Part A: Summary & Referencing Exercise Due to implications for related research in areas of accounting and finance, Time series behaviour of earnings is crucial for empirical studies (Beaver 1970). Issues regarding Income smoothing, the relative forecast ability of alternative income measurements, and interim reporting, were discussed by Beaver (1970: pp. 62). These studies share mutual reliance upon a knowledge of the process creating accounting earnings, despite representing a comprehensive spectrum of predictive contexts (Beaver 1970).
When taken as a group, the studies offer a variety of models, and findings of the studies with respect to these models, according to Beaver (1970: pp. 64), “appear conflicting, or at the very least paradoxical”. “A large portion of accounting research is concerned with potential measurement errors in accounting data in general, and in accounting earnings in particular” (Beaver 1970). Lacking knowledge of the process creating the information, it is impossible to acquire insight of the measurement errors (Beaver 1970).
Security prices and returns reflect one mapping of underlying events that affect wealth changes, while another is provided by the accounting system (Beaver 1970). Yet, evidence of relationship between them is sparse (Beaver 1970). Due to the fact that companies highlight a wide array of earnings figures, the evaluation of earnings is often arduous (Bellovary, Giacomino and Akers 2005). Furthermore, the income statement alone is “not useful in predicting future earnings” (Bellovary, Giacomino and Akers 2005).
Although there is insufficient knowledge about the decision processes of users of accounting data, there appears to be an agreement that forecasting of future profitability of the firm (or its securities) is common to many decision models (Beaver 1970). Since a knowledge of the underlying process is a prerequisite to the construction of an optimal fore-casting system, the forecasting process cannot proceed very far without such knowledge generating earnings observations (Beaver 1970). Hence, a study was set about to investigate in a preliminary way the statistical properties of time series observations on earnings variables (Beaver 1970).
The analysis of time series data was separated into three states: (1) investigation, (2) model selection and fitting, and (3) application (Granger and Hatanaka, cited in Beaver 1970). References Beaver, WH 1970, ‘The Time Series Behavior of Earnings’, Journal of Accounting Research, Vol. 8, Empirical Research in Accounting: Selected Studies, pp. 62-99, accessed 8 August 2010, from . Bellavary, JL, Giacomino, DE & Akers, MD 2005, ‘Earnings Quality: It’s Time to Measure and Report’, The CPA Journal, November 2005 Issue, accessed 15 August 2010, from .