Big loans to small businesses: predicting winners and losers in an entrepreneurial lending experiment

Gharad Bryan, Dean Karlan and Adam Osman

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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 "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 existing practice leads to substantial misallocation. We argue that some entrepreneurs are overoptimistic 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; heterogenous treatment effects; psychometric data; small and medium enterprises (search for similar items in EconPapers)
JEL-codes: D24 M21 O12 O16 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2024-09-20
New Economics Papers: this item is included in nep-ban, nep-big, nep-cfn, nep-exp and nep-sbm
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Published in American Economic Review, 20, September, 2024, 114(9), pp. 2825 - 2860. ISSN: 0002-8282

Downloads: (external link)
http://eprints.lse.ac.uk/120637/ Open access version. (application/pdf)

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 (2022)
Working Paper: Big Loans to Small Businesses: Predicting Winners and Losers in an Entrepreneurial Lending Experiment (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:120637

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