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We estimate the cost of cultural biases in high-stake economic decisions by comparing agents’ peer-to-peer lending choices with those the same agents make under the assistance of an automated robo-advisor. We first confirm substantial in-group vs. out-group and stereotypical discrimination, which are stronger for lenders who reside where historical cultural biases are higher. We then exploit our unique setting to document that cultural biases are costly: agents face 8% higher default rates on favored-group borrowers when unassisted. The returns they earn on favored groups increase by 7.3 percentage points when assisted. The high riskiness of the marginal borrowers from favorite groups largely explains the bad performance of culturally-biased choices. Because varying economic incentives do not reduce agents’ biases, inaccurate statistical discrimination—unconscious biased beliefs about borrowers’ quality—can explain our results better than taste-based discrimination.
In the aftermath of the financial crisis, the ECB has experienced an unprecedented deterioration in the level of trust. This raises the question as to what factors determine trust in central banking. We use a unique cross-country dataset which includes a rich set of socio-economic characteristics and supplement it with variables meant to reflect a country’s macroeconomic condition. We find that besides individual socio-economic characteristics, macroeconomic conditions play a crucial role in the trust-building process. Our results suggest that agents are boundedly rational in the trust-building process and that current ECB market operations may even be beneficial for trust in the ECB in the long-run.