alex
2011-01-01
There is an ambiguity in Amartya Sen's capability approach as to what constitutes an individual's resources, conversion factors and valuable functionings. What we here call the "circularity problem" points to the fact that all three concepts seem to be mutually endogenous and interdependent. To econometrically account for this…
Resources and Constraints: Public Education and the Economic Environment in Ontario, 1978-1987.
ERIC Educational Resources Information Center
Foot, David K.
Considering the national and provincial economic environments for the next decade, this paper projects financial resources and constraints likely to be faced by school boards in Ontario over the same period. The study utilizes an econometric model developed by the Institute for Policy Analysis of the University of Toronto. The findings indicate…
ERIC Educational Resources Information Center
Mushrush, Christopher E.
2013-01-01
Traditionally, public funding of higher education has been viewed as cyclical, where support falls during times of economic downturn and then recovers as the economy improves. This view, however, is being challenged as budgetary shortfalls are becoming more common for states, even in times of economic growth, due to structural constraints. Using…
Econometric analysis of fire suppression production functions for large wildland fires
Thomas P. Holmes; David E. Calkin
2013-01-01
In this paper, we use operational data collected for large wildland fires to estimate the parameters of economic production functions that relate the rate of fireline construction with the level of fire suppression inputs (handcrews, dozers, engines and helicopters). These parameter estimates are then used to evaluate whether the productivity of fire suppression inputs...
Declining national park visitation: An economic analysis
Thomas H. Stevens; Thomas A. More; Marla Markowski-Lindsay
2014-01-01
Visitation to the major nature-based national parks has been declining. This paper specifies an econometric model that estimates the relative impact of consumer incomes, travel costs, entry fees and other factors on per capita attendance from 1993 to 2010. Results suggest that entrance fees have had a statistically significant but small impact on per capita attendance...
The Effects of International Mobility on European Researchers: Comparing Intra-EU and U.S. Mobility
ERIC Educational Resources Information Center
Veugelers, Reinhilde; Van Bouwel, Linda
2015-01-01
Using econometric analysis on survey data from European-born and European-educated researchers who are internationally mobile after their PhD within Europe or to the United States, we find significant positive effects from international mobility on scientific productivity, as well as several other positive career development effects. European…
Vietnam: The Political Economy of Education in a "Socialist" Periphery
ERIC Educational Resources Information Center
London, Jonathan D.
2006-01-01
In this article I examine historic changes in the goals, conduct and outcomes of education policies in Vietnam from the 1940s to the present, under the Communist Party of Vietnam. Recent studies of Vietnam's education system centre on econometric and demographic analysis of education data dating back to the early 1990s, when Vietnam began an…
An Econometric Examination of the Behavioral Perspective Model in the Context of Norwegian Retailing
ERIC Educational Resources Information Center
Sigurdsson, Valdimar; Kahamseh, Saeed; Gunnarsson, Didrik; Larsen, Nils Magne; Foxall, Gordon R.
2013-01-01
The behavioral perspective model's (BPM; Foxall, 1990) retailing literature is built on extensive empirical research and techniques that were originally refined in choice experiments in behavioral economics and behavior analysis, and then tested mostly on British consumer panel data. We test the BPM in the context of Norwegian retailing. This…
Colin A. McMillan Photo of Colin A. McMillan. Colin McMillan Researcher IV-Operations Research Econometrics Research Interests Systems-level energy efficiency analysis Material and energy flows in economies ; Journal of Industrial Ecology 17, no. 5 (October 2013): 700-11. doi:10.1111/jiec.12050 McMillan, C.A., S.J
78 FR 29258 - Blueberry Promotion, Research and Information Order; Assessment Rate Increase
Federal Register 2010, 2011, 2012, 2013, 2014
2013-05-20
.... \\6\\ The econometric model used statistical methods with time series data to measure how strongly the... program has been over 15 times greater than the costs. At the opposite end of the spectrum in the supply... times greater than the costs. Given the wide range of supply responses considered in the analysis, and...
Robust estimation procedure in panel data model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shariff, Nurul Sima Mohamad; Hamzah, Nor Aishah
2014-06-19
The panel data modeling has received a great attention in econometric research recently. This is due to the availability of data sources and the interest to study cross sections of individuals observed over time. However, the problems may arise in modeling the panel in the presence of cross sectional dependence and outliers. Even though there are few methods that take into consideration the presence of cross sectional dependence in the panel, the methods may provide inconsistent parameter estimates and inferences when outliers occur in the panel. As such, an alternative method that is robust to outliers and cross sectional dependencemore » is introduced in this paper. The properties and construction of the confidence interval for the parameter estimates are also considered in this paper. The robustness of the procedure is investigated and comparisons are made to the existing method via simulation studies. Our results have shown that robust approach is able to produce an accurate and reliable parameter estimates under the condition considered.« less
Fuel poverty as a major determinant of perceived health: the case of France.
Lacroix, E; Chaton, C
2015-05-01
The number of households in fuel poverty is growing. Individuals increasingly struggle to heat their homes, and therefore, a growing number of individuals are exposed to low temperatures, which can affect their health. This study sought to determine the link between a subjective measure of fuel poverty (self-reported feeling cold) and self-reported health. The impact of other particular individual and environmental features on self-reported health were also analysed. Econometric analysis. The study method uses self-reported perception of thermal discomfort (self-reported feeling cold) as a proxy for fuel poverty. The French database of the Healthcare and Insurance survey carried by the Institute for Research and Information on Health Economics (IRDES) was used to estimate a dichotomous probit model. The estimation allows us to infer a negative impact of fuel poverty on self-reported health. Thus, a person in fuel poverty is 2.36 percentage points more likely to report poor or fair health status than a person who is not in fuel poverty. It may be appropriate to reduce the impacts of fuel poverty to provide support for the most vulnerable categories of individuals with respect to the health impacts of fuel poverty and cold homes, e.g., chronic patients who experience difficulty heating their homes. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
Econometric Assessment of "One Minute" Paper as a Pedagogic Tool
ERIC Educational Resources Information Center
Das, Amaresh
2010-01-01
This paper makes an econometric testing of one-minute paper used as a tool to manage and assess instruction in my statistics class. One of our findings is that the one minute paper when I have tested it by using an OLS estimate in a controlled Vs experimental design framework is found to statistically significant and effective in enhancing…
The Anatomy of a Likely Donor: Econometric Evidence on Philanthropy to Higher Education
ERIC Educational Resources Information Center
Lara, Christen; Johnson, Daniel
2014-01-01
In 2011, philanthropic giving to higher education institutions totaled $30.3 billion, an 8.2% increase over the previous year. Roughly, 26% of those funds came from alumni donations. This article builds upon existing economic models to create an econometric model to explain and predict the pattern of alumni giving. We test the model using data…
An Econometric Approach to Evaluate Navy Advertising Efficiency.
1996-03-01
This thesis uses an econometric approach to systematically and comprehensively analyze Navy advertising and recruiting data to determine Navy... advertising cost efficiency in the Navy recruiting process. Current recruiting and advertising cost data are merged into an appropriate data base and...evaluated using multiple regression techniques to find assessments of the relationships between Navy advertising expenditures and recruit contracts attained
Patterns of Marine Corps Reserve Continuation Behavior: Pre- and Post-9/11
2011-03-01
to consider when studying reserve retention and very difficult to measure using multivariate econometric models, which rely solely on observational...chapter present an interesting supplement to standard economic theoretical perspectives commonly used in econometric analyses. Notably, the structural...relevant to this thesis. These factors contribute to the over- arching themes of job satisfaction and organizational commitment and therefore ultimately
Predicting future forestland area: a comparison of econometric approaches.
SoEun Ahn; Andrew J. Plantinga; Ralph J. Alig
2000-01-01
Predictions of future forestland area are an important component of forest policy analyses. In this article, we test the ability of econometric land use models to accurately forecast forest area. We construct a panel data set for Alabama consisting of county and time-series observation for the period 1964 to 1992. We estimate models using restricted data sets-namely,...
An econometric model of the U.S. pallet market
Albert T. Schuler; Walter B. Wallin
1979-01-01
A need for quantitative information on demand and price has been expressed by the pallet industry. In response to this, an econometric model of the aggregate U.S. pallet market was developed. Demand was found to be affected by real pallet price, industrial and food production levels, and slipsheet prices. Supply was affected by real price, housing starts lagged 1 year...
ERIC Educational Resources Information Center
Nurnberg, Peter; Schapiro, Morton; Zimmerman, David
2010-01-01
The college choice process can be reduced to three questions: (1) Where does a student apply?; (2) Which schools accept the students?; and (3) Which offer of admission does the student accept? This paper addresses question three. Specifically, we offer an econometric analysis of the matriculation decisions made by students accepted to Williams…
ERIC Educational Resources Information Center
Handa, M. L.
This report describes some models the author developed to investigate the simultaneous interaction of decisionmakers in a province-wide educational system and to help formulate educational policy for achieving specified enrollments and expenditures. In chapter one, the author describes the models that examine the process of simultaneous…
ERIC Educational Resources Information Center
Nurnberg, Peter; Schapiro, Morton; Zimmerman, David
2012-01-01
This paper provides an econometric analysis of the matriculation decisions made by students accepted to Williams College, one of the nation's most highly selective colleges and universities. Using data for the Williams classes of 2008 through 2012 to estimate a yield model, we find that--conditional on the student applying to and being accepted by…
Enhancing Hungarian Special Forces through Transformation -- The Shift to Special Operations Forces
2010-06-01
heteroskedasticity and the Ramsey RESET test . For the detailed regression results see Appendix B. Damodar N. Gujarati, Basic Econometrics , Third...96 Table 13. Ramsey RESET test using powers of the fitted values of DV1 (relative attitude toward HUNSF... Ramsey RESET test using powers of the fitted values of DV1 (relative attitude toward HUNSF) B. REGRESSION ANALYSIS
Thomas P. Holmes; Kevin J. Boyle
2005-01-01
A hybrid stated-preference model is presented that combines the referendum contingent valuation response format with an experimentally designed set of attributes. A sequence of valuation questions is asked to a random sample in a mailout mail-back format. Econometric analysis shows greater discrimination between alternatives in the final choice in the sequence, and the...
ERIC Educational Resources Information Center
Yigermal, Moges Endalamaw
2017-01-01
The main objective of the paper is to investigate the determinant factors affecting the academic performance of regular undergraduate students of Arba Minch university (AMU) chamo campus students. To meet the objective, the Pearson product moment correlation statistical tool and econometrics data analysis (OLS regression) method were used with the…
ERIC Educational Resources Information Center
Shih, Cheng Ping; Tillett, Denroy; Lawrence, Nadine
2012-01-01
Taiwan has proven and continues to prove its economic prowess as a fast and well developed nation. One theory to account for this accomplishment is its continued success in developing its best natural resource--its people--through education. A continuum of this practice is the implementation of Higher Education and then International Higher…
The Ratio of Public Investment in Education in China
ERIC Educational Resources Information Center
Liu, Zeyun; Yuan, Liansheng
2007-01-01
Based on cross-section data worldwide and time series data in China, the essay is intended to make an analysis of the factors which have impacts on the ratio of public investment in education by using econometric models and then the future ratio may be predicted. Conclusions are as follows. First, the proportion of fiscal revenue to GDP (gross…
ERIC Educational Resources Information Center
Levine, Judith A.; Pollack, Harold
This study used linked maternal-child data from the 1997-1998 National Longitudinal Survey of Youth to explore the wellbeing of children born to teenage mothers. Two econometric techniques explored the causal impact of early childbearing on subsequent child and adolescent outcomes. First, a fixed-effect, cousin-comparison analysis controlled for…
Reducing the Digital Divide through ICT Adoption: Factors, Barriers, and How ICT in Schools Can Help
ERIC Educational Resources Information Center
Tengtrakul, Pitikorn
2013-01-01
Through econometric analysis of data from multiple surveys, this study explores factors that affect ICT adoption and evaluates the extent to which ICT in schools affect the ICT adoption of surrounding communities, in order to provide a perspective that can help narrow the gap of digital divide. Understanding factors affecting ICT adoption may…
Economics of Job Search: A Biracial Analysis of Job Search Behavior of Urban Male Youth Ages 18-22.
ERIC Educational Resources Information Center
Stephenson, Stanley P., Jr.
This study presents and tests an econometric model of job search behavior for youth. The main hypothesis is that differences in search behavior help account for youth-adult employment differences and that within the youth group, black-white unemployment and earnings differentials can be partially explained by job search behavior. Endogenous…
Chin, Wen Cheong; Lee, Min Cherng; Yap, Grace Lee Ching
2016-01-01
High frequency financial data modelling has become one of the important research areas in the field of financial econometrics. However, the possible structural break in volatile financial time series often trigger inconsistency issue in volatility estimation. In this study, we propose a structural break heavy-tailed heterogeneous autoregressive (HAR) volatility econometric model with the enhancement of jump-robust estimators. The breakpoints in the volatility are captured by dummy variables after the detection by Bai-Perron sequential multi breakpoints procedure. In order to further deal with possible abrupt jump in the volatility, the jump-robust volatility estimators are composed by using the nearest neighbor truncation approach, namely the minimum and median realized volatility. Under the structural break improvements in both the models and volatility estimators, the empirical findings show that the modified HAR model provides the best performing in-sample and out-of-sample forecast evaluations as compared with the standard HAR models. Accurate volatility forecasts have direct influential to the application of risk management and investment portfolio analysis.
Empirical spatial econometric modelling of small scale neighbourhood
NASA Astrophysics Data System (ADS)
Gerkman, Linda
2012-07-01
The aim of the paper is to model small scale neighbourhood in a house price model by implementing the newest methodology in spatial econometrics. A common problem when modelling house prices is that in practice it is seldom possible to obtain all the desired variables. Especially variables capturing the small scale neighbourhood conditions are hard to find. If there are important explanatory variables missing from the model, the omitted variables are spatially autocorrelated and they are correlated with the explanatory variables included in the model, it can be shown that a spatial Durbin model is motivated. In the empirical application on new house price data from Helsinki in Finland, we find the motivation for a spatial Durbin model, we estimate the model and interpret the estimates for the summary measures of impacts. By the analysis we show that the model structure makes it possible to model and find small scale neighbourhood effects, when we know that they exist, but we are lacking proper variables to measure them.
Modeling the assessment of the economic factors impact on the development of social entrepreneurship
NASA Astrophysics Data System (ADS)
Absalyamov, T.; Kundakchyan, R.; Zulfakarova, L.; Zapparova, Z.
2017-12-01
The article deals with the research of modern trends in the development of social entrepreneurship in Russia. The results of the research allow the authors to identify a system of factors that affect the development of entrepreneurship in the modern Russian economy. Moreover, the authors argue the regional specificity of the development of social entrepreneurship. The paper considers specific features and formulates the main limitations of the development of entrepreneurship and the competitive environment in the social sphere. The authors suggest an econometric model for assessing the influence of economic factors on the development of socially-oriented entrepreneurship and present an algorithm for calculating its components. The results of the econometric analysis identify the main factors of the change in the performance indicators of entrepreneurial activity and determine the degree of their impact on social entrepreneurship. The results and conclusions can serve as an estimation of the socioeconomic consequences of the sustainability disruption of the entrepreneurial potential realization in the social sphere.
NASA Astrophysics Data System (ADS)
Wells, Aaron Raymond
This research focuses on the Emory and Obed Watersheds in the Cumberland Plateau in Central Tennessee and the Lower Hatchie River Watershed in West Tennessee. A framework based on market and nonmarket valuation techniques was used to empirically estimate economic values for environmental amenities and negative externalities in these areas. The specific techniques employed include a variation of hedonic pricing and discrete choice conjoint analysis (i.e., choice modeling), in addition to geographic information systems (GIS) and remote sensing. Microeconomic models of agent behavior, including random utility theory and profit maximization, provide the principal theoretical foundation linking valuation techniques and econometric models. The generalized method of moments estimator for a first-order spatial autoregressive function and mixed logit models are the principal econometric methods applied within the framework. The dissertation is subdivided into three separate chapters written in a manuscript format. The first chapter provides the necessary theoretical and mathematical conditions that must be satisfied in order for a forest amenity enhancement program to be implemented. These conditions include utility, value, and profit maximization. The second chapter evaluates the effect of forest land cover and information about future land use change on respondent preferences and willingness to pay for alternative hypothetical forest amenity enhancement options. Land use change information and the amount of forest land cover significantly influenced respondent preferences, choices, and stated willingness to pay. Hicksian welfare estimates for proposed enhancement options ranged from 57.42 to 25.53, depending on the policy specification, information level, and econometric model. The third chapter presents economic values for negative externalities associated with channelization that affect the productivity and overall market value of forested wetlands. Results of robust, generalized moments estimation of a double logarithmic first-order spatial autoregressive error model (inverse distance weights with spatial dependence up to 1500m) indicate that the implicit cost of damages to forested wetlands caused by channelization equaled -$5,438 ha-1. Collectively, the results of this dissertation provide economic measures of the damages to and benefits of environmental assets, help private landowners and policy makers identify the amenity attributes preferred by the public, and improve the management of natural resources.
NASA Technical Reports Server (NTRS)
1976-01-01
The feasibility of systematically quantifying the economic benefits of secondary applications of NASA related R and D was investigated. Based upon the tools of economic theory and econometric analysis, a set of empirical methods was developed and selected applications were made to demonstrate their workability. Analyses of the technological developments related to integrated circuits, cryogenic insulation, gas turbines, and computer programs for structural analysis indicated substantial secondary benefits accruing from NASA's R and D in these areas.
Quantifying the benefits to the national economy from secondary applications of NASA technology
NASA Technical Reports Server (NTRS)
1976-01-01
The feasibility of systematically quantifying the economic benefits of secondary applications of NASA related R and D is investigated. Based upon the tools of economic theory and econometric analysis, it develops a set of empirical methods and makes selected applications to demonstrate their workability. Analyses of the technological developments related to integrated circuits, cryogenic insulation, gas turbines, and computer programs for structural analysis indicated substantial secondary benefits accruing from NASA's R and D in these areas.
NASA Astrophysics Data System (ADS)
Gass, S. I.
1982-05-01
The theoretical and applied state of the art of oil and gas supply models was discussed. The following areas were addressed: the realities of oil and gas supply, prediction of oil and gas production, problems in oil and gas modeling, resource appraisal procedures, forecasting field size and production, investment and production strategies, estimating cost and production schedules for undiscovered fields, production regulations, resource data, sensitivity analysis of forecasts, econometric analysis of resource depletion, oil and gas finding rates, and various models of oil and gas supply.
ERIC Educational Resources Information Center
Aksoy, Tevfik; Link, Charles R.
2000-01-01
Uses panel estimation techniques to estimate econometric models of mathematics achievement determinants for a nationally representative sample of high-school students. Extra time spent on math homework increases test scores; an extra hour of TV viewing negatively affects scores. Longer math periods also help. (Contains 56 references.) (MLH)
ERIC Educational Resources Information Center
Kadane, Joseph B.; And Others
This paper offers a preliminary analysis of the effects of a semi-segregated school system on the IQ's of its students. The basic data consist of IQ scores for fourth, sixth, and eighth grades and associated environmental data obtained from their school records. A statistical model is developed to analyze longitudinal data when both process error…
Analytical Tools for Affordability Analysis
2015-04-30
flunk this basic test from their inception. —Honorable Ashton B. Carter (2010), Under Secretary of Defense for Acquisition, Technology, and Logistics... Testing , and Evaluation] funding has been lost to cancelled programs. (Decker & Wagner, 2011) The Army is scarcely unique in this regard. All... econometric model of how schedule affects cost should take advantage of these different cost categories and treat them separately when they are known
ERIC Educational Resources Information Center
Sulku, Seher Nur; Abdioglu, Zehra
2015-01-01
This study investigates the factors influencing the success of students in primary schools in Turkey. TIMSS 2011 data for Turkey, measuring the success of eighth-grade students in the field of mathematics, were used in an econometric analysis, performed using classical linear regression models. Two hundred thirty-nine schools participated in the…
1991-09-01
However, there is no guarantee that this would work; for instance if the data were generated by an ARCH model (Tong, 1990 pp. 116-117) then a simple...Hill, R., Griffiths, W., Lutkepohl, H., and Lee, T., Introduction to the Theory and Practice of Econometrics , 2th ed., Wiley, 1985. Kendall, M., Stuart
NASA Technical Reports Server (NTRS)
Brown, Molly E.; Tondel, Fabien; Essam, Timothy; Thorne, Jennifer A.; Mann, Bristol F.; Eilerts, Gary
2012-01-01
Monitoring and incorporating diverse market and staple food information into food price indices is critical for food price analyses. Satellite remote sensing data and earth science models have an important role to play in improving humanitarian aid timing, delivery and distribution. Incorporating environmental observations into econometric models will improve food security analysis and understanding of market functioning.
Linking land-use projections and forest fragmentation analysis.
Andrew J. Plantinga; Ralph J. Alig; Henry Eichman; David J. Lewis
2007-01-01
An econometric model of private land-use decisions is used to project land use to 2030 for each county in the continental United States. On a national scale, forest area is projected to increase overall between 0.1 and 0.2 percent per year between now and 2030. However, forest area is projected to decrease in a majority of regions, including the key forestry regions of...
ERIC Educational Resources Information Center
Ranieri, Antonio, Ed.
2013-01-01
This report provides an analysis of the labour market impacts of EU policy interventions designed to support the transition to a job-rich, low-carbon economy. The approach taken is innovative as it combines quantitative (econometric modelling) and qualitative (case study) methods to investigate the expected impact of sustainable energy policies on…
Econometric comparisons of liquid rocket engines for dual-fuel advanced earth-to-orbit shuttles
NASA Technical Reports Server (NTRS)
Martin, J. A.
1978-01-01
Econometric analyses of advanced Earth-to-orbit vehicles indicate that there are economic benefits from development of new vehicles beyond the space shuttle as traffic increases. Vehicle studies indicate the advantage of the dual-fuel propulsion in single-stage vehicles. This paper shows the economic effect of incorporating dual-fuel propulsion in advanced vehicles. Several dual-fuel propulsion systems are compared to a baseline hydrogen and oxygen system.
The Changing Balance: South and North Korean Capabilities for Long-Term Military Competition
1985-12-01
econometric model. Ideally, a model should be estimated over one period and then tested over a different period. If one esti- mates and tests over the...unprecedented impending shift of political leadership from Kim II-Sung to his son, Kim Chong-Il. Section III summarizes an aggregative econometric ...model of the South Korean economy, which we have developed to test the effect on that economy of alternative South Korean military force postures and
Evaluation to Redesign a Prototype Officer Data Base for Interdisciplinary Research
1992-01-01
accommodate cohort longitudinal research and econometric model testing . Recommendations regarding the adoption of the LOADB were presented. Utilization...commission data sets (Younkman, 1987), and the AIMS data set ( Ramsey & Younkman, 1989). An analysis of selected standardized tests for ROTC screening was...ARI Research Note 92-16 Evaluation to Redesign a Prototype il Officer Data Base for Interdisciplinary Research Dianne D. Younkman and Lori G. Ramsey
From deficit to surplus: An econometric analysis of US trade balance in forest products
Daowei Zhang; Ying Lin; Jeffrey P. Prestemon
2017-01-01
Although the US trade deficit has persisted since 1975, the country changed in 2009 from a net importer to a net exporter of forest products, emerging as the world's largest exporter of forest products. Drawing on recent data, we model the real dollar value of US exports, imports, and the trade balance in forest products to identify factors likely to explain this...
ERIC Educational Resources Information Center
Marston, Stephen Tilney
The study derives a model of the unemployment insurance (UI) system and its relationship to the labor market, estimates it with data from the Detroit Standard Metropolitan Statistical Area, and evaluates its potential use to forecast UI benefit amounts, UI insured unemployment, and UI exhaustions. It further uses the model to analyze policy issues…
1980-04-01
published in "The Soviet Union in the Third World: Success or Failure." ed. by Robert H. pp 258 Donaldson. Westejuw Press. Boulder Co.. Summer Mengel ...34 14 Navy Enlistinents." 34 pp.. Mar 1980 pp.. Non 1979 (Reprinted from Journal Chew. Istri. 70112), 15 Jun 1979). AD A076 287 PP 277 Mengel , Marc
Sabes-Figuera, Ramon; McCrone, Paul; Kendricks, Antony
2013-04-01
Economic evaluation analyses can be enhanced by employing regression methods, allowing for the identification of important sub-groups and to adjust for imperfect randomisation in clinical trials or to analyse non-randomised data. To explore the benefits of combining regression techniques and the standard Bayesian approach to refine cost-effectiveness analyses using data from randomised clinical trials. Data from a randomised trial of anti-depressant treatment were analysed and a regression model was used to explore the factors that have an impact on the net benefit (NB) statistic with the aim of using these findings to adjust the cost-effectiveness acceptability curves. Exploratory sub-samples' analyses were carried out to explore possible differences in cost-effectiveness. Results The analysis found that having suffered a previous similar depression is strongly correlated with a lower NB, independent of the outcome measure or follow-up point. In patients with previous similar depression, adding an selective serotonin reuptake inhibitors (SSRI) to supportive care for mild-to-moderate depression is probably cost-effective at the level used by the English National Institute for Health and Clinical Excellence to make recommendations. This analysis highlights the need for incorporation of econometric methods into cost-effectiveness analyses using the NB approach.
Allocation of Future Federal Airport and Airway Costs.
1986-12-01
attributable to users are allocated among them based upon Ramsey Pricing which minimizes the distortion in aviation markets resulting from the allocation of...the years following 1992, the producers price Uindex projections made by Wharton Econometric Forecasting . Associates1 were employed. This latter set...and on econometric cost estimation techniques. These are Volumes 3 and 5 respectively. 68 A(A A11 I FSZK7_ ODi Id Lin <j< .99 C-4 x\\ M LL- < P7 Pi0
Econometrics in outcomes research: the use of instrumental variables.
Newhouse, J P; McClellan, M
1998-01-01
We describe an econometric technique, instrumental variables, that can be useful in estimating the effectiveness of clinical treatments in situations when a controlled trial has not or cannot be done. This technique relies upon the existence of one or more variables that induce substantial variation in the treatment variable but have no direct effect on the outcome variable of interest. We illustrate the use of the technique with an application to aggressive treatment of acute myocardial infarction in the elderly.
Econometric model for age- and population-dependent radiation exposures
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sandquist, G.M.; Slaughter, D.M.; Rogers, V.C.
1991-01-01
The economic impact associated with ionizing radiation exposures in a given human population depends on numerous factors including the individual's mean economic status as a function age, the age distribution of the population, the future life expectancy at each age, and the latency period for the occurrence of radiation-induced health effects. A simple mathematical model has been developed that provides an analytical methodology for estimating the societal econometrics associated with radiation effects are to be assessed and compared for economic evaluation.
Forest management and economics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Buongiorno, J.; Gilless, J.K.
1987-01-01
This volume provides a survey of quantitative methods, guiding the reader through formulation and analysis of models that address forest management problems. The authors use simple mathematics, graphics, and short computer programs to explain each method. Emphasizing applications, they discuss linear, integer, dynamic, and goal programming; simulation; network modeling; and econometrics, as these relate to problems of determining economic harvest schedules in even-aged and uneven-aged forests, the evaluation of forest policies, multiple-objective decision making, and more.
An Econometric Analysis of the Effectiveness of Compensation to Retention
2009-03-01
increased significantly in recent years. A 2005 study estimated that 72 percent of enlisted members had one or more years of college education...DoD only uses basic pay in calculating the retirement annuity. The Office of the Actuary found that while a 20-year retiree may be entitled to 50...percent of RMC ( Actuary , 2007:10). The current retirement system available to eligible uniformed personnel is a defined benefit plan. Employee
U.S. COIN Doctrine: Betting the Future on a Too Distant Past
2012-05-17
authority. This conceptualization also draws on the Maoist model of insurgency reflecting the influence that 20th Century events have on current...doctrine. The model for legitimate government is a representative government, which Galula points out, is responsive to the needs of its people. JP 1-02... econometrics approach to address the COIN problem. Systems analysis implied that there were two competing systems, insurgency and COIN, with the
ERIC Educational Resources Information Center
General Accounting Office, Washington, DC.
To compile its projections of future employment levels, the Bureau of Labor Statistics (BLS) combines the following five interlinked models in a six-step process: a labor force model, an econometric model of the U.S. economy, an industry activity model, an industry labor demand model, and an occupational labor demand model. The BLS was asked to…
Understrength Air Force Officer Career Fields. A Force Management Approach
2005-01-01
LtCol John Crown (DPSA). In addition, we had very helpful interviews with Mr. Vaughan Blackstone (DPAPP) and Mr. Dennis Miller (DPPAO). Also at...econometric impact analysis that was used to determine an optimal bonus amount or target population prior to bonus implementation.15 The success of...problems in managing personnel assignments. First, there is a high " tax " for special-duty jobs that requires them to place personnel officers into
Testing simulation and structural models with applications to energy demand
NASA Astrophysics Data System (ADS)
Wolff, Hendrik
2007-12-01
This dissertation deals with energy demand and consists of two parts. Part one proposes a unified econometric framework for modeling energy demand and examples illustrate the benefits of the technique by estimating the elasticity of substitution between energy and capital. Part two assesses the energy conservation policy of Daylight Saving Time and empirically tests the performance of electricity simulation. In particular, the chapter "Imposing Monotonicity and Curvature on Flexible Functional Forms" proposes an estimator for inference using structural models derived from economic theory. This is motivated by the fact that in many areas of economic analysis theory restricts the shape as well as other characteristics of functions used to represent economic constructs. Specific contributions are (a) to increase the computational speed and tractability of imposing regularity conditions, (b) to provide regularity preserving point estimates, (c) to avoid biases existent in previous applications, and (d) to illustrate the benefits of our approach via numerical simulation results. The chapter "Can We Close the Gap between the Empirical Model and Economic Theory" discusses the more fundamental question of whether the imposition of a particular theory to a dataset is justified. I propose a hypothesis test to examine whether the estimated empirical model is consistent with the assumed economic theory. Although the proposed methodology could be applied to a wide set of economic models, this is particularly relevant for estimating policy parameters that affect energy markets. This is demonstrated by estimating the Slutsky matrix and the elasticity of substitution between energy and capital, which are crucial parameters used in computable general equilibrium models analyzing energy demand and the impacts of environmental regulations. Using the Berndt and Wood dataset, I find that capital and energy are complements and that the data are significantly consistent with duality theory. Both results would not necessarily be achieved using standard econometric methods. The final chapter "Daylight Time and Energy" uses a quasi-experiment to evaluate a popular energy conservation policy: we challenge the conventional wisdom that extending Daylight Saving Time (DST) reduces energy demand. Using detailed panel data on half-hourly electricity consumption, prices, and weather conditions from four Australian states we employ a novel 'triple-difference' technique to test the electricity-saving hypothesis. We show that the extension failed to reduce electricity demand and instead increased electricity prices. We also apply the most sophisticated electricity simulation model available in the literature to the Australian data. We find that prior simulation models significantly overstate electricity savings. Our results suggest that extending DST will fail as an instrument to save energy resources.
