EconPapers    
Economics at your fingertips  
 

Corruption and natural resource rents: evidence from quantile regression

Keisuke Okada and Sovannroeun Samreth

Applied Economics Letters, 2017, vol. 24, issue 20, 1490-1493

Abstract: This study examines the impacts of oil rents on corruption for 157 countries. While existing studies have primarily focused on average effects, we employ quantile regression to estimate the effects of natural resource abundance for different corruption levels. We consider the effects of natural resource rents, mainly oil rents and then compare them with those of total and non-oil natural resources rents. The estimation results show that, generally, more oil rents increase corruption. Specifically, impacts are larger in countries with an intermediate level of corruption and smaller in highly corrupt countries. While total resource rents increase corruption significantly, non-oil resource rents do not. This may be due to non-oil resource rent management (mainly inland) being more subject to public scrutiny. Non-oil natural resources are concentrated in the less-developed sub-Saharan African countries, where corruption is prevalent; therefore, the impacts of natural resource rents are unremarkable.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (28)

Downloads: (external link)
http://hdl.handle.net/10.1080/13504851.2017.1287849 (text/html)
Access to full text is restricted to subscribers.

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:taf:apeclt:v:24:y:2017:i:20:p:1490-1493

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20

DOI: 10.1080/13504851.2017.1287849

Access Statistics for this article

Applied Economics Letters is currently edited by Anita Phillips

More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-31
Handle: RePEc:taf:apeclt:v:24:y:2017:i:20:p:1490-1493