Corruption in the Times of Pandemia

Serie

  • SocArXiv

Resumen

  • The public health and economic crisis caused by the COVID-19 pandemic has pushed governments to substantially and swiftly increase spending. Consequently, public procurement rules have been relaxed in many places to expedite transactions. However, this may also create opportunities for inefficiency and corruption. Using contract-level information on public spending from Colombia’s e-procurement platform, and a difference-in-differences identification strategy, we find that municipalities classified by a machine learning algorithm as more prone to corruption react to the spending surge by using a larger proportion of discretionary non-competitive contracts and increasing their average value, especially to procure crisis-related items. Additionally, in places that rank higher on our corruption scale, contracts signed during the emergency are more likely to have cost overruns, be awarded to campaign donors, and exhibit implementation inefficiencies. Our evidence suggests that these negative shocks may increase waste and corruption, and thus governments should bolster instances of monitoring and oversight.

fecha de publicación

  • 2020

Líneas de investigación

  • COVID-19
  • Corruption
  • Machine learning
  • Public procurement

Issue

  • js8by