The Determinants of Earnings Management in Indonesian Public Companies

Authors

  • Leonardo Davidsi Sipayung Universitas Negeri Makassar
  • Fitriana Universitas Negeri Makassar
  • Eureka Try Zarazwanty R Laega Universitas Negeri Makassar

DOI:

https://doi.org/10.26858/brain.v3i1.62

Keywords:

Accrual Earnings Management, Real Earnings Management, Linear Regression, Logistic Regression

Abstract

Indonesia is the biggest economy in the southeast Asia. This paper investigates the earnings management behavior of Indonesian public firms. The earnings management activities have been divided into three parts. Namely, accrual earnings management, real earnings management and fraud detection. Our findings indicate that earnings management activities are common for Indonesian firms. Firm size and asset growth have significant relationship associated, with various directions, with both accrual earnings management and real management activities for Indonesian firms. We also find that firm size, asset growth, ROE, and debt ratio consistently have significant relationship to real earnings management. In predicting the possibility of Indonesian firm to commit financial fraud, we find that manipulating gross margin, sales growth, depreciations and expenses related to sales and general administration is common seen from fraudulent firms in Indonesia.

Downloads

Download data is not yet available.

References

Anh, N. H., Linh, N. H., & Yoon, S. W. (2018), Earnings Manipulation Benchmark For Nonfinancial Listed Companies In Vietnamese Stock Market, working paper. https://ideas.repec.org/a/ibf/acttax/v10y2018i1p39-49.html

Beneish, M. D. (1999). The detection of earnings manipulation. Financial Analyst Journal. 55(5). 24-36.

Beneish, M. D., Lee, M.C.C., & Nichols, D.C. (2013). Earnings manipulation and expected returns. Financial Analyst Journal. 69(2). 57-82.

Chen, F., Chi, D., & Wang, Y. (2015). Detecting biotechnology industry‟s earnings management using Bayesian network, principle component analysis, back propagation neural network, and decision tree. Economic Modelling. 461-10.

Dechow, P. M., & Dichev, I. D. (2002). The quality of accruals and earnings: The role of accrual estimation errors. The Accounting Review, 77(s-1), 35–59.

Dechow, P.M., Sloan, R.G., & Sweeny, A.P. (1995). Detecting earnings management. The AccountingReview. 70(2). 193-225.

Ezazi, E. M., Ghotbi, F. S., & Ghotbi, S. F. (2013). Predicting earning management using RBF, ICA, and SVM in firms listed in Tehran security exchange. Asian Journal of Management Research. 4(1). 208-220.

Graham, J., Harvey, C., & Rajgopal, S. (2005). The economic implications of corporate financial reporting. Journal of Accounting and Economic. 40. 3-73.

Gunny, K. 2005. What are the consequences of real earnings management?. Working paper, University of California, Berkeley, CA.

Hewitt, M., Hodge, F., & Pratt, J. (2014). How the discover of accruals-based versus real earnings management affects investment decisions: The important of trust. Working paper.

Hoglund, H. (2012). Detecting earnings management with neural network. Expert System with Applications. 39(10). 9564-9570.

Hribar, P., & Collins, D. W. (2002). Errors in estimating accruals: implications for empirical research. Journal Account Res. 40(1). 105-134.

Kothari, S. P., Mizik. N., Roychowdhury, S. (2012). Managing for the moment: The role of real activity versus accruals earnings management in SEO valuation. Working paper.

Loftus, J. A., & Sin, S. (1997). The role of current and non-current accruals in the relation between stock returns and earnings. Accounting and Finance. 47(2). 147-161.

Marquardt, C. A., & Wiedman, C. I. (2004). The effect of earnings management on the value relevance of accounting information. Journal of Business Finance and Accoutning. 31(3/4). 297-332.

Namazi, M., & Maharluie, M. S. (2015). Detecting earnings management via statistical and neural network techniques. International Journal of Economics and Management Engineering. 9(7). 2520-2528.

Nguyen, Khanh. (2008). Financial statement fraud: Motives, methods, cases and detection. Boca Raton, Florida, USA.

Palepu, K. G., Healy, P. M., & Bernard, V. L. (2003). Business Analysis and Valuation Using Financial Statements: Text and Cases. 3rd ed. South-Western.

Priantara, Diaz. (2013). Fraud auditing and investigation. Mitra Wacana Media Publisher Jakarta, Indonesia.

Richardson, S. A., Sloan, R. G., Soliman, M. T., & Tuma, I. (2005). Accrual reliability, earnings persistence, and stock prices. Journal of Accounting and Economics. 39(3). 437-485.

Roychowdhury, S. (2006). Earnings management through real activities manipulation. Journal of Accounting and Research. 42(33). 335-370.

Rezaee, Zabihollah. (2002). Financial statement fraud: prevention and detection. John Wiley & Sons, Inc. New York.

Schipper, K. (1989). Earning Management. Accounting Horizon. 3. 91-106.

Sloan, R. G. (1996). Do Stock Price Fully Reflect Information in Accruals and Cash Flows about Future Earnings? The Accounting Review. 71(3). 289-315.

Spohr, J. (2004). Earnings Management and IPO-Evidence from Finland. Liiketaloudellinen aikakauskirja2. 157-172.

Tarjo & Herawati, N. (2015). Application of beneish m-score models and data mining to detect financial fraud. Procedia-Social and Behavioral Sciences. 211. 924-930.

Zang, A. Z. 2006. Evidence on the tradeoff between real manipulation and accrual manipulation. Working paper. Duke University.

Downloads

Published

2026-06-06

How to Cite

Sipayung, L. D., Fitriana, & Laega, E. T. Z. R. (2026). The Determinants of Earnings Management in Indonesian Public Companies. Business Research and Administration Innovation, 3(1), 194–209. https://doi.org/10.26858/brain.v3i1.62