Let's continue to discuss the resource curse. In previous posts about the curse of resources we came to an important point: perhaps the problem is not the resource wealth itself, but how much the economy depends on it and how exactly we measure this wealth in the first place. The next step in this discussion was taken by the Mehlom-Mona-Torvik trio in their 2006 paper "Institutions and the Resource Curse". They started from a simple observation: among resource-rich countries there are both clear losers and fairly successful countries. What does the result depend on?
Their answer can be summarized as follows: the impact of resources on the economy depends on the quality of the institutions. The authors present a distinction between producer-friendly institutions (encouraging the development of entrepreneurship) and grabber-friendly institutions (encouraging the pursuit of rent). In the first case, it is more profitable for the entrepreneur to engage in production and create value; And secondly, fight for access to existing rent.
If the institutions are weak (the property is poorly protected, corruption flourishes, the bureaucracy does not work well), then the wealth of resources makes the struggle over the rent profitable and contributes to the flow of entrepreneurial efforts from productive activity to the rent struggle itself. If the institutions are well designed, this effect does not occur, and resources are more likely to complete productive entrepreneurial activity.
It is worth emphasizing that the authors do not claim that resources corrupt institutions, which then inhibit growth. They show that the same institutions that developed in the country during the resource boom determine how rent will be invested. That is, natural resources become a kind of "quality test" of established institutions.
In the empirical part, the authors take almost the same data as Zacks & Warner: 87 countries, GDP growth per capita in 1965–1990, the share of primary exports in GDP as an indicator of resource allocation and a standard set of control variables.