Using R for introductory econometrics / Florian Heiss

Bibliography: p. [335]-336. Index.

I. Regression analysis with cross-sectional data. The simple regression model — Multiple regression analysis: estimation — Multiple regression analysis: inference — Multiple regression analysis: OLS asymptotics — Multiple regression analysis: further issues — Multiple regression analysis with qualitative regressors — Heteroscedasticity — More on specification and data issues — II. Regression analysis with time series data. Basic regression analysis with time series data — Further issues in using OLS with time series data — Serial correlation and heteroscedasticity in time series regressions — III. Advanced topics. Pooling cross-sections across time: simple panel data methods — Advanced panel data methods — Instrumental variables estimation and two stage least squares — Simultaneous equations models — Limited dependent variable models and sample selection corrections — Advanced time series topics — Carrying out an empirical project — IV. Appendices. R scripts.

"This book does not attempt to provide a self-contained discussion of econometric models and methods. It also does not give an independent general introduction to R. Instead, it builds on the excellent and popular textbook 'Introductory Econometrics' by Wooldridge (2016). It is compatible in terms of topics, organization, terminology, and notation, and is designed for a seamless transition from theory to practice."--