RAND HRS CAMS Data File 2017 (V1), supported by NIA and SSA
The RAND HRS CAMS Data File 2017 (V1) is a user-friendly version of Part B of the CAMS survey. It contains annualized, cleaned, and aggregated spending and consumption variables with consistent and intuitive naming conventions across waves. Specifically, total household spending and household consumption are calculated across all categories and for these subsets of spending: nondurables, durables, housing and transportation. This data file can be easily merged to the RAND HRS Longitudinal File and other HRS files as described in the data codebook. The RAND HRS CAMS Data File 2017 (V1) is based on 2001 (V3), 2003 (V2), 2005 (V1), 2007 (V1), 2009 (V1), 2011 (V2), 2013 (V2), 2015 (V1), and 2017 (V1) final data releases.
The National Institute on Aging (NIA) and the Social Security Administration (SSA) provided funding and support for the development of this file.
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 CAMS Data File 2017 (V1) can be found in the “RAND Contributed Files” section on the right-hand side of the page.
For more detailed information, please see the documents:RAND HRS CAMS Data File 2017 (V1) Data Description (PDF) RAND HRS CAMS Data File 2017 (V1) Data Codebook (PDF)
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: