Quantile regression (QR) methods fit a linear model for conditional quantiles, just as ordinary least squares (OLS) regression estimates a linear model for conditional means. An attractive feature of the OLS estimator is that it gives a minimum mean square error approximation to the conditional...

This paper is about identification and estimation in a triangular nonparametric structural model with instrumental variables and non-additive errors. Identification and estimation is based on a control function consisting of the conditional distribution function of the endogenous variable given...

We are interested in estimating the average effect of a binary treatment on a scalar outcome. If assignment to the treatment is independent of the potential outcomes given pre-treatment variables, biases associated with simple treatment-control average comparisons can be removed by adjusting for...

Instrumental Variables (IV) methods identify internally valid causal effects for individuals whose treatment status is manipulable by the instrument at hand. Inference for other populations inevitably requires some sort of homogeneity assumption. I develop a simple theoretical framework that...