Semiparametric Regression for the Applied Econometrician
$36.00 ( ) USD
Part of Themes in Modern Econometrics
- Author: Adonis Yatchew, University of Toronto
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Adonis Yatchew provides simple and flexible (nonparametric) techniques for analyzing regression data. He includes a series of empirical examples with the estimation of Engel curves and equivalence scales, scale economies, household gasoline consumption, housing prices, option prices and state price density estimation. The book is of interest to a broad range of economists including those working in industrial organization, labor, development, and urban, energy and financial economics.Read more
- Offers practical nonparametric and semiparametric techniques for applied practitioners, filling a real gap in this advanced literature
- Numerous empirical examples provided
- Data and code (in S-Plus) will also appeal to practitioners
Reviews & endorsements
"This outstanding textbook transforms abstract theoretical developments in nonparametric and semiparametric regression models into insightful and illuminating applications of great interest to empirical econometricians. The examples and exercises are well-crafted, and data and software code are accessible via the Internet."
Ernst Berndt, MITSee more reviews
"Yatchew has written an exceptionally clear and accessible book. Full of applications to household consumption data, it makes an invaluable text and reference for the applied researcher."
Richard Blundell, University College, London
"An invaluable resource for the applied econometrician who wants to learn how to do applied nonparametric and semiparametric empirical studies. The many empirical examples as well as the theoretical development demonstrate a deep understanding of the topics covered."
Jerry Hausman, MIT
"This fluent book is an excellent source for learning, or updating oneas knowledge of semi- and nonparametric methods and their applications. It is a valuable addition to the existent books on these topics."
Rosa Matzkin, Northwestern University
"Yatchew's book is an excellent account of semiparametric regression. The material is nicely integrated by using a simple set of ideas which exploit the impact of differencing and weighting operations on the data. The empirical applications are attractive and will be extremely helpful for those encountering this material for the first time."
Adrian Pagan, Australian National University
"At the University of Toronto Adonis Yatchew is known for excellence in teaching. The key to this excellence is the succinct transparency of his exposition. At its best such exposition transcends the medium of presentation (either lecture or text). This monograph reflects the clarity of the authoras thinking on the rapidly expanding fields of semiparametric and nonparametric analysis. Both students and researchers will appreciate the mix of theory and empirical application."
Dale Poirier, University of California, Irvine
"A concise self-contained treatment of nonparametric and seminonparametric regression models and their applications in econometrics. It is written in an accessible style and provides key intuition for nonparametric and seminonparametric regression methods in a cross-sectional, essentially independently distributed, setting. Well-explained theoretical ideas are illustrated by many real-data examples and exercises, mainly from the field of applied microeconometrics."
Fabio Trojani, University of St. Gallen, Journal of the American Statistician
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- Date Published: December 2004
- format: Adobe eBook Reader
- isbn: 9780511058349
- contains: 30 b/w illus. 22 tables
- availability: This item is not supplied by Cambridge University Press in your region. Please contact eBooks.com for availability.
Table of Contents
List of figures and tables
1. Introduction to differencing
2. Background and overview
3. Introduction to smoothing
4. Higher-order differencing procedures
5. Nonparametric functions of several variables
6. Constrained estimation and hypothesis testing
7. Index models and other semiparametric specifications
8. Bootstrap procedures
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