CEO dismissals attract considerable attention, presumably because of the visibility, publicity, and intrigue that often surrounds the decision to fire the CEO. With the goal of advancing scholarly understanding of CEO dismissals, we examine whether CEO gender influences the likelihood of dismissal. We theorize and find that ceteris paribus, female CEOs are significantly more likely to be dismissed than male CEOs. Perhaps even more importantly, we find a CEO gender by firm performance interaction such that male CEOs are less likely to be dismissed when firm performance is high (compared to when it is low), whereas female CEOs have a similar level of dismissal likelihood regardless of firm performance. Notably, our results are robust to multiple analytical techniques and various econometric specifications, bringing greater credence to the validity of our findings. Implications and directions for future research are also discussed.

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We show that a news‐based measure of economic policy uncertainty (EPU) negatively forecasts momentum. A 1‐standard‐deviation increase in EPU is associated with a 1.11% decrease in risk‐adjusted momentum returns. The predictive power of EPU is robust after controlling for previously documented economic state variables and macroeconomic uncertainty. We provide an explanation for these results from the perspective of a fund flow‐induced trading mechanism and offer direct empirical support. The literature documents that momentum can be partially attributed to performance‐chasing mutual fund flows. We find that this flow‐induced mechanism functions more effectively in low EPU states, thereby generating stronger stock momentum.

We identify the real and social costs associated with neighborhood blight by creating unique neighborhood blight indices based on average individual property blight scores in Memphis, Tennessee. Both individual property blight scores and neighborhood blight indices negatively impact single-family sale prices and assessed valuations. We validate the data accuracy of a 2016 blight survey, finding that supplemental information collected for each property accurately predicts its assigned blight score. We apply factor analysis, Shapley-Owen decomposition, and hedonic regressions to identify blight drivers that include neighborhood demographic and economic factors associated with both individual property and neighborhood blight. We find that blight scores provide informational value in addition to county assessor and data for each property and census data for each neighborhood. We quantify neighborhood characteristics and demographic factors impacting both individual property and neighborhood blight effects on neighborhood esthetics and property values that helps identify blight resolution alternatives.

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