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Price-volume Correlation in the Housing Market: Causality and Co-movements

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Abstract

Housing market cycles are featured by a positive correlation of prices and trading volume, which is conventionally attributed to a causal relationship between prices and volume. This paper analyzes the housing markets in 114 metropolitan statistical areas in the United States from 1990 to 2002, treats both prices and volume as endogenous variables, and studies whether and how exogenous shocks cause co-movements of prices and volume. At quarterly frequency, we find that, first, both home prices and trading volume are affected by conditions in labor markets, the mortgage market, and the stock market, and the effects differ between markets with low and high supply elasticity. Second, home prices Granger cause trading volume, but the effects are asymmetric—decreases in prices reduce trading volume, and increases in prices have no effect. Third, trading volume also Granger causes home prices, but only in markets with inelastic supply. Finally, we find a statistically significant positive price–volume correlation; which, however, is mainly explained by co-movements of prices and volume caused by exogenous shocks, instead of the Granger causality between prices and volume.

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Notes

  1. Falling prices reduce homeowners’ home equity values. Therefore, when homeowners want to sell their houses, to ensure that the proceeds from selling would be sufficient to repay their mortgages and provide down payments on new homes, they need to ask for higher prices, which increases the time on the market and reduces the trading volume.

  2. While there is a large literature in finance about the determinants of trading volume as well as return-volume relations in the stock market, this paper focuses on the theories that are specifically developed for housing markets and motivated by the fact that houses are both consumption goods and investments.

  3. It is worth noting that many housing analysts presume that volume increases lead price increases. For example, Miller and Sklarz (1986) show that changes in sales volume in Honolulu and Salt Lake lead price changes by one or two years.

  4. A list of excluded MSAs, PMSAs, and NECMs are available upon request.

  5. We also assume constant demolition rates as a percentage over total units, and our results are robust to this assumption.

  6. We conduct robustness checks for this specification by also including squared contemporaneous exogenous variables and lagged exogenous variables. Our estimation results are very similar and our Granger causality test results are intact.

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Acknowledgements

We thank Michael LaCour-Little, participants of 2005 AREUEA mid-year conference, seminar participants at Colorado University at Boulder, and two anonymous referees for insightful comments. All errors are ours.

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Authors and Affiliations

  1. Pension Real Estate Association, 100 Pearl Street, 13th Floor, Hartford, CT, 06103, USA

    Jim Clayton

  2. School of Business Administration, University of San Diego, 5998 Alcalá Park, San Diego, CA, 92110-2492, USA

    Norman Miller

  3. Leeds School of Business, University of Colorado at Boulder, 419 UCB, Boulder, CO, 80309-0419, USA

    Liang Peng

Authors
  1. Jim Clayton
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  2. Norman Miller
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  3. Liang Peng
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Corresponding author

Correspondence to Liang Peng.

Appendix: The list of the 114 MSAs in our analysis

Appendix: The list of the 114 MSAs in our analysis

Table 7 The list of the 114 MSAs in our analysis
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Clayton, J., Miller, N. & Peng, L. Price-volume Correlation in the Housing Market: Causality and Co-movements. J Real Estate Finan Econ 40, 14–40 (2010). https://doi.org/10.1007/s11146-008-9128-0

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