This paper studies semiparametric identification in linear index discrete response panel data models with fixed effects. Departing from the classic binary response static panel data model, this paper examines identification in the binary response dynamic panel data model and the ordered response...

We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a covariate sequentially exogenous conditional on lagged outcomes and covariates). The choice model is indexed by a scalar parameter 0, whereas the distribution of unit-specific...

This paper studies the identifying power of conditional quantile restrictions in short panels with fixed effects. In contrast to classical fixed effects models with conditional mean restrictions, conditional quantile restrictions are not preserved by taking differences in the regression equation...

Firms often have imperfect information about demand for their products. We develop an integrated econometric and theoretical framework to model firm demand assessment and subsequent pricing decisions with limited information. We introduce a panel data discrete choice model whose realistic...

This paper analyzes the identification question in censored panel data models, where the censoring can depend on both observable and unobservable variables in arbitrary ways. Under some general conditions, we derive the tightest sets on the parameter of interest. These sets (which can be...

We present an econometric framework for robust pricing based on credible assumptions about consumer behavior. First, we introduce a panel data discrete choice model whose realistic assumptions about consumer behavior result in partial identification of preferences. Next we address the resulting...