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How Well Do Individuals Predict the Selling Prices of Their Homes?

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  • Hugo Benitez-Silva
  • Selcuk Eren
  • Frank Heiland
  • Sergi Jimenez-Martín

Abstract

Self-reported home values are widely used as a measure of housing wealth by researchers; the accuracy of this measure, however, is an open empirical question, and requires some type of market assessment of the values reported. In this study, the authors examine the predictive power of self-reported housing wealth when estimating housing prices, utilizing the portion of the University of Michigan's Health and Retirement Study covering 1992-2006. They find that homeowners, on average, overestimate the value of their properties by 5–10 percent. More importantly, the authors establish a strong correlation between accuracy and the economic conditions at the time of the property's purchase. While most individuals overestimate the value of their property, those who buy during more difficult economic times tend to be more accurate; in some cases, they even underestimate the property's value. The authors find a surprisingly strong, likely permanent, and in many cases long-lived effect of the initial conditions surrounding the purchase of properties, and on how individuals value them. This cyclicality of the overestimation of house prices provides some explanation for the difficulties currently faced by many homeowners, who were expecting large appreciations in home value to rescue them in case of interest rate increases--which could jeopardize their ability to live up to their financial commitments.

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  • Hugo Benitez-Silva & Selcuk Eren & Frank Heiland & Sergi Jimenez-Martín, 2009. "How Well Do Individuals Predict the Selling Prices of Their Homes?," Economics Working Paper Archive wp_571, Levy Economics Institute.
  • Handle: RePEc:lev:wrkpap:wp_571
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    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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