Social capital predicts corruption risk in towns

TL;DR

This study investigates how the structure of social networks within towns influences corruption levels, finding that fragmented networks increase corruption risk while diverse external connections reduce it.

Contribution

It provides empirical evidence linking social capital characteristics to corruption risk at the town level using large-scale data from Hungary.

Findings

Fragmented social networks correlate with higher corruption risk.

Diverse external social connections are associated with lower corruption.

Social network structure influences local government transparency.

Abstract

Corruption is a social plague: gains accrue to small groups, while its costs are borne by everyone. Significant variation in its level between and within countries suggests a relationship between social structure and the prevalence of corruption, yet, large scale empirical studies thereof have been missing due to lack of data. In this paper we relate the structural characteristics of social capital of towns with corruption in their local governments. Using datasets from Hungary, we quantify corruption risk by suppressed competition and lack of transparency in the town's awarded public contracts. We characterize social capital using social network data from a popular online platform. Controlling for social, economic, and political factors, we find that settlements with fragmented social networks, indicating an excess of \textit{bonding social capital} have higher corruption risk and towns with more diverse external connectivity, suggesting a surplus of \textit{bridging social capital} are less exposed to corruption. We interpret fragmentation as fostering in-group favoritism and conformity, which increase corruption, while diversity facilitates impartiality in public life and stifles corruption.