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 order to demonstrate the usefulness of the approach, we
use it to examine the impact of rural-urban migration on the likelihood that households in rural
China fall below the poverty line. In this application, it is shown that migration is important for
reducing the likelihood that poor households remain in poverty and that non-poor households
fall into poverty. Furthermore, it is demonstrated that failure to control for unobserved
heterogeneity would lead the researcher to underestimate the impact of migrant labor
markets on reducing the probability of falling into poverty.