Econometric Analysis of Cross Section and Panel Data

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The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated.

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.

 

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Contents

INTRODUCTION AND BACKGROUND
1
Basic Asymptotic Theory
37
LINEAR MODELS
51
Coefficient Models
73
Instrumental Variables Estimation of SingleEquation Linear Models
89
Additional SingleEquation Topics
123
Estimating Systems of Equations by Ordinary Least Squares
161
System Estimation by Instrumental Variables
207
NONLINEAR MODELS AND RELATED TOPICS
559
Variable Model
599
Multinomial and Ordered Response Models
643
Corner Solution Responses
667
Variable Model
685
Count Fractional and Other Nonnegative Responses
723
Censored Data Sample Selection and Attrition
777
Stratified Sampling and Cluster Sampling
853

Simultaneous Equations Models
239
Basic Linear Unobserved Effects Panel Data Models
281
More Topics in Linear Unobserved Effects Models
345
GENERAL APPROACHES TO NONLINEAR ESTIMATION
395
Maximum Likelihood Methods
469
Generalized Method of Moments and Minimum Distance Estimation
525
Restrictions
542
Estimating Average Treatment Effects
903
Discontinuity
959
Duration Analysis
983
References
1025
Index
1045
Copyright

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About the author (2010)

Jeffrey M. Wooldridge is University Distinguished Professor of Economics at Michigan State University and a Fellow of the Econometric Society.

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