Analysis of Discrimination in Prime and Subprime Mortgage Markets
R. Glenn Hubbard
Columbia Business School - Finance and Economics; National Bureau of Economic Research (NBER)
Rutgers Business School
California State Polytechnic University, Pomona
November 22, 2011
This paper examines evidence of lending discrimination in prime and subprime mortgage markets in New Jersey. Existing single-equation studies of race-based discrimination in mortgage lending assume race is uncorrelated with the disturbance term in the loan denial regression. At the individual loan-level, we show that race is correlated with both observable and unobservable risk variables, leading to biased coefficient estimates. To mitigate this problem, we specify a system of equations and use a full information maximum likelihood (FIML) method that does not need to identify instrumental variables for system identification. We find that minorities are less likely to be rejected than whites in the subprime market. The individual loan-level FIML results are robust to using two-stage least squares when we examine discrimination at the neighborhood-level. We also find that the reduction in rejection rates to minority neighborhoods from 1996 to 2008 cannot be fully justified by risk, suggesting a relaxation of lending standards to minority neighborhoods. Using the methodology of Mian and Sufi , we also find evidence for strong credit supply effects.
Number of Pages in PDF File: 47
Keywords: subprime, discrimination, banking
JEL Classification: J15, G21working papers series
Date posted: December 22, 2011
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