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"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."--Back cover

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.

Cover 1 Contents 6 Preface 22 Acknowledgments 30 I Introduction and Background 32 1 Introduction 34 2 Conditional Expectations and Related Concepts in Econometrics 44 3 Basic Asymptotic Theory 68 II Linear Models 82 4 Single-Equation Linear Model and Ordinary Least Squares Estimation 84 5 Instrumental Variables Estimation of Single-Equation Linear Models 120 6 Additional Single-Equation Topics 154 7 Estimating Systems of Equations by Ordinary Least Squares and Generalized Least Squares 192 8 System Estimation by Instrumental Variables 238 9 Simultaneous Equations Models 270 10 Basic Linear Unobserved Effects Panel Data Models 312 11 More Topics in Linear Unobserved Effects Models 376 III General Approaches to Nonlinear Estimation 426 12 M-Estimation, Nonlinear Regression, and Quantile Regression 428 13 Maximum Likelihood Methods 500 14 Generalized Method of Moments and Minimum Distance Estimation 556 IV Nonlinear Models and Related Topics 590 15 Binary Response Models 592 16 Multinomial and Ordered Response Models 674 17 Corner Solution Responses 698 18 Count, Fractional, and Other Nonnegative Responses 754 19 Censored Data, Sample Selection, and Attrition 808 20 Stratified Sampling and Cluster Sampling 884 21 Estimating Average Treatment Effects 934 22 Duration Analysis 1014 References 1056 Index 1076