1981-09-17
leading life companies, 1979 69 i A A TABLES 16 A comparative example of the reserve test Calculation 76 17 Comparative income tax burden of life...pp. 159-61. 2/J. David Cummins, An Econometric Model of the Life Insurance Sector of the U.S. Economy (Lexington, Mass.: Lexington Books, 1975), p. 57...3/Cummins, Econometric Model, p. 44. 4/Fact Book 1979, p. 32. 23 decades earlier. 1/ This decline has been attributed to two sources. First, as
IWR-MAIN Water Use Forecasting System. Version 5.1. User’s Manual and System Description
1987-12-01
Crosschecks for Input Data 1-68 11-1 Organization of the IWR-MAIN System H-8 11-2 Example of Econometric Demand Model 11-9 11-3 Example of Unit Use Coefficient...Unaccounted (entry does not affect default Loss and free service calculations) Y Conservation Data City Name: Test City USA Fl-Hetp, F2-return to monu, F4...socioeconomic data. 1-11 (1) Internal Growth Models The IWR-MAIN program contains a subroutine called GROWTH which uses econometric growth models based on
Robust Bounded Influence Tests in Linear Models
1988-11-01
sensitivity analysis and bounded influence estimation. In: Evaluation of Econometric Models, J. Kmenta and J.B. Ramsey (eds.) Academic Press, New York...1R’OBUST bOUNDED INFLUENCE TESTS IN LINEA’ MODELS and( I’homas P. [lettmansperger* Tim [PennsylvanLa State UJniversity A M i0d fix pu111 rsos.p JJ 1 0...November 1988 ROBUST BOUNDED INFLUENCE TESTS IN LINEAR MODELS Marianthi Markatou The University of Iowa and Thomas P. Hettmansperger* The Pennsylvania
Estimating the Standard Error of Robust Regression Estimates.
1987-03-01
error is 0(n4/5). In another Monte Carlo study, McKean and Schrader (1984) found that the tests resulting from studentizing ; by _3d/1/2 with d =0(n4 /5...44 4 -:~~-~*v: -. *;~ ~ ~*t .~ # ~ 44 % * ~ .%j % % % * . ., ~ -%. -14- Sheather, S. J. and McKean, J. W. (1987). A comparison of testing and...Wiley, New York. Welsch, R. E. (1980). Regression Sensitivity Analysis and Bounded- Influence Estimation, in Evaluation of Econometric Models eds. J
1982-06-09
32 V. An Econometric Model of Retention 71 Bibliography 166 Appendix A Appendix B Volume II Appendix C Appendix D Appendix E Volume III Appendix F...RETENTION OF ENLISTED PE.(U R O0URC RE SE ARCH CORP NH L LEG E ST AIT ION TO 09 jN 82 F4698 _H 8 -0063 NCASFEEEFhEE 5/9 hE EhsohEohmhhhhEE
1974-10-01
FIRST-TERM VOLUNTEER ENLISTMENTS WITH RESPECT TO UNEMPLOY - MENT RATES AND RECRUITING STRENGTH 3 Introduction 3 Findings of Previous Studies 4...variation in the dependent variable (volunteers per QMA) is not explained by the variation in the independent variables (relative wages, unemploy ...variable and one equation with an unemploy - ment variable. He found that the pay elasticity decreased from 1.77 to 1.01 with the addition of the
Statistical and Economic Techniques for Site-specific Nematode Management.
Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L
2014-03-01
Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.
Measuring the costs and benefits of conservation programs
DOE Office of Scientific and Technical Information (OSTI.GOV)
Einhorn, M.A.
1985-07-25
A step-by-step analysis of the effects of utility-sponsored conservation promoting programs begins by identifying several factors which will reduce a program's effectiveness. The framework for measuring cost savings and designing a conservation program needs to consider the size of appliance subsidies, what form incentives should take, and how will customer behavior change as a result of incentives. Continual reevaluation is necessary to determine whether to change the size of rebates or whether to continue the program. Analytical tools for making these determinations are improving as conceptual breakthroughs in econometrics permit more rigorous analysis. 5 figures.
Nitrogen Oxide Emission, Economic Growth and Urbanization in China: a Spatial Econometric Analysis
NASA Astrophysics Data System (ADS)
Zhou, Zhimin; Zhou, Yanli; Ge, Xiangyu
2018-01-01
This research studies the nexus of nitrogen oxide emissions and economic development/urbanization. Under the environmental Kuznets curve (EKC) hypothesis, we apply the analysis technique of spatial panel data in the STIRPAT framework, and thus obtain the estimated impacts of income/urbanization on nitrogen oxide emission systematically. The empirical findings suggest that spatial dependence on nitrogen oxide emission distribution exist at provincial level, and the inverse N-shape EKC describes both income-nitrogen oxide and urbanization-nitrogen oxide nexuses. In addition, some well-directed policy advices are made to reduce the nitrogen oxide emission in future.
NASA Astrophysics Data System (ADS)
Travaglini, Guido
2015-09-01
Solar activity, as measured by the yearly revisited time series of sunspot numbers (SSN) for the period 1700-2014 (Clette et al., 2014), undergoes in this paper a triple statistical and econometric checkup. The conclusions are that the SSN sequence: (1) is best modeled as a signal that features nonlinearity in mean and variance, long memory, mean reversion, 'threshold' symmetry, and stationarity; (2) is best described as a discrete damped harmonic oscillator which linearly approximates the flux-transport dynamo model; (3) its prediction well into the 22nd century testifies of a substantial fall of the SSN centered around the year 2030. In addition, the first and last Gleissberg cycles show almost the same peak number and height during the period considered, yet the former slightly prevails when measured by means of the estimated smoother. All of these conclusions are achieved by making use of modern tools developed in the field of Financial Econometrics and of two new proposed procedures for signal smoothing and prediction.
Kaliakatsou, Evridiki; Bell, J Nigel B; Thirtle, Colin; Rose, Daniel; Power, Sally A
2010-05-01
Numerous experiments have demonstrated reductions in the yields of cereal crops due to tropospheric O(3), with losses of up to 25%. However, the only British econometric study on O(3) impacts on winter wheat yields, found that a 10% increase in AOT40 would decrease yields by only 0.23%. An attempt is made here to reconcile these observations by developing AOT40 maps for Great Britain and matching levels with a large number of standardised trial plot wheat yields from many sites over a 13-year period. Panel estimates (repeated measures on the same plots with time) show a 0.54% decrease in yields and it is hypothesised that plant breeders may have inadvertently selected for O(3) tolerance in wheat. Some support for this is provided by fumigations of cultivars of differing introduction dates. A case is made for the use of econometric as well as experimental studies in prediction of air pollution induced crop loss. Copyright 2009 Elsevier Ltd. All rights reserved.
Family planning choice behaviour in urban slums of Bangladesh: an econometric approach.
Barkat, A; Rahman, M U; Bose, M L
1997-03-01
Bangladesh's urban population is projected to account for 26% of the country's total population by the year 2000 and 37% by 2015. A 1991 Bangladesh census report found that about 21 million of the total 111.5 million population were living in urban areas. 1551 currently-married women of reproductive age in 1551 households sampled from a representative sample of 91 slums in the metropolitan areas of Dhaka, Chittagong, and Khulna participated in a study of family planning behavior choice. 673 of the women were practicing family planning. The authors describe the construction of the econometric model used for analysis. Economic status as indicated by household income was found to considerably influence people's decisions concerning family planning practices. Higher women's educational status is also positively correlated with family planning practice. Husband's educational status has a less significant effect upon family planning practice. The change of a person from non-Muslim to Muslim has an insignificant, though positive, impact upon family planning practice. The more a woman feels empowered, being over age 19 years, the greater the number of living children, and the lower the level of preference for sons, the more likely a woman is to practice family planning.
Measuring Efficiency of Secondary Healthcare Providers in Slovenia
Blatnik, Patricia; Bojnec, Štefan; Tušak, Matej
2017-01-01
Abstract The chief aim of this study was to analyze secondary healthcare providers' efficiency, focusing on the efficiency analysis of Slovene general hospitals. We intended to present a complete picture of technical, allocative, and cost or economic efficiency of general hospitals. Methods We researched the aspects of efficiency with two econometric methods. First, we calculated the necessary quotients of efficiency with the stochastic frontier analyze (SFA), which are realized by econometric evaluation of stochastic frontier functions; then, with the data envelopment analyze (DEA), we calculated the necessary quotients that are based on the linear programming method. Results Results on measures of efficiency showed that the two chosen methods produced two different conclusions. The SFA method concluded Celje General Hospital is the most efficient general hospital, whereas the DEA method concluded Brežice General Hospital was the hospital to be declared as the most efficient hospital. Conclusion Our results are a useful tool that can aid managers, payers, and designers of healthcare policy to better understand how general hospitals operate. The participants can accordingly decide with less difficulty on any further business operations of general hospitals, having the best practices of general hospitals at their disposal. PMID:28730180
Redshaw, Sarah; Ingham, Valerie; McCutcheon, Marion; Hicks, John; Burmeister, Oliver
2018-02-01
To assess the impact of network communications, community participation and elements of vulnerability on the perception of social cohesiveness in the Blue Mountains local government area (Blue Mountains LGA). A questionnaire was administered to residents of the Blue Mountains LGA. Econometric analysis of the resulting data was undertaken. Blue Mountains LGA, Australia. One thousand one hundred and three residents of the Blue Mountains LGA responded to the questionnaire. The responses enabled the construction of variables measuring individual perceptions of community cohesiveness, their network communications and community participation. Demographic data and data on the vulnerabilities of individuals were also collected. The data were used in an econometric model which identified that network communications and community participation impacted positively on perceptions of social cohesiveness while vulnerability factors had a negative impact. Remedial action to build community cohesiveness and network communications can be expected to have a positive impact on social cohesiveness. In developing strategies to build community cohesiveness and network communication, particular care needs to be taken to ensure the inclusion of those members of society who are regarded as the most vulnerable. © 2017 National Rural Health Alliance Inc.
NASA Astrophysics Data System (ADS)
Ausloos, Marcel; Nedic, Olgica; Dekanski, Aleksandar; Mrowinski, Maciej J.; Fronczak, Piotr; Fronczak, Agata
2017-02-01
This paper aims at providing a statistical model for the preferred behavior of authors submitting a paper to a scientific journal. The electronic submission of (about 600) papers to the Journal of the Serbian Chemical Society has been recorded for every day from Jan. 01, 2013 till Dec. 31, 2014, together with the acceptance or rejection paper fate. Seasonal effects and editor roles (through desk rejection and subfield editors) are examined. An ARCH-like econometric model is derived stressing the main determinants of the favorite day-of-week process.
The Science of Science Policy: A Federal Research Roadmap
2008-11-01
and Atmospheric Administra on, h p://www.ncdc.noaa.gov/ oa /climate/globalwarming.html#q4. T S S P : A F R R4 maintain the na on’s dominance...econometric studies, surveys, case studies, and retrospec ve analyses. Econometric studies include the macroeconomic growth models pioneered by Robert...R A W ha t a re th e be ha vi or al fo un da o ns o f i nn ov a- o n? U nd er st an di ng th e be ha vi or o f i nd iv id ua ls an d
Energy modeling. Volume 2: Inventory and details of state energy models
NASA Astrophysics Data System (ADS)
Melcher, A. G.; Underwood, R. G.; Weber, J. C.; Gist, R. L.; Holman, R. P.; Donald, D. W.
1981-05-01
An inventory of energy models developed by or for state governments is presented, and certain models are discussed in depth. These models address a variety of purposes such as: supply or demand of energy or of certain types of energy; emergency management of energy; and energy economics. Ten models are described. The purpose, use, and history of the model is discussed, and information is given on the outputs, inputs, and mathematical structure of the model. The models include five models dealing with energy demand, one of which is econometric and four of which are econometric-engineering end-use models.
An Analysis of Selectivity Bias in the Medicare AAPCC
Dowd, Bryan; Feldman, Roger; Moscovice, Ira; Wisner, Catherine; Bland, Pat; Finch, Mike
1996-01-01
Using econometric models of endogenous sample selection, we examine possible payment bias to Medicare Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA)-risk health maintenance organizations (HMOs) in the Twin Cities in 1988. We do not find statistically significant evidence of favorable HMO selection. In fact, the sign of the selection term indicates adverse selection into HMOs. This finding is interesting, in view of the fact that three of the five risk HMOs in the study have since converted to non-risk contracts. PMID:10158735
Cost Growth in Weapons Systems: Re-examining Rubber Baselines and Economic Factors
2007-03-01
committee members for their support in this endeavor. They allowed me to test my econometric limits without performing the analysis for me. I...Bruesch-Pagan Het Test Ramsey Omitted Variable Test 6 The adjusted r-squared value indicates that this model explains nearly 16% of the factors...Observations 1150 Chi2(1) 69.01 P(Chi) 0.0000 F(3, 1139) 7.22 P(F) 0.0001 Bruesch-Pagan Het Test Ramsey Omitted Variable Test The results of these two
Stochastic Calculus and Differential Equations for Physics and Finance
NASA Astrophysics Data System (ADS)
McCauley, Joseph L.
2013-02-01
1. Random variables and probability distributions; 2. Martingales, Markov, and nonstationarity; 3. Stochastic calculus; 4. Ito processes and Fokker-Planck equations; 5. Selfsimilar Ito processes; 6. Fractional Brownian motion; 7. Kolmogorov's PDEs and Chapman-Kolmogorov; 8. Non Markov Ito processes; 9. Black-Scholes, martingales, and Feynman-Katz; 10. Stochastic calculus with martingales; 11. Statistical physics and finance, a brief history of both; 12. Introduction to new financial economics; 13. Statistical ensembles and time series analysis; 14. Econometrics; 15. Semimartingales; References; Index.
The stability of coupled renewal-differential equations with econometric applications
NASA Technical Reports Server (NTRS)
Rhoten, R. P.; Aggarwal, J. K.
1969-01-01
Concepts and results are presented in the fields of mathematical modeling, economics, and stability analysis. A coupled renewal-differential equation structure is presented as a modeling form for systems possessing hereditary characteristics, and this structure is applied to a model of the Austrian theory of business cycles. For realistic conditions, the system is shown to have an infinite number of poles, and conditions are presented which are both necessary and sufficient for all poles to lie strictly in the left half plane.
Biggeri, M; Nannini, M; Putoto, G
2018-03-01
Community health insurance (CHI) aims to provide financial protection and facilitate health care access among poor rural populations. Given common operational challenges that hamper the full development of the scheme, there is need to undertake systematic feasibility studies. These are scarce in the literature and usually they do not provide a comprehensive analysis of the local context. The present research intends to adopt a mixed-methods approach to assess ex-ante the feasibility of CHI. In particular, eight preconditions are proposed to inform the viability of introducing the micro insurance. A case study located in rural northern Uganda is presented to test the effectiveness of the mixed-methods procedure for the feasibility purpose. A household survey covering 180 households, 8 structured focus group discussions, and 40 key informant interviews were performed between October and December 2016 in order to provide a complete and integrated analysis of the feasibility preconditions. Through the data collected at the household level, the population health seeking behaviours and the potential insurance design were examined; econometric analyses were carried out to investigate the perception of health as a priority need and the willingness to pay for the scheme. The latter component, in particular, was analysed through a contingent valuation method. The results validated the relevant feasibility preconditions. Econometric estimates demonstrated that awareness of catastrophic health expenditures and the distance to the hospital play a critical influence on household priorities and willingness to pay. Willingness is also significantly affected by socio-economic status and basic knowledge of insurance principles. Overall, the mixed-methods investigation showed that a comprehensive feasibility analysis can shape a viable CHI model to be implemented in the local context. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Wen, Shaobo; An, Haizhong; Chen, Zhihua; Liu, Xueyong
2017-08-01
In traditional econometrics, a time series must be in a stationary sequence. However, it usually shows time-varying fluctuations, and it remains a challenge to execute a multiscale analysis of the data and discover the topological characteristics of conduction in different scales. Wavelet analysis and complex networks in physical statistics have special advantages in solving these problems. We select the exchange rate variable from the Chinese market and the commodity price index variable from the world market as the time series of our study. We explore the driving factors behind the behavior of the two markets and their topological characteristics in three steps. First, we use the Kalman filter to find the optimal estimation of the relationship between the two markets. Second, wavelet analysis is used to extract the scales of the relationship that are driven by different frequency wavelets. Meanwhile, we search for the actual economic variables corresponding to different frequency wavelets. Finally, a complex network is used to search for the transfer characteristics of the combination of states driven by different frequency wavelets. The results show that statistical physics have a unique advantage over traditional econometrics. The Chinese market has time-varying impacts on the world market: it has greater influence when the world economy is stable and less influence in times of turmoil. The process of forming the state combination is random. Transitions between state combinations have a clustering feature. Based on these characteristics, we can effectively reduce the information burden on investors and correctly respond to the government's policy mix.
Investigation on Law and Economics Based on Complex Network and Time Series Analysis.
Yang, Jian; Qu, Zhao; Chang, Hui
2015-01-01
The research focuses on the cooperative relationship and the strategy tendency among three mutually interactive parties in financing: small enterprises, commercial banks and micro-credit companies. Complex network theory and time series analysis were applied to figure out the quantitative evidence. Moreover, this paper built up a fundamental model describing the particular interaction among them through evolutionary game. Combining the results of data analysis and current situation, it is justifiable to put forward reasonable legislative recommendations for regulations on lending activities among small enterprises, commercial banks and micro-credit companies. The approach in this research provides a framework for constructing mathematical models and applying econometrics and evolutionary game in the issue of corporation financing.
Entropy Econometrics for combining regional economic forecasts: A Data-Weighted Prior Estimator
NASA Astrophysics Data System (ADS)
Fernández-Vázquez, Esteban; Moreno, Blanca
2017-10-01
Forecast combination has been studied in econometrics for a long time, and the literature has shown the superior performance of forecast combination over individual predictions. However, there is still controversy on which is the best procedure to specify the forecast weights. This paper explores the possibility of using a procedure based on Entropy Econometrics, which allows setting the weights for the individual forecasts as a mixture of different alternatives. In particular, we examine the ability of the Data-Weighted Prior Estimator proposed by Golan (J Econom 101(1):165-193, 2001) to combine forecasting models in a context of small sample sizes, a relative common scenario when dealing with time series for regional economies. We test the validity of the proposed approach using a simulation exercise and a real-world example that aims at predicting gross regional product growth rates for a regional economy. The forecasting performance of the Data-Weighted Prior Estimator proposed is compared with other combining methods. The simulation results indicate that in scenarios of heavily ill-conditioned datasets the approach suggested dominates other forecast combination strategies. The empirical results are consistent with the conclusions found in the numerical experiment.
Ratio-based estimators for a change point in persistence.
Halunga, Andreea G; Osborn, Denise R
2012-11-01
We study estimation of the date of change in persistence, from [Formula: see text] to [Formula: see text] or vice versa. Contrary to statements in the original papers, our analytical results establish that the ratio-based break point estimators of Kim [Kim, J.Y., 2000. Detection of change in persistence of a linear time series. Journal of Econometrics 95, 97-116], Kim et al. [Kim, J.Y., Belaire-Franch, J., Badillo Amador, R., 2002. Corringendum to "Detection of change in persistence of a linear time series". Journal of Econometrics 109, 389-392] and Busetti and Taylor [Busetti, F., Taylor, A.M.R., 2004. Tests of stationarity against a change in persistence. Journal of Econometrics 123, 33-66] are inconsistent when a mean (or other deterministic component) is estimated for the process. In such cases, the estimators converge to random variables with upper bound given by the true break date when persistence changes from [Formula: see text] to [Formula: see text]. A Monte Carlo study confirms the large sample downward bias and also finds substantial biases in moderate sized samples, partly due to properties at the end points of the search interval.
Spatial data analytics on heterogeneous multi- and many-core parallel architectures using python
Laura, Jason R.; Rey, Sergio J.
2017-01-01
Parallel vector spatial analysis concerns the application of parallel computational methods to facilitate vector-based spatial analysis. The history of parallel computation in spatial analysis is reviewed, and this work is placed into the broader context of high-performance computing (HPC) and parallelization research. The rise of cyber infrastructure and its manifestation in spatial analysis as CyberGIScience is seen as a main driver of renewed interest in parallel computation in the spatial sciences. Key problems in spatial analysis that have been the focus of parallel computing are covered. Chief among these are spatial optimization problems, computational geometric problems including polygonization and spatial contiguity detection, the use of Monte Carlo Markov chain simulation in spatial statistics, and parallel implementations of spatial econometric methods. Future directions for research on parallelization in computational spatial analysis are outlined.
[Demand for cigarettes and tax increases in El Salvador].
Ramos-Carbajales, Alejandro; González-Rozada, Martín; Vallarino, Hugo
2016-10-01
Analyze short- and long-term elasticities of demand for cigarettes in El Salvador as a tool for supporting recommendations on tax increases to reduce prevalence and consumption through price increases. Demand for cigarettes in El Salvador was analyzed through an econometric time-series model using a database from El Salvador's General Directorate of Internal Taxes (DGII) and the General Directorate of Statistics and Census (DIGESTYC). The analysis period was quarterly: 2000Q1-2012Q4. The usual tests were done to prevent a spurious econometric estimation. It was found that the variables volume sales, actual sale prices, and actual per capita income exhibited first-order cointegration; this result makes it possible to use an error correction model with short- and long-term elasticity estimates. Only long-term elasticities were found to be statistically significant to 5%. Results show long-term price elasticity (5 quarters) of -0.9287 and income price elasticity of 0.9978. Absolute price elasticity is somewhat high, although it is within the levels estimated in other studies in low per-capita income countries. A tax increase from a base amount of US$1.04 per pack of 20 cigarettes to US$1.66 within three years would reduce demand by 20% to 31% and would increase tax revenues by 9% to 22%.
Market for ethanol feed joint products
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hertzmark, D.; Gould, B.
1979-10-01
This report presents results of econometric estimations and mathematical simulations of markets for joint feed products of motor ethanol. The major issues considered are the nature of current market price relationships, effects on prices, including feed substitutes prices, and effects of demands for increased use of distillers' grains and gluten meal. The econometric section shows that soybean meal was by far the dominant force in the pricing of the two products. However, neither one could be adequately explained without the inclusion of corn in the estimating equations. Later research shows that this was due to the importance of both feedsmore » for metabolizable energy as well as for protein in livestock diets. Current ration formulations would require some discounting of the value of the protein content of the two feeds. Careful siting of the ethanol facilities, and flexible design of the plants so that a maximum number of products may be extracted from the feedstock, seem necessary. Finally, the analysis indicates that substitution in animal diets of these joint products for the corn or milo used originally requires that additional energy be supplied to the animal by some type of forage crop. This implies that additional land may be required for energy production, for such marginal crops as hay and alfalfa, rather than for row crops.« less
Knapp, Sabine; Kumar, Shashi; Sakurada, Yuri; Shen, Jiajun
2011-05-01
This study uses econometric models to measure the effect of significant wave height and wind strength on the probability of casualty and tests whether these effects changed. While both effects are in particular relevant for stability and strength calculations of vessels, it is also helpful for the development of ship construction standards in general to counteract increased risk resulting from changing oceanographic conditions. The authors analyzed a unique dataset of 3.2 million observations from 20,729 individual vessels in the North Atlantic and Arctic regions gathered during the period 1979-2007. The results show that although there is a seasonal pattern in the probability of casualty especially during the winter months, the effect of wind strength and significant wave height do not follow the same seasonal pattern. Additionally, over time, significant wave height shows an increasing effect in January, March, May and October while wind strength shows a decreasing effect, especially in January, March and May. The models can be used to simulate relationships and help understand the relationships. This is of particular interest to naval architects and ship designers as well as multilateral agencies such as the International Maritime Organization (IMO) that establish global standards in ship design and construction. Copyright © 2011 Elsevier Ltd. All rights reserved.
2013-01-01
Economic evaluation in modern health care systems is seen as a transparent scientific framework that can be used to advance progress towards improvements in population health at the best possible value. Despite the perceived superiority that trial-based studies have in terms of internal validity, economic evaluations often employ observational data. In this review, the interface between econometrics and economic evaluation is explored, with emphasis placed on highlighting methodological issues relating to the evaluation of cost-effectiveness within a bivariate framework. Studies that satisfied the eligibility criteria exemplified the use of matching, regression analysis, propensity scores, instrumental variables, as well as difference-in-differences approaches. All studies were reviewed and critically appraised using a structured template. The findings suggest that although state-of-the-art econometric methods have the potential to provide evidence on the causal effects of clinical and policy interventions, their application in economic evaluation is subject to a number of limitations. These range from no credible assessment of key assumptions and scarce evidence regarding the relative performance of different methods, to lack of reporting of important study elements, such as a summary outcome measure and its associated sampling uncertainty. Further research is required to better understand the ways in which observational data should be analysed in the context of the economic evaluation framework. PMID:24229445
Existing agricultural ecosystem in China leads to environmental pollution: an econometric approach.
Hongdou, Lei; Shiping, Li; Hao, Li
2018-06-17
Sustainable agriculture ensures food security and prevents starvation. However, the need to meet the increasing food demands of the growing population has led to poor and unsustainable agricultural practices, which promote environmental degradation. Given the contributions of agricultural ecosystems to environmental pollution, we investigated the impact of the agricultural ecosystem on environmental pollution in China using time series data from 1960 to 2014. We employed several methods for econometric analysis including the unit root test, Johansen test of cointegration, Granger causality test, and vector error correction model. Evidence based on the long-run elasticity indicates that a 1% increase in the emissions of carbon dioxide (CO 2 ) equivalent to nitrous oxide from synthetic fertilizers will increase the emissions of CO 2 by 1.52% in the long run. Similarly, a 1% increase in the area of harvested rice paddy, cereal production, biomass of burned crop residues, and agricultural GDP will increase the carbon dioxide emissions by 0.85, 0.63, 0.37, and 0.22%, respectively. The estimated results indicate that there are long-term equilibrium relationships among the selected variables considered for the agricultural ecosystem and carbon dioxide emissions. In particular, we identified bidirectional causal associations between CO 2 emissions, biomass of burned crop residues, and cereal production. Graphical abstract ᅟ.
2016-01-01
Background Many markets have traditionally been dominated by a few best-selling products, and this is also the case for the health care industry. However, we do not know whether the market will be more or less concentrated when health care services are delivered online (known as E-consultation), nor do we know how to reduce the concentration of the E-consultation market. Objective The aim of this study was to investigate the concentration of the E-consultation market and how to reduce its concentration through information disclosure mechanisms (online reputation and self-representation). Methods We employed a secondary data econometric analysis using transaction data obtained from an E-consultation Website (haodf.com) for three diseases (infantile pneumonia, diabetes, and pancreatic cancer) from 2008 to 2015. We included 2439 doctors in the analysis. Results The E-consultation market largely follows the 20/80 principle, namely that approximately 80% of orders are fulfilled by nearly 20% of doctors. This is much higher than the offline health care market. Meanwhile, the market served by doctors with strong online reputations (beta=0.207, P<.001) or strong online self-representation (beta=0.386, P<.001) is less concentrated. Conclusions When health care services are delivered online, the market will be more concentrated (known as the “Superstar” effect), indicating poor service efficiency for society as a whole. To reduce market concentration, E-consultation websites should provide important design elements such as ratings of doctors (user feedback), articles contributed by doctors, and free consultation services (online representation). A possible and important way to reduce the market concentration of the E-consultation market is to accumulate enough highly rated or highly self-represented doctors. PMID:27793793
Self-insurance and worksite alcohol programs: an econometric analysis.
Kenkel, D S
1997-03-01
The worksite is an important point of access for alcohol treatment and prevention, but not all firms are likely to find offering alcohol programs profitable. This study attempts to identify at a conceptual and empirical level factors that are important determinants of the profitability of worksite alcohol programs. A central question considered in the empirical analysis is whether firms' decisions about worksite alcohol programs are related to how employee group health insurance is provided. The data used are from the 1992 National Survey of Worksite Health Promotion Activities (N = 1,389-1,412). The econometric analysis focuses on measures of whether the surveyed firms offer Employee Assistance Programs (EAPs), individual counseling, group classes and resource materials regarding alcohol and other substance abuse. Holding other factors constant, the probability that a self-insured firm offers an EAP is estimated to be 59%, compared to 51% for a firm that purchases market group health insurance for its employees. Unionized worksites and larger worksites are also found to be more likely to offer worksite alcohol programs, compared to nonunionized smaller worksites. Worksites with younger work-forces are less likely than those with older employees to offer alcohol programs. The empirical results are consistent with the conceptual framework from labor economics, since self-insurance is expected to increase firms' demand for worksite alcohol programs while large worksite is expected to reduce the average program cost. The role of union status and workforce age suggests it is important to consider workers' preferences for the programs as fringe benefits. The results also suggest that the national trend towards self-insurance may be leading to more prevention and treatment of worker alcohol-related problems.
Investigation on Law and Economics Based on Complex Network and Time Series Analysis
Yang, Jian; Qu, Zhao; Chang, Hui
2015-01-01
The research focuses on the cooperative relationship and the strategy tendency among three mutually interactive parties in financing: small enterprises, commercial banks and micro-credit companies. Complex network theory and time series analysis were applied to figure out the quantitative evidence. Moreover, this paper built up a fundamental model describing the particular interaction among them through evolutionary game. Combining the results of data analysis and current situation, it is justifiable to put forward reasonable legislative recommendations for regulations on lending activities among small enterprises, commercial banks and micro-credit companies. The approach in this research provides a framework for constructing mathematical models and applying econometrics and evolutionary game in the issue of corporation financing. PMID:26076460
An evaluation of dynamic mutuality measurements and methods in cyclic time series
NASA Astrophysics Data System (ADS)
Xia, Xiaohua; Huang, Guitian; Duan, Na
2010-12-01
Several measurements and techniques have been developed to detect dynamic mutuality and synchronicity of time series in econometrics. This study aims to compare the performances of five methods, i.e., linear regression, dynamic correlation, Markov switching models, concordance index and recurrence quantification analysis, through numerical simulations. We evaluate the abilities of these methods to capture structure changing and cyclicity in time series and the findings of this paper would offer guidance to both academic and empirical researchers. Illustration examples are also provided to demonstrate the subtle differences of these techniques.
NASA Technical Reports Server (NTRS)
1974-01-01
An econometric investigation into the markets for agricultural commodities is summarized. An overview of the effort including the objectives, scope, and architecture of the analysis and the estimation strategy employed is presented. The major empirical results and policy conclusions are set forth. These results and conclusions focus on the economic importance of improved crop forecasts, U.S. exports, and government policy operations. A number of promising avenues of further investigation are suggested.
Raising household saving: does financial education work?
