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16108 57
2008-08-17
<p><br/> </p><p></p><p>《Econometric Modeling and Inference》</p><p><br/>The goal of this book is to present the main statistical tools of econometrics, focusing<br/>specifically on modern econometric methodology. The authors unify the approach<br/>by using a small number of estimation techniques, mainly generalized method of<br/>moments (GMM) estimation and kernel smoothing. The choice of GMM is explained<br/>by its relevance in structural econometrics and its prominent position in<br/>econometrics overall. The book is in four parts. Part I explains general methods.<br/>Part II studies statistical models that are best suited for microeconomic data. Part III<br/>deals with dynamic models that are designed for macroeconomic and financial applications.<br/>In Part IV the authors synthesize a set of problems that are specific to<br/>statistical methods in structural econometrics, namely identification and overidentification,<br/>simultaneity, and unobservability. Many theoretical examples illustrate<br/>the discussion and can be treated as application exercises. Nobel Laureate James J.<br/>Heckman offers a foreword to the work.</p>
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Heckman鼎力推荐的计量经济学教材

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2008-8-17 14:26:00

这是Heckman专门为该书写的序言:

Jean-Pierre Florens,Vˆelayoudom Marimoutou, and Anne P´eguin-Feissolle have
done economics a great service by writing this basic contribution to the teaching
of econometrics. Econometrics is a major research tool for empirical economics.
It unites economics with statistics and extends statistical methods to apply to
economic problems and economic data.
Many introductory econometrics textbooks for graduate students have a cookbook
quality. They summarize existing knowledge useful for particular problems
without laying the foundations for extending existing knowledge. Rules
are given without reasons and general principles. Readers who do not know the
basic principles have trouble adapting existing knowledge to fit their application.
This book provides an introduction to current econometric knowledge that
focuses on teaching the reader foundational statistical principles. It exposits the
basic statistical principles underlying modern econometrics. This keeps alive
and rejuvenates the tradition of Haavelmo (1944), who, in his Nobel Prize–
winning contribution, first synthesized economic statistics with rigorous probability
theory. It surveys a large array of econometric models and gives the reader
the foundations required to adapt and extend those models to fit their applications.
This book is wide ranging in that it covers classical econometric methods
associated with linear regression and modern semiparametric cross-section and
time series methods. It provides the reader with a useful introduction to a powerful
set of tools and a guide towhere to go to read the more advanced literature on a
variety of topics useful in many fields of economics. Rigorous probability foundations
are given and problems of inference and estimation are also discussed.
Readers of this book, be they graduate students or professional economists,
will benefit from its depth and range. There is much value in learning modern
empirical methods unified by rigorous statistical principles.
James J. Heckman

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2008-8-17 14:45:00
买来看看,不知道里面是什么版本
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2008-8-17 19:45:00

是吗

现在计量的书太多了。

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2008-8-18 07:45:00
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2008-8-18 10:34:00
good book
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