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Author: Qu, Xi
Publisher:
ISBN:
Category :
Languages : en
Pages : 158
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Chapter Two focuses on three classical tests, namely, Wald, LM, and LR, of spatial interactions in the simultaneous SAR Tobit model. We derive the asymptotic distributions of those three tests under both the null and the local alternative hypotheses, establish their asymptotic equivalence and local efficiency, and study finite sample properties using the Monte Carlo simulation. The tests are applied to an empirical example involving the school district income tax in Iowa in 2009. Among 361 school districts, 18.3 percent had rates of zero, so it fits the Tobit setting. Testing results indicate the existence of tax competition among neighboring school districts.
Author: Qu, Xi
Publisher:
ISBN:
Category :
Languages : en
Pages : 158
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Book Description
Chapter Two focuses on three classical tests, namely, Wald, LM, and LR, of spatial interactions in the simultaneous SAR Tobit model. We derive the asymptotic distributions of those three tests under both the null and the local alternative hypotheses, establish their asymptotic equivalence and local efficiency, and study finite sample properties using the Monte Carlo simulation. The tests are applied to an empirical example involving the school district income tax in Iowa in 2009. Among 361 school districts, 18.3 percent had rates of zero, so it fits the Tobit setting. Testing results indicate the existence of tax competition among neighboring school districts.
Author:
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ISBN:
Category :
Languages : en
Pages :
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Author: Wei Wang
Publisher:
ISBN:
Category :
Languages : en
Pages : 147
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Abstract: This dissertation is composed of three essays on spatial econometric models with missing data. Spatial models that have a long history in regional science and geography have received substantial attention in various areas of economics recently. Applications of spatial econometric models prevail in urban, developmental and labor economics among others. In practice, an issue that researchers often face is the missing data problem. Although many solutions such as list-wise deletion and EM algorithm can be found in literature, most of them are either not suited for spatial models or hard to apply due to technical difficulties. My research focuses on the estimation of the spatial econometric models in the presence of missing data problems. The first chapter develops a GMM method based on linear moments for the estimation of mixed regressive, spatial autoregressive (MRSAR) models with missing observations in the dependent variables. The estimation method uses the expectation of the missing data, as a function of the observed independent variables and the parameters to be estimated, to replace the missing data themselves in the estimation. The proposed GMM estimators are shown to be consistent and asymptotically normal. Feasible optimal weighting matrix for the GMM estimation is given. We extend our estimation method to MRSAR models with heteroskedastic disturbances, high order MRSAR models and unbalanced spatial panel data models with random effects as well. From these extensions, we see that the proposed GMM method has more compatibility, compared with the conventional EM algorithm. The second chapter considers a group interaction model first proposed by Lee (2006); this model is a special case of the spatial autoregressive (SAR) models. It is a first attempt to estimate the model in a more general random sample setting, i.e. a framework in which only a random sample rather than the whole population in a group is available. We incorporate group heteroskedasticity along with the endogenous, exogenous and group fixed effects in the model. We prove that, under some basic assumptions and certain identification conditions, the quasi maximum likelihood (QML) estimators are consistent and asymptotically normal when the functional form of the group heteroskedasticity is known. Two types of misspecifications are considered, and, under each, the estimators are inconsistent. We also propose IV estimation in the case that the group heteroskedasticity is unknown. A LM test of group heteroskedasticity is given at the end. The third chapter considers the same group interaction model as that in the second chapter, but focuses on the large group interaction case and uses a random effects setting for the group specific characters. A GMM estimation framework using moment conditions from both within and between equations is applied to the model. We prove that under some basic assumptions and certain identification conditions, the GMM estimators are consistent and asymptotically normal, and the convergence rates of the estimators are higher than those of the estimators derived from the within equations only. Feasible optimal GMM estimators are proposed.
Author: Xiaoyi Han
Publisher:
ISBN:
Category :
Languages : en
Pages : 244
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My job market paper, "Bayesian Estimation of a Spatial Autoregressive Model with an Unobserved Endogenous Spatial Weight Matrix and Unobserved Factors", examines the specification and estimation of the SAR model with new features. Motivated by the spillover effects of state medicaid spending on welfare programs, we combine all these new features together for the first time in the SAR model. Specifically, we focus on two ways of defining neighborliness (a source of unobserved spatial weight matrix W): one based on geographical distance and the other on "economic" distance. In this particular application, endogeneity of W comes from the correlation of economic distance and the disturbances in the SAR equation. Unobserved factors are introduced to control for common shocks to all states. For the estimation of the model, the Bayesian MCMC method is employed, which is also supported by simulation results. We find that a dollar increase in a state's neighbors' Medicaid related spending will increase its own Medicaid related spending by about 52 cents. Both geographical and economic distances are shown to have significant effects on the interaction strength of state Medicaid related spending. Our results suggest that in the context of Medicaid spending, welfare motivated move and yardstick competition are both sources of strategic interactions among state governments.
