ABSTRACT This study examines how the use of causal language in conveying relative performance feedback impacts subsequent task performance. Research in linguistics has shown that causal language, defined as language reflecting the search for reasons (commonly expressed through words such as “because” and “thus”), impacts how recipients process received information. We use a laboratory experiment to show that causal language has a differential effect when used in negative versus positive feedback. In the case where initial relative performance is low, the high use of causal language in the resulting negative performance feedback leads to a greater improvement in subsequent performance, compared to low use of causal language. Conversely, when initial relative performance is high, greater use of causal language in delivering positive feedback results in a smaller improvement in performance. Our results indicate that employees' cognitive processes and reactions to performance feedback are influenced by the language used in explanations.

ABSTRACT: Regulators and the financial press have criticized credit rating agencies (CRAs) for exacerbating the financial crisis by providing overly optimistic debt ratings. Allegedly, CRAs departed from their quantitative models in order to please security issuers with higher credit ratings. In response, the Dodd-Frank Act of 2010 required the Securities and Exchange Commission to conduct a study on alternative models for compensating CRAs. We conduct an experiment exploring how the credit ratings of M.B.A. students, who assume the role of credit rating analysts, are affected by two proposals for reform: (1) changing who pays the CRAs, and (2) requiring analysts to justify departures from a quantitative model. We find that credit ratings are highest when the borrower pays CRAs for ratings and a justification requirement is not in place. Implementing either proposed reform independently reduces credit ratings, but credit ratings are not further reduced when both reforms are implemented together. Data Availability: Data are available from the authors upon request.