A Critical Review of Allen, E., Larson, C.R. and Sloan, R.G. (2013). Accrual reversals, earnings and stock returns. Journal of Accounting and Economics, 56 (-), pp.113-255.

Literature Review, 2016

6 Pages, Grade: 71





Critique of Data used

Critique of Methodology and Models

Critique of Findings




Accounting numbers are supposed to be reliable and relevant. However, due to the use of accrual based accounting reliability can be flawed. Accruals are used to make earnings more relevant than cash flows, hence they put every business transaction into the period in which they belong (Richardson et al., 2005), but at the cost of reducing reliability. Furthermore, accruals can be used to increase or decrease earnings in one period and if they are used correctly this variation will be reversed with following cash flows. These variations of earnings can have an impact on share prices and corporate decision making. Thus, Allen, Larson and Sloan (2013) investigate to what extend accruals are reversed and what impact they have on the stock market. Firstly, this critical review will summarize the article, then it will critique data, methodology and findings before it finishes with a conclusion.


Allen, Larson and Sloan (2013) examine in Accrual reversals, earnings and stock returns how earnings, cash flows and accruals influence stock returns. In particular, they look at accruals and separate them into “good accruals” and “accrual estimation error” to analyse the impact of each on future stock returns, cash flows and earnings. Furthermore, the authors analyse if both types of accruals are reversed by cash flows and how long this takes. To conduct their analysis, they collect data from a large sample, set up a model to calculate “good accruals” and “accrual estimation error” and perform statistical calculations. They find that accruals consist of a process which addresses company growth and another process which reverses changes in working capital. Besides that, they state how only accrual estimation error is a sign for earnings management and how estimation error is the most likely factor to lower earnings persistence.

Critique of Data used

The article uses data of the time frame from 1962 to 2009 of about 2,680 US publicly listed companies, which is a large time frame with a large group of companies and hence this sample is significant. For a serial correlation, which is one statistical method they are using, a large time frame is necessary, as it tries to find patterns in data (Kim, Kim and Ergün, 2015). All data is taken of the COMPUSTAT database, which is a reliable and commonly used data source and only relatively few mistakes in data can be detected (Hribar, 2016). Further, all financial service companies were excluded from the sample in order to enhance the significance of results. This approach is reasonable as accruals are a relatively small part of financial service company’s earnings and using data of those companies might blur overall results.

In general, the data used is valid, but it does have some limitations. Firstly, only data from US publicly listed companies is used, however, most companies in the US are not publicly listed but privately owned. Moreover, companies from outside the US were not considered and considering them could lead to different results as most countries use different accounting standards and legislation, which can have a large impact on reported earnings and accruals.

Critique of Methodology and Models

Allen, Larson and Sloan (2013) use an ex post perspective on accruals in contrast to Jones (1991), who uses an ex ante evaluation. Hence, their definition of accruals differs from Jones (1991) even though her definition is the standard definition. As accruals are an estimation of future benefits and obligations, the ex post approach, which looks at accruals in retro perspective by including Cash Flows of the period t+1, is a more effective perspective than the ex ante perspective because it includes known future data.

The original model, which they use to distinguish between good accruals and accrual estimation error, has been designed by Dechow and Dichev (2002) and modified by Bushman, Smith and Zhang (2011). Therefore, as it not a new model, it is tested and approved by further research and hence valid. Further, a qualitative research by Dichev et al. (2013), which interviews CFO’s on their thoughts about earnings quality, revealed that most of the CFO’s consider a large discrepancy between earnings, accruals and cash flow as a sign for poor earnings quality. Since the model used is based on this discrepancy, the study of Dichev et al. (2013) adds weight to the validity of the model. Also, they test the model with a sample that is known to have an accrual estimation error to verify it and the results are supporting their model used, too.

By using the Pearson and Spearman correlation coefficient, a valid and widely applied statistical model, which is more than a century old (Kim, Kim and Ergün, 2015) and which is a method to detect serial correlation, they further increase the validity of their research.

Despite all the positive aspects of their work, some limitations exist. Initially, their work does not consider factors such as corporate governance, industry environment, management compensation and auditor’s opinion, while only sales and employee growth are considered. According to Richardson et al. (2005), this is a limitation of the model they are using. Furthermore, Dichev et al. (2013) explore the importance of industry and macroeconomic influences on earnings quality and find that roughly 50% of earnings quality derive from external factors.

Additionally, their article examines stock returns and accrual reversals for the period t+1, but longer reversal periods are possible and might affect future earnings, too. Besides that, the long-term effect of accrual reversal and cash flows on stock returns with a period larger then t+1 is not investigated even though the long-term perspective is of high interest to many investors.

Moreover, accruals used by Allen, Larson and Sloan (2013) do not include non-current operating assets or investing accruals, but only working capital and current accruals. Those accruals, which they have not used, can have a big impact on earnings quality and thus on stock returns (Richardson et al., 2005). But they do not include those accruals because only current and working capital accruals reverse in the following year, whereas other accruals persist longer and therefore would be more difficult to measure. Thus, this is a limitation to their model as it only considers a short-term perspective.

Critique of Findings

They are first to find that accruals consist of two processes, where one process is about firm growth and the other about reversing changes in working capital, which is a large contribution to their field of research. Furthermore, they suggest that research in earnings management should separate between good accruals and accrual estimation error as mainly estimation error is a sign for earnings management. However, earnings management research (Alissa et al., 2013) does not only consider earnings management through accruals but also through real factors, which are not accounting related and within accruals it follows older models such as Jones’s (1991) model.


Excerpt out of 6 pages


A Critical Review of Allen, E., Larson, C.R. and Sloan, R.G. (2013). Accrual reversals, earnings and stock returns. Journal of Accounting and Economics, 56 (-), pp.113-255.
University of Westminster  (Westminster Business School)
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Accrual reversal, earnings, stock returns, accounting, earnings quality
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Johannes Laake (Author), 2016, A Critical Review of Allen, E., Larson, C.R. and Sloan, R.G. (2013). Accrual reversals, earnings and stock returns. Journal of Accounting and Economics, 56 (-), pp.113-255., Munich, GRIN Verlag, https://www.grin.com/document/365551


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