The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

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