An Introduction to Modern Econometrics Using Stata

Par : Christopher F. Baum
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  • Nombre de pages341
  • PrésentationBroché
  • FormatGrand Format
  • Poids0.705 kg
  • Dimensions18,5 cm × 23,5 cm × 2,0 cm
  • ISBN1-59718-013-0
  • EAN9781597180139
  • Date de parution01/01/2006
  • ÉditeurStata Press

Résumé

An Introduction to Modern Econometrics Using Stata surveys many of the econometric tools used in modem empirical research and how to use them in Stata. Baum presents the essential elements of working with economic and financial data, including cross-section, time-series, and panel-data structures ; merge, append, and reshape tools ; and data validation. He covers approaches such as linear regression, generalized least squares, regression with indicator variables, instrumental-variables methods, panel-data models, and models of limited dependent variables.
Baum illustrates these techniques with examples from the applied literature, using datasets that are downloadable from the book's web site. An appendix presents the basics of Stata do-file programming. The book develops the necessary analytical results needed to understand using estimators, hypothesis tests, and tests of model validity. Readers need no prior experience with Stata. The book should be particularly useful for those who have had an econometrics course and some experience with statistical packages but who need a clear guide to using state-of-the-art econometric techniques in Stata.
An Introduction to Modern Econometrics Using Stata surveys many of the econometric tools used in modem empirical research and how to use them in Stata. Baum presents the essential elements of working with economic and financial data, including cross-section, time-series, and panel-data structures ; merge, append, and reshape tools ; and data validation. He covers approaches such as linear regression, generalized least squares, regression with indicator variables, instrumental-variables methods, panel-data models, and models of limited dependent variables.
Baum illustrates these techniques with examples from the applied literature, using datasets that are downloadable from the book's web site. An appendix presents the basics of Stata do-file programming. The book develops the necessary analytical results needed to understand using estimators, hypothesis tests, and tests of model validity. Readers need no prior experience with Stata. The book should be particularly useful for those who have had an econometrics course and some experience with statistical packages but who need a clear guide to using state-of-the-art econometric techniques in Stata.