In this paper we consider ML estimation for a broad class of parameter-driven models for discrete dependent variables with spatial correlation. Under this class of models, which includes spatial discrete choice models, spatial Tobit models and spatial count data models, the dependent variable is...

The paper develops and estimates a dynamic structural model that allows for the interrelations between girls' schooling and mothers' labor market participation decision, in a rural area of Pakistan where drop-out rates are considerably high. The model incorporates home production, which is...

We provide a general framework for investigating partial identification of structural dynamic discrete choice models and their counterfactuals, along with uniformly valid inference procedures. In doing so, we derive sharp bounds for the model parameters, counterfactual behavior, and...