The Effect of Natural Resource Dependence on Energy Intensity (in Persian)
Ali Motavasseli () and
Mohammad Hossein Hassirian
Additional contact information
Ali Motavasseli: Institute for management and planning studies, Tehran, Iran
Mohammad Hossein Hassirian: Institute for management and planning studies, Tehran, Iran.
The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی و بودجه), 2021, vol. 26, issue 3, 29-47
Abstract:
This study investigates the effect of natural resource dependence on energy intensity of 75 countries between 1993 through 2015 in the aggregate level. Natural resource dependence is measured using four different proxies; the ratio of fuel export to GDP and total export, the ratio of mineral resource rent to GDP, and the ratio of natural resource rent to GDP. The effects of these proxies on energy intensity of countries are estimated using Arellano-Bond estimator. The results show a positive effect of subsoil resource dependence on energy intensity of countries. However, this effect is reversed once the forest resource rents are added to the measure of resource dependence. These effects are robust with respect to changes in weather and energy price proxies.
Keywords: Resource Curse; Energy Intensity; Arellano-Bond; Resource Abundance; Resource Dependence (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
http://jpbud.ir/article-1-2019-en.pdf (application/pdf)
http://jpbud.ir/article-1-2019-en.html (text/html)
http://jpbud.ir/article-1-2019-fa.html (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:auv:jipbud:v:26:y:2021:i:3:p:29-47
Access Statistics for this article
More articles in The Journal of Planning and Budgeting (٠صلنامه برنامه ریزی و بودجه) from Institute for Management and Planning studies Contact information at EDIRC.
Bibliographic data for series maintained by Nahid Jebeli ( this e-mail address is bad, please contact ).