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A bivariate probit approach to the determination of employment: a study of teen employment differentials in Los Angeles County

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  • Madhu Mohanty

Abstract

Following a bivariate probit approach and using the 1990 Public Use Microdata Samples (PUMS) for Los Angeles County, this study shows that the employment of teenage workers depends on both the worker's participation decision as well as the employer's hiring decision. Omission of the role of participation decision from the estimation of employment probability yields misleading evidence of hiring discrimination against Blacks. This evidence, however, disappears when the participation and hiring equations are estimated jointly in a bivariate framework. The study finds no evidence of discrimination against females and Latinos. In addition, the study shows that family, household and neighbourhood characteristics play significant roles in the determination of teen employment.

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  • Madhu Mohanty, 2002. "A bivariate probit approach to the determination of employment: a study of teen employment differentials in Los Angeles County," Applied Economics, Taylor & Francis Journals, vol. 34(2), pages 143-156.
    • Handle: RePEc:taf:applec:v:34:y:2002:i:2:p:143-156
    DOI: 10.1080/00036840010028585
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    References listed on IDEAS

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    1. Madhu Mohanty, 1998. "Do US employers discriminate against females when hiring their employees?," Applied Economics, Taylor & Francis Journals, vol. 30(11), pages 1471-1482.
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    8. Tom Larson & Madhu Mohanty, 1999. "Minority youth employment, residential location, and neighborhood jobs: A study of Los Angeles County," The Review of Black Political Economy, Springer;National Economic Association, vol. 27(2), pages 33-62, December.
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    Cited by:

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    3. Guifu Chen & Shigeyuki Hamori, 2014. "Bivariate Probit Analysis of the Differences Between Male and Female Formal Employment in Urban China," SpringerBriefs in Economics, in: Rural Labor Migration, Discrimination, and the New Dual Labor Market in China, edition 127, chapter 0, pages 65-76, Springer.
    4. Maksym Obrizan, 2011. "A Bayesian Model of Sample Selection with a Discrete Outcome Variable: Detecting Depression in Older Adults," Discussion Papers 41, Kyiv School of Economics.
    5. Schwiebert, Jörg, 2012. "Semiparametric Estimation of a Binary Choice Model with Sample Selection," Hannover Economic Papers (HEP) dp-505, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    6. Maksym, Obrizan, 2010. "A Bayesian Model of Sample Selection with a Discrete Outcome Variable," MPRA Paper 28577, University Library of Munich, Germany.
    7. Adolfo Sachsida & Mario J. C. Mendonca & Paulo R. A. Loureiro & Antonio Nascimento Junior & Roberto Ellery & Tito Belchior Silva Moreira, 2018. "Crime and Discrimination in the Labor Market: An Empirical Approach," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(3), pages 196-204, March.
    8. Melanie Jones & Paul Latreille, 2011. "Disability and self-employment: evidence for the UK," Applied Economics, Taylor & Francis Journals, vol. 43(27), pages 4161-4178.
    9. Morais, Flávio & Serrasqueiro, Zélia & Ramalho, Joaquim J.S., 2020. "The zero-leverage phenomenon: A bivariate probit with partial observability approach," Research in International Business and Finance, Elsevier, vol. 53(C).

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