Lisciandra et al. on Political Corruption

Maurizio Lisciandra, Antonio Miralles Asensio, and Fabio Monteforte (LUMSA University, Boston University - Department of Economics and University of Messina) have posted Search and Matching in Political Corruption (The B.E. Journal of Economic Analysis & Policy, 2023) on SSRN. Here is the abstract:

 

We develop a search and matching model to analyze the dynamics of the political corruption market. This model serves as a framework for evaluating the effectiveness of a set of anti-corruption policies. Contrary to expectations, conventional policies such as enhancing penalties or allocating greater resources to criminal investigations do not universally emerge as the most effective tools. For mitigating small-scale political corruption, the optimal strategy is to curtail corruption signaling, achieved, for instance, through enhancing transparency and competitiveness in the exchanges between entrepreneurs and politicians. For large-scale corruption, raising the costs of corruption signaling proves less effective as a deterrent compared to ex-post policy measures, such as improved detection effectiveness and harsher sanctions.