Gale, William G; Harris, Benjamin H; Levine, Ruth
2012-01-01
This article highlights the prevalence and economic outcomes of financial illiteracy among American households, and reviews previous research that examines how improving financial literacy affects household saving. Analysis of the research literature suggests that previous financial literacy efforts have yielded mixed results. Evidence suggests that interventions provided for employees in the workplace have helped increase household saving, but estimates of the magnitude of the impact vary widely. For financial education initiatives targeted to other groups, the evidence is much more ambiguous, suggesting a need for more econometrically rigorous evaluations.
The effect of relationship status on health with dynamic health and persistent relationships.
Kohn, Jennifer L; Averett, Susan L
2014-07-01
The dynamic evolution of health and persistent relationship status pose econometric challenges to disentangling the causal effect of relationships on health from the selection effect of health on relationship choice. Using a new econometric strategy we find that marriage is not universally better for health. Rather, cohabitation benefits the health of men and women over 45, being never married is no worse for health, and only divorce marginally harms the health of younger men. We find strong evidence that unobservable health-related factors can confound estimates. Our method can be applied to other research questions with dynamic dependent and multivariate endogenous variables. Copyright © 2014 Elsevier B.V. All rights reserved.
Clement, Matthieu; Meunie, Andre
2010-01-01
The object of this article is to examine the relation between social inequalities and pollution. First of all we provide a survey demonstrating that, from a theoretical point of view, a decrease in inequality has an uncertain impact on the environment. Second, on the basis of these conceptual considerations, we propose an econometric analysis based on panel data (fixed-effects and dynamic panel data models) concerning developing and transition countries for the 1988-2003 period. We examine specifically the effect of inequality on the extent of local pollution (sulphur dioxide emissions and organic water pollution) by integrating the Gini index into the formulation of the environmental Kuznets' curve.
Municipal water consumption forecast accuracy
NASA Astrophysics Data System (ADS)
Fullerton, Thomas M.; Molina, Angel L.
2010-06-01
Municipal water consumption planning is an active area of research because of infrastructure construction and maintenance costs, supply constraints, and water quality assurance. In spite of that, relatively few water forecast accuracy assessments have been completed to date, although some internal documentation may exist as part of the proprietary "grey literature." This study utilizes a data set of previously published municipal consumption forecasts to partially fill that gap in the empirical water economics literature. Previously published municipal water econometric forecasts for three public utilities are examined for predictive accuracy against two random walk benchmarks commonly used in regional analyses. Descriptive metrics used to quantify forecast accuracy include root-mean-square error and Theil inequality statistics. Formal statistical assessments are completed using four-pronged error differential regression F tests. Similar to studies for other metropolitan econometric forecasts in areas with similar demographic and labor market characteristics, model predictive performances for the municipal water aggregates in this effort are mixed for each of the municipalities included in the sample. Given the competitiveness of the benchmarks, analysts should employ care when utilizing econometric forecasts of municipal water consumption for planning purposes, comparing them to recent historical observations and trends to insure reliability. Comparative results using data from other markets, including regions facing differing labor and demographic conditions, would also be helpful.
Modeling of gold production in Malaysia
NASA Astrophysics Data System (ADS)
Muda, Nora; Ainuddeen, Nasihah Rasyiqah; Ismail, Hamizun; Umor, Mohd Rozi
2013-04-01
This study was conducted to identify the main factors that contribute to the gold production and hence determine the factors that affect to the development of the mining industry in Malaysia. An econometric approach was used by performing the cointegration analysis among the factors to determine the existence of long term relationship between the gold prices, the number of gold mines, the number of workers in gold mines and the gold production. The study continued with the Granger analysis to determine the relationship between factors and gold production. Results have found that there are long term relationship between price, gold production and number of employees. Granger causality analysis shows that there is only one way relationship between the number of employees with gold production in Malaysia and the number of gold mines in Malaysia.
A κ-generalized statistical mechanics approach to income analysis
NASA Astrophysics Data System (ADS)
Clementi, F.; Gallegati, M.; Kaniadakis, G.
2009-02-01
This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low-middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful.
Residential demand for energy. Volume 1: Residential energy demand in the US
NASA Astrophysics Data System (ADS)
Taylor, L. D.; Blattenberger, G. R.; Rennhack, R. K.
1982-04-01
Updated and improved versions of the residential energy demand models that are currently used in EPRI's Demand 80/81 Model are presented. The primary objective of the study is the development and estimation of econometric demand models that take into account in a theoretically appropriate way the problems caused by decreasing-block pricing in the sale of electricity and natural gas. An ancillary objective is to take into account the impact on electricity, natural gas, and fuel oil demands of differences and changes in the availability of natural gas. Econometric models of residential demand are estimated for all three fuel tyes using time series data by state. Price and income elasticities for a number of alternative models are presented.
Economics of technological change - A joint model for the aircraft and airline industries
NASA Technical Reports Server (NTRS)
Kneafsey, J. T.; Taneja, N. K.
1981-01-01
The principal focus of this econometric model is on the process of technological change in the U.S. aircraft manufacturing and airline industries. The problem of predicting the rate of introduction of current technology aircraft into an airline's fleet during the period of research, development, and construction for new technology aircraft arises in planning aeronautical research investments. The approach in this model is a statistical one. It attempts to identify major factors that influence transport aircraft manufacturers and airlines, and to correlate them with the patterns of delivery of new aircraft to the domestic trunk carriers. The functional form of the model has been derived from several earlier econometric models on the economics of innovation, acquisition, and technological change.
Econometrics and data of the 9 sector Dynamic General Equilibrium Model. Volume III. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berndt, E.R.; Fraumeni, B.M.; Hudson, E.A.
1981-03-01
This report presents the econometrics and data of the 9 sector Dynamic General Equilibrium Model. There are two key components of 9DGEM - the model of household behavior and the model of produconcrneer behavior. The household model is concerned with decisions on consumption, saving, labor supply and the composition of consumption. The producer model is concerned with output price formation and determination of input patterns and purchases for each of the nine producing sectors. These components form the behavioral basis of DGEM. The remaining components are concerned with constraints, balance conditions, accounting, and government revenues and expenditures (these elements aremore » developed in the report on the model specification).« less
A national econometric forecasting model of the dental sector.
Feldstein, P J; Roehrig, C S
1980-01-01
The Econometric Model of the the Dental Sector forecasts a broad range of dental sector variables, including dental care prices; the amount of care produced and consumed; employment of hygienists, dental assistants, and clericals; hours worked by dentists; dental incomes; and number of dentists. These forecasts are based upon values specified by the user for the various factors which help determine the supply an demand for dental care, such as the size of the population, per capita income, the proportion of the population covered by private dental insurance, the cost of hiring clericals and dental assistants, and relevant government policies. In a test of its reliability, the model forecast dental sector behavior quite accurately for the period 1971 through 1977. PMID:7461974
NASA Technical Reports Server (NTRS)
Mccandless, S. W.; Miller, B. P.
1974-01-01
The SEASAT satellite system is planned as a user-oriented system for timely monitoring of global ocean dynamics and mapping the global ocean geoid. The satellite instrumentation and modular concept are discussed. Operational data capabilities will include oceanographic data services, direct satellite read-out to users, and conversational retrieval and analysis of stored data. A case-study technique, generalized through physical and econometric modeling, indicates potential economic benefit from SEASAT to users in the following areas: ship routing, iceberg reconnaissance, arctic operations, Alaska pipeline ship link, and off-shore oil production.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1994-01-01
The bibliography contains citations concerning the use of mathematical models in trend analysis and forecasting of energy supply and demand factors. Models are presented for the industrial, transportation, and residential sectors. Aspects of long term energy strategies and markets are discussed at the global, national, state, and regional levels. Energy demand and pricing, and econometrics of energy, are explored for electric utilities and natural resources, such as coal, oil, and natural gas. Energy resources are modeled both for fuel usage and for reserves. (Contains 250 citations and includes a subject term index and title list.)
Energy supply and demand modeling. (Latest citations from the NTIS data base). Published Search
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1992-10-01
The bibliography contains citations concerning the use of mathematical models in trend analysis and forecasting of energy supply and demand factors. Models are presented for the industrial, transportation, and residential sectors. Aspects of long term energy strategies and markets are discussed at the global, national, state, and regional levels. Energy demand and pricing, and econometrics of energy, are explored for electric utilities and natural resources, such as coal, oil, and natural gas. Energy resources are modeled both for fuel usage and for reserves. (Contains 250 citations and includes a subject term index and title list.)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1994-12-01
The bibliography contains citations concerning the use of mathematical models in trend analysis and forecasting of energy supply and demand factors. Models are presented for the industrial, transportation, and residential sectors. Aspects of long term energy strategies and markets are discussed at the global, national, state, and regional levels. Energy demand and pricing, and econometrics of energy, are explored for electric utilities and natural resources, such as coal, oil, and natural gas. Energy resources are modeled both for fuel usage and for reserves. (Contains 250 citations and includes a subject term index and title list.)
Handling preference heterogeneity for river services' adaptation to climate change.
Andreopoulos, Dimitrios; Damigos, Dimitrios; Comiti, Francesco; Fischer, Christian
2015-09-01
Climate projection models for the Southern Mediterranean basin indicate a strong drought trend. This pattern is anticipated to affect a range of services derived from river ecosystems and consecutively deteriorate the sectoral outputs and household welfare. This paper aims to evaluate local residents' adaptation preferences for the Piave River basin in Italy. A Discrete Choice Experiment accounting for adaptation scenarios of the Piave River services was conducted and the collected data were econometrically analyzed using Random Parameters Logit, Latent Class and Covariance Heterogeneity models. In terms of policy-relevant outcomes, the analysis indicates that respondents are willing to pay for adaptation plans. This attitude is reflected on the compensating surplus to sustain the current state of the Piave, which corresponds to a monthly contribution of 80€ per household. From an econometric point of view, the results show that it is not sufficient to take solely into account general heterogeneity, provided that distinct treatment of the heterogeneity produces rather different welfare estimates. This implies that analysts should examine a set of criteria when deciding on how to better approach heterogeneity for each empirical data set. Overall, non-market values of environmental services should be considered when formulating cost-effective adaptation measures for river systems undergoing climate change effects and appropriate heterogeneity approximation could render these values unbiased and accurate. Copyright © 2015 Elsevier Ltd. All rights reserved.
Jabor, A; Vlk, T; Boril, P
1996-04-15
We designed a simulation model for the assessment of the financial risks involved when a new diagnostic test is introduced in the laboratory. The model is based on a neural network consisting of ten neurons and assumes that input entities can have assigned appropriate uncertainty. Simulations are done on a 1-day interval basis. Risk analysis completes the model and the financial effects are evaluated for a selected time period. The basic output of the simulation consists of total expenses and income during the simulation time, net present value of the project at the end of simulation, total number of control samples during simulation, total number of patients evaluated and total number of used kits.
The value of information as applied to the Landsat Follow-on benefit-cost analysis
NASA Technical Reports Server (NTRS)
Wood, D. B.
1978-01-01
An econometric model was run to compare the current forecasting system with a hypothetical (Landsat Follow-on) space-based system. The baseline current system was a hybrid of USDA SRS domestic forecasts and the best known foreign data. The space-based system improved upon the present Landsat by the higher spatial resolution capability of the thematic mapper. This satellite system is a major improvement for foreign forecasts but no better than SRS for domestic forecasts. The benefit analysis was concentrated on the use of Landsat Follow-on to forecast world wheat production. Results showed that it was possible to quantify the value of satellite information and that there are significant benefits in more timely and accurate crop condition information.
Econometrics 101: forecasting demystified
DOE Office of Scientific and Technical Information (OSTI.GOV)
Crow, R.T.
1980-05-01
Forecasting by econometric modeling is described in a commonsense way which omits much of the technical jargon. A trend of continuous growth is no longer an adequate forecasting tool. Today's forecasters must consider rapid changes in price, policies, regulations, capital availability, and the cost of being wrong. A forecasting model is designed by identifying future influences on electricity purchases and quantifying their relationships to each other. A record is produced which can be evaluated and used to make corrections in the models. Residential consumption is used to illustrate how this works and to demonstrate how power consumption is also relatedmore » to the purchase and use of equipment. While models can quantify behavioral relationships, they cannot account for the impacts of non-price factors because of limited data. (DCK)« less
Econometric models for predicting confusion crop ratios
NASA Technical Reports Server (NTRS)
Umberger, D. E.; Proctor, M. H.; Clark, J. E.; Eisgruber, L. M.; Braschler, C. B. (Principal Investigator)
1979-01-01
Results for both the United States and Canada show that econometric models can provide estimates of confusion crop ratios that are more accurate than historical ratios. Whether these models can support the LACIE 90/90 accuracy criterion is uncertain. In the United States, experimenting with additional model formulations could provide improved methods models in some CRD's, particularly in winter wheat. Improved models may also be possible for the Canadian CD's. The more aggressive province/state models outperformed individual CD/CRD models. This result was expected partly because acreage statistics are based on sampling procedures, and the sampling precision declines from the province/state to the CD/CRD level. Declining sampling precision and the need to substitute province/state data for the CD/CRD data introduced measurement error into the CD/CRD models.
Stranded cost recovery: Reregulating the electricity markets in the United States
NASA Astrophysics Data System (ADS)
Wagle, Pushkar Ghanashyam
2000-10-01
For the past few years, Stranded Cost recovery has been one of the most contentious issues regarding the restructuring of electricity markets among the regulators, researchers, and the other interested parties. Among the states that have moved towards retail competition, some have already made decisions regarding the levels of the stranded cost recovery. So the question is: how have these states handled the "stranded cost problem"? Following the introduction and the historical perspective of the industry in the first chapter, the second chapter takes a broad view for understanding the overall process of deregulation. It attempts to analyze why some states have made a rapid transition to competition in the electric utility industry, while other states are just beginning to consider the issue. White (1996) and Ando & Palmer (1998) have conducted a similar exercise. We present a more comprehensive and theoretically informed econometric analysis that sheds light over some of the crucial issues involved in restructuring, such as, stranded cost recovery, regulation of transmission and distribution sectors, and establishment of Independent System Operator, etc. This chapter offers the rationale for alternative econometric techniques, and extends the political economy analysis to incorporate actual timings of retail competition. Once we have identified the role of stranded cost in restructuring and the theoretical foundations, we study empirically the political economy of states' decisions to grant stranded cost recovery. This constitutes the third chapter. Here, we concentrate on California and Pennsylvania, two states that are at the frontiers of deregulation, and compare their respective treatments of the stranded cost. We probe the reasons behind Pennsylvania's lead over California on the path towards deregulation.
[Economic impact of nosocomial bacteraemia. A comparison of three calculation methods].
Riu, Marta; Chiarello, Pietro; Terradas, Roser; Sala, Maria; Castells, Xavier; Knobel, Hernando; Cots, Francesc
2016-12-01
The excess cost associated with nosocomial bacteraemia (NB) is used as a measurement of the impact of these infections. However, some authors have suggested that traditional methods overestimate the incremental cost due to the presence of various types of bias. The aim of this study was to compare three assessment methods of NB incremental cost to correct biases in previous analyses. Patients who experienced an episode of NB between 2005 and 2007 were compared with patients grouped within the same All Patient Refined-Diagnosis-Related Group (APR-DRG) without NB. The causative organisms were grouped according to the Gram stain, and whether bacteraemia was caused by a single or multiple microorganisms, or by a fungus. Three assessment methods are compared: stratification by disease; econometric multivariate adjustment using a generalised linear model (GLM); and propensity score matching (PSM) was performed to control for biases in the econometric model. The analysis included 640 admissions with NB and 28,459 without NB. The observed mean cost was €24,515 for admissions with NB and €4,851.6 for controls (without NB). Mean incremental cost was estimated at €14,735 in stratified analysis. Gram positive microorganism had the lowest mean incremental cost, €10,051. In the GLM, mean incremental cost was estimated as €20,922, and adjusting with PSM, the mean incremental cost was €11,916. The three estimates showed important differences between groups of microorganisms. Using enhanced methodologies improves the adjustment in this type of study and increases the value of the results. Copyright © 2015 Elsevier España, S.L.U. and Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.
An empirical analysis of cigarette demand in Argentina
Martinez, Eugenio; Mejia, Raul; Pérez-Stable, Eliseo J
2014-01-01
Objective To estimate the long-term and short-term effects on cigarette demand in Argentina based on changes in cigarette price and income per person >14 years old. Method Public data from the Ministry of Economics and Production were analysed based on monthly time series data between 1994 and 2010. The econometric analysis used cigarette consumption per person >14 years of age as the dependent variable and the real income per person >14 years old and the real average price of cigarettes as independent variables. Empirical analyses were done to verify the order of integration of the variables, to test for cointegration to capture the long-term effects and to capture the short-term dynamics of the variables. Results The demand for cigarettes in Argentina was affected by changes in real income and the real average price of cigarettes. The long-term income elasticity was equal to 0.43, while the own-price elasticity was equal to −0.31, indicating a 10% increase in the growth of real income led to an increase in cigarette consumption of 4.3% and a 10% increase in the price produced a fall of 3.1% in cigarette consumption. The vector error correction model estimated that the short-term income elasticity was 0.25 and the short-term own-price elasticity of cigarette demand was −0.15. A simulation exercise showed that increasing the price of cigarettes by 110% would maximise revenues and result in a potentially large decrease in total cigarette consumption. Conclusion Econometric analyses of cigarette consumption and their relationship with cigarette price and income can provide valuable information for developing cigarette price policy. PMID:23760657
Brunelli, Alessandro; Salati, Michele; Refai, Majed; Xiumé, Francesco; Rocco, Gaetano; Sabbatini, Armando
2007-09-01
The objectives of this study were to develop a risk-adjusted model to estimate individual postoperative costs after major lung resection and to use it for internal economic audit. Variable and fixed hospital costs were collected for 679 consecutive patients who underwent major lung resection from January 2000 through October 2006 at our unit. Several preoperative variables were used to develop a risk-adjusted econometric model from all patients operated on during the period 2000 through 2003 by a stepwise multiple regression analysis (validated by bootstrap). The model was then used to estimate the postoperative costs in the patients operated on during the 3 subsequent periods (years 2004, 2005, and 2006). Observed and predicted costs were then compared within each period by the Wilcoxon signed rank test. Multiple regression and bootstrap analysis yielded the following model predicting postoperative cost: 11,078 + 1340.3X (age > 70 years) + 1927.8X cardiac comorbidity - 95X ppoFEV1%. No differences between predicted and observed costs were noted in the first 2 periods analyzed (year 2004, $6188.40 vs $6241.40, P = .3; year 2005, $6308.60 vs $6483.60, P = .4), whereas in the most recent period (2006) observed costs were significantly lower than the predicted ones ($3457.30 vs $6162.70, P < .0001). Greater precision in predicting outcome and costs after therapy may assist clinicians in the optimization of clinical pathways and allocation of resources. Our economic model may be used as a methodologic template for economic audit in our specialty and complement more traditional outcome measures in the assessment of performance.
An empirical analysis of cigarette demand in Argentina.
Martinez, Eugenio; Mejia, Raul; Pérez-Stable, Eliseo J
2015-01-01
To estimate the long-term and short-term effects on cigarette demand in Argentina based on changes in cigarette price and income per person >14 years old. Public data from the Ministry of Economics and Production were analysed based on monthly time series data between 1994 and 2010. The econometric analysis used cigarette consumption per person >14 years of age as the dependent variable and the real income per person >14 years old and the real average price of cigarettes as independent variables. Empirical analyses were done to verify the order of integration of the variables, to test for cointegration to capture the long-term effects and to capture the short-term dynamics of the variables. The demand for cigarettes in Argentina was affected by changes in real income and the real average price of cigarettes. The long-term income elasticity was equal to 0.43, while the own-price elasticity was equal to -0.31, indicating a 10% increase in the growth of real income led to an increase in cigarette consumption of 4.3% and a 10% increase in the price produced a fall of 3.1% in cigarette consumption. The vector error correction model estimated that the short-term income elasticity was 0.25 and the short-term own-price elasticity of cigarette demand was -0.15. A simulation exercise showed that increasing the price of cigarettes by 110% would maximise revenues and result in a potentially large decrease in total cigarette consumption. Econometric analyses of cigarette consumption and their relationship with cigarette price and income can provide valuable information for developing cigarette price policy. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-05-15
... bioethics, behavioral sciences, economics and statistics, as well as representatives of transplant...; law and bioethics; behavioral sciences; economics and econometrics; organ procurement organizations...
Han, Hyemin; Park, Joonsuk
2018-01-01
Recent debates about the conventional traditional threshold used in the fields of neuroscience and psychology, namely P < 0.05, have spurred researchers to consider alternative ways to analyze fMRI data. A group of methodologists and statisticians have considered Bayesian inference as a candidate methodology. However, few previous studies have attempted to provide end users of fMRI analysis tools, such as SPM 12, with practical guidelines about how to conduct Bayesian inference. In the present study, we aim to demonstrate how to utilize Bayesian inference, Bayesian second-level inference in particular, implemented in SPM 12 by analyzing fMRI data available to public via NeuroVault. In addition, to help end users understand how Bayesian inference actually works in SPM 12, we examine outcomes from Bayesian second-level inference implemented in SPM 12 by comparing them with those from classical second-level inference. Finally, we provide practical guidelines about how to set the parameters for Bayesian inference and how to interpret the results, such as Bayes factors, from the inference. We also discuss the practical and philosophical benefits of Bayesian inference and directions for future research. PMID:29456498
The Importance of Statistical Modeling in Data Analysis and Inference
ERIC Educational Resources Information Center
Rollins, Derrick, Sr.
2017-01-01
Statistical inference simply means to draw a conclusion based on information that comes from data. Error bars are the most commonly used tool for data analysis and inference in chemical engineering data studies. This work demonstrates, using common types of data collection studies, the importance of specifying the statistical model for sound…
Li, Jia; Zhang, Ya; Ma, Ling; Liu, Xuan
2016-10-28
Many markets have traditionally been dominated by a few best-selling products, and this is also the case for the health care industry. However, we do not know whether the market will be more or less concentrated when health care services are delivered online (known as E-consultation), nor do we know how to reduce the concentration of the E-consultation market. The aim of this study was to investigate the concentration of the E-consultation market and how to reduce its concentration through information disclosure mechanisms (online reputation and self-representation). We employed a secondary data econometric analysis using transaction data obtained from an E-consultation Website (haodf.com) for three diseases (infantile pneumonia, diabetes, and pancreatic cancer) from 2008 to 2015. We included 2439 doctors in the analysis. The E-consultation market largely follows the 20/80 principle, namely that approximately 80% of orders are fulfilled by nearly 20% of doctors. This is much higher than the offline health care market. Meanwhile, the market served by doctors with strong online reputations (beta=0.207, P<.001) or strong online self-representation (beta=0.386, P<.001) is less concentrated. When health care services are delivered online, the market will be more concentrated (known as the "Superstar" effect), indicating poor service efficiency for society as a whole. To reduce market concentration, E-consultation websites should provide important design elements such as ratings of doctors (user feedback), articles contributed by doctors, and free consultation services (online representation). A possible and important way to reduce the market concentration of the E-consultation market is to accumulate enough highly rated or highly self-represented doctors. ©Jia Li, Ya Zhang, Ling Ma, Xuan Liu. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.10.2016.
2013-01-01
Background There is a growing interest in examining the current state of care and identifying opportunities for improving care and reducing costs at the end of life. The aim of this study is to examine patterns of health care use at the end of life and place of death and to describe the basic characteristics of the decedents in the last six months of their life. Methods The empirical analysis is based on data from 58,732 Swiss residents who died between 2007 and 2011. All decedents had mandatory health insurance with Helsana Group, the largest health insurer in Switzerland. Descriptive statistical techniques were used to provide a general profile of the study population and determinants of the outcome for place of death were analyzed with an econometric approach. Results There were substantial and significant differences in health care utilization in the last six months of life between places of death. The mean numbers of consultations with a general practitioner or a specialist physician as well as the number of different medications and the number of hospital days was consistently highest for the decedents who died in a hospital. We found death occurred in Switzerland most frequently in hospitals (38.4% of all cases) followed by nursing homes (35.1%) and dying at home (26.6%). The econometric analysis indicated that the place of death is significantly associated with age, sex, region and multiple chronic conditions. Conclusions The importance of nursing homes and patients’ own homes as place of death will continue to grow in the future. Knowing the determinants of place of death and patterns of health care utilization of decedents can help decision makers on the allocation of these needed health care services in Switzerland. PMID:23530717
Economic Drought Impact on Agriculture: analysis of all agricultural sectors affected
NASA Astrophysics Data System (ADS)
Gil, M.; Garrido, A.; Hernández-Mora, N.
2012-04-01
The analysis of drought impacts is essential to define efficient and sustainable management and mitigation. In this paper we present a detailed analysis of the impacts of the 2004-2008 drought in the agricultural sector in the Ebro river basin (Spain). An econometric model is applied in order to determine the magnitude of the economic loss attributable to water scarcity. Both the direct impacts of drought on agricultural productivity and the indirect impacts of drought on agricultural employment and agroindustry in the Ebro basin are evaluated. The econometric model measures losses in the economic value of irrigated and rainfed agricultural production, of agricultural employment and of Gross Value Added both from the agricultural sector and the agro-industrial sector. The explanatory variables include an index of water availability (reservoir storage levels for irrigated agriculture and accumulated rainfall for rainfed agriculture), a price index representative of the mix of crops grown in each region, and a time variable. The model allows for differentiating the impacts due to water scarcity from other sources of economic losses. Results show how the impacts diminish as we approach the macro-economic indicators from those directly dependent on water abstractions and precipitation. Sectors directly dependent on water are the most affected with identifiable economic losses resulting from the lack of water. From the management perspective implications of these findings are key to develop mitigation measures to reduce drought risk exposure. These results suggest that more open agricultural markets, and wider and more flexible procurement strategies of the agro-industry reduces the socio-economic exposure to drought cycles. This paper presents the results of research conducted under PREEMPT project (Policy relevant assessment of the socioeconomic effects of droughts and floods, ECHO - grant agreement # 070401/2010/579119/SUB/C4), which constitutes an effort to provide a comprehensive assessment of the socioeconomic impacts of the 2004-2008 drought in the Ebro river basin
NASA Astrophysics Data System (ADS)
Jeuck, James A.
This dissertation consists of research projects related to forest land use / land cover (LULC): (1) factors predicting LULC change and (2) methodology to predict particular forest use, or "potential working timberland" (PWT), from current forms of land data. The first project resulted in a published paper, a meta-analysis of 64 econometric models from 47 studies predicting forest land use changes. The response variables, representing some form of forest land change, were organized into four groups: forest conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified, from 21 F2A models, 21 F2D models, 12 F2NF models, and 10 U2D models. These variables were organized into a hierarchy of 119 independent variable groups, 15 categories, and 4 econometric drivers suitable for conducting simple vote count statistics. Vote counts were summarized at the independent variable group level and formed into ratios estimating the predictive success of each variable group. Two ratio estimates were developed based on (1) proportion of times independent variables successfully achieved statistical significance (p ≤0.10), and (2) proportion of times independent variables successfully met the original researchers'expectations. In F2D models, popular independent variables such as population, income, and urban proximity often achieved statistical significance. In F2A models, popular independent variables such as forest and agricultural rents and costs, governmental programs, and site quality often achieved statistical significance. In U2D models, successful independent variables included urban rents and costs, zoning issues concerning forestland loss, site quality, urban proximity, population, and income. F2NF models high success variables were found to be agricultural rents, site quality, population, and income. This meta-analysis provides insight into the general success of econometric independent variables for future forest use or cover change research. The second part of this dissertation developed a method for predicting area estimates and spatial distribution of PWT in the US South. This technique determined land use from USFS Forest Inventory and Analysis (FIA) and land cover from the National Land Cover Database (NLCD). Three dependent variable forms (DV Forms) were derived from the FIA data: DV Form 1, timberland, other; DV Form 2, short timberland, tall timberland, agriculture, other; and DV Form 3, short hardwood (HW) timberland, tall HW timberland, short softwood (SW) timberland, tall SW timberland, agriculture, other. The prediction accuracy of each DV Form was investigated using both random forest model and logistic regression model specifications and data optimization techniques. Model verification employing a "leave-group-out" Monte Carlo simulation determined the selection of a stratified version of the random forest model using one-year NLCD observations with an overall accuracy of 0.53-0.94. The lower accuracy side of the range was when predictions were made from an aggregated NLCD land cover class "grass_shrub". The selected model specification was run using 2011 NLCD and the other predictor variables to produce three levels of timberland prediction and probability maps for the US South. Spatial masks removed areas unlikely to be working forests (protected and urbanized lands) resulting in PWT maps. The area of the resulting maps compared well with USFS area estimates and masked PWT maps and had an 8-11% reduction of the USFS timberland estimate for the US South compared to the DV Form. Change analysis of the 2011 NLCD to PWT showed (1) the majority of the short timberland came from NLCD grass_shrub; (2) the majority of NLCD grass_shrub predicted into tall timberland, and (3) NLCD grass_shrub was more strongly associated with timberland in the Coastal Plain. Resulting map products provide practical analytical tools for those interested in studying the area and distribution of PWT in the US South.
The impact of energy, transport, and trade on air pollution in China
DOE Office of Scientific and Technical Information (OSTI.GOV)
Poon, J.P.H.; Casas, I.; He, C.F.
2006-09-15
A team of U.S.- and China-based geographers examines the relationship between China's economic development and its environment by modeling the effects of energy, transport, and trade on local air pollution emissions (sulfur dioxide and soot particulates) using the Environmental Kuznets model. Specifically, the latter model is investigated using spatial econometrics that take into account potential regional spillover effects from high-polluting neighbors. The analysis finds an inverted-U relationship for sulfur dioxide but a U-shaped curve for soot particulates. This suggests that soot particulates such as black carbon may pose a more serious environmental problem in China than sulfur dioxide.
Climate change and economic growth: a heterogeneous panel data approach.
Sequeira, Tiago Neves; Santos, Marcelo Serra; Magalhães, Manuela
2018-05-31
Climate change is a global phenomenon. Its impact on economic growth must therefore be analyzed in accordance with its (time-varying) common effects. We present an econometric analysis that evaluates this effect taking into account its global nature. Contrary to previous evidence that ignores the global effects, we obtain that the rising temperature has not decreased growth in real GDP per capita in the second half of the twentieth century for the world countries. However, we obtain a negative effect of rising temperatures and a positive effect of rising precipitation in poor countries. This positive effect of rising precipitation is also confirmed for hot and temperate countries.
Identifiability and Problems of Model Selection for Time-Series Analysis in Econometrics.
1980-01-01
Z is defined by (2.1) Fx + ( y( If x(t), T c R;dt for discrete-time, that is, with the time set T = Z = integers, a system F is given by * The...O1/14/81 cb (2.2) x(t + 1) Fx (t) + Gu(t), y(t) = Hx(t), t c Z. In (2.1-2.2), the real (or complex) vectors x, u, and y are called state, inpuI, and...compulsory. Astro - loryi has been tried. No optimist would quarrel with the declaration of one of von NE!MAfrIiI’s direct successors that "exposure to the
2017-01-01
The U.S. Energy Information Administration's Short-Term Energy Outlook (STEO) produces monthly projections of energy supply, demand, trade, and prices over a 13-24 month period. Every January, the forecast horizon is extended through December of the following year. The STEO model is an integrated system of econometric regression equations and identities that link data on the various components of the U.S. energy industry together in order to develop consistent forecasts. The regression equations are estimated and the STEO model is solved using the EViews 9.5 econometric software package from IHS Global Inc. The model consists of various modules specific to each energy resource. All modules provide projections for the United States, and some modules provide more detailed forecasts for different regions of the country.
