Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

The book 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 highli...

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Main Authors: RACINE, Jeffrey, SU, Liangjun, ULLAH, Aman
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2014
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Online Access:https://ink.library.smu.edu.sg/soe_research/1449
https://search.library.smu.edu.sg/primo-explore/fulldisplay?docid=SMU_ALMA2137023970002601&context=L&vid=SMU_NUI&search_scope=Everything&tab=default_tab&lang=en_US
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spelling sg-smu-ink.soe_research-24482017-08-03T04:35:16Z Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics RACINE, Jeffrey SU, Liangjun ULLAH, Aman The book 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. 2014-02-01T08:00:00Z text https://ink.library.smu.edu.sg/soe_research/1449 https://search.library.smu.edu.sg/primo-explore/fulldisplay?docid=SMU_ALMA2137023970002601&context=L&vid=SMU_NUI&search_scope=Everything&tab=default_tab&lang=en_US Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Econometrics non-parametric statistics Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Econometrics
non-parametric statistics
Econometrics
spellingShingle Econometrics
non-parametric statistics
Econometrics
RACINE, Jeffrey
SU, Liangjun
ULLAH, Aman
Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics
description The book 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.
format text
author RACINE, Jeffrey
SU, Liangjun
ULLAH, Aman
author_facet RACINE, Jeffrey
SU, Liangjun
ULLAH, Aman
author_sort RACINE, Jeffrey
title Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics
title_short Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics
title_full Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics
title_fullStr Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics
title_full_unstemmed Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics
title_sort oxford handbook of applied nonparametric and semiparametric econometrics and statistics
publisher Institutional Knowledge at Singapore Management University
publishDate 2014
url https://ink.library.smu.edu.sg/soe_research/1449
https://search.library.smu.edu.sg/primo-explore/fulldisplay?docid=SMU_ALMA2137023970002601&context=L&vid=SMU_NUI&search_scope=Everything&tab=default_tab&lang=en_US
_version_ 1770571466722508800