Introductory econometrics: a modern approach

Wooldridge uses a systematic approach motivated by the major problems facing applied researchers. This text provides important understanding for empirical work in many social sciences, as well as for carrying out research projects.

"My motivation for writing the first edition of 'Introductory Econometrics : A Modern Approach' was that I saw a fairly wide gap between how econometrics is taught to undergraduates and how empirical researchers think about and apply econometric methods. I became convinced that teaching introductory econometrics from the perspective of professional users of econometrics would actually simplify the presentation, in addition to making the subject much more interesting. The emphasis in this edition is still on applying econometrics to real-world problems. Each econometric method is motivated by a particular issue facing researchers analyzing nonexperimental data. The focus in the main text is on understanding and interpreting the assumptions in light of actual empirical applications : the mathematics required is no more than college algebra and basic probability and statistics."--adapted from Preface, page xii.

Preface -- About the author -- Chapter 1. The nature of econometrics and economic date -- Part 1. Regression Analysis with Cross-Sectional Data. Chapter 2. The simple regression model -- Chapter 3. Multiple regression analysis : Estimation -- Chapter 4. Multiple regression analysis : Inference -- Chapter 5. Multiple regression analysis : OLS asymptotics -- Chapter 6. Multiple regression analysis : Further issues -- Chapter 7. Multiple regression analysis with qualitative information -- Chapter 8. Heteroskedasticity -- Chapter 9. More on specification and data issues -- Part 2. Regression Analysis with Time Series Data. Chapter 10. Basic regression analysis with time series data -- Chapter 11. Further issues in using OLS with time series data -- Chapter 12. Serial correlation and heteroskedasticity in time series regressions -- Part 3. Advanced Topics. Chapter 13. Pooling cross sections across time : Simple panel data methods -- Chapter 14. Advanced panel data methods -- Chapter 15. Instrumental variables estimation and two-stage least squares -- Chapter 16. Simultaneous equations models -- Chapter 17. Limited dependent variable models and sample selection corrections -- Chapter 18…