Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We implement a lab-in-the-field experiment with 334 Turkish loan officers to document gender discrimination in small business lending and unpack mechanisms. Officers review multiple real-life loan applications in which we randomize applicant gender. While unconditional approval rates are the same, 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 discrimination is concentrated among young, inexperienced, and gender-biased officers. Discrimination mainly affects female loan applicants in male-dominated industries, indicating how financial frictions can perpetuate entrepreneurial gender segregation across sectors.