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Potential Biases in Measurement of Wage Inequality

Paper Session

Saturday, Jan. 6, 2018 8:00 AM - 10:00 AM

Pennsylvania Convention Center, 203-A
Hosted By: Labor and Employment Relations Association
  • Chair: Samuel L. Myers Jr., University of Minnesota-Twin Cities

Examining the Black-White Earnings Differential with Administrative Records

Michael S. Gideon
,
U.S. Census Bureau
Misty L. Heggeness
,
U.S. Census Bureau
Marta Murray-Close
,
U.S. Census Bureau
Samuel L. Myers Jr.
,
University of Minnesota-Twin Cities

Abstract

In this paper, we explore how measurement error affects estimated returns to human capital characteristics in predicting earnings. We find that estimated returns to age and education may depend on the source of earnings data and that the impact of changing the source data may differ by race. Using standard analytical tools for measuring wage discrimination, we find that less of the racial wage gap is explained by worker characteristics when using a Current Population Survey Annual Social and Economic Supplement (CPS ASEC) self-reported earnings measure rather than a measure of earnings from the Social Security Administration’s Detailed Earnings Record (DER). While other studies have examined issues of misreporting, specifically at the tail ends of the income distribution, our analysis extends beyond distributional changes to examine the impact of the source of earnings data on inequality measurement. Overall, our results provide informative and relevant information for understanding the extent to which self-reported earnings data and reported earnings from administrative records influences the estimation of inequality and our interpretation of factors that drive earnings inequality by race in the United States, specifically the black-white earnings gap.

Are Blacks Lazy?

William A. Darity Jr.
,
Duke University
Darrick Hamilton
,
New School
Samuel L. Myers Jr.
,
University of Minnesota-Twin Cities
Gregory N. Price
,
Morehouse College
Man Xu
,
University of Minnesota-Twin Cities

Abstract

This paper attempts to replicate the controversial findings of Hamermesh, et al. (2016) who use the American Time Use Survey to show that there are racial differences in work effort that could bias measurement of wage inequality. Our paper examines the effects of non-response rates on estimates of hours worked and the share of the work day spend not working, a proxy for laziness. By using the American Time Use Survey 2003-15, this paper seeks to identify the rate at which workers spend time at work performing non-work related activities. We identify population level biases in the survey, discuss ways that these biases may be wrongly attributed to race or ethnicity, and connect ways these attributions may prevent workers from earning wages based on their effort. The paper addresses core questions posed in measuring racial disparities in work effort.

Earnings Inequality and the Role of the Firm

John M. Abowd
,
U.S. Census Bureau and Cornell University
Kevin L. McKinney
,
U.S. Census Bureau

Abstract

Using U.S. longitudinal linked employer-employee data, we analyze the role of the employer in explaining earnings inequality. From 2004 to 2013, year-to-year movements between the bottom, middle and top of the earnings distribution average 20.5 million workers annually. For stayers and movers, we decompose earnings in the previous and current year into a firm and non-firm component. Using the estimated components, we show there are large gains from working at a top-paying firm for all skill types. Working for a high-paying firm produces benefits today, through higher earnings, that persist through an increase in the probability of upward mobility. High-paying firms facilitate moving workers to the top of the distribution and keeping them there.
Discussant(s)
William Spriggs
,
Howard University
Charles M. Hokayem
,
Centre College
Bradley L. Hardy
,
American University
JEL Classifications
  • J7 - Labor Discrimination