Econometric Analysis Of Cross Section And Panel Data

The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods substantially revised and updatedThe 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 andor 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