Türk Bankacılık Sektöründe Kar Yönetimi Uygulamaları: Borsa İstanbul Örneği

Kar yönetimi, şirketlerin hedeflenen dönem karına ulaşmak için genel kabul görmüş muhasebe ilkeleri, muhasebe standartları ve yasal düzenlemelerdeki esnekliklerden faydalanarak finansal sonuçlarını gerçeğe uygun olmayan bir şekilde raporlamasıdır. Bu çalışmada ekonomik ve finansal sistem içerisinde en önemli role sahip olan bankaların kar yönetimi uygulamalarına başvurup başvurmadıklarının panel veri analizi yöntemiyle tespit edilmesi amaçlanmaktadır. Ayrıca kredi kayıp karşılıkları ile sürdürülen faaliyetler vergi öncesi kar değişkenleri arasındaki nedensellik ilişkisi hem panel geneli hem de panel birimleri için Emirmahmutoğlu ve Köse (2011) Panel Granger Nedensellik Testi kullanılmıştır. Bu amaç doğrultusunda, Borsa İstanbul (BİST)’da işlem gören kamu, özel ve yabancı sermayeli on ticari bankanın 2009-2019 yılları arasındaki çeyrek dönemlik faaliyet raporları örneklem olarak ele alınmıştır. Bankaların anılan faaliyet yıllarını kapsayan finansal tablolarındaki aktif toplamları, krediler ve alacaklar, takipteki krediler, kredi kayıp karşılıkları, sürdürülen faaliyetler öncesi vergi karı veya zararı, net dönem karı veya zararı kalemlerinin tutarları ve ayrıca gayri safi yurtiçi hasıla ile enflasyon oranları makro değişkenler olarak modelde yer almaktadır. Elde edilen bulgulara göre, seçilmiş bankaların kredi kayıp karşılıkları üzerinde; kredi kayıp karşılıklarının kendi gecikmeli değeri, sürdürülen faaliyetler öncesi vergi karı veya zararı, sorunlu krediler ve aktif büyüklüğü istatistiksel olarak pozitif ve anlamlı, sermaye yeterlilik oranı ve ekonomik büyüme oranı ise negatif ve anlamlı bir etkiye sahiptir. Kredi kayıp karşılıkları üzerinde; dönem karı veya zararı, kredi-mevduat oranı ve enflasyon oranı değişkenleri ise istatistiksel olarak anlamlı bir etkiye sahip değildir.

Anahtar Kelimeler:

Banka, Borsa İstanbul, Muhasebe Manipülasyonu, Kar Yönetimi, Kredi Kayıp Karşılıkları

Earnings Management Practices In Turkish Banking Sector: The Case Of Borsa İstanbul

Earnings management are defined as the unfair values reporting of financial results by manipulating accounting in line with flexibility the generally accepted accounting principles, accounting standards and legal regulations in order to reach the targeted profit or loss for the period. This study is aimed to determine whether banks, having the most important role in the economic and financial system, apply to earnings management practices by panel data analysis method. Also, Emirmahmutoğlu and Köse (2011) Panel Granger Causality Test is used for the causality relationship between loan loss provisions and the variables of continuing operations and net profit/loss for both the panel in general and the panel units. For this purpose, quarterly financial reports of ten public, private and foreign capital commercial banks traded in Borsa Istanbul (BIST) between 2009-2019 are taken as a sample. Total assets, loans and receivables, non-performing loans, loan loss provisions, profit or loss before taxes on continuing operations and net profit/loss. According to the findings on loan loss provisions of selected banks, the lagged value of loan loss provisions, profit or loss before taxes on continuing operations, non-performing loans and asset size have a statistically positive and significant effect while capital adequacy ratio and economic growth rate have a negative and significant effect. Over the variable of loan loss provisions, profit or loss for the period, loan-deposit ratio and inflation rate have not a statistically significant effect.

Keywords:

Bank, Borsa İstanbul, Accounting Manipulation, Earnings Management, Loan Loss Provisions,

