The DOI matches its Crossref record.
State Dependence, Serial Correlation and Heterogeneity in Intertemporal Labor Force Participation of Married Women
Open accessAbstract
A dynamic search framework is developed to analyze the intertemporal labor force participation behavior of married women, using longitudinal data to allow for a rich dynamic structure. The sensitivity to alternative distributional assumptions is evaluated using linear probability and probit models. The dynamic probit models are estimated using maximum simulated likelihood (MSL) estimation, to overcome the computational difficulties inherent in maximum likelihood estimation of models with nontrivial error structures. The results find that participation decisions are characterized by significant state dependence, unobserved heterogeneity, and negative serial correlation in the error component. The hypothesis that fertility decisions are exogenous to women's participation decisions is rejected when dynamics are ignored; however, there is no evidence against this hypothesis in dynamic model specifications. Women's participation response is stronger to permanent than current nonlabor income, reflecting unobserved taste factors.
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Citations
Cited by
Adda, J., Dustmann, C., & Stevens, K. (2017) · Journal of Political Economy · doi:10.1086/690952 · Cited by 467
Female Labour Force Participation: Past Trends and Main Determinants in OECD Countries
(2003) · OECD Economics Department Working Papers · doi:10.1787/082872464507 · Cited by 240
Dynamics of health and labor market risks
Haan, P., & Myck, M. (2009) · Journal of Health Economics · doi:10.1016/j.jhealeco.2009.09.001 · Cited by 96
Metadata
- Authors
- Hyslop, D. R.
- Venue
- Econometrica
- Publisher
- The Econometric Society
- Published
- 1999-11
- Volume
- 67
- Issue
- 6
- Pages
- 1255-1294
- ISSN
- 0012-9682 (ISSN-L)
- 1468-0262
- OpenAlex
- W2064325874
- Cited by
- 449
- References
- 0
- FWCI
- 13.48
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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