This book introduces econometrics at graduate level, and then specializes
in micro-econometrics topics such as method of moments, limited and qualitative dependent
variables, sample-selection models, panel data, nonparametric estimators and specification
tests, and semi(non)-parametric methods.
The coverage is up-to-date and broad as well as in depth. Many empirical
examples are included along with a computer program appendix. Both graduate students and
researchers, applied or theoretical, in all disciplines using observational data will find
this book useful as a textbook as well as a research monograph for self-study and
reference.
The second edition is three times the length of the first edition. One chapter on liner
equation systems has been added and several sections on panel data are new. Sections for
the following topics have been added: LDV's with endogenous regressors, competing risks,
nonparametric survival and hazard function estimation, rank-based semiparametric methods,
differencing-based semiparametric methods, semiparametric estimators for duration models,
integrated moment specification tests, nonparametric control function approaches,
nonparametric additive models, various transformation of response variables, and
nonparametric specification and significance tests. The appendix now contains the proofs
for some important results in the main text and new sections for the following topics:
review of mathematical and statistical backgrounds, nested logit, U-statistics, GMM with
integrated squared moments, goodness-of-fit tests for distribution functions, joint test
for all quantiles, review on test, non-nested model test, stratified sampling and
weightedM-estimator, empirical likelihood estimator, stochastic-process convergence and
applications, and bootstrap.
Table of Contents
Chapter 1 Methods of Moments for Single Linear Equation Models
1 Least Squares Estimator (LSE) 1
2 Heteroskedasticity and Homoskedasticity 17
3 Testing Linear Hypotheses 25
4 Instrumental Variable Estimator (IVE) 31
5 Generalized Method-of-Moment Estimator (GMM) 42
6 Generalized Least Squares Estimator (GLS) 48
Chapter 2 Methods of Moments for Multiple Linear Equation Systems
1 System LSE, IVE, and GMM 53
2 Simultaneous Equations and Identification 66
3 Methods of Moments for Panel Data 75
Chapter 3 M-Estimator and Maximum Likelihood Estimator (MLE)
1 M-Estimator 91
2 Maximum Likelihood Estimator (MLE) 96
3 M-Estimator with Nuisance Parameters 102
4 Method-of-Moment Tests (MMT) 108
5 Tests Comparing Two Estimators 112
6 Three Tests for MLE 117
7 Numerical Optimization and One-Step Efficient Estimation
Chapter 4 Nonlinear Models and Estimators 133
1 Nonlinear Least Squares Estimator (NLS) 133
2 Quantile and Mode Regression 145
3 GMM for Nonlinear Models 156
4 Minimum Distance Estimation (MDE) 168
Chapter 5 Parametric Methods for Single Equation LDV Models
1 Binary Response 177
2 Ordered Discrete Response 189
3 Count Response 198
4 Censored Response and Related LDV Models 206
5 Parametric Estimators for Duration 216
Chapter 6 Parametric Methods for Multiple Equation LDV Models
1 Multinomial Choice Models 229
2 Methods of Simulated Moments (MSM) 244
3 Sample-Selection Models 252
4 LDV’s with Endogenous Regressors 269
5 Panel-Data Binary-Response Models 285
6 Competing Risks* 296
Chapter 7 Kernel Nonparametric Estimation 303
1 Kernel Density Estimator 303
2 Consistency and Bandwidth Choice 313
3 Asymptotic Distribution 322
4 Finding Modes* 329
5 Survival and Hazard Under Random Right-Censoring* 333
6 Kernel Nonparametric Regression 344
7 Topics in Kernel Nonparametric Regression 353
Chapter 8 Bandwidth-Free Semiparametric Methods 363
1 Quantile Regression for LDV models 363
2 Methods Based on Modality and Symmetry 383
3 Rank-Based Methods 397
4 Differencing-Based Estimators 415
5 Estimators for Duration Models 421
6 Integrated-Moment Specification Tests* 431
Chapter 9 Bandwidth-Dependent Semiparametric Methods 441
1 Two-Stage Estimator with Nonparametric First-Stage 441
2 Nonparametric TSE for Endogenous Regressors 449
3 Control-Function (CF) Approaches 456
4 Single Index Models 464
5 Semi-linear Models 479
6 Additive Models 488
7 Transformation of Response Variables 497
8 Nonparametric Specification and Significance Tests 510
Appendix I: Mathematical Backgrounds and Chapter Appendices 531
Appendix II: Supplementary Topics 615
Appendix III: Select GAUSS Programs 705
References 727
Index 759
800 pages, Hardcover
