A comprehensive, up-to-date textbook on nonparametric methods for
students and researchers 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.
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