Systems GMM estimates of the health care spending and GDP relationship: a note.
Kumar, Saten
2013-06-01
This paper utilizes the systems generalized method of moments (GMM) [Arellano and Bover (1995) J Econometrics 68:29-51; Blundell and Bond (1998) J Econometrics 87:115-143], and panel Granger causality [Hurlin and Venet (2001) Granger Causality tests in panel data models with fixed coefficients. Mime'o, University Paris IX], to investigate the health care spending and gross domestic product (GDP) relationship for organisation for economic co-operation and development countries over the period 1960-2007. The system GMM estimates confirm that the contribution of real GDP to health spending is significant and positive. The panel Granger causality tests imply that a bi-directional causality exists between health spending and GDP. To this end, policies aimed at raising health spending will eventually improve the well-being of the population in the long run.
Computationally intensive econometrics using a distributed matrix-programming language.
Doornik, Jurgen A; Hendry, David F; Shephard, Neil
2002-06-15
This paper reviews the need for powerful computing facilities in econometrics, focusing on concrete problems which arise in financial economics and in macroeconomics. We argue that the profession is being held back by the lack of easy-to-use generic software which is able to exploit the availability of cheap clusters of distributed computers. Our response is to extend, in a number of directions, the well-known matrix-programming interpreted language Ox developed by the first author. We note three possible levels of extensions: (i) Ox with parallelization explicit in the Ox code; (ii) Ox with a parallelized run-time library; and (iii) Ox with a parallelized interpreter. This paper studies and implements the first case, emphasizing the need for deterministic computing in science. We give examples in the context of financial economics and time-series modelling.
Paradoxical Behavior of Granger Causality
NASA Astrophysics Data System (ADS)
Witt, Annette; Battaglia, Demian; Gail, Alexander
2013-03-01
Granger causality is a standard tool for the description of directed interaction of network components and is popular in many scientific fields including econometrics, neuroscience and climate science. For time series that can be modeled as bivariate auto-regressive processes we analytically derive an expression for spectrally decomposed Granger Causality (SDGC) and show that this quantity depends only on two out of four groups of model parameters. Then we present examples of such processes whose SDGC expose paradoxical behavior in the sense that causality is high for frequency ranges with low spectral power. For avoiding misinterpretations of Granger causality analysis we propose to complement it by partial spectral analysis. Our findings are illustrated by an example from brain electrophysiology. Finally, we draw implications for the conventional definition of Granger causality. Bernstein Center for Computational Neuroscience Goettingen
Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information
NASA Astrophysics Data System (ADS)
Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David
2018-05-01
The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.
ERIC Educational Resources Information Center
Elleman, Amy M.
2017-01-01
Inference ability is considered central to discourse processing and has been shown to be important across models of reading comprehension. To evaluate the impact of inference instruction, a meta-analysis of 25 inference studies in Grades K-12 was conducted. Results showed that inference instruction was effective for increasing students' general…
Econometrics of inventory holding and shortage costs: the case of refined gasoline
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krane, S.D.
1985-01-01
This thesis estimates a model of a firm's optimal inventory and production behavior in order to investigate the link between the role of inventories in the business cycle and the microeconomic incentives for holding stocks of finished goods. The goal is to estimate a set of structural cost function parameters that can be used to infer the optimal cyclical response of inventories and production to shocks in demand. To avoid problems associated with the use of value based aggregate inventory data, an industry level physical unit data set for refined motor gasoline is examined. The Euler equations for a refiner'smore » multiperiod decision problem are estimated using restrictions imposed by the rational expectations hypothesis. The model also embodies the fact that, in most periods, the level of shortages will be zero, and even when positive, the shortages are not directly observable in the data set. These two concerns lead us to use a generalized method of moments estimation technique on a functional form that resembles the formulation of a Tobit problem. The estimation results are disappointing; the model and data yield coefficient estimates incongruous with the cost function interpretations of the structural parameters. These is only some superficial evidence that production smoothing is significant and that marginal inventory shortage costs increase at a faster rate than do marginal holding costs.« less
Estimating Environmental Compliance Costs for Industry (1981)
The paper discusses the pros and cons of existing approaches to compliance cost estimation such as ex post survey estimation and ex ante estimation techniques (input cost accounting methods, engineering process models and, econometric models).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deason, Jeff; Murphy, Sean
A new study by Berkeley Lab found that residential Property Assessed Clean Energy (R-PACE) programs increased deployment of residential solar photovoltaic (PV) systems in California, raising it by about 7-12% in cities that adopt these programs. R-PACE is a financing mechanism that uses a voluntary property tax assessment, paid off over time, to facilitate energy improvements and, in some jurisdictions, water and resilience measures. While previous studies demonstrated that early, regional R-PACE programs increased solar PV deployment, this new analysis is the first to demonstrate these impacts from the large, statewide R-PACE programs dominating the California market today, which usemore » private capital to fund the upfront costs of the improvements. Berkeley Lab estimated the impacts using econometric techniques on two samples: -Large cities only, allowing annual demographic and economic data as control variables -All California cities, without these annual data Analysis of both samples controls for several factors other than R-PACE that would be expected to drive solar PV deployment. We infer that on average, cities with R-PACE programs were associated with greater solar PV deployment in our study period (2010-2015). In the large cities sample, solar PV deployment in jurisdictions with R-PACE programs was higher by 1.1 watts per owner-occupied household per month, or 12%. Across all cities, solar PV deployment in jurisdictions with R-PACE programs was higher by 0.6 watts per owner-occupied household per month, or 7%. The large cities results are statistically significant at conventional levels; the all-cities results are not. The estimates imply that the majority of solar PV deployment financed by R-PACE programs would likely not have occurred in their absence. Results suggest that R-PACE programs have increased PV deployment in California even in relatively recent years, as R-PACE programs have grown in market share and as alternate approaches for financing solar PV have developed. The U.S. Department of Energy’s Building Technologies Office supported this research.« less
Tahmasebi, Nima; Kebriaeezadeh, Abbas
2015-01-01
Prescribing behavior of physicians affected by many factors. The present study is aimed at discovering the simultaneous effects of the evaluated factors (including: price, promotion and demographic characteristics of physicians) and quantification of these effects. In order to estimate these effects, Fluvoxamine (an antidepressant drug) was selected and the model was figured out by panel data method in econometrics. We found that insurance and advertisement respectively are the most effective on increasing the frequency of prescribing, whilst negative correlation was observed between price and the frequency of prescribing a drug. Also brand type is more sensitive to negative effect of price than to generic. Furthermore, demand for a prescription drug is related with physician demographics (age and sex). According to the results of this study, pharmaceutical companies should pay more attention to the demographic characteristics of physicians (age and sex) and their advertisement and pricing strategies.
Optimizing distance-based methods for large data sets
NASA Astrophysics Data System (ADS)
Scholl, Tobias; Brenner, Thomas
2015-10-01
Distance-based methods for measuring spatial concentration of industries have received an increasing popularity in the spatial econometrics community. However, a limiting factor for using these methods is their computational complexity since both their memory requirements and running times are in {{O}}(n^2). In this paper, we present an algorithm with constant memory requirements and shorter running time, enabling distance-based methods to deal with large data sets. We discuss three recent distance-based methods in spatial econometrics: the D&O-Index by Duranton and Overman (Rev Econ Stud 72(4):1077-1106, 2005), the M-function by Marcon and Puech (J Econ Geogr 10(5):745-762, 2010) and the Cluster-Index by Scholl and Brenner (Reg Stud (ahead-of-print):1-15, 2014). Finally, we present an alternative calculation for the latter index that allows the use of data sets with millions of firms.
Tahmasebi, Nima; Kebriaeezadeh, Abbas
2015-01-01
Prescribing behavior of physicians affected by many factors. The present study is aimed at discovering the simultaneous effects of the evaluated factors (including: price, promotion and demographic characteristics of physicians) and quantification of these effects. In order to estimate these effects, Fluvoxamine (an antidepressant drug) was selected and the model was figured out by panel data method in econometrics. We found that insurance and advertisement respectively are the most effective on increasing the frequency of prescribing, whilst negative correlation was observed between price and the frequency of prescribing a drug. Also brand type is more sensitive to negative effect of price than to generic. Furthermore, demand for a prescription drug is related with physician demographics (age and sex). According to the results of this study, pharmaceutical companies should pay more attention to the demographic characteristics of physicians (age and sex) and their advertisement and pricing strategies. PMID:25901174
Cyberspace Security Econometrics System (CSES) - U.S. Copyright TXu 1-901-039
DOE Office of Scientific and Technical Information (OSTI.GOV)
Abercrombie, Robert K; Schlicher, Bob G; Sheldon, Frederick T
2014-01-01
Information security continues to evolve in response to disruptive changes with a persistent focus on information-centric controls and a healthy debate about balancing endpoint and network protection, with a goal of improved enterprise/business risk management. Economic uncertainty, intensively collaborative styles of work, virtualization, increased outsourcing and ongoing compliance pressures require careful consideration and adaptation. The Cyberspace Security Econometrics System (CSES) provides a measure (i.e., a quantitative indication) of reliability, performance, and/or safety of a system that accounts for the criticality of each requirement as a function of one or more stakeholders interests in that requirement. For a given stakeholder, CSESmore » accounts for the variance that may exist among the stakes one attaches to meeting each requirement. The basis, objectives and capabilities for the CSES including inputs/outputs as well as the structural and mathematical underpinnings contained in this copyright.« less
Loop Evolution Observed with AIA and Hi-C
NASA Technical Reports Server (NTRS)
Mulu-Moore, Fana; Winebarger, Amy R.; Cirtain, Jonathan W.; Kobayashi, Ken; Korreck, Kelly E.; Golub, Leon; Kuzin, Sergei; Walsh, Robert William; DeForest, Craig E.; De Pontieu, Bart;
2012-01-01
In the past decade, the evolution of EUV loops has been used to infer the loop substructure. With the recent launch of High Resolution Coronal Imager (Hi-C), this inference can be validated. In this presentation we discuss the first results of loop analysis comparing AIA and Hi-C data. In the past decade, the evolution of EUV loops has been used to infer the loop substructure. With the recent launch of High Resolution Coronal Imager (Hi-C), this inference can be validated. In this presentation we discuss the first results of loop analysis comparing AIA and Hi-C data.
Bond, Lyndal; Hilton, Shona
2014-01-01
Background: Novel policy interventions may lack evaluation-based evidence. Considerations to introduce minimum unit pricing (MUP) of alcohol in the UK were informed by econometric modelling (the ‘Sheffield model’). We aim to investigate policy stakeholders’ views of the utility of modelling studies for public health policy. Methods: In-depth qualitative interviews with 36 individuals involved in MUP policy debates (purposively sampled to include civil servants, politicians, academics, advocates and industry-related actors) were conducted and thematically analysed. Results: Interviewees felt familiar with modelling studies and often displayed detailed understandings of the Sheffield model. Despite this, many were uneasy about the extent to which the Sheffield model could be relied on for informing policymaking and preferred traditional evaluations. A tension was identified between this preference for post hoc evaluations and a desire for evidence derived from local data, with modelling seen to offer high external validity. MUP critics expressed concern that the Sheffield model did not adequately capture the ‘real life’ world of the alcohol market, which was conceptualized as a complex and, to some extent, inherently unpredictable system. Communication of modelling results was considered intrinsically difficult but presenting an appropriate picture of the uncertainties inherent in modelling was viewed as desirable. There was general enthusiasm for increased use of econometric modelling to inform future policymaking but an appreciation that such evidence should only form one input into the process. Conclusion: Modelling studies are valued by policymakers as they provide contextually relevant evidence for novel policies, but tensions exist with views of traditional evaluation-based evidence. PMID:24367068
Econometric analysis of the impact of the relationship of GDP and the pension capital
NASA Astrophysics Data System (ADS)
Nepp, A. N.; Amiryan, A. A.
2016-12-01
The article demonstrates the impact of institutional risks on indicators of compulsory pension insurance and describes the results of a comparative analysis of investment risks faced by the pension systems of the Russian Federation and OECD countries. Efficiency of private companies managing pension funds in Russia and OECD countries is compared and analyzed to show the necessity to liberalize requirements placed on investments of pension savings funds. On the basis of the available statistical data, the article puts forward and discusses the hypothesis that increasing of the basic indicators of the pension system is possible by reducing its institutional risks. It is concluded that if the institutional risks are reduced and the level of trust increases, there will be enhance growth in the pension system key indicators, such as pension payments and the replacement rate.
NASA Astrophysics Data System (ADS)
Gordon, K.; Houser, T.; Kopp, R. E., III; Hsiang, S. M.; Larsen, K.; Jina, A.; Delgado, M.; Muir-Wood, R.; Rasmussen, D.; Rising, J.; Mastrandrea, M.; Wilson, P. S.
2014-12-01
The United States faces a range of economic risks from global climate change - from increased flooding and storm damage, to climate-driven changes in crop yields and labor productivity, to heat-related strains on energy and public health systems. The Risky Business Project commissioned a groundbreaking new analysis of these and other climate risks by region of the country and sector of the economy. The American Climate Prospectus (ACP) links state-of-the-art climate models with econometric research of human responses to climate variability and cutting edge private sector risk assessment tools, the ACP offers decision-makers a data driven assessment of the specific risks they face. We describe the challenge, methods, findings, and policy implications of the national risk analysis, with particular focus on methodological innovations and novel insights.
Analysis of the impact of immigration on labour market using spatial models
NASA Astrophysics Data System (ADS)
Polonyankina, Tatiana
2017-07-01
This paper investigates the impact of immigration on employment and unemployment of a host country. The question to answer is: How does employment/unemployment in the host country change after an increase in number of immigrants? The analysis is taking into account only legal immigrants in recession period. The model is combining classical regression of cross-sectional data with spatial econometrics models where cross-section dependencies are captured by a spatial matrix. The intention is by using spatial models analyse the sensitivity of employment/unemployment rate on change in a share of immigration in a region. The used panel data are based on the Labour force survey and on available macro data in Eurostat for 3 European countries (Germany, Austria and Czech Republic) grouped into cells by NUTS regions in a recession period.
Integrating transit and urban form : final report, December 2008.
DOT National Transportation Integrated Search
2008-09-01
This study develops an integrated behavioral model of transit patronage and urban form. Although herein focused on transit, the framework can be easily generalized to study other forms of travel. Advanced econometric methods are used to test specific...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-08-13
...; behavioral sciences; economics and econometrics; organ procurement organizations; transplant candidates..., non-physician transplant professions, nursing, epidemiology, immunology, law and bioethics, behavioral sciences, economics and statistics, as well as representatives of transplant candidates, transplant...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-09-22
... bioethics; behavioral sciences; economics and econometrics; organ procurement organizations; transplant..., non-physician transplant professions, nursing, epidemiology, immunology, law and bioethics, behavioral sciences, economics and statistics, as well as representatives of transplant candidates, transplant...
The Role of the Manufacturer in Air Transportation Planning
NASA Technical Reports Server (NTRS)
Mackenzie, J.
1972-01-01
The role of the aircraft manufacturer in the airline industry is considered. The process is illustrated by using a fictitious airline as an example--that is, a case study approach with Mid-Coast Airways serving as the example. Both in slide form and with supporting papers, a brief history of the airline, a description of its route structure and a forecast based on econometric analysis are presented. Once the forecast rationale is explained, information outlines the requirements for additional aircraft and the application of new aircraft across the system using alternative fleet plan options. The fleet plan is translated into financial summaries which indicate the relative merit of alternative aircraft types or operating plans.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1990-06-01
This bibliography contains citations concerning the use of mathematical models in trend analysis and forecasting of energy supply and demand factors. Models are presented for the industrial, transportation, and residential sectors. Aspects of long term energy strategies and markets are discussed at the global, national, state, and regional levels. Energy demand and pricing, and econometrics of energy, are explored for electric utilities and natural resources, such as coal, oil, and natural gas. Energy resources are modeled both for fuel usage and for reserves. (This updated bibliography contains 201 citations, none of which are new entries to the previous edition.)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1988-04-01
This bibliography contains citations concerning the utilization of mathematical models in trend analysis and forecasting of energy supply and demand factors. Models are presented for the industrial, transportation, and residential sectors. Aspects of long-term energy strategies and markets are discussed at the global, national, state, and regional levels. Energy demand and pricing, and econometrics of energy, are explored for electric utilities and natural resources, such as coal, oil, and natural gas. Energy resources are modeled both for fuel usage and for reserves. (This updated bibliography contains 201 citations, 129 of which are new entries to the previous edition.)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1990-06-01
This bibliography contains citations concerning the use of mathematical models in trend analysis and forecasting of energy supply and demand factors. Models are presented for the industrial, transportation, and residential sectors. Aspects of long term energy strategies and markets are discussed at the global, national, state, and regional levels. Energy demand and pricing, and econometrics of energy, are explored for electric utilities and natural resources, such as coal, oil, and natural gas. Energy resources are modeled both for fuel usage and for reserves. (This updated bibliography contains 200 citations, all of which are new entries to the previous edition.)
Engel, Christoph; Hamann, Hanjo
2016-01-01
The (German) market for law professors fulfils the conditions for a hog cycle: In the short run, supply cannot be extended or limited; future law professors must be hired soon after they first present themselves, or leave the market; demand is inelastic. Using a comprehensive German dataset, we show that the number of market entries today is negatively correlated with the number of market entries eight years ago. This suggests short-sighted behavior of young scholars at the time when they decide to prepare for the market. Using our statistical model, we make out-of-sample predictions for the German academic market in law until 2020.
Price impact on urban residential water demand: A dynamic panel data approach
NASA Astrophysics Data System (ADS)
ArbuéS, Fernando; BarberáN, Ramón; Villanúa, Inmaculada
2004-11-01
In this paper, we formulate and estimate a model of residential water demand with the aim of evaluating the potential of pricing policies as a mechanism for managing residential water. The proposed econometric model offers a new perspective on urban water demand analysis by combining microlevel data with a dynamic panel data estimation procedure. The empirical application suggests that residential users are more responsive to a lagged average price specification. Another result of the estimated model is that price is a moderately effective tool in reducing residential water demand within the present range of prices, with the estimated values for income elasticity and "elasticity of consumption with respect to family size" reinforcing this conclusion.
Valuing Eastern Visibility: A Field Test of the Contingent Valuation Method (1993)
The report describes the Eastern visibility survey design in detail, presents the implementation of and data obtained from the surveys, provides summary statistics on the overall response and discusses the econometric techniques employed to value benefits.
NASA Astrophysics Data System (ADS)
Grove, J. Morgan; Locke, Dexter H.; O'Neil-Dunne, Jarlath P. M.
2014-09-01
Several social theories have been proposed to explain the uneven distribution of vegetation in urban residential areas: population density, social stratification, luxury effect, and ecology of prestige. We evaluate these theories using a combination of demographic and socio-economic predictors of vegetative cover on all residential lands in New York City. We use diverse data sources including the City's property database, time-series demographic and socio-economic data from the US Census, and land cover data from the University of Vermont's Spatial Analysis Lab (SAL). These data are analyzed using a multi-model inferential, spatial econometrics approach. We also examine the distribution of vegetation within distinct market categories using Claritas' Potential Rating Index for Zipcode Markets (PRIZM™) database. These categories can be disaggregated, corresponding to the four social theories. We compare the econometric and categorical results for validation. Models associated with ecology of prestige theory are more effective for predicting the distribution of vegetation. This suggests that private, residential patterns of vegetation, reflecting the consumption of environmentally relevant goods and services, are associated with different lifestyles and lifestages. Further, our spatial and temporal analyses suggest that there are significant spatial and temporal dependencies that have theoretical and methodological implications for understanding urban ecological systems. These findings may have policy implications. Decision makers may need to consider how to most effectively reach different social groups in terms of messages and messengers in order to advance land management practices and achieve urban sustainability.
Grove, J Morgan; Locke, Dexter H; O'Neil-Dunne, Jarlath P M
2014-09-01
Several social theories have been proposed to explain the uneven distribution of vegetation in urban residential areas: population density, social stratification, luxury effect, and ecology of prestige. We evaluate these theories using a combination of demographic and socio-economic predictors of vegetative cover on all residential lands in New York City. We use diverse data sources including the City's property database, time-series demographic and socio-economic data from the US Census, and land cover data from the University of Vermont's Spatial Analysis Lab (SAL). These data are analyzed using a multi-model inferential, spatial econometrics approach. We also examine the distribution of vegetation within distinct market categories using Claritas' Potential Rating Index for Zipcode Markets (PRIZM™) database. These categories can be disaggregated, corresponding to the four social theories. We compare the econometric and categorical results for validation. Models associated with ecology of prestige theory are more effective for predicting the distribution of vegetation. This suggests that private, residential patterns of vegetation, reflecting the consumption of environmentally relevant goods and services, are associated with different lifestyles and lifestages. Further, our spatial and temporal analyses suggest that there are significant spatial and temporal dependencies that have theoretical and methodological implications for understanding urban ecological systems. These findings may have policy implications. Decision makers may need to consider how to most effectively reach different social groups in terms of messages and messengers in order to advance land management practices and achieve urban sustainability.
NASA Astrophysics Data System (ADS)
Hu, Haixin
This dissertation consists of two parts. The first part studies the sample selection and spatial models of housing price index using transaction data on detached single-family houses of two California metropolitan areas from 1990 through 2008. House prices are often spatially correlated due to shared amenities, or when the properties are viewed as close substitutes in a housing submarket. There have been many studies that address spatial correlation in the context of housing markets. However, none has used spatial models to construct housing price indexes at zip code level for the entire time period analyzed in this dissertation to the best of my knowledge. In this paper, I study a first-order autoregressive spatial model with four different weighing matrix schemes. Four sets of housing price indexes are constructed accordingly. Gatzlaff and Haurin (1997, 1998) study the sample selection problem in housing index by using Heckman's two-step method. This method, however, is generally inefficient and can cause multicollinearity problem. Also, it requires data on unsold houses in order to carry out the first-step probit regression. Maximum likelihood (ML) method can be used to estimate a truncated incidental model which allows one to correct for sample selection based on transaction data only. However, convergence problem is very prevalent in practice. In this paper I adopt Lewbel's (2007) sample selection correction method which does not require one to model or estimate the selection model, except for some very general assumptions. I then extend this method to correct for spatial correlation. In the second part, I analyze the U.S. gasoline market with a disequilibrium model that allows lagged-latent variables, endogenous prices, and panel data with fixed effects. Most existing studies (see the survey of Espey, 1998, Energy Economics) of the gasoline market assume equilibrium. In practice, however, prices do not always adjust fast enough to clear the market. Equilibrium assumptions greatly simplify statistical inference, but are very restrictive and can produce conflicting estimates. For example, econometric models of markets that assume equilibrium often produce more elastic demand price elasticity than their disequilibrium counterparts (Holt and Johnson, 1989, Review of Economics and Statistics, Oczkowski, 1998, Economics Letters). The few studies that allow disequilibrium, however, have been limited to macroeconomic time-series data without lagged-latent variables. While time series data allows one to investigate national trends, it cannot be used to identify and analyze regional differences and the role of local markets. Exclusion of the lagged-latent variables is also undesirable because such variables capture adjustment costs and inter-temporal spillovers. Simulation methods offer tractable solutions to dynamic and panel data disequilibrium models (Lee, 1997, Journal of Econometrics), but assume normally distributed errors. This paper compares estimates of price/income elasticity and excess supply/demand across time periods, regions, and model specifications, using both equilibrium and disequilibrium methods. In the equilibrium model, I compare the within group estimator with Anderson and Hsiao's first-difference 2SLS estimator. In the disequilibrium model, I extend Amemiya's 2SLS by using Newey's efficient estimator with optimal instruments.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Iledare, O.O.; Pulsipher, A.G.; Baumann, R.H.
1996-12-31
The current expanded role of smaller independent oil producers in the OCS has led to concern about the possibility of increased risk of accidents in E&P operations on the Gulf of Mexico OCS. In addition, questions have been posed concerning the effects of the Minerals Management Service`s (MMS) safety regulations and inspection program, firm size, and industry practices on the risk of accidents in E&P operations on the Gulf of Mexico OCS. The specific purposes of the study reported in this paper were to ascertain (1) whether any empirical justification exists for the widespread concern that an increase in independentsmore » relative share of E&P operations in the Gulf OCS region will be detrimental to safety, and (2) whether MMS policies and safety programs have reduced the frequency or severity of accidents on the OCS. Our statistical and descriptive analyses of data on accidents from MMS provide no statistical evidence to support the apprehension that an expanded role for independents in E&P activity constitutes any major threat to safety on the OCS. Further, the results of our econometrics analysis confirm the expectation that the more effective MMS inspectors are at detecting incidents of noncompliance the lower the rate of accidents on the OCS is, ceteris paribus. In addition the results indicate that the variability in platform exposure years--cumulative age of operating platform--in comparison to other factors explains a significant portion of the variation in accidents per operating platform. That is, the platform aging process provides more opportunity for accidents than any other contributing factors. Our econometrics analysis also suggests that, if the other factors contributing to offshore accidents are held constant, the responsiveness of accident rate to drilling activity is inelastic while the response of accident rate to production activity levels is elastic.« less
DOT National Transportation Integrated Search
2015-12-01
We develop an econometric framework for incorporating spatial dependence in integrated model systems of latent variables and multidimensional mixed data outcomes. The framework combines Bhats Generalized Heterogeneous Data Model (GHDM) with a spat...
SPATIAL STATISTICS AND ECONOMETRICS FOR MODELS IN FISHERIES ECONOMICS. (R828012)
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...
A Framework for Restructuring the Military Retirement System
2013-07-01
Associate Professor of Economics in the Social Sciences Department at West Point where he teaches econometrics and labor economics. His areas of...others worth considering, but each should be carefully benchmarked against our proposed framework. 25 ENDNOTES 1. Office of the Actuary , Statistical
Federal Register 2010, 2011, 2012, 2013, 2014
2013-10-23
... the set of risk factors whose behavior is included in the econometric models underlying STANS, time series of proportional changes in implied volatilities for a range of tenors and in-the-money and out-of...
Eliminating Problems Caused by Multicollinearity: A Warning.
ERIC Educational Resources Information Center
Kennedy, Peter E.
1982-01-01
Explains why an econometric practice introduced by J.C. Soper cannot eliminate the problems caused by multicollinearity. The author suggests that it can be a useful technique in that it forces researchers to pay more attention to the specifications of their models. (AM)
Drug target inference through pathway analysis of genomics data
Ma, Haisu; Zhao, Hongyu
2013-01-01
Statistical modeling coupled with bioinformatics is commonly used for drug discovery. Although there exist many approaches for single target based drug design and target inference, recent years have seen a paradigm shift to system-level pharmacological research. Pathway analysis of genomics data represents one promising direction for computational inference of drug targets. This article aims at providing a comprehensive review on the evolving issues is this field, covering methodological developments, their pros and cons, as well as future research directions. PMID:23369829
NASA Astrophysics Data System (ADS)
Bock, Mark Joseph
Demand-side management (DSM), defined as the "planning, implementation, and monitoring of utility activities designed to encourage consumers to modify their pattern of electricity usage, including the timing and level of electricity demand," is a relatively new concept in the U.S. electric power industry. Nevertheless, in twenty years since it was first introduced, utility expenditures on DSM programs, as well as the number of such programs, have grown rapidly. At first glance, it may seem peculiar that a firm would actively attempt to reduce demand for its primary product. There are two primary explanations as to why a utility might pursue DSM: regulatory mandate, and self-interest. The purpose of this dissertation is to determine the impact these influences have on the amount of DSM undertaken by utilities. This research is important for two reasons. First, it provides insight into whether DSM will continue to exist as competition becomes more prevalent in the industry. Secondly, it is important because no one has taken a comprehensive look at firm-level DSM activity on an industry-wide basis. The primary data set used in this dissertation is the U.S. Department of Energy's Annual Electric Utility Report, Form EIA-861, which represents the most comprehensive data set available for analyzing DSM activity in the U.S. There are four measures of DSM activity in this data set: (1) utility expenditures on DSM programs; (2) energy savings by DSM program participants; and (3) the actual and (4) the potential reductions in peak load resulting from utility DSM measures. Each is used as the dependent variable in an econometric analysis where independent variables include various utility characteristics, regulatory characteristics, and service territory and customer characteristics. In general, the results from the econometric analysis suggest that in 1993, DSM activity was primarily the result of regulatory pressure. All of the evidence suggests that if DSM continues to exist in a deregulated environment, it will be at a greatly reduced level. This conclusion holds unless utilities see advantages to DSM as a marketing tool to increase customer satisfaction and loyalty.
Generality in nanotechnologies and its relationship to economic performance
NASA Astrophysics Data System (ADS)
Gomez Baquero, Fernando
In the history if economic analysis there is perhaps no more important question than the one of how economic development is achieved. For more than a century, economists have explored the role of technology in economic growth but there is still much to be learned about the effect that technologies, in particular emerging ones, have on economic growth and productivity. The objective of this research is to understand the relationship between nanotechnologies and economic growth and productivity, using the theory of General Purpose Technology (GPT)-driven economic growth. To do so, the Generality Index (calculated from patent data) was used to understand the relative pervasiveness of nanotechnologies. The analysis of trends and patterns of Generality Index, using the largest group of patents since the publication of the NBER Patent Database, indicates that nanotechnologies possess a higher average Generality than other technological groups. Next, the relationship between the Generality Index and Total Factor Productivity (TFP) was studied using econometric analysis. Model estimates indicate that the variation in Generality for the group of nanotechnologies can explain a large proportion of the variation in TFP. However, the explanatory power of the entire set of patents (not just nanotechnologies) is larger and corresponds better to the expected theoretical models. Additionally, there is a negative short-run relationship between Generality and TFP, conflicting with part of the theoretical GPT-models. Finally, the relationship between the Generality of nanotechnologies and policy-driven investment events, such as R&D investments and grant awards, was studied using econometric methods. The statistical evidence suggests that NSF awards are related to technologies with higher Generality, while NIH awards and NNI investments are related to a lower average Generality. Overall, results of this research work indicate that the introduction of pervasive technologies into an economic system sets in motion an interesting series of events that can both increase and decrease productivity and therefore economic growth. The metrics and methods developed in this work emphasize the importance of developing and using new metrics for strategic decision making, both in the private sector and in the public sector.
NASA Astrophysics Data System (ADS)
Bandres Motola, Miguel A.
