Modeling the Democratic Peace as a Kantian Selection Process

Computational modeling is used to improve our understanding of how the democratic peace unfolds as a historical process in time and space. Whereas most of the conventional literature interprets the phenomenon as a constant and universal law operating at the state level, the author follows Immanuel Kant and treats democratic cooperation as an emergent macroprocess. The current study explores three causal mechanisms. First, strategic tagging introduces a way for democracies to select out like-minded cooperators. Second, regime-sensitive alliances enable democratic states to defend the gains of cooperation. Third, liberal collective security complements the liberal alignments. Based on these processes, it is possible to “grow” cooperative outcomes in an inhospitable geopolitical environment. Because tagging alone is insufficient, alliances, and sometimes even collective security, are necessary to produce perpetual peace. Such outcomes are characterized by high levels of spatial clustering.

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