The Census-Enhanced Health and Retirement Study (CenHRS) project links Health and Retirement Study (HRS) respondents to data on a broad range of characteristics of their employers.

Linkage of these employer data to the HRS creates a unique data infrastructure. The HRS includes data on wealth, income, work, demographics, family structure, expectations, health, and cognition; modules on a wide range of economic and health topics; links to other administrative data including Social Security earnings records, company pension plans, and Medicare expenditures and treatments; and, most recently, biomarkers including genetic sequences. Employer data include information on organizational structure, firm size, employment, industry, location, investment, factor inputs, international transactions, and characteristics of the firm’s workforce, including earnings, age, race, gender, immigrant status, and employment tenure. Together, these data will be valuable to researchers across the economics, health, sociology, and psychology disciplines, among others. To learn more about these data and how to access them, see our NBER Summer Institute Aging Workshop slides and application procedures overview. To read a draft of our paper describing the linkage approach and using the data, “Finding Needles in Haystacks: Multiple-Imputation Record Linkage Using Machine Learning,” email us at CenHRSinfo@umich.edu.