A Practical Guide to Quantitative Research in Economics, Finance and Development Studies
Introduces first-year social science undergraduates to the practical aspects of simple regression analysis, without adopting an esoteric, mathematical approach.
Running Regressions introduces first-year social science undergraduates, particularly those studying economics and business, to the practical aspects of simple regression analysis, without adopting an esoteric, mathematical approach. It shows that statistical analysis can be simultaneously straightforward, useful and interesting, and can deal with topical, real-world issues. Each chapter introduces an economic theory or idea by relating it to an issue of topical interest, and explains how data and econometric analysis can be used to test it. The book can be used as a self-standing text or to supplement conventional econometric texts. It is also ideally suited as a guide to essays and project work.
List of figures; List of tables; List of boxes; List of acronyms; How to use this book; Part I. Simple Regression and Data Analysis: 1. An introduction to ordinary least squares; 2. Running simple regressions: global poverty and growth; 3. Using logs and estimating elasticities: demand for air travel; 4. Hypothesis testing: health expenditures and the quality of life; Part II. Multiple Regression and Diagnostic Testing: 5. Multiple regression analysis: housing demand in the UK; 6. Heteroscedasticity: R 7. Autocorrelation: tourism and the environment; 8. Model misspecification: Tobin's q and investment in the USA; Part III. Time Series Econometrics: 9. Structural breaks, non-stationarity and spurious regressions: venture capital and computing investment in the USA; 10. Error correction models AND cointegration: consumption and the multiplier in the UK; Part IV. Advanced Topics: 11. Panel estimation: divorce and income; 12. Binary dependent variables: war and poverty; Index.