Abstract
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 such 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 simulation (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 is to find the right combination of policies that leads to reductions in corruption. We characterize this difficulty through a rugged landscape that governments navigate through changes in their total budget and in 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.
Highlights
The World Bank asserts—in its 2017 World Development Report: Governance and the Law—that legal improvements to the rule of law have rarely succeed in achieving drastic reductions of corruption.4Baez-Camargo and Passas (2017) offer a reasonable explanation: the ineffectiveness of reforms to the rule of law may originates from inconsistencies between the de jure governance and the social norms that guide citizens and bureaucrats; that is to say, from the disregard of systemic effects
We find that improvements to the rule of law do not necessarily generate lower levels of corruption in all countries because, in the real world, (1) the ceteris paribus condition for other policy issues does not hold and (2) co-movements in other topics introduce effects that may oppose the traditional conduits of anti-corruption policies
Our computational approach has three key advantages over traditional econometric analyses: (1) it does not require pooling cross-national data, so the model is calibrated for each country individually; (2) it provides micro-foundations of a causal process that links expenditure, the rule of law, and corruption, and (3) it can control for the interactions that take place among a relatively high number of indicators
Summary
Public governance has become one of the main topics in the international development agenda. in spite of significant efforts to procure public governance through the rule of law, there seems to be a mismatch between the expectations from policy prescriptions and real-world outcomes. In this regard, the World Bank asserts—in its 2017 World Development Report: Governance and the Law—that legal improvements to the rule of law have rarely succeed in achieving drastic reductions of corruption.4Baez-Camargo and Passas (2017) offer a reasonable explanation: the ineffectiveness of reforms to the rule of law may originates from inconsistencies between the de jure governance and the social norms that guide citizens and bureaucrats; that is to say, from the disregard of systemic effects. In spite of significant efforts to procure public governance through the rule of law, there seems to be a mismatch between the expectations from policy prescriptions and real-world outcomes.. Our computational approach has three key advantages over traditional econometric analyses: (1) it does not require pooling cross-national data, so the model is calibrated for each country individually (i.e., it is consistent with the ‘context matters’ premise by incorporating country-specific characteristics); (2) it provides micro-foundations of a causal process that links expenditure, the rule of law, and corruption (i.e., it is more suitable to deal with problems of endogeneity and revere causation), and (3) it can control for the interactions that take place among a relatively high number of indicators (i.e., it is scalable with respect to the dimensions of the policy space).
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