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Linking U.S. State-Level Housing Market Returns and the Consumption-(Dis)Aggregate Wealth Ratio

Author

Listed:
  • Mehmet Balcilar

    (Eastern Mediterranian University)

  • Rangan Gupta

    (University of Pretoria)

  • Ricardo M. Sousa

    (University of Minho, NIPE and LSE Alumni Association)

  • Mark E. Wohar

    (University of Nebraska-Omaha)

Abstract

Using state-level data for the U.S. housing market over the period of 1975:Q1-2012:Q2, we show that the consumption-wealth ratios derived from aggregate wealth (cay) and disaggregate (i.e. financial and housing) wealth (cday) are strong predictors of real housing returns (and their volatility). Additionally, we find that, barring the extreme ends of their respective conditional distributions, such effect is stronger for housing return volatility than housing returns. All in all, our findings show that state-level regressions can recover a large degree of heterogeneity that country-level exercises typically ignore. Such heterogeneity is prominent not only in terms of consumption smoothing behavior, but also with regard to housing return predictability.

Suggested Citation

  • Mehmet Balcilar & Rangan Gupta & Ricardo M. Sousa & Mark E. Wohar, 2020. "Linking U.S. State-Level Housing Market Returns and the Consumption-(Dis)Aggregate Wealth Ratio," Working Papers 202094, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202094
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    Cited by:

    1. Qi-an Chen & Huashi Li & Jianyi Lin & Yunfeng Gao, 2025. "The Role of Housing Mortgage Leverage in Stock Asset Pricing: Evidence from the Chinese A-share Market," The Journal of Real Estate Finance and Economics, Springer, vol. 71(2), pages 209-253, August.
    2. Mehmet Balcilar & Gizem Uzuner & Festus Victor Bekun & Mark E. Wohar, 2023. "Housing price uncertainty and housing prices in the UK in a time-varying environment," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(2), pages 523-549, May.

    More about this item

    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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