BibTex RIS Kaynak Göster

Dynamic Efficiency of Turkish Banks: a DEA Window and Malmquist Index Analysis for the Period of 2003-2012

Yıl 2015, Cilt: 23 Sayı: 24, 71 - 97, 21.04.2015
https://doi.org/10.17233/se.09289

Öz

This article utilizes data envelopment analysis (DEA) in order to obtain technical efficiency and allocative efficiency scores of 23 commercial banks which operate in Turkey uninterruptedly between 2003 and 2012. According to results of CCR model analysis 3 banks are not technically efficient in the first years, the number of technically inefficient banks doubles in 2012. On the other hand the number of allocatively inefficient banks is only 5 in the first year and the number declines to 4 in the last year. The number of technically inefficient banks in the beginning is only one in terms of BCC model yet the number rose to 4 at the end of the study period. The relevant figure for allocative efficiency is 10 in the beginning and 16 at the end. DEA window analysis indicates that public banks with high amount of deposits tend to have higher efficiency scores while private banks have lower efficiency scores. The highest average in efficiency scores for all the banks occur in win4 to win5 (2006-’09 to 2007-’10) period. The Malmquist Index is used to analyze total factor productivity and its increase merely by two thousandth (0,002) for all the enterprises.

Kaynakça

  • Asmild, M. & J.C. Paradi & V. Aggarwall & C. Schaffnit (2004), “Combining DEA window analysis with the Malmquist Index approach in a study of the Canadian banking industry”, Journal of Productivity Analysis, 21, 67–89.
  • Avkiran, N.K. (2004), “Decomposing technical efficiency and window analysis”, Studies in Economics and Finance, 22 (1), 61-91.
  • Avkiran, N.K. (2008), “Association of DEA super-efficiency estimates with financial ratios: Investigating the case for Chinese banks”, Omega, 39, 323–334.
  • Banker, R.D. & A. Charnes & W.W. Cooper (1984), “Some models for estimating technical and scale inefficiencies in data envelopment analysis”, Management Science, 30(9), 1078-1092.
  • Caves, D. & L.R. Christiensen & W.E. Diewert (1982), “The economic theory of indeks numbers and the measurement of input, output and productivity”, Econometrica, 50, 1393-1414.
  • Charnes, A. & W.W. Cooper & A.Y. Lewin & R.C. Morey & J. Rousseau (1985), “Sensitivity and stability analysis in DEA”, Annals of Operations Research, 2, 139-156.
  • Charnes, A. & W.W. Cooper & E. Rhodes (1978), “Measuring the efficiency of decision making units”, European Journal of Operational Research, 2, 429-444.
  • Charnes, A. & W.W. Cooper & E. Rhodes (1979), “Short communication: Measuring the efficiency of decision making units”, European Journal of Operational Research, 3, 339.
  • Charnes, A. & W.W. Cooper & L.M. Seiford (1995), “Extension to DEA models”, in: A. Charnes, W.W. Cooper, A.Y. Lewin, & L.M. Seiford (eds.), Data envelopment analysis: Theory, methodology and applications, Berlin: Springer.
  • Cooper, W.W. & L.M. Seiford & K. Tone (2006), Introduction to data envelopment analysis and its uses, New York: Springer.
  • Cooper, W.W. & L.M. Seiford & J. Zhu (2011), “Data envelopment analysis: History, models, and interpretations”, in: W.W. Cooper, L.M. Seiford, & J. Zhu (eds.), Handbook on Data Envelopment Analysis (2nd Ed.), Berlin: Springer.
  • Coşkun, M. & H.N. Ardor & A.H. Çermikli & H.O. Eruygur & F. Öztürk & İ. Tokatlıoğlu & G. Aykaç & T. Dağlaroğlu (2012), Türkiye’de bankacılık sektörü piyasa yapısı, firma davranışları ve rekabet analizi, İstanbul: Türkiye Bankalar Birliği.
  • Das, A. & S. Ghosh (2006), “Financial deregulation and efficiency: An empirical analysis of Indian banks during the post reform period”, Review of Financial Economics, 15, 193–221.
  • Debreu, G. (1951), “The coefficient of resource utilization”, Econometrica, 19(3), 273–292.
