This thesis aims to properly test three hypotheses derived from
existing political theories about distributive politics by employing
Bayesian multilevel modeling. The specific case of
intergovernmental grants, the Special Local Allocation Grants,
in Korea at two nested levels (districts and provinces) from 2005 to
2006, verifies that unlike classical regression models, the Bayesian
multilevel regression model can capture regional variations in the
allocation and utilize substantive knowledge from previous
literature. In particular, the model finds that a significant positive
association between the amount of intergovernmental grants and being
an electorally unstable province in a broad region affected by
regional voting behavior (i.e., Electorally Unstable Provinces Hypothesis) even
after controlling for the need-based criteria. It justifies the chief
executive's strategy to target an electorally unstable [swing]
province even within a supporter region because people in the
electorally stable province are strongly affiliated with a regional
(or ethnic) identity so that they may be satisfied with the allocation
of grants even if they are not the main beneficiaries. Thus, while the
allocation is concentrated on core supporters that are well known
quantities at the district level, the allocation at the higher level
can be decided by the efficient targeting strategy. This finding provides a
strong implication for decentralized democratic governments under
circumstances where significant regionally (or ethnically)
affiliated-voting is observed. In Korea, the disproportional
allocations of central government grants to electorally unstable
province within its supporter region (Jeolla) from 2005 to 2008 helped
the government party to increase its vote share in the unstable
province (Jeonam) by 20% in 2008. The vote share in the electorally stable province (Jeonbuk) reduced only by 2.9\% in comparison with that in the previous election. It was a remarkable outcome, considering the the government party was defeated by the wide margin 13% nationwide and experienced a swing against it by 20.3% across the country in the election.