The Time-Series Properties of Annual Earnings

Albrecht, W. Steve; Lookabill, Larry L.; McKeown, James C.

doi:10.2307/2490350

Cited by 195 publications

(75 citation statements)

References 12 publications

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“…11 For example, Lev and Thiagarajan (LT, 1993) and Abarbanell and Bushee (AB, 1997) focus on inventory and accounts receivable. With respect to inventory accruals, the quality metric, which measures poor quality, is significantly negatively associated with future changes in EPS (AB, 1997) and contemporaneous returns (LT, 10 Early studies that analyzed the statistical process that underlies earnings include Foster, 1977;Watts and Leftwich, 1977;Albrecht, Lookabill, and McKeown, 1977;Beaver, 1970; and Griffin, 1977. Baginski, Lorek, Willinger, andBranson (1999) emphasize that time-series modeling assumptions can create significant differences in parameter estimates, and lead to different economic conclusions about persistence.…”

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confidence: 99%

Understanding Earnings Quality: A Review of the Proxies, Their Determinants and Their Consequences

Dechow¹,

2010

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Researchers have used various measures as indications of "earnings quality" including persistence, accruals, smoothness, timeliness, loss avoidance, investor responsiveness, and external indicators such as restatements and SEC enforcement releases. For each measure, we discuss causes of variation in the measure as well as consequences. We reach no single conclusion on what earnings quality is because "quality" is contingent on the decision context. We also point out that the "quality" of earnings is a function of the firm's fundamental performance. The contribution of a firm's fundamental performance to its earnings quality is suggested as one area for future work. Over the years, researchers have devised various measures of "earnings quality" to represent decision usefulness in specific decision contexts. These measures, however, have become proxies for "earnings quality" in a generic sense, absent a decision context. The result is that some papers use a proxy for earnings quality that does not match the hypothesized form of decision usefulness in their study, but they nonetheless find results that are consistent with their hypothesis. Other papers are intentionally agnostic and find robust results across multiple proxies for earnings quality. The fact that researchers find consistent and robust results across proxies suggests that there is common component to the various measures of quality, which is the firm's fundamental earnings process. Existing research does not clearly distinguish the impact of a firm's fundamental earnings process on the decision usefulness ("quality") of its earnings from the impact of the application of accounting measurement to that process. Research attention has focused on earnings management that reduces the reliability of earnings rather than on the ability of specific features of an accrual-based accounting system to provide a more decision-useful measure, conditional on the firm's fundamental earnings process. September 2009Thanks to Michelle Hanlon (the editor), Shiva Rajgopal, Terry Shevlin, Nemit Shroff, Richard Sloan, and Rodrigo Verdi for helpful comments. The framework for this review is based on Schrand's discussion of earnings quality at the April 2006 CARE Conference sponsored by the Center for Accounting Research at the University of Notre Dame. *Title Page/Author Identifier Page/Abstract 1 Understanding earnings quality: A review of the proxies, their determinants and their consequencesWe begin with a definition of "earnings quality" that sets the scope of our review. Higher quality earnings more faithfully represent the features of the firm's fundamental earnings process that are relevant to a specific decision made by a specific decision-maker. Our definition implies that the term "earnings quality" is meaningless without specifying the decision context, because the relevant features of the firm's fundamental earnings process differ across decisions and decision makers. Consistent with this broad definition, we review approximately 350 published papers on e...

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confidence: 99%

Understanding Earnings Quality: A Review of the Proxies, Their Determinants and Their Consequences

Dechow¹,

2010

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“…When superior knowledge exists, it can be exploited with considerable advantage to improve predictive accuracy and reliability in relation to a random walk based model which has been shown to be quite robust (Ball and Watts, 1972;Albrecht et al, 1977;Watts and Leftwich, 1977, among others), Moreover, given the uncertainty inherent in selecting a proper model under the Box-Jenkins procedure, the Kalman procedure can provide less variable estimates in relation to the former when the underlying earnings process is correctly assessed. The analysis herein yielded results consistent with the procedure assumed in (1).…”

Section: Discussionmentioning

confidence: 99%

The filtering of transitory noise in earnings numbers

Lieber

Melnick

Ronen

1983

Journal of Forecasting

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This paper applies the Kalman filtering procedure to estimate persistent and transitory noise components of accounting earnings. Designating the transitory noise component separately (under a label such as extraordinary items) in financial reports should help users predict future earnings. If a firm has no foreknowledge of future earnings, managers can apply a filter to a firm's accounting earnings more efficiently than an interested user. If management has foreknowledge of earnings, application of a filtering algorithm can result in smoothed variables that convey information otherwise not available to users. Application of a filtering algorithm to a sample of firms revealed that a substantial number of firms exhibited a significant transitory noise component of earnings. Also, for those firms whose earnings exhibited a significant departure from the random walk process, the paper shows that filtering can be fruitfully applied to improve predictive ability. KEY WORDS Kalman filter Annual earnings Predictive abilityPersistent and transitory componentsThe subject of reporting extraordinary items has drawn considerable attention (Ronen et al., 1977, provide a partial representative list of references). Barnea et al. (1976) proposed that managers use their judgement to determine which income items are persistent and which are transitory, and classify the first as ordinary and the second as extraordinary. The claim that such a classification is useful to investors is based on the following propositions:1. The persistent component of income contributes more than the transitory component to the value (and changes therein) of securities. This proposition is consistent with extant security valuation models (such as that of Miller and Modigliani, 1961; see also Ball and Watts, 1972). Some empirical support for this hypothesis is provided by Ronen and SadanPrediction of future earnings is facilitated by presenting the two components separately. This proposition is also supported by empirical evidence given by Ronen and Sadan (1 98 1, (1981, pp.

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“…Regarding the former, there is a huge number of studies that have shown the predictive ability of current earnings for predicting future earnings (e.g., Ball and Watts, 1972;Albretch et al, 1977;Watts and Leftwich, 1977). Concerning book value of equity, the Ohlson valuation model (1995) shows its usefulness for predictive purposes, being that higher the lower the persistence of current earnings.…”

Section: Methodology Variables and Hypothesismentioning

confidence: 99%