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A Primer in Econometric Theory Hardcover – 5 August 2016
by
John Stachurski
(Author)
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A concise treatment of modern econometrics and statistics, including underlying ideas from linear algebra, probability theory, and computer programming.This book offers a cogent and concise treatment of econometric theory and methods along with the underlying ideas from statistics, probability theory, and linear algebra. It emphasizes foundations and general principles, but also features many solved exercises, worked examples, and code listings. After mastering the material presented, readers will be ready to take on more advanced work in different areas of quantitative economics and to understand papers from the econometrics literature. The book can be used in graduate-level courses on foundational aspects of econometrics or on fundamental statistical principles. It will also be a valuable reference for independent study.One distinctive aspect of the text is its integration of traditional topics from statistics and econometrics with modern ideas from data science and machine learning; readers will encounter ideas that are driving the current development of statistics and increasingly filtering into econometric methodology. The text treats programming not only as a way to work with data but also as a technique for building intuition via simulation. Many proofs are followed by a simulation that shows the theory in action. As a primer, the book offers readers an entry point into the field, allowing them to see econometrics as a whole rather than as a profusion of apparently unrelated ideas.
- Print length448 pages
- LanguageEnglish
- PublisherMIT Press Academic
- Publication date5 August 2016
- Reading age18 years and up
- Dimensions23.11 x 18.03 x 2.79 cm
- ISBN-100262034905
- ISBN-13978-0262034906
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Product description
About the Author
John Stachurski is Professor of Economics at the Australian National University and the author of Economic Dynamics- Theory and Computation (MIT Press).
Product details
- Publisher : MIT Press Academic (5 August 2016)
- Language : English
- Hardcover : 448 pages
- ISBN-10 : 0262034905
- ISBN-13 : 978-0262034906
- Reading age : 18 years and up
- Dimensions : 23.11 x 18.03 x 2.79 cm
- Best Sellers Rank: 339,231 in Books (See Top 100 in Books)
- 313 in Econometrics (Books)
- 450 in Statistics (Books)
- 1,017 in Business Education & Reference
- Customer Reviews:
About the author
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John Stachurski is a professor at Australian National University. He is a winner of the ARC Discovery Outstanding Reseacher Award and the IJET Lionel McKenzie Prize, awarded to young authors who have made outstanding contributions to economic theory. His research is published in such leading journals as Econometrica and Journal of Economic Theory.
Customer reviews
4.8 out of 5 stars
4.8 out of 5
16 global ratings
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Top reviews from other countries
- JonasReviewed in the Netherlands on 8 November 2022
5.0 out of 5 stars Nice
Verified PurchaseConcise and modern treatment of theoretical econometrics. Good balance between rigour and intuition. The most important prerequisites are undergraduate-level real analysis and linear algebra. Previous exposure to probability theory is helpful but not absolutely necessary.
- Richard RiveroReviewed in the United States on 18 July 2017
5.0 out of 5 stars This is an excellent text covering a wide range of topics
Verified PurchaseThis is an excellent text covering a wide range of topics. There are plenty of examples and many exercises (with solutions!) which test key concepts without requiring a ton of "cleverness," making the textbook useful for expedient self-study. Indeed, it's one of the few mathematical works that I've managed to read cover-to-cover.
- Manuel Cuellar-RioReviewed in the United States on 12 October 2016
4.0 out of 5 stars Nicely written and concise!!!
Verified Purchase¿What skills should you master to do modern econometrics and beyond? That is answered by Stachurski's. A text that points to the basis of all the topics included, without distractions; but with more than enough exercises to practice. I am still working on it.