Fee Download A Primer in Econometric Theory (MIT Press), by John Stachurski
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A Primer in Econometric Theory (MIT Press), by John Stachurski
Fee Download A Primer in Econometric Theory (MIT Press), by John Stachurski
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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.
- Sales Rank: #186104 in Books
- Published on: 2016-08-05
- Original language: English
- Dimensions: 9.00" h x .94" w x 7.00" l, .0 pounds
- Binding: Hardcover
- 448 pages
Review
This important book fills a gap in the existing curriculum by providing a firm foundation in linear algebra, statistics, and coding for students who want to study advanced econometrics. And there's more: it also exposes students to methods of machine learning and computational statistics, offering a broader perspective on modern data analytic techniques.
(Hal Varian, Chief Economist, Google)A Primer in Econometric Theory presents key foundations and supplements them with good examples. It vividly shows the benefits given to us by decades of technical progress in econometrics and computational methods. Stachurski's writing style presents technical arguments in attractive and accessible ways.
(Thomas J. Sargent, New York University)John Stachurski's text, A Primer in Econometric Theory is a concise and elegant book that provides a more conceptual introduction to econometrics that coincides well with my own preferred way of teaching the subject to first-year graduate students. It is clear, rigorous, and provides a large number of interesting exercises with solutions. I will use it in my own econometrics teaching and recommend it to complement other applied econometrics books.
(John Rust, Gallagher Family Professor of Economics, Georgetown University)When I learned the fundamentals of linear algebra and economic theory as a graduate student, I found most textbooks and courses had an emphasis on theory but very little in terms of software. The emphasis on teaching these ideas through modern programming tools such as Julia, Python, and R not only makes the material far more accessible but also equips the readers of this book for their professional careers. I wish I had such a book when I was in grad school!
(Viral Shah, Co-inventor of Julia programming language, Co-founder of Julia Computing, Co-author of Rebooting India) About the Author
John Stachurski is Professor of Economics at Australian University and the author of Economic Dynamics: Theory and Computation (MIT Press).
Most helpful customer reviews
5 of 5 people found the following review helpful.
Nicely written and concise!!!
By Manuel Cuellar-Rio
¿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.
0 of 0 people found the following review helpful.
This is an excellent text covering a wide range of topics
By Richard Rivero
This 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.
7 of 7 people found the following review helpful.
Really good introductory graduate level book that provides a great deal of intuition
By Alp Eren
Here is the deal: I have a PhD in Economics was never good with data tools. Every Econometrics class I took started with linear regression and proceeded from there. I think this is a terrible way of teaching it. This book is different. It blends Probability theory well with statistics then adds Econometric tools as part of a bigger picture. It provides a lot of intuition. It also provides a better framework to add more skills in fields like machine learning as well. You can read this book on top of your undergraduate education then specialize on whatever you are going to do.
Besides you should check his quant-econ website.
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