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

Author

Listed:
  • Geoffrey M. Ngene

    (Mercer University)

  • Daniel P. Sohn

    (Mercer University)

  • M. Kabir Hassan

    (University of New Orleans)

Abstract

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.

Suggested Citation

  • Geoffrey M. Ngene & Daniel P. Sohn & M. Kabir Hassan, 2017. "Time-Varying and Spatial Herding Behavior in the US Housing Market: Evidence from Direct Housing Prices," The Journal of Real Estate Finance and Economics, Springer, vol. 54(4), pages 482-514, May.
  • Handle: RePEc:kap:jrefec:v:54:y:2017:i:4:d:10.1007_s11146-016-9552-5
    DOI: 10.1007/s11146-016-9552-5
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    3. Akshita Singh & Shailendra Kumar & Utkarsh Goel & Amar Johri, 2023. "Behavioural biases in real estate investment: a literature review and future research agenda," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-17, December.
    4. Rangan Gupta & Chi Keung Marco Lau & Wendy Nyakabawo, 2018. "Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment," Working Papers 201866, University of Pretoria, Department of Economics.
    5. Esin Cakan & Riza Demirer & Rangan Gupta & Josine Uwilingiye, 2019. "Economic Policy Uncertainty and Herding Behavior Evidence from the South African Housing Market," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(1), pages 88-113, March.
    6. Gabauer, David & Gupta, Rangan & Marfatia, Hardik A. & Miller, Stephen M., 2024. "Estimating U.S. housing price network connectedness: Evidence from dynamic Elastic Net, Lasso, and ridge vector autoregressive models," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 349-362.
    7. Balcilar, Mehmet & Gupta, Rangan & Sousa, Ricardo M. & Wohar, Mark E., 2021. "Linking U.S. State-level housing market returns, and the consumption-(Dis)Aggregate wealth ratio," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 779-810.
    8. Xu, Xiaoyue & Mi, Anran & Li, Xiuting & Li, Xuerong & Dong, Jichang, 2024. "Bad news travels fast: Network analysis of the Chinese housing market connectivity," China Economic Review, Elsevier, vol. 84(C).
    9. Sercan Demiralay & Erhan Kilincarslan, 2024. "Uncertainty Measures and Sector-Specific REITs in a Regime-Switching Environment," The Journal of Real Estate Finance and Economics, Springer, vol. 69(3), pages 545-584, October.
    10. Bouri, Elie & Gupta, Rangan & Kyei, Clement Kweku & Shivambu, Rinsuna, 2021. "Uncertainty and daily predictability of housing returns and volatility of the United States: Evidence from a higher-order nonparametric causality-in-quantiles test," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 200-206.
    11. Rangan Gupta & Damien Moodley, 2023. "Housing Search Activity and Quantiles-Based Predictability of Housing Price Movements in the United States," Working Papers 202335, University of Pretoria, Department of Economics.
    12. Geoffrey M. Ngene & Rangan Gupta, 2021. "Impact of Housing Policy Uncertainty on Herding Behavior: Evidence from UK's Regional Housing Markets," Working Papers 202115, University of Pretoria, Department of Economics.
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    More about this item

    Keywords

    Herding; CSAD; Housing market; Regimes; Switching regression;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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