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Econometrics读书介绍

类别 页数 译者 网友评分 年代 出版社
书籍 690页 9.1 2020 Princeton University Press
定价 出版日期 最近访问 访问指数
USD 115.00 2020-02-20 … 2020-07-09 … 94
主题/类型/题材/标签
Econometrics,经济学,计量经济学,教材,计量,经济,经典计量教材系列,Economics,
作者
Fumio Hayashi      ISBN:9780691010182    原作名/别名:《》
内容和作者简介
Econometrics摘要

Hayashi's "Econometrics" promises to be the next great synthesis of modern econometrics. It introduces first year PhD 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 distinctiv...

作者简介

Hayashi's "Econometrics" promises to be the next great synthesis of modern econometrics. It introduces first year PhD 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.

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