Modelling the accruals process and assessing unexpected accruals*

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are positive or negative if normal accruals are negative. The converse is true for conservative earnings management. In the absence of heterogeneity in parameters (i.e., =1), abnormal accruals and normal accruals are perfectly correlated either in the same or opposite direction. Let us illustrate this perfect correlation with accrued revenue for which cash flow is realized one period after income recognition. In Table 5, this numerical example assumes that accrued revenue is $100 in year 1 and it grows at 20% per year. [Table 5 about here] Panel A shows the journal entry for this transaction if it is accounted for unbiasedly and the resulting accruals (which are the difference between initiated and reversed accounts receivable) are the normal accruals. Panel B shows the journal entry for this transaction if it is accounted for conservatively such that no revenue is recognized until the cash flow is realized. Since the resulting accruals from this conservative treatment are zero, the resulting abnormal accruals are thus -100% of normal accruals. The correlation between abnormal and normal accruals in this scenario is thus –1. Finally, Panel C shows the journal entry for this transaction if it is accounted for aggressively such that 20% of the next period‟s accrued revenue is recognized (prematurely) in this period. Since the resulting accruals from this aggressive treatment are 24% higher than the normal accruals, the resulting abnormal accruals are thus 24% of normal accruals. Hence, the correlation between abnormal and normal accruals in this scenario is 1. 22 22 A similar example can be made for cross-sectional firms 38
Hence, to manage earnings downward (upward), firms can delay (accelerate) the recognition of positive normal accruals. As a result, total accruals will be lower (higher) than the normal accruals, and abnormal accruals will be (negative) positive. If the same level of conservatism (aggression) is to be maintained across time or firms, more negative (positive) abnormal accruals are needed as normal accruals increase. In such a setting of no heterogeneity in the parameters, there will be a perfect negative (positive) correlation between abnormal and normal accruals. 23 5.2 Implications For well-specified models such as the encompassing model and the modified version of the Dechow and Dichev (2002) model, my analysis reveals their resulting unexpected accruals are contaminated by two factors – income distortion of the benchmark firms and deviation in operating policy between this firm and the benchmark firms. One necessary condition for unexpected accruals to fully capture abnormal accruals is that the benchmark firms‟ income on average should be neutral (i.e., m=0). It is no coincidence that this is also one of the necessary conditions that will result in a zero correlation between abnormal and normal accruals among firms. On the other hand, when the income of benchmark firms is on average biased in one direction (m≠0), abnormal and normal accruals are correlated. It is also no coincidence that the resulting unexpected accruals under such a condition fail to capture abnormal accruals in full 24 . 23 The presence of heterogenity is likely to decrease this perfect correlation. In particular, the correlation between normal and abnormal accruals is an inverse function of the variation in parameters that capture accounting and firm policies among observations. For instance, if the variation in accounting (firm) policy is as large as the variation in abnormal (normal) accruals among observations, the absolute correlation will be reduced to 0.5. If the former variation is lower (larger) than the latter, it will be higher (lower) than the absolute value of 0.5. The matching procedure proposed by Kothari et al. (2004) is likely to decrease the heterogeneity and increase the correlation. 24 See section 4.1 for details. 39
Page 1 and 2: Modelling the accruals process and
Page 3 and 4: insights into what unexpected accru
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
Page 15 and 16: period of income recognition and ca
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: The item m m CNI , 1 a a CNI
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
Page 53 and 54: Table 2: Summary of Accruals Compon
Page 55 and 56: Table 4: Summary of the Bias in Une

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