Natural Resources, Governance, and Corruption

Abstract:

In efforts to explain the resource curse, researchers have examined the connection between the resource curse and national corruption. Because being relatively rich in natural resources may encourage rent-seeking behavior, some have speculated that the root cause of the curse might be corruption rather than an abundance of natural resources. The evidence is mixed. This article turns the question around and asks, given political, cultural, institutional, and economic influences, whether there is a statistical relationship between resource abundance and corruption. The focus is on the interaction of autocratic governance and resource abundance. The results suggest that the rents on natural resources alone are not a strong cause of corruption. There is evidence that natural resources combined with autocratic governance influences corruption but, after controlling for other influences the relationship is not strong and the results are sensitive to the way that corruption is operationalized. Meanwhile, several non-resource variables including, larger government, more competition, political stability, and business freedom do seem to reduce national corruption. The study is based on 125 nations using average 2012–2016 variable values.

Keywords::

• natural resources
• governance
• corruption
• institutions

JEL Classification Codes::

• B5
• H11
• K42
• D73
• L7
• O13

Notes

¹ The World Bank (n.d.) calculates rents as “the difference between the price of a commodity and the average cost of producing it” and defines total natural resource rents as “the sum of oil rents, natural gas rents, coal rents (hard and soft), mineral rents, and forest rents.”

² The consequences of corruption are generally thought to be negative (Bardhan 1997; Beck and Maher 1986; Lien 1986; Leys 1965; Leff 1964; Meon and Sekkat 2005; Meon and Weill 2010).

³ The case-studies of this research are Singapore, Hong Kong, Chile, Afghanistan, Swaziland, India, and Nigeria.

⁴ Dimant and Tosato 2017; Fan, Lin, and Treisman 2009; Fisman and Gatti 2002; Lambsdorff 2007; Myint 2000; Rose-Ackerman and Palifka 2016; Sandholtz and Koetzle 2000; Svensson 2005; Tanzi 1998; Treisman 2000, 2007.

Additional information

Notes on contributors

Leila Shadabi

Leila Shadabi is a recent doctoral graduate and Richard V. Adkisson is Professor Emeritus at New Mexico State University. This article is based on Dr. Shadabi's doctoral research

Richard V. Adkisson

Leila Shadabi is a recent doctoral graduate and Richard V. Adkisson is Professor Emeritus at New Mexico State University. This article is based on Dr. Shadabi's doctoral research