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Corruption in the Times of Pandemia

Jorge Gallego (), Mounu Prem and Juan Vargas

Working papers from Red Investigadores de Economía

Abstract: The public health crisis caused by the COVID-19 pandemic, coupled with the subsequent economic emergency and social turmoil, has pushed governments to substantially and swiftly increase spending. Because of the pressing nature of the crisis, public procurement rules and procedures have been relaxed in many places in order to expedite transactions. However, this may also create opportunities for 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 traditionally more prone to corruption react to the pandemic-led spending surge by using a larger proportion of discretionary non-competitive contracts and increasing their average value. This is especially so in the case of contracts to procure crisis-related goods and services. Our evidence suggests that large negative shocks that require fast and massive spending may increase corruption, thus at least partially offsetting the mitigating effects of this fiscal instrument.

Keywords: DiCorruption; COVID-19; Public procurement; Machine learning (search for similar items in EconPapers)
JEL-codes: H57 D73 I18 H75 (search for similar items in EconPapers)
Pages: 30
Date: 2020-05
New Economics Papers: this item is included in nep-big, nep-cmp, nep-hea and nep-lam
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Working Paper: Corruption in the times of pandemia (2020) Downloads
Working Paper: Corruption in the times of Pandemia (2020) Downloads
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