@article {7504, title = {Using the Health and Retirement Study to Analyze Housing Decisions, Housing Values, and Housing Prices}, journal = {Cityscape: A Journal of Policy Development and Research}, volume = {12}, year = {2010}, note = {Using Smart Source Parsing pp}, pages = {149-58}, publisher = {12}, abstract = {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.}, keywords = {Consumption and Savings, Demographics, Housing, Income, Net Worth and Assets, Retirement Planning and Satisfaction}, author = {Hugo Ben{\'\i}tez-Silva and Sel{\c c}uk Eren and Frank Heiland and Jimenez-Martin, Sergi} } @article {5748, title = {How Well Do Individuals Predict the Selling Prices of Their Homes?}, number = {No. 571}, year = {2008}, institution = {The Levy Economics Institute}, address = {New York, New York}, abstract = {Self-reported home values are widely used as a measure of housing wealth by researchers employing a variety of data sets and studying a number of different individual and household level decisions. The accuracy of this measure is an open empirical question, and requires some type of market assessment of the values reported. In this research, we study the predictive power of self-reported housing wealth when estimating sales prices utilizing the Health and Retirement Study. We find that homeowners, on average, overestimate the value of their properties by between 5 and 10 . We also find a strong correlation between accuracy and the economic conditions (measured by the prevalent interest rate, the growth of household income, and the growth of median housing prices) at the time of the purchase of the property. While most individuals overestimate the value of their properties, those who bought during more difficult economic times tend to be more accurate, and in some cases even underestimate the value of their house. This cyclicality of the overestimation of house prices can provide some clues regarding the reasons for the difficulties currently faced by many homeowners.}, keywords = {Housing, Net Worth and Assets}, doi = {http://dx.doi.org/10.2139/ssrn.1107165}, author = {Hugo Ben{\'\i}tez-Silva and Sel{\c c}uk Eren and Frank Heiland and Jimenez-Martin, Sergi} }