Efficiency Analysis by Combination of Frontier Methods: Evidence from Unreplicated Linear Functional Relationship Model

• Autorzy: Omar Sharif , Md Zobaer Hasan , Chang Yun Fah , Mahboobeh Zangeneh Sirdari
• Języki publikacji: EN

Abstrakty

EN

This study proposes a new efficiency measurement technique CDS as combination of data envelopment analysis (DEA) and stochastic frontier analysis (SFA) and compares the CDS efficiency score with the DEA and SFA efficiency scores. The financial companies listed in Malaysian Stock Exchange for the period 2007-2016 are used to estimate the different types of efficiency score. Besides, linear regression analysis and ULFR (unreplicated linear functional relationship) analysis are used to analyze the performance of this CDS technique with the DEA and SFA techniques. The result suggests that the most efficient model is CDS which has a significant positive correlation with profit risk. Among the CDS, DEA and SFA techniques, the recommended technique (CDS) shows higher coefficient of determination values for both ULFR (0.9994) and linear regression (0.292) analysis. Also, based on the results of CDS, this study postulates that the most efficient firm is ACSM (Aeon Credit Service (M) Bhd) and the least efficient firm is MAY (Malayan Banking Bhd).(original abstract)

Słowa kluczowe

EN

Data Envelopment Analysis (DEA); Stochastic Frontier Analysis (SFA); Linear models

PL

Metoda DEA (analiza obwiedni danych); Metoda SFA (stochastyczna analiza graniczna); Modele liniowe

• Czasopismo: Business and Economic Horizons
• Rocznik: 2019
• Numer: vol. 15, iss. 1
• Strony: 107--125

