The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

Abstract

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 Hardle, 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