Sex differences in access to a small enterprise development fund in Peru

Buvinić, Mayra; Berger, Marguerite

doi:10.1016/0305-750x(90)90018-s

Cited by 49 publications

(32 citation statements)

References 3 publications

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“…Concerning the borrower's gender, the result shows that men make up the largest share of this Tunisian MFI's clients. This confirms results of other studies showing that women face more difficulties than men in terms of accessing credit (Buvinic and Berger, 1990;Godquin, 2004). It is also worth noting that the default frequency is slightly higher for the unmarried borrowers than for the married ones.…”

Section: Univariate Analysissupporting

confidence: 92%

Can Credit-Scoring Models Effectively Predict Microloans Default? Statistical Evidence from the Tunisian Microfinance Bank

Baklouti¹,

Bouri²

2014

Global Credit Review

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Section: Univariate Analysissupporting

confidence: 92%

Can Credit-Scoring Models Effectively Predict Microloans Default? Statistical Evidence from the Tunisian Microfinance Bank

Baklouti¹,

Bouri²

2014

Global Credit Review

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“…The literature has also explored the reasons behind such a gender gap. Buvinic and Berger (1990) find that female entrepreneurs struggle more with loan applications, while Lusardi and Tufano (2009) find lower overall financial literacy among women. However, behavioral differences might also be important, leading to taste rather than statistical discrimination (Beck, Behr and Madestam, 2011).…”

Section: Introductionmentioning

confidence: 99%

Access to Finance in Sub-Saharan Africa: Is There a Gender Gap?

2013

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract: This paper assesses whether there is a gender gap in the use of financial services by businesses and individuals in Sub-Saharan Africa. We show the existence of an unconditional gender gap, as the absolute use of financial services is higher for males than females. However, when key observable characteristics of the enterprises or individuals are taken into account the gender gap disappears. In the case of enterprises, we explain our finding with differences in key characteristics and a poential selection bias -females owned ones are smaller, younger and less likely to run sole proprietorships than men, furthermore these are more likely to innovate and more prevalent in sectors that tend to rely less on access to external finance. In the case of individuals, the lower use of formal financial services by women can be explained by gender gaps in other dimensions related to the use of financial services, such as their lower level of income and education, and by their household and employment status. Exploring the reasons for not applying or being unbanked shows that traditional bank barriers such as higher interest rates, lack of formal income or job are more binding for females than for males. This suggests that, conditional on their observable characteristics, females do not have inherently lower demand nor that there is taste-based discrimination. Permanent repository linkJEL Classification: G21; J16

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“…Additional evidence on gender discrimination in Italian small business lending is provided by Bellucci, Borisov and Zazzaro (2009). Buvinic andBerger (1990) andFletschner (2009) show that women keep being more credit-rationed than men by MFIs.…”

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confidence: 99%

Microfinance and Gender: Is There a Glass Ceiling on Loan Size?

Agier¹,

Szafarz²

2013

World Development

189

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Microfinance institutions serve a majority of female borrowers. But do men and women benefit from same credit conditions? This paper investigates this issue by presenting an original model and testing its predictions on an exceptional database including 34,000 loan applications from a Brazilian microfinance institution over an eleven-year period. The model considers a lender that offers standardized loan contracts with a fixed interest rate, which is common practice in microfinance. It demonstrates that biased loan attribution may lead to three different outcomes, depending on the bias intensity: 1) denial of all applications from a given group, 2) a "glass ceiling" effect, namely loan downsizing of the largest projects from a given group, or 3) no impact. The empirical analysis detects no gender bias in approval rate, but uncovers a glass ceiling effect hurting female applicants. Moreover, this effect is insensitive to the credit officer's gender. In conclusion, the good news is that the microfinance practice does ensure a fair access to credit. The bad news is the presence of a glass ceiling faced by female entrepreneurs with larger projects. AbstractMicronance institutions serve a majority of female borrowers. But do men and women benet from same credit conditions ? This paper investigates this issue by presenting an original model and testing its predictions on an exceptional database including 34,000 loan applications from a Brazilian micronance institution over an eleven-year period. The model considers a lender that oers standardized loan contracts with a xed interest rate, which is common practice in micronance. It demonstrates that biased loan attribution may lead to three dierent outcomes, depending on the bias intensity: 1) denial of all applications from a given group, 2) a glass ceiling eect, namely loan downsizing of the largest projects from a given group, or 3) no impact. The empirical analysis detects no gender bias in approval rate, but uncovers a glass ceiling eect hurting female applicants. Moreover, this eect is insensitive to the credit ocer's gender. In conclusion, the good news is that the micronance practice does ensure a fair access to credit. The bad news is the presence of a glass ceiling faced by female entrepreneurs with larger projects.

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Sex differences in access to a small enterprise development fund in Peru

Cited by 49 publications

References 3 publications

Can Credit-Scoring Models Effectively Predict Microloans Default? Statistical Evidence from the Tunisian Microfinance Bank

Can Credit-Scoring Models Effectively Predict Microloans Default? Statistical Evidence from the Tunisian Microfinance Bank

Access to Finance in Sub-Saharan Africa: Is There a Gender Gap?

Microfinance and Gender: Is There a Glass Ceiling on Loan Size?

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