The Roles That Forecast Surprise and Forecast Error Play in Determining Management Forecast Precision

Jong-Hag Choi, Seoul National University
Linda Myers
David Ziebart
Yoonseok ZANG, Singapore Management University

Abstract

Studying the determinants of management forecast precision is important because a better understanding of the factors affecting management’s choice of forecast precision can provide investors and other users with cues about the characteristics of the information contained in the forecasts. In addition, as regulators assess the regulation of voluntary management disclosures, they need to better understand how managers choose among forecast precision disclosure alternatives. Using 16,872 management earnings forecasts collected from 1995 through 2004, we provide strong evidence that forecast precision is negatively associated with the magnitude of the forecast surprise and that this negative association is stronger when the forecast is bad news than when it is good news. We also find that forecast precision is negatively associated with the absolute magnitude of the forecast error that proxies for the forecast uncertainty that managers face when they issue forecasts, and that the negative association is stronger when forecast errors are negative. These results are consistent with greater liability concerns related to bad news forecasts and negative forecast errors, respectively. Our study provides educators and researchers with important insights into management’s choice of earnings forecast precision, which is a component of the voluntary disclosure process that is not well understood.