Essay one estimates changes in small business customer energy consumption (kWh) patterns resulting from a seasonally differentiated pricing structure. Econometric analysis leverages cross-sectional time series data across the entire population of affected customers, from 2007 through the present. Observations include: monthly energy usage (kWh), relevant customer segmentations, local daily temperature, energy price, and region-specific economic conditions, among other variables. The study identifies the determinants of responsiveness to seasonal price differentiation. In addition, estimated energy consumption changes occurring during the 2010 summer season are reported for the average customer and in aggregate grouped by relevant customer segments, climate zone, and total customer base. Essay two develops an econometric modeling methodology to evaluate load impacts for short duration demand response events. The study analyzes time series data from a season of direct load control program tests aimed at integrating demand response into the wholesale electricity market. I have combined "fuzzy logic" with binary variables to create "fuzzy indicator variables" that allow for measurement of short duration events while using industry standard model specifications. Typically, binary variables for every hour are applied in load impact analysis of programs dispatched in hourly intervals. As programs evolve towards integration with the wholesale market, event durations become irregular and often occur for periods of only a few minutes. This methodology is innovative in that it conserves the degrees of freedom in the model while allowing for analysis of high frequency data using fixed effects. Essay three examines the effects of strategies, intangibles, and FDA news on the stocks of young biopharmaceutical firms. An event study methodology is used to explore those effects. This study investigates 20,839 announcements from 1990 to 2005. Announcements on drug development, alliances, publications, presentations, and FDA approval have a positive effect on the short-term performance of young biopharmaceutical firms. Announcements on goals not met, FDA drug approval denied, and changes in structural organizations have a negative effect on the short-term performance of young biopharmaceutical firms.
Adaptability of Irrigation to a Changing Monsoon in India: How far can we go?
NASA Astrophysics Data System (ADS)
Zaveri, E.; Grogan, D. S.; Fisher-Vanden, K.; Frolking, S. E.; Wrenn, D. H.; Nicholas, R.
2014-12-01
Agriculture and the monsoon are inextricably linked in India. A large part of the steady rise in agricultural production since the onset of the Green Revolution in the 1960's has been attributed to irrigation. Irrigation is used to supplement and buffer crops against precipitation shocks, but water availability for such use is itself sensitive to the erratic, seasonal and spatially heterogeneous nature of the monsoon. We provide new evidence on the relationship between monsoon changes, irrigation variability and water availability by linking a process based hydrology model with an econometric model for one of the world's most water stressed countries. India uses more groundwater for irrigation than any other country, and there is substantial evidence that this has led to depletion of groundwater aquifers. First, we build an econometric model of historical irrigation decisions using detailed agriculture and weather data spanning 35 years. Multivariate regression models reveal that for crops grown in the wet season, irrigation is sensitive to distribution and total monsoon rainfall but not to ground or surface water availability. For crops grown in the dry season, total monsoon rainfall matters most, and its effect is sensitive to groundwater availability. The historical estimates from the econometric model are used to calculate future irrigated areas under three different climate model predictions of monsoon climate for the years 2010 - 2050. These projections are then used as input to a physical hydrology model, which quantifies supply of irrigation water from sustainable sources such as rechargeable shallow groundwater, rivers and reservoirs, to unsustainable sources such as non- rechargeable groundwater. We find that the significant variation in monsoon projections lead to very different results. Crops grown in the dry season show particularly divergent trends between model projections, leading to very different groundwater resource requirements.
The Role of Probability-Based Inference in an Intelligent Tutoring System.
ERIC Educational Resources Information Center
Mislevy, Robert J.; Gitomer, Drew H.
Probability-based inference in complex networks of interdependent variables is an active topic in statistical research, spurred by such diverse applications as forecasting, pedigree analysis, troubleshooting, and medical diagnosis. This paper concerns the role of Bayesian inference networks for updating student models in intelligent tutoring…
Application of Transformations in Parametric Inference
ERIC Educational Resources Information Center
Brownstein, Naomi; Pensky, Marianna
2008-01-01
The objective of the present paper is to provide a simple approach to statistical inference using the method of transformations of variables. We demonstrate performance of this powerful tool on examples of constructions of various estimation procedures, hypothesis testing, Bayes analysis and statistical inference for the stress-strength systems.…
Education And Gender Bias in the Sex Ratio At Birth: Evidence From India
ECHÁVARRI, REBECA A.; EZCURRA, ROBERTO
2010-01-01
This article investigates the possible existence of a nonlinear link between female disadvantage in natality and education. To this end, we devise a theoretical model based on the key role of social interaction in explaining people’s acquisition of preferences, which justifies the existence of a nonmonotonic relationship between female disadvantage in natality and education. The empirical validity of the proposed model is examined for the case of India, using district-level data. In this context, our econometric analysis pays particular attention to the role of spatial dependence to avoid any potential problems of misspecification. The results confirm that the relationship between the sex ratio at birth and education in India follows an inverted U-shape. This finding is robust to the inclusion of additional explanatory variables in the analysis, and to the choice of the spatial weight matrix used to quantify the spatial interdependence between the sample districts. PMID:20355693
Education and gender bias in the sex ratio at birth: evidence from India.
Echávarri, Rebeca A; Ezcurra, Roberto
2010-02-01
This article investigates the possible existence of a nonlinear link between female disadvantage in natality and education. To this end, we devise a theoretical model based on the key role of social interaction in explaining people's acquisition of preferences, which justifies the existence of a nonmonotonic relationship between female disadvantage in natality and education. The empirical validity of the proposed model is examined for the case of India, using district-level data. In this context, our econometric analysis pays particular attention to the role of spatial dependence to avoid any potential problems of misspecification. The results confirm that the relationship between the sex ratio at birth and education in India follows an inverted U-shape. This finding is robust to the inclusion of additional explanatory variables in the analysis, and to the choice of the spatial weight matrix used to quantify the spatial interdependence between the sample districts.
[Between fetishism and survival: are scientific articles a form of academic merchandise?].
Castiel, Luis David; Sanz-Valero, Javier
2007-12-01
This article discusses the possible meanings of the intense prevailing concern in academic circles over the notion of research productivity, as reflected in an excess number of articles published in various scientific journals. The numerical accounting of articles published by researchers in scientific journals with renowned academic status serves to legitimize academics in their fields of work, in various ways. In this sense, we suggest that scientific articles take on aspects of merchandise-as-fetish, according to Marx's theory of use-value and exchange-value and Benjamin's exposure value. Meanwhile, the biological notions of selection and evolution are used as metaphorical elements in "bibliographic Darwinism". There are references as to the possibility many of the prevailing bibliometric concerns serve as instruments for econometric analysis, especially to orient and enhance cost-effectiveness analysis in research investments of various orders and types, from the point of view of their economic return.
Journal of Air Transportation, Volume 8, No. 2. Volume 8, No. 2
NASA Technical Reports Server (NTRS)
Bowen, Brent (Editor); Kabashkin, Igor (Editor); Nickerson, Jocelyn (Editor)
2003-01-01
The mission of the Journal of Air Transportation (JAT) is to provide the global community immediate key resource information in all areas of air transportation. This journal contains articles on the following:Fuel Consumption Modeling of a Transport Category Aircraft: A FlightOperationsQualityAssurance (F0QA) Analysis;Demand for Air Travel in the United States: Bottom-Up Econometric Estimation and Implications for Forecasts by Origin and Destination Pairs;Blind Flying on the Beam: Aeronautical Communication, Navigation and Surveillance: Its Origins and the Politics of Technology: Part I1 Political Oversight and Promotion;Blind Flying on the Beam: Aeronautical Communication, Navigation and Surveillance: Its Origins and the Politics of Technology: Part 111: Emerging Technologies;Ethics Education in University Aviation Management Programs in the US: Part Two B-Statistical Analysis of Current Practice;Integrating Human Factors into the Human-computer Interface: and How Best to Display Meteorological Information for Critical Aviation Decision-making and Performance.
Shin, Junha; Lee, Insuk
2015-01-01
Phylogenetic profiling, a network inference method based on gene inheritance profiles, has been widely used to construct functional gene networks in microbes. However, its utility for network inference in higher eukaryotes has been limited. An improved algorithm with an in-depth understanding of pathway evolution may overcome this limitation. In this study, we investigated the effects of taxonomic structures on co-inheritance analysis using 2,144 reference species in four query species: Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, and Homo sapiens. We observed three clusters of reference species based on a principal component analysis of the phylogenetic profiles, which correspond to the three domains of life—Archaea, Bacteria, and Eukaryota—suggesting that pathways inherit primarily within specific domains or lower-ranked taxonomic groups during speciation. Hence, the co-inheritance pattern within a taxonomic group may be eroded by confounding inheritance patterns from irrelevant taxonomic groups. We demonstrated that co-inheritance analysis within domains substantially improved network inference not only in microbe species but also in the higher eukaryotes, including humans. Although we observed two sub-domain clusters of reference species within Eukaryota, co-inheritance analysis within these sub-domain taxonomic groups only marginally improved network inference. Therefore, we conclude that co-inheritance analysis within domains is the optimal approach to network inference with the given reference species. The construction of a series of human gene networks with increasing sample sizes of the reference species for each domain revealed that the size of the high-accuracy networks increased as additional reference species genomes were included, suggesting that within-domain co-inheritance analysis will continue to expand human gene networks as genomes of additional species are sequenced. Taken together, we propose that co-inheritance analysis within the domains of life will greatly potentiate the use of the expected onslaught of sequenced genomes in the study of molecular pathways in higher eukaryotes. PMID:26394049
Cocco, S; Monasson, R; Sessak, V
2011-05-01
We consider the problem of inferring the interactions between a set of N binary variables from the knowledge of their frequencies and pairwise correlations. The inference framework is based on the Hopfield model, a special case of the Ising model where the interaction matrix is defined through a set of patterns in the variable space, and is of rank much smaller than N. We show that maximum likelihood inference is deeply related to principal component analysis when the amplitude of the pattern components ξ is negligible compared to √N. Using techniques from statistical mechanics, we calculate the corrections to the patterns to the first order in ξ/√N. We stress the need to generalize the Hopfield model and include both attractive and repulsive patterns in order to correctly infer networks with sparse and strong interactions. We present a simple geometrical criterion to decide how many attractive and repulsive patterns should be considered as a function of the sampling noise. We moreover discuss how many sampled configurations are required for a good inference, as a function of the system size N and of the amplitude ξ. The inference approach is illustrated on synthetic and biological data.
Do Executives' Backgrounds Matter to IPO Investors? Evidence from the Life Science Industry
Chok, Jay; Qian, Jifeng
2013-01-01
In this study, we focus on the impact of senior executives' industry backgrounds on the amount of capital raised in the stock market. The primary contribution of the study entails applying the upper echelon theory to the initial public offering (IPO) phenomenon. Specifically, we hypothesize that the industry backgrounds of corporate executives affect the amount of capital that the firm raised in the primary stock market. We argue that the firm's future investment strategies are unobserved by the investors ex-ante and investors expect firms' investment strategies to be based on the executives' industry backgrounds. As a result, the executives' industry backgrounds influence the investors' expectations about what investment strategies the firm is likely to deploy. Furthermore, the above logic also suggests that executives of different industry backgrounds should prefer different investment strategies corresponding with demand for different amount of capital. As a result, we expect the industry backgrounds to covary with the capital raised from both the supply and demand perspectives. To test the hypotheses, we ran a reduced econometric model wherein the executives' background predicts the amount of capital raised. Regression analyses suggest that the capital raised is negatively associated with the number of senior executives with prior career experience in the healthcare and genomic sectors but positively associated with the number of senior executives with prior career experience in regulatory affairs. The results provide tentative support for the notion that investors infer corporate strategies from senior executives' industry backgrounds. PMID:23690920
Tan, Chuen Seng; Støer, Nathalie C; Chen, Ying; Andersson, Marielle; Ning, Yilin; Wee, Hwee-Lin; Khoo, Eric Yin Hao; Tai, E-Shyong; Kao, Shih Ling; Reilly, Marie
2017-01-01
The control of confounding is an area of extensive epidemiological research, especially in the field of causal inference for observational studies. Matched cohort and case-control study designs are commonly implemented to control for confounding effects without specifying the functional form of the relationship between the outcome and confounders. This paper extends the commonly used regression models in matched designs for binary and survival outcomes (i.e. conditional logistic and stratified Cox proportional hazards) to studies of continuous outcomes through a novel interpretation and application of logit-based regression models from the econometrics and marketing research literature. We compare the performance of the maximum likelihood estimators using simulated data and propose a heuristic argument for obtaining the residuals for model diagnostics. We illustrate our proposed approach with two real data applications. Our simulation studies demonstrate that our stratification approach is robust to model misspecification and that the distribution of the estimated residuals provides a useful diagnostic when the strata are of moderate size. In our applications to real data, we demonstrate that parity and menopausal status are associated with percent mammographic density, and that the mean level and variability of inpatient blood glucose readings vary between medical and surgical wards within a national tertiary hospital. Our work highlights how the same class of regression models, available in most statistical software, can be used to adjust for confounding in the study of binary, time-to-event and continuous outcomes.
Zou, Xiang; Azam, Muhammad; Islam, Talat; Zaman, Khalid
2016-02-01
The objective of the study is to examine the impact of environmental indicators and air pollution on "health" and "wealth" for the low-income countries. The study used a number of promising variables including arable land, fossil fuel energy consumption, population density, and carbon dioxide emissions that simultaneously affect the health (i.e., health expenditures per capita) and wealth (i.e., GDP per capita) of the low-income countries. The general representation for low-income countries has shown by aggregate data that consist of 39 observations from the period of 1975-2013. The study decomposes the data set from different econometric tests for managing robust inferences. The study uses temporal forecasting for the health and wealth model by a vector error correction model (VECM) and an innovation accounting technique. The results show that environment and air pollution is the menace for low-income countries' health and wealth. Among environmental indicators, arable land has the largest variance to affect health and wealth for the next 10-year period, while air pollution exerts the least contribution to change health and wealth of low-income countries. These results indicate the prevalence of war situation, where environment and air pollution become visible like "gun" and "bullet" for low-income countries. There are required sound and effective macroeconomic policies to combat with the environmental evils that affect the health and wealth of the low-income countries.
Do executives' backgrounds matter to IPO investors? Evidence from the life science industry.
Chok, Jay; Qian, Jifeng
2013-01-01
In this study, we focus on the impact of senior executives' industry backgrounds on the amount of capital raised in the stock market. The primary contribution of the study entails applying the upper echelon theory to the initial public offering (IPO) phenomenon. Specifically, we hypothesize that the industry backgrounds of corporate executives affect the amount of capital that the firm raised in the primary stock market. We argue that the firm's future investment strategies are unobserved by the investors ex-ante and investors expect firms' investment strategies to be based on the executives' industry backgrounds. As a result, the executives' industry backgrounds influence the investors' expectations about what investment strategies the firm is likely to deploy. Furthermore, the above logic also suggests that executives of different industry backgrounds should prefer different investment strategies corresponding with demand for different amount of capital. As a result, we expect the industry backgrounds to covary with the capital raised from both the supply and demand perspectives. To test the hypotheses, we ran a reduced econometric model wherein the executives' background predicts the amount of capital raised. Regression analyses suggest that the capital raised is negatively associated with the number of senior executives with prior career experience in the healthcare and genomic sectors but positively associated with the number of senior executives with prior career experience in regulatory affairs. The results provide tentative support for the notion that investors infer corporate strategies from senior executives' industry backgrounds.
The Determinants of College Student Retention
ERIC Educational Resources Information Center
Guerrero, Adam A.
2010-01-01
This study attempts to add to the college student dropout literature by examining persistence decisions at private, non-selective university using previously unstudied explanatory variables and advanced econometric methods. Three main contributions are provided. First, proprietary data obtained from a type of university that is underrepresented in…
47 CFR 1.363 - Introduction of statistical data.
Code of Federal Regulations, 2010 CFR
2010-10-01
... case of sample surveys, there shall be a clear description of the survey design, including the... evidence in common carrier hearing proceedings, including but not limited to sample surveys, econometric... description of the experimental design shall be set forth, including a specification of the controlled...
47 CFR 1.363 - Introduction of statistical data.
Code of Federal Regulations, 2013 CFR
2013-10-01
... case of sample surveys, there shall be a clear description of the survey design, including the... evidence in common carrier hearing proceedings, including but not limited to sample surveys, econometric... description of the experimental design shall be set forth, including a specification of the controlled...
47 CFR 1.363 - Introduction of statistical data.
Code of Federal Regulations, 2014 CFR
2014-10-01
... case of sample surveys, there shall be a clear description of the survey design, including the... evidence in common carrier hearing proceedings, including but not limited to sample surveys, econometric... description of the experimental design shall be set forth, including a specification of the controlled...
47 CFR 1.363 - Introduction of statistical data.
Code of Federal Regulations, 2012 CFR
2012-10-01
... case of sample surveys, there shall be a clear description of the survey design, including the... evidence in common carrier hearing proceedings, including but not limited to sample surveys, econometric... description of the experimental design shall be set forth, including a specification of the controlled...
47 CFR 1.363 - Introduction of statistical data.
Code of Federal Regulations, 2011 CFR
2011-10-01
... case of sample surveys, there shall be a clear description of the survey design, including the... evidence in common carrier hearing proceedings, including but not limited to sample surveys, econometric... description of the experimental design shall be set forth, including a specification of the controlled...
Analytic Methods for Adjusting Subjective Rating Schemes.
ERIC Educational Resources Information Center
Cooper, Richard V. L.; Nelson, Gary R.
Statistical and econometric techniques of correcting for supervisor bias in models of individual performance appraisal were developed, using a variant of the classical linear regression model. Location bias occurs when individual performance is systematically overestimated or underestimated, while scale bias results when raters either exaggerate…
USDA-ARS?s Scientific Manuscript database
An integrated foundation is presented to study the impacts of external forcings on irrigated agricultural systems. Individually, models are presented that simulate groundwater hydrogeology and econometric farm level crop choices and irrigated water use. The natural association between groundwater we...
New Insights into Signed Path Coefficient Granger Causality Analysis.
Zhang, Jian; Li, Chong; Jiang, Tianzi
2016-01-01
Granger causality analysis, as a time series analysis technique derived from econometrics, has been applied in an ever-increasing number of publications in the field of neuroscience, including fMRI, EEG/MEG, and fNIRS. The present study mainly focuses on the validity of "signed path coefficient Granger causality," a Granger-causality-derived analysis method that has been adopted by many fMRI researches in the last few years. This method generally estimates the causality effect among the time series by an order-1 autoregression, and defines a positive or negative coefficient as an "excitatory" or "inhibitory" influence. In the current work we conducted a series of computations from resting-state fMRI data and simulation experiments to illustrate the signed path coefficient method was flawed and untenable, due to the fact that the autoregressive coefficients were not always consistent with the real causal relationships and this would inevitablely lead to erroneous conclusions. Overall our findings suggested that the applicability of this kind of causality analysis was rather limited, hence researchers should be more cautious in applying the signed path coefficient Granger causality to fMRI data to avoid misinterpretation.
Demand for health care in Denmark: results of a national sample survey using contingent valuation.
Gyldmark, M; Morrison, G C
2001-10-01
In this paper we use willingness to pay (WTP) to elicit values for private insurance covering treatment for four different health problems. By way of obtaining these values, we test the viability of the contingent valuation method (CVM) and econometric techniques, respectively, as means of eliciting and analysing values from the general public. WTP responses from a Danish national sample survey, which was designed in accordance with existing guidelines, are analysed in terms of consistency and validity checks. Large numbers of zero responses are common in WTP studies, and are found here; therefore, the Heckman selectivity model and log-transformed OLS are employed. The selectivity model is rejected, but test results indicate that the lognormal model yields efficient and unbiased estimates. The results give confidence in the WTP estimates obtained and, more generally, in CVM as a means of valuing publicly provided goods and in econometrics as a tool for analysing WTP results containing many zero responses.
Waste production and regional growth of marine activities an econometric model.
Bramati, Maria Caterina
2016-11-15
Coastal regions are characterized by intense human activity and climatic pressures, often intensified by competing interests in the use of marine waters. To assess the effect of public spending on the regional economy, an econometric model is here proposed. Not only are the regional investment and the climatic risks included in the model, but also variables related to the anthropogenic pressure, such as population, economic activities and waste production. Feedback effects of economic and demographic expansion on the pollution of coastal areas are also considered. It is found that dangerous waste increases with growing shipping and transportation activities and with growing population density in non-touristic coastal areas. On the other hand, the amount of non-dangerous wastes increases with marine mining, defense and offshore energy production activities. However, lower waste production occurs in areas where aquaculture and touristic industry are more exploited, and accompanied by increasing regional investment in waste disposal. Copyright © 2016 Elsevier Ltd. All rights reserved.
Projected electric power demands for the Potomac Electric Power Company. Volume 1
DOE Office of Scientific and Technical Information (OSTI.GOV)
Estomin, S.; Kahal, M.
1984-03-01
This three-volume report presents the results of an econometric forecast of peak and electric power demands for the Potomac Electric Power Company (PEPCO) through the year 2002. Volume I describes the methodology, the results of the econometric estimations, the forecast assumptions and the calculated forecasts of peak demand and energy usage. Separate sets of models were developed for the Maryland Suburbs (Montgomery and Prince George's counties), the District of Columbia and Southern Maryland (served by a wholesale customer of PEPCO). For each of the three jurisdictions, energy equations were estimated for residential and commercial/industrial customers for both summer and wintermore » seasons. For the District of Columbia, summer and winter equations for energy sales to the federal government were also estimated. Equations were also estimated for street lighting and energy losses. Noneconometric techniques were employed to forecast energy sales to the Northern Virginia suburbs, Metrorail and federal government facilities located in Maryland.« less
Adaptive Elastic Net for Generalized Methods of Moments.
Caner, Mehmet; Zhang, Hao Helen
2014-01-30
Model selection and estimation are crucial parts of econometrics. This paper introduces a new technique that can simultaneously estimate and select the model in generalized method of moments (GMM) context. The GMM is particularly powerful for analyzing complex data sets such as longitudinal and panel data, and it has wide applications in econometrics. This paper extends the least squares based adaptive elastic net estimator of Zou and Zhang (2009) to nonlinear equation systems with endogenous variables. The extension is not trivial and involves a new proof technique due to estimators lack of closed form solutions. Compared to Bridge-GMM of Caner (2009), we allow for the number of parameters to diverge to infinity as well as collinearity among a large number of variables, also the redundant parameters set to zero via a data dependent technique. This method has the oracle property, meaning that we can estimate nonzero parameters with their standard limit and the redundant parameters are dropped from the equations simultaneously. Numerical examples are used to illustrate the performance of the new method.
NASA Astrophysics Data System (ADS)
Bowen, Eric
In this dissertation, I investigate the effectiveness of renewable policies and consider their impact on electricity markets. The common thread of this research is to understand how renewable policy incentivizes renewable generation and how the increasing share of generation from renewables affects generation from fossil fuels. This type of research is crucial for understanding whether policies to promote renewables are meeting their stated goals and what the unintended effects might be. To this end, I use econometric methods to examine how electricity markets are responding to an influx of renewable energy. My dissertation is composed of three interrelated essays. In Chapter 1, I employ recent scholarship in spatial econometrics to assess the spatial dependence of Renewable Portfolio Standards (RPS), a prominent state-based renewable incentive. In Chapter 2, I explore the impact of the rapid rise in renewable generation on short-run generation from fossil fuels. And in Chapter 3, I assess the impact of renewable penetration on coal plant retirement decisions.
NASA Astrophysics Data System (ADS)
Loomis, John
2003-04-01
Past recreation studies have noted that on-site or visitor intercept surveys are subject to over-sampling of avid users (i.e., endogenous stratification) and have offered econometric solutions to correct for this. However, past papers do not estimate the empirical magnitude of the bias in benefit estimates with a real data set, nor do they compare the corrected estimates to benefit estimates derived from a population sample. This paper empirically examines the magnitude of the recreation benefits per trip bias by comparing estimates from an on-site river visitor intercept survey to a household survey. The difference in average benefits is quite large, with the on-site visitor survey yielding 24 per day trip, while the household survey yields 9.67 per day trip. A simple econometric correction for endogenous stratification in our count data model lowers the benefit estimate to $9.60 per day trip, a mean value nearly identical and not statistically different from the household survey estimate.
Public budgets for energy RD&D and the effects on energy intensity and pollution levels.
Balsalobre, Daniel; Álvarez, Agustín; Cantos, José María
2015-04-01
This study, based on the N-shaped cubic model of the environmental Kuznets curve, analyzes the evolution of per capita greenhouse gas emissions (GHGpc) using not just economic growth but also public budgets dedicated to energy-oriented research development and demonstration (RD&D) and energy intensity. The empirical evidence, obtained from an econometric model of fixed effects for 28 OECD countries during 1994-2010, suggests that energy innovations help reduce GHGpc levels and mitigate the negative impact of energy intensity on environmental quality. When countries develop active energy RD&D policies, they can reduce both the rates of energy intensity and the level of GHGpc emissions. This paper incorporates a moderating variable to the econometric model that emphasizes the effect that GDP has on energy intensity. It also adds a variable that reflects the difference between countries that have made a greater economic effort in energy RD&D, which in turn corrects the GHG emissions resulting from the energy intensity of each country.
Children's weight and participation in organized sports.
Quinto Romani, Annette
2011-11-01
Literature dealing with the impact of organized sports on children's weight has been marked by a lack of consensus. A major weakness characterizing most of this research is a lack of proper measurement methods. This paper seeks to fill an important knowledge gap through careful application of econometric methods. Estimations are carried out using data on 1,400 children attending 6th grade in 2008 in the municipality of Aalborg, Denmark. We use standard ordinary least squares (OLS) and class fixed effects to explore the effect of sports participation on body mass index (BMI) as well as underweight, overweight and obesity. Results indicate that participation in organized sports reduced BMI by 2.1%. Likewise it reduced the likelihood of being overweight by 8.2 percentage points and obese by 3.1 percentage points. It is the unique dataset combined with econometric methods that distinguishes our contribution from that of others in the field, thereby offering new insight. Results using statistically sound methods suggest that participation in organized sports has a beneficial effect on children's weight.
The Probability Heuristics Model of Syllogistic Reasoning.
ERIC Educational Resources Information Center
Chater, Nick; Oaksford, Mike
1999-01-01
Proposes a probability heuristic model for syllogistic reasoning and confirms the rationality of this heuristic by an analysis of the probabilistic validity of syllogistic reasoning that treats logical inference as a limiting case of probabilistic inference. Meta-analysis and two experiments involving 40 adult participants and using generalized…
Hamann, Hanjo
2016-01-01
The (German) market for law professors fulfils the conditions for a hog cycle: In the short run, supply cannot be extended or limited; future law professors must be hired soon after they first present themselves, or leave the market; demand is inelastic. Using a comprehensive German dataset, we show that the number of market entries today is negatively correlated with the number of market entries eight years ago. This suggests short-sighted behavior of young scholars at the time when they decide to prepare for the market. Using our statistical model, we make out-of-sample predictions for the German academic market in law until 2020. PMID:27467518
Unequal Recovery? Federal Resource Distribution after a Midwest Flood Disaster
Muñoz, Cristina E.; Tate, Eric
2016-01-01
Following severe flooding in 2008, three Iowa communities acquired over 1000 damaged properties to support disaster recovery and mitigation. This research applies a distributive justice framework to analyze the distribution of disaster recovery funds for property acquisition. Two research questions drive the analysis: (1) how does recovery vary by acquisition funding source; and (2) what is the relationship between recovery and vulnerable populations? Through spatial econometric modeling, relative recovery is compared between two federal programs that funded the acquisitions, and across socially vulnerable populations. The results indicate both distributive and temporal inequalities in the allocation of federal recovery funds. In particular, Latino and elderly populations were associated with lower recovery rates. Recommendations for future research in flood recovery and acquisitions are provided. PMID:27196921
Unequal Recovery? Federal Resource Distribution after a Midwest Flood Disaster.
Muñoz, Cristina E; Tate, Eric
2016-05-17
Following severe flooding in 2008, three Iowa communities acquired over 1000 damaged properties to support disaster recovery and mitigation. This research applies a distributive justice framework to analyze the distribution of disaster recovery funds for property acquisition. Two research questions drive the analysis: (1) how does recovery vary by acquisition funding source; and (2) what is the relationship between recovery and vulnerable populations? Through spatial econometric modeling, relative recovery is compared between two federal programs that funded the acquisitions, and across socially vulnerable populations. The results indicate both distributive and temporal inequalities in the allocation of federal recovery funds. In particular, Latino and elderly populations were associated with lower recovery rates. Recommendations for future research in flood recovery and acquisitions are provided.
NASA Astrophysics Data System (ADS)
Alsing, Justin; Wandelt, Benjamin; Feeney, Stephen
2018-07-01
Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood assumptions or approximations. Likelihood-free inference generically involves simulating mock data and comparing to the observed data; this comparison in data space suffers from the curse of dimensionality and requires compression of the data to a small number of summary statistics to be tractable. In this paper, we use massive asymptotically optimal data compression to reduce the dimensionality of the data space to just one number per parameter, providing a natural and optimal framework for summary statistic choice for likelihood-free inference. Secondly, we present the first cosmological application of Density Estimation Likelihood-Free Inference (DELFI), which learns a parametrized model for joint distribution of data and parameters, yielding both the parameter posterior and the model evidence. This approach is conceptually simple, requires less tuning than traditional Approximate Bayesian Computation approaches to likelihood-free inference and can give high-fidelity posteriors from orders of magnitude fewer forward simulations. As an additional bonus, it enables parameter inference and Bayesian model comparison simultaneously. We demonstrate DELFI with massive data compression on an analysis of the joint light-curve analysis supernova data, as a simple validation case study. We show that high-fidelity posterior inference is possible for full-scale cosmological data analyses with as few as ˜104 simulations, with substantial scope for further improvement, demonstrating the scalability of likelihood-free inference to large and complex cosmological data sets.
Caley, Peter; Ramsey, David S L; Barry, Simon C
2015-01-01
A recent study has inferred that the red fox (Vulpes vulpes) is now widespread in Tasmania as of 2010, based on the extraction of fox DNA from predator scats. Heuristically, this inference appears at first glance to be at odds with the lack of recent confirmed discoveries of either road-killed foxes--the last of which occurred in 2006, or hunter killed foxes--the most recent in 2001. This paper demonstrates a method to codify this heuristic analysis and produce inferences consistent with assumptions and data. It does this by formalising the analysis in a transparent and repeatable manner to make inference on the past, present and future distribution of an invasive species. It utilizes Approximate Bayesian Computation to make inferences. Importantly, the method is able to inform management of invasive species within realistic time frames, and can be applied widely. We illustrate the technique using the Tasmanian fox data. Based on the pattern of carcass discoveries of foxes in Tasmania, we infer that the population of foxes in Tasmania is most likely extinct, or restricted in distribution and demographically weak as of 2013. It is possible, though unlikely, that that population is widespread and/or demographically robust. This inference is largely at odds with the inference from the predator scat survey data. Our results suggest the chances of successfully eradicating the introduced red fox population in Tasmania may be significantly higher than previously thought.
Caley, Peter; Ramsey, David S. L.; Barry, Simon C.
