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Explaining cross-racial differences in teenage labor force participation: Results from a two-sided matching model

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Date
2010-05-01
Authors
Ahn, T
Arcidiacono, P
Murphy, A
Swinton, O
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Abstract
White teenagers are substantially more likely to search for employment than black teenagers. This differential occurs despite the fact that, conditional on race, individuals from disadvantaged backgrounds are more likely to search. While the racial wage gap is small, the unemployment rate for black teenagers is substantially higher than that of white teenagers. We develop a two-sided search model where firms are partially able to search on demographics. Model estimates reveal that firms are more able to target their search on race than on age. Employment and wage outcome differences explain half of the racial gap in labor force participation rates. © 2009 Elsevier B.V. All rights reserved.
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Journal article
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https://hdl.handle.net/10161/6940
Published Version (Please cite this version)
10.1016/j.jeconom.2009.09.017
Publication Info
Ahn, T; Arcidiacono, P; Murphy, A; & Swinton, O (2010). Explaining cross-racial differences in teenage labor force participation: Results from a two-sided matching model. Journal of Econometrics, 156(1). pp. 201-211. 10.1016/j.jeconom.2009.09.017. Retrieved from https://hdl.handle.net/10161/6940.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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Scholars@Duke

Arcidiacono

Peter S. Arcidiacono

William Henry Glasson Distinguished Professor of Economics
Professor Arcidiacono specializes in research involving applied microeconomics, applied economics, and labor economics. His research primarily focuses on education and discrimination. His work focuses specifically on the exploration of a variety of subjects, such as structural estimation, affirmative action, minimum wages, teen sex, discrimination, higher education, and dynamic discrete choice models, among others. He recently received funding from a National Science Foundation Grant for his pro
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