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Performance shocks and misreporting

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  • Gerakos, Joseph
  • Kovrijnykh, Andrei
Abstract
We propose a parsimonious stochastic model of reported earnings that links misreporting to performance shocks. Our main analytical prediction is that misreporting leads to a negative second-order autocorrelation in the residuals from a regression of current earnings on lagged earnings. We also propose a stylized dynamic model of earnings manipulation and demonstrate that both earnings smoothing and target-beating considerations result in the same predictions of negative second-order autocorrelations. Empirically, we find that the distribution of this measure is asymmetric around zero with 27% of the firms having significantly negative estimates. Using this measure, we specify a methodology to estimate the intensity of misreporting and to create estimates of unmanipulated earnings. Our estimates of unmanipulated earnings are more correlated with contemporaneous returns and have higher volatility than reported earnings. With respect to economic magnitude, we find that, in absolute terms, median misreporting is 0.7% of total assets. Moreover, firms in our sample subject to SEC AAERs have significantly higher estimates of manipulation intensity.

Suggested Citation

  • Gerakos, Joseph & Kovrijnykh, Andrei, 2013. "Performance shocks and misreporting," Journal of Accounting and Economics, Elsevier, vol. 56(1), pages 57-72.
    • Handle: RePEc:eee:jaecon:v:56:y:2013:i:1:p:57-72
    DOI: 10.1016/j.jacceco.2013.04.001
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    2. Andrew B. Jackson, 2018. "Discretionary Accruals: Earnings Management ... or Not?," Abacus, Accounting Foundation, University of Sydney, vol. 54(2), pages 136-153, June.
    3. Boahen, Eric & Mamatzakis, Emmanuel, 2016. "Do Religion, Corporate Governance and BIG 4 Audit Interactions Affect Misclassification?," MPRA Paper 76804, University Library of Munich, Germany.
    4. Yim, Andrew, 2013. "Mixture and Continuous 'Discontinuity' Hypotheses: An Earnings Management Model with Auditor-Required Adjustment," MPRA Paper 44702, University Library of Munich, Germany.
    5. Theodore E. Christensen & Adrienna Huffman & Melissa F. Lewis‐Western & Rachel Scott, 2022. "Accruals earnings management proxies: Prudent business decisions or earnings manipulation?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(3-4), pages 536-587, March.
    6. Matthias Breuer & David Windisch, 2019. "Investment Dynamics and Earnings‐Return Properties: A Structural Approach," Journal of Accounting Research, Wiley Blackwell, vol. 57(3), pages 639-674, June.
    7. Anastasia A. Zakolyukina, 2018. "How Common Are Intentional GAAP Violations? Estimates from a Dynamic Model," Journal of Accounting Research, Wiley Blackwell, vol. 56(1), pages 5-44, March.
    8. Lewellen, Jonathan & Resutek, Robert J., 2019. "Why do accruals predict earnings?," Journal of Accounting and Economics, Elsevier, vol. 67(2), pages 336-356.
    9. Thomas R. Dyckman & Stephen A. Zeff, 2015. "Accounting Research: Past, Present, and Future," Abacus, Accounting Foundation, University of Sydney, vol. 51(4), pages 511-524, December.
    10. Bo Chen & Bin Zhang & Hua-qing Wu, 2015. "Misreporting behaviour in iterated prisoner's dilemma game with combined trust strategy," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(1), pages 31-43, January.
    11. Nguyet T. M. Nguyen & Abdullah Iqbal & Radha K. Shiwakoti, 2022. "The context of earnings management and its ability to predict future stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 59(1), pages 123-169, July.
    12. Du, Kai, 2019. "Investor expectations, earnings management, and asset prices," Journal of Economic Dynamics and Control, Elsevier, vol. 105(C), pages 134-157.
    13. Dongshin Kim & Dongkuk Lim & Jonathan A. Wiley, 2023. "Narrative Investment-Risk Disclosure & REIT Investment," The Journal of Real Estate Finance and Economics, Springer, vol. 66(2), pages 542-567, February.
    14. Christian Leuz & Peter D. Wysocki, 2016. "The Economics of Disclosure and Financial Reporting Regulation: Evidence and Suggestions for Future Research," Journal of Accounting Research, Wiley Blackwell, vol. 54(2), pages 525-622, May.
    15. Robert Bloomfield & Mark W. Nelson & Eugene Soltes, 2016. "Gathering Data for Archival, Field, Survey, and Experimental Accounting Research," Journal of Accounting Research, Wiley Blackwell, vol. 54(2), pages 341-395, May.
    16. Ian D. Gow & David F. Larcker & Peter C. Reiss, 2016. "Causal Inference in Accounting Research," Journal of Accounting Research, Wiley Blackwell, vol. 54(2), pages 477-523, May.
    17. Andrew B. Jackson & Brian R. Rountree & Konduru Sivaramakrishnan, 2017. "Earnings co-movements and earnings manipulation," Review of Accounting Studies, Springer, vol. 22(3), pages 1340-1365, September.
    18. Matthias Breuer & Harm H. Schütt, 2023. "Accounting for uncertainty: an application of Bayesian methods to accruals models," Review of Accounting Studies, Springer, vol. 28(2), pages 726-768, June.
    19. Nezlobin, Alexander & Sloan, Richard G. & Giedt, Jenny Zha, 2022. "Construct validity in accruals quality research," LSE Research Online Documents on Economics 112165, London School of Economics and Political Science, LSE Library.

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