A Course in Econometrics 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024


A Course in Econometrics

简体网页||繁体网页
Arthur S. Goldberger 作者
Harvard University Press
译者
1991-04-15 出版日期
432 页数
USD 73.00 价格
Hardcover
丛书系列
9780674175440 图书编码

A Course in Econometrics 在线电子书 图书标签: 经济学  经济  计量经济学  econometrics  经管  Econometrics  计量  统计学   


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发表于2024-06-30


A Course in Econometrics 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

A Course in Econometrics 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

A Course in Econometrics 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



A Course in Econometrics 在线电子书 用户评价

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在看woodridge之前看的

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一本计量很好的入门的书,深入浅出,问题意识很好,既有简单的入门,也有复杂的一些计量方法,适合很多人读

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读十遍也不为过

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little book but shing insights!!!!

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读十遍也不为过

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A Course in Econometrics 在线电子书 图书描述

The primary purpose of this book is to prepare students for empirical research in economics. But it also equips those who plan to specialize in econometric theory and those whose empirical interests are in sociology or business. Aimed at first-year graduate students and advanced undergraduates, "A Course in Econometrics" covers the fundamentals - classical regression and simultaneous equations - but also contains clear treatments of symptotic theory and nonlinear regression. The innovative features of the text include: (1) a focus on the conditional expectation function and best linear predictor as interesting characteristics of a population: (2) a thoughtful interpretation of assumptions on the disturbance term in linear regression; (3) a consistent development of estimators as sample analogs of population parameters; (4) a careful discussion of alternative sampling schemes to clarify the distinction between random and idea explanatory variables; (5) a development of asymptotic theory that emphasizes a simple prototypical case; (6) a cautionary treatment of the use and abuse of significance tests; (7) an introduction to simultaneous equation models that focuses on structural parameters as invariant across populations. The text includes instructive exercises and graphs, along with several complete data sets.

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