The Oxford handbook of applied nonparametric and semiparametric econometrics and statistics / edited by Jeffrey Racine, Liangjun Su, and Aman Ullah.

pt. 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
pt. II INVERSE PROBLEMS
3. Asymptotic Normal Inference in Linear Inverse Problems / Eric Renault
4. Identification and Well-Posedness in Nonparametric Models with Independence Conditions / Victoria Zinde-Walsh
pt. III ADDITIVE MODELS
5. Nonparametric Additive Models / Joel L. Horowitz
6. Oracally Efficient Two-step Estimation for Additive Regression / Lijian Yang
7. Additive Models: Extensions and Related Models / Melanie Schienle
pt. 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 / Yonghui Zhang
10. Data-Driven Model Evaluation: A Test for Revealed Performance / Christopher F. Parmeter
11. Support Vector Machines with Evolutionary Model Selection for Default Prediction / Christian M. Hafner
pt. V TIME SERIES
12. Series Estimation of Stochastic Processes: Recent Developments and Econometric Applications / Zhipeng Liao
13. Identification, Estimation, and Specification in a Class of Semilinear Time Series Models / Jiti Gao
14. Nonparametric and Semiparametric Estimation and Hypothesis Testing with Nonstationary Time Series / Qi Li
pt. VI CROSS SECTION
15. Nonparametric and Semiparametric Estimation of a Set of Regression Equations / Yun Wang
16. Searching for Rehabilitation in Nonparametric Regression Models with Exogenous Treatment Assignment / Esfandiar Maasoumi.