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Quality-Adjusted House Price Indexes

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  • Adam D. Nowak
  • Patrick S. Smith

Abstract

The constant-quality assumption in repeat-sales house price indexes (HPIs) introduces a significant time-varying attribute bias. The direction, magnitude, and source of the bias varies throughout the market cycle and across metropolitan statistical areas (MSAs). We mitigate the bias using a data-driven textual analysis approach that identifies and includes salient text from real estate agent remarks in the repeat-sales estimation. Absent the text, MSA-level HPIs are biased downward by as much as 7 percent during the financial crisis and upward by as much as 20 percent after the crisis. The geographic concentration of the bias magnifies its effect on local HPIs.

Suggested Citation

  • Adam D. Nowak & Patrick S. Smith, 2020. "Quality-Adjusted House Price Indexes," American Economic Review: Insights, American Economic Association, vol. 2(3), pages 339-356, September.
    • Handle: RePEc:aea:aerins:v:2:y:2020:i:3:p:339-56
    DOI: 10.1257/aeri.20190337
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    References listed on IDEAS

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    Cited by:

    1. William N Goetzmann & Christophe Spaenjers & Stijn Van Nieuwerburgh, 2021. "Real and Private-Value Assets [Gendered prices]," The Review of Financial Studies, Society for Financial Studies, vol. 34(8), pages 3497-3526.
    2. Walter D'Lima & Luis Arturo Lopez & Archana Pradhan, 2022. "COVID‐19 and housing market effects: Evidence from U.S. shutdown orders," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(2), pages 303-339, June.
    3. Stephen L. Ross & Tingyu Zhou, 2020. "Documenting Loss Aversion Using Evidence of Round Number Bias," Working Papers 2020-079, Human Capital and Economic Opportunity Working Group.
    4. Collins, Courtney A. & Kaplan, Erin K., 2022. "Demand for School Quality and Local District Administration," Economics of Education Review, Elsevier, vol. 88(C).
    5. Gallin, Joshua & Molloy, Raven & Nielsen, Eric & Smith, Paul & Sommer, Kamila, 2021. "Measuring aggregate housing wealth: New insights from machine learning ☆," Journal of Housing Economics, Elsevier, vol. 51(C).
    6. Cigdem Gedikli & Robert Hill & Oleksandr Talavera & Okan Yilmaz, 2023. "The hidden cost of smoking: Rent premia in the housing market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(3), pages 611-629, May.
    7. Pollack, Adam B. & Kaufmann, Robert K., 2022. "Increasing storm risk, structural defense, and house prices in the Florida Keys," Ecological Economics, Elsevier, vol. 194(C).
    8. Crocker H. Liu & Patrick S. Smith, 2023. "School quality as a catalyst for bidding wars and new housing development," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 51(4), pages 785-818, July.
    9. Stephen L. Ross & Tingyu Zhou, 2020. "Documenting Loss Aversion using Evidence of Round Number Bias," Working papers 2020-17, University of Connecticut, Department of Economics.

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    More about this item

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • 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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