This paper investigates whether being a local leader affects a firm's stock price crash risk. We find that local leadership, in terms of being a relatively large firm in a surrounding locality, decreases a firm's stock price crash risk. The results are robust to both an instrumental variable and a difference-in-differences regression approach. We also document that the impact on crash risk depends on the extent to which local communities are likely to be monitoring local firms through their stock market participation rates, the information environment surrounding these firms, and the level of industry competition. Overall, our results highlight a novel benefit of being a local leader, as it is associated with a higher level of local monitoring which renders the firm less prone to crash risk.

This study investigates whether gender pay inequality in the top management team, measured by gender pay slice (GPS), is a factor in Say on Pay (SoP) voting as required by the 2010 Dodd-Frank Act. Since CEOs are known to play a distinct role in SoP voting, we treat CEOs separately and define GPS as the fraction of total non-CEO executive compensation captured by females. Controlling for numerous factors including CEO pay and CEO gender, ISS recommendations, pay composition, firm performance, and other firm characteristics, we find robust evidence of a negative relation between non-CEO GPS and SoP votes, but this gender-based difference in SoP voting does not extend to the CEO. Taken together, our findings imply that gender equality in terms of SoP voting is still an issue for female executives at the sub-top level.

This paper hypothesizes and finds that firms audited by city‐industry specialists have more timely disclosures of contingent losses from litigation when there is no news coverage relating to the legal case prior to management disclosures. A closer examination reveals that this result is explained by the specialist auditors’ prior experience auditing clients in the same office and industry who are involved with litigation. In our setting, disclosures of litigation‐related contingent losses, we identify two kinds of knowledge generated from experience: industry knowledge and litigation knowledge. Industry knowledge helps auditors detect and correct poor implementation of guidance for litigation loss contingency disclosures. Auditors gain litigation knowledge from auditing clients in a given office and industry with previous involvement as defendants. Thus, the two types of knowledge interact in their effects on reporting outcomes.

This paper examines the influence of stakeholder orientation on the shareholder-employee conflict characterized by the propensity of firms to engage in share purchases and leave employee pensions underfunded. Utilizing the enactment of US state-level constituency statutes, we find that firms in states that have adopted constituency statutes exhibit a weaker share repurchase-pension underfunding propensity, especially those with high default risk. The mechanism is through union intervention and labor representatives on boards. The effect is moderated for firms headquartered in high-social-capital regions, operating with higher human capital, possessing a history of employee litigation, and maintaining lower and short-horizon institutional ownership. After implementing constituency statutes, share repurchase announcements are associated with lower returns for firms with higher pension deficits. Our findings suggest that stakeholder orientation can discipline the shareholder-employee conflict.

In the presence of litigation-facing suppliers, the supply chain relationship is at risk. Suppliers with principal customers (dependent suppliers) have a higher concentration of sales to customers, and they are more at risk relative to suppliers without principal customers (non-dependent suppliers). As a result, we predict and find that litigation disclosure patterns differ for the two supplier types: dependent suppliers are more likely to delay bad news and accelerate good news related to litigation outcomes, compared to non-dependent suppliers. Such strategic disclosure patterns in our end-game setting are opposite to those documented in the existing supply chain literature for the repeated-game setting (for example, Hui, Klasa, and Yeung 2012).

In this study, we forecast the realized volatility of the S&P 500 index using the heterogeneous autoregressive model for realized volatility (HAR-RV) and its various extensions. Our models take into account the time-varying property of the models’ parameters and the volatility of realized volatility. A dynamic model averaging (DMA) approach is used to combine the forecasts of the individual models. Our empirical results suggest that DMA can generate more accurate forecasts than individual model in both statistical and economic senses. Models that use time-varying parameters have greater forecasting accuracy than models that use the constant coefficients. The superiority of time-varying parameter models is also found in volatility density forecasting.