- Tapa dura: 712 páginas
- Editor: Princeton University Press (19 de noviembre de 2000)
- Idioma: Inglés
- ISBN-10: 0691010188
- ISBN-13: 978-0691010182
- Valoración media de los clientes: 1 opinión de cliente
- Clasificación en los más vendidos de Amazon: nº69.932 en Libros en idiomas extranjeros (Ver el Top 100 en Libros en idiomas extranjeros)
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Econometrics (Inglés) Tapa dura – 19 nov 2000
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Descripción del producto
"Econometrics strikes a good balance between technical rigor and clear exposition. . . . The use of empirical examples is well done throughout. I very much like the use of old 'classic' examples. It gives students a sense of history-and shows that great empirical econometrics is a matter of having important ideas and good data, not just fancy new methods. . . . The style is just great, informal and engaging."-James H. Stock, John F. Kennedy School of Government, Harvard University "Econometrics covers both modern and classic topics without shifting gears. The coverage is quite advanced yet the presentation is simple. Hayashi brings students to the frontier of applied econometric practice through a careful and efficient discussion of modern economic theory. The empirical exercises are very useful. . . . The projects are carefully crafted and have been thoroughly debugged."-Mark W. Watson, Princeton University "Econometrics will be a very useful book for intermediate and advanced graduate courses. It covers the topics with an easy to understand approach while at the same time offering a rigorous analysis. The computer programming tips and problems should also be useful to students. I highly recommend this book for an up-to-date coverage and thoughtful discussion of topics in the methodology and application of econometrics."-Jerry A. Hausman, Massachusetts Institute of Technology "Students of econometrics and their teachers will find this book to be the best introduction to the subject at the graduate and advanced undergraduate level. Starting with least squares regression, Hayashi provides an elegant exposition of all the standard topics of econometrics, including a detailed discussion of stationary and non-stationary time series. The particular strength of the book is the excellent balance between econometric theory and its applications, using GMM as an organizing principle throughout. Each chapter includes a detailed empirical example taken from classic and current applications of econometrics."-Dale Jorgensen, Harvard University
Reseña del editor
Hayashi's Econometrics promises to be the next great synthesis of modern econometrics. It introduces first year Ph.D. students to standard graduate econometrics material from a modern perspective. It covers all the standard material necessary for understanding the principal techniques of econometrics from ordinary least squares through cointegration. The book is also distinctive in developing both time-series and cross-section analysis fully, giving the reader a unified framework for understanding and integrating results. Econometrics has many useful features and covers all the important topics in econometrics in a succinct manner. All the estimation techniques that could possibly be taught in a first-year graduate course, except maximum likelihood, are treated as special cases of GMM (generalized methods of moments). Maximum likelihood estimators for a variety of models (such as probit and tobit) are collected in a separate chapter. This arrangement enables students to learn various estimation techniques in an efficient manner. Eight of the ten chapters include a serious empirical application drawn from labor economics, industrial organization, domestic and international finance, and macroeconomics. These empirical exercises at the end of each chapter provide students a hands-on experience applying the techniques covered in the chapter. The exposition is rigorous yet accessible to students who have a working knowledge of very basic linear algebra and probability theory. All the results are stated as propositions, so that students can see the points of the discussion and also the conditions under which those results hold. Most propositions are proved in the text. For those who intend to write a thesis on applied topics, the empirical applications of the book are a good way to learn how to conduct empirical research. For the theoretically inclined, the no-compromise treatment of the basic techniques is a good preparation for more advanced theory courses.Ver Descripción del producto
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Ha surgido un problema al filtrar las opiniones justo en este momento. Vuelva a intentarlo en otro momento.
Me encanta la edición, personalmente creo que está muy bien estructurado y considero que es bastante claro.
El envío perfecto, el libro ha llegado en perfectas condiciones y en la fecha fijada.
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Wow...I still remember the pain. Trying to prove things that almost seemed impossible and stuff that they never taught me in college.
To be fair the book is well written. And I confirmed this with my hardcore econ PhD friends. Also, that is why a lot of econometrics professors love this book. However, if you do not have a solid math/ econometrics background then I suggest starting with easier book such as Wooldridge or Cameron's Econometrics book. Then look at Hayashi. Also, it is super helpful if you have a friend that can help you with the math and the proofs.
Also, these days, there are lot of Econometrics YouTube videos and other materials online, so you can supplement them. But ultimately, you have to really go through the pain and then you will see the beauty.
To meet the demand for accessible econometric literature in other disciplines, authors and publishers have produced textbooks that are much less mathematically demanding than the staple sources. Examples include Wooldridge's Introductory Econometrics, Gujarati's Essentials of Econometrics, Stockman and Watson's Introductory Econometrics, and Mirer's Economic Statistics and Econometrics. Also, Peter Kennedy's Guide to Econometrics is an accessible catalog of tests and correctives for violation of assumptions, provided the non-specialists stay out of the technical appendices.
However, Hayashi's Econometrics clearly does not belong in the category of textbooks that appeal to a broad-based audience of social scientists. Hayashi, quite rightly, has a different audience in mind, and he assumes that the reader knows and has facility in applying the mathematics that is legitimately expected of economists. He also liberally incorporates economic theory into his presentation. While the econometric texts mentioned above lean heavily on OLS estimators, Hayashi treats OLS as just a special case of the generalized method of moments, a concept that is entirely alien to most students and practitioners who are not well schooled in the mathematical methods of economics.
One consequence is that social scientists who are not cautious in selection of self-instructional materials order Hayashi's text and are then dumbfounded when they encounter mathematics and economic theory that they are not prepared to handle. Sure, they could take the time and effort needed to get up to speed, but most folks are in a hurry and have more pressing concerns for released time and sabbaticals.
I was introduced to econometrics in an independent study thirty-five years ago. I was assigned sections from the first edition of Johnston's Econometric Methods and Kmenta's Elements of Econometrics, as well as few journal articles, and was then on my own. As a result, I can sympathize with other non-economists' frustration. Johnston and Kmenta may seem pretty accessible now, but at the time they were regarded as difficult. I initially preferred Kmenta because his first edition (as well as his second) did not require practiced facility with matrix algebra. I'm still embarrassed to recall, however, how mystified I was when Kmenta began introducing alternatives to OLS estimators. I didn't know there were any! I eventually learned a lot, but making sense of Johnston forced me teach myself the rudiments of matrix algebra.
I know that textbook publishing is a racket, just look at the prices. But I think that publishers have an obligation to very conspicuously apprise prospective readers that a text like Hayashi's understandably makes demands on the reader that non-economists typically will not meet. Otherwise, social scientists who might use applied econometrics in their less mathematically-intensive disciplines will waste money and be deprived of statistical tools they might put to good use.