Working Paper: CEPR ID: DP14340
Authors: Michelle Brock; Ralph de Haas
Abstract: We implement a lab-in-the-field experiment with 334 Turkish loan officers to document gender discrimination in small business lending and to unpack the mechanisms at play. Each officer reviews multiple real-life loan applications in which we randomize the applicant's gender. While unconditional approval rates are the same for male and female applicants, loan officers are 26 percent more likely to require a guarantor when we present the same application as coming from a female instead of a male entrepreneur. A causal forest algorithm to estimate heterogeneous treatment effects reveals that this discrimination is strongly concentrated among young, inexperienced, and gender-biased loan officers. Discrimination mainly affects female loan applicants in male-dominated industries, indicating how financial frictionscan perpetuate entrepreneurial gender segregation across sectors.
Keywords: gender bias; bank credit; implicit association test; lab-in-the-field; causal forest
JEL Codes: D81; D83; D91; G21; G41; L26
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Loan officer gender discrimination (J79) | Guarantor requirement (H81) |
| Loan officer characteristics (age, experience, biases) (G51) | Loan officer gender discrimination (J79) |
| Guarantor requirement (H81) | Entrepreneurial gender segregation (L26) |
| Loan officer gender discrimination (J79) | Female applicants' creditworthiness perception (G51) |