Entrepreneurs in developing countries vary widely in their ability to use grant or loan financing to increase their businesses’ growth; often, only a small group are successful at doing so. This suggests substantial scope to increase targeting precision of credit and loan programs for small and medium-sized enterprises (SMEs), albeit a challenging endeavor, as even rigorous screening processes and sophisticated statistical models have not been very predictive of high-growth businesses in such programs. Recent research, however, points to a promising possibility of using information in the community to predict which entrepreneurs and firms have high returns to capital.
In this project, we aim to extend this literature by leveraging a randomised control trial in a large-scale business support program in Ghana to explore whether the networks of entrepreneurs who own small firms (sized 6-30 employees), including peers and other stakeholders such as suppliers, are an untapped source of information on marginal returns. For these market participants, we explore their ability to predict entrepreneurs’ returns, not only to capital but also to managerial consulting and a peer learning intervention. We also examine whether prediction accuracy varies in the short- vs longer-run.
