Time-Varying and Spatial Herding Behavior in the US Housing Market: Evidence from Direct Housing Prices

  • Geoffrey M. NgeneEmail author
  • Daniel P. Sohn
  • M. Kabir Hassan


This paper investigates herding behavior in the US residential housing market. The sample period is 1975 M01 to 2015 M06. The study utilizes the housing price index of each of the 50 states and Washington DC to form nine census region-based markets, or portfolios and then employs switching and quantile regressions to examine the spatial and time-varying disparities of housing return dispersions and investors’ herding behavior. The study finds that the degree of herding varies across regimes, regions and conditional distributions. The regime-specific herd formation may be partially originated by extreme housing market conditions, bull and bear housing market conditions, uncertainty in national financial markets, economic recessions and uncertainty of economic policies. The bull housing markets exhibits stronger effects on return dispersion than down markets, which is consistent with the “flight-to-safety” consensus behavior of investors. The study also finds that positive and negative linear and nonlinear returns magnify dispersions in an asymmetric manner. The increase in co-movement and interdependence of state and regional-level housing markets returns among geographically diverse states and regions offer little hope of successful geographical portfolio diversification strategies for U.S housing market investors. Moreover, time-invariant modeling may yield incorrect inferences regarding herd formation in regional housing markets.


Herding CSAD Housing market Regimes Switching regression 

JEL Classification

G14 G15 



We are greatly indebted to Professor Emeritus John M. Dunaway for reading our manuscript, providing some valuable insights and redacting the original manuscript.


