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...

This paper surveys three topics: vector autoregressive (VAR) models with integrated regressors, cointegration, and structural VAR modeling. The paper begins by developing methods to study potential "unit root" problems in multivariate models, and then presents a simple set of rules designed to...