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Spatial Econometrics
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Table of Contents

1. Spatial Models: Basic Issues 2. Specification and Estimation 3. Spill Over Effects in Spatial Models 4. Predictors in Spatial Models 5. Problems in Estimating Weighting Matrices 6. Additional Endogenous Variables: and Possible Nonlinearities 7. Bayesian Analysis 8. Pre-test and Sample Selection Issues in Spatial Analysis 9. HAC Estimation of V-C Matrices 10. Missing Data and Edge Issues 11. Tests for Spatial Correlation 12. Non-Nest Models and the J-Test 13. Endogenous Weighting Matrices: Specification and Estimation 14. Systems of Spatial Equations 15. Panel Data Models Appendix A: Introduction to large sample theory Appendix B: Spatial Models in R

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Supports graduate and PhD students seeking to develop skills in the derivation, analysis and implementation of tractable econometric models using spatial dimensions

About the Author

Harry Kelejian is Professor of Economics at the University of Maryland. He has held academic positions at Princeton and New York Universities. He has also been a Visiting Professor at the Institute for Advanced Studies in Vienna, Austria (1979, 2005, 2006); at the Australian National University in Canberra (1982); and at the University of Konstanz in Germany (1997). He was selected in 1995 for the Prentice Hall of Fame Economist Series. He publishes widely in applied and theoretical econometrics. Gianfranco Piras is an Associate Professor of Economics at the Busch School of Business and Economics at The Catholic University of America. Formerly, he was a Research Assistant Professor at the Regional Research Institute at West Virginia University. He has also spent time at the Department of City and Regional Planning at Cornell University, the Regional Economic Application Laboratory at the University of Illinois at Urbana-Champaign, and at the GeoDa center at Arizona State University. He held a position of Assistant Professor at the Universidad Catolica del Norte in Chile. Dr. Piras is a member of the editorial board of Letters of Spatial and Resource Sciences. Dr. Piras' research interests include spatial econometrics and statistics, urban and regional economics, computational methods and software development. He is one of the developers of the R software for statistical computing and he is currently working on two main libraries, for the estimation of spatial panel data models (SPLM), and for the application of GM methods in spatial econometrics (SPHET).

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