The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics (Oxford Handbooks in Economics)

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9780199857944: The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics (Oxford Handbooks in Economics)
Reseña del editor:

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. Chapters by 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, time series, 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 the true 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.

Biografía del autor:

Jeffrey S. Racine is a Professor in the Department of Economics and the Graduate Program in Statistics in the Department of Mathematics and Statistics at McMaster University, where he holds the Senator William McMaster Chair in Econometrics. He received his Ph.D. in economics from the University of Western Ontario. He is currently the Associate Editor of Econometric Reviews and The Journal of Econometric Methods. Liangjun Su is a Professor of Economics in the School of Economics at Singapore Management University. He received his PhD in economics from the University of California at San Diego. He was a recipient of the Lee Kuan Yew Fellowship for Research Excellence in 2011. He is an Associate Editor for Econometric Theory and Journal of Econometrics. Aman Ullah is a Distinguished Professor and Chair in the Department of Economics at the University of California, Riverside. He received his Ph.D. in economics from the Delhi School of Economics at University of Delhi, India. Dr. Ullah is currently a member of the editorial boards of EconometricReviews, Empirical Analysis, and Journal of Quantitative Economics, among others.

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Racine, Jeffrey; Su, Liangjun; Ullah, Aman
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Descripción Oxford University Press Inc, United States, 2014. Hardback. Estado de conservación: New. 249 x 180 mm. Language: English . Brand New Book. 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. Chapters by 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, time series, 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 the true 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. Nº de ref. de la librería AOP9780199857944

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Racine, Jeffrey; Su, Liangjun; Ullah, Aman
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Descripción Oxford University Press Inc, United States, 2014. Hardback. Estado de conservación: New. 249 x 180 mm. Language: English . Brand New Book. 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. Chapters by 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, time series, 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 the true 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. Nº de ref. de la librería AOP9780199857944

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