2017
DOI: 10.1515/bejm-2016-0060
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The marriage unemployment gap

Abstract: In this paper we document that married individuals face a lower unemployment rate than their single counterparts. We refer to this phenomenon as the marriage unemployment gap. Despite dramatic demographic changes in the labor market over the last decades, this gap has been remarkably stable both for men and women. Using a flow-decomposition exercise, we assess which transition probabilities (across labor force states) are behind this phenomenon: For men, the main driver is the higher job losing probabilities f… Show more

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Cited by 4 publications
(2 citation statements)
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“…While the standard framework used to study the effects of UI focuses on single‐agent models, this paper provides a more complete picture because of three reasons. First, as pointed out in Choi and Valladares‐Esteban (), married and single individuals display striking differences in labor market dynamics and performance, even after controlling for observable differences . Married individuals have lower unemployment rates than their single counterparts, suggesting that the two groups may have different needs with respect to UI.…”
Section: Introductionmentioning
confidence: 89%
See 1 more Smart Citation
“…While the standard framework used to study the effects of UI focuses on single‐agent models, this paper provides a more complete picture because of three reasons. First, as pointed out in Choi and Valladares‐Esteban (), married and single individuals display striking differences in labor market dynamics and performance, even after controlling for observable differences . Married individuals have lower unemployment rates than their single counterparts, suggesting that the two groups may have different needs with respect to UI.…”
Section: Introductionmentioning
confidence: 89%
“…We follow Choi and Valladares‐Esteban () to compute labor market transitions by using monthly data from the Current Population Survey (CPS) controlling for observable characteristics and adjusting for other known empirical issues: we correct the data for classification errors and time aggregation bias. Transition probabilities are cleaned from the effect of race, age, census division, education, and the number of children in the household.…”
Section: Mapping the Model To Us Datamentioning
confidence: 99%