FOREIGN AID AND GOVERNANCE IN A COMPLEX ADAPTIVE SYSTEM
Date
2020
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Abstract
Donors and foreign aid agencies have come to believe that ‘good governance’ facilitates economic and, by extension, overall development. However, their lack of success in identifying what initiatives are most effective in promoting better outcomes is discouraging. Conventional linear regression techniques are of limited help due to sample size considerations which hinder their ability to fully capture the complex effects of non-economic factors such as the culture and institutions in recipient nations. In this dissertation, I develop an agent-based model of governance and development which, combined with Monte Carlo simulations, overcomes the constraints of traditional econometric analysis. Using 83 development indicators and aid categories for 123 countries over 15 years, I demonstrate which aspects of governance contribute most to development and trace how this relationship changes across different host country contexts such as varying regimes, initial conditions, and budgetary resources. By examining scenarios based on current foreign aid practice, I determine that in aggregate, donors are pursuing incoherent policies in terms of good governance promotion. This model identifies how agencies can prioritize aid efforts to better promote good governance accounting for the contexts in which the programs must operate.