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Corporate governance and earnings management nexus: evidence from the UK and Egypt using neural networks

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Corporate governance and earnings management nexus: evidence from the UK and Egypt using neural networks. / Abdou, Hussein A.; Ellelly, Nouran N.; Elamer, Ahmed A.; Hussainey, Khaled; Yazdifar, Hassan.

In: International Journal of Finance and Economics, 29.08.2020.

Research output: Contribution to journalArticlepeer-review

Harvard

Abdou, HA, Ellelly, NN, Elamer, AA, Hussainey, K & Yazdifar, H 2020, 'Corporate governance and earnings management nexus: evidence from the UK and Egypt using neural networks', International Journal of Finance and Economics. https://doi.org/10.1002/ijfe.2120

APA

Abdou, H. A., Ellelly, N. N., Elamer, A. A., Hussainey, K., & Yazdifar, H. (2020). Corporate governance and earnings management nexus: evidence from the UK and Egypt using neural networks. International Journal of Finance and Economics. https://doi.org/10.1002/ijfe.2120

Vancouver

Abdou HA, Ellelly NN, Elamer AA, Hussainey K, Yazdifar H. Corporate governance and earnings management nexus: evidence from the UK and Egypt using neural networks. International Journal of Finance and Economics. 2020 Aug 29. https://doi.org/10.1002/ijfe.2120

Author

Abdou, Hussein A. ; Ellelly, Nouran N. ; Elamer, Ahmed A. ; Hussainey, Khaled ; Yazdifar, Hassan. / Corporate governance and earnings management nexus: evidence from the UK and Egypt using neural networks. In: International Journal of Finance and Economics. 2020.

Bibtex

@article{a19e277ebe274cf391cf54743bc63da0,
title = "Corporate governance and earnings management nexus: evidence from the UK and Egypt using neural networks",
abstract = "Using conventional regressions and Generalized Regression Neural Networks (GRNN), we examine the relationship between Corporate Governance (CG) and Earnings Management (EM). We also examine whether governance quality moderates the association between EM and CG for a sample of British and Egyptian companies. Our findings show that: (a) UK firms are likely to have lower levels of EM if they: have smaller boards, are dominated by independent outside directors, and have a low percentage of female directors; (b) Egyptian firms are likely to have lower levels of EM if they: have larger boards, are dominated by independent outside directors, and have a low percentage of female directors; (c) The governance quality (control of corruption) has a significant hidden effect on EM. Since our results provide empirical evidence that the board of directors plays a vital role in mitigating EM, these findings might lead to an improvement in the credibility of financial statements for investors in both the UK and Egypt. As policy implications, our findings inform regulators and policy-makers that corruption has a very strong hidden effect on EM and that they can deter EM by controlling the corruption level in their countries.",
keywords = "Earnings management, Corporate governance, Governance quality, Neural networks, Corruption",
author = "Abdou, {Hussein A.} and Ellelly, {Nouran N.} and Elamer, {Ahmed A.} and Khaled Hussainey and Hassan Yazdifar",
year = "2020",
month = aug,
day = "29",
doi = "10.1002/ijfe.2120",
language = "English",
journal = "International Research Journal of Finance and Economics",
issn = "1450-2887",
publisher = "EuroJournals, Inc.",

}

RIS

TY - JOUR

T1 - Corporate governance and earnings management nexus: evidence from the UK and Egypt using neural networks

AU - Abdou, Hussein A.

AU - Ellelly, Nouran N.

AU - Elamer, Ahmed A.

AU - Hussainey, Khaled

AU - Yazdifar, Hassan

PY - 2020/8/29

Y1 - 2020/8/29

N2 - Using conventional regressions and Generalized Regression Neural Networks (GRNN), we examine the relationship between Corporate Governance (CG) and Earnings Management (EM). We also examine whether governance quality moderates the association between EM and CG for a sample of British and Egyptian companies. Our findings show that: (a) UK firms are likely to have lower levels of EM if they: have smaller boards, are dominated by independent outside directors, and have a low percentage of female directors; (b) Egyptian firms are likely to have lower levels of EM if they: have larger boards, are dominated by independent outside directors, and have a low percentage of female directors; (c) The governance quality (control of corruption) has a significant hidden effect on EM. Since our results provide empirical evidence that the board of directors plays a vital role in mitigating EM, these findings might lead to an improvement in the credibility of financial statements for investors in both the UK and Egypt. As policy implications, our findings inform regulators and policy-makers that corruption has a very strong hidden effect on EM and that they can deter EM by controlling the corruption level in their countries.

AB - Using conventional regressions and Generalized Regression Neural Networks (GRNN), we examine the relationship between Corporate Governance (CG) and Earnings Management (EM). We also examine whether governance quality moderates the association between EM and CG for a sample of British and Egyptian companies. Our findings show that: (a) UK firms are likely to have lower levels of EM if they: have smaller boards, are dominated by independent outside directors, and have a low percentage of female directors; (b) Egyptian firms are likely to have lower levels of EM if they: have larger boards, are dominated by independent outside directors, and have a low percentage of female directors; (c) The governance quality (control of corruption) has a significant hidden effect on EM. Since our results provide empirical evidence that the board of directors plays a vital role in mitigating EM, these findings might lead to an improvement in the credibility of financial statements for investors in both the UK and Egypt. As policy implications, our findings inform regulators and policy-makers that corruption has a very strong hidden effect on EM and that they can deter EM by controlling the corruption level in their countries.

KW - Earnings management

KW - Corporate governance

KW - Governance quality

KW - Neural networks

KW - Corruption

U2 - 10.1002/ijfe.2120

DO - 10.1002/ijfe.2120

M3 - Article

JO - International Research Journal of Finance and Economics

JF - International Research Journal of Finance and Economics

SN - 1450-2887

ER -

ID: 21751445