Reducing Corruption Through Crowdsourcing

Inefficiency and corruption typify the delivery of public services in many developing countries. In addition, citizen access to transparent information on the specific problems encountered at government offices—which they could use to plan their attempts to acquire service—is rarely available, partly because of substantial personal risks individuals face for reporting corrupt behavior.
This project develops and pilots an application to crowdsource information on the performance of Indian government offices. The team evaluates the impact of an innovative crowd-­sourcing application generically called the Citizen Feedback Model (CFM), which aggregates and publicizes user-­reported data on corruption and the quality of service delivery at Indian government offices. For each government office in the study, the team creates a score based on citizens’ reports about the quality of service delivery. They then randomize the exposure of bureaucrats to their office’s score and assess impact on the quality of service delivery and bribe taking. They will also evaluate the impact of providing citizens with CFM scores via a mobile app and SMS messaging. The team hypothesizes that improving flows of information about the honesty of bureaucrats will influence the usage by citizens of specific offices and reduce the propensity of bureaucrats to ask for bribes.