Forecasting

We examine whether the use of budgetary information for performance evaluation and resource allocation is associated with systematic biases in the forecasts of senior executives of their firm’s future performance. Using a unique and proprietary data set of senior executives’ non-public profit expectations from 2013 to 2019, we find that an increase of importance in budget-based performance evaluation for subordinates is associated with underestimating future profit. This indicates that senior executives do not fully adjust for distortions in employee-generated information to budgets. Our results also suggest that this downward bias in budgets partially corrects for the otherwise, on average, too high profit expectations. We find partial support for the association of resource allocation with overestimating future profits.

I investigate whether managers learn from conversations about their firm on Twitter when forming their expectations about future firm performance. I conjecture that tweets addressed to or about the firm, as initiated by its different stakeholder groups, such as customers, employees, or suppliers, contain useful and timely forward-looking information. I use a machine-learning-based natural language processing algorithm to analyze 11 million stakeholder-initiated tweets before the announcement of 4,131 sales forecast from 2013 to 2020. I find evidence that managers could learn from listening to conversations about their firm on Twitter and improve forecast precision before they announce their forecasts: I show that information in conversations is negatively associated with the directional error in management sales forecasts, suggesting that managers do not adequately account for third-party information: When the conversational information is negative, managers overestimate future sales. In contrast, managers tend to underestimate future sales when it is positive. Further, I find the relevance of Twitter information increases the closer the information is released to the forecast announcement date.