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Nonparametric econometrics. Theory and practice. (English) Zbl 1183.62200
Princeton, NJ: Princeton University Press (ISBN 978-0-691-12161-1/hbk). xxi, 746 p. (2007).
Publisher’s 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. This book 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 operates 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 text is tailored to the needs of applied econometricians and social scientists. The authors emphasize nonparametric techniques suited to the rich array of data types, continuous, nominal, and ordina, within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables. The book covers all the material necessary to understand and apply nonparametric methods for real-world problems.

MSC:
62P20 Applications of statistics to economics
62P25 Applications of statistics to social sciences
62G05 Nonparametric estimation
62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics
62G08 Nonparametric regression and quantile regression
62-02 Research exposition (monographs, survey articles) pertaining to statistics
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