Introductory Econometrics
Using Monte Carlo Simulation with Microsoft Excel

This accessible textbook and supporting web site use Excel (R) to teach introductory econometrics.

Humberto Barreto (Author), Frank Howland (Author)

9780521843195, Cambridge University Press

Hardback, published 26 December 2005

800 pages, 4 tables
25.9 x 18.5 x 5.1 cm, 1.56 kg

'The authors wrote a textbook on introductory econometrics which is different from most textbooks by using Monte Carlo simulation with Microsoft Excel. The book is written for undergraduate students in econometrics who should not be explicitly confronted with formal mathematics but instead with visual explanations of abstract ideas.' Zentralblatt MATH

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.

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.

Subject Areas: Applied mathematics [PBW], Probability & statistics [PBT], Economic statistics [KCHS], Econometrics [KCH]