Abstract

Earnings nonresponse in household surveys is widespread, yet there is limited knowledge of how nonresponse biases earnings measures. We examine the consequences of nonresponse on earnings gaps and inequality using Current Population Survey individual records linked to administrative earnings data. The common assumption that earnings are missing at random is rejected. Nonresponse across the earnings distribution is U-shaped, highest in the left and right tails. Inequality measures differ between household and administrative data due in part to nonresponse. Nonresponse biases earnings differentials by race, gender, and education, particularly in the tails. Flexible copula-based models can account for nonrandom nonresponse.

Document Type

Article

Publication Date

10-2019

Notes/Citation Information

Published in Journal of Political Economy, v. 127, no. 5.

© 2019 by The University of Chicago. All rights reserved.

The copyright holder has granted the permission to post the article here.

Digital Object Identifier (DOI)

https://doi.org/10.1086/701807

Related Content

Supplementary materials are available online at https://www.journals.uchicago.edu/doi/suppl/10.1086/701807.

Available for download on Thursday, October 01, 2020

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