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Measuring Aggregate Housing Wealth : New Insights from an Automated Valuation Model

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  • Joshua H. Gallin
  • Raven S. Molloy
  • Eric R. Nielsen
  • Paul A. Smith
  • Kamila Sommer

Abstract

We construct a new measure of aggregate U.S. housing wealth based on Zillow's Automated Valuation Model (AVM). AVMs offer advantages over other methods because they are based on recent market transaction prices, utilize large datasets which include property characteristics and local geographic variables, and are updated frequently with little lag. However, using Zillow's AVM to measure aggregate housing wealth requires overcoming several challenges related to the representativeness of the Zillow sample. We propose methods that address these challenges and generate a new estimate of aggregate U.S. housing wealth from 2001 to 2016. This new measure provides insights into some of the disadvantages of other approaches to measuring housing wealth. Specifically, with respect to the owner valuations typically used in survey data, it appears that homeowners were slow to recognize the drop in housing wealth during the financial crisis and that their estimates of this drop were unrealistically small. At the same time, repeat-sales price indexes appear to overstate the extent of the drop in value between 2006 and 2011 and overstate the recovery thereafter.

Suggested Citation

  • Joshua H. Gallin & Raven S. Molloy & Eric R. Nielsen & Paul A. Smith & Kamila Sommer, 2018. "Measuring Aggregate Housing Wealth : New Insights from an Automated Valuation Model," Finance and Economics Discussion Series 2018-064, Board of Governors of the Federal Reserve System (U.S.).
  • Handle: RePEc:fip:fedgfe:2018-64
    DOI: 10.17016/FEDS.2018.064
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    Cited by:

    1. Tomaz Cajner & Leland D. Crane & Ryan A. Decker & Adrian Hamins-Puertolas & Christopher Kurz, 2019. "Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data," NBER Chapters, in: Big Data for Twenty-First Century Economic Statistics, National Bureau of Economic Research, Inc.
    2. Lepinteur, Anthony & Waltl, Sofie R., 2020. "Tracking Owners' Sentiments: Subjective Home Values, Expectations and House Price Dynamics," Department of Economics Working Paper Series 299, WU Vienna University of Economics and Business.
    3. Emmanuel Saez & Gabriel Zucman, 2020. "Trends in US Income and Wealth Inequality: Revising After the Revisionists," NBER Working Papers 27921, National Bureau of Economic Research, Inc.
    4. Michael M. Batty & Jesse Bricker & Joseph S. Briggs & Alice Henriques Volz & Elizabeth Ball Holmquist & Susan Hume McIntosh & Kevin B. Moore & Eric R. Nielsen & Sarah Reber & Molly Shatto & Kamila Som, 2019. "Introducing the Distributional Financial Accounts of the United States," Finance and Economics Discussion Series 2019-017, Board of Governors of the Federal Reserve System (U.S.).
    5. Michael Batty & Jesse Bricker & Joseph Briggs & Sarah Friedman & Danielle Nemschoff & Eric Nielsen & Kamila Sommer & Alice Henriques Volz, 2021. "The Distributional Financial Accounts of the United States," NBER Chapters, in: Measuring Distribution and Mobility of Income and Wealth, National Bureau of Economic Research, Inc.
    6. Garbarino, Nicola & Guin, Benjamin, 2020. "High water, no marks? Biased lending after extreme weather," Bank of England working papers 856, Bank of England.

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    More about this item

    Keywords

    Consumer economics and finance; Data collection and estimation; Flow of funds; Residential real estate;
    All these keywords.

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • 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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