Skip to content
A repository for analyses of the Fed's SCF.
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.

Survey of Consumer Finances


This is a repository that contains analyses around the Survey of Consumer Finances (SCF) put out by the Federal Reserve every 3 years. This takes a cross-sectional survey of the finances of U.S. families, in terms of their balance sheets, pensions, income, demographics, etc.

Analysis of the data associated to the survey is a bit complicated, for several reasons:

  • The survey design of the SCF itself is complicated. It involves the creation of 5 "replicates" for each family that participates in the survey. The data associated to each replicate is slightly different and imputed using a method described in this paper. This provides both privacy and more robust statistics due to the imputation of missing data in a variety of ways. Associated to this design is a collection of replicate weights that dictate how to analyze the data obtained from the replicates in an appropriate way.
  • It is a long survey, with many questions that have conditional responses based on previous questions;
  • The variables are coded in a variety of ways that require an examination of the codebook to interpret;
  • The public data set has a lot of censoring (e.g. of racial demographics) to protect the privacy of participants.


  • The data is loaded using the lodown package as recommended on the SCF website, which automatically obtains and parses the SCF survey data into 5 chunks of data, one for each replicate.

    It also obtains the replicate weight data and parses it into a format suitable for usage with the survey package.

  • The survey package is used to analyze the data. This package understands how to perform calculations on surveys when replicate weights are given, e.g. summary statistics, fitting linear models, etc.


Each analysis is contained in a subfolder of this directory. They are generally wrapped up in R project files and have dependencies managed via packrat, which should make them completely reproducible. Go to a subfolder and view the README for more specific information.

You can’t perform that action at this time.