DP16573 Big Loans to Small Businesses: Predicting Winners and Losers in an Entrepreneurial Lending Experiment

Author(s):	Gharad Bryan, Dean S. Karlan, Adam Osman
Publication Date:	September 2021
Date Revised:	May 2022
Keyword(s):	Enterprise credit, entrepreneurship, Heterogeneous Treatment Effects, Psychometric data, Small and medium enterprises
JEL(s):	D22, D24, L26, M21, O12, O16
Programme Areas:	Labour Economics, Development Economics
Link to this Page:	cepr.org/active/publications/discussion_papers/dp.php?dpno=16573

We experimentally study the impact of substantially larger enterprise loans in Egypt. Larger loans generate small average impacts, but machine learning using psychometric data reveals that "top-performers" (those with the highest predicted treatment effects) substantially increase profits, while profits drop for poor-performers. The large differences imply that lender credit allocation decisions matter for aggregate income, yet we find that existing practice leads to substantial misallocation. We argue that some entrepreneurs are over-optimistic and squander the opportunities presented by larger loans by taking on too much risk, and show the promise of allocations based on entrepreneurial type relative to firm characteristics.