This chapter considers methods for evaluating the impact of social programs in the presence of nonrandom program placement or program selection. It first presents the evaluation problem as a missing data problem and then considers various solutions proposed in the statistics and econometrics...

This chapter discusses how applied researchers in corporate finance can address endogeneity concerns. We begin by reviewing the sources of endogeneity—omitted variables, simultaneity, and measurement error—and their implications for inference. We then discuss in detail a number of...

Most research questions in agricultural and applied economics are of a causal nature, i.e., how one or more variables (e.g., policies, prices, the weather) affect one or more other variables (e.g., the welfare of individuals or the society, the demanded or produced quantity, pollution). Only a...

In this article, we review quantile models with endogeneity. We focus on models that achieve indentification through the use of instrumental variables and discuss conditions under which partial and point identification are obtained. We discuss key conditions, which include monotonicity and...

We provide an overidentification test for a nonparametric treatment model where individuals are allowed to select into treatment based on unobserved gains. Our test can be used to test the validity of instruments in a framework with essential heterogeneity (Imbens and Angrist 1994). The...

This paper analyzes estimators based on the instrumental variable quantile regression (IVQR) model (Chernozhukov and Hansen, 2004, 2005, 2006) under the local quantile treatment effects (LQTE) framework (Abadie et al., 2002). I show that the quantile treatment effect (QTE) estimators in the IVQR...