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Semiparametric regression for the applied econometrician

Author: Adonis Yatchew
Publisher: New York : Cambridge University Press, 2003.
Series: Themes in modern econometrics.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book provides simple and flexible (nonparametric) techniques for analyzing regression data. It includes a series of empirical examples including estimation of Engel curves and equivalence scales, scale economies, household gasoline consumption, housing prices, option prices and state price density estimation.
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Yatchew, Adonis.
Semiparametric regression for the applied econometrician.
New York : Cambridge University Press, 2003
(DLC) 2002041002
(OCoLC)50912745
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Adonis Yatchew
ISBN: 0511064675 9780511064678 0511073135 9780511073137
OCLC Number: 57218482
Description: 1 online resource (xix, 213 pages) : illustrations.
Contents: Cover; Half-title; Series-title; Title; Copyright; Dedication; Contents; List of Figures and Tables; Preface; 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; Appendix A --
Mathematical Preliminaries; Appendix B --
Proofs; Appendix C --
Optimal Differencing Weights; Appendix D --
Nonparametric Least Squares; Appendix E --
Variable Definitions.
Series Title: Themes in modern econometrics.
Responsibility: Adonis Yatchew.

Abstract:

This book provides simple and flexible (nonparametric) techniques for analyzing regression data. It includes a series of empirical examples including estimation of Engel curves and equivalence scales, scale economies, household gasoline consumption, housing prices, option prices and state price density estimation.

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