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Politicizing consumer credit

Journal of Financial Economics 2021 139(2), 627-655 open access
Powerful politicians can interfere with the enforcement of regulations. As such, expected political interference can affect constituents’ behavior. Using rotations of Senate committee chairs to identify variation in political power and expected regulatory relief, we study powerful politicians’ effect on consumer lending to communities protected by fair-lending regulations. We find a 7.5% reduction in credit access to minority neighborhoods in states with new committee chairs. Larger reductions occur in Community Reinvestment Act-eligible neighborhoods and when Senators serve on committees that oversee the enforcement of fair-lending laws. Banks headquartered in powerful Senators’ states are responsible for the reduction in credit access.

Hacking corporate reputations

Review of Finance 2026 30(3), 795-862 open access
We exploit unexpected corporate data breaches to study the loss and repair of corporate reputation. Reputation loss decreases equity and brand values, increases customer churn, and prompts more negative media coverage. Firms repair their reputation by increasing their charitable donations and have CSR scores that are more than 0.5 standard deviations higher. They increase political contributions, employee wages, and IT investment. These actions are targeted to stakeholders that are particularly important or in situations that are particularly salient to their stakeholders. We observe similar dynamics of reputation loss and repair following the release of negative news about firms’ social behaviors.

Price revelation from insider trading: Evidence from hacked earnings news

Journal of Financial Economics 2022 143(3), 1162-1184 open access
From 2010 to 2015, a group of traders illegally accessed earnings information before their public release by hacking several newswire services. We use this scheme as a natural experiment to investigate how informed investors select among private signals and how efficiently financial markets incorporate private information contained in trades into prices. We construct a measure of qualitative information using machine learning and find that the hackers traded on both qualitative and quantitative signals. The hackers’ trading caused 15% more of the earnings news to be incorporated in prices before their public release. Liquidity providers responded to the hackers’ trades by widening spreads.