Labor Market Segmentation and the Distribution of Income: New Evidence from Internal Census Bureau Data

Markus P.A. Schneider Ellis Scharfenaker
Authors registered in the RePEc Author Service: Ellis Scharfenaker and Markus P. A. Schneider ()

Working Paper Series, Department of Economics, University of Utah from University of Utah, Department of Economics

Abstract: In this paper, we present new findings that validate earlier literature on the apparent segmentation of the US earnings distribution. Previous contributions posited that the observed distribution of earnings combined two or three distinct signals and was thus appropriately modeled as a finite mixture of distributions. Furthermore, each component in the mixture appeared to have distinct distributional features hinting at qualitatively distinct generating mechanisms behind each component, providing strong evidence for some form of labor market segmentation. This paper presents new findings that support these earlier conclusions using internal CPS ASEC data spanning a much longer study period from 1974 to 2016. The restricted-access internal data is not subject to the same level of top-coding as the public-use data that earlier contributions to the literature were based on. The evolution of the mixture components provides new insights about changes in the earnings distribution including earnings inequality. In addition, we correlate component membership with worker type to provide a tacit link to various theoretical explanations for labor market segmentation, while solving the problem of assigning observations to labor market segments a priori.

Keywords: Inequality; Income Distribution; Mixture Model JEL Classification:C16; D32; J01 (search for similar items in EconPapers)
Pages: 39
Date: 2019
New Economics Papers: this item is included in nep-lab
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Citations: View citations in EconPapers (3)

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Working Paper: Labor Market Segmentation and the Distribution of Income: New Evidence from Internal Census Bureau Data (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:uta:papers:2019_08

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