Corruption is an endemic societal problem with profound implications in the development of nations. In combating this issue, cross-national evidence supporting the effectiveness of the rule of law seems at odds with poorly realized outcomes from reforms inspired in the academic literature. This paper provides an explanation for such contradiction. By building a computational approach, we develop three methodological novelties into the empirical study of corruption: (1) modeling government expenditure as a more adequate intervention variable than traditional indicators, (2) generating large within-country variation by means of bottom-up simulations (instead of cross-national data pooling), and (2) accounting for all possible interactions between covariates through a spillover network. Our estimates suggest that, the least developed a country is, the more difficult it is to find the right combination of policies that lead to reductions in corruption. We characterize this difficulty through a rugged landscape that governments navigate when changing the total budget size and the relative expenditure towards the rule of law. Importantly our method helps identifying the—country-specific—policy issues that complement the rule of law in the fight against corruption.

腐败是一个地方性的社会问题，对国家的发展具有深远的影响。在解决这个问题时，支持法治有效性的跨国证据似乎与学术文献中启发性的改革成果不佳相矛盾。本文为这种矛盾提供了解释。通过建立一种计算方法，我们将三种方法学的新颖性发展到腐败的实证研究中：（1）将政府支出建模为比传统指标更合适的干预变量，（2）通过自下而上的模拟产生较大的国内内部差异（而不是跨国数据池），以及（2）通过溢出网络说明协变量之间的所有可能相互作用。我们的估计表明，最不发达国家是 找到导致减少腐败的正确政策组合就更加困难。我们通过崎landscape的形势来形容这种困难，当政府改变总预算规模和相对法治的相对支出时，政府会驾驭这种崎landscape的形势。重要的是，我们的方法有助于确定针对国家/地区的政策问题，这些问题可在反腐败斗争中补充法治。