Micro-Econometrics: Methods of Moments and Limited Dependent Variables / Edition 2

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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, shastic-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.

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Editorial Reviews

From the Publisher

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)

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Product Details

  • ISBN-13: 9780387953762
  • Publisher: Springer New York
  • Publication date: 10/14/2009
  • Edition description: 2nd ed. 2010
  • Edition number: 2
  • Pages: 770
  • Product dimensions: 9.21 (w) x 6.14 (h) x 1.63 (d)

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.

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