Matt Blackwell

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We address a major discrepancy in matching methods for causal inference in observational data. Since these data are typically plentiful, the goal of matching is to reduce bias and only secondarily to keep variance low. However, most matching methods seem designed for the opposite problem, guaranteeing sample size ex ante but limiting bias by controlling for(More)
The recent subprime mortgage crisis has brought to the forefront the possibility of discriminatory lending on the basis of race or gender. I explore these claims using approximately 10 million observations collected by the federal government in 2006 through the Home Mortgage Disclosure Act. I address two possible theories of discrimination: (1) structural(More)
We address a major discrepancy in matching methods for causal inference in observational data. Since these data are typically plentiful, the goal of matching is to reduce bias and only secondarily to keep variance low. However, most matching methods seem designed for the opposite goal, guaranteeing sample size ex ante but limiting bias by controlling for(More)
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