Modelling the accruals process and assessing unexpected accruals*

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1 Introduction The focus of earnings management research to date has been on the identification, motivation, and consequences of earnings management (Healy and Wahlen 1999). This paper attempts to address the identification issue while remaining silent about the other two issues. One common approach to identifying earnings management is via unexpected accruals where total accruals are regressed on variables that are proxies for normal accruals and unexpected accruals are the unexplained components or residual of total accruals (see Healy and Wahlen 1999 for details). The common accruals models employed in the literature are the Jones model (Jones 1991) and subsequent modifications, notably the modified Jones model found in Dechow et al. (1995) and the model in Ball and Shivakumar (2006) that incorporates conditional conservatism. However, all of these models were developed on an ad-hoc basis and their theoretical validity is open to question. McNicols (2000) argues that this black-box approach reduces confidence in the ability of estimates of abnormal accruals capture the exercise of accounting discretion by management. The paper addresses this concern by focussing on two main objectives. First, this paper defines accruals, explores the role of normal and abnormal accruals, and models them in a general setting. This helps us to better understand the drivers of normal and abnormal accruals so that researchers can adopt a systematic approach (rather than a black-box approach) in identifying the factors that explain accruals. Second, I assess the bias in unexpected accruals (the empirical measure) from the aforementioned accruals models in capturing abnormal accruals (the theoretical construct) and provide determinants and a reason for the bias. To my knowledge, this is the first paper that has done this to date. This contribution is significant in that it provides new 2
insights into what unexpected accruals actually capture, what determines the direction and the magnitude of their bias or contamination, and why such a bias or contamination arises. I begin by adopting the idea in Richardson et al. (2005) to comprehensively measure accruals by subtracting the income under cash accounting from the income under accrual accounting. In addition to the balance sheet approach provided in Richardson et al. (2005), I also consider the income statement approach to calculate accruals under clean surplus accounting. This reconciliation offers insight into the conclusion in Hribar and Colins (2002) that the accruals calculated under both methods are different. With this accruals definition in mind, I first model normal accruals as the accruals resulting from the neutral accrual process that shifts cash flow recognition in income to a time that unbiasedly reflects underlying fundamentals. As the sum of accrued and deferred components, normal accruals are driven by growth in income and changes in accruals and deferrals policies. Second, I model abnormal accruals as the accruals that distort the neutral accruals process by accelerating and/or delaying cash flow recognition in income. The two factors that drive abnormal accruals are a change in accounting policy and forward income growth. Finally, I combine the normal and abnormal accruals into the final accruals model under clean surplus accounting. My model is appealing in that it does not impose restrictive assumptions on firms‟ fundamentals. It merely requires (a) the basic accounting identity to hold, (b) accruals to alter the timing of cash flow recognition in income over time, and (c) the aggregated income to be equal to the aggregated cash flow over the life span of firms. These three conditions can hardly be regarded 3
Page 1: Modelling the accruals process and
Page 5 and 6: attributed to the firm‟s biased a
Page 7 and 8: 2 Direct and indirect method to cal
Page 9 and 10: flow associated with income recogni
Page 11 and 12: change in net financial obligations
Page 13 and 14: t t TACC CNICFt T t t t titti CNI
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Page 17 and 18: expenses or receive less revenue in
Page 19 and 20: any accounting distortions (conserv
Page 21 and 22: this paper). Combining the normal a
Page 23 and 24: 4 Assessing unexpected accruals mea
Page 25 and 26: firm j and the benchmark firms. The
Page 27 and 28: If there is no deviation in operati
Page 29 and 30: accruals is highly positive (negati
Page 31 and 32: These restrictions respectively imp
Page 33 and 34: The second source of contamination
Page 35 and 36: Even if the use of changes in cash
Page 37 and 38: The item m m CNI , 1 a a CNI
Page 39 and 40: Hence, to manage earnings downward
Page 41 and 42: 6 Conclusion My analysis reveals th
Page 43 and 44: References Ball, R., Shivakumar, L.
Page 45 and 46: Appendix 1: Derivation of Normal Ac
Page 47 and 48: accrued (initiated deferred) propor
Page 49 and 50: The portion of underlying income in
Page 51 and 52: Hence, the correlation between norm
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Table 2: Summary of Accruals Compon
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Table 4: Summary of the Bias in Une
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Modelling the accruals process and assessing unexpected accruals*

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