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How Disaggregation Enhances the Credibility of Management Earnings Forecasts
Authors:D ERIC HIRST  LISA KOONCE  SHANKAR VENKATARAMAN
Institution:Department of Accounting, McCombs School of Business, The University of Texas.
Abstract:An important problem facing managers is how to enhance the credibility, or believability, of their earnings forecasts. In this paper, we experimentally test whether a characteristic of a management earnings forecast—namely, whether it is disaggregated—can affect its credibility. We also test whether disaggregation moderates the relation between managerial incentives and forecast credibility. Disaggregated forecasts include an earnings forecast as well as forecasts of other key line items comprising that earnings forecast. Our results indicate that disaggregated forecasts are judged to be more credible than aggregated ones and that disaggregation works to counteract the effect of high incentives. We also develop and test an original model that explains how disaggregation positively impacts three factors that, in turn, influence forecast credibility: perceived precision of management's beliefs, perceived clarity of the forecast, and perceived financial reporting quality. We show that forecast disaggregation works to remedy incentive problems only via its effect on perceived financial reporting quality. Overall, our study adds to our understanding of how managers can credibly communicate their expectations about the future to market participants.
Keywords:
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