  1. Ades, A., & Chua, H. B. (1997). Thy neighbor’s curse: regional instability and economic growth. Journal of Economic Growth, 2(3), 279–304.CrossRefGoogle Scholar
  2. Bachmann, R., Elstner, S., & Sims, E. R. (2010). Uncertainty and economic activity: evidence from business survey data. American Economic Journal: Macroeconomics, 5(2), 217–249.Google Scholar
  3. Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18, 1–22.Google Scholar
  4. Baker, D. (2005). Housing bubble fact sheet, CEPR issue brief, Centre for Economic Policy Research.Google Scholar
  5. Baker, S.R., Bloom, N., & Davis, S.J. (2013). Measuring economic policy uncertainty. Working Paper No. 13–02, Booth School of Business, The University of Chicago.Google Scholar
  6. Barnes, M., & Hughes, A.W. (2002). A quantile regression analysis of the cross section of stock market returns, FRB Boston Working Paper series No. 02–2, Federal Reserve Bank of Boston.Google Scholar
  7. Baur, D. (2006). Multivariate market association and its extremes. Journal of International Financial Markets Institutions and Money, 16, 355–369.CrossRefGoogle Scholar
  8. Bekaert, G., & Wu, G. (2000). Asymmetric volatility and risk in equity markets. Review of Financial Studies, 13, 1–42.CrossRefGoogle Scholar
  9. Bernanke, B. S. (1983). Irreversibility, uncertainty, and cyclical investment. The Quarterly Journal of Economics, 98(1), 85–106.CrossRefGoogle Scholar
  10. Bernanke, B.S., Gertler, M., & Gilchrist, S. (1999). The financial accelerator in a quantitative business cycle framework. In Handbooks in Economics, 15, 1999. Amsterdam: Elsevier, 1341–1393.Google Scholar
  11. Bikhchandani, S., Hirshleifer, D., & Welch, I.  (1992). A theory of fads, fashion, custom and cultural changes as informational cascades. Journal of Political Economy, 100, 992–1026.Google Scholar
  12. Bikhchandani, S., & Sharma, S. (2001). Herd behavior in financial markets. IMF staff papers. International Monetary Fund, 47(3), 279–310. doi: 10.2307/3867650.Google Scholar
  13. Brunnermeier, M. (2009). Deciphering the liquidity and credit crunch 2007–08. Journal of Economic Perspectives, 23, 77–100.CrossRefGoogle Scholar
  14. Carlino, G. A., & DeFina, R. H. (1998). The differential regional effects of monetary policy. The Review of Economics and Statistics, 80, 572–587.CrossRefGoogle Scholar
  15. Carlino, G.A., & DeFina, R.H. (1999). Do states respond differently to changes in monetary policy? Business Review, Federal Reserve Bank of Philadelphia (July/August), 17–27.Google Scholar
  16. Chang, E. C., Cheng, J. W., & Khorana, A. (2000). An examination of herd behavior in equity markets: an international perspective. Journal of Banking and Finance, 24, 1651–1679.CrossRefGoogle Scholar
  17. Chevalier, J., & Ellison, G. (1999). Are some mutual fund managers better than others? Cross-sectional patterns in behavior and performance. Journal of Finance, 54, 875–899.CrossRefGoogle Scholar
  18. Chiang, T. C., & Zheng, D. (2010). An empirical analysis of herd behavior in global stock markets. Journal of Banking and Finance, 34, 1911–1921.CrossRefGoogle Scholar
  19. Chiang, T. C., Li, J., & Tan, L. (2010). Empirical investigation of herding behavior in Chinese stock markets: Evidence from quantile regression analysis. Global Finance Journal, 21, 111–124.CrossRefGoogle Scholar
  20. Chiang, T. C., Tan, L., Li, J., & Nelling, E. (2013). Dynamic herding behavior in pacific-basin markets: evidence and implications. Multinational Finance Journal, 17(3–4), 165–200.CrossRefGoogle Scholar
  21. Christie, W. G., & Huang, R. D. (1995). Following the pied piper: do individual returns herd around the market? Financial Analysts Journal, 51, 31–37.CrossRefGoogle Scholar
  22. Collard, F., Dellas, H., Diba, B., & Loisel, O. (2012). Optimal monetary and prudential policies. CREST Working Paper No. 2012-34, Bank of France Working Paper No. 413.Google Scholar
  23. Conrad, J., Gultekin, M., & Kaul, G. (1991). Asymmetric predictability of conditional variances. Review of Financial Studies, 4, 597–622.CrossRefGoogle Scholar
  24. Crawford, G., & Fratantoni, M. (2003). Assessing the forecasting performance of regime-switching, ARIMA and GARCH models of house prices. Real Estate Economics, 31, 223–243.CrossRefGoogle Scholar
