All good things go together
One of the central challenges of studying state development is that its closely related to many other things. This video illustrates how key global economic and political variables are interrelated and discusses the difficulty of identifying cause and effect in state development.
When studying the state, we can see that all good things go together. States that function effectively – whether measured by high World Bank governance scores or low Corruption Perception scores – these countries also have higher levels of economic development, lower levels of political violence, and often are more democratic. The combination of rule of law and economic opportunity produce higher levels of health, education and other measures of quality of life, like access to clean water.
Authors Timothy Besley and Torsten Persson in their book Pillars of Prosperity called these relationships “development clusters.” In development clusters, wealth, capacity, and stability on the one hand and poverty, corruption, and violence on the other hand reinforce each other, creating virtuous circles for some countries and vicious cycles for the rest.
The gaps between rich and poor in state development and stability are further complicated by regional disparities, with the richest countries of the “Global North” having better governance and quality of life and the countries of the Global South facing lower levels of both political and economic development. And the gap between rich and poor has more than tripled over the past fifty years.
To identify ways countries can escape the low development trap, it would be helpful to better understand what causes what, but these factors are so interrelated it can be difficult.
For example, as Susan Rose-Ackerman and Bonnie Palifka describe in Corruption and Government, high levels of corruption in a country depress its economic output by making it harder start businesses, among other things. Low development then fosters even more corruption, in part by keeping salaries for public officials low (among other things).
How do we start to untangle this web and identify causes?
First, while the famous phrase that “correlation does not equal causation” is true (just because two variables are related to each other doesn’t mean that one causes the other), it is also true that variables need to be related for one of them to cause the other. The readings by Persson et al and McDonnell both do this – they go beyond the broad generalizations about relationships between poverty and corruption to identify specific factors that are common to people who work in high corruption vs. high capacity bureaucracies. Peter Evans in Embedded Autonomy does this as well, pointing to the importance of strong ties between bureaucrats and firms in countries that promote economic development.
The next question we ask about causality is, which came first? Causes have to happen before the things they effect (at least in politics), but this can be difficult in a world where political attitudes and institutions develop slowly over time. When two things are happening simultaneously – like corruption and growth – we have a chicken and the egg problem.
The authors we read this week and next resolve this problem by something called process-tracing – describing the path that a country took from a cause (like initial political institutions) to an outcome (economic prosperity). By specifying each step the country took along the way, they can start to disentangle the threads of the relationship.