Measuring annual report narratives disclosure

Purpose - This paper aims to investigate empirically the common alternative methods of measuring annual report narratives. Five alternative methods are employed, a weighted and un-weighted disclosure index and three textual coding systems, measuring the amount of space devoted to relevant disclosures. Design/methodology/approach - The authors investigate the forward-looking voluntary disclosures of 30 UK non-financial companies. They employ descriptive analysis, correlation matrix, mean comparisont-test, rankings and multiple regression analysis of disclosure measures against determinants of corporate voluntary reporting. Findings - The results reveal that while the alternative methods of forward-looking voluntary disclosure are highly correlated, important significant differences do nevertheless emerge. In particular, it appears important to measure volume rather than simply the existence or non-existence of each type of disclosure. Overall, we detect that the optimal method is content analysis by text-unit rather than by sentence. Originality/value - This paper contributes to the extant literature in forward-looking disclosure by reporting important differences among alternative content analyses. However, the decision regarding whether this should be a computerised or a manual content analysis appears not to be driven by differences in the resulting measures. Rather, the choice is the outcome of a trade-off between the time involved in setting up coding rules for computerised analysis versus the time saved undertaking the analysis itself.