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What can Fifty-Two Collateralizable Wealth Measures tell us about Future Housing Market Returns? Evidence from U.S. State-Level Data

Author

Listed:
  • Mehmet Balcilar

    (Eastern Mediterranian University)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa)

  • Ricardo M. Sousa

    (University of Minho, NIPE and LSE Alumni Association)

  • Mark E. Wohar

    (College of Business Administration, University of Nebraska at Omaha, 6708 Pine Street, Omaha, NE 68182, USA; School of Business and Economics, Loughborough University, Leicestershire, LE11 3TU, UK)

Abstract

We use a novel U.S. state-level database to evaluate the role of housing wealth as a provider of collateral services. First, we estimate the cointegrating relationship between housing wealth and labour income for all 50 states, as well as the District of Columbia (D.C.), and overall U.S. We do not find evidence of a structural break in such link due to the presence of economic recessions or financial crises. Then, we assess the predictive ability of the housing wealth-to-income ratios (labelled by hwy) for state-level future real housing returns. We uncover: (i) positive estimates for the elasticity of housing wealth with respect to labour income, which are also largely heterogeneous across U.S. states; and (ii) a negative link between the housing wealth-to-income ratios and future housing returns, albeit the forecasting power of hwy also varies considerably across states. We conclude that country-level regressions typically "mask" this diversity of features surrounding the usefulness of housing in collateral provision and unfavourable labour income shock smoothing that state-level frameworks are able to recover.

Suggested Citation

  • Mehmet Balcilar & Rangan Gupta & Ricardo M. Sousa & Mark E. Wohar, 2019. "What can Fifty-Two Collateralizable Wealth Measures tell us about Future Housing Market Returns? Evidence from U.S. State-Level Data," Working Papers 201974, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201974
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    Cited by:

    1. Lake, A., 2020. "Behavioural Finance at Home: Testing Deviations of House Prices from their Fundamental Values," Cambridge Working Papers in Economics 20104, Faculty of Economics, University of Cambridge.
    2. 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.

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    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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