CE Methodology

This page contains information on the methodology used to calculate and collect CE information and the quality of the CE data. Also included are links to the CE public use microdata documentation and files, and general articles and research papers using CE data including documents in the CE research library.


BLS Handbook of Methods

  • BLS Handbook of Methods, Chapter 16, Consumer Expenditures and Income (HTML) (PDF)

OPLC Program Comparisons

Frequently Asked Questions (FAQs)

Methodology Reports

    Data Quality in the CE

    The Consumer Expenditure Survey (CE) has historically provided some limited metrics for data users to evaluate the overall quality of output provided in its products. Published tables provide standard errors, the public-use microdata user guide provides response rates, and the public-use microdata datasets provide all the variables and flags necessary for users to create his or her own quality measures. There has long been a recognition for the need for more comprehensive data quality metrics that are timely and routinely updated, accessible to data users from a single source. However, there is also recognition of the high cost in terms of resources and commitment to identifying appropriate metrics and establishing the information base necessary to routinely produce reports on survey data quality. In order for this effort to be sustainable, the benefits from it must be relevant and useful to survey operations and data users.

    The Data Quality Profile Report is the first in a series of iterations towards a single reference source on a comprehensive set of CE data quality metrics that are timely and routinely updated for the Consumer Expenditure Quarterly Interview Survey (CEQ) and the Consumer Expenditure Diary Survey (CED). The initial measures presented in this first report are based on collected data and producible with limited resources. The decision to release the first report with only a very limited set of measures is based on the recognition of the benefits of “learning-by-doing” – providing CE with insight as to what resources might be needed to produce such a product routinely. As a better understanding of the infrastructure needed for creating measures of data quality in the CE develops, more metrics will be produced.

    Articles and Research Papers

    Public-Use Microdata

    Survey Forms


    Last Modified Date: November 23, 2015