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

Gharad Bryan, Dean Karlan and Adam Osman

No 16573, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: We experimentally study the impact of relatively large 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.

Keywords: entrepreneurship; Enterprise credit; Heterogeneous treatment effects; Psychometric data; Small and medium enterprises (search for similar items in EconPapers)
JEL-codes: D22 D24 L26 M21 O12 O16 (search for similar items in EconPapers)
Date: 2022-05
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Related works:
Journal Article: Big Loans to Small Businesses: Predicting Winners and Losers in an Entrepreneurial Lending Experiment (2024)
Working Paper: Big loans to small businesses: predicting winners and losers in an entrepreneurial lending experiment (2024)
Working Paper: Big Loans to Small Businesses: Predicting Winners and Losers in an Entrepreneurial Lending Experiment (2021)
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