Misclassification Errors and the Underestimation of U.S. Unemployment Rates

40 Pages Posted: 12 Jul 2010 Last revised: 8 May 2025

See all articles by Shuaizhang Feng

Shuaizhang Feng

Shanghai University of Finance and Economics - Department of Economics; Princeton University; IZA Institute of Labor Economics

Yingyao Hu

University of Texas at Austin

Abstract

Using recent results in the measurement error literature, we show that the official U.S. unemployment rates substantially underestimate the true levels of unemployment, due to misclassification errors in labor force status in Current Population Surveys. Our closed-form identification of the misclassification probabilities relies on the key assumptions that the misreporting behaviors only depend on the true values and that the true labor force status dynamics satisfy a Markov-type property. During the period of 1996 to 2009, the corrected monthly unemployment rates are 1 to 4.6 percentage points (25% to 45%) higher than the official rates, and are more sensitive to changes in business cycles. Labor force participation rates, however, are not affected by this correction. We also provide results for various subgroups of the U.S. population defined by gender, race and age.

Keywords: Current Population Survey, unemployment rate, labor force participation rate, misclassification, measurement error

JEL Classification: J21, J64, C14

Suggested Citation

Feng, Shuaizhang and Hu, Yingyao, Misclassification Errors and the Underestimation of U.S. Unemployment Rates. IZA Discussion Paper No. 5057, Available at SSRN: https://ssrn.com/abstract=1638513

Shuaizhang Feng (Contact Author)

Shanghai University of Finance and Economics - Department of Economics ( email )

777 Guoding Road
Shanghai, AK Shanghai 200433
China

Princeton University

22 Chambers Street
Princeton, NJ 08544-0708
United States

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

Yingyao Hu

University of Texas at Austin ( email )

2317 Speedway
Austin, TX Texas 78712
United States

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