Panel Data Econometrics

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"This is a useful reference work that brings together many recent developments in estimation with panel data. The emphasis on semiparametric and limited dependent variable methods provides a good complement to other recent books on the subject."
-Arthur Lewbel, Boston College

"Professor Lee has combined accessible technical discussions of modern panel data treatments with their empirical implementation in models containing limited dependent ...
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Overview

"This is a useful reference work that brings together many recent developments in estimation with panel data. The emphasis on semiparametric and limited dependent variable methods provides a good complement to other recent books on the subject."
-Arthur Lewbel, Boston College

"Professor Lee has combined accessible technical discussions of modern panel data treatments with their empirical implementation in models containing limited dependent variables. It arrives on the scene soon after our profession recognized the importance of such models by awarding of the 2000 Nobel Prize in Economics to D. McFadden and J. Heckman. A must for any serious graduate student who intends to carry out modern research in econometric theory and/or empirical research in the social sciences."
-Robin C. Sickles, Professor of Economics and Statistics, Rice University


This practical, accessible, detailed examination of recent developments in panel data econometrics highlights semiparametric approaches, providing distribution-free estimators for limited response models. It offers detailed accounts of delicate subjects, such as panel data sample selection models, and is well supplemented by examples and empirical exercises. For both empirical researchers who wish to apply panel data methods and the person who is serious about using semi-parametric methods in panel data analysis, Professor Lee's comprehensive examination of recent estimation methods, his practical clues and insights, and his discussions of computational feasibility separate his book from other econometrics texts.

KEY FEATURES
* Focuses on practical implementation and computational feasibility of estimationmethods
* Compares parametric and semiparametric approaches, highlighting advantages of new methods
* Provides distribution-free estimators for limited response models
* Includes innovative programs with accompanying data sets on disk
* Presents computational steps and recent methods in panel data analysis
* Describes main theoretical ideas behind the generalized method-of-moments (GMM) estimation

Audience: Practitioners such as econometricians, theoretic and empirical economists working in labor, public, urban, welfare, and environmental, as well as microeconomists in general; graduate students taking a one-semester econometrics or statistics course.

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Editorial Reviews

Booknews
A textbook for a one-quarter or one-semester graduate course for students who have taken one or two econometrics courses. It describes recent developments in panel data econometrics, emphasizing weak model assumptions. In recognition that available econometric packages are not flexible enough for recent methods, the computational steps as well as the main theoretical ideas are presented so students can analyze panel data on their own. The disk contains data sets and programs for the empirical examples in the text; it requires Windows. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780124406568
  • Publisher: Emerald Group Pub Ltd
  • Publication date: 4/1/2002
  • Edition description: BOOK&DISK
  • Pages: 195
  • Product dimensions: 6.10 (w) x 9.52 (h) x 0.66 (d)

Meet the Author

Department of Economics, Sungkyunkwan University, Seoul, South Korea
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Table of Contents

Preface
1 Introduction to Panel Data Issues
Extra Time Dimension 2
Temporal Moment Conditions 4
Time-Varying Parameters 6
The Unit-Specific Term and Its Removal by Differencing 8
Other Ways to Remove Unit-Specific Term 9
Dynamic Features and Restrictions on Parameters 11
Error Term Structure 13
2 Methods-of-Moments for Panel Linear Models
Review of Cross-Section IVE and GMM 18
Panel Linear Model 22
Moment Conditions and Panel IVE and GMM 25
IVE with Differenced Regressors 30
IVE with Differenced Errors 36
An Empirical Example on Production Function 43
3 Topics for Panel Linear Models
Wave-by-Wave Estimation and Time-Varying Parameters 50
Minimum Distance Estimation for Related-Effect 57
Dynamic Models 61
Spatial Dependence and Its Tests Using Panel Data 65
Efficiency Gain, Wald-Type Tests, Panel VAR, and Long-Run and Short-Run Effects 69
4 Panel Data Estimators for Binary Responses
Conditional Logit for T = 2 83
Conditional Logit for T [is greater than or equal to] 3 92
Panel Probit 99
Root-Nh Consistent Estimators 105
A Root-N Consistent Estimator 110
An Empirical Example for Panel Probit and Conditional Logit 114
5 Panel Data Estimators for Limited Responses
Review of Cross-Section Nonlinear IVE and GMM 120
Nearly Parametric Methods for Count Response 124
Moment-Based Estimators for Count Responses 132
Root-N Consistent Estimator for Censored Response 140
Conditional Logit for Multinomial Responses 143
An Empirical Example for Count Response 148
6 Panel Data and Sample Selection Models
Cross-Section Sample Selection Models and Two Estimators 155
Panel Sample Selection Models and Heckman's Two-Stage Analogs 163
Two First-Difference Estimators for Censored Selection 171
A Root-Nh Consistent Estimator for Binary Selection 175
LSE on Trimmed and Differenced Panel due to Attrition 178
Data and Gauss Programs 182
References 184
Index 193
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