Although the Stata software package is suitable for a wide range of empirical research, the author focuses mainly on economic and financial applications. The material as well as the examples are adapted from course notes for undergraduate and graduate-level econometrics.
After a short introductory chapter which mainly informs about Stata, how to install the necessary software and the support materials, chapters two to four give an introduction into the data handling features in Stata, including among others transformation of data, organizing and handling economic data, distinguishing between time series data, cross sectional data and panel data. More technical details about data handling can be found in Appendix A. Appendix B deals with the basics of Stata programming.
Chapters 4 to 10 present the econometric tools in Stata, commonly used in econometrics as well as in financial econometrics. After an introduction into the basic regression techniques including hypotheses testing, the author discusses the specification of functional forms and misspecification and/or specification tests. Chapter six is devoted to regression analysis with non-i.i.d. errors which translates into the problems of heteroskedasticity and serial correlations as well. Regression with indicator variables constitute chapter seven, and chapter eight is concerned with instrumental variables estimators with special emphasis on GMM estimation. Testing overidentifying restrictions in GMM, testing for endogeneity in IV estimation, testing for heteroskedasticity in the IV context, and testing the relevance of instruments are issues also contained in chapter eight. Panel-data models with the distinction between fixed and random effects are introduced in chapter nine. More advanced techniques in the context of panel-data models include IV models for panel-data and dynamic panel-data models. The final chapter ten deals with models of discrete and limited dependent variables. The models discussed here include ordered logit and probit models, truncated regression and tobit models, bivariate probit models and as an introduction the general latent variables approach.
In all chapters and for all topics discussed in the book, the author gives the respective Stata commands, interpretes the estimation and testing results of the examples, and presents the text book formulas for some uncommon test statistics. The book may be used for beginners in applied econometrics and financial econometrics using Stata. It is a quick and easy introduction to the programming features and language of Stata, and so it is not necessary to go through the thick handbooks delivered by the Stata Corporation.