Evaluation of Performance of Iranian Commercial Banks Method: Bootstrap Algorithm

Document Type : Scientific paper

Authors

1 Professor, Department of Economics, Faculty of Economics, Allameh Tabataba'i University, Tehran, Iran

2 PhD student, Faculty of Economics, Allameh Tabatabai University

Abstract

The assessment of the economies of different countries of the world indicates that banks play the role of economic arteries of countries and Iran's economy is not only an exception to this rule, but Iran's economy is a bank-oriented economy; therefore, the study of the performance of Iranian banks plays a very important role in future policies. This research was done by aim investigating the performance of a set of commercial banks in Iran during the period of 1394-1380. The findings of the research indicate that the type of return to scale of the commercial banks of Iran during the mentioned period is constant and the Bootstrap algorithm has caused a decrease in the average efficiency over the mentioned time period so that by applying the Bootstrap algorithm, set of  Iranian commercial banks has been inefficient for all years. The Bootstrap has reduced the average performance by 4%, and has also reduced bias and has caused more realistic performance scores. The best performance of commercial banks was in 1387 and the worst performance was in the year 1380. The Bootstrap algorithm makes it possible to rank the performance scores, which was not possible in the absence of the algorithm. A exact assessment of banking performance can lead to bank reform.

Keywords

References

Ahn, Daniel P. & Rodney D. Ludema (2017). The Sword and the Shield: The Economics of Targeted Sanctions, mimeo,https://papers.ssrn.com/sol/papers.cfm
Alimohammadlou, M. & Mohammadi, S. (2016). Evaluating the productivity using Malmquist index based on double frontiers data Procedia. Social and Behavioral Sciences 230, 58 – 66 (In Persian).
Arab Mazar, A. & Keighbadi, S. (2006). The status of loan debt in the Iranian banking system. Journal of Islamic Economics, Sixth Year, Summer
Bahari, A. & Hosseini Nahad, Gh. (2011). Application of Bootstrap Process in Data Envelopment Analysis Models. Third National Conference on Data Envelopment Analysis, July.
Chaabouni, S. (2017). China's regional tourism efficiency: A two-stage double bootstrap data envelopment analysis. Journal of Destination Marketing & Management
Dreger, Christian, Jarko Fidrmuc, Konstantin Kholodilin & Dirk Ulbricht (2016). “Between the hammer and the anvil: The impact of economic sanctions and oil prices on Russia’s ruble,” Journal of Comparative Economics, 44(2), 295–308.
Ebadi, S. (2011). The method for ranking performance scores using Bootstrap. Journal of Applied Mathematics, Lahijan Branch, 8 (2), Summer, 29-44 (In Persian).
Elisa Périco, E., Brandão Santana, N., Aparecida do Nascimento Rebelatto, D. (2015). Estimating the efficiency from Brazilian banks: a bootstrapped Data Envelopment Analysis (DEA). http://dx.doi.org/10.1590/0103-6513.185714
Emami Meibodi, A. (2005) Principles of Measuring Efficiency and Productivity. Institute for Business Studies and Research, Second Edition.
Fallah, M. (2007). Evaluation of Performance  of Insurance Branches Using Data Envelopment Analysis. News in the World of Insurance, Nos. 115 and 116, p. 24-18
Fukuyama, H., & Weber, WL. (2015). Measuring bank performance with a dynamic network Luenberger indicator. Annals of Operational Research, on line 18 June, forthcoming, DOI 10.1007/s10479-015-1922-5.
Fare, R., Grosskopf, S., & Hernandez-Sancho, F., (2004). Environmental performance: an index number approach. Journal of Resource and Energy Economics 26,  343–352
Ghaderi, E.(2015). The impact of the United States sanctions on Iran’s trade flows– A gravity model approach. Södertörns University, Department of Economics. Masters Thesis 30 hp
Gitto,S.,Mancuso, P. (2011). Bootstrapping the Malmquist indexes for Italian airports. Int. J. Production Economics 135, 403–411
Heibati, F., Seyed Nourani, S M R, & Dadkhah, S. (2009). Evaluation Performance of Private Banks of Iran Compared to Arab Banks of Persian Gulf. Special Letter of Bank, No.6.
Kalate Rahmani, R., Anwar Rostami, A. A., Aghaei M A. & Azar, A. (2015). Analytical Procedures in Auditing: An Application of the Bootstrap Data Envelopment Analysis Approach. Journal of Financial Accounting Research, 7(25), 49-70
Khaki, Gh. (2009). Introduction to Productivity Management (Analysis in Organization). sayenama Institute, Fifth Edition.
Kordbache, H. (2010). Quasi-parametric robust estimation in determining inefficiencies in Iranian banking system: Bootstrap method. Journal of Economic Research, 46 (2), 159-192
Kordbache, H,. Mehregan N,. Taqavi, B. (2013). Will the performance of bank branches be affected by the characteristics of branch managers? Journal of Applied Economics, 3(11).
Korhonen, L. Simola, H. Solanko, L.(2018).Sanctions, counter-sanctions and Russia − Effects on economy, trade and finance. Bank of Finland, BOFIT Institute for Economies in Transition
 
