Nathaniel Hendren, a professor of economics at MIT, presents research on credit access in the United States, focusing on how background factors such as race, parental income, and hometown influence individuals’ access to affordable credit. Using a unique dataset linking credit bureau, census, and tax data for about 25 million individuals, including an intergenerational sample, Hendren explores disparities in credit scores and credit access across different demographic groups. The study reveals significant gaps in credit scores by race, with Black Americans having substantially lower average scores compared to White and Asian Americans, and these disparities emerge early in life and persist throughout the life cycle.
The research further examines the intersection of race and parental income, showing that credit score gaps persist across all income levels, with Black individuals consistently having lower scores than White individuals at comparable parental income levels. Geographic variation also plays a role; for example, low-income White individuals growing up in different counties exhibit varying credit scores, highlighting the influence of local environments. Hendren emphasizes the persistence of credit scores over time, noting that early-life credit scores strongly predict future creditworthiness, unlike income which tends to show more mean reversion.
Hendren investigates potential algorithmic biases in credit scoring, focusing on two key concepts: calibration bias and balance bias. Calibration bias occurs when, at the same credit score, different racial groups have different probabilities of delinquency, with Black individuals more likely to default than White individuals at equivalent scores. Balance bias, on the other hand, looks at error rates across groups, revealing that Black individuals with no delinquency history still tend to have lower credit scores than their White counterparts. These opposing biases arise because of underlying group differences in repayment rates, making it impossible for credit scoring algorithms to be perfectly fair on both dimensions simultaneously.
The study also explores the determinants of repayment differences, finding that income and wealth alone do not fully explain the observed disparities. Instead, Hendren argues that childhood environments and social capital play a crucial role. Using a natural experiment approach based on age of exposure to different geographic locations, the research suggests that growing up in areas with better repayment outcomes causally improves individuals’ future credit behavior. This effect is robust even after controlling for family fixed effects, indicating that place-based childhood influences significantly shape financial behaviors in adulthood.
Finally, Hendren highlights the intergenerational transmission of creditworthiness, showing that parents’ credit scores strongly predict their children’s likelihood of delinquency, beyond what can be explained by income or wealth. The findings suggest that credit access disparities are deeply rooted in early-life conditions and social environments, contributing to persistent racial and economic inequalities. The research calls attention to the complex interplay between algorithmic fairness, socioeconomic factors, and policy interventions aimed at improving credit access and economic mobility.
