  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. Ensuring efficient
use and distribution of that aid is important to donors and to Malawi citizens.
However, because of individual donor goals and difficulty in tracking donor
coordination, determining presence or absence of efficient aid allocation is
difficult. 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. Using this model, first we use inferences on coefficients to
examine whether or not there is evidence of efficient aid allocation within
each sector. Second, we use this model to determine a more efficient aid
allocation scenario and compare this scenario to the current allocation to
provide insight for future aid donations.
