Network Structures of Power and COVID-19 Bailouts

Abstract

Using a database of 189,000+ Colombian firms, I study the effect of CEOs' centrality and political connections on access to PAEF ("Programa de Apoyo al Empleo Formal"), a government bailouts program launched during COVID-19 crisis to subsidy wages, and the ex-post economic efficiency of these factor. Natural Language Processing algorithms and complex networks measures are used to identify ownership and control links of economic elites based on their complete names, gauge prominence of CEOs and their closeness to politicians. I find that CEOs' centrality (not political connections) was positively associated with a higher probability of getting bailouts, but there were not differential effects of these factors in the impacts of the program. These results cannot be interpreted as evidence of any illegal behavior, but of special preferences during turbulent times after controlling by financial and geographical features.