Should She Stay or Should She Go? CEO Gender and the Performance-Turnover Gradient (with Beatrice Ferrario)

Does CEO turnover respond more sharply to firm performance when the CEO is a woman? In a broad sample of US public firms, we find that female CEOs separate from their firms more often than male CEOs, and that their turnover is more than twice as sensitive to industry-adjusted stock returns. This gender gap in performance sensitivity survives matching on observable firm characteristics and restricting the sample to firms that have had both a male and a female CEO, and is concentrated on weak performance. The gap is not explained by selection, since women are no more likely than men to be appointed to observably distressed firmsl by voluntary exits, since the gap golds among explicitly forced departures; or by Bayesian learnings about ability, since the gap is no smaller when boards have observed the CEO longer, or hired one with a more informative track record. Instead, we document several facts consistent with gendered attribution of responsibility: on earnings calls, analysts hold management more responsible for a missed quarter when the firm is female-led; after weak performance the broader C-suite tends to follow a male CEO out but stays when a woman leaves; the gender gap in gradients is specific to the CEO, the role ultimately held responsible for firm performance, and does not extend to CFOs or COOs; finally, the gap is largest in male-typed industries, where women are least representative of the typical leader. Together, these patterns identify the turnover margin as a channel that can erode women's representation at the top even after they reach it. 

Who Gets the Benefit of the Doubt? CEO Gender and News about Firm Performance

I show that financial markets react asymmetrically to bad news about firm performance depending on whether it is delivered by male or female CEOs. This asymmetry manifests itself in analysts’ forecasts, stock returns on earnings announcement days, and even in the tone that analysts adopt in earnings conference calls. I argue that these patterns have a common origin in a reduced skepticism towards male CEOs. To make this case, I first document that analysts' beliefs about firm performance under-react to bad news from male-led companies relative to the rational expectations benchmark, whereas they adjust rationally to similar bad news from female-led companies. Next, I show that investors also display this biased reaction to news, with stock returns reacting less negatively to negative surprises from male-led companies relative to their female-led peers on earnings announcement days. I then shed light on the mechanism by showing that after negative surprises, analysts express less disagreement with the narrative conveyed by male- relative to female-led firms.

[Online Appendix]

The Diffusion of New Technologies (with Aakash Kalyani, Nicholas Bloom, Tarek Hassan, Josh Lerner, and Ahmed Tahoun)

The Quarterly Journal of Economics

We identify phrases associated with novel technologies using textual analysis of patents, job postings, and earnings calls, enabling us to identify four stylized facts on the diffusion of jobs relating to new technologies. First, the development of economically impactful new technologies is geographically highly concentrated, more so even than overall patenting: 56% of the most economically impactful technologies come from just two U.S. locations, Silicon Valley and the Northeast Corridor. Second, as the technologies mature and the number of related jobs grows, hiring spreads geographically. But this process is very slow, taking around 50 years to disperse fully. Third, while initial hiring in new technologies is highly skill biased, over time the mean skill level in new positions declines, drawing in an increasing number of lower-skilled workers. Finally, the geographic spread of hiring is slowest for higher-skilled positions, with the locations where new technologies were pioneered remaining the focus for the technology’s high-skill jobs for decades.

[Data] [NBER Working Paper]

Scientific Innovations and their Technological Applications (with Aakash Kalyani, Nicholas Bloom, Tarek Hassan, Josh Lerner, and Ahmed Tahoun)

How does CEO Gender Shape the Interpretation of Financial Information? (with Beatrice Ferrario)

We study how CEO gender shapes the interpretation of financial information. In a three-round survey experiment, participants analyze real financial cases in which the CEO’s gender is randomly assigned. In each round, they provide incentivized EPS forecasts and evaluations of managerial talent and firm fundamentals, both before and after receiving noisy "expert" signals — randomized to be optimistic or pessimistic — and additional contextual vignettes. We find pronounced gender asymmetries in earnings expectations. Participants hold more optimistic prior earnings beliefs for male-led firms than for female-led ones, and this optimism persists in posterior beliefs. Belief updating is asymmetric with respect to the sign of the news: while bad news elicits pessimism across the board, the effect is stronger for female-led companies. Using predictive regressions of forecast errors on forecast revisions, we find that participants overreact to good news from male-led firms, while this overreaction is attenuated for female-led firms. Finally, we test whether these expectation gaps can be explained by differences in beliefs about CEO talent or firm fundamentals, but find no evidence that either channel accounts for the observed gender asymmetries.

Anchored Inflation Expectations and the Term Structure of Interest Rates (with Carlos Carvalho, Stefano Eusepi, and Frederico Bastone)

Evidence suggests that the moments of the nominal yield curve depend on whether inflation expectations are anchored or not. Yet, traditional term structure models overlook this critical factor. This paper explores the implications of the anchoring of long-run inflation expectations to the term structure of nominal interest rates, proposing a conceptual framework with endogenous anchoring of inflation expectations. The model assumes that agents have subjective beliefs instead of rational expectations — following Carvalho et al. (2023)  — and allows for long-run inflation and real interest trends that are non-stationary — as in Bauer and Rudebusch (2020).