State Dependence, Serial Correlation and Heterogeneity in Intertemporal Participation Behavior: Monte Carlo Evidence and Empirical Results for Married Women

The labor force participation behavior of married women, particularly their responses to husbands' labor market outcomes and the effects of fertility variables, is modeled using longitudinal data to control for a rich dynamic structure. Simulation methods provide a feasible approach to overcome the computational difficulties inherent in classical maximum likelihood estimation of models with non-trivial error structures. The models are estimated using the method of maximum simulated likelihood (MSL) estimation. The empirical results imply that women's participation outcomes are characterised by significant structural state dependence, unobserved heterogeneity, and serially correlated transitory latent component of error. The results show that the effect of husbands' permanent earnings on the participation decision is significantly stronger than that of current earnings; however, the implied income elasticities of participation are small, on the order of -0.10. The results also provide strong evidence that fertility variables are not exogenous to women's participation decisions. Although MSL estimation is biased for a finite number of simulations, I provide Monte Carlo evidence that suggests the simulation bias in the estimators is generally not large relative to the sampling errors, except when there is positive serial correlation and either significant heterogeneity or state dependence, or when the form of the unobserved heterogeneity is misspecified. In these cases, the estimated serial correlation and state dependence effects have substantial negative and positive bias, respectively.