A Spatial Generalized Linear Mixed Model for Analyzing Efficiency of Foreign Aid Allocation
White, Philip, Candace Berrett, Shannon Neeley Tass, and Michael G. Findley. 2018. "A Spatial Generalized Linear Mixed Model for Analyzing Efficiency of Foreign Aid Allocation" The American Statistician 73(4): 385-399.
Abstract: The Open Aid Malawi initiative has collected an unprecedented database that identifies as much location-specific information as possible for each of over 2500 individual foreign aid donations to Malawi since 2003. The efficient use and distribution of such aid is important to donors and to Malawi citizens. However, because of individual donor goals and difficulty in tracking donor coordination it is difficult to determine whether aid allocation is efficient. We compare several Bayesian spatial generalized linear mixed models to relate aid allocation to various economic indicators within seven donation sectors. We find that the spatial gamma regression model best predicts current aid allocation. While we are cautious about making strong claims based on this exploratory study, we provide a methodology by which one could (i) evaluate the efficiency of aid allocation via a study of the locations of current aid allocation as compared to the need at those locations and (ii) come up with a strategy for efficient allocation of resources in conditions where there exists an ideal relationship between aid allocation and economic sectors.
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