Survey of Consumer Finances (SCF)
The 2019 Survey of Consumer Finances (SCF) is the most recent survey conducted. Below are links to the bulletin article, interactive chartbook, historical bulletin tables, full public dataset, extract dataset, replicate weight files, and documentation.
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Summary Results
Disparities in Wealth by Race and Ethnicity in the 2019 Survey of Consumer Finances
Wealth and Income Concentration in the SCF: 1989-2019
SCF Interactive Chart
The SCF Interactive Chart creates time series charts representing estimates in the historic tables, and covers the period 1989 to the most recent survey year. For each variable and classification group, the charts show the percent of families in the group who have the item and the median and mean amounts of holdings for those who have the item. Users should be aware that because robust techniques were not used to calculate the mean estimates, results in some instances may be strongly affected by outliers. All dollar variables are inflation-adjusted to 2019 dollars.
See description of files and technical documentation for more information
Historic Tables
The following tables are based on those that have historically appeared in the Bulletin article. Estimates for all survey years from 1989 to the most recent survey year are included in both nominal and real terms.
File Type | File* | Documentation | Last Updated |
---|---|---|---|
Excel Based on Internal Data | Estimates in nominal dollars (2.6 MB Excel) Estimates inflation-adjusted to 2019 dollars (2.6 MB Excel) |
11/17/2020 | |
Excel Based on Public Data | Estimates in nominal dollars (2.5 MB Excel) Estimates inflation-adjusted to 2019 dollars (2.5 MB Excel) |
11/17/2020 |
See description of files and technical documentation for more information
Survey Data and Replicate Weight Files
WARNING: Please review the following PDF for instructions on how to calculate correct standard errors. As a result of multiple imputation, the dataset you are downloading contains five times the number of actual observations. Failure to account for the imputations and the complex sample design will result in incorrect estimation of standard errors.
File Type | Main Survey Data* | Replicate Weight File (X42001) | Documentation | Last Updated |
---|---|---|---|---|
SAS | CPORT version (11 MB ZIP)** COPY/EXPORT version (15 MB ZIP)** |
CPORT version (34 MB ZIP) COPY/EXPORT version (34 MB ZIP) |
3/10/2022 | |
STATA | Stata version (10 MB ZIP)** | Stata version (36 MB ZIP) | 3/10/2022 | |
ASCII | ASCII (42 MB ZIP)** Variable Map: Excel (Excel) Variable Map: Tab-delimited (ASCII) |
3/10/2022 |
**See See Recent Changes page
See description of files and technical documentation for more information
Special note to R users: An outside programmer has created scripts for converting and working with SCF data. These scripts are available for download from: http://asdfree.com/survey-of-consumer-finances-scf.html
File Type | File* | Documentation | Last Updated |
---|---|---|---|
SDA online analysis | SDA analysis tool |
Creating SCF Bulletin Tables in SDA (DOC) |
11/04/2021 |
SAS | SAS extract data (3 MB ZIP) | 11/04/2021 | |
STATA | Stata extract data (3 MB ZIP) | 11/04/2021 | |
CSV | CSV extract data (3 MB ZIP) | 11/04/2021 |
See description of files and technical documentation for more information
Documentation
File* | Last Updated |
---|---|
Codebook (2.6 MB ASCII) | 9/28/2020 |
Showcards (PDF) | 9/28/2020 |
Questionnaire Outline (PDF) | 9/28/2020 |
MR Interview Program (10 MB ASCII) | 9/28/2020 |
See description of files and technical documentation for more information
Description of files and technical documentation
SCF Interactive Chart
The SCF Interactive Chart contains time series charts using triennial SCF data covering the period 1989 to 2019. The variables included are ones that appear in a selected set of the tables in the Bulletin article. For each variable and classification group, the charts show the percent of families in the group who have the item and the median and mean amounts of holdings for those who have any. All dollar estimates are given in 2019 dollars. The definitions of the summary variables are given by the SAS program used to create them.
Tables based on public data
The calculations reported in these tables are weighted estimates made from the public data. These calculations may be convenient for users who want to ensure that their estimates align with those made for the writing of the most recent Bulletin article. The program that creates the variables can be found in the documentation column of the table.
Table based on internal data
The calculations reported in these tables are weighted estimates made from the internal data, incorporating any weighting adjustments implemented in the analysis of those data for purposes of the summary articles in the Federal Reserve Bulletin. The program that creates the variables can be found in the documentation column of the table.