Author: Sang-Yeob Lee
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 117
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Abstract: The first essay explores the consequences of misspecified spatial interdependence structure in SAR models with a row-normalized weight matrix. I provide the analytical formulae for the asymptotic biases of the OLS estimator when a spatial weight matrix is over-specified, under-specified, or omitted in a simple linear regression model. I then design Monte Carlo experiments to study how a misspecified spatial weight matrix in the SAR model might impact the finite sample properties of the 2SLSE and MLE. The major finding is that an "over-specification" of the weight matrix causes less bias in 2SLSE and MLE as well as lower RMSE than an "under-specification." The results also strongly suggest that goodness of fit measures such as adjusted R-square and log-likelihood can serve as selection criteria for the choice of a spatial weight matrix. In the second essay, I consider the effectiveness of Wald, distance difference, minimum Chi-square, and gradient tests within GMM framework in selecting different specifications of spatial weights in SAR models. The two major results I obtain are (1) that for each of the five tests, GMM framework significantly improves the empirical power of the tests over 2SLS framework, and (2) that when performed in GMM framework, all five tests have suitable empirical size and power with similar performance outcomes. Finally, the third essay investigates the nature of competition in the retail gasoline market using a two year panel data of weekly prices for gas stations in San Diego County. I use IV methods to estimate several spatial autoregressive (SAR) models of stations' price reaction functions after specifying spatial weights based on distance between stations. By using the SAR model, I am able to identify that the brand of competing stations and their relative geographic proximity to the original station are important factors in explaining price variation across gasoline stations, as opposed to just the number of competing stations.
Author: Yu-Hsien Kao
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Daniel A. Griffith
Publisher: Springer Science & Business Media
ISBN: 1475728999
Category : Business & Economics
Languages : en
Pages : 206
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The purpose of models is not to fit the data but to sharpen the questions. S. Karlin, 11th R. A. Fisher Memorial Lecture, Royal Society, 20 April 1983 We are proud to offer this volume in honour of the remarkable career of the Father of Spatial Econometrics, Professor Jean Paelinck, presently of the Tinbergen Institute, Rotterdam. Not one to model solely for the sake of modelling, the above quotation nicely captures Professor Paelinck's unceasing quest for the best question for which an answer is needed. His FLEUR model has sharpened many spatial economics and spatial econometrics questions! Jean Paelinck, arguably, is the founder of modem spatial econometrics, penning the seminal introductory monograph on this topic, Spatial Econometrics, with Klaassen in 1979. In the General Address to the Dutch Statistical Association, on May 2, 1974, in Tilburg, "he coined the term [spatial econometrics] to designate a growing body of the regional science literature that dealt primarily with estimation and testing problems encountered in the implementation of multiregional econometric models" (Anselin, 1988, p. 7); he already had introduced this idea in his introductory report to the 1966 Annual Meeting of the Association de Science Regionale de Langue Fran~aise.
Author: Lung-fei Lee
Publisher: World Scientific
ISBN: 9811270503
Category : Business & Economics
Languages : en
Pages : 894
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Book Description
This is the most recently developed book in Spatial Econometrics which cover important models and estimation methods. Its coverage is rather broad, and some of the topics covered have only been developed in the recent econometric literature in spatial econometrics.The book summarizes our devoted efforts on spatial econometrics that represent joint contributions with former PhD advisees from the Ohio State University in Columbus, Ohio, USA.The coverage is comprehensive and there are a total of sixteen chapters from basic statistics and statistical theory of linear-quadratic forms, law of large numbers (LLN) and central limit theory (CLT) on martingales to nonlinear spatial mixing and spatial near-epoch dependence theories, which can justify the statistic inferences for various spatial models and their estimation. New estimation and testing approaches in empirical likelihood and general empirical likelihood, and Bootstrapping are presented. Model selection is also discussed in this book. In addition to the popular spatial autoregressive models, there are chapters on multivariate SAR models, simultaneous SAR models, and panel dynamic spatial models. Recent econometric developments on intertemporal spatial models with rational expectations and flows data in trade theory will also be included. In terms of statistics, classical estimation, testing and inference are the main concerns, and we provide classical inference for the justification of Bayesian simulation approaches.
Author: Luc Anselin
Publisher: Springer Science & Business Media
ISBN: 3662056178
Category : Business & Economics
Languages : en
Pages : 516
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Book Description
World-renowned experts in spatial statistics and spatial econometrics present the latest advances in specification and estimation of spatial econometric models. This includes information on the development of tools and software, and various applications. The text introduces new tests and estimators for spatial regression models, including discrete choice and simultaneous equation models. The performance of techniques is demonstrated through simulation results and a wide array of applications related to economic growth, international trade, knowledge externalities, population-employment dynamics, urban crime, land use, and environmental issues. An exciting new text for academics with a theoretical interest in spatial statistics and econometrics, and for practitioners looking for modern and up-to-date techniques.
Author: Omer Kara
Publisher:
ISBN:
Category :
Languages : en
Pages : 299
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