Thursday 30 April 2009

Microeconometrics Reviews

Microeconometrics



Author: A. Colin Cameron
Edition:
Publisher: Cambridge University Press
Binding: Hardcover
ISBN: 0521848059
Price:
You Save: 22%




Microeconometrics: Methods and Applications



This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data.Microeconometrics review. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey dataRead full reviews of Micro-Econometrics for Policy, Program, and Treatment Effects (Advanced Texts in Econometrics).

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Micro-Econometrics for Policy, Program, and Treatment Effects (Advanced Texts in Econometrics)
About the Author Myoung-jae Lee is Associate Professor in the School of Economics and Social Sciences at Singapore Management University. He has held positions at Pennsylvania State University, Tilburg University in The Netherlands, London School of Economics, Tsukuba University in Japan and Sungkyunkwan University in Seoul.

Micro-Econometrics for Policy, Program, and Treatment Effects (Advanced Texts in Econometrics)
Micro-Econometrics for Policy, Program, and Treatment Effects (Advanced Texts in Econometrics) -

Microeconometrics Using Stata
An outstanding introduction to microeconometrics and how to do microeconometric research using Stata, this book covers topics often left out of microeconometrics textbooks and omitted from basic introductions to Stata. Cameron and Trivedi provide the most complete and up-to-date survey of microeconometric methods available in Stata. They begin by introducing simulation methods and then use them to illustrate features of the estimators and tests described in the rest of the book. They address eac

Micro-Econometrics
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.
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. S

Microeconometrics Using Stata
This outstanding introduction to microeconometrics research using Stata offers the most complete and up-to-date survey of methods available. The authors address each topic with an in-depth example and demonstrate how to use Stata's programming features to implement methods for which the application does not have a specific command.



Microeconometrics Reviews


The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on seven large and exceptionally rich data sets.

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