The Study of the Effect of Measurement Subjectivity on the Forecasting of Persistent and Non-Persistent Components of Earnings by Financial Analysts

The correct method of classification is one of the ways to improve the understandability of financial statements. This paper has two purposes. Firstly, the effect of the persistence and subjectivity classification on the forecasting of analysts is investigated. Second, it examines the effect of the presentation format of income statement on the analysts’ forecast. This research in terms of purpose is applied research, in terms of method is quasi-empirical and in the point of data collection is survey. In this research, to test the research hypotheses, questionnaire based scenario is used. In this research the questionnaire of Hewitt et al (2015) research is used. The statistical sample of research includes 136 analysts participated in Tehran Stock exchange which were selected by available sampling method. The period of research is 2017 and its subject field is behavioral accounting. The results show when forecasting a high persistence earnings item, analysts forecast a lower amount when measurement subjectivity is high. Also, when forecasting a low persistence earnings item, analysts forecast a lower amount when measurement subjectivity is high. These results hold both sequential and matrix format. The other results indicate the presentation format of income statement has not significant effect on analysts forecasting.