Can corruption indices lead to statistical discrimination? Experimental evidence from a within-country setting

Abstract Corruption indices can provide valuable insights into varying levels of misconduct across regions, but they may also encourage statistical discrimination by transferring group-level attributes onto individuals. This paper examines how information about within-country regional corruption affects perceptions and trust. Using a pre-registered online experiment, we matched participants with partners from three Russian regions that differ in their corruption rankings. Participants estimated how many individuals from each region would report a favorable outcome in a coin toss, and decided how much to trust them as first movers in a trust game. Knowing the corruption indices not only led participants to view individuals from more corrupt regions as more dishonest and less trustworthy, but this information also prompted them to see those from less corrupt regions as more honest and trustworthy. This widened the perceived differences in honesty and trustworthiness between residents from and less corrupt regions. When allowed to choose their sources of information, about half of the participants opted to view the corruption index, further magnifying these perception gaps. Our findings highlight how group-level corruption data can influence individual-level interactions and foster statistical discrimination.