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Semiparametric regression for the applied econometrician / Adonis Yatchew.

By: Material type: TextTextSeries: Themes in modern econometricsPublication details: New York : Cambridge University Press, 2003.Description: 1 online resource (xix, 213 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 0511064675
  • 9780511064678
  • 0511073135
  • 9780511073137
Subject(s): Genre/Form: Additional physical formats: Print version:: Semiparametric regression for the applied econometrician.DDC classification:
  • 330/.01/519536 22
LOC classification:
  • HB139 .Y38 2003eb
Other classification:
  • F224. 0
Online resources:
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.
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.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library EBSCO Business Available
Total holds: 0

Includes bibliographical references (pages 197-207) and index.

Print version record.

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.

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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