  • Denizer, C.A. & M. Dinc & M. Tarimcilar (2007), “Financial liberalization and banking efficiency: Evidence from Turkey”, Journal of Productivity Analysis, 27, 177–195. Doi: 10.1007/s11123-007-0035-9
  • Farrell, M.J. (1957), “The measurement of productive efficiency”, Journal of the Royal Statistical Society, 120(3), 253–281.
  • Fukuyama, H. & R. Matousek (2011), “Efficiency of Turkish banking: Two-stage network system. Variable returns to scale model”, Journal of International Financial Markets, Institutions & Money, 21, 75–91. Doi: 10.1016/j.intfin.2010.08.004
  • Havranek, T. & Z. Irsova (2013), “Determinants of bank performance in transition countries: A data envelopment analysis”, Transition Studies Review, 20, 1-17. Doi: 10.1007/s11300-013-0270-x
  • Isik, I. & M.K. Hassan (2003), “Financial deregulation and total factor productivity change: An empirical study of Turkish commercial banks”, Journal of Banking & Finance, 27, 1455–1485. Doi: 10.1016/S0378-4266(02)00288-1
  • Koopmans, T.C. (1951), “An analysis of production as an efficient combination of activities”, in: T. C. Koopmans (ed.), Activity analysis of production and allocation, New Jersey: John Wiley and Sons.
  • Kutlar, A. & A. Kabasakal & M. Sarıkaya (2013), “Determination of the efficiency of the world railway companies by method of DEA and comparison of their efficiency by Tobit analysis”, Quality and Quantity, 47(6), 3575-3602. Doi: 10.1007/s11135-012-9741-0
  • Liu, F.F. & P.H. Wang (2008), “DEA Malmquist productivity measure: Taiwanese semiconductor companies”, International Journal of Production Economic, 112, 367-379.
  • Malmquist S. (1953), “Indeks number and indifferences surfaces”, Trabajos de Estatistica, 4, 209-242.
  • Mercan, M. & A. Reisman & R. Yolalan & A.B. Emel (2003), “The effect of scale and mode of ownership on the financial performance of the Turkish banking sector: results of a DEA-based analysis”, Socio-Economic Planning Sciences, 37, 185–202. Doi: 10.1016/S0038-0121(02)00045-9
  • Paradin, J.C. & H. Zhu (2013), “A survey on bank branch efficiency and performance research with data envelopment analysis”, Omega, 41, 61–79.
  • Pasiouras, F. (2008), “Estimating the technical and scale efficiency of Greek commercial banks: The impact of credit risk, off-balance sheet activities, and international operations”, Research in International Business and Finance, 22, 301-318.
  • Staub, R.B. & G.S. Souza & B.M. Tabak (2010), “Innovative applications of O.R. evolution of bank efficiency in Brazil: A DEA approach”, European Journal of Operational Research, 202, 204–213.
  • Sufian, F. (2006), “Trends in the efficiency of publicly listed Malaysian commercial banks over-time: A non-parametric DEA window analysis approach”, Banks and Bank Systems, 1(2), 144-167.
  • Sufian, F. & M.Z. Abdulmajid (2007a), “Deregulation, consolidation and banks efficiency in Singapore: Evidence from event study window approach and Tobit analysis”, International Review of Economics, 54, 261–283. Doi: 10.1007/s12232-007-0017-2
  • Sufian, F. & M.Z. Abdulmajid (2007b), “Singapore banking efficiency and its relation to stock returns: A DEA window analysis approach”, International Journal of Business Studies, 15(1), 83-106.
  • Tulkens, H. & P.V. Eeckaut (1995), “Nonparametric efficiency, progress and regress measures for panel data: Methodological aspects”, European Journal of Operations Research, 80, 474–499.
  • Unvan, Y.A. & H. Tatlidil (2012) “Efficiency in the Turkish banking system: A data envelopment approach”, International Journal of Basic & Applied Sciences, 12(02), 168-186.
  • Webb, R.W. (2003), “Levels of efficiency in UK retail banks: A DEA window analysis”, International Journal of the Economics of Business, 10(3), 305-322.
  • Yang, C. (2014), “An enhanced DEA model for decomposition of technical efficiency in banking”, Annals of Operations Research, 214, 167-185. Doi: 10.1007/s10479-011-0926-z

