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  • 高等院校双语教材?经济系列?计量经济分析(第6版)[平装]
  • 共1个商家     34.30元~34.30
  • 作者:张成思(改编),威廉·H·格林(WilliamH.Greene)(作者)
  • 出版社:中国人民大学出版社;第1版(2009年9月1日)
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  • ISBN:9787300112060

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    《计量经济分析(第6版)》是计量经济学领域经典的教材之一。《计量经济分析(第6版)》对计量经济学领域的知识做了全面概述及整合,并且保持及时的更新,因而无论对社会学、医学、环境经济学还是政治学、经济学等领域,都能提供独特的研究视角和方法。

    作者简介

    作者:(美国)威廉·H·格林(William H.Greene) 改编:张成思

    威廉·H·格林,1976年毕业于美国威斯康星大学麦迪逊分校(University of Wisconsin,Madison),获经济学博士学位。现任美国纽约大学(University of New York)斯特恩商学院(Stern School of Business)经济学教授、丰田汽车讲席教授。曾任教于康奈尔大学,并担任宾夕法尼亚州立大学、悉尼大学、牛津大学等学术机构的访问教授。
    格林教授在理论计量方法研究方面有突出的贡献,特别是在面板数据方面。此外,他在应用计量方面也有出色的成果。在国际一流学术期刊发表论文一百多篇,其中有不少发表在国际顶级期刊上,如《美国经济评论》(American Economic Review)、《计量经济学》(Econometrica)、《经济学展望》(Journal of Economic Perspective)、《计量经济学杂志》(Journal of Econometrics)等。

    目录

    第一部分 线性回归模型
    第1章 引言
    第2章 经典多元线性回归模型
    第3章 最小二乘法
    第4章 最小二乘估计的统计特性

    第二部分 广义回归模型
    第5章 广义回归模型与异方差
    第6章 面板数据模型
    第7章 回归方程组

    第三部分 工具变量与联立方程模型
    第8章 工具变量估计
    第9章 联立方程模型

    第四部分 估计方法
    第10章 最小距离估计与广义矩估计法
    第11章 极大似然估计

    第五部分 时间序列与宏观计量经济学
    第12章 序列相关
    第13章 带有滞后变量的回归模型

    第六部分 横截面、面板数据及微观计量经济学
    第14章 离散选择模型
    第15章 截断、设限与样本选择
    附录 实际应用中的数据

    序言

    《计量经济分析》是计量经济学领域经典的教材之一。这本教材自1990年问世以来,在全球众多高校的中高级计量经济学课程中得到广泛使用.成为计量经济学领域的研究人员不可多得的案头参考资料。
    近年来,随着计量经济学学科的飞速发展,许多最新的前沿研究成果不断地充实到教材当中。这样,与其他主流的经济学类教材一样,《计量经济分析》从1990年第一版开始至2008年,已经更新到第六版。
    通读第六版原文,不难发现其内容详尽,资料充实,案例丰富,为读者提供了非常全面的参考素材。而这本经典教材在内容上的不断扩充,也确实彰显了学科的发展速度。但是,在选用教材的过程中,广大教师可能还需要考虑教学学时、教学内容的覆盖面以及教学难度等问题。尤其是在学时安排比较紧凑的情况下,不可能将全书所有内容都进行讲解。同时,学生可能也需要有选择地阅读基本且重要的内容。有鉴于此,《计量经济分析》(第六版)的精编版在完整版的基础上进行了删节,删减的依据是主要保留计量经济学比较基本与核心的重点内容(如最小二乘、广义回归以及重要的模型诊断检验内容等),适当保留部分重要的前沿内容(如面板数据回归的相关内容等)。这样,如果没有足够的时间阅读《计量经济分析》的全书完整版,就可以选择精编版,从而也能体会到这本著作的精髓。这在一定程度上避免了由于教材篇幅过长而可能给读者带来“只见树木不见森林”的问题。
    当然,在条件和时间允许的情况下,格林的这本经典计量经济学教材的完整版,还是非常值得一读的。对于学生、教师和研究人员来说,选择完整版作为案头必备的参考资料,而选择精编版作为教学和研读的工具,可能会收到更好的效果。

    文摘

    插图:


    We can make a useful distinction between theoretical and applied econometrics. The-orists develop new techniques for estimation and hypothesis testing and analyze theconsequences of applying particular methods when the assumptions that justify thosemethods are not met. Applied econometricians are the users of these techniques andthe analysts of data ("real world" and simulated). Of course, the distinction is farfrom clean; practitioners routinely develop new analytical tools for the purposes ofthe study that they are involved in. This book contains a large amount of economet-ric theory, but it is directed toward applied econometrics. I have attempted to surveytechniques, admittedly some quite elaborate and intricate, that have seen wide use "inthe field."
    Another useful distinction can be made between microeconometrics and macro-econometrics. The former is characterized largely by its analysis of cross section andpanel data and by its focus on individual consumers, firms, and micro-level decisionmakers. Macroeconometrics is generally involved in the analysis of time-series data,usually of broad aggregates such as price levels, the money supply, exchange rates,output, investment, and so on. Once again, the boundaries are not sharp. The very largefield of financial econometrics is concerned with long time-series data and occasionallyvast panel data sets, but with a very focused orientation toward models of individualbehavior. The analysis of market returns and exchange rate behavior is neither macro-nor microeconometric, or perhaps it is some of both. Another application that we willexamine in this text concerns spending patterns of municipalities, which, again, restssomewhere between the two fields.
    Applied econometric methods will be used for estimation of important quantities,analysis of economic outcomes, markets or individual behavior, testing theories, and forforecasting. The last of these is an art and science in itself, and (fortunately) the subjectof a vast library of sources. Although we will briefly discuss some aspects of forecasting,our interest in this text will be on estimation and analysis of models. The presentation,where there is a distinction to be made, will contain a blend of microeconometric andmacroeconometric techniques and app
    ications. The first 11 chapters of the book arelargely devoted to results that form the platform of both areas. Chapters 12 to 13 focuson time series modeling while Chapters 14 to 15 are devoted to methods more suitedto cross sections and panels, and methods used more frequently in microeconometrics.We will not be spending any time on financial econometrics. For those with an interestin this field, I would recommend the celebrated work by Campbell, Lo, and Mackinlay(1997) and, for a more time-series-oriented approach, Tsay (2005). It is also necessaryto distinguish between time-series analysis (which is not our focus) and methods thatprimarily use time-series data. The former is, like forecasting, a growth industry servedby its own literature in many fields. While we will employ some of the techniques oftime-series analysis, we will spend relatively little time developing first principles.
    The techniques used in econometrics have been employed in a widening vari-ety of fields, including political methodology, sociology [see, e.g., Long (1997) andDeMaris (2004)], health economics, medical research (how do we handle attrition frommedical treatment studies?) environmental economics, transportation engineering, andnumerous others. Practitioners in these fields and many more are all heavy users of thetechniques described in this text.