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Abdullah, H., Bujang, I., ve Ahmad, I. (2013). Loan loss provisions and earnings management in Malaysian banking industry. Global Journal of Business and Social Science Review, 1(1), 93-104.
Acar, M. (2017). Türk finans sektörünün kar yönetimi ve karların süreğenliği üzerinden kar kalitesinin incelenmesi. Bankacılar Dergisi, 28(102), 37-62.
Ahmed, A. S., Takeda, C., ve Thomas, S. (1999). Bank loan loss provisions: A reexamination of capital management, earnings management and signaling effects. Journal of Accounting and Economics, 28(1), 1-25.
Altuk Özden, E., ve Ataman, B. (2014). Kar yönetimi ve yöntemleri. Marmara Üniversitesi Öneri Dergisi. 11(42), 13-25.
Anandarajan, A., Hasan, I., ve McCarthy, C. (2005). The use of loan loss provisions for earnings, capital management and signalling by Australian banks. Erişim Adresi: https://research.library.fordham.edu/cgi/viewcontent.cgi?article=1004vecontext=crif_working_papers
Anderson, T. W., ve Hsiao, C. (1981). Estimation of dynamic models with error components. Journal of the American Statistical Association. 76(375), 598-606.
Arellano, M., ve Bond, S. (1991). Some tests of speciﬁcation for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277-297.
Arellano, M., ve Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29-51.
Asteriou, D., ve Hall, S. G. (2011). Applied econometrics. London: Palgrave.
Beatty, A., Chamberlain, S. L., ve Magliolo, J. (1995). Managing financial reports of commercial banks: The influence of taxes, regulatory capital and earnings. Journal of Accounting Research, 33(2), 231-261.
Bhat, V. N. (1996). Banks and income smoothing: An empirical analysis. Applied Financial Economics, 6(6), 505-510.
Binder, M., Hsiao, C., ve Pesaran, M. H. (2005). Estimation and inference in short panel vector autoregressions with unit roots and cointegration. Econometric Theory, 21(4), 795–837.
Blundell, R., Bond, S., ve Windmeijer, F. (2001). Estimation in dynamic panel data models: Improving on the performance of the standard GMM estimator. Working Papers No. W00/12. London: Institute for Fiscal Studies (IFS). Erişim Adresi: http://hdl.handle.net/10419/90837
Bond, S. R., Hoeffler, A., ve Temple, J. R. (2001). GMM estimation of empirical growth models. Erişim Adresi: https://jontemple.org.uk/wp-content/uploads/2020/06/bht10.pdf
Bun, M. J. G., ve Windmeijer, F. (2010). The weak instrument problem of the system GMM estimator in dynamic panel data models. Econometrics Journal, 13(1), 95–126.
Cheng, Q., Warfield, T., ve Ye, M. (2011). Equity incentives and earnings management: Evidence from the banking industry. Journal of Accounting, Auditing and Finance, 26(2), 317-349.
Chudik, A., ve Pesaran, M. H. (2021). An augmented Anderson–Hsiao estimator for dynamic short-t panels. Econometric Reviews, 41(4), 1-32.
Collins, J. H., Shackelford, D. A., ve Wahlen, J. M. (1995). Bank differences in the coordination of regulatory capital, earnings, and taxes. Journal of Accounting Research, 33(2), 263-291.
Copeland, R. M. (1968). Income smoothing. Journal of Accounting Research, 6, 101-116.
Cornett, M. M., McNutt, J. J., ve Tehranian, H. (2009). Corporate governance and earnings management at large US bank holding companies. Journal of Corporate Finance, 15(4), 412-430.
Dechow, P. M., ve Skinner, D. J. (2000). Earnings management: Reconciling the views of accounting academics, practitioners and regulators. Accounting Horizons, 14(2), 235-250.
Degeorge, F., Patel, J., ve Zeckhauser, R. (1999). Earnings management to exceed thresholds. The Journal of Business, 72(1), 1-33.
Dong, X., Liu, J., ve Hu, B. (2012). Research on the relationship of commercial bank’s loan loss provision and earning management and capital management. Journal of Service Science and Management, 5, 171-179.
Emirmahmutoğlu, F., ve Köse, N. (2011). Testing for Granger causality in heterogeneous mixed panels. Economic Modelling, 28(3), 870-876.
Fernando, W. D. I., ve Ekanayake, E. M. N. N. (2015). Do commercial banks use loan loss provisions to smooth their income? Empirical evidence from Sri Lankan commercial banks. Journal of Finance and Bank Management, 3(1), 167-179.
Fukase, E. (2010). Revisiting linkages between openness, education and economic growth: System GMM approach. Journal of Economic Integration, 25(1), 193-222.
Greenawalt, M. B., ve Sinkey, J. F. (1988). Bank loan-loss provisions and the income-smoothing hypothesis: An empirical analysis 1976–1984. Journal of Financial Services Research, 1(4), 301-318.
Grougiou, V., Leventis, S., Dedoulis, E., ve Owusu-Ansah, S. (2014). Corporate social responsibility and earnings management in US banks. Accounting Forum, 38(3), 155-169.
Healy, P. M. (1985). The effect of bonus schemes on accounting decisions. Journal of Accounting and Economics, 7(1-3), 85-107.
