The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

ISBN-10:
0199857946
ISBN-13:
9780199857944
Pub. Date:
01/30/2014
Publisher:
Oxford University Press
ISBN-10:
0199857946
ISBN-13:
9780199857944
Pub. Date:
01/30/2014
Publisher:
Oxford University Press
The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

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Overview

This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. These data-driven models seek to replace the classical parametric models of the past, which were rigid and often linear. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures. They provide a balanced view of new developments in the modeling of cross-section, time series, panel, and spatial data. Topics of the volume include: the methodology of semiparametric models and special regressor methods; inverse, ill-posed, and well-posed problems; methodologies related to additive models; sieve regression, nonparametric and semiparametric regression, and the true error of competing approximate models; support vector machines and their modeling of default probability; series estimation of stochastic processes and their application in Econometrics; identification, estimation, and specification problems in semilinear time series models; nonparametric and semiparametric techniques applied to nonstationary or near nonstationary variables; the estimation of a set of regression equations; and a new approach to the analysis of nonparametric models with exogenous treatment assignment.

Product Details

ISBN-13: 9780199857944
Publisher: Oxford University Press
Publication date: 01/30/2014
Series: Oxford Handbooks
Pages: 558
Product dimensions: 7.10(w) x 9.80(h) x 1.30(d)

About the Author

Jeffrey S. Racine is a Professor in the Department of Economics and the Graduate Program in Statistics in the Department of Mathematics and Statistics at McMaster University, where he holds the Senator William McMaster Chair in Econometrics. He received his Ph.D. in economics from the University of Western Ontario. He is currently the Associate Editor of Econometric Reviews and The Journal of Econometric Methods.

Liangjun Su is a Professor of Economics in the School of Economics at Singapore Management University. He received his PhD in economics from the University of California at San Diego. He was a recipient of the Lee Kuan Yew Fellowship for Research Excellence in 2011. He is an Associate Editor for Econometric Theory and Journal of Econometrics.

Aman Ullah is a Distinguished Professor and Chair in the Department of Economics at the University of California, Riverside. He received his Ph.D. in economics from the Delhi School of Economics at University of Delhi, India. Dr. Ullah is currently a member of the editorial boards of Econometric Reviews, Empirical Analysis, and Journal of Quantitative Economics, among others.

Table of Contents

Contents

List of Contributors

Preface

PART 1: METHODOLOGY
1. The Hilbert Space Theoretical Foundation of Semi-Nonparametric Modeling
Herman J. Bierens

2. An Overview of the Special Regressor Method
Arthur Lewbel

PART 2: INVERSE PROBLEMS
3. Asymptotic Normal Inference in Linear Inverse Problems
Marine Carrasco, Jean-Pierre Florens, and Eric Renault

4. Identification and Well-Posedness in Nonparametric Models with Independence Conditions
Victoria Zinde-Walsh

PART 3: ADDITIVE MODELS
5. Nonparametric Additive Models
Joel L. Horowitz

6. Oracally Efficient Two-Step Estimation for Additive Regression
Shujie Ma and Lijian Yang

7. Additive Models: Extensions and Related Models
Enno Mammen, Byeong U. Park, and Melanie Schienle

PART 4: MODEL SELECTION AND AVERAGING
8. Nonparametric Sieve Regression: Least Squares, Averaging Least Squares, and Cross-Validation
Bruce E. Hansen

9. Variable Selection in Nonparametric and Semiparametric Regression Models
Liangjun Su and Yonghui Zhang

10. Data-Driven Model Evaluation: A Test for Revealed Performance
Jeffrey S. Racine and Christopher F. Parmeter

11. Support Vector Machines with Evolutionary Model Selection for Default Prediction
Wolfgang Karl Härdle, Dedy Dwi Prastyo, and Christian Hafner

PART 5: TIME SERIES
12. Series Estimation of Stochastic Processes: Recent Developments and Econometric Applications
Peter C.B. Phillips and Zhipeng Liao

13. Identification, Estimation, and Specification in a Class of Semi-Linear Time Series Models
Jiti Gao

14. Nonparametric and Semiparametric Estimation and Hypothesis Testing with Nonstationary Time Series
Yiguo Sun and Qi Li

PART 6: CROSS SECTION
15. Nonparametric and Semiparametric Estimation of a Set of Regression Equations
Aman Ullah and Yun Wang

16. Searching for Rehabilitation in Nonparametric Regression Models with Exogenous Treatment Assignment
Daniel J. Henderson and Esfandiar Maasoumi
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