Dynamic Efficiency of Turkish Banks: a DEA Window and Malmquist Index Analysis for the Period of 2003-2012

Yıl 2015, Cilt: 23 Sayı: 24, 71 - 97, 21.04.2015
https://doi.org/10.17233/se.09289

Öz

This article utilizes data envelopment analysis (DEA) in order to obtain technical efficiency and allocative efficiency scores of 23 commercial banks which operate in Turkey uninterruptedly between 2003 and 2012. According to results of CCR model analysis 3 banks are not technically efficient in the first years, the number of technically inefficient banks doubles in 2012. On the other hand the number of allocatively inefficient banks is only 5 in the first year and the number declines to 4 in the last year. The number of technically inefficient banks in the beginning is only one in terms of BCC model yet the number rose to 4 at the end of the study period. The relevant figure for allocative efficiency is 10 in the beginning and 16 at the end. DEA window analysis indicates that public banks with high amount of deposits tend to have higher efficiency scores while private banks have lower efficiency scores. The highest average in efficiency scores for all the banks occur in win4 to win5 (2006-’09 to 2007-’10) period. The Malmquist Index is used to analyze total factor productivity and its increase merely by two thousandth (0,002) for all the enterprises.

Kaynakça

  • Asmild, M. & J.C. Paradi & V. Aggarwall & C. Schaffnit (2004), “Combining DEA window analysis with the Malmquist Index approach in a study of the Canadian banking industry”, Journal of Productivity Analysis, 21, 67–89.
  • Avkiran, N.K. (2004), “Decomposing technical efficiency and window analysis”, Studies in Economics and Finance, 22 (1), 61-91.
  • Avkiran, N.K. (2008), “Association of DEA super-efficiency estimates with financial ratios: Investigating the case for Chinese banks”, Omega, 39, 323–334.
  • Banker, R.D. & A. Charnes & W.W. Cooper (1984), “Some models for estimating technical and scale inefficiencies in data envelopment analysis”, Management Science, 30(9), 1078-1092.
  • Caves, D. & L.R. Christiensen & W.E. Diewert (1982), “The economic theory of indeks numbers and the measurement of input, output and productivity”, Econometrica, 50, 1393-1414.
  • Charnes, A. & W.W. Cooper & A.Y. Lewin & R.C. Morey & J. Rousseau (1985), “Sensitivity and stability analysis in DEA”, Annals of Operations Research, 2, 139-156.
  • Charnes, A. & W.W. Cooper & E. Rhodes (1978), “Measuring the efficiency of decision making units”, European Journal of Operational Research, 2, 429-444.
  • Charnes, A. & W.W. Cooper & E. Rhodes (1979), “Short communication: Measuring the efficiency of decision making units”, European Journal of Operational Research, 3, 339.
  • Charnes, A. & W.W. Cooper & L.M. Seiford (1995), “Extension to DEA models”, in: A. Charnes, W.W. Cooper, A.Y. Lewin, & L.M. Seiford (eds.), Data envelopment analysis: Theory, methodology and applications, Berlin: Springer.
  • Cooper, W.W. & L.M. Seiford & K. Tone (2006), Introduction to data envelopment analysis and its uses, New York: Springer.
  • Cooper, W.W. & L.M. Seiford & J. Zhu (2011), “Data envelopment analysis: History, models, and interpretations”, in: W.W. Cooper, L.M. Seiford, & J. Zhu (eds.), Handbook on Data Envelopment Analysis (2nd Ed.), Berlin: Springer.
  • Coşkun, M. & H.N. Ardor & A.H. Çermikli & H.O. Eruygur & F. Öztürk & İ. Tokatlıoğlu & G. Aykaç & T. Dağlaroğlu (2012), Türkiye’de bankacılık sektörü piyasa yapısı, firma davranışları ve rekabet analizi, İstanbul: Türkiye Bankalar Birliği.
  • Das, A. & S. Ghosh (2006), “Financial deregulation and efficiency: An empirical analysis of Indian banks during the post reform period”, Review of Financial Economics, 15, 193–221.
  • Debreu, G. (1951), “The coefficient of resource utilization”, Econometrica, 19(3), 273–292.
