計量經(jīng)濟分析

前言

《計量經(jīng)濟分析》是計量經(jīng)濟學領域經(jīng)典的教材之一。這本教材自1990年問世以來，在全球眾多高校的中高級計量經(jīng)濟學課程中得到廣泛使用.成為計量經(jīng)濟學領域的研究人員不可多得的案頭參考資料。近年來，隨著計量經(jīng)濟學學科的飛速發(fā)展，許多最新的前沿研究成果不斷地充實到教材當中。這樣，與其他主流的經(jīng)濟學類教材一樣，《計量經(jīng)濟分析》從1990年第一版開始至2008年，已經(jīng)更新到第六版。通讀第六版原文，不難發(fā)現(xiàn)其內(nèi)容詳盡，資料充實，案例豐富，為讀者提供了非常全面的參考素材。而這本經(jīng)典教材在內(nèi)容上的不斷擴充，也確實彰顯了學科的發(fā)展速度。但是，在選用教材的過程中，廣大教師可能還需要考慮教學學時、教學內(nèi)容的覆蓋面以及教學難度等問題。尤其是在學時安排比較緊湊的情況下，不可能將全書所有內(nèi)容都進行講解。同時，學生可能也需要有選擇地閱讀基本且重要的內(nèi)容。有鑒于此，《計量經(jīng)濟分析》（第六版）的精編版在完整版的基礎上進行了刪節(jié)，刪減的依據(jù)是主要保留計量經(jīng)濟學比較基本與核心的重點內(nèi)容（如最小二乘、廣義回歸以及重要的模型診斷檢驗內(nèi)容等），適當保留部分重要的前沿內(nèi)容（如面板數(shù)據(jù)回歸的相關內(nèi)容等）。這樣，如果沒有足夠的時間閱讀《計量經(jīng)濟分析》的全書完整版，就可以選擇精編版，從而也能體會到這本著作的精髓。這在一定程度上避免了由于教材篇幅過長而可能給讀者帶來“只見樹木不見森林”的問題。當然，在條件和時間允許的情況下，格林的這本經(jīng)典計量經(jīng)濟學教材的完整版，還是非常值得一讀的。對于學生、教師和研究人員來說，選擇完整版作為案頭必備的參考資料，而選擇精編版作為教學和研讀的工具，可能會收到更好的效果。

內(nèi)容概要

《計量經(jīng)濟分析》是計量經(jīng)濟領域“圣經(jīng)”般的教材。它對計量經(jīng)濟學領域的知識做了全面概述及整合，并且保持及時的更新，因而無論對社會學、醫(yī)學、環(huán)境經(jīng)濟學還是政治學、經(jīng)濟學等領域，都能提供獨特的研究視角和方法。    本書可作為社會科學領域本科高年級或研究生學習計量經(jīng)濟學的教材。它有兩個目標：一是將學生引入應用計量經(jīng)濟學的殿堂，包括回歸分析的基本方法，以及在發(fā)現(xiàn)線性模型不充分或不適當時所使用的各種模型；二是向讀者充分介紹理論背景，并讓讀者認識到，這里所學習的一些新模型，就是我們所熟悉的某些模型在同一原理下的自然引申。

作者簡介

威廉·H·格林，1976年畢業(yè)于美國威斯康星大學麥迪遜分校（University of Wisconsin，Madison），獲經(jīng)濟學博士學位?，F(xiàn)任美國紐約大學（University of New York）斯特恩商學院（Stern School of Business）經(jīng)濟學教授、豐田汽車講席教授。曾任教于康奈爾大學，并擔任賓夕

書籍目錄

第一部分  線性回歸模型  第1章  引言  第2章  經(jīng)典多元線性回歸模型  第3章  最小二乘法  第4章  最小二乘估計的統(tǒng)計特性第二部分  廣義回歸模型  第5章  廣義回歸模型與異方差  第6章  面板數(shù)據(jù)模型  第7章  回歸方程組第三部分  工具變量與聯(lián)立方程模型  第8章  工具變量估計  第9章  聯(lián)立方程模型第四部分  估計方法  第10章  最小距離估計與廣義矩估計法  第11章  極大似然估計第五部分  時間序列與宏觀計量經(jīng)濟學  第12章  序列相關  第13章  帶有滯后變量的回歸模型第六部分  橫截面、面板數(shù)據(jù)及微觀計量經(jīng)濟學  第14章  離散選擇模型  第15章  截斷、設限與樣本選擇附錄  實際應用中的數(shù)據(jù)

章節(jié)摘錄

插圖：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 appications. 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.

編輯推薦

　　《計量經(jīng)濟分析（第6版）》對計量經(jīng)濟學領域的知識做了全面概述及整合，并且保持及時的更新，因而無論對社會學、醫(yī)學、環(huán)境經(jīng)濟學還是政治學、經(jīng)濟學等領域，都能提供獨特的研究視角和方法。

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