This paper considers fixed effects (FE) estimation for linear panel data models under possible model misspecification when both the number of individuals, n, and the number of time periods, T, are large. We first clarify the probability limit of the FE estimator and argue that this probability...

This paper uses a consumption-based dynamic quantile preference model to estimate the elasticity of intertemporal substitution (EIS) across different levels of risk attitude. In the quantile model, the risk attitude is captured by the quantile and is, therefore, separable from the EIS. This is...

We propose a new inverse probability weighting (IPW) estimator for moment condition models with missing data. Our estimator is easy to implement and compares favorably with existing IPW estimators, including augmented inverse probability weighting (AIPW) estimators, in terms of efficiency,...