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Spatial Lag Models with Nested Random Effects: An Instrumental Variable Procedure with an Application to English House Prices

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This paper sets up a nested random effects spatial autoregressive panel data model to explain annual house price variation for 2000-2007 across 353 local authority districts in England. The estimation problem posed is how to allow for the endogeneity of the spatial lag variable producing the simultaneous spatial spillover of prices across districts together with the nested random effects in a panel data setting. To achieve this, the paper proposes new estimators based on the instrumental variable approaches of Kelejian and Prucha (1998) and Lee (2003) for the cross-sectional spatial autoregressive model. Monte Carlo results show that our estimators perform well relative to alternative approaches and produces estimates based on real data that are consistent with the theoretical house price model underpinning the reduced form.

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  • Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2013. "Spatial Lag Models with Nested Random Effects: An Instrumental Variable Procedure with an Application to English House Prices," Center for Policy Research Working Papers 161, Center for Policy Research, Maxwell School, Syracuse University.
    • Handle: RePEc:max:cprwps:161
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    1. Robert J. Barro, 1998. "Determinants of Economic Growth: A Cross-Country Empirical Study," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262522543, April.
    2. Baltagi, Badi H. & Liu, Long, 2011. "Instrumental variable estimation of a spatial autoregressive panel model with random effects," Economics Letters, Elsevier, vol. 111(2), pages 135-137, May.
    3. Bernard Fingleton, 2008. "A Generalized Method of Moments Estimator for a Spatial Panel Model with an Endogenous Spatial Lag and Spatial Moving Average Errors," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(1), pages 27-44.
    4. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    5. Lauridsen, J. & Kosfeld, R., 2004. "A wald Test for Spatial Nonstationarity," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 22, pages 1-12, Diciembre.
    6. Bernard Fingleton & Julie Le Gallo, 2008. "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances: Finite sample properties," Papers in Regional Science, Wiley Blackwell, vol. 87(3), pages 319-339, August.
    7. Bernard Fingleton, 2009. "A generalized method of moments estimator for a spatial model with moving average errors, with application to real estate prices," Studies in Empirical Economics, in: Giuseppe Arbia & Badi H. Baltagi (ed.), Spatial Econometrics, pages 35-57, Springer.
    8. Lung-Fei Lee & Jihai Yu, 2013. "Near Unit Root in the Spatial Autoregressive Model," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(3), pages 314-351, September.
    9. Luisa Corrado & Bernard Fingleton, 2012. "Where Is The Economics In Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 210-239, May.
    10. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    11. Bernard Fingleton, 2009. "Simulating Wages and House Prices Using the NEG," Working Papers 0913, University of Strathclyde Business School, Department of Economics.
    12. Pines,David & Sadka,Efraim & Zilcha,Itzhak (ed.), 1998. "Topics in Public Economics," Cambridge Books, Cambridge University Press, number 9780521561365, September.
    13. H. Baltagi, Badi & Heun Song, Seuck & Cheol Jung, Byoung, 2001. "The unbalanced nested error component regression model," Journal of Econometrics, Elsevier, vol. 101(2), pages 357-381, April.
    14. Julie Le Gallo & Bernard Fingleton, 2008. "Estimating spatial models with endogenous variables, a spatial lag and spatially dependent disturbances : finite sample properties," Post-Print hal-00485035, HAL.
    15. Steven Brakman & Harry Garretsen & Marc Schramm, 2004. "The Spatial Distribution of Wages: Estimating the Helpman‐Hanson Model for Germany," Journal of Regional Science, Wiley Blackwell, vol. 44(3), pages 437-466, August.
    16. Manfred M. Fischer & Arthur Getis (ed.), 2010. "Handbook of Applied Spatial Analysis," Springer Books, Springer, number 978-3-642-03647-7, June.
    17. H. Hanson, Gordon, 2005. "Market potential, increasing returns and geographic concentration," Journal of International Economics, Elsevier, vol. 67(1), pages 1-24, September.
    18. Higgins, Matthew J. & Levy, Daniel & Young, Andrew T., 2006. "Growth and Convergence across the United States: Evidence from County-Level Data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 88(4), pages 671-681.
    19. Badi H. Baltagi & Chihwa Kao & Long Liu, 2013. "The Estimation and Testing of a Linear Regression with Near Unit Root in the Spatial Autoregressive Error Term," Spatial Economic Analysis, Taylor & Francis Journals, vol. 8(3), pages 241-270, September.
    20. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1.
    21. Mark D. Partridge, 2005. "Does Income Distribution Affect U.S. State Economic Growth?," Journal of Regional Science, Wiley Blackwell, vol. 45(2), pages 363-394, May.
    22. Bernard Fingleton, 2008. "Housing Supply, Housing Demand, and Affordability," Urban Studies, Urban Studies Journal Limited, vol. 45(8), pages 1545-1563, July.
    23. Montmarquette, Claude & Mahseredjian, Sophie, 1989. "Does School Matter for Educational Achievement? A Two-Way Nested-Error Components Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(2), pages 181-193, April-Jun.
    24. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    25. JesúS Mur & F. Javier Trívez, 2003. "Unit Roots and Deterministic Trends in Spatial Econometric Models," International Regional Science Review, , vol. 26(3), pages 289-312, July.
    26. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    27. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    28. Sukesh K. Ghosh, 1976. "Estimating from a More General Time-Series Cum Cross-Section Data Structure," The American Economist, Sage Publications, vol. 20(1), pages 15-21, March.
    29. Michael Beenstock & Dan Feldman & Daniel Felsenstein, 2012. "Testing for Unit Roots and Cointegration in Spatial Cross-Section Data," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(2), pages 203-222, June.
    30. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    31. Glaeser, Edward L., 2008. "Cities, Agglomeration, and Spatial Equilibrium," OUP Catalogue, Oxford University Press, number 9780199290444.
    32. Corrado, L. & Fingleton, B., 2011. "Multilevel Modelling with Spatial Effects," SIRE Discussion Papers 2011-13, Scottish Institute for Research in Economics (SIRE).
    33. Jørgen Lauridsen & Reinhold Kosfeld, 2006. "A test strategy for spurious spatial regression, spatial nonstationarity, and spatial cointegration," Papers in Regional Science, Wiley Blackwell, vol. 85(3), pages 363-377, August.
    34. Kristian Behrens & Frédéric Robert‐Nicoud, 2009. "Krugman's Papers in Regional Science: The 100 dollar bill on the sidewalk is gone and the 2008 Nobel Prize well‐deserved," Papers in Regional Science, Wiley Blackwell, vol. 88(2), pages 467-489, June.
    35. Antweiler, Werner, 2001. "Nested random effects estimation in unbalanced panel data," Journal of Econometrics, Elsevier, vol. 101(2), pages 295-313, April.
    36. Badi Baltagi & Seuck Heun Song & Byoung Cheol Jung, 2002. "Simple Lm Tests For The Unbalanced Nested Error Component Regression Model," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 167-187.
    37. Bernard Fingleton, 2006. "A cross‐sectional analysis of residential property prices: the effects of income, commuting, schooling, the housing stock and spatial interaction in the English regions," Papers in Regional Science, Wiley Blackwell, vol. 85(3), pages 339-361, August.
    38. Lung-fei Lee, 2003. "Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances," Econometric Reviews, Taylor & Francis Journals, vol. 22(4), pages 307-335.
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    More about this item

    Keywords

    House Prices; Panel Data; Spatial Lag; Nested Random Effects; In-strumental Variables; Spatial Dependence;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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