SETTING OPTIMAL NUMERIC TARGETS IN BANKING: A PRACTICAL APPLICATION ON PARTICIPATION BANKING CREDITS

Öz

The aim of this study is to work out a practical numeric performance appraisal methodology application on a whole group that contains subunits, and for the example of the model; Islamic Banking Credits for Türkiye is used. The quarterly data for between 2005: Q1 to 2023: Q3 is used for the analysis. Pedroni Cointegration Test, its pre and post-tests: Augmented Dickey Fuller Tests, Pesaran CD Tests, Swamy S Tests, Dumitrescu & Hurlin, Granger Non-Causality Test and finally Augmented Mean Group Estimator are used to set out the targets and analyzing the performance. The application results have significant preestimation and post-estimation test results for 90% significance level for Agriculture, Industry, Construction, Service, Communication, Finance, Real Estate and Health sub-sectors and for the whole aggregate group. The empirical results show that Türkiye Islamic Banking Credits may decrease in all significant sectors for the fourth quartile of 2023. Further research on the Total Amount for Islamic Banks Credits for Türkiye can be estimated.

Anahtar Kelimeler

• Augmented Mean Group Estimator
• Targeting
• Performance Appraisal
• Islamic Banking
• Cointegration

Bankacılıkta En Uygun Sayısal Hedeflerin Belirlenmesi: Katılım Bankacılığı Kredilerinde Bir Uygulama

Öz

Bu çalışmanın amacı, alt birimleri içeren bütün bir grup üzerinde pratik bir sayısal performans değerlendirme metodolojisi uygulaması yapmaktır ve model örneği için; Türkiye İslami Bankacılık Kredileri kullanılmaktadır. Analiz için 2005: 1.Ç ile 2023: 3.Ç arasındaki üç aylık veriler kullanılmıştır. Pedroni Eşbütünleşme Testi, ön testleri ve son testleri: Hedefleri belirlemek ve performansı analiz etmek için Augmented Dickey Fuller Testleri, Pesaran CD Testleri, Swamy S Testleri, Dumitrescu & Hurlin, Granger Nedensellik Testi ve son olarak Artırılmış Ortalama Grup Tahmincisi kullanılmıştır. Uygulama sonuçları, Tarım, Sanayi, İnşaat, Hizmet, İletişim, Finans, Gayrimenkul ve Sağlık alt sektörleri ve tüm toplulaştırılmış grup için 90% Anlamlılık Düzeyi için anlamlı ön tahmin ve tahmin sonrası test sonuçlarına sahiptir. Ampirik sonuçlar, Türkiye İslami Bankacılık Kredileri’ nin 2023 yılının dördüncü çeyreğinde tüm anlamlı sektörlerde azalabileceğini göstermektedir. Türkiye İslami Bankacılık Kredilerinin tahminlenmesi bundan sonraki çalışmalar için önerilebilir.

Anahtar Kelimeler

• Artırılmış Ortalama Grup Tahmincisi
• Hedefleme
• Performans Değerlendirmesi
• Katılım Bankacılığı
• Eşbütünleşme

Kaynakça

1. Ahn, H., and Le, M.H., (2015). DEA Efficiency of German Savings Banks: Evidence from a GoalOriented Perspective. Journal of Business Economics, 85:953–975.
2. Alicioglu, Y., (2023). Have Investment Incentives Really Helped to Increase GDP? Turkiye Example. Proceedings Book of 26th Finance Symposium, Turkiye.
3. Amirteimoori, A. and Tabar, M.M. (2010). Resource Allocation and Target Setting in Data Envelopment Analysis. Expert Systems with Applications, 37(4):3036-3039.
4. An, Q., Wu, Q., Zhou, X. and Chen, X., (2021). Closest target setting for two-stage network system: An application to the commercial banks in China. Expert Systems with Applications, 175 (1), https://doi.org/10.1016/j.eswa.2021.114799
5. BRSA. (2023). Monthly Banking Sector data of Islamic Banks. Retrieved December 8th, 2023, from https://www.bddk.org.tr/BultenAylik/
6. Camaho, A.S. and Dyson, R.G., (1999). Efficiency, Size, Benchmarks and Targets for Bank Branches: An Application of Data Envelopment Analysis. Journal of the Operational Research Society, 50:903-915.
7. Eberhardt, M. and Bond, S., (2009). Cross-section Dependence in Nonstationary Panel Models: a Novel Estimator. MPRA, Munich Personal RePEc Archive.
8. Eberhardt, M. and Teal, F., (2010). Productivity Analysis in Global Manufacturing Production. University of Oxford, Department of Economics, Discussion Paper Series.

9. Farahbakhsh, F., Kheradyar, S., Shahroodi, K. and Farahbod, F., (2024). Prioritizing the Key Factors for Performance Evaluation of Iran’s Banking System Based on the Balanced Scorecard (BSC) Approach and the Fuzzy Analytic Network Process (FANP). International Journal of Nonlinear Analytic Applications, 15(1):151-160.
10. Karas, Z., (2024). Financial Performance Evaluation with Multi Criteria Decision Making Approaches in the Turkish Banking Sector. Electronic Journal of Social Sciences, 23(90):798-820.
11. Liu, X., Yang, F. and Wu, J., (2019). DEA Considering Technological Heterogeneity and Intermediate Output Target Setting: the Performance Analysis of Chinese Commercial Banks. Annals of Operations Research, 291: 605–626.
12. Lovell, C. A.N. and Pastor, J.T., (1997). Target Setting: An Application to a Bank Branch Network. European Journal of Operational Research, 98(2): 290-299.
13. Nugroho, A.P., (2024). Comparative Analysis of the Efficiency of Islamic and Conventional Banking Systems: A Literature Review. Journal of Economic, Business and Accounting, 7(2):2815-2826.
14. Portela, M.C.A.S., Thanassoulis, E., and Simpson, G., (2004). Negative Data in DEA: a Directional Distance Approach Applied to Bank Branches. Journal of the Operational Research Society, 55(2004): 1-12.
15. Ragab Amhana, Z. B., and Thomas A. B., (2024). The Impact of Performance Appraisal on Employees’ Productivity in Financial Institutions: A Case of the United States Banking Sector. European Journal of Business, 4(4):270-282.
16. Tuna, Y. and Sekkeli, F.E. (2020). Effects of Participation Banking on Real Sector. BMIJ (Business and Management Studies an International Journal), 8(2):1501-1522 doi: http://dx.doi.org/ 10.15295/bmij.v8i2.1443
17. TURKSTAT. (2023). Gross Domestic Product at Current Prices - by Income Approach Value and Percentage Change, Quarter III: July-September, 2023. Retrieved December 8th, 2023, from https://data.tuik.gov.tr/Kategori/GetKategori?p=Ulusal-Hesaplar-113.
18. Yanikkaya, H. & Pabuçcu, Y.U. (2017). Causes and solutions for the stagnation of Islamic banking in Turkey. ISRA International Journal of Islamic Finance, 9 (1), 43-61.
19. Yang, J., Wong, B.Y.H., Xu, D. and Stewart, T.J. (2009). Integrating DEA-oriented Performance Assessment and Target Setting Using Interactive MOLP Methods. European Journal of Operational Research, 195(1):205-222.
20. Yang, J.B. Wong, B.Y.H., Xu, D.L., Liu, X.B. and Steuer, R.E. (2010). Integrated Bank Performance Assessment and Management Planning Using Hybrid Minimax Reference Point – DEA Approach. European Journal of Operational Research, 207(2010):1506–1518.