Pavol Durana

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Articles (14)

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Various models have been created all around the world to identify enterprises that manipulate their earnings. These earnings management techniques aid businesses in enhancing their financial performance or gaining some competitive advantages. The primary goal of this article was to identify the firm-specific characteristics that affect how businesses manage their earnings using a sample of 15,716 businesses from various economic sectors in the Slovak environment during a 3 year period. The level of earnings management was measured by discretionary accruals using the Kasznik model. In this paper, a correspondence analysis using the chi-square distance measure was applied to find the dependence between the earnings management practices and firm-specific features (firm size, legal form, and sectoral classification). The results of the study indicate that aggressive (income-increasing) earnings management practices are typical of small enterprises with a public limited ownership structure, mostly in sectors R and M (using the NACE sectoral classification). Conservative (income decreasing) practices can be observed in enterprises in the sectors J or F, and they are also used by medium-sized enterprises and those with private limited ownership structure. The results revealed that large enterprises do not tend to manipulate their earnings, as well as enterprises operating in sector K. The insights of this study may provide important and useful information for shareholders and regulators in evaluating determinants that are effective in mitigating earnings management practices. Authorities, regulators, analysts, and auditors may find the importance of the discovered variances helpful in identifying various strategies and techniques for earnings manipulation that may differ among industries according to their typical characteristics.

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Collaborators (4)

Jaroslav Belas

University of Information Technology and Management in Rzeszow

POLAND
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Roman Blazek

-

CZECH REPUBLIC
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Dominika Gajdosikova

-

SLOVAKIA
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Martin Cepel

Associate Professor

-

CZECH REPUBLIC
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