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Original Articles

Overvaluation and earnings management: Does the degree of overvaluation matter?

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Pages 121-146 | Published online: 02 Apr 2018
 

Abstract

We examine whether the choice of earnings management strategies employed by managers of overvalued firms depends on the degree of market overvaluation. By distinguishing between substantially overvalued (SOV) and relatively overvalued (ROV) firms, we find that SOV firms significantly inflate earnings using both accruals-based and real earnings management. In contrast, managers of ROV firms do not engage in accruals-based earnings management and their firms’ accounts tend to report higher discretionary expenses. The reported higher discretionary expenses of ROV firms are comparable to the discretionary expenses of firms in the expanding stage of their business life cycle, a pattern consistent with ROV firms increasing discretionary expenses to finance growth and hence justify the high market valuation. Overall, we show that the existing evidence on income-increasing earnings management by overvalued firms is mainly driven by the pressure to sustain the high market valuation of firms that are substantially overvalued.

Acknowledgements

The paper has greatly benefited from useful discussions and comments from Steven Young, William Rees, Andrew Stark, Brian Singleton-Green, Alan Goodacre, Martin Walker, Mark Hughes, Gordon Alexander, Lawrence Kryzanowski, Philip Gharghori, J. Henk Von Eije, Lorne Switzer, Marta Gomez-Puig, Christian Riis Flor, Alexander Subbotin, Victoria Krivogorsky, Edmund Keung, Benedikt Link, Roger Silvers, Jia Liu, Shen Yun, Tuan Ho. We would also like to thank the editors of the Accounting and Business Research and two anonymous reviewers for valuable suggestions and comments. All remaining errors are ours.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 In Section 4.4, we also use other cut-off points and show that the main findings do not qualitatively change.

2 Despite recent criticisms that accrual models, such as the one used in this paper, might be misspecified (Ball Citation2013, Owens et al. Citation2017), the modified-Jones model is still one of the most popularly used models to empirically proxy for earnings management. To mitigate the concerns about model misspecification, we replicate the main analysis using some variations of the modified-Jones model, including the following: (i) suppressing the intercept; (ii) using the balance sheet approach to estimate total accruals and (iii) using the original Jones model. Unreported results show that none of the main conclusions of the paper qualitatively change when different accrual models are used.

3 Roychowdhury (Citation2006) also develops measures for sales and production manipulation. As noted by Roychowdhury (Citation2006), sales and production manipulation would negatively affect abnormal cash flow, while a cut in discretionary expense to inflate earnings would lead to higher abnormal cash flow. The opposing effects make it difficult to interpret the results, especially if the three measures are employed together. In addition, production manipulation is only available to manufacturing firms. During our sample period, Rhodes-Kropf et al. (Citation2005) reports that manufacturing firms contribute only 14% of the UK’s Gross Value Added in 1997, and the contribution declines consistently to reach 9.9% in 2012. Therefore, constraining the sample to only manufacturing firms would impair the implications of the paper for non-manufacturing firms, which play a more important role in the UK. For these reasons, we do not examine sales and production manipulation in this paper.

4 See the Appendix for further details.

5 We acknowledge that our approach to identify SOV and ROV firms is somewhat arbitrary. Please see Section 4.4 for a robustness test to mitigate this concern.

6 Depending on the time period, we could refer to the Big 5 or 6 audit firms. Hereafter, in the interest of brevity, we will refer to the Big 4.

7 Since there are many control variables, an immediate concern is multicollinearity. shows that there is no considerable correlation between the explanatory variables. We also calculate the variance inflation factors (VIF) for all the predictors in equations (3) and (4). The unreported results show that none of the VIFs is above 3.92, except for the VIF for PABDEX (13.07) in equation (4), mostly due to its high correlation with aROA (Pearson correlation coefficient is 0.792, significant at the 1% level). To mitigate the concern, we re-estimate equation (4) without aROA on the right-hand side, and the main results do not qualitatively change (the VIF for PABDEX drops to 2.46). As a last check, equations (3) and (4) are re-estimated using only aSIZE, VB and aROA as control variables. The unreported results show that when using this specification, the main conclusions are qualitatively the same.

8 The data used to estimate the four-factor model, including the risk-free rate, returns on the market portfolio, size, book-to-market and momentum factors are sourced from the database made available by Gregory et al. (Citation2013).

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