TESTING TECHNICAL AND SCALE EFFICIENCY OF KAZAKH BANKS: EVIDENCE BASED ON DATA ENVELOPMENT ANALYSIS

Abstract

This paper tests technical and scale efficiency of 20 Kazakh banks using annual data on three inputs (interest expenses, non-interest expenses and deposits) and three outputs (interest income, non-interest income and loans) over the period 2007-2011. Two input-oriented data envelopment analysis models of Charnes et al (1978) and Banker et al (1984), which are based on constant return to scale and variable return to scale respectively, are used to evaluate technical efficiency, whereas scale efficiency is computed by dividing the former efficiency ratio by the latter one. The results obtained show that the average efficiency ratios of individual banks under constant and variable returns to scale range from 0.88 and 1.00 to 0.93 and 1.00 respectively, whereas those of all banks between 0.95 and 0.98 respectively. Only are the five banks (ATFB, Citibank, HSBC bank, KazInvest bank and Exim bank) the most efficient banks in Kazakhstan, since their efficiency ratios have been consistently equal to unity, implying that these banks operate at their optimal levels. The efficiency scores of the remaining 15 banks range from 0.88 to 0.99, and as such the majority of these banks do not seem to operate far more below their optimal level. The results indicate that the performance of the Kazakh banks deteriorated substantially during the global financial crisis of 2008 because the CRS ratio dropped from 0.65 in 2007 to 0.50 in 2008 and to 0.40 in 2009. The results also confirm that most of the foreign banks perform relatively better than domestic banks.

Keywords

• Non-parametric method, Data envelopment analysis, commercial banks

Kaynakça

1. Akimov, Alexandr and Dollery, Brain (2007), “An Evolution of Kazakhstan’s
2. Financial System Reforms in 1993-2002”, Working Paper Series in Economics
3. No. 2007-3, University of New England School of Economics, pp.1-22.
4. Balino, Tomas, Hoelscher, David and Holder, Jakob (1997), “Evolution of
5. Monetary Policy Instrument in Russia”, Working Paper No. 180, International Monetary Fund, pp. 1-33. Banker, R.D., Charnes, A. and Cooper, W.W. (1984), “Some Models for
6. Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis”, Management Science, Vol. 30, Issue 9, pp. 1078-1092.
7. Charnes A., Cooper W.W., Rhodes E. (1978), “Measuring Efficiency of Decision
8. Making Units”, European Journal of Operational Research, Vol. 2, Issue 6, pp. 444. Fries, Steven and Taci, Anita (2005), “Cost Efficiency of Banks in Transition:

9. Evidence from 289 Banks in 15 Post-Communist Countries”, Journal of Banking and Finance, Volume 29, No. 1, pp.55-81. Hoelscher, David (1998), “Bank Restructuring in Kazakhstan”, IMF Working Paper No. 98/97, pp. 1-33
10. Jermakowicz, Waldyslaw and Irishev, Berlin (1996), “The Banking System in
11. Kazakhstan”, CASE Network Studies and Analyses No. 89, pp. 1-37. Khbhakar, Subal and Peresetsky, Antoly (2013),
12. “Cost efficiency of Kazakhstan and Russian Banks: Results from Competing Panel Data Models”, Macroeconomics and Finance in Emerging Market Economies, Volume 6, Issue 1, pp. 88-113. Prresetsky, Anatoly (2010), “Bank Cost Efficiency in Kazakhstan and Russia”,
13. Bank of Finland BOFIT Discussion Paper N0.1.