Performance share plans are an increasingly important component of executive compensation. They are equity-based, long-term incentive plans where the number of shares to be awarded is a quasi-linear function of a performance result over a fixed time period. We derive closed-form formulas for the value of a performance share plan when the performance measure is: (1) a non-traded measure following an Arithmetic Brownian Motion (e.g., earnings per share), (2) a non-traded measure following a Geometric Brownian Motion (e.g., revenue), or (3) a rank-order tournament of traded asset returns that are following Arithmetic Brownian Motions (e.g., percentile of ranked stock returns). Then we empirically test our valuation formulas. We find that our valuation formulas are more accurate for performance share plans based on earnings per share when forecasting using analyst consensus prior to the grant date. We also find that the efficiency of our valuation model greatly depends on the method used to forecast future firm performance. The policy implication is that FASB should consider requiring that grant date fair value be estimated using valuation formulas such as ours.

We empirically study whether carbon emissions affect firms’ cost of capital raised on conventional bond markets. We find that firms with higher carbon emissions face higher spreads in the secondary market but not in the primary market. We show that this gap is related to uncertainty about climate concerns that affects differently primary and secondary market. This gap is also affected by the reputation of underwriting dealers: high reputation promotes the incorporation of climate concerns into bond yields. Our findings imply that, on average, carbon emissions do not affect the cost of capital in bond markets, thereby reducing firms’ financial incentives for decarbonization.

We develop a dynamic capital structure model to study how agency conflicts between managers and shareholders affect the joint determination of financing and investment decisions. We show that there are two agency conflicts with opposing effects on a manager’s choice of investment: first, the consumption of private benefits channel leads managers not only to choose a lower optimal leverage, but also to underinvest, and second, compensation linked to firm size may lead managers to overinvest. We fit the model to the data and show that the average firm slightly overinvests, younger CEOs invest more than older ones, while CEOs with longer tenure overinvest more than CEOs with shorter tenure. (JEL G12, G31, G32)

We show that early joiners—nonfounder employees in the first year of a startup—play a critical role in shaping firm performance. We use administrative employer-employee matched data on U.S. startups and utilize premature death as a natural experiment that exogenously separates talent from startups. We find that losing an early joiner has large negative effects on employment and revenues that persist for at least ten years. In contrast, losing a later joiner yields only a small and temporary decline in firm performance. Our results imply that organization capital, an important driver of startup success, is embodied in early joiners.

ABSTRACT We study how corporate boards set earnings performance targets in CEOs’ annual incentive plans (AIPs) and the implications for strategic management earning guidance. We find that corporate boards rely on management and analyst information in setting the earnings performance targets, and the weight placed on each signal increases with its precision. We also find that management earnings guidance issued before compensation committee meetings (“event-window management forecast (MF)”) is more pessimistic than that issued by the same firm at other times. The pessimism in the event-window MF is more pronounced when the expected managerial benefits of having lower performance targets are greater. Ex post, the event-window MF pessimism is associated with higher bonus payouts to CEOs. We use a theoretical framework to illustrate how the use of earnings performance targets might drive our findings. This study highlights boards’ tradeoffs in designing executive compensation and the resulting managerial strategic disclosure. JEL Classifications: G34; M41; M52.