Imputing Missing Values in the US Census Bureau's County Business Patterns

41 Pages Posted: 29 Jan 2020 Last revised: 14 Feb 2020

See all articles by Peter Schott

Peter Schott

Yale University

Natalie Yang

University of Chicago

Fabian Eckert

University of California, San Diego (UCSD), Division of Social Sciences, Department of Economics

Teresa Fort

Dartmouth College - Tuck School of Business

Multiple version iconThere are 2 versions of this paper

Date Written: January 2020

Abstract

The County Business Patterns data published by the US Census Bureau track employment by county and industry from 1946 to the present. Two features of the data limit their usefulness to researchers in practice: (1) employment for the majority of county-industry cells is suppressed to protect confidentiality, and (2) industry classifications change over time. We address both issues. First, we develop a linear programming method that exploits the large set of adding-up constraints implicit in the hierarchical arrangement of the data to impute missing employment. Second, we provide concordances to map all data to a consistent set of industry codes.

Suggested Citation

Schott, Peter and Yang, Natalie and Eckert, Fabian and Fort, Teresa, Imputing Missing Values in the US Census Bureau's County Business Patterns (January 2020). CEPR Discussion Paper No. DP14352, Available at SSRN: https://ssrn.com/abstract=3526078

Peter Schott

Yale University ( email )

New Haven, CT 06520
United States

Natalie Yang

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

Fabian Eckert (Contact Author)

University of California, San Diego (UCSD), Division of Social Sciences, Department of Economics ( email )

CA
United States

Teresa Fort

Dartmouth College - Tuck School of Business ( email )

Hanover, NH 03755
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
1
Abstract Views
209
PlumX Metrics