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Theoretical Models on Distinguishing Market Conditions

Author

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  • Paul Anglin
  • Yanmin Gao

Abstract

We offer two perspectives on using evidence to distinguish a “buyers’ market” from a “sellers’ market” from “balanced” market conditions in a real estate market. The first perspective recognizes the effects of randomness and studies how to weigh multiple indicators of market conditions when estimating the hidden state of the market. We derive optimal weights based on the sensitivity and the noisiness of each indicator. Numerical simulations suggest the magnitude of the benefits associated with optimal weighting. Our second perspective emphasizes that the current state of the market depends on lagged indicators. Using the case of two indicators, we characterize the time path jointly and discuss the short term and medium term properties of the solution. In particular, those properties help when trying to understand how long unbalanced market conditions would persist. These two perspectives enable us to discuss specific examples which illustrate why the definition of, say, a sellers’ market can be confusing. We suggest that the use of a likelihood ratio may help.

Suggested Citation

  • Paul Anglin & Yanmin Gao, 2025. "Theoretical Models on Distinguishing Market Conditions," ERES eres2025_72, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2025_72
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    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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