This paper is an expository review of recently developed techniques that are designed to evaluate macroeconomic policy using econometric models ; The exposition focuses on dynamic stochastic models with rational expectations and with discrete time. The method of undetermined coefficients is used...

This review of data problems in econometrics has been prepared for the Handbook of Econometrics (Vol. 3, Chap. 25, forthcoming). It starts with a review of the ambivalent relationship between data and econometricians, emphasizing the largely second-hand nature of economic data and the...

This paper uses the marginal treatment effect (MTE) to unify the nonparametric literature on treatment effects with the econometric literature on structural estimation using a nonparametric analog of a policy invariant parameter; to generate a variety of treatment effects from a common...

Econometric analyses of treatment response commonly use instrumental variable (IV) assumptions to identify treatment effects. Yet the credibility of IV assumptions is often a matter of considerable disagreement, with much debate about whether some covariate is or is not a "valid instrument" in...

A central problem in applied empirical work is to separate out the patterns in the data that are due to poor production of the data, such as e.g. non-response and measurement errors, from the patterns attributable to the economic phenomena studied. This paper interprets this inference problem as...

We explore alternative approaches to numerical solutions of large rational expectations models. We discuss and compare several current alternatives, focussing on the tradeoffs in accuracy, space, and speed. The models range from representative agent models with many goods and capital stocks, to...

This paper considers models for unobservables in duration models. It demonstrates how cross-section and time-series variation in regressors facilitates identification of single-spell, competing risks and multiple spell duration models. We also demonstrate the limited value of traditional...

We offer simple quasi-likelihood methods for estimating regression models with a fractional dependent variable and for performing asymptotically valid inference. Compared with log-odds type procedures, there is no difficulty in recovering the regression function for the fractional variable, and...