Top Management Team Connectedness and Management Earnings Forecasts
Top Management Team Connectedness and Management Earnings Forecasts
곽소연(홍익대학교 경영연구소)
39권 2호, 107~144쪽
초록
[Purpose] This paper examines how connectedness within the top management team (TMT) affect precision and frequency of management earnings forecasts, and its forecast error. On the one hand, connections can increase bonding and cohesion among individuals, which facilitates communication and information transfer. On the other hand, connections can promote groupthink behavior (Janis 1972) which leads to less frequent exchange of information and underestimation of variation in information. Therefore, it is not clear ex-ante how connectedness within the TMT would affect management earnings forecasts. [Methodology]Sample consists of S&P 1500 U.S. firms on Execucomp database from 1999 to 2012. Connectedness within the TMT is measured in two ways, one from pre-existing network and the other formed through the current firm. [Findings]Greater connectedness within the TMT through pre-existing networks is associated with more precise and frequent forecasts, and lower forecast error. However, connectedness formed within the current firm do not have any association. This is consistent with pre-existing network connections promoting more frequent and open sharing of information, rather than groupthink behavior. [Implications]This paper provides some implications to investors and regulators who are concerned about the credibility of forward-looking information provided by the management. Specifically, investors could utilize the disclosure of background information of the executives to evaluate the credibility of management earnings forecasts. However, since the presentation of such biographies are inconsistent from company to company, regulators could consider providing specific guidelines on the content and form. Also, while prior literature on connections in accounting and finance generally documents negative effects of connections, this paper highlights that connections can benefit shareholders by improving the informational environment.
Abstract
[Purpose] This paper examines how connectedness within the top management team (TMT) affect precision and frequency of management earnings forecasts, and its forecast error. On the one hand, connections can increase bonding and cohesion among individuals, which facilitates communication and information transfer. On the other hand, connections can promote groupthink behavior (Janis 1972) which leads to less frequent exchange of information and underestimation of variation in information. Therefore, it is not clear ex-ante how connectedness within the TMT would affect management earnings forecasts. [Methodology]Sample consists of S&P 1500 U.S. firms on Execucomp database from 1999 to 2012. Connectedness within the TMT is measured in two ways, one from pre-existing network and the other formed through the current firm. [Findings]Greater connectedness within the TMT through pre-existing networks is associated with more precise and frequent forecasts, and lower forecast error. However, connectedness formed within the current firm do not have any association. This is consistent with pre-existing network connections promoting more frequent and open sharing of information, rather than groupthink behavior. [Implications]This paper provides some implications to investors and regulators who are concerned about the credibility of forward-looking information provided by the management. Specifically, investors could utilize the disclosure of background information of the executives to evaluate the credibility of management earnings forecasts. However, since the presentation of such biographies are inconsistent from company to company, regulators could consider providing specific guidelines on the content and form. Also, while prior literature on connections in accounting and finance generally documents negative effects of connections, this paper highlights that connections can benefit shareholders by improving the informational environment.
- 발행기관:
- 한국회계정보학회
- 분류:
- 회계학