Using the Health and Retirement Study To Analyze Housing Decisions, Housing Values, and Housing Prices
Data Shop, a department of Cityscape, presents short articles or notes on the uses of data in housing and urban research. Through this department, PD&R introduces readers to new and overlooked data sources and to improved techniques in using well-known data. The emphasis is on sources and methods that analysts can use in their own work. Researchers often run into knotty data problems involving data interpretation or manipulation that must be solved before a project can proceed, but they seldom get to focus in detail on the solutions to such problems. If you have an idea for an applied, data-centric note of no more than 3,000 words, please send a one-paragraph abstract to email@example.com for consideration.
As with the articles in this issue, this introduction reflects the views of the authors and does not necessarily reflect the views of the U.S. Department of Housing and Urban Development.
Few existing surveys provide detailed longitudinal information on households and their homes. This article introduces a data source, the Health and Retirement Study (HRS), which has this detailed information but has received little attention by housing researchers to date. The HRS is a rich longitudinal data set that provides information on house values, house prices, and detailed personal characteristics of those who own and sell their homes. The HRS is a nationally representative longitudinal survey that originally sampled 7,700 households headed by an individual aged 51 to 61 in the first interviews in 1992 and 1993. It now also samples additional cohorts of older Americans. Although the HRS is the data set of choice when analyzing the retirement behavior, savings, and health status of older Americans, given its wealth of demographic, health, and socioeconomic data, it has been rarely used to answer questions regarding the housing market. A seldom used section of the questionnaire provides detailed information about real estate transactions by households, however, enabling researchers to repeatedly observe both self-reported house values and the actual selling prices of properties sold since 1992 (originally bought in the past five decades). The article describes a number of important housing-related measures available in the HRS and illustrates the usefulness of these data by conducting a statistical analysis of the accuracy of self-reported home values. Specifically, we analyze the predictive power of self-reported housing wealth when estimating housing prices using the HRS data. The evidence shows a slight overestimation of housing values by older Americans.
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