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Published in: Journal of Quantitative Economics 2/2019

28-10-2018 | Original Article

New Evidence on the Relationship Between Crude Oil Consumption and Economic Growth in the US: A Quantile Causality and Cointegration Approach

Authors: Amine Lahiani, Ramzi Benkraiem, Anthony Miloudi, Muhammad Shahbaz

Published in: Journal of Quantitative Economics | Issue 2/2019

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Abstract

This paper investigates the long-run and short-run relationship between WTI crude oil consumption and economic growth, covering the US economy for the period from 1955Q1 to 2016Q4. The Quantile ARDL approach developed by Cho et al. (2015) is applied to examine the long-run cointegrating relationship between the variables. Additionally, a quantile Granger causality test developed by Troster (2017) is also applied to examine the causal association between crude oil consumption and economic growth. The empirical evidence underscores the presence of nonlinearities and locational asymmetries. The growth hypothesis holds for the smallest quantiles, suggesting a unidirectional causality relationship running from oil consumption to economic growth. A feedback effect between oil consumption and economic growth is found for the medium quantiles. This empirical evidence has concrete implications for economists and energy policy makers.

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Footnotes
1
Recently, the US Energy Information Administration (EIA) includes renewable biofuels, such as ethanol and biodiesel in consumption of petroleum products. Liquids produced from natural gas are also included.
 
2
Readers seeking more information about US consumption of coal, oil, and other liquid products as a share of the total use of energy from 1949 to 2014 are referred to the US Energy Information Administration website.
 
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Metadata
Title
New Evidence on the Relationship Between Crude Oil Consumption and Economic Growth in the US: A Quantile Causality and Cointegration Approach
Authors
Amine Lahiani
Ramzi Benkraiem
Anthony Miloudi
Muhammad Shahbaz
Publication date
28-10-2018
Publisher
Springer India
Published in
Journal of Quantitative Economics / Issue 2/2019
Print ISSN: 0971-1554
Electronic ISSN: 2364-1045
DOI
https://doi.org/10.1007/s40953-018-0147-2

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