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We develop a theory to show how external and internal corporate governance mechanisms affect innovation. We predict a U-shaped relation between innovation and external takeover pressure, which arises from the interaction between expected takeover premia and private benefits of control. Using ex ante and ex post innovation measures, we find strong empirical support for the predicted relation. We exploit the variation in takeover pressure created by the passage of antitakeover laws across different states. Innovation is fostered either by an unhindered market for corporate control or by antitakeover laws that are severe enough to effectively deter takeovers.

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We examine the dynamic forecasting behavior of investment analysts in response to their prior performance relative to their peers within a continuous time/multi-period framework. Our model predicts a U-shaped relationship between the boldness of an analyst's forecast, that is, the deviation of her forecast from the consensus and her prior relative performance. In other words, analysts who significantly out perform or under perform their peers issue bolder forecasts than intermediate performers. We then test these predictions of our model on observed analyst forecast data. Consistent with our theoretical predictions, we document an approximately U-shaped relationship between analysts' prior relative performance and the deviation of their forecasts from the consensus. Our theory examines the impact of both explicit incentives in the form of compensation structures and implicit incentives in the form of career concerns, on the dynamic forecasting behavior of analysts. Consistent with existing empirical evidence, our results imply that analysts who face greater employment risk (that is, the risk of being fired for poor performance) have greater incentives to herd, that is, issue forecasts that deviate less from the consensus. Our multi-period model allows us to examine the dynamic forecasting behavior of analysts in contrast with the extant two-period models that are static in nature. Moreover, the model also differs significantly from existing theoretical models in that it does not rely on any specific assumptions regarding the existence of asymmetric information and/or differential analyst abilities.

This paper characterizes the liquidity discount, the difference between the market value of a trader's position and its value when liquidated. This discount occurs whenever traders face downward sloping demand curves for shares and execution lags in selling shares. This characterization enables one to modify the standard value at risk (VaR) computation to include liquidity risk.