Essays On Panel Data And Spatial Models
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Essays On Panel Data And Spatial Models
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Author : Dong Li
language : en
Publisher:
Release Date : 2000
Essays On Panel Data And Spatial Models written by Dong Li and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.
Essays On Spatial Panel Data Models With Common Factors
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Author : Wei Shi
language : en
Publisher:
Release Date : 2016
Essays On Spatial Panel Data Models With Common Factors written by Wei Shi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
My dissertation research addresses issues in spatial panel data models, which study the interactions of economic units across space and time. Individuals interact with their neighbors and the outcomes are interdependent. The strength of the interaction depends on the distance between the individuals, which can be based on geography or constructed from economic theory. Accounting for spatial interactions allows one to quantify both the direct effect of a variable and its indirect effect through impacting neighbors. However, two issues often arise. First, spatial dependence can be alternatively generated from common unobserved factors (e.g. economy-wide shocks) where neighbors have similar responses. Second, the distance between economic units can be endogenous, and this will in fact be the case if the distance is constructed from variables that correlate with disturbances in the outcomes. The first chapter studies the estimation of a dynamic spatial panel data model with interactive individual and time effects with large n and T. The model has a rich spatial structure including contemporaneous spatial interaction and spatial heterogeneity. Dynamic features include individual time lag and spatial diffusion. In a standard two way fixed effects panel regression model, the unobservables contain an individual specific but time invariant component, and a component that is time variant but common across individuals. We generalize this model by allowing the interaction between time effects and individual effects. This chapter provides a tool for empirical researchers to guard against attributing correlated responses to common time effects as spatial effects. The interactive effects are treated as parameters, so as to allow correlations between the interactive effects and the regressors. We consider a quasi-maximum likelihood estimation and show estimator consistency and characterize its asymptotic distribution. The Monte Carlo experiment shows that the estimator performs well and the proposed bias correction is effective. The second chapter proposes a unified approach to model endogenous spatial dependences while accounting for common factors. The spatial weights matrices are constructed from variables that may correlate with the disturbances in the outcomes. We make minimal assumptions on the distributions of the factors and follow a fixed effects approach. We provide conditions under which the quasi-maximum likelihood estimator is consistent and asymptotically normal, under the asymptotics where both the cross section and time dimensions become large. The limiting distribution is normal but may not be centered for the estimates of the spatial interaction coefficient and the variances. An analytical bias correction is proposed to improve the inference. The Monte Carlo simulations demonstrate good finite sample properties of the bias corrected estimator. We illustrate the empirical relevance of the theory by applying the method to analyze the effect of house price dynamics on reverse mortgage origination rates.
Three Essays On Spatial Econometric Models With Missing Data
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Author : Wei Wang
language : en
Publisher:
Release Date : 2010
Three Essays On Spatial Econometric Models With Missing Data written by Wei Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
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.
Essays On Spatial Dynamic Panel Data Model Theories And Applications
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Author : Jihai Yu
language : en
Publisher:
Release Date : 2007
Essays On Spatial Dynamic Panel Data Model Theories And Applications written by Jihai Yu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
This dissertation is composed of three papers about the theories and application of spatial dynamic panel data model with fixed effects. The first paper investigates the asymptotic properties of quasi-maximum likelihood estimators for spatial dynamic panel data with fixed effects when both the number of individuals n and the number of time periods T are large. We consider the case where T is asymptotically large relative to n, the case where T is asymptotically proportional to n, and the case where n is asymptotically large relative to T. In the case where T is asymptotically large relative to n, the estimators are nT consistent and asymptotically normal, with the limit distribution centered around 0. When n is asymptotically proportional to T, the estimators are nT consistent and asymptotically normal, but the limit distribution is not centered around 0; and when n is large relative to T, the estimators are consistent with rate T, and have a degenerate limit distribution. We also propose a bias correction for our estimators. We show that when T grows faster than n1/3, the correction will asymptotically eliminate the bias and yield a centered confidence interval. The second paper covers a nonstationary case where there are units roots in the data generating process. When not all the roots in the DGP are unity, the estimators rate of convergence will be the same as the stationary case, and the estimators can be asymptotically normal. But for the estimators' asymptotic variance matrix, it will be driven by the nonstationary component into a singular matrix. Consequently, a linear combination of the spatial and dynamic effects can converge with a higher rate. We also propose a bias correction for our estimators. We show that when T grows faster than n 1/3, the correction will asymptotically eliminate the bias and yield a centered confidence interval. In the third paper, a spatial dynamic panel data approach is proposed to study growth convergence in the U.S. economy. In neoclassical model, countries are assumed to be independent from each other, which does not hold in the real world. We introduce technological spillovers and factor mobility into the neoclassical framework, showing that the convergence rate is higher and there is spatial correlation. Exploiting annual data on personal state income spanning period 1961-2000 for the 48 contiguous states, we obtain empirical results consistent with the model prediction.
