Journal of Theoretical Politics

Most writers on political science methods seem to suggest that explanation means causal explanation. Certainly, many explanations in the political sciences are causal. However, natural science often provides non-causal explanations, while non-causal explanations are recognized by philosophers of science. Causal inference, in itself, is not a causal explanation; it explains alongside theory. In this paper, we defend explanatory pluralism, arguing that many important explanations in political science are not causal in nature. We identify two important types of non-causal explanation – constitutive explanation (CE) and explanation by constraint (EC) – providing examples from the political sciences literature. We conclude by outlining what we believe non-causal explanation can contribute to political science.

I formally characterize three objectives of causally-oriented empirical research: identification, explanation, and generalization. I then analyze some logical relationships between them. Loosely, causal identification is measurability of treatment effects from data; causal explanation occurs when a unique theoretical model is consistent with observed data; and causal generalization is application of a causal model from one setting to another. I show that explanation implies identification but not vice versa; that explanation is possible even if no pairwise causal effects are identified for any variables; and that improvement in identification also improves explanation. Causal generalization requires a known mapping of causal models across cases based on the background or contextual characteristics of each case. Necessary conditions to recover this mapping empirically are stringent and require theoretical commitments. Overall the results show a strong connection between theoretical models and causal inference.

Despite expectations that large-scale anti-corruption campaigns would enhance governance, they often lead to bureaucratic inefficiencies and economic decline, as seen in China and Vietnam. This paper examines these purges as a top-down accountability mechanism in authoritarian regimes. Through a game-theoretic model, we demonstrate that systemic corruption traps rulers in a persistent trade-off between social productivity and political stability. Whether rulers incentivize informants, distinguish between ideologically congruent and non-congruent agents, prioritize profit or survival, or base purges on corruption or performance, the core dilemma remains—and often becomes more intricate. Our findings challenge the effectiveness of mass purges as a sustainable governance strategy.