While there is evidence that return migration promotes entrepreneurship and self-employment of those who migrated, previous studies have not focused on whether migration provides the same benefits to individuals who did not migrate. Using a unique dataset that provides information on both...

This paper proposes a parametric approach to estimating a dynamic binary response panel data model that allows for endogenous contemporaneous regressors. Such a model is of particular value for settings in which one wants to estimate the effects of an endogenous treatment on a binary outcome. In...

Mundlak (1978) proposed the addition of time averages to the usual panel equation in order to remove the fixed effects bias. We extend this Mundlak equation further by replacing the time-varying explanatory variables by the corresponding deviations from the averages over time, while keeping the...

Probit and logit models typically require a normalization on the error variance for model identification. This paper shows that in the context of sample mean probability decompositions, error variance normalizations preclude estimation of the effects of group differences in the latent variable...

Union density in Germany has declined remarkably during the last two decades. We estimate socio-economic and workplace-related determinants of union membership in East and West Germany using data from the German Socio-Economic Panel by means of Chamberlain-Mundlack correlated random effects...

This paper presents a convenient shortcut method for implementing the Heckman estimator of the dynamic random effects probit model using standard software. It then compares the three estimators proposed by Heckman, Orme and Wooldridge based on three alternative approximations, first in an...

If certain start-up characteristics will indicate a business success, knowing such characteristics could generate more successful start-ups and more efficient start-up counseling. Our study will contribute to this by quantifying individual success determinants of freelance start-ups. The data...

A common approach to dealing with missing data is to estimate the model on the common subset of data, by necessity throwing away potentially useful data. We derive a new probit type estimator for models with missing covariate data where the dependent variable is binary. For the benchmark case of...

This paper develops a simulation estimation algorithm that is particularly useful for estimating dynamic panel data models with unobserved endogenous state variables. The new approach can easily deal with the commonly encountered and widely discussed quot;initial conditions problem,quot; as well...