2015-01-01
A recent study has inferred that the red fox (Vulpes vulpes) is now widespread in Tasmania as of 2010, based on the extraction of fox DNA from predator scats. Heuristically, this inference appears at first glance to be at odds with the lack of recent confirmed discoveries of either road-killed foxes—the last of which occurred in 2006, or hunter killed foxes—the most recent in 2001. This paper demonstrates a method to codify this heuristic analysis and produce inferences consistent with assumptions and data. It does this by formalising the analysis in a transparent and repeatable manner to make inference on the past, present and future distribution of an invasive species. It utilizes Approximate Bayesian Computation to make inferences. Importantly, the method is able to inform management of invasive species within realistic time frames, and can be applied widely. We illustrate the technique using the Tasmanian fox data. Based on the pattern of carcass discoveries of foxes in Tasmania, we infer that the population of foxes in Tasmania is most likely extinct, or restricted in distribution and demographically weak as of 2013. It is possible, though unlikely, that that population is widespread and/or demographically robust. This inference is largely at odds with the inference from the predator scat survey data. Our results suggest the chances of successfully eradicating the introduced red fox population in Tasmania may be significantly higher than previously thought. PMID:25602618
On the Ability To Infer Deficiency in Mathematics From Performance in Physics Using Hierarchies
ERIC Educational Resources Information Center
Riban, David M.
1971-01-01
Presents the procedures, results, and conclusions of a study designed to see if mathematical deficiencies can be inferred from PSSC students' performance by using a hierarchical model of requisite skills. Assuming inferences were possible, remediation was given. No effect due to remediation was observed but analysis indicated incidental learning…
Meta-learning framework applied in bioinformatics inference system design.
Arredondo, Tomás; Ormazábal, Wladimir
2015-01-01
This paper describes a meta-learner inference system development framework which is applied and tested in the implementation of bioinformatic inference systems. These inference systems are used for the systematic classification of the best candidates for inclusion in bacterial metabolic pathway maps. This meta-learner-based approach utilises a workflow where the user provides feedback with final classification decisions which are stored in conjunction with analysed genetic sequences for periodic inference system training. The inference systems were trained and tested with three different data sets related to the bacterial degradation of aromatic compounds. The analysis of the meta-learner-based framework involved contrasting several different optimisation methods with various different parameters. The obtained inference systems were also contrasted with other standard classification methods with accurate prediction capabilities observed.
Middle School Learners' Use of Latin Roots to Infer the Meaning of Unfamiliar Words
ERIC Educational Resources Information Center
Crosson, Amy C.; McKeown, Margaret G.
2016-01-01
This study investigated how middle school students leverage information about bound Latin roots (e.g., "voc" in "advocate" and "vociferous") to infer meanings of unfamiliar words, and how instruction may facilitate morphological analysis using roots. A dynamic assessment of morphological analysis was administered to…
DOT National Transportation Integrated Search
2011-09-01
This paper will describe an integrated approach to documenting and quantifying the impacts of bypasses : on small communities, with a focus on what economic impacts, if any, occur, and how these impacts : change over time. Two similarly sized communi...
Energy Models and the Policy Process.
ERIC Educational Resources Information Center
De Man, Reinier
1983-01-01
Describes the function of econometric and technological models in the policy process, and shows how different positions in the Dutch energy discussion are reflected by the application of different model methodologies. Discussion includes the energy policy context, a conceptual framework for using energy models, and energy scenarios in policy…
The Ontology of Science Teaching in the Neoliberal Era
ERIC Educational Resources Information Center
Sharma, Ajay
2017-01-01
Because of ever stricter standards of accountability, science teachers are under an increasing and unrelenting pressure to demonstrate the effects of their teaching on student learning. Econometric perspectives of "teacher quality" have become normative in assessment of teachers' work for accountability purposes. These perspectives seek…
Evaluating the Flipped Classroom: A Randomized Controlled Trial
ERIC Educational Resources Information Center
Wozny, Nathan; Balser, Cary; Ives, Drew
2018-01-01
Despite recent interest in flipped classrooms, rigorous research evaluating their effectiveness is sparse. In this study, the authors implement a randomized controlled trial to evaluate the effect of a flipped classroom technique relative to a traditional lecture in an introductory undergraduate econometrics course. Random assignment enables the…
Female-Male Earnings Differentials and Occupational Structure.
ERIC Educational Resources Information Center
Terrell, Katherine
1992-01-01
A review of econometric literature on female-male wage differences and asymmetrical distribution in occupations shows that differences in returns to human capital (i.e., discrimination) explains far more of the wage gap than differences in education and experience. Crowding of women into few occupations depresses wages. (SK)
Federal Register 2010, 2011, 2012, 2013, 2014
2011-03-01
..., econometrics, cognitive psychology, and computer science as they pertain to the full range of Census Bureau... technical expertise from the following disciplines: demography, economics, geography, psychology, statistics..., psychology, statistics, survey methodology, social and behavioral sciences, Information Technology, computing...
Effect of fare and travel time on the demand for domestic air transportation
NASA Technical Reports Server (NTRS)
Eriksen, S. E.; Liu, E. W.
1979-01-01
An econometric travel demand model was presented. The model was used for analyzing long haul domestic passenger markets in the United States. The results showed the sensitivities of demand to changes in fares and speed reflecting technology through more efficient aircraft designs.
Motor Vehicle Demand Models : Assessment of the State of the Art and Directions for Future Research
DOT National Transportation Integrated Search
1981-04-01
The report provides an assessment of the current state of motor vehicle demand modeling. It includes a detailed evaluation of one leading large-scale econometric vehicle demand model, which is tested for both logical consistency and forecasting accur...
Hurley, Daniel; Araki, Hiromitsu; Tamada, Yoshinori; Dunmore, Ben; Sanders, Deborah; Humphreys, Sally; Affara, Muna; Imoto, Seiya; Yasuda, Kaori; Tomiyasu, Yuki; Tashiro, Kosuke; Savoie, Christopher; Cho, Vicky; Smith, Stephen; Kuhara, Satoru; Miyano, Satoru; Charnock-Jones, D. Stephen; Crampin, Edmund J.; Print, Cristin G.
2012-01-01
Gene regulatory networks inferred from RNA abundance data have generated significant interest, but despite this, gene network approaches are used infrequently and often require input from bioinformaticians. We have assembled a suite of tools for analysing regulatory networks, and we illustrate their use with microarray datasets generated in human endothelial cells. We infer a range of regulatory networks, and based on this analysis discuss the strengths and limitations of network inference from RNA abundance data. We welcome contact from researchers interested in using our inference and visualization tools to answer biological questions. PMID:22121215
Sun, Junfeng; Li, Zhijun; Tong, Shanbao
2012-01-01
Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals. PMID:22577470
Vernazza, Christopher R; Wildman, John R; Steele, Jimmy G; Whitworth, John M; Walls, Angus W G; Perry, Ross; Matthews, Roger; Hahn, Petra; Donaldson, Cam
2015-08-01
Determining the value of, or strength of preference for health care interventions is useful for policy makers in planning health care services. Willingness to pay (WTP) is an established economic technique to determine the strength of preferences for interventions by eliciting monetary valuations from individuals in hypothetical situations. The objective of this study was to elicit WTP values for a dental preventive intervention and to analyze the factors affecting these as well as investigating the validity of the WTP method. Patients aged 40 years plus attending dental practices in the UK and Germany were recruited on a consecutive basis over one month. Participants received information about a novel root caries prevention intervention. They then completed a questionnaire including a WTP task. Where the coating was indicated, patients were offered this for a payment and acceptance was recorded. Analysis included econometric modelling and comparison of expected (based on stated WTP) versus actual behaviour. The mean WTP for the coating was £96.41 (standard deviation 60.61). Econometric models showed that no demographic or dental history factors were significant predictors of WTP. 63% of the sample behaved as expected when using stated WTP to predict whether they would buy the coating. The remainder were split almost equally between those expected to pay but who did not and those who were expected to refuse but paid. Values for a caries preventive intervention had a large and unpredictable variance. In comparing hypothetical versus real preferences both under- and over-valuation occurs. Wide and unpredictable variation in valuations for prevention may mean that there are difficult policy questions around what resource should be allocated to dental prevention and how to target this resource. Copyright © 2015 Elsevier Ltd. All rights reserved.
HUMAN DECISIONS AND MACHINE PREDICTIONS.
Kleinberg, Jon; Lakkaraju, Himabindu; Leskovec, Jure; Ludwig, Jens; Mullainathan, Sendhil
2018-02-01
Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the variable the algorithm predicts; for instance, judges may care specifically about violent crimes or about racial inequities. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: one policy simulation shows crime reductions up to 24.7% with no change in jailing rates, or jailing rate reductions up to 41.9% with no increase in crime rates. Moreover, all categories of crime, including violent crimes, show reductions; and these gains can be achieved while simultaneously reducing racial disparities. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals. JEL Codes: C10 (Econometric and statistical methods and methodology), C55 (Large datasets: Modeling and analysis), K40 (Legal procedure, the legal system, and illegal behavior).
HUMAN DECISIONS AND MACHINE PREDICTIONS*
Kleinberg, Jon; Lakkaraju, Himabindu; Leskovec, Jure; Ludwig, Jens; Mullainathan, Sendhil
2018-01-01
Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the variable the algorithm predicts; for instance, judges may care specifically about violent crimes or about racial inequities. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: one policy simulation shows crime reductions up to 24.7% with no change in jailing rates, or jailing rate reductions up to 41.9% with no increase in crime rates. Moreover, all categories of crime, including violent crimes, show reductions; and these gains can be achieved while simultaneously reducing racial disparities. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals. JEL Codes: C10 (Econometric and statistical methods and methodology), C55 (Large datasets: Modeling and analysis), K40 (Legal procedure, the legal system, and illegal behavior) PMID:29755141
García-Martín, Guillermina; Martín-Reyes, Guillermina; Dawid-Milner, Marc Stefan; Chamorro-Muñoz, M Isabel; Pérez-Errazquin, Francisco; Romero-Acebal, Manuel
2013-05-16
Epilepsy is a chronic illness that requires a long-term periodic follow-up of the patient and this means that as time goes by the number of patients attended increases, with the ensuing added cost for the healthcare system. To determine the factors involved in the time until an epileptic patient's next visit. Our sample consisted of a selection of patients who visited the epilepsy clinic at our hospital consecutively during one year. Their clinical situation and relationship with the medical advice they were given, together with the factors involved in the time elapsed until the next visit, were analysed by means of predictive econometric models. There is a clear association between the patient's clinical situation and the modification of the treatment proposed by the neurologist in the previous visit. The factors involved in the time until the next visit were the frequency of seizures, adverse side effects from medicines -above all those that affect cognition- and the medical advice given to the patient. Polytherapy, psychoaffective disorders or the patient's social situation were not found to be significant. Follow-up visits in a specific epilepsy clinic improves the patient's situation. This is the first analysis of the demand for healthcare in patients with epilepsy conducted by means of econometric methods and from a mixed physician-patient perspective. Since the factors that determine the time until the next visit can be modified, the number of visits per year could be reduced, thus improving patients' clinical situation. We suggest a greater amount of time should be spent per visit so as to be able to have a bearing on it and thereby cut costs in the long term.
Komen, Kibii; Olwoch, Jane; Rautenbach, Hannes; Botai, Joel; Adebayo, Adetunji
2015-03-01
Malaria in Limpopo Province of South Africa is shifting and now observed in originally non-malaria districts, and it is unclear whether climate change drives this shift. This study examines the distribution of malaria at district level in the province, determines direction and strength of the linear relationship and causality between malaria with the meteorological variables (rainfall and temperature) and ascertains their short- and long-run variations. Spatio-temporal method, Correlation analysis and econometric methods are applied. Time series monthly meteorological data (1998-2007) were obtained from South Africa Weather Services, while clinical malaria data came from Malaria Control Centre in Tzaneen (Limpopo Province) and South African Department of Health. We find that malaria changes and pressures vary in different districts with a strong positive correlation between temperature with malaria, r = 0.5212, and a weak positive relationship for rainfall, r = 0.2810. Strong unidirectional causality runs from rainfall and temperature to malaria cases (and not vice versa): F (1, 117) = 3.89, ρ = 0.0232 and F (1, 117) = 20.08, P < 0.001 and between rainfall and temperature, a bi-directional causality exists: F (1, 117) = 19.80; F (1,117) = 17.14, P < 0.001, respectively, meaning that rainfall affects temperature and vice versa. Results show evidence of strong existence of a long-run relationship between climate variables and malaria, with temperature maintaining very high level of significance than rainfall. Temperature, therefore, is more important in influencing malaria transmission in Limpopo Province.
Möser, Anke
2010-08-01
In Germany, the rising importance of out-of-home consumption, increasing usage of convenience products and decreasing knowledge of younger individuals how to prepare traditional dishes can be seen as obvious indicators for shifting patterns in food preparation. In this paper, econometric analyses are used to shed more light on the factors which may influence the time spent on food preparation in two-parent family households with children. Two time budget surveys, carried out 1991/92 and 2001/02 through the German National Statistical Office, provide the necessary data. Time budget data analyses reveal that over the last ten years the time spent on food preparation in Germany has decreased. The results point out that time resources of a household, for example gainful employment of the parents, significantly affect the amount of time spent on food preparation. The analysis confirms further that there is a more equal allocation of time spent on cooking, baking or laying the table between women and men in the last ten years. Due to changing attitudes and conceivably adaption of economic conditions, differences in time devoted to food preparation seem to have vanished between Eastern and Western Germany. Greater time spent on eating out in Germany as well as decreasing time spent on food preparation at home reveal that the food provisioning of families is no longer a primarily private task of the households themselves but needs more public attention and institutional offers and help. Among other points, the possibility of addressing mothers' lack of time as well as growing "food illiteracy" of children and young adults are discussed. 2010 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Harder, B.J.
1995-03-01
Louisiana wetlands require careful management to allow exploitation of non-renewable resources without destroying renewable resources. Current regulatory requirements have been moderately successful in meeting this goal by restricting development in wetland habitats. Continuing public emphasis on reducing environmental impacts of resource development is causing regulators to reassess their regulations and operators to rethink their compliance strategies. We examined the regulatory system and found that reducing the number of applications required by going to a single application process and having a coherent map of the steps required for operations in wetland areas would reduce regulatory burdens. Incremental changes can be mademore » to regulations to allow one agency to be the lead for wetland permitting at minimal cost to operators. Operators need cost effective means of access that will reduce environmental impacts, decrease permitting time, and limit future liability. Regulators and industry must partner to develop incentive based regulations that can provide significant environmental impact reduction for minimal economic cost. In addition regulators need forecasts of future E&P trends to estimate the impact of future regulations. To determine future activity we attempted to survey potential operators when this approach was unsuccessful we created two econometric models of north and south Louisiana relating drilling activity, success ratio, and price to predict future wetland activity. Results of the econometric models indicate that environmental regulations have a small but statistically significant effect on drilling operations in wetland areas of Louisiana. We examined current wetland practices and evaluated those practices comparing environmental versus economic costs and created a method for ranking the practices.« less
Santric-Milicevic, M; Vasic, V; Terzic-Supic, Z
2016-08-15
In times of austerity, the availability of econometric health knowledge assists policy-makers in understanding and balancing health expenditure with health care plans within fiscal constraints. The objective of this study is to explore whether the health workforce supply of the public health care sector, population number, and utilization of inpatient care significantly contribute to total health expenditure. The dependent variable is the total health expenditure (THE) in Serbia from the years 2003 to 2011. The independent variables are the number of health workers employed in the public health care sector, population number, and inpatient care discharges per 100 population. The statistical analyses include the quadratic interpolation method, natural logarithm and differentiation, and multiple linear regression analyses. The level of significance is set at P < 0.05. The regression model captures 90 % of all variations of observed dependent variables (adjusted R square), and the model is significant (P < 0.001). Total health expenditure increased by 1.21 standard deviations, with an increase in health workforce growth rate by 1 standard deviation. Furthermore, this rate decreased by 1.12 standard deviations, with an increase in (negative) population growth rate by 1 standard deviation. Finally, the growth rate increased by 0.38 standard deviation, with an increase of the growth rate of inpatient care discharges per 100 population by 1 standard deviation (P < 0.001). Study results demonstrate that the government has been making an effort to control strongly health budget growth. Exploring causality relationships between health expenditure and health workforce is important for countries that are trying to consolidate their public health finances and achieve universal health coverage at the same time.
Deduced Inference in the Analysis of Experimental Data
ERIC Educational Resources Information Center
Bird, Kevin D.
2011-01-01
Any set of confidence interval inferences on J - 1 linearly independent contrasts on J means, such as the two comparisons [mu][subscript 1] - [mu][subscript 2] and [mu][subscript 2] - [mu][subscript 3] on 3 means, provides a basis for the deduction of interval inferences on all other contrasts, such as the redundant comparison [mu][subscript 1] -…
Social networks help to infer causality in the tumor microenvironment.
Crespo, Isaac; Doucey, Marie-Agnès; Xenarios, Ioannis
2016-03-15
Networks have become a popular way to conceptualize a system of interacting elements, such as electronic circuits, social communication, metabolism or gene regulation. Network inference, analysis, and modeling techniques have been developed in different areas of science and technology, such as computer science, mathematics, physics, and biology, with an active interdisciplinary exchange of concepts and approaches. However, some concepts seem to belong to a specific field without a clear transferability to other domains. At the same time, it is increasingly recognized that within some biological systems--such as the tumor microenvironment--where different types of resident and infiltrating cells interact to carry out their functions, the complexity of the system demands a theoretical framework, such as statistical inference, graph analysis and dynamical models, in order to asses and study the information derived from high-throughput experimental technologies. In this article we propose to adopt and adapt the concepts of influence and investment from the world of social network analysis to biological problems, and in particular to apply this approach to infer causality in the tumor microenvironment. We showed that constructing a bidirectional network of influence between cell and cell communication molecules allowed us to determine the direction of inferred regulations at the expression level and correctly recapitulate cause-effect relationships described in literature. This work constitutes an example of a transfer of knowledge and concepts from the world of social network analysis to biomedical research, in particular to infer network causality in biological networks. This causality elucidation is essential to model the homeostatic response of biological systems to internal and external factors, such as environmental conditions, pathogens or treatments.
A Note on Verification of Computer Simulation Models
ERIC Educational Resources Information Center
Aigner, Dennis J.
1972-01-01
Establishes an argument that questions the validity of one test'' of goodness-of-fit (the extent to which a series of obtained measures agrees with a series of theoretical measures) for the simulated time path of a simple endogenous (internally developed) variable in a simultaneous, perhaps dynamic econometric model. (Author)
The Case of Effort Variables in Student Performance.
ERIC Educational Resources Information Center
Borg, Mary O.; And Others
1989-01-01
Tests the existence of a structural shift between above- and below-average students in the econometric models that explain students' grades in principles of economics classes. Identifies a structural shift and estimates separate models for above- and below-average students. Concludes that separate models as well as educational policies are…
77 FR 71788 - Notice of Change to the Publication of Natural Gas Wellhead Prices
Federal Register 2010, 2011, 2012, 2013, 2014
2012-12-04
... gas wellhead price using a time-series econometric model, which incorporates data from historical... (DOE). ACTION: Notice of a discontinuation of series in the publication of natural gas wellhead prices... price series. Beginning in January 2013, EIA will discontinue publishing wellhead prices, and will begin...
Duration Models to Analyze Dating Relationship: The Controversial Role of Gift Giving.
ERIC Educational Resources Information Center
Huang, Ming-Hui; Yu, Shihti
2000-01-01
Econometric duration models were used to analyze dating relationships of 225 college students. Using gifts to enhance the self, express love, and announce relationships helped ensure the success of relationships. Gifts that were too frequent or rare resulted in self-depreciation and anxiety and harmed relationships. (SK)
Teaching Students Not to Dismiss the Outermost Observations in Regressions
ERIC Educational Resources Information Center
Kasprowicz, Tomasz; Musumeci, Jim
2015-01-01
One econometric rule of thumb is that greater dispersion in observations of the independent variable improves estimates of regression coefficients and therefore produces better results, i.e., lower standard errors of the estimates. Nevertheless, students often seem to mistrust precisely the observations that contribute the most to this greater…
Impact of Education on the Income of Different Social Groups
ERIC Educational Resources Information Center
Yue, Changjun; Liu, Yanping
2007-01-01
This study investigates, statistically and econometrically, the income level, income inequality, education inequality, and the relationship between education and income of different social groups, on the basis of the Chinese Urban Household Survey conducted in 2005, the Gini coefficient and the quartile regression method. Research findings…
A Transactions Cost Economics Approach to Defense Acquisition Management
2006-12-30
A path-breaking econometric study (Masten et al., 1991) based on the procurement of components and services by a large naval shipbuilder indicates...philosophy with four formal levels of hierarchical IPTs—from project-level working groups to over- arching OSD-level “teams.” Key in the IPT concept is
Overskilling Dynamics and Education Pathways
ERIC Educational Resources Information Center
Mavromaras, Kostas; McGuinness, Seamus
2012-01-01
This paper uses panel data and econometric methods to estimate the incidence and the dynamic properties of overskilling among employed individuals. The paper begins by asking whether there is extensive overskilling in the labour market, and whether overskilling differs by education pathway. The answer to both questions is yes. The paper continues…
A Research-Based Development Economics Course for Undergraduates
ERIC Educational Resources Information Center
Singh, Prakarsh; Guo, Hongye; Morales, Alvaro
2015-01-01
The authors present details of a research-based course in development economics taught at a private liberal arts college. There were three key elements in this class: teaching of applied econometrics, group presentations reviewing published and working papers in development economics, and using concepts taught in class to write an original…
Value of Weather Information in Cranberry Marketing Decisions.
NASA Astrophysics Data System (ADS)
Morzuch, Bernard J.; Willis, Cleve E.
1982-04-01
Econometric techniques are used to establish a functional relationship between cranberry yields and important precipitation, temperature, and sunshine variables. Crop forecasts are derived from the model and are used to establish posterior probabilities to be used in a Bayesian decision context pertaining to leasing space for the storage of the berries.
University-Industry Research Collaboration: A Model to Assess University Capability
ERIC Educational Resources Information Center
Abramo, Giovanni; D'Angelo, Ciriaco Andrea; Di Costa, Flavia
2011-01-01
Scholars and policy makers recognize that collaboration between industry and the public research institutions is a necessity for innovation and national economic development. This work presents an econometric model which expresses the university capability for collaboration with industry as a function of size, location and research quality. The…
The Determinants of Girls' Educational Enrollment in Ghana. Working Paper.
ERIC Educational Resources Information Center
Johnson, Rebecca; Kyle, Steven
This study examined the determinants of school enrollment in Ghana, considering historical and social information to formulate an econometric model of school enrollment patterns for households. Data came from a 1989 survey of households in Ghana. The survey collected basic information about community characteristics, health and school facilities,…
USDA-ARS?s Scientific Manuscript database
An integrated foundation is presented to study the impacts of external forcings on irrigated agricultural systems. Individually, models are presented that simulate groundwater hydrogeology and econometric farm level crop choices and irrigated water use. The natural association between groundwater we...
Statistical Cost Estimation in Higher Education: Some Alternatives.
ERIC Educational Resources Information Center
Brinkman, Paul T.; Niwa, Shelley
Recent developments in econometrics that are relevant to the task of estimating costs in higher education are reviewed. The relative effectiveness of alternative statistical procedures for estimating costs are also tested. Statistical cost estimation involves three basic parts: a model, a data set, and an estimation procedure. Actual data are used…
USDA-ARS?s Scientific Manuscript database
The economic cost of achieving desired environmental outcomes from uniform and variable rate fertilizer application technologies depends both on market forces and agronomic properties. Using spatial econometric methods, we analyze the impact of nitrogen fertilizer supply by terrain attribute on the...
Data Analysis Techniques for Physical Scientists
NASA Astrophysics Data System (ADS)
Pruneau, Claude A.
2017-10-01
Preface; How to read this book; 1. The scientific method; Part I. Foundation in Probability and Statistics: 2. Probability; 3. Probability models; 4. Classical inference I: estimators; 5. Classical inference II: optimization; 6. Classical inference III: confidence intervals and statistical tests; 7. Bayesian inference; Part II. Measurement Techniques: 8. Basic measurements; 9. Event reconstruction; 10. Correlation functions; 11. The multiple facets of correlation functions; 12. Data correction methods; Part III. Simulation Techniques: 13. Monte Carlo methods; 14. Collision and detector modeling; List of references; Index.
USDA-ARS?s Scientific Manuscript database
Objective: To examine the risk factors of developing functional decline and make probabilistic predictions by using a tree-based method that allows higher order polynomials and interactions of the risk factors. Methods: The conditional inference tree analysis, a data mining approach, was used to con...
Dehmer, Matthias; Kurt, Zeyneb; Emmert-Streib, Frank; Them, Christa; Schulc, Eva; Hofer, Sabine
2015-01-01
In this paper, we investigate treatment cycles inferred from diabetes data by means of graph theory. We define the term treatment cycles graph-theoretically and perform a descriptive as well as quantitative analysis thereof. Also, we interpret our findings in terms of nursing and clinical management. PMID:26030296
Middle School Learners' Use of Latin Roots to Infer the Meaning of Unfamiliar Words
ERIC Educational Resources Information Center
Crosson, Amy C.; McKeown, Margaret G.
2016-01-01
This study investigated how middle school students leverage information about bound Latin roots (e.g., voc in "advocate" and "vociferous") to infer meanings of unfamiliar words, and how instruction may facilitate morphological analysis using roots. A dynamic assessment of morphological analysis was administered to 29 sixth…
Arc_Mat: a Matlab-based spatial data analysis toolbox
NASA Astrophysics Data System (ADS)
Liu, Xingjian; Lesage, James
2010-03-01
This article presents an overview of Arc_Mat, a Matlab-based spatial data analysis software package whose source code has been placed in the public domain. An earlier version of the Arc_Mat toolbox was developed to extract map polygon and database information from ESRI shapefiles and provide high quality mapping in the Matlab software environment. We discuss revisions to the toolbox that: utilize enhanced computing and graphing capabilities of more recent versions of Matlab, restructure the toolbox with object-oriented programming features, and provide more comprehensive functions for spatial data analysis. The Arc_Mat toolbox functionality includes basic choropleth mapping; exploratory spatial data analysis that provides exploratory views of spatial data through various graphs, for example, histogram, Moran scatterplot, three-dimensional scatterplot, density distribution plot, and parallel coordinate plots; and more formal spatial data modeling that draws on the extensive Spatial Econometrics Toolbox functions. A brief review of the design aspects of the revised Arc_Mat is described, and we provide some illustrative examples that highlight representative uses of the toolbox. Finally, we discuss programming with and customizing the Arc_Mat toolbox functionalities.
Summary and recommendations. [reduced gravitational effects on materials manufactured in space
NASA Technical Reports Server (NTRS)
1975-01-01
An economic analysis using econometric and cost benefit analysis techniques was performed to determine the feasibility of space processing of certain products. The overall objectives of the analysis were (1) to determine specific products or processes uniquely connected with space manufacturing, (2) to select a specific product or process from each of the areas of semiconductors, metals, and biochemicals, and (3) to determine the overall price/cost structure of each product or process considered. The economic elements of the analysis involved a generalized decision making format for analyzing space manufacturing, a comparative cost study of the selected processes in space vs. earth manufacturing, and a supply and demand study of the economic relationships of one of the manufacturing processes. Space processing concepts were explored. The first involved the use of the shuttle as the factory with all operations performed during individual flights. The second concept involved a permanent unmanned space factory which would be launched separately. The shuttle in this case would be used only for maintenance and refurbishment. Finally, some consideration was given to a permanent manned space factory.
Siciliani, Luigi
2006-01-01
Policy makers are increasingly interested in developing performance indicators that measure hospital efficiency. These indicators may give the purchasers of health services an additional regulatory tool to contain health expenditure. Using panel data, this study compares different parametric (econometric) and non-parametric (linear programming) techniques for the measurement of a hospital's technical efficiency. This comparison was made using a sample of 17 Italian hospitals in the years 1996-9. Highest correlations are found in the efficiency scores between the non-parametric data envelopment analysis under the constant returns to scale assumption (DEA-CRS) and several parametric models. Correlation reduces markedly when using more flexible non-parametric specifications such as data envelopment analysis under the variable returns to scale assumption (DEA-VRS) and the free disposal hull (FDH) model. Correlation also generally reduces when moving from one output to two-output specifications. This analysis suggests that there is scope for developing performance indicators at hospital level using panel data, but it is important that extensive sensitivity analysis is carried out if purchasers wish to make use of these indicators in practice.
The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.
Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J
2017-12-01
The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.
CADDIS Volume 4. Data Analysis: Biological and Environmental Data Requirements
Overview of PECBO Module, using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, methods for inferring environmental conditions, statistical scripts in module.
Relative evolutionary rate inference in HyPhy with LEISR.
Spielman, Stephanie J; Kosakovsky Pond, Sergei L
2018-01-01
We introduce LEISR (Likehood Estimation of Individual Site Rates, pronounced "laser"), a tool to infer relative evolutionary rates from protein and nucleotide data, implemented in HyPhy. LEISR is based on the popular Rate4Site (Pupko et al., 2002) approach for inferring relative site-wise evolutionary rates, primarily from protein data. We extend the original method for more general use in several key ways: (i) we increase the support for nucleotide data with additional models, (ii) we allow for datasets of arbitrary size, (iii) we support analysis of site-partitioned datasets to correct for the presence of recombination breakpoints, (iv) we produce rate estimates at all sites rather than at just a subset of sites, and (v) we implemented LEISR as MPI-enabled to support rapid, high-throughput analysis. LEISR is available in HyPhy starting with version 2.3.8, and it is accessible as an option in the HyPhy analysis menu ("Relative evolutionary rate inference"), which calls the HyPhy batchfile LEISR.bf.
NASA Astrophysics Data System (ADS)
Wilting, Jens; Lehnertz, Klaus
2015-08-01
We investigate a recently published analysis framework based on Bayesian inference for the time-resolved characterization of interaction properties of noisy, coupled dynamical systems. It promises wide applicability and a better time resolution than well-established methods. At the example of representative model systems, we show that the analysis framework has the same weaknesses as previous methods, particularly when investigating interacting, structurally different non-linear oscillators. We also inspect the tracking of time-varying interaction properties and propose a further modification of the algorithm, which improves the reliability of obtained results. We exemplarily investigate the suitability of this algorithm to infer strength and direction of interactions between various regions of the human brain during an epileptic seizure. Within the limitations of the applicability of this analysis tool, we show that the modified algorithm indeed allows a better time resolution through Bayesian inference when compared to previous methods based on least square fits.
A refined method for multivariate meta-analysis and meta-regression.
Jackson, Daniel; Riley, Richard D
2014-02-20
Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects' standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. Copyright © 2013 John Wiley & Sons, Ltd.
Causal inference in economics and marketing.
Varian, Hal R
2016-07-05
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference.
