Disaggregation and the Quality of Management Earnings Forecasts

Abstract

In recent years, a substantial percentage of managers voluntarily choose to provide disaggregated earnings forecasts, i.e., earnings forecasts supplemented with additional numerical forecasts for other line items on the income statement. We examine whether such disaggregation yields higher-quality (i.e., more accurate and less biased) management earnings forecasts, and whether market reactions to disaggregated vs. aggregated forecasts are consistent with the quality of these forecasts. We find that: (1) for good news forecasts, earnings forecasts with disaggregated information are no different from aggregated earnings forecasts in either bias or accuracy; (2) for bad news forecasts, earnings forecasts with disaggregated information are significantly less accurate and, on average, more optimistic than aggregated earnings forecasts; 3) stock market reactions to disaggregated good news forecasts are no different from stock market reactions to aggregated good news forecasts, but stock market reactions to disaggregated bad news forecasts are more negative than stock market reactions to aggregated bad news forecasts. Taken together, our results suggest that disaggregated earnings forecasts are no better than and sometimes even worse than aggregated earnings forecasts and that investors anticipate and adjust for the biases associated with disaggregation in management earnings forecast.