Entrepreneurial motivation and business performance: evidence from a French Microfinance Institution

Abstract

This article examines the link between entrepreneurial motivation and business performance in the French microfinance context. Using hand-collected data on business microcredits from a Microfinance Institution (MFI), we provide an indirect measure of entrepreneurial success through loan repayment performance. Controlling for the endogeneity of entrepreneurial motivation in a bivariate probit model, we find that “necessity entrepreneurs” are more likely to have difficulty repaying their microcredits than “opportunity entrepreneurs”. However, type of motivation does not appear to make a difference to business survival. We test for the robustness of our results using parametric duration models and show that necessity entrepreneurs experience difficulties in loan repayment earlier than their opportunity counterparts, corroborating our initial findings. Our results are also robust to a sharper analysis of motivation, focusing on unemployment (on the necessity side) and non-pecuniary benefits from success (on the opportunity side).

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Notes

  1. 1.

    Sometimes, microfinance institutions do not differentiate between two types of products, since the boundary between the business and the household is not clearly drawn.

  2. 2.

    In France in the first semester of 2002, almost 36% of all business start-ups were (partly) financed by commercial bank loans (source: authors’ own computations using data from the French National Institute of Statistics and Economic Studies). Furthermore, commercial banks are the main providers of small-business finance, according to Berger and Udell (2002).

  3. 3.

    Reed et al. (2014) report that MFIs in the industrialized world represent 4.4% of total MFIs reporting to the Microcredit Summit Campaign, serving less then 3% of microfinance clients.

  4. 4.

    The European Commission defines the microcredit as a loan of up to EUR 25,000 tailored for micro-enterprises employing less than 10 people (91% of all European firms), and unemployed or inactive people who want to go into self-employment but do not have access to traditional banking services.

  5. 5.

    Kariv and Coleman (2015) show that both types of entrepreneurs are likely to request small loans.

  6. 6.

    Still, the abundance of subsidies may explain the scarcity of complementary financial products such as microsavings (Cozarenco et al. 2016).

  7. 7.

    At the European level, the European Investment Fund offers guarantees to microfinance providers through the Employment and Social Innovation (EaSI) Guarantee Instrument. The guarantee rate is up to 80%. At the national level, France Active Guarantee (FAG) offers guarantees up to 70% of the amount of business microcredits and Fonds de Cohésion Sociale and Caritas up to 50% of the amount of personal microcredits. For all these initiatives, cap loss rates apply.

  8. 8.

    It can also be linked to the notion of passion, which may be related to entrepreneurial motivation (Dalborg and Wincent 2015).

  9. 9.

    To that extent, the theoretical predictions concerning the link between entrepreneurial motivation and business performance seem to be ambiguous. We formalize this argument in the working paper version of this paper (Bourlès and Cozarenco 2017), in which we adapt the canonical model of Tirole (2006) to account for microcredit specificity and differences between necessity and opportunity entrepreneurs. We show that the probability of success of a business increases in the entrepreneurs’ non-pecuniary benefit from success and decreases in their external opportunity. This result suggests an ambiguous effect of entrepreneurial motivation on business survival.

  10. 10.

    This can moreover be combined with bootstrapping by the necessity entrepreneurs (Jonsson and Lindbergh 2013).

  11. 11.

    We thank an anonymous referee for pointing out this issue.

  12. 12.

    As a consequence, the MFI does not provide dynamic incentives through progressive lending (Armendáriz and Morduch 2010).

  13. 13.

    The so-called honor loans are subsidized personal loans granted by the French government to start or buy out a business. Their size varies between EUR 2000 and 50,000.

  14. 14.

    The 3-year survival rate for businesses created in 2010 in PACA region. Source: the French National Institute of Statistics and Economic Studies website, accessed on June 14, 2016.

  15. 15.

    We thank an anonymous referee for pointing out this issue.

  16. 16.

    Taylor (1996) suggests a non-linear effect of age on self-employed earnings.

  17. 17.

    Mimicking a two-step procedure would not lead to consistent parameter estimations, according to Wooldridge (2010).

  18. 18.

    Given the non-linear relationship, the effect would become negative for individuals older than 80 years old. However, we do not have such observations in our data set.

  19. 19.

    These public partners generally also provide business development services, explaining the high correlation we observe between the provision of business development services and our “other debts” variable. As the effects of business development services on our dependent variables are less significant than the ones of “other debt,” the latter variable seems to be a better control.

  20. 20.

    After 24 months, the sample size becomes too small to trigger robust results.

  21. 21.

    This means that the likelihood to experience repayment problems was 0.48 higher for necessity entrepreneurs than for opportunity entrepreneurs in the subsample in which we delete all the observation with at least three late payments during the first year after credit disbursement.

  22. 22.

    The drop at m = 12 corresponds to the subsample in which we drop the the highest number of observations.

  23. 23.

    The 95% confidence interval does not show significant difference between coefficients.

  24. 24.

    We additionally use the Cox proportional hazards model (Cox 1992), which is a semi-parametric model, since the proportionality assumption cannot be rejected in our data (Schoenfeld 1981). This model yields similar results. They are available from the authors upon request.

  25. 25.

    We thank an anonymous referee for pointing out this issue.

  26. 26.

    These probabilities of default appear particularly large, especially for the microfinance industry where MFIs generally boast very high repayment rates (Armendáriz and Morduch 2010). However, they are generated by our conservative approach assuming that all the borrowers experiencing repayment problems will actually not repay their loan. It is worth reminding that in our sample 43% of individuals had at least three unpaid installments in their credit history.

  27. 27.

    According to Brabant et al. (2007), the operating cost per borrower (including the application analysis, credit disbursement and follow-up but excluding non-financial services) varies between EUR 735 and EUR 500 per year for licensed MFIs in France.

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Acknowledgements

The authors would like to thank Mohamed Belhaj, Olivier Chanel, Dominique Henriet, Xavier Joutard, Frank Lasch, Bernard Sinclair-Desgagné, Roy Thurik, and Peter van der Zwan for useful comments and discussions; and Marjorie Sweetko for English language revision. The authors are grateful to Colette Grunenberger for research assistance.

Funding

Anastasia Cozarenco benefited from LabEx “Entrepreneurship” (University of Montpellier, France) funding. This “laboratory of excellence” is funded by the French government in recognition of high-level research initiatives in the human and natural sciences.

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Correspondence to Renaud Bourlès.

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Bourlès, R., Cozarenco, A. Entrepreneurial motivation and business performance: evidence from a French Microfinance Institution. Small Bus Econ 51, 943–963 (2018). https://doi.org/10.1007/s11187-017-9961-8

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Keywords

  • Opportunity and necessity entrepreneurs
  • Business microcredit
  • Loan repayment
  • Business survival

JEL Classification

  • C30
  • C41
  • G21
  • L26
  • M13