This paper is concerned with high-dimensional panel data models where the number of regressors can be much larger than the sample size. Under the assumption that the true parameter vector is sparse we establish finite sample upper bounds on the estimation error of the Lasso under two different...

This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular, we show that the Bridge estimator is oracle efficient. It can correctly distinguish between...

This paper considers estimation of a dynamic discrete choice model with second order state dependence in the presence of strictly exogenous time-varying explanatory variables. We propose new method for estimating such models, and a small Monte Carlo study suggests that the method erforms well in...

In this paper, we perform an extensive Monte Carlo study of the finite sample properties of different estimators for panel data sample selection models. The estimators investigated are various two-step estimators and maximum likelihood estimators with simultaneous equations for the...