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Business Training Allocation and Credit Scoring: Theory and Evidence from Microcredit in France

Author

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  • Renaud Bourlès

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Anastasia Cozarenco

    (CERMi - Centre for European Research in Microfinance, ULB - Université libre de Bruxelles = Free University of Brussels, SBS-EM, Centre Emile Bernheim - ULB - Université libre de Bruxelles = Free University of Brussels - SBS-EM)

  • Dominique Henriet

    (GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Xavier Joutard

    (UL2 - Université Lumière - Lyon 2, GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique)

Abstract

The microcredit market, where inexperienced micro-borrowers meet experienced microfinance institutions (MFIs), is subject to reversed asymmetric information. Thus, MFIs' choices can shape borrowers' beliefs and their behavior. We analyze how this mechanism may influence microfinance institution decisions to allocate business training. By means of a theoretical model, we show that superior information can lead the MFI not to train (or to train less) riskier borrowers. We then investigate whether this mechanism is empirically relevant, using data from a French MFI. Confirming our theoretical reasoning, we find a non-monotonic relationship between the MFI's decision to train and the risk that micro-borrowers represent.

Suggested Citation

  • Renaud Bourlès & Anastasia Cozarenco & Dominique Henriet & Xavier Joutard, 2015. "Business Training Allocation and Credit Scoring: Theory and Evidence from Microcredit in France," Working Papers halshs-01171949, HAL.
    • Handle: RePEc:hal:wpaper:halshs-01171949
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01171949v2
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    References listed on IDEAS

    as
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    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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