The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

Part I: 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 II: 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 III: 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 IV: 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 V: 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 VI: 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