Influence of earnings management on forecasting corporate failure

David Veganzones, Eric Séverin and Souhir Chlibi

International Journal of Forecasting, 2023, vol. 39, issue 1, 123-143

Abstract: This paper studies the relationship between corporate failure forecasting and earnings management variables. Using a new threshold model approach that separates samples into different regimes according to a threshold variable, the authors examine regimes to evaluate the prediction capacities of earnings management variables. By proposing this threshold model and applying it innovatively, this research reveals boundaries within which earnings management variables can yield superior corporate failure forecasting. The inclusion of earnings management variables in corporate failure models improves failure prediction capacities for firms that manipulate substantial earnings. Furthermore, an accruals-based variable improves predictions of failed firms, but the real activities-based variable improves predictions of non-failed firms. These findings highlight the importance of indicators of the magnitude of earnings management and the tools used to improve the performance of corporate failure models. The proposed model can determine the predictive power of particular explanatory variables to forecast corporate failure.

Keywords: Forecasting; Corporate failure; Earnings management; Threshold model; Finance (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:39:y:2023:i:1:p:123-143

DOI: 10.1016/j.ijforecast.2021.09.006

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