The section on cross-sectional techniques is thorough, with up-to-date treatments of instrumental-variables methods for linear models and of quantile-regression methods. The next section of the book covers estimators for the parameters of linear panel-data models. The authors' choice of topics is unique: after addressing the standard random-effects and fixed-effects methods, the authors also describe mixed linear models-a method used in many areas outside of econometrics. Cameron and Trivedi not only address methods for nonlinear regression models but also show how to code new nonlinear estimators in Stata.
In addition to detailing nonlinear methods, which are omitted from most econometrics textbooks, this section shows researchers and students how to easily implement new nonlinear estimators. The authors next describe inference using analytical and bootstrap approximations to the distribution of test statistics. This section highlights Stata's power to easily obtain bootstrap approximations, and it also introduces the basic elements of statistical inference.
Cameron and Trivedi then include an extensive section about methods for different nonlinear models. They begin by detailing methods for binary dependent variables. This section is followed by sections about multinomial models, tobit and selection models, count-data models, and nonlinear panel-data models.
Two appendices about Stata programming complete the book. The unique combination of topics, intuitive introductions to methods, and detailed illustrations of Stata examples make Microeconometrics Using Stata an invaluable, hands-on addition to the library of anyone who uses microeconometric methods. Bouoiyour, J. What does bitcoin look like? International Journal of Economics and Finance 6: Journal of Real Estate Financial Economics — College Station: Stata Press Table Descriptive statistics of the sample are in Table Author : Christopher F.
Baum Publisher: ISBN: Category: Econometrics Page: View: Read Now » Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, An Introduction to Modern Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how the theories are applied to real data sets using Stata.
Presenting many of the econometric theories used in modern empirical research, this introduction illustrates how to apply these concepts using Stata. The book examines how quantitative methods can be applied in corporate finance and accounting research in order to predict companies getting into financial distress.
Presented in a clear and straightforward manner, it also suggests methods for linking corporate governance to financial performance, and discusses what the determinants of accounting disclosures are. Exploring these questions by way of numerous practical examples, this book is intended for researchers, practitioners and students who are not yet familiar with the variety of approaches available for data analysis and microeconometrics.
Log in using a Shibboleth account. Colin Cameron and Pravin K. Trivedi, is an outstanding introduction to microeconometrics and how to do microeconometric research using Stata. Aimed at students and researchers, this book covers topics 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. The revised edition has been updated to reflect the new features available in Stata 11 that are germane to microeconomists.
Instead of using mfx and the user-written margeff commands, the revised edition uses the new margins command, emphasizing both marginal effects at the means and average marginal effects. Factor variables, which allow you to specify indicator variables and interaction effects, replace the xi command.
The new gmm command for generalized method of moments and nonlinear instrumental-variables estimation is presented, along with several examples.
Finally, the chapter on maximum likelihood estimation incorporates the enhancements made to ml in Stata Early in the book, Cameron and Trivedi introduce simulation methods and then use them to illustrate features of the estimators and tests described in the rest of the book.
While simulation methods are important tools for econometricians, they are not covered in standard textbooks.
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