Aging and Predicting Inferences: A Diffusion Model Analysis
ERIC Educational Resources Information Center
McKoon, Gail; Ratcliff, Roger
2013-01-01
In the domain of discourse processing, it has been claimed that older adults (60-0-year-olds) are less likely to encode and remember some kinds of information from texts than young adults. The experiment described here shows that they do make a particular kind of inference to the same extent that college-age adults do. The inferences examined were…
Causal inference in economics and marketing
Varian, Hal R.
2016-01-01
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual—a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference. PMID:27382144
"Magnitude-based inference": a statistical review.
Welsh, Alan H; Knight, Emma J
2015-04-01
We consider "magnitude-based inference" and its interpretation by examining in detail its use in the problem of comparing two means. We extract from the spreadsheets, which are provided to users of the analysis (http://www.sportsci.org/), a precise description of how "magnitude-based inference" is implemented. We compare the implemented version of the method with general descriptions of it and interpret the method in familiar statistical terms. We show that "magnitude-based inference" is not a progressive improvement on modern statistics. The additional probabilities introduced are not directly related to the confidence interval but, rather, are interpretable either as P values for two different nonstandard tests (for different null hypotheses) or as approximate Bayesian calculations, which also lead to a type of test. We also discuss sample size calculations associated with "magnitude-based inference" and show that the substantial reduction in sample sizes claimed for the method (30% of the sample size obtained from standard frequentist calculations) is not justifiable so the sample size calculations should not be used. Rather than using "magnitude-based inference," a better solution is to be realistic about the limitations of the data and use either confidence intervals or a fully Bayesian analysis.
Comparison of Urban Human Movements Inferring from Multi-Source Spatial-Temporal Data
NASA Astrophysics Data System (ADS)
Cao, Rui; Tu, Wei; Cao, Jinzhou; Li, Qingquan
2016-06-01
The quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide human movements inferring from two types of spatial-temporal data at traffic analysis zone (TAZ) level. The first type of human movement is inferred from long-time smart card transaction data recording the boarding actions. The second type of human movement is extracted from citywide time sequenced mobile phone data with 30 minutes interval. Travel volume, travel distance and travel time are used to measure aggregated human movements in the city. To further examine the relationship between the two types of inferred movements, the linear correlation analysis is conducted on the hourly travel volume. The obtained results show that human movements inferred from smart card data and mobile phone data have a correlation of 0.635. However, there are still some non-ignorable differences in some special areas. This research not only reveals the citywide spatial-temporal human dynamic but also benefits the understanding of the reliability of the inference of human movements with big spatial-temporal data.
Steele, Vaughn R.; Bernat, Edward M.; van den Broek, Paul; Collins, Paul F.; Patrick, Christopher J.; Marsolek, Chad J.
2012-01-01
Successful comprehension during reading often requires inferring information not explicitly presented. This information is readily accessible when subsequently encountered, and a neural correlate of this is an attenuation of the N400 event-related potential (ERP). We used ERPs and time-frequency (TF) analysis to investigate neural correlates of processing inferred information after a causal coherence inference had been generated during text comprehension. Participants read short texts, some of which promoted inference generation. After each text, they performed lexical decisions to target words that were unrelated or inference-related to the preceding text. Consistent with previous findings, inference-related words elicited an attenuated N400 relative to unrelated words. TF analyses revealed unique contributions to the N400 from activity occurring at 1–6 Hz (theta) and 0–2 Hz (delta), supporting the view that multiple, sequential processes underlie the N400. PMID:23165117
Statistics for nuclear engineers and scientists. Part 1. Basic statistical inference
DOE Office of Scientific and Technical Information (OSTI.GOV)
Beggs, W.J.
1981-02-01
This report is intended for the use of engineers and scientists working in the nuclear industry, especially at the Bettis Atomic Power Laboratory. It serves as the basis for several Bettis in-house statistics courses. The objectives of the report are to introduce the reader to the language and concepts of statistics and to provide a basic set of techniques to apply to problems of the collection and analysis of data. Part 1 covers subjects of basic inference. The subjects include: descriptive statistics; probability; simple inference for normally distributed populations, and for non-normal populations as well; comparison of two populations; themore » analysis of variance; quality control procedures; and linear regression analysis.« less
Economic considerations for bariatric surgery and morbid obesity
Frezza, Eldo E; Wacthell, Mitchell; Ewing, Bradley
2009-01-01
The obesity epidemic is also an economic tragedy. This analysis evaluates the economic effects and the potential to improve the well-being of both individual and societal wealth. Econometric techniques should carefully assess the degree to which obesity affects declines in business output, employment, income, and tax revenues at the regional and national levels. Microeconomics assesses lost productivity and associated wages and profit. Macroeconomics assesses trends associated with employment, inflation, interest rates, money supply, and output. To decrease the adverse economic consequences of the obesity epidemic, policy makers must emphasize bariatric surgery as a cost-effective option for qualified patients. Early intervention, education, and tax rebates for obese individuals who undergo bariatric surgery and for medical centers and doctors would likely have positive economic effects on the whole economy in a few years. PMID:21935309
Application of conditional moment tests to model checking for generalized linear models.
Pan, Wei
2002-06-01
Generalized linear models (GLMs) are increasingly being used in daily data analysis. However, model checking for GLMs with correlated discrete response data remains difficult. In this paper, through a case study on marginal logistic regression using a real data set, we illustrate the flexibility and effectiveness of using conditional moment tests (CMTs), along with other graphical methods, to do model checking for generalized estimation equation (GEE) analyses. Although CMTs provide an array of powerful diagnostic tests for model checking, they were originally proposed in the econometrics literature and, to our knowledge, have never been applied to GEE analyses. CMTs cover many existing tests, including the (generalized) score test for an omitted covariate, as special cases. In summary, we believe that CMTs provide a class of useful model checking tools.
Economic considerations for bariatric surgery and morbid obesity.
Frezza, Eldo E; Wacthell, Mitchell; Ewing, Bradley
2009-01-01
The obesity epidemic is also an economic tragedy. This analysis evaluates the economic effects and the potential to improve the well-being of both individual and societal wealth. Econometric techniques should carefully assess the degree to which obesity affects declines in business output, employment, income, and tax revenues at the regional and national levels. Microeconomics assesses lost productivity and associated wages and profit. Macroeconomics assesses trends associated with employment, inflation, interest rates, money supply, and output. To decrease the adverse economic consequences of the obesity epidemic, policy makers must emphasize bariatric surgery as a cost-effective option for qualified patients. Early intervention, education, and tax rebates for obese individuals who undergo bariatric surgery and for medical centers and doctors would likely have positive economic effects on the whole economy in a few years.
MEDISE: A macroeconomic model for energy planning in Costa Rica
DOE Office of Scientific and Technical Information (OSTI.GOV)
Booth, S.R.; Leiva, C.L.
This report describes the development and results of MEDISE, an econometric macroeconomic model for energy planning in Costa Rica. The model is a simultaneous system of 19 equations that was constructed using ENERPLAN, an energy planning tool developed by the United Nations for use in developing countries. The equations were estimated using regression analysis on a data time series of 1966 to 1984. ENERPLAN's model solution package was used to obtain forecasts of 19 economic variables from 1985 to 2005. the modeling effort was conducted jointly by Los Alamos Central American Energy and Resources Project (CAP) personnel and the Energymore » Sector Directorate of Costa Rica during 1986. The CAP was funded by the US Agency for International Development. 6 refs., 3 figs., 11 tabs.« less
Modeling conflict : research methods, quantitative modeling, and lessons learned.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rexroth, Paul E.; Malczynski, Leonard A.; Hendrickson, Gerald A.
2004-09-01
This study investigates the factors that lead countries into conflict. Specifically, political, social and economic factors may offer insight as to how prone a country (or set of countries) may be for inter-country or intra-country conflict. Largely methodological in scope, this study examines the literature for quantitative models that address or attempt to model conflict both in the past, and for future insight. The analysis concentrates specifically on the system dynamics paradigm, not the political science mainstream approaches of econometrics and game theory. The application of this paradigm builds upon the most sophisticated attempt at modeling conflict as a resultmore » of system level interactions. This study presents the modeling efforts built on limited data and working literature paradigms, and recommendations for future attempts at modeling conflict.« less
The relation between global migration and trade networks
NASA Astrophysics Data System (ADS)
Sgrignoli, Paolo; Metulini, Rodolfo; Schiavo, Stefano; Riccaboni, Massimo
2015-01-01
In this paper we develop a methodology to analyze and compare multiple global networks, focusing our analysis on the relation between human migration and trade. First, we identify the subset of products for which the presence of a community of migrants significantly increases trade intensity, where to assure comparability across networks we apply a hypergeometric filter that lets us identify those links which intensity is significantly higher than expected. Next, proposing a new way to define country neighbors based on the most intense links in the trade network, we use spatial econometrics techniques to measure the effect of migration on international trade, while controlling for network interdependences. Overall, we find that migration significantly boosts trade across countries and we are able to identify product categories for which this effect is particularly strong.
NASA Astrophysics Data System (ADS)
Herrmann, K.
2009-11-01
Information-theoretic approaches still play a minor role in financial market analysis. Nonetheless, there have been two very similar approaches evolving during the last years, one in the so-called econophysics and the other in econometrics. Both generalize the notion of GARCH processes in an information-theoretic sense and are able to capture kurtosis better than traditional models. In this article we present both approaches in a more general framework. The latter allows the derivation of a wide range of new models. We choose a third model using an entropy measure suggested by Kapur. In an application to financial market data, we find that all considered models - with similar flexibility in terms of skewness and kurtosis - lead to very similar results.
Demand modelling of passenger air travel: An analysis and extension, volume 2
NASA Technical Reports Server (NTRS)
Jacobson, I. D.
1978-01-01
Previous intercity travel demand models in terms of their ability to predict air travel in a useful way and the need for disaggregation in the approach to demand modelling are evaluated. The viability of incorporating non-conventional factors (i.e. non-econometric, such as time and cost) in travel demand forecasting models are determined. The investigation of existing models is carried out in order to provide insight into their strong points and shortcomings. The model is characterized as a market segmentation model. This is a consequence of the strengths of disaggregation and its natural evolution to a usable aggregate formulation. The need for this approach both pedagogically and mathematically is discussed. In addition this volume contains two appendices which should prove useful to the non-specialist in the area.
Parallel imports and the pricing of pharmaceutical products: evidence from the European Union.
Ganslandt, Mattias; Maskus, Keith E
2004-09-01
We consider policy issues regarding parallel imports (PIs) of brand-name pharmaceuticals in the European Union, where such trade is permitted. We develop a simple model in which an original manufacturer competes in its home market with PI firms. The model suggests that for small trade costs the original manufacturer will accommodate the import decisions of parallel traders and that the price in the home market falls as the volume of parallel imports rises. Using data from Sweden we find that the prices of drugs subject to competition from parallel imports fell relative to other drugs over the period 1994-1999. Econometric analysis finds that parallel imports significantly reduced manufacturing prices, by 12-19%. There is evidence that this effect increases with multiple PI entrants.
Liu, Ning; Zhou, Lihua; Hauger, J Scott
2013-01-01
This paper undertakes a direct, comprehensive assessment of the long-term sustainability of desertification rehabilitation in China under a plausible but worst case scenario where governmental interventions, in the form of payments for environmental services (PES), will cease. The analysis is based on household behavior as well as experimental data. Our econometric results highlight the main obstacles to the sustainability of rehabilitation programs subsequent to cessation of government intervention, including specific shortfalls in households' preference for a free ride, budget constraints, attitudes, tolerance of and responsibility for desertification, and dissatisfaction with governmental actions. We conclude that desertification rehabilitation is not sustainable in China without continued governmental intervention. The results of this study are intended to support policy makers as they consider future directions for rehabilitation sustainability.
Overview of PECBO Module, using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, methods for inferring environmental conditions, statistical scripts in module.
Feinauer, Christoph; Procaccini, Andrea; Zecchina, Riccardo; Weigt, Martin; Pagnani, Andrea
2014-01-01
In the course of evolution, proteins show a remarkable conservation of their three-dimensional structure and their biological function, leading to strong evolutionary constraints on the sequence variability between homologous proteins. Our method aims at extracting such constraints from rapidly accumulating sequence data, and thereby at inferring protein structure and function from sequence information alone. Recently, global statistical inference methods (e.g. direct-coupling analysis, sparse inverse covariance estimation) have achieved a breakthrough towards this aim, and their predictions have been successfully implemented into tertiary and quaternary protein structure prediction methods. However, due to the discrete nature of the underlying variable (amino-acids), exact inference requires exponential time in the protein length, and efficient approximations are needed for practical applicability. Here we propose a very efficient multivariate Gaussian modeling approach as a variant of direct-coupling analysis: the discrete amino-acid variables are replaced by continuous Gaussian random variables. The resulting statistical inference problem is efficiently and exactly solvable. We show that the quality of inference is comparable or superior to the one achieved by mean-field approximations to inference with discrete variables, as done by direct-coupling analysis. This is true for (i) the prediction of residue-residue contacts in proteins, and (ii) the identification of protein-protein interaction partner in bacterial signal transduction. An implementation of our multivariate Gaussian approach is available at the website http://areeweb.polito.it/ricerca/cmp/code. PMID:24663061
Schaffter, Thomas; Marbach, Daniel; Floreano, Dario
2011-08-15
Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data. However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks. Here, we describe a novel and comprehensive method for in silico benchmark generation and performance profiling of network inference methods available to the community as an open-source software called GeneNetWeaver (GNW). In addition to the generation of detailed dynamical models of gene regulatory networks to be used as benchmarks, GNW provides a network motif analysis that reveals systematic prediction errors, thereby indicating potential ways of improving inference methods. The accuracy of network inference methods is evaluated using standard metrics such as precision-recall and receiver operating characteristic curves. We show how GNW can be used to assess the performance and identify the strengths and weaknesses of six inference methods. Furthermore, we used GNW to provide the international Dialogue for Reverse Engineering Assessments and Methods (DREAM) competition with three network inference challenges (DREAM3, DREAM4 and DREAM5). GNW is available at http://gnw.sourceforge.net along with its Java source code, user manual and supporting data. Supplementary data are available at Bioinformatics online. dario.floreano@epfl.ch.
Algorithm Optimally Orders Forward-Chaining Inference Rules
NASA Technical Reports Server (NTRS)
James, Mark
2008-01-01
People typically develop knowledge bases in a somewhat ad hoc manner by incrementally adding rules with no specific organization. This often results in a very inefficient execution of those rules since they are so often order sensitive. This is relevant to tasks like Deep Space Network in that it allows the knowledge base to be incrementally developed and have it automatically ordered for efficiency. Although data flow analysis was first developed for use in compilers for producing optimal code sequences, its usefulness is now recognized in many software systems including knowledge-based systems. However, this approach for exhaustively computing data-flow information cannot directly be applied to inference systems because of the ubiquitous execution of the rules. An algorithm is presented that efficiently performs a complete producer/consumer analysis for each antecedent and consequence clause in a knowledge base to optimally order the rules to minimize inference cycles. An algorithm was developed that optimally orders a knowledge base composed of forwarding chaining inference rules such that independent inference cycle executions are minimized, thus, resulting in significantly faster execution. This algorithm was integrated into the JPL tool Spacecraft Health Inference Engine (SHINE) for verification and it resulted in a significant reduction in inference cycles for what was previously considered an ordered knowledge base. For a knowledge base that is completely unordered, then the improvement is much greater.
Synthetic Indicators of Quality of Life in Europe
ERIC Educational Resources Information Center
Somarriba, Noelia; Pena, Bernardo
2009-01-01
For more than three decades now, sociologists, politicians and economists have used a wide range of statistical and econometric techniques to analyse and measure the quality of life of individuals with the aim of obtaining useful instruments for social, political and economic decision making. The aim of this paper is to analyse the advantages and…
Gender and Migration Background in Intergenerational Educational Mobility
ERIC Educational Resources Information Center
Schneebaum, Alyssa; Rumplmaier, Bernhard; Altzinger, Wilfried
2016-01-01
We employ 2011 European Union Statistics on Income and Living Conditions survey data for Austria to perform uni- and multivariate econometric analyses to study the role of gender and migration background (MB) in intergenerational educational mobility. We find that there is more persistence in the educational attainment of girls relative to their…
Gaming via Computer Simulation Techniques for Junior College Economics Education. Final Report.
ERIC Educational Resources Information Center
Thompson, Fred A.
A study designed to answer the need for more attractive and effective economics education involved the teaching of one junior college economics class by the conventional (lecture) method and an experimental class by computer simulation techniques. Econometric models approximating the "real world" were computer programed to enable the experimental…
ERIC Educational Resources Information Center
Cooper, Michelle Asha
2009-01-01
This study uses data from the Educational Longitudinal Study of 2002 to test a conceptual model that integrates aspects of sociological and econometric frameworks into a traditional status attainment model for educational aspirations. Using descriptive and logistic analyses, this study advanced understanding of the patterns and stability of…
Learning-Testing Process in Classroom: An Empirical Simulation Model
ERIC Educational Resources Information Center
Buda, Rodolphe
2009-01-01
This paper presents an empirical micro-simulation model of the teaching and the testing process in the classroom (Programs and sample data are available--the actual names of pupils have been hidden). It is a non-econometric micro-simulation model describing informational behaviors of the pupils, based on the observation of the pupils'…
Lessons in Reading Reform: Finding What Works. Technical Appendix
ERIC Educational Resources Information Center
Betts, Julian R.; Zau, Andrew C.; Koedel, Cory
2010-01-01
This technical appendix provides more detail on the reading reforms implemented under the Blueprint for Student Success project in the San Diego Unified School District (SDUSD) between 2000 and 2005. It provides details on the dataset, the econometric methods the authors employed, and the results, which are also detailed and discussed in the main…
An Econometric Model of the Scholastic Aptitude Test Performance of State Educational Systems.
ERIC Educational Resources Information Center
Hashway, Robert M.; And Others
1991-01-01
Nationwide data were partitioned into wealth, fiscal policy, fiscal orientation, and Scholastic Aptitude Test (SAT) performance and participation. Largest between-group differences show that low SAT achieving states have a larger percentage of seniors taking the SAT, along with higher per capita income, per pupil expenditures, and teacher…
ERIC Educational Resources Information Center
Manski, Charles F.; And Others
The processes of choosing a college and being accepted by a college are analyzed, based on data on nearly 23,000 seniors from more than 1,300 high schools from the National Longitudinal Study of the Class of 1972. Econometric modeling and descriptive statistics are provided on: student behavior in selecting a college, choosing school/nonschool…
The determinants of hardwood lumber price
William G. Luppold; Jennifer M. Jacobsen; Jennifer M. Jacobsen
1985-01-01
Econometric equations were estimated to determine the effects of domestic foreign hardwood lumber demands on oak and hardwood lumber prices. Oak price seemed to be more sensitive to changes in exports than overall hardwood lumber price. However, the main determinants of hardwood lumber and oak lumber prices were found to be domestic demand and millstock levels.
The effect of personal experience on choice-based preferences for wildfire protection programs
Tom Holmes; Armando Gonzalez-Caban; John Loomis; Jose Sanchez
2013-01-01
In this paper, we investigate homeowner preferences and willingness to pay for wildfire protection programs using a choice experiment with three attributes: risk, loss and cost. Preference heterogeneity among survey respondents was examined using three econometric models and risk preferences were evaluated by comparing willingness to pay for wildfire protection...
Revisiting the Principle of Relative Constancy: Consumer Mass Media Expenditures in Belgium.
ERIC Educational Resources Information Center
Dupagne, Michel; Green, R. Jeffery
1996-01-01
Proposes two new econometric models for testing the principle of relative constancy (PRC). Reports on regression and cointegration analyses conducted with Belgian mass media expenditure data from 1953-91. Suggests that alternative mass media expenditure models should be developed because PRC lacks of economic foundation and sound empirical…
Investment in Communications and Transportation: Socio-economic Impacts on Rural Development.
ERIC Educational Resources Information Center
Hilewick, Carol Lee; And Others
Two rural counties served as model areas in a comparison of the size and sequence of socioeconomic changes that investment in communications, as opposed to investment in transportation networks, might stimulate. A series of communications, rail, and highway changes were simulated through the use of an econometric model. An Industrial Communication…
Unionism and Productivity in West Virginia Coal Mining.
ERIC Educational Resources Information Center
Boal, William M.
1990-01-01
This study presents econometric estimates of the effects of unionism on productivity in 83 West Virginia coal mines in the early 1920s. Results show that unionism significantly reduced productivity at small mines but not at large mines. The author ascribes this effect to systematic differences between small and large operations in the quality of…
ERIC Educational Resources Information Center
Jaggars, Shanna Smith; Xu, Di
2016-01-01
Policymakers have become increasingly concerned with measuring--and holding colleges accountable for--students' labor market outcomes. In this article we introduce a piecewise growth curve approach to analyzing community college students' labor market outcomes, and we discuss how this approach differs from two popular econometric approaches:…
A Diagrammatic Exposition of Regression and Instrumental Variables for the Beginning Student
ERIC Educational Resources Information Center
Foster, Gigi
2009-01-01
Some beginning students of statistics and econometrics have difficulty with traditional algebraic approaches to explaining regression and related techniques. For these students, a simple and intuitive diagrammatic introduction as advocated by Kennedy (2008) may prove a useful framework to support further study. The author presents a series of…
Cognitive Functioning and the Probability of Falls among Seniors in Havana, Cuba
ERIC Educational Resources Information Center
Trujillo, Antonio J.; Hyder, Adnan A.; Steinhardt, Laura C.
2011-01-01
This article explores the connection between cognitive functioning and falls among seniors (greater than or equal to 60 years of age) in Havana, Cuba, after controlling for observable characteristics. Using the SABE (Salud, Bienestar, and Envejecimiento) cross-sectional database, we used an econometric strategy that takes advantage of available…
Econometric Models of Education, Some Applications. Education and Development, Technical Reports.
ERIC Educational Resources Information Center
Tinbergen, Jan; And Others
This report contains five papers which describe mathematical models of the educational system as it relates to economic growth. Experimental applications of the models to particular educational systems are discussed. Three papers, by L. J. Emmerij, J. Blum, and G. Williams, discuss planning models for the calculation of educational requirements…
Web-based Learning Environments Guided by Principles of Good Teaching Practice.
ERIC Educational Resources Information Center
Chizmar, John F.; Walbert, Mark S.
1999-01-01
Describes the preparation and execution of a statistics course, an undergraduate econometrics course, and a microeconomic theory course that all utilize Internet technology. Reviews seven principles of teaching practice in order to demonstrate how to enhance the quality of student learning using Web technologies. Includes reactions by Steve Hurd…
Handbook of the Economics of Education. Volume 3
ERIC Educational Resources Information Center
Hanushek, Eric A., Ed.; Machin, Stephen J., Ed.; Woessmann, Ludger, Ed.
2011-01-01
How does education affect economic and social outcomes, and how can it inform public policy? Volume 3 of the Handbooks in the Economics of Education uses newly available high quality data from around the world to address these and other core questions. With the help of new methodological approaches, contributors cover econometric methods and…
The paper describes a new way to estimate an efficient econometric model of global emissions of carbon dioxide (CO2) by nation, sector, and fuel type. Equations for fuel intensity are estimated for coal, oil, natural gas, electricity, and heat for six sectors: agricultural, indus...
Economic factors influencing land use changes in the South-Central United States
Ralph J. Alig; Fred C. White; Brian C. Murray
1988-01-01
Econometric models of land use change were estimated for two physiographic regions in the South-Central United States. Results are consistent-with the economic hierarchy of land use, with population and personal income being significant explanatory variables. Findings regarding the importance of relative agricultural and forestry market-based incomes in influencing...
New Employment Forecasts. Hotel and Catering Industry 1988-1993.
ERIC Educational Resources Information Center
Measurement for Management Decision, Ltd., London (England).
Econometric forecasting models were used to forecast employment levels in the hotel and catering industry in Great Britain through 1993 under several different forecasting scenarios. The growth in employment in the hotel and catering industry over the next 5 years is likely to be broadly based, both across income levels of domestic consumers,…
Influences on Labor Market Outcomes of African American College Graduates: A National Study
ERIC Educational Resources Information Center
Strayhorn, Terrell L.
2008-01-01
Using an expanded econometric model, this study sought to estimate more precisely the net effect of independent variables (i.e., attending an HBCU) on three measures of labor market outcomes for African American college graduates. Findings reveal a statistically significant, albeit moderate, relationship between measures of background, human and…
Lecture Attendance, Study Time, and Academic Performance: A Panel Data Study
ERIC Educational Resources Information Center
Andrietti, Vincenzo; Velasco, Carlos
2015-01-01
The authors analyze matched administrative survey data on economics students enrolled in two econometrics courses offered in consecutive terms at a major public university in Spain to assess the impact of lecture attendance and study time on academic performance. Using proxy variables in a cross-sectional regression setting, they find a positive…
The Relationship of Class Size Effects and Teacher Salary
ERIC Educational Resources Information Center
Peevely, Gary; Hedges, Larry; Nye, Barbara A.
2005-01-01
The effects of class size on academic achievement have been studied for decades. Although the results of small-scale, randomized experiments and large-scale, econometric studies point to positive effects of small classes, some scholars see the evidence as ambiguous. Recent analyses from a 4-year, large-scale, randomized experiment on the effects…
1987-06-01
consumer preferences provide influences that can stimulate the rate of growth of the endogenous and/or exogenous income industries. B. EXPORT INDUSTRIES...location quotient was selected to alleviate 12 some of the problems created by consumer preferences and expendi- ture patterns. This value was compared
Child Care and the Labor Supply of Married Women: Reduced Form Evidence.
ERIC Educational Resources Information Center
Ribar, David C.
1992-01-01
With data from the Survey of Income Program Participation, a three-equation, reduced-form econometric model is used to generate estimates revealing that the cost of market child care decreases the labor force participation of married women. High wages increase likelihood of working and use of paid child care. (SK)
The Effect of Income Taxation on Labor Supply in the United States.
ERIC Educational Resources Information Center
Triest, Robert K.
1990-01-01
A study used an econometric model to examine the effect of income taxation on labor supply of married women and men. Male labor supply was found to be relatively invariant to income. Impact on married women depended upon the method used to estimate the labor supply function. (SK)
Economic impacts of hurricanes on forest owners
Jeffrey P. Prestemon; Thomas P. Holmes
2010-01-01
We present a conceptual model of the economic impacts of hurricanes on timber producers and consumers, offer a framework indicating how welfare impacts can be estimated using econometric estimates of timber price dynamics, and illustrate the advantages of using a welfare theoretic model, which includes (1) welfare estimates that are consistent with neo-classical...
10 CFR 905.11 - What must an IRP include?
Code of Federal Regulations, 2010 CFR
2010-01-01
... forecasting method, including but not limited to the time series, end-use, and econometric methods. The... projected durability of such savings measured over time; and must treat demand and supply resources on a... implement its IRP. (i) The IRP must state the time period that the action plan covers, and the action plan...
10 CFR 905.11 - What must an IRP include?
Code of Federal Regulations, 2011 CFR
2011-01-01
... forecasting method, including but not limited to the time series, end-use, and econometric methods. The... projected durability of such savings measured over time; and must treat demand and supply resources on a... implement its IRP. (i) The IRP must state the time period that the action plan covers, and the action plan...
10 CFR 905.11 - What must an IRP include?
Code of Federal Regulations, 2012 CFR
2012-01-01
... forecasting method, including but not limited to the time series, end-use, and econometric methods. The... projected durability of such savings measured over time; and must treat demand and supply resources on a... implement its IRP. (i) The IRP must state the time period that the action plan covers, and the action plan...
10 CFR 905.11 - What must an IRP include?
Code of Federal Regulations, 2014 CFR
2014-01-01
... forecasting method, including but not limited to the time series, end-use, and econometric methods. The... projected durability of such savings measured over time; and must treat demand and supply resources on a... implement its IRP. (i) The IRP must state the time period that the action plan covers, and the action plan...
10 CFR 905.11 - What must an IRP include?
Code of Federal Regulations, 2013 CFR
2013-01-01
... forecasting method, including but not limited to the time series, end-use, and econometric methods. The... projected durability of such savings measured over time; and must treat demand and supply resources on a... implement its IRP. (i) The IRP must state the time period that the action plan covers, and the action plan...
An examination of the relationships between hardwood lumber and stumpage prices in Ohio
William G. Luppold; Jeffrey P. Prestemon; John E. Baumgras
1998-01-01
Understanding the relationship between hardwood lumber and stumpage prices is critical in evaluating market efficiency and in understanding the potential impact of changing technology on stumpage markets. Unfortunately, the complexity of the hardwood lumber market and lack of reliable data make it difficult to evaluate this relationship using traditional econometric...
What Do Cost Functions Tell Us about the Cost of an Adequate Education?
ERIC Educational Resources Information Center
Costrell, Robert M.; Hanushek, Eric; Loeb, Susanna
2008-01-01
Econometric cost functions have begun to appear in education adequacy cases with greater frequency. Cost functions are superficially attractive because they give the impression of objectivity, holding out the promise of scientifically estimating the cost of achieving specified levels of performance from actual data on spending. By contrast, the…
Does a hospital's quality depend on the quality of other hospitals? A spatial econometrics approach
Gravelle, Hugh; Santos, Rita; Siciliani, Luigi
2014-01-01
We examine whether a hospital's quality is affected by the quality provided by other hospitals in the same market. We first sketch a theoretical model with regulated prices and derive conditions on demand and cost functions which determine whether a hospital will increase its quality if its rivals increase their quality. We then apply spatial econometric methods to a sample of English hospitals in 2009–10 and a set of 16 quality measures including mortality rates, readmission, revision and redo rates, and three patient reported indicators, to examine the relationship between the quality of hospitals. We find that a hospital's quality is positively associated with the quality of its rivals for seven out of the sixteen quality measures. There are no statistically significant negative associations. In those cases where there is a significant positive association, an increase in rivals' quality by 10% increases a hospital's quality by 1.7% to 2.9%. The finding suggests that for some quality measures a policy which improves the quality in one hospital will have positive spillover effects on the quality in other hospitals. PMID:25843994
Does a hospital's quality depend on the quality of other hospitals? A spatial econometrics approach.
Gravelle, Hugh; Santos, Rita; Siciliani, Luigi
2014-11-01
We examine whether a hospital's quality is affected by the quality provided by other hospitals in the same market. We first sketch a theoretical model with regulated prices and derive conditions on demand and cost functions which determine whether a hospital will increase its quality if its rivals increase their quality. We then apply spatial econometric methods to a sample of English hospitals in 2009-10 and a set of 16 quality measures including mortality rates, readmission, revision and redo rates, and three patient reported indicators, to examine the relationship between the quality of hospitals. We find that a hospital's quality is positively associated with the quality of its rivals for seven out of the sixteen quality measures. There are no statistically significant negative associations. In those cases where there is a significant positive association, an increase in rivals' quality by 10% increases a hospital's quality by 1.7% to 2.9%. The finding suggests that for some quality measures a policy which improves the quality in one hospital will have positive spillover effects on the quality in other hospitals.