  25. Davig, T. (2004). Regime-switching debt and taxation. Journal of Monetary Economics, 51, 837–859.CrossRefGoogle Scholar
  26. Demirer, R., & Kutan, A. M. (2006). Does herding behavior exist in Chinese stock markets? Journal of International Financial Markets Institutions and Money, 16, 123–142.CrossRefGoogle Scholar
  27. Demirer, R., Kutan, A. M., & Chen, C. (2010). Do investors herd in emerging stock markets? Evidence from the Taiwanese market. Journal of Economic Behavior & Organization, 76, 283–295.CrossRefGoogle Scholar
  28. Devenow, A., & Welch, I. (1996). Rational herding in financial economics. European Economic Review, 40, 603–615.CrossRefGoogle Scholar
  29. Duffee, G.R. (2001). Asymmetric cross-sectional dispersion in stock returns: Evidence and implications. Working Papers in Applied Economic Theory, Federal Reserve Bank of San Francisco, No. 2000–18.Google Scholar
  30. Economou, F., Kostakis, A., & Philippas, N. (2011). Cross-country effects in herding behavior: evidence from four South European markets. Journal of International Financial Markets, Institutions & Money, 21, 443–460.CrossRefGoogle Scholar
  31. European Central Bank. (2007). Progress towards a framework for financial stability assessment, speech by José-Manuel González-Páramo, Member of the Executive Board of the ECB, OECD World Forum on “Statistics, Knowledge and Policy”, Istanbul, 28 June.Google Scholar
  32. Foldvary, F. (1997). The business cycle: a georgist-austrian synthesis. American Journal of Economics and Sociology, 56(4), 521–541.CrossRefGoogle Scholar
  33. Gadanecz, B., & Jayaram, K. (2008). Measures of financial stability - A review. In: Proceedings of the IFC Conference on "Measuring financial innovation and its impact", Basel, 26–27 August 2008Google Scholar
  34. Gleason, K. C., Mathur, I., & Peterson, M. A. (2004). Analysis of intraday herding behavior among the sector ETFs. Journal of Empirical Finance, 11, 681–694.CrossRefGoogle Scholar
  35. Goodfellow, C., Bohl, M. T., & Gebka, B. (2009). Together we invest? Individual and institutional investors’ trading behavior in Poland. International Review of Financial Analysis, 18, 212–221.CrossRefGoogle Scholar
  36. Goyal, A., & Santa-Clara, P. (2003). Idiosyncratic risk matters! Journal of Finance, 58(3), 975–1008.CrossRefGoogle Scholar
  37. Gündüz, Y., & Orcun, K. (2014). Impacts of the financial crisis on Eurozone sovereign CDS spreads. Journal of International Money and Finance, 49, 425–442.CrossRefGoogle Scholar
  38. Gupta, R., & Kabundi, A. (2010). The effect of monetary policy on house price inflation: A factor augmented vector autoregression (FAVAR) approach.  Journal of Economic Studies, 37(6), 616–626.Google Scholar
  39. Gupta, R., & Miller, S. M. (2012). The time series properties of house prices: a case study of the Southern California market. Journal of Real Estate Finance and Economics, 44, 339–361.CrossRefGoogle Scholar
  40. Hamilton, J. D. (1988). Rational-expectations econometric analysis of changes in regime: an investigation of the term structure of interest rates. Journal of Economic Dynamics and Control, 12, 385–423.CrossRefGoogle Scholar
  41. Hamilton, J.D. (2005). What’s real about the business cycle? NBER Working Paper Series, National Bureau of Economic Research.Google Scholar
  42. Harrison, F. (2010). Boom bust: House prices, Banking and the depression of 2010, London: Shepheard-Walwyn.
  43. Hirshleifer, D., & Teoh, S. H. (2003). Herd behavior and cascading in capital markets: a review and synthesis. European Financial Management, 9, 25–66.CrossRefGoogle Scholar
  44. Hong, Y., Tu, J., & Zhou, G. (2007). Asymmetries in stock returns: statistical tests and economic evaluation. Review of Financial Studies, 20(5), 1547–1581.CrossRefGoogle Scholar
  45. Hoyt, H. (1970). The urban real estate cycle-performances and prospects. Urban Land Institute Technical Bulletin; No. 38, 537–547. Urban Land Institute, Washington.Google Scholar
  46. Hwang, S., & Salmon, M. (2004). Market stress and herding. Journal of Empirical Finance, 11, 585–616.CrossRefGoogle Scholar
  47. Jarque, C. M., & Bera, A. K. (1987). A test for normality of observations and regression residuals. International Statistical Review, 55(2), 163–172.CrossRefGoogle Scholar
  48. Kennedy, P. (2008). A guide to econometrics. Malden: Blackwell Publishing.Google Scholar
