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

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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.

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  • 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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    1. Michelle H. Dreiman & Anthony Pennington-Cross, 2004. "Alternative Methods of Increasing the Precision of Weighted Repeat Sales House Prices Indices," The Journal of Real Estate Finance and Economics, Springer, vol. 28(4), pages 299-317, May.
    2. Christopher D. Carroll & Misuzu Otsuka & Jiri Slacalek, 2011. "How Large Are Housing and Financial Wealth Effects? A New Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(1), pages 55-79, February.
    3. John M. Clapp & Hyon–Jung Kim & Alan E. Gelfand, 2002. "Predicting Spatial Patterns of House Prices Using LPR and Bayesian Smoothing," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 30(4), pages 505-532.
    4. Jack Favilukis & Sydney C. Ludvigson & Stijn Van Nieuwerburgh, 2017. "The Macroeconomic Effects of Housing Wealth, Housing Finance, and Limited Risk Sharing in General Equilibrium," Journal of Political Economy, University of Chicago Press, vol. 125(1), pages 140-223.
    5. William B. Peterman & Kamila Sommer, 2019. "How Well Did Social Security Mitigate The Effects Of The Great Recession?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 60(3), pages 1433-1466, August.
    6. David Genesove & Christopher Mayer, 2001. "Loss Aversion and Seller Behavior: Evidence from the Housing Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(4), pages 1233-1260.
    7. Goodman, John Jr. & Ittner, John B., 1992. "The accuracy of home owners' estimates of house value," Journal of Housing Economics, Elsevier, vol. 2(4), pages 339-357, December.
    8. Case, Bradford & Pollakowski, Henry O & Wachter, Susan M, 1997. "Frequency of Transaction and House Price Modeling," The Journal of Real Estate Finance and Economics, Springer, vol. 14(1-2), pages 173-187, Jan.-Marc.
    9. Saez, Emmanuel & Zucman, Gabriel, 2014. "Wealth Inequality in the United States since 1913: Evidence from Capitalized Income Tax Data," CEPR Discussion Papers 10227, C.E.P.R. Discussion Papers.
    10. Matteo Iacoviello & Stefano Neri, 2010. "Housing Market Spillovers: Evidence from an Estimated DSGE Model," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(2), pages 125-164, April.
    11. Katherine A. Kiel & Jeffrey E. Zabel, 1999. "The Accuracy of Owner‐Provided House Values: The 1978–1991 American Housing Survey," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 27(2), pages 263-298, June.
    12. Ferreira, Fernando & Gyourko, Joseph & Tracy, Joseph, 2010. "Housing busts and household mobility," Journal of Urban Economics, Elsevier, vol. 68(1), pages 34-45, July.
    13. Jung Hyun Choi & Gary Painter, 2018. "Self†Reported vs. Market Estimated House Values: Are Homeowners Misinformed or Are They Purposely Misreporting?," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 46(2), pages 487-520, June.
    14. Sewin Chan & Samuel Dastrup & Ingrid Gould Ellen, 2016. "Do Homeowners Mark to Market? A Comparison of Self-Reported and Estimated Market Home Values During the Housing Boom and Bust," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 44(3), pages 627-657, July.
    15. Gatzlaff, Dean H & Haurin, Donald R, 1997. "Sample Selection Bias and Repeat-Sales Index Estimates," The Journal of Real Estate Finance and Economics, Springer, vol. 14(1-2), pages 33-50, Jan.-Marc.
    16. Jesse M. Abraham & William S. Schauman, 1991. "New Evidence on Home Prices from Freddie Mac Repeat Sales," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 19(3), pages 333-352, September.
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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, pages 147-170, 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. Garbarino, Nicola & Guin, Benjamin, 2021. "High water, no marks? Biased lending after extreme weather," Journal of Financial Stability, Elsevier, vol. 54(C).
    4. 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.
    5. 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.).
    6. 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, pages 641-677, National Bureau of Economic Research, Inc.

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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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