Using the Health and Retirement Study to Analyze Housing Decisions, Housing Values, and Housing Prices

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.

Using Smart Source Parsing pp

Personal Income, Wealth, and Their Distributions/Housing Demand/Housing/Wealth/Asset accumulation/retirement planning/Mobility/property values

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