Featured below and available for download are raw survey datasets. The FDIC code used to generate all analysis datasets from the raw (unedited) Census files is available inside the zip files, as is a data dictionary summarizing all analysis variables and comparability across survey years. Each zip file also contains a sample SAS, Stata, and R program to read in the CSV data.
Downloads
Public-use Current Population Survey (CPS) Unbanked/Underbanked supplement files from January 2009, June 2011, June 2013, June 2015, June 2017, and June 2019 are available for download. Raw (unedited) data, documentation, and replicate weights (to support balanced repeated replication variance estimates) can be downloaded from the Census Bureau. See Census’ CPS website for additional detail on survey methodology and other documentation. For information on analytic variables created from the CPS data, see the data dictionary.
In addition, household-level analysis datasets containing the variables described in the 2009, 2011, 2013, 2015, 2017, and 2019 FDIC published reports are available below, along with relevant documentation.
2009-2019 Multi-Year Analysis Dataset
The 2009-2019 Multi-Year Analysis Dataset contains analysis variables from the 2009, 2011, 2013, 2015, 2017, and 2019 surveys. As detailed in the data dictionary, many of these variables are comparable over time and are central to the analyses described in the published survey reports.
The 2009-2019 Multi-Year Analysis Dataset contains single-year weights over time for comparison and also five-year weights for 2009-2013, 2011-2015, 2013-2017, and 2015-2019 to generate five-year averaged estimates. Five-year weights can be used to generate estimates for smaller geographies/subpopulations with insufficient sample size to generate estimates in any one year.
Yearly Analysis Datasets
The yearly analysis household-level datasets include the raw (unedited) variables from the base CPS and Unbanked/Underbanked Supplement, in addition to the relevant analysis variables as described in the data dictionary above.
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