This highly accessible and innovative text with supporting web site uses Excel (R) to teach the core concepts of econometrics without advanced mathematics. It enables students to use Monte Carlo simulations in order to understand the data generating process and sampling distribution. Intelligent repetition of concrete examples effectively conveys the properties of the ordinary least squares (OLS) estimator and the nature of heteroskedasticity and autocorrelation. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software. The accompanying web site with text support can be found at www.wabash.edu/econometrics.
Humberto Barreto is DeVore Professor of Economics at Wabash College, Indiana. He received his Ph.D. from the University of North Carolina at Chapel Hill. Professor Barreto has lectured often on teaching economics with computer-based methods, including the National Science Foundation's Chautuqua program for short courses using simulation. He has received the Indiana Sears Roebuck Teaching Award and the Wabash College McLain-McTurnan Arnold Award for Teaching Excellence. The author of The Entrepreneur in Microeconomic Theory, Professor Barreto has served as a Fulbright Scholar in the Dominican Republic. He is the manager of electronic information for the History of Economics Society and the director of the opportunities to Learn about Business program at Wabash College. Frank M. Howland is Associate Professor of Economics at Wabash College. He earned his PhD in Economics from Stanford University. Professor Howland was a visiting researcher at FEDEA on Madrid in 1995-6. His academic research focuses on college savings plans.
1. Introduction; Part I. Description: 2. Correlation; 3. Pivot tables; 4. Computing regression; 5. Interpreting regression; 6. Functional form; 7. Multivariate regression; 8. Dummy variables; Part II. Inference: 9. Monte Carlo simulation; 10. Inferential statistics review; 11. Measurement box model; 12. Comparing two populations; 13. The classical econometric model; 14. The Gauss Markov theorem; 15. Understanding the standard error; 16. Hypothesis testing and confidence intervals; 17. F tests; 18. Omitted variable bias; 19. Heteroskedasticity; 20. Autocorrelation; 21. The series topics; 22. Dummy dependent variables; 23. Bootstrap; 24. Simultaneous equations.
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- ID: 9780521843195
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