Key Performance Indicators and Analysts' Earnings Forecast Accuracy: An Application of Content Analysis

Abstract

We examine the association between the extent of change in key performance indicator (KPI) disclosures and the accuracy of forecasts made by analysts. KPIs are regarded as improving both the transparency and relevancy of public financial information. The results of using linear regression models show that contrary to our prediction and the hypothesis of this paper, there is no significant association between the change in non-financial KPI disclosures and the accuracy of analysts' forecasts. Nonetheless, when we employ a non-linear regression and deflate the absolute value of forecast errors (the dependent variable in this study) by the stock price, the results support the hypothesis of an association between a change in non-financial KPI reporting and the accuracy of analyst forecasts. These results have policy implications, as worldwide policymakers, regulators, corporations and analysts underscore the importance of KPI disclosures.