Essays In Spatial Panel Econometrics
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Author : Silvia Palombi
language : en
Publisher:
Release Date : 2015
Essays In Spatial Panel Econometrics written by Silvia Palombi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
The third essay (Chapter 4) is an extension of the previous chapter, and provides conclusive evidence by implementing a more formal and rigorous approach to testing a null model against a non-nested alternative, i.e. the J-test. This is a well-established technique for choosing among non-nested rivals, and in this chapter I develop a version of the test for specifications (SARAR-RE models) which feature spatially correlated error components, thus accounting for interregional heterogeneity via random effects (also subjected, like the disturbances, to a spatially autoregressive process), as well as a spatial lag of the dependent variable and additional, potentially endogenous regressors. This chapter thus makes a valuable addition to the literature on non-nested hypotheses testing in the spatial panel context by extending the toolkit to random-effects models. I also provide Monte Carlo evidence showing that there are distributional issues associated with the asymptotic use of the J-test in small-to-medium samples, so another novelty of this chapter is the implementation of a Bootstrap scheme to construct a valid null reference distribution in finite samples when the null and alternative are SARAR-RE models estimated by S2SLS / GMM. In terms of the empirical application, bootstrap J-test results confirm the bootstrap ANM results from the previous chapter that the wage curve rejects NEG theory while UE theory is equally successful. Another finding, from the methodological angle, is that the bootstrap J-test is a reliable and effective procedure for correcting asymptotic reference critical values and distinguishing between competing hypotheses in all cases where one is not a reduced form of the other.The fourth and final essay (Chapter 5) is one of few to reconsider from a spatial panel econometric perspective an economic relationship - the 'empirical law of economics' known as Okun's Law - which has been traditionally considered at macro level with no attention for sub-national phenomena; it is the first to do so for Great Britain, looking at the 128 British NUTS3 regions over the period 1985-2011. By means of specialist techniques recently devised for spatial data, I show that regional interdependencies have a prominent role in the unemployment-output relationship; the total Okun's Law effect itself is close to the 'law' of -0.30 but more than two thirds of this are accounted for by the impact on local unemployment rate of real output variations in areas nearby, a finding suggesting that policy intervention at both national and regional level on a country's labour market can be more effective if spatial effects are factored into the analysis and modelled / tested explicitly.
Three Essays On Spatial Econometrics And Empirical Industrial Organization
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Author : Sang-Yeob Lee
language : en
Publisher:
Release Date : 2008
Three Essays On Spatial Econometrics And Empirical Industrial Organization written by Sang-Yeob Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Econometrics categories.
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.
Recent Advances In Linear Models And Related Areas
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Author : Shalabh
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-07-11
Recent Advances In Linear Models And Related Areas written by Shalabh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-11 with Mathematics categories.
This collection contains invited papers by distinguished statisticians to honour and acknowledge the contributions of Professor Dr. Dr. Helge Toutenburg to Statistics on the occasion of his sixty-?fth birthday. These papers present the most recent developments in the area of the linear model and its related topics. Helge Toutenburg is an established statistician and currently a Professor in the Department of Statistics at the University of Munich (Germany) and Guest Professor at the University of Basel (Switzerland). He studied Mathematics in his early years at Berlin and specialized in Statistics. Later he completed his dissertation (Dr. rer. nat. ) in 1969 on optimal prediction procedures at the University of Berlin and completed the post-doctoral thesis in 1989 at the University of Dortmund on the topic of mean squared error superiority. He taught at the Universities of Berlin, Dortmund and Regensburg before joining the University of Munich in 1991. He has various areas of interest in which he has authored and co-authored over 130 research articles and 17 books. He has made pioneering contributions in several areas of statistics, including linear inference, linear models, regression analysis, quality engineering, Taguchi methods, analysis of variance, design of experiments, and statistics in medicine and dentistry.
Three Essays On Residential Land Development
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Author : Douglas Harvey Wrenn (II)
language : en
Publisher:
Release Date : 2012
Three Essays On Residential Land Development written by Douglas Harvey Wrenn (II) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
In our last essay, we develop a nonparametric estimation technique for spatial panel data. Using a Monte Carlo experiment, we show how extending current geographically weighted regression (GWR) models to account for temporal heterogeneity provides a better fit to the data when coefficient heterogeneity exists in both the spatial and temporal dimensions. We also show how the technique can be used in modeling real-world land use change by applying the proposed technique to a panel dataset of historical subdivision development.
Estimation Of Spatial Panels
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Author : Lung-fei Lee
language : en
Publisher: Now Publishers Inc
Release Date : 2011
Estimation Of Spatial Panels written by Lung-fei Lee and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Business & Economics categories.
Estimation of Spatial Panels provides some recent developments on the specification and estimation of spatial panel models.
Essays In Panel Data Econometrics
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Author : Marc Nerlove
language : en
Publisher: Cambridge University Press
Release Date : 2005-11-10
Essays In Panel Data Econometrics written by Marc Nerlove and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-11-10 with Business & Economics categories.
This volume collects seven classic essays on panel data econometrics, and a cogent essay on the history of the subject.