Knowledge that Transforms

Visionary CEOs have strong beliefs about the right course of action for their firms. How should a board of directors that does not necessarily share the visionary CEO's confidence advise and monitor the CEO? We consider a model in which the board can acquire costly information about the firm's optimal strategic direction. The board not only advises the CEO on strategy, but also must approve it, and the CEO exerts effort to implement the strategy. We find that the board gathers less information when the CEO believes more strongly in his vision. Further, depending on the strength of the CEO's belief bias, the board either plays an advisory role, a monitoring role, or a rubberstamping role. The model predicts that in firms that are led by highly visionary CEOs, boards are passive in that they acquire little information and rubberstamp the visionary's proposal. Nevertheless, shareholders prefer the visionary over an unbiased manager in industries in which obtaining information about the correct course of action is difficult and costly.

To what extent does the narrative context surrounding the numbers in financial statements alter the informativeness of these numbers, that is, contextualize them? Answering this question empirically presents a methodological challenge. Leveraging recent advances in deep learning, we propose a method to uncover the value of contextual information learned from the (deep) interactions between numeric and narrative disclosures. We show that the contextualization of accounting numbers makes them substantially more informative in shaping beliefs about a firm's future, especially when numeric data are less reliable. In fact, the informational value of interactions dominates the direct informational value of the narrative context. We corroborate this finding by showing that stock markets and financial analysts incorporate the interactions between narrative and numeric information when making forecasts. We also demonstrate the value of our approach by identifying rich firm‐year–specific heterogeneity in earnings persistence. We discuss a number of avenues for future research.

The successful candidate will teach 24 credits per academic year, including courses within the

Business and Economics Department invites applications for a full-time faculty position (open rank) to begin August 2024.The successful candidate can expect to teach courses primarily in the areas of accounting.The teaching load for the position is 24 credit hours per academic year, normally three courses each semester, along