Description of full public data set files
SAS format
The full final survey data are available to the public in two SAS transport formats that may be used with the current version of SAS. (Help is available for importing these files as SAS data sets.) One version is created using PROC CPORT; this is the smaller of the two files. The second one is created using PROC COPY with the EXPORT option; this file may be particularly convenient for users who do not have access to SAS, but who do have some means of translating the data set to another form using a software package that does not support CPORT files.
STATA format
Because the data set contains approximately 5300 variables, users will need to use Stata SE if they wish to import all the variables. Users of standard Stata will need to specify a subset of variables when using the data set.
ASCII format
The variables included in the ASCII format have exactly the same values as those in the SAS and Stata data set. The layout of the variables is given by a format file, which is provided in Excel and tab-delimited formats. Note that under certain operating systems the end of record marker will add one character to the record length listed in the format file.
Description of summary extract public data files
SDA analysis tool
A program provided by a third party for the online analysis of summary variables such as the statistics found in the Federal Reserve Bulletin article. SDA is developed and maintained by the Computer-assisted Survey Methods Program (CSM) at the University of California, Berkeley. The Help/FAQ file linked to at the top of the SDA page provides instructions on how to perform analysis of the data.
SAS format
The summary extract data set contains variables used in the Federal Reserve Bulletin article. All dollar variables have been inflation-adjusted to 2019 dollars. Definitions of the variables in the summary extract dataset can be found in the SAS program used to create the data set. The SAS version is created using PROC CPORT, a version using PROC COPY and the EXPORT option is not provided due to the limitation on the length of variable names when using the EXPORT option.
CSV format
Due to column limitations in versions of Excel prior to 2007, the full file can only be viewed in Excel 2007 and later versions.
About the documentation
Codebook for the 2019 Survey of Consumer Finances
The codebook contains the text, variable names, and responses for the questions asked in the survey. Also provided are a brief summary of the technical features of the survey design; a copy of the source code for the CAPI program, a concordance of variable names in the final data set and those used in the CAPI program; two programs that calculate standard errors for regression models and another program to calculate standard errors for simple statistics such as weighted medians, all three of which account for sampling error and multiple imputation; and a list of the variables included in the public data set.
Net Worth Flowchart
This flowchart shows how net worth is calculated using the various asset and debt variables available in the Summary Extract Dataset.
Showcards
At key points during the administration of the interview, interviewers show the respondents a series of cards containing information relevant to framing or answering a question. Most of this information is displayed as part of the question text or response categories, but some is more general.
Questionnaire Outline
This outline cover the major topics addressed in the interview and it includes a reference to the SCF variable numbers. Users may wish to consult this outline to identify areas of interest and then use the variable numbers to locate the more detailed information given in the codebook.
MR Interview (r) Computer Code used for Computer-Assisted Personal Interviewing (CAPI)
The 2019 survey data were collected using CAPI. A copy of the source code for the program is provided below. In previous years of the SCF, an executable version of the CAPI program has been provided, but for 2019, only a text version of the program code is available. Right click and choose save, then change the file extension to .mdd and this should allow licensed users of MR Interview to use the file with the software.
Missing Data
Missing data in the survey have been imputed five times using a multiple imputation technique. The information is stored in five separate imputation replicates (implicates). Thus, for the 5,783 families interviewed for the survey, there are 28,915 records in the data set. Six observations were deleted for the public version of the data set for purposes of disclosure avoidance; thus, there are 28,885 records in the public data set for 5,777 families. The codebook provides more detail on the structure of the data set and the steps taken for disclosure avoidance.
Replicate Weight Files
For many purposes, one must consider the sampling error of SCF estimates. However, because detailed information on the sample design cannot be released, and because of the complexity of the SCF design, users cannot apply some of the standard procedures for variance estimation.
A set of sample replicates has been created with bootstrap techniques and analysis weights have been computed independently for each replicate. Analysts may use these weights to make approximate estimates of sampling variance. Replicate weights corresponding to X42001 are available. See the codebook (txt) for more details. When uncompressed and restored to a V9.1.3 engine SAS data set, each file requires approximately 70 MB of disk space.
* Some browser versions will download these files in unzipped form; the resulting files may require up to 72 MB of disk space. All of the versions of the full and summary extract public data sets are provided in compressed form as WINZIP files. Return to text