We develop a method that identifies the attention paid by earnings call participants to firms' climate change exposures. The method adapts a machine learning keyword discovery algorithm and captures exposures related to opportunity, physical, and regulatory shocks associated with climate change....

Little attention has been given to the role of leadership characteristics in the organization design literature despite significant evidence of its importance in explaining firm behavior. This study develops and tests a model to assess the effects of leadership style on three control choices...

Using tools described in our earlier work (Hassan et al., 2019, 2020), we develop text-based measures of the costs, benefits, and risks listed firms in the US and over 80 other countries associate with the spread of Covid-19 and other epidemic diseases. We identify which firms expect to gain or...

We adapt simple tools from computational linguistics to construct a new measure of political risk faced by individual US firms: the share of their quarterly earnings conference calls that they devote to political risks. We validate our measure by showing it correctly identifies calls containing...

We study theoretically and empirically the relation between altruism preferences and incentive contract design. Theoretically, we extend Fischer and Huddart (2008) to investigate how social norms reinforce altruism preferences, thus affecting the optimal contract design related to incentive...

Using tools from computational linguistics, we construct new measures of the impact of Brexit on listed firms in the United States and around the world; these measures are based on the proportion of discussions in quarterly earnings conference calls on the costs, benefits, and risks associated...

Many decisions are made based on persuasion. In the persuasion process, self-interested agents produce information to convince an evaluator to approve their proposals. Whether an evaluator will discount the agents' suggestions and reject their proposal is neither clear nor obvious. We highlight...