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Title: Special items, financial reporting and equity valuation
Author: Abdalla, Ahmed Mahmoud Ahmed Ahmed
ISNI:       0000 0004 5991 2004
Awarding Body: King's College London
Current Institution: King's College London (University of London)
Date of Award: 2016
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This thesis examines the information content of earnings components conditional on the existence of misclassification of core earnings as transitory earnings in the income statement (often referred to as classification shifting), and how this misclassification is likely to induce a “hidden” core earnings element in reported transitory earnings. The thesis focuses on a major type of the misclassification of earnings line items, namely the transfer of negative core earnings (operating expenses and losses) to negative special items in order to increase net core earnings, while bottom-line earnings remain unaffected. The thesis comprises three empirical essays. In the first essay, we develop a vector autoregression (VAR) of a set of accounting information that includes, in addition to other accounting variables, two components of transitory earnings; a shifted core earnings component and a purified transitory earnings component. The model analysis derives two properties of shifted core earnings. First, shifted core earnings forecast future abnormal earnings similar to core earnings. Second, shifted core earnings provide a “bad news” signal of management incompetence. Using special items as an objective measure of transitory earnings, we develop an innovative approach to decompose special items into core and transitory components. Our empirical results support the former property of shifted core earnings, and show little evidence for the latter one. The model demonstrates how the properties of the transitory earnings components map into stock prices. However, we find empirically that stock prices do not fully reflect the heterogeneity between the two components of transitory earnings, but rather overstate the shifters‟ entire special items, which are mostly income decreasing items, as if they are all shifted core earnings. In the second essay, we investigate the manager‟s incentive to misclassify negative core earnings as negative special items, and the change in the composition of negative special items as a result of the misclassification. We find that large negative special items are increasing with the difference between reported core earnings in the prior period and expected core earnings in the current period. Extremely large negative special items are more likely associated with GAAPviolation rather than allowable discretion within GAAP. We distinguish between two types of misclassification signals, an “informative” signal associated with steady improvements in negative special items predictability and a “noisy” signal associated with a pattern in earnings response coefficients (ERC) that is inconsistent with improvements in negative special items predictability. We propose and find that the measures of negative special items predictability of future earnings go hand-in-hand with the extent of an informative signal based on the difference between reported core earnings in the prior period and expected core earnings in the current period. However, stock prices do not fully impound information in this identified informative signal, and react to a “noisy” reporting signal that is based on the level of earnings before special items in the income statement. In the third essay, we investigate whether analysts fully understand the nature and quality of negative special items when they adjust actual earnings and whether their future earnings forecast incorporates the actual persistence of negative special items components. We identify an alternative direct approach to measure the core and transitory elements of negative special items. We validate our measures by showing that the identified core component is more persistent and has very low asymmetric timeliness relative to the identified transitory component. We expand our decomposition of negative special items further in order to examine the nature of negative special items included in and excluded from street earnings. We find that the analysts‟ inclusion decision reflects analysts‟ expertise in processing information in special items. The analysts‟ treatment of negative special items does not lead to predictable forecast errors, consistent with analysts fully understanding the persistence of negative special items components. This result is robust to partitioning the sample between different disclosure and information environments and adding analysts forecast efficiency controls.
Supervisor: Li, Yong ; Clubb, Colin David Berryhill ; Heath, Christian Consitt Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available