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

   
Introduction
Based on conceptual framework of financial reporting, the primary purpose of financial reporting is to assist the investors to make economic decisions. Therefore, understandability of financial statements is very important to them. The correct method of classification is one of the ways to improve the understandability of financial statements. Many researchers believe that classifying earnings items based on their underlying attributes is useful for forecasting and valuation. Previous studies showed that persistence classifications lead to better prediction (Fairfield et al, 1996). In addition, subjectivity is another attribute that is important for investors and analysts. Persistence is the extent to which an earnings item is indicative of its future amount and subjectivity is the extent to which managers use judgment to measure the amount of the earnings item (Hewitt et al, 2015). In previous studies, persistence and measurement subjectivity classifications are displayed separately in financial statement. This research is based on two streams of literature on subjectivity and persistence and investigates both subjectivity and persistence clarifications in financial statement. 
In measurement subjectivity, intentional and unintentional errors are increased. Thus, when the measurement subjectivity is high, it seems that persistence classification is misreported. In other words, if management classifies the special items as a high persistence, analysts expect that they have low persistence. In addition, if management classifies the earnings item as a low persistence, analysts perceive that this item is high persistence. Therefore, when measurement subjectivity is in high level, analysts rely less on persistence classifications for forecasting. Accordingly, combining persistence and measurement subjectivity classifications improve the predictive content of reported earnings and are used by analysts and investors.
Previous studies often investigated the sequential format to present the earnings items in income statements. In this format, the persistence and measurement subjectivity classifications are displayed separately (Schkade and Kleinmuntz, 1994). Although the sequential format has been considered by standard setters, psychology theory supports the usefulness of matrix format. Because in this format persistence classifications are displayed on rows and measurement subjectivity classifications are displayed on columns. In matrix format analysts require acquiring only one value to process both classifications, while the sequential format sometimes requires analysts to acquire values across multiple columns to process these classifications. Thus, matrix format facilitates analysts’ processing of the classifications (Hewitt et al, 2015). 
 
Hypotheses
This paper has two purposes. Firstly, the effect of the persistence and subjectivity classification on the prediction of analysts is investigated. Second, it examines the effect of the presentation format of income statement on the analysts’ forecast. 
 
Methods
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, the questionnaire of Hewitt et al (2015) research is used. The statistical sample of research includes 136 analysts participating in Tehran Stock exchange selected by available sampling method. The period of research is 2017 and its subject field is behavioral accounting.
 
Results
The results show when forecasting a high persistence earnings item, analysts forecast a lower amount when measurement subjectivity is high. In addition, 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.
 
Discussion and Conclusion
In general, it is inferred from the findings of the present research that when the measurement subjectivity is high, analysts rely less on this item and forecast a lower amount. The measurement subjectivity and persistence classification affect analysts’ forecasting. Therefore, it is useful to classify the earnings item in income statement. Moreover, because of having expertise, the presentation format doesn’t affect analysts in earnings items processing and their forecasting.