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The Dynamics of Liquidity in Commercial Property Markets: Revisiting Supply and Demand Indexes in Real Estate

Author

Listed:
  • Dorinth W. Dijk

    (MIT Center for Real Estate
    Economic Policy, Research Department)

  • David M. Geltner

    (MIT Center for Real Estate)

  • Alex M. Minne

    (School of Business, Department of Finance)

Abstract

A common definition of liquidity in real estate investment is the ability to sell property assets quickly at full value, as reflected by transaction volume. The present paper makes methodological and conceptual contributions in the study and understanding of liquidity. First, we extend the Fisher et al. (Real Estate Economics, 31(2), 269–303, 2003) Fisher et al. (The Journal of Real Estate Finance and Economics, 34(1), 5–33, 2007) methodology for the separate tracking of changes in reservation prices on the demand (potential buyers) and supply (potential sellers) sides of the asset market. We show how to apply the methodology to a repeat sales indexing framework, allowing application to typical commercial property transaction price datasets, which lack appraisal valuations or complete data regarding property characteristics. We also use a Bayesian, structural time series approach to estimate the indexes. These methodological enhancements enable much more granular supply and demand index estimation, including at the metropolitan level. Second, we propose a Liquidity Metric based on the indexes, and show that the normal liquidity dynamic in commercial property asset markets is “pro-cyclical”, that is, price and trading volume tend to move together, with demand tending to lead supply. Additionally, we observe an “anomalous” dynamic that occurs about 25 percent of the time, in which the Liquidity Metric declines while consummated prices are rising. This anomalous dynamic is often associated with the end of a period of rapid price growth.

Suggested Citation

  • Dorinth W. Dijk & David M. Geltner & Alex M. Minne, 2022. "The Dynamics of Liquidity in Commercial Property Markets: Revisiting Supply and Demand Indexes in Real Estate," The Journal of Real Estate Finance and Economics, Springer, vol. 64(3), pages 327-360, April.
  • Handle: RePEc:kap:jrefec:v:64:y:2022:i:3:d:10.1007_s11146-020-09782-5
    DOI: 10.1007/s11146-020-09782-5
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    References listed on IDEAS

    as
    1. Genesove, David & Han, Lu, 2012. "Search and matching in the housing market," Journal of Urban Economics, Elsevier, vol. 72(1), pages 31-45.
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    17. Paul E. Carrillo & Eric R. Wit & William Larson, 2015. "Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the United States and the Netherlands," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 43(3), pages 609-651, September.
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    Cited by:

    1. Ahlfeldt, Gabriel M. & Heblich, Stephan & Seidel, Tobias, 2023. "Micro-geographic property price and rent indices," Regional Science and Urban Economics, Elsevier, vol. 98(C).
    2. 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.

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    More about this item

    Keywords

    Liquidity; Commercial real estate; Bayesian repeat sales price index; Equilibrium dynamics; Constant liquidity index;
    All these keywords.

    JEL classification:

    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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