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Kliestik Tomas (University of Zilina, Slovak Republic), Valaskova Katarina (University of Zilina, Slovakia), Nica Elvira (Bucharest Academy of Economic Studies, Romania), Kovacova Maria (University of Zilina, Slovak Republic), Lazaroiu George (Spiru Haret University, Romania)
Advanced Methods of Earnings Management : Monotonic Trends and Change-Points under Spotlight in the Visegrad Countries
Oeconomia Copernicana, 2020, vol. 11, nr 2, s. 371-400, aneks, bibliogr. 67 poz.
Finanse przedsiębiorstwa, Zarządzanie zyskami
Enterprise finance, Earnings management
JEL Classification: C22, G32, G40
This paper was supported by the Slovak Research and Development Agency under Grant number APVV-17-0546: Variant Comprehensive Model of Earnings Management in Conditions of the Slovak Republic as an Essential Instrument of Market Uncertainty Reduction.
Kraje Grupy Wyszehradzkiej
Visegrad Group countries
Research background: Enterprises manage earnings in an effort to balance their profit fluctuations to provide increasingly consistent earnings in every reporting period. Earnings management is legal and very effective method of accounting techniques and may be used to obtain specific objectives of the enterprises involving the manipulation of accruals. Therefore, there is a need to analyze it in the context of group of countries, while the issue of their detection in the new ways appears.
Purpose of the article: The analysis of annual earnings before interest and taxes (EBIT) of 5,640 enterprises from the Visegrad Four during the period 2009-2018 confirms that the development of earnings management in these countries is not a randomness. Thus, the aim of this article is to determine the existence of positive trend in earnings management and to detect the change-point in its development for each Visegrad country.
Methods: Grubbs test, Mann-Kendall trend test and Buishand test were used as appropriate statistical methods. Mann-Kendall test identifies significant monotonic trend occurrence in earnings manipulation in every country. Buishand test indicates significant years, which divides the development of EBIT into two homogenous groups with individual central lines.
Findings & Value added: Based on the statistical analysis applied, we rejected randomness in the managing of earning, but we determined the trend of its increasing. The positive earnings manipulation was not homogenous in the analyzed period, however, a change-point was defined. Year 2014 was identified as a break-point for Slovak, Polish and Hungarian enterprises considering the earnings manipulation. Year 2013 was detected as a change-point in Czech enterprises. The methodical approach used may be very helpful for researchers from other countries to determine, detect and understand earnings management as well as for the investors to make decisions based on a specificities of an individual country. (original abstract)
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  1. Agha, O. M. A. M., Bağçacı, S. Ç., & Şarlak, N. (2017). Homogeneity analysis of precipitation series in North Iraq. IOSR Journal of Applied Geology and Geophysics, 5(03). doi: 10.9790/0990-0503025763.
  2. Ahmad, N. H., & Deni, S. M. (2013). Homogeneity test on daily rainfall series for Malaysia. Matematika, 29. doi: 10.11113/matematika.v29.n.586.
  3. Archibald, T. R. (1967). The return to straight-line depreciation: an analysis of a change in accounting method. Journal of Accounting Research. doi: 10.2307/2489918.
  4. Ashander, L., Kliestikova, J., Durana, P., & Vrbka, J. (2019). The decision-making logic of big data algorithmic analytics. Contemporary Readings in Law and Social Justice, 11(1). doi:10.22381/CRLSJ11120199.
  5. Beidleman, C. R. (1973). Income smoothing: the role of management. Accounting Review, 48(4).
  6. Beneish, M. D. (1997). Detecting GAAP violation: implications for assessing earnings management among firms with extreme financial performance. Journal of Accounting and Public Policy, 16(3). doi: 10.1016/S0278-4254(97)00023-9.
  7. Buishand, T. A. (1982). Some methods for testing the homogeneity of rainfall records. Journal of Hydrology, 58(1-2). doi: 10.1016/0022-1694(82)90066-X.
  8. Buishand, T. A. (1984). Tests for detecting a shift in the mean of hydrological time series. Journal of Hydrology, 73(1-2). doi: 10.1016/0022-1694(84)90032-5.
  9. Chen, T., Xing, J., & Huo, X. D. (2020). Study on nonparametric statistic method applied to nuclear criticality safety analysis of spent fuel rack. Annals of Nuclear Energy, 137. doi: 10.1016/j.anucene.2019.107065.
  10. Copeland, R. M. (1968). Income smoothing. Journal of Accounting Research. doi: 10.2307/2490073.
  11. DeAngelo, L. E. (1986). Accounting numbers as market valuation substitutes: a study of management buyouts of public stockholders. Accounting Review, 61(3).
  12. Dechow, P. M., Richardson, S. A., & Tuna, I. (2003). Why are earnings kinky? An examination of the earnings management explanation. Review of Accounting Studies, 8(2-3). doi: 10.1023/A:1024481916719.
  13. Dechow, P. M., Sloan, R. G., & Sweeney, A. P. (1995). Detecting earnings management. Accounting Review, 4.
  14. Dopuch, N., & Drake, D. F. (1966). The effect of alternative accounting rules for nonsubsidiary investments. Journal of Accounting Research. doi: 10.2307/2490182.