  • Denizer, C.A. & M. Dinc & M. Tarimcilar (2007), “Financial liberalization and banking efficiency: Evidence from Turkey”, Journal of Productivity Analysis, 27, 177–195. Doi: 10.1007/s11123-007-0035-9
  • Farrell, M.J. (1957), “The measurement of productive efficiency”, Journal of the Royal Statistical Society, 120(3), 253–281.
  • Fukuyama, H. & R. Matousek (2011), “Efficiency of Turkish banking: Two-stage network system. Variable returns to scale model”, Journal of International Financial Markets, Institutions & Money, 21, 75–91. Doi: 10.1016/j.intfin.2010.08.004
  • Havranek, T. & Z. Irsova (2013), “Determinants of bank performance in transition countries: A data envelopment analysis”, Transition Studies Review, 20, 1-17. Doi: 10.1007/s11300-013-0270-x
  • Isik, I. & M.K. Hassan (2003), “Financial deregulation and total factor productivity change: An empirical study of Turkish commercial banks”, Journal of Banking & Finance, 27, 1455–1485. Doi: 10.1016/S0378-4266(02)00288-1
  • Koopmans, T.C. (1951), “An analysis of production as an efficient combination of activities”, in: T. C. Koopmans (ed.), Activity analysis of production and allocation, New Jersey: John Wiley and Sons.
  • Kutlar, A. & A. Kabasakal & M. Sarıkaya (2013), “Determination of the efficiency of the world railway companies by method of DEA and comparison of their efficiency by Tobit analysis”, Quality and Quantity, 47(6), 3575-3602. Doi: 10.1007/s11135-012-9741-0
  • Liu, F.F. & P.H. Wang (2008), “DEA Malmquist productivity measure: Taiwanese semiconductor companies”, International Journal of Production Economic, 112, 367-379.
  • Malmquist S. (1953), “Indeks number and indifferences surfaces”, Trabajos de Estatistica, 4, 209-242.
  • Mercan, M. & A. Reisman & R. Yolalan & A.B. Emel (2003), “The effect of scale and mode of ownership on the financial performance of the Turkish banking sector: results of a DEA-based analysis”, Socio-Economic Planning Sciences, 37, 185–202. Doi: 10.1016/S0038-0121(02)00045-9
  • Paradin, J.C. & H. Zhu (2013), “A survey on bank branch efficiency and performance research with data envelopment analysis”, Omega, 41, 61–79.
  • Pasiouras, F. (2008), “Estimating the technical and scale efficiency of Greek commercial banks: The impact of credit risk, off-balance sheet activities, and international operations”, Research in International Business and Finance, 22, 301-318.
  • Staub, R.B. & G.S. Souza & B.M. Tabak (2010), “Innovative applications of O.R. evolution of bank efficiency in Brazil: A DEA approach”, European Journal of Operational Research, 202, 204–213.
  • Sufian, F. (2006), “Trends in the efficiency of publicly listed Malaysian commercial banks over-time: A non-parametric DEA window analysis approach”, Banks and Bank Systems, 1(2), 144-167.
  • Sufian, F. & M.Z. Abdulmajid (2007a), “Deregulation, consolidation and banks efficiency in Singapore: Evidence from event study window approach and Tobit analysis”, International Review of Economics, 54, 261–283. Doi: 10.1007/s12232-007-0017-2
  • Sufian, F. & M.Z. Abdulmajid (2007b), “Singapore banking efficiency and its relation to stock returns: A DEA window analysis approach”, International Journal of Business Studies, 15(1), 83-106.
  • Tulkens, H. & P.V. Eeckaut (1995), “Nonparametric efficiency, progress and regress measures for panel data: Methodological aspects”, European Journal of Operations Research, 80, 474–499.
  • Unvan, Y.A. & H. Tatlidil (2012) “Efficiency in the Turkish banking system: A data envelopment approach”, International Journal of Basic & Applied Sciences, 12(02), 168-186.
  • Webb, R.W. (2003), “Levels of efficiency in UK retail banks: A DEA window analysis”, International Journal of the Economics of Business, 10(3), 305-322.
  • Yang, C. (2014), “An enhanced DEA model for decomposition of technical efficiency in banking”, Annals of Operations Research, 214, 167-185. Doi: 10.1007/s10479-011-0926-z
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Aziz Kutlar

