Introductory Econometrics: Using Monte Carlo Simulation with Microsoft Excel [Hardcover]

This accessible textbook and supporting web site use Excel (R) to teach introductory econometrics.This introductory econometrics book is radically different from its competitors. Where other texts are filled with formulas and jargon, packed with a great deal of advanced material and require advanced mathematics, its fundamental strategy is to use clear language and take advantage of recent developments in computers to create concrete, visual explanations of difficult, abstract ideas. For more, readers may visit the web site at www.wabash.edu/econometrics.This introductory econometrics book is radically different from its competitors. Where other texts are filled with formulas and jargon, packed with a great deal of advanced material and require advanced mathematics, its fundamental strategy is to use clear language and take advantage of recent developments in computers to create concrete, visual explanations of difficult, abstract ideas. For more, readers may visit the web site at www.wabash.edu/econometrics.This highly accessible and innovative text (and accompanying website: www.wabash.edu/econometrics) uses Excel (R) workbooks powered by Visual Basic macros to teach the core concepts of econometrics without advanced mathematics. It enables students to run monte Carlo simulations in which they repeatedly sample from artificial data sets in order to understand the data generating process and sampling distribution. 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.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.lST