Nonparametric Econometrics: Theory and Practice

A textbook on nonparametric methods for students and researchers, covering theory, techniques, and empirical tests, is essential for keeping up with emerging economic analysis methods. It is tailored to the needs of applied econometricians and social scientists, emphasizing nonparametric techniques suited to discrete data types and the properties of nonparametric estimators in the presence of irrelevant variables.

Format: Paperback / softback
Length: 768 pages
Publication date: 18 July 2023
Publisher: Princeton University Press

A comprehensive and up-to-date textbook on nonparametric methods for students and researchers in nonparametric and semiparametric statistics and econometrics has long been needed. Until now, students and researchers have relied on the latest journal articles to stay up-to-date with these emerging methods of economic analysis.

Nonparametric Econometrics fills a significant gap by gathering the most up-to-date theory and techniques in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook make it an ideal introduction for graduate students and an indispensable resource for researchers.

Nonparametric and semiparametric methods have gained prominence in recent decades, particularly among statisticians working with social scientists who often deal with categorical data such as nominal and ordinal variables. The conventional nonparametric approach to handling discrete variables is acknowledged to be inadequate.

This book is specifically designed to meet the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques that can handle a wide range of data types, including continuous, nominal, and ordinal, within a unified framework. They also highlight the properties of nonparametric estimators when dealing with potentially irrelevant variables.

Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems. It provides a comprehensive guide to nonparametric techniques, including kernel density estimation, local polynomial regression, and nonparametric regression. The book also discusses the advantages and limitations of nonparametric methods and provides practical examples and applications in fields such as economics, finance, and social sciences.

In conclusion, Nonparametric Econometrics is a valuable resource for students and researchers seeking to advance their knowledge and skills in nonparametric and semiparametric statistics and econometrics. With its comprehensive coverage, accessible format, and practical examples, this textbook is an essential tool for anyone interested in applying these methods to real-world problems.

Dimension: 254 x 178 (mm)
ISBN-13: 9780691248080