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

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  • Gharad Bryan
  • Dean Karlan
  • Adam Osman

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.

Suggested Citation

  • Gharad Bryan & Dean Karlan & Adam Osman, 2024. "Big Loans to Small Businesses: Predicting Winners and Losers in an Entrepreneurial Lending Experiment," American Economic Review, American Economic Association, vol. 114(9), pages 2825-2860, September.
    • Handle: RePEc:aea:aecrev:v:114:y:2024:i:9:p:2825-60
    DOI: 10.1257/aer.20220616
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    18. repec:idb:brikps:82331 is not listed on IDEAS
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    Cited by:

    1. Masselus, Lise & Petrik, Christina & Ankel-Peters, Jörg, 2024. "Lost in the Design Space? Construct Validity in the Microfinance Literature," OSF Preprints nwp8k_v1, Center for Open Science.
    2. Oriana Bandiera & Robin Burgess & Erika Deserranno & Ricardo Morel & Imran Rasul & Munshi Sulaiman & Jack Thiemel, 2022. "Microfinance and Diversification," Economica, London School of Economics and Political Science, vol. 89(S1), pages 239-275, June.
    3. Masselus, Lise & Petrik, Christina & Ankel-Peters, Jörg, 2024. "Lost in the design space? Construct validity in the microfinance literature," Ruhr Economic Papers 1097, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    4. Alibhai,Aly Salman & Cassidy,Rachel Margaret & Goldstein,Markus P. & Papineni,Sreelakshmi, 2022. "Evening the Credit Score ? Impact of Psychometric Loan Appraisal for Women Entrepreneurs," Policy Research Working Paper Series 10230, The World Bank.

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    More about this item

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • L26 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Entrepreneurship
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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