"I highly recommend this book for graduate classes in econometrics. We have used it at MIT and the students find it extremely helpful. Wooldridge covers topics in a highly readable and insightful way." Jerry Hausman , John and Jennie S. MacDonald Professor of Economics, MIT "In this leading econometrics textbook, Wooldridge offers a very good explanation of the basics of the field -- making it a great resource for econometrics students -- and a contemporary treatment of many important topics, making it a wonderful reference for researchers as well. The new edition provides clear explanations of many recent developments." Whitney Newey , Jane Berkowitz Carlton and Dennis William Carlton Professor of Microeconomics, MIT "This second edition provides a comprehensive, accessible, and updated treatment of cross section and panel data methods. The book is full of useful insights, applications, and worked problems. It will serve as an invaluable textbook and reference for graduate students and researchers alike." Richard Blundell , Institute for Fiscal Studies, University College London
Descripción del producto
The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis.Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.