Testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression

© Springer International Publishing AG 2017. The distinct points of view about factors driving economic growth are introduced all the time in which some effectively useful suggestions then become the growth theories, which in turn lead to various researches on economic growth. This paper aims to exa...

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Main Authors:	Pathairat Pastpipatkul, Paravee Maneejuk, Songsak Sriboonchitta
Format:	Book Series
Published:	2018
Subjects:	Computer Science
Online Access:	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012915946&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57117
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Institution:	Chiang Mai University

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spelling	th-cmuir.6653943832-571172018-09-05T03:35:13Z Testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression Pathairat Pastpipatkul Paravee Maneejuk Songsak Sriboonchitta Computer Science © Springer International Publishing AG 2017. The distinct points of view about factors driving economic growth are introduced all the time in which some effectively useful suggestions then become the growth theories, which in turn lead to various researches on economic growth. This paper aims to examine the joint validity of the growth theories using our introduced model named copula based seemingly unrelated quantile kink regression as a key tool in this work. We concentrate exclusively on the experience of Thailand and found that the growth models can prove their validities for the Thai economy through this experiment. 2018-09-05T03:35:13Z 2018-09-05T03:35:13Z 2017-02-01 Book Series 1860949X 2-s2.0-85012915946 10.1007/978-3-319-50742-2_32 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012915946&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57117
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
topic	Computer Science
spellingShingle	Computer Science Pathairat Pastpipatkul Paravee Maneejuk Songsak Sriboonchitta Testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression
description	© Springer International Publishing AG 2017. The distinct points of view about factors driving economic growth are introduced all the time in which some effectively useful suggestions then become the growth theories, which in turn lead to various researches on economic growth. This paper aims to examine the joint validity of the growth theories using our introduced model named copula based seemingly unrelated quantile kink regression as a key tool in this work. We concentrate exclusively on the experience of Thailand and found that the growth models can prove their validities for the Thai economy through this experiment.
format	Book Series
author	Pathairat Pastpipatkul Paravee Maneejuk Songsak Sriboonchitta
author_facet	Pathairat Pastpipatkul Paravee Maneejuk Songsak Sriboonchitta
author_sort	Pathairat Pastpipatkul
title	Testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression
title_short	Testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression
title_full	Testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression
title_fullStr	Testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression
title_full_unstemmed	Testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression
title_sort	testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression
publishDate	2018
url	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85012915946&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/57117
_version_	1681424818760581120

Testing the validity of economic growth theories using copula-based seemingly unrelated quantile kink regression

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