Lee, Y. Tenerelli, T. Joo, S. (2017). An Analysis of Korean Bank Performance Using a Double Bootstrapped DEA Analysis, International Journal on Governmental Financial Management XVII (2) 
Mardani, A. Streimikiene, D. Balezentis, T. Zameri Mat Saman, M. Md Nor, K. Khoshnava, M. (2018). Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends. Energies
Nazari, A., Tarkhani, A. & Niloufar, P. (2018). Investigating the Factors Affecting the Performance of Private and Public Banks in Iran (Simar and Wilson Two-Step Method). Conference on National Production and Sustainable Employment, Challenges and Solutions.
Neuenkirch, M., Neumeier, F. (2016). The impact of US sanctions on poverty. Journal of Development Economics 121,110–119
Neuenkirch, N. Neumeier, F.(2015). The Impact of UN and US Economic Sanctions on GDP Growth. European Journal of Political Economy
Nguyen, T., Ttip,D., & Ngo, T. (2018). Operational Efficiency of Bank Loans and Deposits: A Case Study of Vietnamese Banking System. International Journal of Financial Studies
Parichatnon, S. Maichum, K. & Peng, K. (2018). Measuring technical efficiency of Thai rubber production using the three-stage data envelopment analysis. Agric. Econ. – Czech, 64, 227–240
Radojicic, M. Radovanovic, S. Jeremic,V. (2018). Measuring The Efficiency Of Banks: The Bootstrapped I-Distance Gar Dea Approach. Technological and Economic Development of Economy, 24 (4): 1581–1605.
Radojicic, M. Savic, G. Radovanovic, S. Jeremic,V.(2015). A Novel Bootstrap Dba-Dea Approach In Evaluating Efficiency Of Banks. “Mircea cel Batran” Naval Academy Scientific Bulletin, XVIII (2).
Sahin, G, Gokdemir, L, Ozturk, D,.(2015). Global Crisis and Its Effect on Turkish Banking Sector: A Study with Data Envelopment Analysis. Istanbul Conference of Economics and Finance, ICEF, 22-23, Istanbul,Turkey
Saraiya, D.(2005). The Impact of Environmental Variables in Efficiency Analysis: A fuzzy clustering-DEA Approach. Master of Science InIndustrial and Systems Engineering (Operations Research)
Soheili, K,. Fattahi, S,. Sarkhondi, M. (2013). Assessing the Bank of Iran's Monetary Strategies for the Production Gap and Inflation Deviation: A Bootstrap Approach. Journal of Economic Modeling Research, No. 21 Autumn 94.
Simar, L.,Wilson, P.,(2007). Estimation and inference in two-stage,semi-parametric models of production processes. Journal of Econometrics 136, 31–64.
Simar, L., Wilson, P.W., (2008).Statistical inference in nonparametric frontier models: recent developments and perspectives. In: Fried, H.O., Lovell, C.A.K., Schmidt, S.S. (Eds.), The Measurement of Productive Efficiency and Productivity GrowthOxford University press.
Sokhanvar. M., Sadeghi. H., Assari. A., Yavari. K. & Mehregan. N. (2012). Determining the Performance of Iranian Electricity Distribution Companies and their Factors Using Data Envelopment Analysis and Two-Stage Approach. Journal of Economic Research, 447 (2).
Sufian, F., Kamarudin, F. & Nassir, A.,(2016). Determinants of efficiency in the malaysian banking sector: Does bank origins matter? Intellectual Economics 10, 38-54
Whang, T. (2011), Playing to the home crowd? Symbolic use of economic sanctions in the United States, International Studies Quarterly 55(3), 787–801.
Macroeconomics Research Letter
Volume 14, Issue 28
April 2020
Pages 169-198

Files

History

  • Receive Date: 04 September 2019
  • Revise Date: 04 October 2019
  • Accept Date: 23 November 2019

Share

How to cite

Statistics