The greatest problem for empirical analysis is how best to allow the context to affect the inferences. Econometric theory presupposes contextual "restrictions" that can be taken as given or assigned a probability distribution. These contextual inputs are rarely available. I illustrate this point...

This chapter develops three topics. (1) Identification of the distributions of treatment effects and the distributions of agent subjective evaluations of treatment effects. Methods for identifying ex ante and ex post distributions are presented and empirical examples are given. (2)...

This chapter uses the marginal treatment effect (MTE) to unify and organize the econometric literature on the evaluation of social programs. The marginal treatment effect is a choice-theoretic parameter that can be interpreted as a willingness to pay parameter for persons at a margin of...

This chapter relates the literature on the econometric evaluation of social programs to the literature in statistics on "causal inference". In it, we develop a general evaluation framework that addresses well-posed economic questions and analyzes agent choice rules and subjective evaluations of...

Economists have devoted increasing attention to the magnitude and consequences of measurement error in their data. Most discussions of measurement error are based on the "classical[equal, rising dots] assumption that errors in measuring a particular variable are uncorrelated with the true value...

When one wants to estimate a model without specifying the functions and distributions parametrically, or when one wants to analyze the identification of a model independently of any particular parametric specification, it is useful to perform a nonparametric analysis of identification. This...

This chapter explains the logic of structural econometric models and compares them to other types of econometric models. We provide a framework researchers can use to develop and evaluate structural econometric models. This framework pays particular attention to describing different sources of...

Economists who use survey or administrative data for inferences regarding a population may want to combine information obtained from two or more samples drawn from the population. This is the case if there is no single sample that contains all relevant variables. A special case occurs if...

Often researchers find parametric models restrictive and sensitive to deviations from the parametric specifications; semi-nonparametric models are more flexible and robust, but lead to other complications such as introducing infinite-dimensional parameter spaces that may not be compact and the...