RAND HRS Detailed Imputations File 2014 (V2), supported by NIA and SSA
The RAND HRS Detailed Imputations File contains the component and ownership variables for all waves that are used in the income, wealth, and medical expenditures summary measures found in the RAND HRS Longitudinal File. It is distributed as a companion file to the RAND HRS Longitudinal File, and is especially useful for those who require more detail than that found in the RAND HRS Longitudinal File.
The method used to develop these imputations is described in the RAND HRS Detailed Imputations File Codebook. Each original income, wealth, and medical expenditure component is imputed separately, and the components are summed to create the summary measures found in the RAND HRS Longitudinal File (e.g., total household income, total wealth, total out-of-pocket medical expenditures). The original components can vary from wave to wave, and are combined when appropriate to provide consistency across waves.
The RAND HRS Detailed Imputations File 2014 (V2) incorporates HRS data from 1992, 1993, 1994, 1995, 1996, 1998, 2000, 2002, 2004, 2006, 2008, 2010, 2012, and 2014. The file incorporates only the core interviews, and does not include exit interviews or any restricted data.
To access the data:
- All HRS and RAND HRS data products are available at: https://hrs.isr.umich.edu/data-products.
- Click the "Register and Access Public Data" link in the bottom left-hand corner of the page.
- If you are not registered with HRS, please click the "New Users" link. Registration is free. You will receive a password within 24 hours.
- Once your account is active, please click the "Registered Users" link, and enter your Userid and Password.
- Click on the "Data Downloads" link, and you will be brought to a page that contains the various data sources that are available for download.
- The RAND HRS Detailed Imputations File 2014 (V2) can be found in the “RAND Contributed Files” section on the right-hand side of the page.
For more detailed information, please see the following documents:
Before doing so, however, we kindly request that users first consult the documentation that accompanies our data products, as we have found that our responses often point users to specific sections of the documentation that provide further detail on the variables mentioned in the users’ queries.
In addition, we recommend that users become familiar with some of the information provided on the HRS website, such as the HRS questionnaires and codebooks for the key variables under study.
We have also found the concordance tool extremely useful to help find available variables across waves: