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Working Paper
How Much Does Racial Bias Affect Mortgage Lending? Evidence from Human and Algorithmic Credit Decisions
We assess racial discrimination in mortgage approvals using new data on mortgage applications. Minority applicants tend to have significantly lower credit scores, higher leverage, and are less likely than white applicants to receive algorithmic approval from race-blind government automated underwriting systems (AUS). Observable applicant- risk factors explain most of the racial disparities in lender denials. Further, we exploit the AUS data to show there are risk factors we do not directly observe, and our analysis indicates that these factors explain at least some of the residual 1-2 ...
Working Paper
Credit Score Doctors
We study how the existence of cutoffs in credit scores affects the behavior of homebuyers. Borrowers are more likely to purchase houses after their credit scores cross over a cutoff to qualify them for a higher credit score bin. However, the credit accounts of these individuals (crossover group) are more likely to become delinquent within four years following home purchases than the accounts of those who had stayed in the same bin (non-crossover group). The effect is not only concentrated in subprime bins, but in other bins as well. It is neither limited to pre-crisis period nor curtailed by ...
Working Paper
The Impact of Missed Payments and Foreclosures on Credit Scores
This paper debunks the common perception that ?foreclosure will ruin your credit score.? Using individual-level data from a credit bureau matched with loan-level mortgage data, it is estimated that the very first missed mortgage payment leads to the biggest reduction in credit scores. The effects of subsequent loan impairments are increasingly muted. Post-delinquency foreclosures have only a minimal effect on credit scores. Moreover, credit scores improve substantially a year after borrowers experience 90-day delinquency or foreclosure. The data supports one possible explanation of this ...
Working Paper
The Unintended Consequences of Employer Credit Check Bans for Labor Markets
Over the last 15 years, 11 states have restricted employers’ access to the credit reports of job applicants. We estimate that county-level job vacancies have fallen by 5.5 percent in occupations affected by these laws relative to exempt occupations in the same counties and national-level vacancies for the same occupations. Cross-sectional heterogeneity suggests that employers use credit reports as signals of a worker’s ability to perform the job: vacancies fall more in counties with a large share of subprime residents, while they fall less for occupations with other commonly available ...
Working Paper
How Much Does Racial Bias Affect Mortgage Lending? Evidence from Human and Algorithmic Credit Decisions
We assess racial discrimination in mortgage approvals using new data on mortgage applications. Minority applicants tend to have significantly lower credit scores, higher leverage, and are less likely than white applicants to receive algorithmic approval from race-blind government automated underwriting systems (AUS). Observable applicant- risk factors explain most of the racial disparities in lender denials. Further, we exploit the AUS data to show there are risk factors we do not directly observe, and our analysis indicates that these factors explain at least some of the residual 1-2 ...
Working Paper
How Much Does Racial Bias Affect Mortgage Lending? Evidence from Human and Algorithmic Credit Decisions
We assess racial discrimination in mortgage approvals using new data on mortgage applications. Minority applicants tend to have significantly lower credit scores, higher leverage, and are less likely than white applicants to receive algorithmic approval from race-blind government automated underwriting systems (AUS). Observable applicant- risk factors explain most of the racial disparities in lender denials. Further, we exploit the AUS data to show there are risk factors we do not directly observe, and our analysis indicates that these factors explain at least some of the residual 1-2 ...
Working Paper
How Much Does Racial Bias Affect Mortgage Lending? Evidence from Human and Algorithmic Credit Decisions
We assess racial discrimination in mortgage approvals using new data on mortgage applications. Minority applicants tend to have significantly lower credit scores, higher leverage, and are less likely than white applicants to receive algorithmic approval from race-blind government automated underwriting systems (AUS). Observable applicant- risk factors explain most of the racial disparities in lender denials. Further, we exploit the AUS data to show there are risk factors we do not directly observe, and our analysis indicates that these factors explain at least some of the residual 1-2 ...