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Semiparametric Regression for the Ap...
~
Gourieroux, Christian.
Semiparametric Regression for the Applied Econometrician.
紀錄類型:
書目-電子資源 : 單行本
正題名/作者:
Semiparametric Regression for the Applied Econometrician./
作者:
Yatchew, Adonis.
其他作者:
Gourieroux, Christian.
出版者:
Cambridge :Cambridge University Press, : 2003.,
面頁冊數:
235 p.
標題:
Econometrics. -
電子資源:
Click here to view book
ISBN:
9780511615887# (electronic bk.)
Semiparametric Regression for the Applied Econometrician.
Yatchew, Adonis.
Semiparametric Regression for the Applied Econometrician.
[electronic resource]. - Cambridge :Cambridge University Press,2003. - 235 p.
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.
Electronic reproduction.
Available via World Wide Web.
Mode of access: World Wide Web.
ISBN: 9780511615887# (electronic bk.)Subjects--Topical Terms:
120795
Econometrics.
Index Terms--Genre/Form:
96803
Electronic books.
LC Class. No.: HB139 .Y38 2003eb
Dewey Class. No.: 330.015195
Semiparametric Regression for the Applied Econometrician.
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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
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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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