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Is there only one way out of in-work poverty? Difference by gender and race in the US

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  • Struffolino, Emanuela
  • Van Winkle, Zachary

Abstract

The persistency of in-work povert y during the last de cades challenges the idea that employment is sufficient to escape poverty. Research has focused on the risk factors associated with in-work poverty, but scholars know little about individu als' experiences after exiting it. The Sequence Analysis Multistate Model proced ure is applied to three high-qual ity longitudinal data sources (NLSY79, NLSY97, and PSID) to establish a typo logy of employment pathways out of in-work poverty and estimate how gender and race are asso ciated with each pathway. We identify five distinct pathways characterized by varying de grees of labor market attachment, economic vulnerability, and volatility. White men are most likely exit in-work poverty into stable employment outside of poverty, while Black men and women likely remain vulnerable and at-risk of social exclusion as well as recurrent spells of in-work poverty. Gender and race differences persist even after controlling for la bor market related characteristics and family demographic behavior.

Suggested Citation

  • Struffolino, Emanuela & Van Winkle, Zachary, 2019. "Is there only one way out of in-work poverty? Difference by gender and race in the US," Discussion Papers, Research Group Demography and Inequality SP I 2019-601, WZB Berlin Social Science Center.
    • Handle: RePEc:zbw:wzbdin:spi2019601
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    File URL: https://www.econstor.eu/bitstream/10419/214684/1/i19-601.pdf
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    References listed on IDEAS

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    1. Jo M. Hale & Christian Dudel & Angelo Lorenti, 2020. "Cumulative disparities in the dynamics of working poverty for later-career U.S. workers (2002-2012)," MPIDR Working Papers WP-2020-028, Max Planck Institute for Demographic Research, Rostock, Germany.
    2. Hale, Jo Mhairi & Dudel, Christian & Lorenti, Angelo, 2020. "Cumulative disparities in the dynamics of working poverty for later-career U.S. workers (2002-2012)," SocArXiv xka5j, Center for Open Science.

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