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Introductory Econometrics
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  • 4 tables
  • Page extent: 800 pages
  • Size: 253 x 177 mm
  • Weight: 1.59 kg
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 (ISBN-13: 9780521843195 | ISBN-10: 0521843197)

DOI: 10.2277/0521843197

Manufactured on demand: supplied direct from the printer

 (Stock level updated: 02:09 GMT, 28 November 2015)



  • Lecturers can request inspection copies of this title.
  • Courses: • Introductory Econometrics, Econometrics, Econometrics and Statistics • Economics, Statistics, Econometrics, Applied Mathematics, Computer Science departments

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

• Active learning with highly accessible introductory text using computers and web site support rather than passive reading • Well-prepared Excel (R) workbooks enable easy Monte Carlo simulation and other analyses


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.


'Hats off to Barreto and Howland for a clearly-written text that introduces the undergraduate to data analysis and econometric techniques using Excel. The book's strength is in using Monte Carlo simulation to illustrate sampling theory and the Gauss Markov theorem. I am in total agreement with the authors that computer-based exercises help to make abstract concepts operations and meaningful. Most juniors and seniors are familiar with the basic features of Excel spreadsheets. Showing them how to use SOLVER, the DATA ANALYSIS TOOLS, and to run Monte Carlo simulations, allows an instructor to take a familiar tool (Excel) and use it to introduce undergraduates to econometrics in an intuitive and non-threatening way.' Jon M. Conrad, Cornell University

'Barreto and Howland have taken a truly innovative approach to teach undergraduate econometrics, using computer simulation methods to illustrate and clarify difficult topics. Fully integrated with Microsoft Excel, this textbook forces students to take a hands-on approach to the subject. There is no better way to learn econometrics than by doing econometrics!' Jason Abrevaya, Purdue University

'Barreto and Howland have done an excellent job of producing an introductory econometric textbook based on Excel software combined with a well written and applied intuitive approach to econometrics. In my opinion, their teaching philosophy is absolutely the correct method: Put the student in front of a computer and teach econometrics by doing econometrics.' Daniel V. Gordon, University of Calgary

'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

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