Over recent years there have been a sequence of important advances in the set of microeconometric techniques available for empirical microeconomics. The aim of the papers contained in this symposium is to bring a number of these techniques within access of applied researchers. Each paper is written with application in mind.

Bootstrap techniques are now becoming commonplace in many applications. The application in Joel Horowitz's paper is to weighted minimum distance estimators of the type used in the Abowd and Card study of earnings and hours. Horowitz provides an illuminating guide to how bootstrap methods can be used to reduce the bias of such estimators and reduce the errors in the coverage probabilities of confidence intervals. Kenneth Chay and Bo Honore look at estimation with censored data and their application is to the earrungs equation. They investigate the value of using weaker assumptions on the error process in estimation.

In my paper with Alan Duncan we provide a practical guide to the use of kernel and local regression techniques. An important focus of our discussion is on the use of kernel regression for the assessment of parametric models and this is applied to the estimation of the Engel curve relationship. Quantile regression is also now part of an empirical microeconomist's tool kit and Moshe Buchinsky gives a detailed guide to implementation with an application to the distribution of earnings. Estimating techniques for selectivity models are discussed by Frank Vella who provides a useful comparison of alternative techniques for cross-section and panel data estimation.

© 2002 by the Board of Regents of the University of Wisconsin System

US ISSN 0022-166X

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