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Measuring the diffusion of housing prices across space and over time*

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  • Ryan R. Brady

Abstract

How fast and how long (and to what magnitude) does a change in housing prices in one region affect its neighbors? In this paper, I apply a time series technique for measuring impulse response functions from local projections to a spatial autoregressive model of housing prices. For a dynamic panel of California counties, the data reveal that the diffusion of regional housing prices across space lasts up to two and half years. This result, and the econometric techniques employed, should be of interest not only to housing and regional economists, but to a variety of applied econometricians as well. Copyright (C) 2009 John Wiley & Sons, Ltd.

Suggested Citation

  • Ryan R. Brady, 2011. "Measuring the diffusion of housing prices across space and over time," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(2), pages 213-231, March.
  • Handle: RePEc:wly:japmet:v:26:y:2011:i:2:p:213-231
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    File URL: http://hdl.handle.net/10.1002/jae.1118
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    1. Case Karl E. & Quigley John M. & Shiller Robert J., 2005. "Comparing Wealth Effects: The Stock Market versus the Housing Market," The B.E. Journal of Macroeconomics, De Gruyter, vol. 5(1), pages 1-34, May.
    2. Christiano, Lawrence J. & Eichenbaum, Martin & Evans, Charles L., 1999. "Monetary policy shocks: What have we learned and to what end?," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 2, pages 65-148, Elsevier.
    3. Clapp, John M. & Tirtiroglu, Dogan, 1994. "Positive feedback trading and diffusion of asset price changes: Evidence from housing transactions," Journal of Economic Behavior & Organization, Elsevier, vol. 24(3), pages 337-355, August.
    4. Holly, Sean & Pesaran, M. Hashem & Yamagata, Takashi, 2010. "A spatio-temporal model of house prices in the USA," Journal of Econometrics, Elsevier, vol. 158(1), pages 160-173, September.
    5. Harry H. Kelejian & Dennis P. Robinson, 1993. "A Suggested Method Of Estimation For Spatial Interdependent Models With Autocorrelated Errors, And An Application To A County Expenditure Model," Papers in Regional Science, Wiley Blackwell, vol. 72(3), pages 297-312, July.
    6. Kelejian, Harry H. & Prucha, Ingmar R., 2002. "2SLS and OLS in a spatial autoregressive model with equal spatial weights," Regional Science and Urban Economics, Elsevier, vol. 32(6), pages 691-707, November.
    7. Tirtiroglu, Dogan, 1992. "Efficiency in housing markets: Temporal and spatial dimensions," Journal of Housing Economics, Elsevier, vol. 2(3), pages 276-292, September.
    8. J. Paul Elhorst, 1996. "A Regional Analysis of Labour Force Participation Rates across the Member States of the European Union," Regional Studies, Taylor & Francis Journals, vol. 30(5), pages 455-465.
    9. John Krainer & Chishen Wei, 2004. "House prices and fundamental value," FRBSF Economic Letter, Federal Reserve Bank of San Francisco, issue oct1.
    10. Attila Varga, 2000. "Local Academic Knowledge Transfers and the Concentration of Economic Activity," Journal of Regional Science, Wiley Blackwell, vol. 40(2), pages 289-309, May.
    11. Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-965, July.
    12. Engelhardt, Gary V., 1996. "House prices and home owner saving behavior," Regional Science and Urban Economics, Elsevier, vol. 26(3-4), pages 313-336, June.
    13. James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
    14. Karl E. Case & Robert J. Shiller, 2003. "Is There a Bubble in the Housing Market?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 34(2), pages 299-362.
    15. Edward L. Glaeser & Joseph Gyourko & Raven E. Saks, 2005. "Why Have Housing Prices Gone Up?," American Economic Review, American Economic Association, vol. 95(2), pages 329-333, May.
    16. Gerald Carlino & Robert Defina, 1998. "The Differential Regional Effects Of Monetary Policy," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 572-587, November.
    17. Min Hwang & John M. Quigley, 2006. "Economic Fundamentals In Local Housing Markets: Evidence From U.S. Metropolitan Regions," Journal of Regional Science, Wiley Blackwell, vol. 46(3), pages 425-453, August.
    18. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    19. Attila Varga, 1998. "Local academic knowledge spillovers and the concentration of economic activity," ERSA conference papers ersa98p493, European Regional Science Association.
    20. 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.
    21. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
    22. Oscar Jorda, 2007. "Inference for Impulse Responses," Working Papers 201, University of California, Davis, Department of Economics.
    23. Fratantoni, Michael & Schuh, Scott, 2003. "Monetary Policy, Housing, and Heterogeneous Regional Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 35(4), pages 557-589, August.
    24. Basu, Sabyasachi & Thibodeau, Thomas G, 1998. "Analysis of Spatial Autocorrelation in House Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 61-85, July.
    25. Kul B. Bhatia, 1987. "Real Estate Assets and Consumer Spending," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(2), pages 437-444.
    26. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291, Decembrie.
    27. Òscar Jordà, 2005. "Estimation and Inference of Impulse Responses by Local Projections," American Economic Review, American Economic Association, vol. 95(1), pages 161-182, March.
    28. Gerald A. Carlino & Robert H. DeFina, 1999. "Do states respond differently to changes in monetary policy?," Business Review, Federal Reserve Bank of Philadelphia, issue Jul, pages 17-27.
    29. J. Paul Elhorst, 2003. "Specification and Estimation of Spatial Panel Data Models," International Regional Science Review, , vol. 26(3), pages 244-268, July.
    30. Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
    31. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
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    Replication

    This item has been replicated by:
  • Shulin Shen & Jindong Pang, 2018. "Measuring the diffusion of housing prices across space and over time: Replication and further evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(3), pages 479-484, April.
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