The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics by Jeffrey Racine

The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

byJeffrey Racine, Liangjun Su, Aman Ullah

Hardcover | January 14, 2014

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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. Chaptersby 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 analysis and modeling of applied sciences with cross-section, timeseries, panel, and spatial data sets. The major topics of the volume include: the methodology of semiparametric models and special regressor methods; inverse, ill-posed, and well-posed problems; different methodologies related to additive models; sieve regression estimators, nonparametric and semiparametric regression models, and thetrue error of competing approximate models; support vector machines and their modeling of default probability; series estimation of stochastic processes and some of their applications in Econometrics; identification, estimation, and specification problems in a class of 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.

About The Author

Jeffrey Racine is Professor in the Department of Economics and the Department of Mathematics and Statistics as well as Senator William McMaster Chair in Econometrics at McMaster University. Liangjun Su is Associate Professor in the School of Economics at Singapore Management University and in the Guanghua School of Management at Peking...
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Title:The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and StatisticsFormat:HardcoverDimensions:544 pages, 9.75 × 6.75 × 0.98 inPublished:January 14, 2014Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0199857946

ISBN - 13:9780199857944

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Table of Contents

List of ContributorsPrefacePART 1: METHODOLOGY1. Herman J. Bierens: The Hilbert Space Theoretical Foundation of Semi-Nonparametric Modeling2. Arthur Lewbel: An Overview of the Special Regressor MethodPART 2: INVERSE PROBLEMS3. Marine Carrasco, Jean-Pierre Florens, and Eric Renault: Asymptotic Normal Inference in Linear Inverse Problems4. Victoria Zinde-Walsh: Identification and Well-Posedness in Nonparametric Models with Independence ConditionsPART 3: ADDITIVE MODELS5. Joel L. Horowitz: Nonparametric Additive Models6. Shujie Ma and Lijian Yang: Oracally Efficient Two-Step Estimation for Additive Regression7. Enno Mammen, Byeong U. Park, and Melanie Schienle: Additive Models: Extensions and Related ModelsPART 4: MODEL SELECTION AND AVERAGING8. Bruce E. Hansen: Nonparametric Sieve Regression: Least Squares, Averaging Least Squares, and Cross-Validation9. Liangjun Su and Yonghui Zhang: Variable Selection in Nonparametric and Semiparametric Regression Models10. Jeffrey S. Racine and Christopher F. Parmeter: Data-Driven Model Evaluation: A Test for Revealed Performance11. Wolfgang Karl Herdle, Dedy Dwi Prastyo, and Christian Hafner: Support Vector Machines with Evolutionary Model Selection for Default PredictionPART 5: TIME SERIES12. Peter C.B. Phillips and Zhipeng Liao: Series Estimation of Stochastic Processes: Recent Developments and Econometric Applications13. Jiti Gao: Identification, Estimation, and Specification in a Class of Semi-Linear Time Series Models14. Yiguo Sun and Qi Li: Nonparametric and Semiparametric Estimation and Hypothesis Testing with Nonstationary Time SeriesPART 6: CROSS SECTION15. Aman Ullah and Yun Wang: Nonparametric and Semiparametric Estimation of a Set of Regression Equations16. Daniel J. Henderson and Esfandiar Maasoumi: Searching for Rehabilitation in Nonparametric Regression Models with Exogenous Treatment Assignment