Energy risk in the arbitrage pricing model: an empirical and theoretical study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bremer, M.A.
1986-01-01
This dissertation empirically explores the Arbitrage Pricing Theory in the context of energy risk for securities over the 1960s, 1970s, and early 1980s. Starting from a general multifactor pricing model, the paper develops a two factor model based on a market-like factor and an energy factor. This model is then tested on portfolios of securities grouped according to industrial classification using several econometric techniques designed to overcome some of the more serious estimation problems common to these models. The paper concludes that energy risk is priced in the 1970s and possibly even in the 1960s. Energy risk is found tomore » be priced in the sense that investors who hold assets subjected to energy risk are paid for this risk. The classic version of the Capital Asset Pricing Model which posits the market as the single priced factor is rejected in favor of the Arbitrage Pricing Theory or multi-beta versions of the Capital Asset Pricing Model. The study introduces some original econometric methodology to carry out empirical tests.« less
Perceived and measured stigma among workers with serious mental illness.
Baldwin, Marjorie L; Marcus, Steven C
2006-03-01
This research analyzed the extent to which self-reports of job-related discrimination by persons with serious mental illness are associated with econometric measures of discrimination. Data were from the 1994-1995 National Health Interview Survey-Disability Supplement. Data for workers with mood, psychotic, or anxiety disorders (N=1,139) were compared with data for those without such disorders (N=66,341). The main outcome measures were self-reports of wages and stigmatizing experiences in the workplace. After the analyses controlled for functional limitations and job characteristics, no significant difference in mean wages was found between workers with serious mental illness who did not report experiencing stigma and those with no mental illness. In contrast, for all types of mental disorders examined, mean wages for workers with serious mental illness who reported experiencing stigma were significantly lower than mean wages for those with no mental illness. Workers' self-reports of stigmatizing experiences in the labor market appear to be consistent with econometric measures of the effect of stigma on wages, suggesting that workers know when they are being discriminated against.
Econometric Model of Rice Policy Based On Presidential Instruction
NASA Astrophysics Data System (ADS)
Abadi Sembiring, Surya; Hutauruk, Julia
2018-01-01
The objective of research is to build an econometric model based on Presidential Instruction rice policy. The data was monthly time series from March 2005 to September 2009. Rice policy model specification using simultaneous equation, consisting of 14 structural equations and four identity equation, which was estimated using Two Stages Least Squares (2SLS) method. The results show that: (1) an increase of government purchasing price of dried harvest paddy has a positive impact on to increase in total rice production and community rice stock, (2) an increase community rice stock lead to decrease the rice imports, (3) an increase of the realization of the distribution of subsidized ZA fertilizers and the realization of the distribution of subsidized NPK fertilizers has a positive impact on to increase in total rice production and community rice stock and to reduce rice imports, (4) the price of the dried harvest paddy is highly responsive to the water content of dried harvest paddy both the short run and long run, (5) the quantity of rice imported is highly responsive to the imported rice price, both short run and long run.
Econometric studies of urban population density: a survey.
Mcdonald, J F
1989-01-01
This paper presents the 1st reasonably comprehensive survey of empirical research of urban population densities since the publication of the book by Edmonston in 1975. The survey summarizes contributions to empirical knowledge that have been made since 1975 and points toward possible areas for additional research. The paper also provides a brief interpretative intellectual history of the topic. It begins with a personal overview of research in the field. The next section discusses econometric issues that arise in the estimation of population density functions in which density is a function only of a distance to the central business district of the urban area. Section 4 summarizes the studies of a single urban area that went beyond the estimation of simple distance-density functions, and Section 5 discusses studies that sought to explain the variations across urban areas in population density patterns. McDonald refers to the standard theory of urban population density throughout the paper. This basic model is presented in the textbook by Mills and Hamilton and it is assumed that the reader is familiar with the model.
Saldaña-Zorrilla, Sergio O; Sandberg, Krister
2009-10-01
Mexico's vast human and environmental diversity offers an initial framework for comprehending some of the prevailing great disparities between rich and poor. Its socio-economic constructed vulnerability to climatic events serves to expand this understanding. Based on a spatial econometric model, this paper tests the contribution of natural disasters to stimulating the emigration process in vulnerable regions of Mexico. Besides coping and adaptive capacity, it assesses the effects of economic losses due to disasters as well as the adverse production and trade conditions of the 1990s on emigration rates in 2000 at the municipality level. Weather-related disasters were responsible for approximately 80 per cent of economic losses in Mexico between 1980 and 2005, mostly in the agricultural sector, which continues to dominate many parts of the country. It is dramatic that this sector generates around only four per cent of gross domestic product but provides a livelihood to about one-quarter of the national population. It is no wonder, therefore, that most emigration from this country arises in vulnerable rural areas.
Multi-InDel Analysis for Ancestry Inference of Sub-Populations in China
Sun, Kuan; Ye, Yi; Luo, Tao; Hou, Yiping
2016-01-01
Ancestry inference is of great interest in diverse areas of scientific researches, including the forensic biology, medical genetics and anthropology. Various methods have been published for distinguishing populations. However, few reports refer to sub-populations (like ethnic groups) within Asian populations for the limitation of markers. Several InDel loci located very tightly in physical positions were treated as one marker by us, which is multi-InDel. The multi-InDel shows potential as Ancestry Inference Marker (AIM). In this study, we performed a genome-wide scan for multi-InDels as AIM. After examining the FST distributions in the 1000 Genomes Database, 12 candidates were selected and validated for eastern Asian populations. A multiplexed assay was developed as a panel to genotype 12 multi-InDel markers simultaneously. Ancestry component analysis with STRUCTURE and principal component analysis (PCA) were employed to estimate its capability for ancestry inference. Furthermore, ancestry assignments of trial individuals were conducted. It proved to be very effective when 210 samples from Han and Tibetan individuals in China were tested. The panel consisting of multi-InDel markers exhibited considerable potency in ancestry inference, and was suggested to be applied in forensic practices and genetic population studies. PMID:28004788
Causal inference in survival analysis using pseudo-observations.
Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T
2017-07-30
Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs to address right-censoring, and often, special techniques are required for that purpose. We will show how censoring can be dealt with 'once and for all' by means of so-called pseudo-observations when doing causal inference in survival analysis. The pseudo-observations can be used as a replacement of the outcomes without censoring when applying 'standard' causal inference methods, such as (1) or (2) earlier. We study this idea for estimating the average causal effect of a binary treatment on the survival probability, the restricted mean lifetime, and the cumulative incidence in a competing risks situation. The methods will be illustrated in a small simulation study and via a study of patients with acute myeloid leukemia who received either myeloablative or non-myeloablative conditioning before allogeneic hematopoetic cell transplantation. We will estimate the average causal effect of the conditioning regime on outcomes such as the 3-year overall survival probability and the 3-year risk of chronic graft-versus-host disease. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
The Information Content of Discrete Functions and Their Application in Genetic Data Analysis
Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.
2017-10-13
The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less
The Information Content of Discrete Functions and Their Application in Genetic Data Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.
The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less
ERIC Educational Resources Information Center
Trumpower, David L.
2015-01-01
Making inferences about population differences based on samples of data, that is, performing intuitive analysis of variance (IANOVA), is common in everyday life. However, the intuitive reasoning of individuals when making such inferences (even following statistics instruction), often differs from the normative logic of formal statistics. The…
Newton, Richard; Wernisch, Lorenz
2014-01-01
Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments. PMID:25148247
New Insights into Signed Path Coefficient Granger Causality Analysis
Zhang, Jian; Li, Chong; Jiang, Tianzi
2016-01-01
Granger causality analysis, as a time series analysis technique derived from econometrics, has been applied in an ever-increasing number of publications in the field of neuroscience, including fMRI, EEG/MEG, and fNIRS. The present study mainly focuses on the validity of “signed path coefficient Granger causality,” a Granger-causality-derived analysis method that has been adopted by many fMRI researches in the last few years. This method generally estimates the causality effect among the time series by an order-1 autoregression, and defines a positive or negative coefficient as an “excitatory” or “inhibitory” influence. In the current work we conducted a series of computations from resting-state fMRI data and simulation experiments to illustrate the signed path coefficient method was flawed and untenable, due to the fact that the autoregressive coefficients were not always consistent with the real causal relationships and this would inevitablely lead to erroneous conclusions. Overall our findings suggested that the applicability of this kind of causality analysis was rather limited, hence researchers should be more cautious in applying the signed path coefficient Granger causality to fMRI data to avoid misinterpretation. PMID:27833547
``Carbon Credits'' for Resource-Bounded Computations Using Amortised Analysis
NASA Astrophysics Data System (ADS)
Jost, Steffen; Loidl, Hans-Wolfgang; Hammond, Kevin; Scaife, Norman; Hofmann, Martin
Bounding resource usage is important for a number of areas, notably real-time embedded systems and safety-critical systems. In this paper, we present a fully automatic static type-based analysis for inferring upper bounds on resource usage for programs involving general algebraic datatypes and full recursion. Our method can easily be used to bound any countable resource, without needing to revisit proofs. We apply the analysis to the important metrics of worst-case execution time, stack- and heap-space usage. Our results from several realistic embedded control applications demonstrate good matches between our inferred bounds and measured worst-case costs for heap and stack usage. For time usage we infer good bounds for one application. Where we obtain less tight bounds, this is due to the use of software floating-point libraries.
Identifying Seizure Onset Zone From the Causal Connectivity Inferred Using Directed Information
NASA Astrophysics Data System (ADS)
Malladi, Rakesh; Kalamangalam, Giridhar; Tandon, Nitin; Aazhang, Behnaam
2016-10-01
In this paper, we developed a model-based and a data-driven estimator for directed information (DI) to infer the causal connectivity graph between electrocorticographic (ECoG) signals recorded from brain and to identify the seizure onset zone (SOZ) in epileptic patients. Directed information, an information theoretic quantity, is a general metric to infer causal connectivity between time-series and is not restricted to a particular class of models unlike the popular metrics based on Granger causality or transfer entropy. The proposed estimators are shown to be almost surely convergent. Causal connectivity between ECoG electrodes in five epileptic patients is inferred using the proposed DI estimators, after validating their performance on simulated data. We then proposed a model-based and a data-driven SOZ identification algorithm to identify SOZ from the causal connectivity inferred using model-based and data-driven DI estimators respectively. The data-driven SOZ identification outperforms the model-based SOZ identification algorithm when benchmarked against visual analysis by neurologist, the current clinical gold standard. The causal connectivity analysis presented here is the first step towards developing novel non-surgical treatments for epilepsy.
The mechanisms of temporal inference
NASA Technical Reports Server (NTRS)
Fox, B. R.; Green, S. R.
1987-01-01
The properties of a temporal language are determined by its constituent elements: the temporal objects which it can represent, the attributes of those objects, the relationships between them, the axioms which define the default relationships, and the rules which define the statements that can be formulated. The methods of inference which can be applied to a temporal language are derived in part from a small number of axioms which define the meaning of equality and order and how those relationships can be propagated. More complex inferences involve detailed analysis of the stated relationships. Perhaps the most challenging area of temporal inference is reasoning over disjunctive temporal constraints. Simple forms of disjunction do not sufficiently increase the expressive power of a language while unrestricted use of disjunction makes the analysis NP-hard. In many cases a set of disjunctive constraints can be converted to disjunctive normal form and familiar methods of inference can be applied to the conjunctive sub-expressions. This process itself is NP-hard but it is made more tractable by careful expansion of a tree-structured search space.
In defence of model-based inference in phylogeography
Beaumont, Mark A.; Nielsen, Rasmus; Robert, Christian; Hey, Jody; Gaggiotti, Oscar; Knowles, Lacey; Estoup, Arnaud; Panchal, Mahesh; Corander, Jukka; Hickerson, Mike; Sisson, Scott A.; Fagundes, Nelson; Chikhi, Lounès; Beerli, Peter; Vitalis, Renaud; Cornuet, Jean-Marie; Huelsenbeck, John; Foll, Matthieu; Yang, Ziheng; Rousset, Francois; Balding, David; Excoffier, Laurent
2017-01-01
Recent papers have promoted the view that model-based methods in general, and those based on Approximate Bayesian Computation (ABC) in particular, are flawed in a number of ways, and are therefore inappropriate for the analysis of phylogeographic data. These papers further argue that Nested Clade Phylogeographic Analysis (NCPA) offers the best approach in statistical phylogeography. In order to remove the confusion and misconceptions introduced by these papers, we justify and explain the reasoning behind model-based inference. We argue that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics. We also examine the NCPA method and highlight numerous deficiencies, either when used with single or multiple loci. We further show that the ages of clades are carelessly used to infer ages of demographic events, that these ages are estimated under a simple model of panmixia and population stationarity but are then used under different and unspecified models to test hypotheses, a usage the invalidates these testing procedures. We conclude by encouraging researchers to study and use model-based inference in population genetics. PMID:29284924
Karakaya, Jale; Karabulut, Erdem; Yucel, Recai M.
2015-01-01
Modern statistical methods using incomplete data have been increasingly applied in a wide variety of substantive problems. Similarly, receiver operating characteristic (ROC) analysis, a method used in evaluating diagnostic tests or biomarkers in medical research, has also been increasingly popular problem in both its development and application. While missing-data methods have been applied in ROC analysis, the impact of model mis-specification and/or assumptions (e.g. missing at random) underlying the missing data has not been thoroughly studied. In this work, we study the performance of multiple imputation (MI) inference in ROC analysis. Particularly, we investigate parametric and non-parametric techniques for MI inference under common missingness mechanisms. Depending on the coherency of the imputation model with the underlying data generation mechanism, our results show that MI generally leads to well-calibrated inferences under ignorable missingness mechanisms. PMID:26379316
Semi-blind Bayesian inference of CMB map and power spectrum
NASA Astrophysics Data System (ADS)
Vansyngel, Flavien; Wandelt, Benjamin D.; Cardoso, Jean-François; Benabed, Karim
2016-04-01
We present a new blind formulation of the cosmic microwave background (CMB) inference problem. The approach relies on a phenomenological model of the multifrequency microwave sky without the need for physical models of the individual components. For all-sky and high resolution data, it unifies parts of the analysis that had previously been treated separately such as component separation and power spectrum inference. We describe an efficient sampling scheme that fully explores the component separation uncertainties on the inferred CMB products such as maps and/or power spectra. External information about individual components can be incorporated as a prior giving a flexible way to progressively and continuously introduce physical component separation from a maximally blind approach. We connect our Bayesian formalism to existing approaches such as Commander, spectral mismatch independent component analysis (SMICA), and internal linear combination (ILC), and discuss possible future extensions.
NASA Astrophysics Data System (ADS)
Vance, Colin James
This dissertation develops spatially explicit econometric models by linking Thematic Mapper (TM) satellite imagery with household survey data to test behavioral propositions of semi-subsistence farmers in the Southern Yucatan Peninsular Region (SYPR) of Mexico. Covering 22,000 km2, this agricultural frontier contains one of the largest and oldest expanses of tropical forests in the Americas outside of Amazonia. Over the past 30 years, the SYPR has undergone significant land-use change largely owing to the construction of a highway through the region's center in 1967. These landscape dynamics are modeled by exploiting a spatial database linking a time series of TM imagery with socio-economic and geo-referenced land-use data collected from a random sample of 188 farm households. The dissertation moves beyond the existing literature on deforestation in three principal respects. Theoretically, the study develops a non-separable model of land-use that relaxes the assumption of profit maximization almost exclusively invoked in studies of the deforestation issue. The model is derived from a utility-maximizing framework that explicitly incorporates the interdependency of the household's production and consumption choices as these affect the allocation of resources. Methodologically, the study assembles a spatial database that couples satellite imagery with household-level socio-economic data. The field survey protocol recorded geo-referenced land-use data through the use of a geographic positioning system and the creation of sketch maps detailing the location of different uses observed within individual plots. Empirically, the study estimates spatially explicit econometric models of land-use change using switching regressions and duration analysis. A distinguishing feature of these models is that they link the dependent and independent variables at the level of the decision unit, the land manager, thereby capturing spatial and temporal heterogeneity that is otherwise obscured in studies using data aggregated to higher scales of analysis. The empirical findings suggest the potential of various policy initiatives to impede or otherwise alter the pattern of land-cover conversions. In this regard, the study reveals that consideration of missing or thin markets is critical to understanding how farmers in the SYPR reach subsistence and commercial cropping decisions.
Essays in financial economics and econometrics
NASA Astrophysics Data System (ADS)
La Spada, Gabriele
Chapter 1 (my job market paper) asks the following question: Do asset managers reach for yield because of competitive pressures in a low rate environment? I propose a tournament model of money market funds (MMFs) to study this issue. I show that funds with different costs of default respond differently to changes in interest rates, and that it is important to distinguish the role of risk-free rates from that of risk premia. An increase in the risk premium leads funds with lower default costs to increase risk-taking, while funds with higher default costs reduce risk-taking. Without changes in the premium, low risk-free rates reduce risk-taking. My empirical analysis shows that these predictions are consistent with the risk-taking of MMFs during the 2006--2008 period. Chapter 2, co-authored with Fabrizio Lillo and published in Studies in Nonlinear Dynamics and Econometrics (2014), studies the effect of round-off error (or discretization) on stationary Gaussian long-memory process. For large lags, the autocovariance is rescaled by a factor smaller than one, and we compute this factor exactly. Hence, the discretized process has the same Hurst exponent as the underlying one. We show that in presence of round-off error, two common estimators of the Hurst exponent, the local Whittle (LW) estimator and the detrended fluctuation analysis (DFA), are severely negatively biased in finite samples. We derive conditions for consistency and asymptotic normality of the LW estimator applied to discretized processes and compute the asymptotic properties of the DFA for generic long-memory processes that encompass discretized processes. Chapter 3, co-authored with Fabrizio Lillo, studies the effect of round-off error on integrated Gaussian processes with possibly correlated increments. We derive the variance and kurtosis of the realized increment process in the limit of both "small" and "large" round-off errors, and its autocovariance for large lags. We propose novel estimators for the variance and lag-one autocorrelation of the underlying, unobserved increment process. We also show that for fractionally integrated processes, the realized increments have the same Hurst exponent as the underlying ones, but the LW estimator applied to the realized series is severely negatively biased in medium-sized samples.
Evaluation of Second-Level Inference in fMRI Analysis
Roels, Sanne P.; Loeys, Tom; Moerkerke, Beatrijs
2016-01-01
We investigate the impact of decisions in the second-level (i.e., over subjects) inferential process in functional magnetic resonance imaging on (1) the balance between false positives and false negatives and on (2) the data-analytical stability, both proxies for the reproducibility of results. Second-level analysis based on a mass univariate approach typically consists of 3 phases. First, one proceeds via a general linear model for a test image that consists of pooled information from different subjects. We evaluate models that take into account first-level (within-subjects) variability and models that do not take into account this variability. Second, one proceeds via inference based on parametrical assumptions or via permutation-based inference. Third, we evaluate 3 commonly used procedures to address the multiple testing problem: familywise error rate correction, False Discovery Rate (FDR) correction, and a two-step procedure with minimal cluster size. Based on a simulation study and real data we find that the two-step procedure with minimal cluster size results in most stable results, followed by the familywise error rate correction. The FDR results in most variable results, for both permutation-based inference and parametrical inference. Modeling the subject-specific variability yields a better balance between false positives and false negatives when using parametric inference. PMID:26819578
Economic Impacts of Wind Turbine Development in U.S. Counties
DOE Office of Scientific and Technical Information (OSTI.GOV)
J., Brown; B., Hoen; E., Lantz
2011-07-25
The objective is to address the research question using post-project construction, county-level data, and econometric evaluation methods. Wind energy is expanding rapidly in the United States: Over the last 4 years, wind power has contributed approximately 35 percent of all new electric power capacity. Wind power plants are often developed in rural areas where local economic development impacts from the installation are projected, including land lease and property tax payments and employment growth during plant construction and operation. Wind energy represented 2.3 percent of the U.S. electricity supply in 2010, but studies show that penetrations of at least 20 percentmore » are feasible. Several studies have used input-output models to predict direct, indirect, and induced economic development impacts. These analyses have often been completed prior to project construction. Available studies have not yet investigated the economic development impacts of wind development at the county level using post-construction econometric evaluation methods. Analysis of county-level impacts is limited. However, previous county-level analyses have estimated operation-period employment at 0.2 to 0.6 jobs per megawatt (MW) of power installed and earnings at $9,000/MW to $50,000/MW. We find statistically significant evidence of positive impacts of wind development on county-level per capita income from the OLS and spatial lag models when they are applied to the full set of wind and non-wind counties. The total impact on annual per capita income of wind turbine development (measured in MW per capita) in the spatial lag model was $21,604 per MW. This estimate is within the range of values estimated in the literature using input-output models. OLS results for the wind-only counties and matched samples are similar in magnitude, but are not statistically significant at the 10-percent level. We find a statistically significant impact of wind development on employment in the OLS analysis for wind counties only, but not in the other models. Our estimates of employment impacts are not precise enough to assess the validity of employment impacts from input-output models applied in advance of wind energy project construction. The analysis provides empirical evidence of positive income effects at the county level from cumulative wind turbine development, consistent with the range of impacts estimated using input-output models. Employment impacts are less clear.« less
NASA Astrophysics Data System (ADS)
Wang, Qianlu
2017-10-01
Urban infrastructure and urbanization influence each other, and quantitative analysis of the relationship between them will play a significant role in promoting the social development. The paper based on the data of infrastructure and the proportion of urban population in Shanghai from 1988 to 2013, use the econometric analysis of co-integration test, error correction model and Granger causality test method, and empirically analyze the relationship between Shanghai's infrastructure and urbanization. The results show that: 1) Shanghai Urban infrastructure has a positive effect for the development of urbanization and narrowing the population gap; 2) when the short-term fluctuations deviate from long-term equilibrium, the system will pull the non-equilibrium state back to equilibrium with an adjust intensity 0.342670. And hospital infrastructure is not only an important variable for urban development in short-term, but also a leading infrastructure in the process of urbanization in Shanghai; 3) there has Granger causality between road infrastructure and urbanization; and there is no Granger causality between water infrastructure and urbanization, hospital and school infrastructures of social infrastructure have unidirectional Granger causality with urbanization.
Famine Early Warning Systems and Their Use of Satellite Remote Sensing Data
NASA Technical Reports Server (NTRS)
Brown, Molly E.; Essam, Timothy; Leonard, Kenneth
2011-01-01
Famine early warning organizations have experience that has much to contribute to efforts to incorporate climate and weather information into economic and political systems. Food security crises are now caused almost exclusively by problems of food access, not absolute food availability, but the role of monitoring agricultural production both locally and globally remains central. The price of food important to the understanding of food security in any region, but it needs to be understood in the context of local production. Thus remote sensing is still at the center of much food security analysis, along with an examination of markets, trade and economic policies during food security analyses. Technology including satellite remote sensing, earth science models, databases of food production and yield, and modem telecommunication systems contributed to improved food production information. Here we present an econometric approach focused on bringing together satellite remote sensing and market analysis into food security assessment in the context of early warning.
Spatial econometric analysis of factors influencing regional energy efficiency in China.
Song, Malin; Chen, Yu; An, Qingxian
2018-05-01
Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.
NASA Astrophysics Data System (ADS)
Konstantakis, Konstantinos N.; Michaelides, Panayotis G.; Vouldis, Angelos T.
2016-06-01
As a result of domestic and international factors, the Greek economy faced a severe crisis which is directly comparable only to the Great Recession. In this context, a prominent victim of this situation was the country's banking system. This paper attempts to shed light on the determining factors of non-performing loans in the Greek banking sector. The analysis presents empirical evidence from the Greek economy, using aggregate data on a quarterly basis, in the time period 2001-2015, fully capturing the recent recession. In this work, we use a relevant econometric framework based on a real time Vector Autoregressive (VAR)-Vector Error Correction (VEC) model, which captures the dynamic interdependencies among the variables used. Consistent with international evidence, the empirical findings show that both macroeconomic and financial factors have a significant impact on non-performing loans in the country. Meanwhile, the deteriorating credit quality feeds back into the economy leading to a self-reinforcing negative loop.
A prior-based integrative framework for functional transcriptional regulatory network inference
Siahpirani, Alireza F.
2017-01-01
Abstract Transcriptional regulatory networks specify regulatory proteins controlling the context-specific expression levels of genes. Inference of genome-wide regulatory networks is central to understanding gene regulation, but remains an open challenge. Expression-based network inference is among the most popular methods to infer regulatory networks, however, networks inferred from such methods have low overlap with experimentally derived (e.g. ChIP-chip and transcription factor (TF) knockouts) networks. Currently we have a limited understanding of this discrepancy. To address this gap, we first develop a regulatory network inference algorithm, based on probabilistic graphical models, to integrate expression with auxiliary datasets supporting a regulatory edge. Second, we comprehensively analyze our and other state-of-the-art methods on different expression perturbation datasets. Networks inferred by integrating sequence-specific motifs with expression have substantially greater agreement with experimentally derived networks, while remaining more predictive of expression than motif-based networks. Our analysis suggests natural genetic variation as the most informative perturbation for network inference, and, identifies core TFs whose targets are predictable from expression. Multiple reasons make the identification of targets of other TFs difficult, including network architecture and insufficient variation of TF mRNA level. Finally, we demonstrate the utility of our inference algorithm to infer stress-specific regulatory networks and for regulator prioritization. PMID:27794550
Steele, Vaughn R; Bernat, Edward M; van den Broek, Paul; Collins, Paul F; Patrick, Christopher J; Marsolek, Chad J
2013-01-25
Successful comprehension during reading often requires inferring information not explicitly presented. This information is readily accessible when subsequently encountered, and a neural correlate of this is an attenuation of the N400 event-related potential (ERP). We used ERPs and time-frequency (TF) analysis to investigate neural correlates of processing inferred information after a causal coherence inference had been generated during text comprehension. Participants read short texts, some of which promoted inference generation. After each text, they performed lexical decisions to target words that were unrelated or inference-related to the preceding text. Consistent with previous findings, inference-related words elicited an attenuated N400 relative to unrelated words. TF analyses revealed unique contributions to the N400 from activity occurring at 1-6 Hz (theta) and 0-2 Hz (delta), supporting the view that multiple, sequential processes underlie the N400. Copyright © 2012 Elsevier B.V. All rights reserved.
Statistical Signal Models and Algorithms for Image Analysis
1984-10-25
In this report, two-dimensional stochastic linear models are used in developing algorithms for image analysis such as classification, segmentation, and object detection in images characterized by textured backgrounds. These models generate two-dimensional random processes as outputs to which statistical inference procedures can naturally be applied. A common thread throughout our algorithms is the interpretation of the inference procedures in terms of linear prediction
A refined method for multivariate meta-analysis and meta-regression
Jackson, Daniel; Riley, Richard D
2014-01-01
Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects’ standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:23996351
Bayesian data analysis in population ecology: motivations, methods, and benefits
Dorazio, Robert
2016-01-01
During the 20th century ecologists largely relied on the frequentist system of inference for the analysis of their data. However, in the past few decades ecologists have become increasingly interested in the use of Bayesian methods of data analysis. In this article I provide guidance to ecologists who would like to decide whether Bayesian methods can be used to improve their conclusions and predictions. I begin by providing a concise summary of Bayesian methods of analysis, including a comparison of differences between Bayesian and frequentist approaches to inference when using hierarchical models. Next I provide a list of problems where Bayesian methods of analysis may arguably be preferred over frequentist methods. These problems are usually encountered in analyses based on hierarchical models of data. I describe the essentials required for applying modern methods of Bayesian computation, and I use real-world examples to illustrate these methods. I conclude by summarizing what I perceive to be the main strengths and weaknesses of using Bayesian methods to solve ecological inference problems.
An Econometric Study of Public School Expenditure Variations Across States, 1951-1967.
ERIC Educational Resources Information Center
Barro, Stephen M.
Nine sets of annual data on State school finances are used to test a theory of expenditure determination by public school districts. The results support implications of the theory regarding effects of personal income, State and federal aid, the relative price of education, the pupil/population ratio, and enrollment growth on per pupil spending. A…
Measuring ICT Use and Learning Outcomes: Evidence from Recent Econometric Studies
ERIC Educational Resources Information Center
Biagi, Federico; Loi, Massimo
2013-01-01
Based on PISA 2009 data, this article studies the relationship between students' computer use and their achievement in reading, mathematics and science in 23 countries. After having categorised computer use into a set of different activities according to the skills they involve, we correlate students' PISA test-scores with an index capturing the…
Revealing Failures in the History of School Finance. NBER Working Paper No. 15491
ERIC Educational Resources Information Center
Lindert, Peter H.
2009-01-01
This essay proposes a set of non-econometric tests using data on wage structure, school resource costs, public expenditures, taxes, and rates of return to explain anomalies in which richer political units deliver less education than poorer ones. Both the anomalies of education history, and its less surprising contrasts, fit broad patterns that can…
39 CFR 3050.26 - Documentation of demand elasticities and volume forecasts.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 39 Postal Service 1 2010-07-01 2010-07-01 false Documentation of demand elasticities and volume forecasts. 3050.26 Section 3050.26 Postal Service POSTAL REGULATORY COMMISSION PERSONNEL PERIODIC REPORTING § 3050.26 Documentation of demand elasticities and volume forecasts. By January 20 of each year, the Postal Service shall provide econometric...
Doing a Monty: Who Opened the Door to This Game for Economists?
ERIC Educational Resources Information Center
Round, David K.
2007-01-01
The Monty Hall three-door, "Let's Make a Deal" game, named after the 1970s television show, is used widely in economics, econometrics, statistics, and game-theory-based teaching, as well as in many other disciplines. Its solutions and underlying assumptions arouse great passion and argument, in both the academic and popular press. Most economists…
Solicitation and Donation: An Econometric Evaluation of Alumni Generosity in Higher Education
ERIC Educational Resources Information Center
Gottfried, Michael A.; Johnson, Erica L.
2006-01-01
This paper evaluates the relationship between alumni solicitation and alumni donation within institutions of higher education. The issue of alumni giving is important for universities because the average cost of university tuition has increased dramatically over the past 20 years at an annual growth rate larger than the United States CPI (Harvard…
John Hof; Curtis Flather; Tony Baltic; Stephen Davies
1999-01-01
The 1999 forest and rangeland condition indicator model is a set of independent econometric production functions for environmental outputs (measured with condition indicators) at the national scale. This report documents the development of the database and the statistical estimation required by this particular production structure with emphasis on two special...
IDA 2004 Cost Research Symposium: Investments in, Use of, and Management of Cost Research
2004-09-01
Database: None Publication: Technical Report Keywords: Government, Aircraft, SD&D, Production, Integration, Data Collection, Database, CER B- 71 ... Martin Plant in Marietta , Georgia,” IDA Paper P-3590, July 2001 “Econometric Modeling of Acquisition Category I Systems at the Raytheon Plant in...NAVSEA) ............................................................ B- 71 Naval Surface Warfare Center, Dahlgren Division (NSWCDD