Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design In The Field

Monday, 23 January, 2017
The impacts of cash grants and access to credit are known to vary widely, but progress on targeting these services to high-ability, reliable entrepreneurs is so far limited. This paper by Hussam, Rigol and Roth (2016) reports on a field experiment in Maharashtra, India that assesses (1) whether community members have information about one another that can be used to identify high-ability microentrepreneurs, (2) whether organic incentives for community members to misreport their information obscure its value, and (3) whether simple techniques from mechanism design can be used to realign incentives for truthful reporting. The researchers asked 1,380 respondents to rank their entrepreneur peers on various metrics of business profitability and growth and entrepreneur characteristics. They also randomly distributed cash grants of about $100 to measure their marginal return to capital. They find that the information provided by community members is predictive of many key business and household characteristics including marginal return to capital. While on average the marginal return to capital is modest, preliminary estimates suggest that entrepreneurs given a community rank one standard deviation above the mean enjoy an 8.8% monthly marginal return to capital and those ranked two standard deviations above the mean enjoy a 13.9% monthly return. When respondents are told their reports influence the distribution of grants, the researchers find a considerable degree of misreporting in favor of family members and close friends, which substantially diminishes the value of reports. Finally, they find that monetary incentives for accuracy, eliciting reports in public, and cross-reporting techniques motivated by implementation theory all significantly improve the accuracy of reports.