We develop results for the use of LASSO and Post-LASSO methods to form first-stage predictions and estimate optimal instruments in linear instrumental variables (IV) models with many instruments, p, that apply even when p is much larger than the sample size, n. We rigorously develop asymptotic...

We study identification and estimation in a binary response model with random coefficients B allowed to be correlated with regressors X. Our objective is to identify the mean of the distribution of B and estimate a trimmed mean of this distribution. Like Imbens and Newey (2009), we use...

We analyze the impact of the quality of candidates running for a mayor position on turnout using a large data set on Italian municipal elections held from 1993 to 2011. We firstly estimate a municipal fixed effects model and show that an increase in the average quality of candidates competing at...

We use a Regression Discontinuity Design (RDD) to evaluate the impact of cost-sharing on the use of health services. In the Italian health system, individuals reaching age 65 and earning low incomes are given total exemption from cost-sharing for health services consumption. Since the...

We consider estimation and inference in panel data models with additive unobserved individual specific heterogeneity in a high dimensional setting. The setting allows the number of time varying regressors to be larger than the sample size. To make informative estimation and inference feasible,...