The resource curse revisited: A Bayesian model averaging approach
Kerim Arin and
Elias Braunfels
Energy Economics, 2018, vol. 70, issue C, 170-178
Abstract:
The evidence for the effects of oil rents on growth is mixed, a result which can be explained with model uncertainty. We address the issue using Bayesian Model Averaging techniques and an updated cross-country data set for long-term growth in the period 1970–2014, including 91 countries and 54 potential growth determinants. We do not find empirical evidence for the existence of a “natural resource curse” in our sample. On the contrary, our results suggest a robust positive effect of oil rents on long-term economic growth. We then introduce interaction terms of oil rents with potential conditions under which oil dependency can lead to sub-standard growth. The results indicate that the positive effect of oil rents may be conditional on the quality of institutions. We test the robustness of our results using a panel data set and find neither a curse nor a positive effect of oil rents on short- to medium-run growth.
Keywords: Oil; Growth; Natural resource curse; Bayesian model averaging (search for similar items in EconPapers)
JEL-codes: O43 O47 Q32 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (69)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0140988318300069
Full text for ScienceDirect subscribers only
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:eee:eneeco:v:70:y:2018:i:c:p:170-178
DOI: 10.1016/j.eneco.2017.12.033
Access Statistics for this article
Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant
More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu (repec@elsevier.com).