  15. Durana, P., Kral, P., Stehel, V., Lazaroiu, G., & Sroka, W. (2019). Quality culture of manufacturing enterprises: a possible way to adaptation to Industry 4.0. Social Sciences, 8(4). doi: 10.3390/socsci8040124.
  16. Fields, T. D., Lys, T. Z., & Vincent, L. (2001). Empirical research on accounting choice. Journal of Accounting and Economics, 31(1-3). doi: 10.1016/S0165-4101(01)00028-3.
  17. Garcia, F. A. A. (2012). Tests to identify outliers in data series. Rio de Janeiro: Pontifical Catholic University of Rio de Janeiro, Industrial Engineering Department.
  18. Gavurova, B., Belas, J., Kocisova, K., Kliestik, T. (2017). Comparison of selected methods for performance evaluation of Czech and Slovak commercial banks. Journal of Business Economics and Management, 18(5).
  19. Ghosh, D., & Vogt, A. (2012). Outliers: an evaluation of methodologies. In: Joint Statistical Meetings. San Diego: American Statistical Association.
  20. Gordon, M. J. (1964). Postulates, principles and research in accounting. Accounting Review, 39(2).
  21. Gordon, M. J., Horwitz, B. N., & Meyers, P. T. (1966). Accounting measurements and normal growth of the firm. Research in Accounting Measurement, 23(4).
  22. Grubbs, F. E. (1950). Sample criteria for testing outlying observations. Annals of Mathematical Statistics, 21(1).
  23. Hansen, M. H., Madow, W. G., & Tepping, B. J. (1983). An evaluation of modeldependent and probability-sampling inferences in sample surveys. Journal of the American Statistical Association, 8(384). doi: 10.1080/01621459.1983.10477018.
  24. Hayhoe, T., Podhorska, I., Siekelova, A., & Stehel, V. (2019). Sustainable manufacturing in Industry 4.0: cross-sector networks of multiple supply chains, cyber-physical production systems, and AI-driven decision-making. Journal of Self-Governance and Management Economics, 7(2). doi:10.22381/JSME7220195.
  25. Healy, P. (1985). The impact of bonus schemes on the selection of accounting principles. Journal of Accounting and Economics, 7(1-3).
  26. Healy, P. M., & Wahlen, J. M. (1999). A review of the earnings management literature and its implications for standard setting. Accounting Horizons, 13(4). doi: 10.2308/acch.1999.13.4.365.
  27. Hepworth, S. R. (1953). Smoothing periodic income. Accounting Review, 28(1).
  28. Hirsch, R. M., & Slack, J. R. (1984). A nonparametric trend test for seasonal data with serial dependence. Water Resources Research, 20(6). doi: 10.1029/WR020i006p00727.
  29. Hirsch, R. M., Slack, J. R., & Smith, R. A. (1982). Techniques of trend analysis for monthly water quality data. Water Resources Research, 18(1). doi: 10.1029/WR018i001p00107.
  30. Höglund, H. (2012). Detecting earnings management with neural networks. Expert Systems with Applications, 39(10). doi: 10.1016/j.eswa.2012.02.096.
  31. Höglund, H. (2013). Estimating discretionary accruals using a grouping genetic algorithm. Expert Systems with Applications, 40(7). doi: 10.1016/j.eswa.2012.10.048.
  32. Hollowell, J. C., Rowland, Z., Kliestik, K., Kliestikova, J. & Dengov, V. V. (2019). Customer loyalty in the sharing economy platforms: how digital personal reputation and feedback systems facilitate interaction and trust between strangers. Journal of Self-Governance and Management Economics, 7(1). doi: 10.22381/JSME7120191.
  33. Jones, J. J. (1991). Earnings management during import relief investigations. Journal of Accounting Research, 29(2). doi: 10.2307/2491047.
  34. Kang, H. M., & Yusof, F. (2012). Homogeneity tests on daily rainfall series. International Journal of Contemporary Mathematical Sciences, 7(1).
  35. Kanovsky, M. (2018). The research effectivity of Slovak universities: quantitative analysis of trends 2008-2017. Slovak Sociological Review, 50(4). doi: 10.31577/sociologia.2018.50.4.17.
  36. Kasznik, R. (1999). On the association between voluntary disclosure and earnings management. Journal of Accounting Research, 37(1). doi: 10.2307/2491396.
  37. Kendall, M. G. (1948). Rank Correlation Methods. Oxford: Griffin.
  38. Key, K. G. (1997). Political cost incentives for earnings management in the cable television industry. Journal of Accounting and Economics, 23(3). doi: 10.1016/S0165-4101(97)00012-8.
  39. Khambhammettu, P. (2005). Appendix Mann-Kendall analysis for the fort ord site. Annual Groundwater Monitoring Report. HydroGeoLogic, Inc.
  40. Kliestik, T., Belas, J., Valaskova, K., Nica, E., & Durana, P. (2020). Ethicality of earnings management: the evidence of earnings smoothing and inflating. Economic Research-Ekonomska Istraživanja (forthcoming).