Ali Kabasakal

Adem Babacan Bu kişi benim

Yayımlanma Tarihi 21 Nisan 2015
Gönderilme Tarihi 14 Nisan 2015
Yayımlandığı Sayı Yıl 2015 Cilt: 23 Sayı: 24

Kaynak Göster

APA Kutlar, A., Kabasakal, A., & Babacan, A. (2015). Dynamic Efficiency of Turkish Banks: a DEA Window and Malmquist Index Analysis for the Period of 2003-2012. Sosyoekonomi, 23(24), 71-97. https://doi.org/10.17233/se.09289
AMA Kutlar A, Kabasakal A, Babacan A. Dynamic Efficiency of Turkish Banks: a DEA Window and Malmquist Index Analysis for the Period of 2003-2012. Sosyoekonomi. Nisan 2015;23(24):71-97. doi:10.17233/se.09289
Chicago Kutlar, Aziz, Ali Kabasakal, ve Adem Babacan. “Dynamic Efficiency of Turkish Banks: A DEA Window and Malmquist Index Analysis for the Period of 2003-2012”. Sosyoekonomi 23, sy. 24 (Nisan 2015): 71-97. https://doi.org/10.17233/se.09289.
EndNote Kutlar A, Kabasakal A, Babacan A (01 Nisan 2015) Dynamic Efficiency of Turkish Banks: a DEA Window and Malmquist Index Analysis for the Period of 2003-2012. Sosyoekonomi 23 24 71–97.
IEEE A. Kutlar, A. Kabasakal, ve A. Babacan, “Dynamic Efficiency of Turkish Banks: a DEA Window and Malmquist Index Analysis for the Period of 2003-2012”, Sosyoekonomi, c. 23, sy. 24, ss. 71–97, 2015, doi: 10.17233/se.09289.
ISNAD Kutlar, Aziz vd. “Dynamic Efficiency of Turkish Banks: A DEA Window and Malmquist Index Analysis for the Period of 2003-2012”. Sosyoekonomi 23/24 (Nisan 2015), 71-97. https://doi.org/10.17233/se.09289.
JAMA Kutlar A, Kabasakal A, Babacan A. Dynamic Efficiency of Turkish Banks: a DEA Window and Malmquist Index Analysis for the Period of 2003-2012. Sosyoekonomi. 2015;23:71–97.
MLA Kutlar, Aziz vd. “Dynamic Efficiency of Turkish Banks: A DEA Window and Malmquist Index Analysis for the Period of 2003-2012”. Sosyoekonomi, c. 23, sy. 24, 2015, ss. 71-97, doi:10.17233/se.09289.
Vancouver Kutlar A, Kabasakal A, Babacan A. Dynamic Efficiency of Turkish Banks: a DEA Window and Malmquist Index Analysis for the Period of 2003-2012. Sosyoekonomi. 2015;23(24):71-97.