Ethnic Differentials on the Labor Market in the Presence of Asymmetric Spatial Sorting: Set Identification and Estimation

No 2014-09, Working Papers from Center for Research in Economics and Statistics

Abstract: This paper aims to isolate the ethnic gap on the labor market that can be attributed to ethnicity and not to differences in individual characteristics or residential location. Controlling for residential location is important as ethnic minorities often live in distressed neighborhoods. It is also challenging because spatial sorting is likely to differ across ethnicities because of labor- or housing-market discrimination. This paper shows that controlling for neighborhoods and observed individual characteristics fails to pro-vide a consistent estimate for the component of the gap accountable to ethnicity only. However, under some assumptions, the quantity of interest is set identified even when heterogeneous sorting patterns across ethnicities are allowed for and the set estimate can still be informative. A two-step estimation method is presented and applied to explain the ethnic employment differential in France, between French individuals of North African ancestry and those with non-immigrant parents. Most of the gap is not due to differences in residential location or individual characteristics, but rather to ethnicity itself

Keywords: ethnic employment gaps; spatial sorting; set identification; discrimination; spatial mismatch (search for similar items in EconPapers)
JEL-codes: C23 J71 R23 (search for similar items in EconPapers)
Pages: 35
Date: 2014-04
New Economics Papers: this item is included in nep-geo and nep-lab
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Related works:
Journal Article: Ethnic differentials on the labor market in the presence of asymmetric spatial sorting: Set identification and estimation (2014)
Working Paper: Ethnic differentials on the labor market in the presence of asymmetric spatial sorting: Set identification and estimation (2014)
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