  41. Kothari, S. P., Leone, A. J., & Wasley, C. E. (2005). Performance matched discretionary accrual measures. Journal of Accounting and Economics, 39(1). doi: 10.1016/j.jacceco.2004.11.002.
  42. Kowo, S. A., & Akinbola, O. A. (2019). Strategic leadership and sustainability performance of small and medium enterprises. Ekonomicko-manazerske Spektrum, 13(1). doi: 10.26552/ems.2019.1.38-50.
  43. Lafferty, C. (2019). Sustainable internet-of-things-based manufacturing systems: Industry 4.0 wireless networks, advanced digitalization, and big data-driven smart production. Economics, Management, and Financial Markets, 14(4). doi: 10.22381/EMFM14420192.
  44. Ludbrook, F., Frajtova Michalikova, K., Musova, Z., & Suler, P. (2019). Business models for sustainable innovation in Industry 4.0: smart manufacturing processes, digitalization of production systems, and data-driven decision making. Journal of Self-Governance and Management Economic, 7(3).
  45. Mann, H. B. (1945). Nonparametric tests against trend. Econometrica: Journal of the Econometric Society. doi: 10.2307/1907187.
  46. McKee, T. E. (2005). Earnings management: an executive perspective. Indiana: Thomson.
  47. McNichols, M. F. (2000). Research design issues in earnings management studies. Journal of Accounting and Public Policy, 19(4-5). doi: 10.1016/S0278-4254(00)00018-1.
  48. McNichols, M., & Wilson, G. P. (1988). Evidence of earnings management from the provision for bad debts. Journal of Accounting Research. doi: 10.2307/2491176.
  49. Meals, D. W., Spooner, J., Dressing, S. A., & Harcum, J. B. (2011). Statistical analysis for monotonic trends, Tech Notes, 6.
  50. Michalkova, L., Frajtova Michalikova, K., & Tănase, A. (2019). Factor analysis and its application in innovation management within manufacturing enterprises in Romania. Ekonomicko-manazerske Spektrum, 13(2). doi: 10.26552/ems.2019.2. 37-45.
  51. Nadanyiova, M., & Durana, P. (2019). Corporate social responsibility as a brand value-enhancing tool. In 8th International scientific symposium economy of eastern Croatia - vision and growth. Osijek: University of Josip Juraj Strossmayer.
  52. Nagy, L. (2016). Ratio indicators database of HGN1 model for measuring enterprise performance. Journal of Knowledge Society, 4(2).
  53. Plumpton, D. (2019). Cyber-physical systems, internet of things, and big data in Industry 4.0: digital manufacturing technologies, business process optimization, and sustainable organizational performance. Economics, Management, and Financial Markets, 14(3). doi:10.22381/EMFM14320193.
  54. Pohlert, T. (2020). Non-parametric trend tests and change-point detection. CC BY-ND.
  55. Rahman, A., Rozsa, Z., & Cepel, M. (2018). Trade credit and bank finance - evidence from the Visegrad Group. Journal of Competitiveness, 10(3).
  56. Ronen, J., & Yaari, V. (2008). Earnings management. Emerging insights, theory, practice, and research. New York: Springer.
  57. Rybicka, K., & Rybicki, P. (2018). Chosen aspects of it systems in management and accounting in companies under globalization. Ekonomicko-manazerske spektrum, 12(2).
  58. Saona, P., Muro, L., & Alvarado, M. (2020). How do the ownership structure and board of directors' features impact earnings management? The Spanish case. Journal of International Financial Management & Accounting, 31(1). doi: 10.1111/jifm.12114.
  59. Schipper, K. (1989). Commentary on earnings management. Acounting Horizon, 11.
  60. Solak, M. K. (2009). Detection of multiple outliers in univariate data sets. Paper SP06-2009. New Jersey: Schering.
  61. Strakova, L. (2020). Earnings management in global background. In SHS Web of Conferences (74, 01032). EDP Sciences. doi: 10.1051/shsconf/20207401032.
  62. Svabova, L., & Durica, M. (2019). Being an outlier: a company non-prosperity sign? Equilibrium. Quarterly Journal of Economics and Economic Policy, 14(2). doi: 10.24136/eq.2019.017.
  63. Svabova, L., & Michalkova, L. (2018). Pre-processing of data in earnings management. Business Economics and Management, 3.
  64. Svabova, L., Adamko, P., & Popescu, G. H. (2019). The analysis of various earnings levels in Visegrad group companies. In Proceedings of the 33rd international business information management association conference. IBIMA.
  65. Tuffnell, C., Kral, P., Durana, P., & Krulicky, T. (2019). Industry 4.0-based manufacturing systems: smart production, sustainable supply chain networks, and real-time process monitoring. Journal of Self-Governance and Management Economics, 7(2). doi:10.22381/JSME7220191.
  66. Valaskova, K., Kliestik, T., & Kovacova, M. (2019). Assessment of selected models of earnings management in economic conditions of Slovakia. In: Proceedings of the 33rd international business information management association conference. IBIMA.
  67. White, G. E. (1970). Discretionary accounting decisions and income normalization. Journal of Accounting Research, 8(2). doi: 10.2307/2490111.
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