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Information Journal Paper

Title

Bankruptcy Prediction Modeling Using the Variables of Earnings Management

Pages

  131-152

Abstract

 The purpose of this research is to modeling and predicts bankruptcy using real and Accrual Earnings Management variables. Based on this, using logistic regression, the accuracy of bankruptcy models before and after adding Earning Management variables were estimated and compared. So, a sample consisting of 1287 years-company during the period 2006 to 2018 has been selected from the companies of Tehran Stock Exchange. The results showed that the predictability power of Altman, Springgate and Zimsky bankruptcy models has increased significantly after adding Accrual Earnings Management variables compared to the initial models. The results also show that the parameters of real earning Management weaken the predictability of Altman, Springgate and Zimsky models. Based on the results, accountants, managers, and economic planners are advised to pay special attention to the phenomenon of corporate Earning Management in order to make their decisions better.

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    APA: Copy

    Ghatebi, Moslem, KHODADADI, VALI, JORJORZADEH, ALIREZA, & Kaab Omeir, Ahmad. (2020). Bankruptcy Prediction Modeling Using the Variables of Earnings Management. ECONOMIC MODELLING, 14(2 (50) ), 131-152. SID. https://sid.ir/paper/397462/en

    Vancouver: Copy

    Ghatebi Moslem, KHODADADI VALI, JORJORZADEH ALIREZA, Kaab Omeir Ahmad. Bankruptcy Prediction Modeling Using the Variables of Earnings Management. ECONOMIC MODELLING[Internet]. 2020;14(2 (50) ):131-152. Available from: https://sid.ir/paper/397462/en

    IEEE: Copy

    Moslem Ghatebi, VALI KHODADADI, ALIREZA JORJORZADEH, and Ahmad Kaab Omeir, “Bankruptcy Prediction Modeling Using the Variables of Earnings Management,” ECONOMIC MODELLING, vol. 14, no. 2 (50) , pp. 131–152, 2020, [Online]. Available: https://sid.ir/paper/397462/en

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