"The dynamic relationship between energy consumption and economic growth in China "

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dc.contributor.advisor
dc.contributor.author Rathnayaka, R.M. Kapila Tharanga
dc.contributor.author Seneviratna, D. M. K. N.
dc.contributor.author Long, Wei
dc.date.accessioned 2023-01-31T08:44:17Z
dc.date.available 2023-01-31T08:44:17Z
dc.date.issued 2018
dc.identifier.citation R. M. Kapila Tharanga Rathnayaka, D. M. K. N. Seneviratna & Wei Long (2018) The dynamic relationship between energy consumption and economic growth in China, Energy Sources, Part B: Economics, Planning, and Policy, 13:5, 264-268, DOI: 10.1080/15567249.2015.1084402
dc.identifier.issn 1556-7249
dc.identifier.uri http://ir.lib.ruh.ac.lk/xmlui/handle/iruor/10560
dc.description.abstract Economic growth of is mainly associated with technical changes as well as energy consumption of a nation. The causality between energy consumption and economic growth has created much more attention in the literature. With advanced technology and automated comfort life, the requirement of energy demand has been increasing rapidly. The goal of this study is to examine the causal relationship between energy consumption and economic growth in China over the period of 1980 – 2013. As a first step, stationary properties of the selected variables were tested using unit root test statistics. Next, the Johansen co-integration with Vector error correction model (VECM) was applied to examine the dynamic links between among the variables. The result confirmed a long run bidirectional causal relation running between energy consumption and economic growth. Furthermore, results make a significant contribution to policy makers to open up a new direction to the development of energy sector in China. en_US
dc.language.iso en en_US
dc.publisher Taylor & Francis en_US
dc.subject Economic Growth en_US
dc.subject Energy Consumption en_US
dc.subject Vector error correction model en_US
dc.title "The dynamic relationship between energy consumption and economic growth in China " en_US
dc.type Article en_US


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