Twórcy

autor

Omar Sharif

• Universiti Tunku Abdul Rahman, Malaysia

autor

Md Zobaer Hasan

• Monash University, Malaysia

autor

Chang Yun Fah

• Universiti Tunku Abdul Rahman, Malaysia

autor

Mahboobeh Zangeneh Sirdari

• Universiti Tunku Abdul Rahman, Malaysia

Bibliografia

• Adrienn, H. (2014). Financing aspects of the hungarian general manufacturers in 2010-2012. Annals of the University of Oradea, Economic Science Series, 23(1), 905-911.
• Aigner, D., Lovell, C., Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6, 21-37.
• Altunbas,Y., Carbo, S., Gardener, E. P., Molyneux, P. (2007). Examining the relationships between capital, risk and efficiency in European banking. European Financial Management, 13(1), 49-70.
• Banker, R., D., Charnes, A., Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078-1092.
• Battese, G. E., Coelli, T. J. (1988). Prediction of firm-level technical efficiencies with a geeneralised frontier production function and panel data, Journal of Econometrics, 38, 387-399.
• Bauer, P. W., Berger, A. N., Ferrier, G. D., Humphrey, D. B. (1998). Consistency Conditions for Regulatory Analysis of Financial Institutions: A Comparison of Frontier Efficiency Methods, Journal of Economics and Business, 50(2), 85-114.
• Berger, A. N., & Humphrey, D., B. (1997). Efficiency of financial institutions: International survey and directions for future research, European Journal of Operational Research, 98(2), 175-212.
• Campbell, J. Y., Shiller, R. J. (1988). Stock Prices, Earnings, and Expected Dividends, The Journal of Finance, 43, 661-676.
• Casu, B., Girardone, C., Molyneux, P. (2004). Productivity change in European banking: a comparison of parametric and non-parametric approaches, J. Bank. Finance, 28, 2521-2540.
• Charnes, A., Cooper, W. W., Rousseau, J., Semple, J. (1987). Data Envelopment Analysis and Axiomatic Notions of Efficiency and Reference Sets, Research Report CCS 558, Centre for Cybernetic Studies. The University of Texas at Austin.
• Cobb, C., Douglas, P. H. (1928). A theory of production, American Economic Review, 18, No. 1, 139-165.
• Coelli, T., Rao, D. S. P., & Battese, G. E. (1998). An introduction to efficiency analysis. Boston: Kluwer Academic Publishers.
• Coelli, T., Rao, D. S. P., O'Donnell, C. C., & Battese, G. E. (2005). An introduction to efficiency and productivity analysis. New York: Springer.
• Coelli, T. J. (1996a). A guide to DEAP Version 2.1 A data envelopment analysis (computer) program (CEPA Working Paper). University of New England.
• Coelli, T. J. (1996b). A guide to FRONTIER Version 4.1 A computer program for stochastic frontier production and cost function estimation (CEPA Working Paper). Department of Econometrics. University of New England.
• Davies, N. O. (2017). Empirical analysis of commercial banks in Malaysia using data envelopment analysis (DEA) Model, International Journal of Banking and Finance Research, 3(1), 40-48.
• Delis, M. D., & Papanikolaou, N. I. (2009). Determinants of bank efficiency: evidence from a semi-parametric methodology, Managerial Finance, 35(3), 260-275.
• Dong, Y., Hamilton, R., & Tippett, M. (2014). Cost efficiency of the Chinese banking sector: A comparison of stochastic frontier analysis and data envelopment analysis, Economic Modelling, 36, 298-308.
• Eisenbeis, R., Ferrier, G., & Kwan, S. (1999). The informativeness of stochastic frontier and programming frontier efficiency scores: Cost efficiency and other measures of bank holding company performance (Working Paper, 99-23), Federal Reserve Bank of Atlanta, December.
• Fah, C. Y., Ghapor Hussin, A., & Rijal, O. M. (2007). An investigation of causation: The unreplicated linear functional relationship model. Journal of Applied Sciences, 7, 20-26.
• Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns, The Journal of Finance, 47, 427-465.
• Fare, R., Grosskopf, S., & Lovell, C. A. K. (1994). Production frontiers. New York: Cambridge University Press.
• Fenyves, V., Tarnóczi, T., & Zsidó, K. (2015). Financial performance evaluation of agricultural enterprises with DEA method, Procedia Economics and Finance, 32(15), 423-431.
• Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries, The American Economic Review, 84(1), 66-83.
• Fernandes, F. D. S., Stasinakis, C., & Bardarova, V. (2018). Two-stage DEA-truncated regression: Application in banking efficiency and financial development, Expert Systems with Applications, 96, 284-301.
• Ferrier, G., & Lovell, C. A. K. (1990). Measuring cost efficiency in banking: Econometric and linear programming evidence, Journal of Econometrics, 46, 229-245.
• Greene, W. H. (1993). The econometric approach to efficiency analysis, in Fried, H. O., Lovell, C. A. K., & Schmidt, S. S. (Eds.), The measurement of productive efficiency (pp. 68-119), New York: Oxford University Press.
