Abstract:

Firm ESG strategy contains two elements: real support and disclosure. While correlated, real ESG support and disclosure of that support are separate decisions, and firms can do both, neither, or either one without the other. In an LGBT setting, I classify firms based on their real LGBT support and their disclosure of that support. I study the effects of full support, silent support, non-support, and virtue signaling, and I find that firms have lower net income, market share, revenue, and market capitalization when they are virtue signalers and when they are silent supporters. This is true both across firms and within firms over time, and the results are robust to selection adjustments and alternative variable measures. In cross-sectional tests, I show the results are weaker for firms in consumer-facing industries and stronger for firms with more diverse employee bases, suggesting the benefits of LGBT support and disclosure are driven by employee stakeholders and not consumers. Additionally, consistent with strategic ESG disclosure, I find that ESG support and disclosure decisions are driven by close competitors. Last, in a novel descriptive result, I show that LGBT non-support is concentrated in the quartile of industries with the lowest percentage of female and minority employees.

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Abstract: We use a shock to the enforcement of fair lending laws—the 2017 change in U.S. political leadership, which led to an immediate 99% drop in DOJ fair lending enforcement—to measure bank lending discrimination. Using a differences-in-differences design, we isolate discriminatory behavior from other potential explanations for interest rate disparities. We find that when enforcement is relaxed, banks charge higher interest rate spreads to Black and Hispanic and LMI borrowers. The increase in spreads is more significant for large banks and banks reprimanded previously. This effect is mitigated by competition but not by bank ESG commitments. Results are not driven by systematic changes in application rates, creditworthiness of borrowers, or loan quality. Results are robust to subsample analysis where we match borrowers to credit scores in Experian and Fannie Mae data. Last, we document that when enforcement increased during the previous administration, interest rate spreads declined for Black and Hispanic borrowers.

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