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• W2890617368 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." @default.
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• W2890617368 date "2018-09-01" @default.
• W2890617368 modified "2023-10-16" @default.
• W2890617368 title "Measuring Aggregate Housing Wealth: New Insights from an Automated Valuation Model" @default.
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• W2890617368 doi "https://doi.org/10.17016/feds.2018.064" @default.
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