Book Description
Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers.
Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data--nominal and ordinal--in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory.
This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types--continuous, nominal, and ordinal--within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables.
Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.
Book Description
This broadly based graduate-level textbook covers the major models and statistical tools currently used in the practice of econometrics. It examines the classical, the decision theory, and the Bayesian approaches, and contains material on single equation and simultaneous equation econometric models. Includes an extensive reference list for each topic.
Customer Reviews:
This was the econometrics bible but they never updated it.......2005-04-02
Judge, et al. was the standard reference in econometrics in the late 80s and early 90s. It's a terrific text because it has both theory and applications (with emphasis on the former, though). The best thing about it at the time of its publication was it was very complete, covering almost everything that was known in econometrics at the time.
Unfortunately, the book was never updated, and now nobody uses it; instead, people use the poorly written one by William Greene, which contributes to the poor education in grad-level econometrics these days. (Have you noticed that today's econometrics students, even the Ph.D. ones and even some assistant professors, don't even understand the relationship between R-squared and t-statistic? I get asked "why am I getting super-high t-statistics while my R^2 is so low?" all the time. If they had read Judge et al., they would have known the answer.)
Even though I loved this book in teh early 90s, I cannot recommend it as a reference book because it is pretty much out of date. Sure, most of the basic stuff (OLS, 2SLS, limited dependent, etc.) is the same, but people who buy a thick book like this want an up-to-date volume, and this book unfortunately does not fit the bill. It's so sad that such a comprehensive and well-written volume has totally languished into obscurity.
Precise and concise.......2003-06-19
Another review stated that Green was a clearer book than Judge et al. No way. This book starts and concludes thoughts without the constant refer to section blah blah blah found in Green. Also Judge et al. is accurate; something sorely missing in Green. Hamilton on the other hand focuses strictly on time series, and forecasting. If you want a solid reference for econometrics this is the most complete and well thought out book available.
outdated.......2000-11-16
I don't want to say too much about this book. I use it a lot. But I think what is in this book has been said so much more clearly elsewhere. I would rather attack econometrics using Greene's clarity or if I were interested in time-series, I would much rather have Hamilton. It is okay. It was a warhorse for its time. But unless you need it for a class, I think there are better references out there.
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Risk Analysis in Theory and Practice (Academic Press Advanced Finance)
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Book Description
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* Balanced treatment of conceptual models and applied analysis
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Download Description
The economics of risk has been a fascinating area of inquiry for at least two reasons. First, hardly any situation requiring economic decisions is certain. The sources of uncertainty are multiple and pervasive, including price risk, income risk, weather risk, and health risk. Resultantly, both private and public decisions under risk render considerable interest. Second, in recent years, there's been significant progress in understanding human behavior under uncertainty. Consequently, we now have a more refined framework to analyze decision making under risk. The author presents an analytical framework and illustrates how to use it to investigate economic decisions under risk. In a sense, the economics of risk is a difficult subject: it involves understanding human decisions in the absence of perfect information. How do we make decisions when we do not know some of events affecting us?
Book Description
This Second Edition of the highly acclaimed introduction to econometrics retains its comprehensive nature and strong authorship, while incorporating much new material. New to this edition are a complete treatment of Bayesian inference, sampling theory, an appendix on linear algebra, and a computer handbook. Presentation covers modern statistical models and focuses on the sampling theory process by which the data were generated, and the statistical consequences of alternative decisions under uncertainty. Asymptotics are introduced early on, for use throughout. Includes at least one applied example to illustrate each model, and contains many analytical and numerical exercises.
Customer Reviews:
Introduction to the Theory and Practice of Econometrics.......2000-05-12
The book is excellent for the mathematically inclined student who masters well linear lagebra. It uses matrix notaion extensively and enables one to generalize results without getting lost. I used that book in my intermediate econometrics course at the undergraduate level. I am convinced it is a mistake to start learning econometrics by first using the algebraic approach then the matrix approach. This only brings about confusion. This book is excellent as when one thinks hard through theoretical results it is much easier to get a good grasp of the empirical results one finds in applied work. I always consult this book first when I am a bit rusty in classical and special topics in econometrics. The book is not up to date to more modern econometrics such as cointegration and unit root analysis (those subjects don't exist in it).
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Book Description
Written in honor of Peter C.B. Phillips of Yale University by some of his former students, these essays analyze a number of state of the art issues in econometrics, all of which Professor Phillips has directly influenced through his scholarly contribution as well as through his remarkable achievements as a teacher. The essays are organized to cover topics in higher-order asymptotics, deficient instruments, nonstationary, LAD and quantile regression, and nonstationary panels. These topics span both theoretical and applied approaches and are intended for use by professionals and advanced graduate students.
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Book Description
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