  49. Koenker, R. (2005). Quantile regression. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  50. Lakonishok, J., Shleifer, A., & Vishny, R. W. (1992). The impact of institutional trading on stock prices. Journal of Financial Economics, 32, 23–44.CrossRefGoogle Scholar
  51. Longin, F., & Solnik, B. (2001). Extreme correlation of international equity markets. Journal of Finance, 56, 649–676.CrossRefGoogle Scholar
  52. Miao, H., Ramchander, S., & Simpson, M. W. (2011). Return and volatility transmission in U.S. Housing markets. Real Estate Economics, 39(4), 701–741.CrossRefGoogle Scholar
  53. Miles, W. (2009). Volatility clustering in U.S home prices. Journal of Real Estate Research, 30(1), 73–90.Google Scholar
  54. Morelli, D. (2010). European capital market integration: an empirical study based on a European asset pricing model. Journal of International Financial Markets Institutions and Money, 20, 363–375.CrossRefGoogle Scholar
  55. Newey, W. K., & West, K. (1987). A simple positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix. Econometrica, 55, 703–708.CrossRefGoogle Scholar
  56. Nofsinger, J., & Sias, R. (1999). Herding and feedback trading by institutional and individual investors. Journal of Finance, 54, 2263–2295.CrossRefGoogle Scholar
  57. Philippas, N., Economou, F., Babalos, V., & Kostakis, A. (2013). Herding behavior in REITs: novel tests and the role of financial crisis. International Review of Financial Analysis, 29, 166–174.CrossRefGoogle Scholar
  58. Quigley, J. M. (2002). Transaction costs and housing markets. In A. O’Sullivan & K. Gilb (Eds.), Housing markets and public policy (pp. 54–64). Malden: Blackwell Publishing.Google Scholar
  59. Sapienza, P., Guiso, L., & Zingales, L. (2013). The determinants of attitudes towards strategic default on mortgages. Journal of Finance, 68(4), 1473–1515.CrossRefGoogle Scholar
  60. Shiller, R. (2007). Understanding recent trends in house prices and home ownership.
  61. Shin, H. S. (2010). Risk and liquidity, Clarendon lectures in Finance. Oxford: Oxford University Press.Google Scholar
  62. Solnik, B., & Roulet, J. (2000). Dispersion as cross-sectional correlation. Financial Analysts Journal, 56(1), 54–61.CrossRefGoogle Scholar
  63. Stephens, M. (2012). Tackling housing market volatility in the UK. Part I: long- and short-term volatility. International Journal of Housing Policy, 12(3), 367–380.CrossRefGoogle Scholar
  64. Stock, J. H., & Watson, M. W. (2003). Forecasting output and inflation: the role of asset prices. Journal of Economic Literature, 41(3), 788–829.CrossRefGoogle Scholar
  65. Tan, L., Chiang, T. C., Mason, J. R., & Nelling, E. (2008). Herding behavior in Chinese stock markets: an examination of A and B shares. Pacific-Basin Finance Journal, 16, 61–77.CrossRefGoogle Scholar
  66. Van Ommeren, J. (2008). Transaction costs in housing markets. Unpublished working paper.Google Scholar
  67. Vargas-Silva, C. (2008a). Monetary policy and the US housing market: a VAR analysis imposing sign restrictions. Journal of Macroeconomics, 30, 977–990.CrossRefGoogle Scholar
  68. Vargas-Silva, C. (2008b). The effect of monetary policy on housing: a Factor- Augmented Vector Autoregression (FAVAR) approach. Applied Economics Letters, 15(10), 749–752.CrossRefGoogle Scholar
  69. Welch, I. (2000). Herding among security analysts. Journal of Financial Economics, 58(3), 369–396.Google Scholar
  70. Wheaton, W. C., & Nechayev, G. (2008). The 1998–2005 housing “bubble” and the current “correction”: what’s different this time? Journal of Real Estate Research, 30(1), 1–26.Google Scholar
  71. Zhu, B., Füss, R., & Rottke, N. B. (2013). Spatial linkages in returns and volatilities among U.S. Regional housing markets. Real Estate Economics, 41(1), 29–64.CrossRefGoogle Scholar
  72. Zhou, J., & Anderson, R. I. (2013). An empirical investigation of herding behavior in the U.S. REIT Market. Journal of Real Estate Finance & Economics, 47, 83–108.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Geoffrey M. Ngene
    • 1
    Email author
  • Daniel P. Sohn
    • 1
  • M. Kabir Hassan
    • 2
  1. 1.Stetson School of Business and EconomicsMercer UniversityMaconUSA
  2. 2.Department of Economics and FinanceUniversity of New OrleansNew OrleansUSA

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