• Hasan, M. Z., Kamil, A. A., Mustafa, A., & Baten, M. A. (2012). A Cobb Douglas stochastic frontier model on measuring domestic bank efficiency in Malaysia, PLoS ONE, 7(8), 1-5.
• Huang, T. H., & Wang, M. H. (2002). Comparison of economic efficiency estimation methods: Parametric and non-parametric techniques, Manchester School, 70, 682-709.
• Hubbard, R. G. (2008). Money, the financial system, and the economy. 6th ed. US: Pearson Education.
• Isik, I., & Hassan, M. K. (2002). Cost and profit efficiency of the Turkish banking industry: An empirical investigation, The Financial Review, 37(2), 257-280.
• Ismail, M. K. A., Rahman, N. M. N. A., Salamudin, N., & Kamaruddin, B. H. (2012). DEA portfolio selection in Malaysian stock market. International Conference on Innovation, Management and Technology Research, ICIMTR2012, Malacca, pp. 739-743.
• Ismail, M. (2005). A study of efficiency and competitive Behaviour of commercial Banks in Malaysia (Doctoral thesis), Retrieved from UMI Dissertation Publishing, UMI Number U584012.
• Janang, J. T., Suhaimi, R., & Salamudin, N. (2013). Directors incentive and technical efficiency of government linked companies in Malaysia: A stochastic frontier analysis, BEIAC 2013-2013 IEEE Business Engineering and Industrial Applications Colloquium, (February 2016), pp. 50-55.
• Katib, M., Nasser, & Mathews, K. (2000). A non-parametric approach to efficiency measurement in the Malaysian banking sector, The Singapore Economic Review, 44, 89-114.
• Kumbhakar, S. C., & Lovell, C. K. (2003). Stochastic frontier analysis. Cambridge University Press.
• Lovell, C. A. K. (1993). Production frontiers and productive efficiency. In Fried, H. O., Lovell, C. A., Schmidt S. S. (Eds.), The measurement of productive efficiency (pp. 3-67). New York: Oxford University Press.
• PatrÃcia, B. N., & Balazs, F. (2014). Returns of private equity comparative analyses of the returns of venture capital and buyout funds in Europe and in the US. Annals of the University of Oradea: Economic Science, 23(1), 820-827.
• Pereira De Souza, M. V., Diallo, M., Castro Souza, R., & Baidya, T. K. N. (2010). The cost efficiency of the Brazilian electricity distribution utilities: a comparison of Bayesian SFA and DEA models. Mathematical Problems in Engineering, 2010, 1-19.
• Resti, A. (1997). Evaluating the cost-efficiency of the Italian banking system: What can be learned from the joint application of parametric and non-parametric techniques, Journal of Banking and Finance, 21, 221-250.
• Saad, M. N., Idris, H., & Edzalina, N. (2011). Efficiency of life insurance companies in Malaysia and Brunei: a comparative analysis, International Journal of Humanities and Social Science, 1(3), 111-122.
• Sealey, C. W. J., & Lindley, J. T. (1977). Inputs, outputs, and a theory of production and cost at semi-parametric methodology, Managerial Finance, 35(3), 260-275.
• Seiford, L. M., & Thrall, R. M. (1990). Recent developments in DEA: the mathematical programming approach to frontier analysis, Journal of Econometrics, 46, 7-38.
• Siew, L. W., Fai, L. K., & Hoe, L. W. (2017). An empirical investigation on the efficiency of financial companies in Malaysia with data envelopment analysis model, American Journal of Information Science and Computer Engineering, 3(3), 32-38.
• Sprent, P. (1990). Some history of functional and structural relationships, Contemporary Mathematics, 112, 3-15.
• Sufian, F. (2004). The efficiency effects of bank mergers and acquisitions in developing economy: Evidence from Malaysia, International Journal of Applied Econometrics and Quantitative Studies, 1(4), 53-74.
• Sufian, F. (2016). Determinants of efficiency in the Malaysian banking sector: Evidence from semi-parametric data envelopment analysis method, Studies in Microeconomics, 4(2), 151-172.
• Sufian, F., & Habibullah, M. S. (2014). Banks' total factor productivity growth in a developing economy: Does globalisation matter?, Journal of International Development. 26(6), 821-852.
• Sufian, F., & Majid, M. A. (2006). Banks' efficiency and stock prices in emerging markets: Evidence from Malaysia. Journal of Asia-Pacific Business, 7(4), 35-53.
• Sufian, F., Kamarudin, F., & Nassir, A. M. (2016). Determinants of efficiency in the Malaysian banking sector: Does bank origins matter?. Intellectual Economics, 10(1), 38-54.
• Suhaimi, R., Abdullah, A., Nee, C. F., & Ibrahim, N. A. (2012). Profit efficiency and competitiveness of commercial banks in Malaysia, World Academy of Science, Engineering and Technology, 66, 627-630.
• Weill, L. (2004). Measuring cost efficiency in European banking: a comparison of frontier techniques. J. Prod. Anal, 21, 133-152.

Identyfikatory

DOI

10.15208/beh.2019.7