Healy, P. M., ve Wahlen, J. M. (1999). A review of the earnings management literature and its implications for standard setting. Accounting Horizons, 13(4), 365-383.
Jiraporna, P., Miller, G. A., Yoon, S. S., ve Kim, Y. S. (2008). Is earnings management opportunistic or beneficial? An agency theory perspective. International Review of Financial Analysis, 17(3), 622-634.
Jung, H., Kwon, H. U., ve Jeon, G. (2015). An alternative system GMM estimation in dynamic panel models. Journal of Economic Theory and Econometrics, 26(2), 57-78.
Kasznik, R. (1999). On the association between voluntary disclosure and earnings management. Journal of Accounting Research, 37(1), 57-81.
Kepsu, M. (2012). Earnings management in the process of preparing corporate financial reports. Sarja/Series A-3. Turku School of Economics. Erişim Adresi: https://www.utupub.fi/bitstream/handle/10024/77180/Ae3_2012.pdf?sequence=1
Koch, T. W., ve Wall, L. D. (2000). The use of accruals to manage reported earnings: Theory and evidence. Federal Reserve Bank of Atlanta: Working Paper 23. Erişim Adresi: http://hdl.handle.net/10419/100815
Kripfganz, S., ve Schwarz, C. (2019). Estimation of linear dynamic panel data models with time‐invariant regressors. Journal of Applied Econometrics, 34(4), 526-546.
Labra, R., ve Torrecillas, C. (2018). Estimating dynamic panel data: A practical approach to perform long panels. Revista Colombiana de Estadística, 41(1), 31-52.
Ma, C. K. (1988). Loan loss reserves and income smoothing: The experience in the US banking industry. Journal of Business Finance and Accounting, 15(4), 487-497.
Ma, M. L., ve Song, V. (2016). Discretionary loan loss provisions and systemic risk in the banking industry. Accounting Perspectives, 15(2), 89-130.
Merchant, K. A., ve Rockness, J. (1994). The ethics of managing earnings: An empirical investigation. Journal of Accounting and Public Policy, 13(1), 79-94.
Moore, M. L. (1973). Management changes and discretionary accounting decisions. Journal of Accounting Research, 11(1), 100-107.
Moral-Benito, E., Allison, P. D., ve Williams, R. A. (2017). Dynamic panel data modelling using maximum likelihood: An alternative to arellano-bond. Applied Economics, 51(20), 2221-2232.
Nickell, S. (1981). Biases in dynamic models with fixed effects. Econometrica, 49(6), 1417–1426.
Nordin, N. ve Nordin, N. (2016). Determinants of innovation in developing countries: A panel generalized method of moments analysis. Journal Ekonomi Malaysia, 50(2), 93–105.
Olszak, M., Pipien, M., Kowalska, I., ve Roszkowska, S. (2017). What drives heterogeneity of cyclicality of loan loss provisions in the EU? Journal of Financial Services Research, 51(1), 55-96.
Ozili, P. K. (2020). Banking sector earnings management using loan loss provisions in the Fintech era. International Journal of Managerial Finance, 18(1), 75-93.
Peasnell, K. V., Pope, P. F., ve Young, S. (2000). Accrual management to meet earnings targets: UK evidence pre-and post-cadbury. The British Accounting Review, 32(4), 415-445.
Robb, S. W. (1998). The effect of analysts forecasts on earnings management in financial institutions. Journal of Financial Research, 21(3), 315-331.
Roodman, D. (2009a). A note on the theme of too many instruments. Oxford Bulletin of Economics and Statistics, 71(1), 135-158.
Roodman, D. (2009b). How to do xtabond2: An introduction to difference and system GMM in Stata. The Stata Journal, 9(1), 86-136.
Ronen, J., ve Yaari, V. (2008). Definition of earnings management: In earnings management. Boston: Springer.
Sevin, S., ve Schroeder, R. (2005). Earnings management: Evidence from SFAS No. 142 reporting. Managerial Auditing Journal, 20(1), 47-54.
Skala, D. (2015). Saving on a rainy day? Income smoothing and procyclicality of loan‐loss provisions in Central European banks. International Finance, 18(1), 25-46.
Schipper, K. (1989). Earnings management. Accounting Horizons. 3(4) 91-102.
Schroeder, R. G., Guinn, R. E., ve Sevin, S. K. (2005). Accounting for asset retirement obligations. The CPA Journal, 75(12), 30-36.
Schroeder, R. G., Clark, M. W., ve Cathey, J. M. (2022). Financial accounting theory and analysis: Text and cases. New Jersey: John Wiley ve Sons.
Stolowy, H., ve Breton, G. (2000). A framework for the classification of accounts manipulations. HEC Accounting ve Management Control Working Paper 708.
Stowoly, H., ve Breton, G. (2004). Accounts manipulation: A literature review and proposed conceptual framework. Review of Accounting and Finance, 3(1), 5-66.
Studenmund, A. H., ve Johnson, A. K. (2016). Using econometrics: A practical guide. Boston: Pearson. Wetmore, J. L., ve Brick, J. R. (1994). Loan-loss provisions of commercial banks and adequate disclosure: A note. Journal of Economics and Business, 46(4), 299-305.
Windmeijer, F. (2005). A finite sample correction for the variance of linear efficient two-step GMM estimators. Journal of Econometrics, 126(1), 25-51.