Synopses & Reviews
This book introduces econometrics at the 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 length of the first edition One chapter on liner equation systems has been added and several new sections on panel data are new. Also 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 weighted M-estimator, empirical likelihood estimator, stochastic-process convergence and applications, and bootstrap. The author, Myoung-jae Lee, is currently a Professor of Economics at Korea University, and has written Panel Data Econometrics: Methods-of-Moments and Limited Dependent Variables (2002, Academic Press) and Micro-Econometrics for Policy, Program, and Treatment Effects (2005, Oxford University Press), which complement the current book in covering micro-econometrics as a whole. The author published extensively across the broad spectrum of micro-econometrics, writing more than 40 academic papers in international journals including top econometrics and statistics journals.
Review
From the reviews of the second edition: "This is a book on microeconometric methods. ... book is particularly useful both for advanced graduate students and for researchers, whether they are theoretically or empirically oriented. ... an excellent basis for an advanced course on semi- and non-parametric econometrics, or simply as a valuable reference book. ... I have found this book to be extremely useful for my own work and I believe that many other readers, either students or researchers, will share that positive experience." (Myoung-jae Lee, The Econometrics Journal, May, 2010) "The book is voluminous at 759 pages. The author discusses various methods of testing and estimation in different models with illustrative empirical examples. The author hopes that theoretically oriented readers will find useful an overview on micro-econometrics and applied researchers will find helpful information on how to apply micro-econometric techniques. This reviewer agrees that the author has succeeded mostly in his aim. ... book is a valuable addition to the literature on micro-econometrics." (B. L. S. Prakasa Rao, Mathematical Reviews, Issue 2011 c)
Synopsis
The classical econometric approach to modelling has been to specify a model up to a finite-dimensional parameter vector, and estimation and testing techniques have been widely used on these finite-dimensional parameter spaces. In the last fifteen years or so however, new methods have been developed to allow more flexible models which utilise infinite-dimensional parameters. Simultaneously, methods of moments estimation have also become more widely used and applied. In this book, the author provides a survey of these modern techniques and how they are applied to limited dependent variable (LDV) models. As well as covering many classical approaches, the topics covered include: instrumental variable estimation, the generalized method of moments, extremum estimators, methods of simulated moments, minimum distance estimation, nonparametric density and regression function estimation, and semiparametric methods for LDV. As a result, many graduate students and research workers will appreciate this up-to-date account. An appendix describes the use of the software package GAUSS to implement these methods in conjunction with some real data sets.
Synopsis
WhenIwrotethebookMethodsofMomentsandSemiparametricEco- metrics for Limited Dependent Variable Models published from Springer in 1996, my motivation was clear: there was no book available to convey the latest messages in micro-econometrics. The messages were that most eco- metric estimators can be viewed as method-of-moment estimators and that inferences for models with limited dependent variables (LDV) can be done without going fully parametric. Time has passed and there are now several books available for the same purpose. These days, methods of moments are the mainstay in econometrics, not just in micro-, but also in macro-econometrics. Many papers have been published for semiparametric methods and LDV models. I, myself, learned much over the years since 1996, so much so that my own view on what should be taught, and how, has changed much. Particularly, my exposure to the "sample selection" and "treatment e?ect" literature has changed the way I look at econometrics now. When I set out to write the second edition of the 1996 book, these changes prompted me to re-title, reorganize, and re-focus the book.
Synopsis
In this book the author surveys new techniques in econometrics which may be used to analyse semiparametric models. As well as covering topics such as instrumental variable estimation, nonparametric density and regression function estimation and semiparametric limited dependent variable models, the book provides details of how these methods may be implemented using software.
Synopsis
Revised and updated, this volume introduces econometrics at the graduate level with a specialized focus on micro-econometrics. New topics include LDV's with endogenous regressors, competing risks, hazard function estimates, and empirical examples.
Synopsis
Up-to-date coverage of most micro-econometric topics; first half parametric, second half semi- (non-) parametric Many empirical examples and tips in applying econometric theories to data Essential ideas and steps shown for most estimators and tests; well-suited for both applied and theoretical readers
Table of Contents
Methods of moments for single linear equation models.- Methods of moments for multiple linear equation systems.- M-Estimator and Maximum Likelihood Estimator (MLE).- Nonlinear models and estimators.- Parametric methods for single equation LDV models.- Parametric methods for multiple equation LDV Models.- Kernel nonparametric estimation.- Bandwidth-free semiparametric methods.- Bandwidth-dependent semiparametric methods.