The Need to go Beyond Deterministic Data Envelopment Analysis (DEA): A Comparative Analysis with Bootstrapping DEA in Risk Management Efficiency Measurements
Keywords:
Data Envelopment Analysis, Bootstrapping DEA, Deterministic, Efficiency, Banking Institutions
Abstract
This paper attempts to rectify the flaws of deterministic data envelopment analysis (DEA), induced from the characteristics of its approach. The disadvantages have drawn considerable attention in the area of banking efficiency studies, and bootstrapping DEA (BDEA) analysis has been proposed in the literature. This paper provides a comparative analysis of each approach to understand their theoretical foundations and mathematical computations, as well as their strengths and weaknesses. The arguments were empirically supported within the context of risk management efficiency analysis in banking institutions. Finally, the paper proved the need for BDEA analysis to be used while advancing measurement precision for risk management efficiency measurements.
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References
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———. 2011b. Technical efficiency in Saudi banks. Expert Systems with Applications, 38(5), 5781-5786.
Assaf, A. & Matawie, K. (2010). Improving the accuracy of DEA efficiency analysis: A bootstrap application to the health care foodservice industry. Applied Economics, 42(27), 3547-3558.
Atkinson, S. E. & Wilson, P. W. (1995). Comparing mean efficiency and productivity scores from small samples: A bootstrap methodology. Journal of Productivity Analysis, 6(2), 137-152.
Banker, R. D. (1993). Maximum likelihood, consistency and data envelopment analysis: A statistical foundation. Management Science, 39(10), 1265-1273.
Banker, R. D. & Morey, R. C. (1986). The use of categorical variables in data envelopment analysis. Management Science, 32(12), 1613-1627.
Barros, C. P., Dumbo, S. & Wanke, P. (2014). Efficiency determinants and capacity issues in Angolan Insurance Companies. South African Journal of Economics, 82(3), 455-467.
Brázdik, F. 2004. Stochastic Data Envelopment Analysis: Oriented and Linearized Models. Working paper series. Charles University. Center for Economic Research and Graduate Education, Charles University, Prague, and the Economics Institute of the Academy of Sciences of the Czech Republic.
Casu, B. & Molyneux, P. (2003). A comparative study of efficiency in European banking. Applied Economics, 35(17), 1865-1876.
Chortareas, G. E., Girardone, C. & Ventouri, A. (2013). Financial freedom and bank efficiency: Evidence from the European Union. Journal of Banking & Finance, 37(4), 1223-1231.
Cotter, J. & Dowd, K. (2006). Estimating financial risk measures for futures positions: A non-parametric approach. SSRN 994523.
Cummins, D. J., Weiss, M. A. & Zi, H. (2003). Economies of Scope in Financial Services: A DEA Bootstrapping Analysis of the US Insurance Industry. The Wharton School, University of Pennsylvania.
Davison, A. C. (1997). Bootstrap Methods and Their Application. New York: Cambridge University Press.
Dia, M., Golmohammadi, A. & Takouda, P. M. (2020). Relative Efficiency of Canadian Banks: A Three-Stage Network Bootstrap DEA. Journal of Risk and Financial Management, 13(4), 68.
Diler, M. (2011). Efficiency, Productivity and Risk Analysis in Turkish Banks: A Bootstrap DEA Approach. Journal of BRSA Banking & Financial Markets, 5(2).
Dong, F. & Featherstone, A. M. (2006). Technical and scale efficiencies for Chinese rural credit cooperatives: A bootstrapping approach in data envelopment analysis. Journal of Chinese Economic and Business Studies, 4(1), 57-75.
Dyson, R. G. & Shale, E. A. (2010). Data envelopment analysis, operational research and uncertainty. Journal of the Operational Research Society, 61(1), 25-34.
Efron, B. (1979). Bootstrap methods: Another look at the jack-knife. The Annals of Statistics 7 (1):1-26.
Efron, B. & Tibshirani, R. J. (1994). An Introduction to the Bootstrap. Florida: Chapman & Hall/CRC.
Emrouznejad, A. & Thanassoulis, E. (2010). Performance Improvement Management Software (PIMsoft): A User Guide.
Filippou, M. & Zervopoulos, P. (2011). Developing a short-term comparative optimization forecasting model for operational units’ strategic planning. Greece: Panteion University of Athens, 14.
Fried, H. O., Lovell, C. K. & Schmidt, S. S. (2008). The Measurement of Productive Efficiency and Productivity Growth. UK: Oxford University Press.
Friedman, L. W. & Friedman, H. H. (2013). Bootstrapping: Resampling Methodology. In Encyclopedia of Operations Research and Management Science: Springer, 127130.
Gijbels, I., Mammen, E., Park, B. U. & Simar, L. (1999). On estimation of monotone and concave frontier functions. Journal of the American Statistical Association, 94(445), 220-228.
Gil, A. & Polyakov, Y. (2003). Integrating market and credit risk in fixed income portfolios. Advances in Portfolio Construction and Implementation, 215.
Goldberg, L. R. (1976). Man versus model of man: Just how conflicting is that evidence? Organizational Behavior and Human Performance, 16(1), 13-22.
Gutiérrez, E., Lozano, S. & Furió, S. (2014). Evaluating the efficiency of international container shipping lines: A bootstrap DEA approach. Maritime Economics & Logistics, 16(1), 55-71.
Halkos, G. & Tzeremes, N. (2010). Performance evaluation using bootstrapping DEA techniques: Evidence from industry ratio analysis. MPRA Paper No. 25072 25072.
Halkos, G., Tzeremes, N. G. & Kourtzidis, S. A. (2012). Measuring public owned university departments’ efficiency: A bootstrapped DEA approach. Journal of Economics and Econometrics, 55(2), 1-24.
Hashemi, H., Mousavi, S. M., Tavakkoli-Moghaddam, R. & Gholipour, Y. (2013). Compromise Ranking Approach with Bootstrap Confidence Intervals for Risk Assessment in Port Management Projects. Journal of Management in Engineering, 29(4), 334-344.
Hawdon, D. (2003). Efficiency, performance and regulation of the international gas industry—a bootstrap DEA approach. Energy Policy, 31(11), 1167-1178.
Huang, X., Zhou, H. & Zhu, H. (2009). A framework for assessing the systemic risk of major financial institutions. Journal of Banking & Finance, 33(11), 2036-2049.
Huang and Li. (2001). Stochastic DEA models with different types of input-output disturbances. Journal of Productivity Analysis, 15(2), 95-113.
Jacobs, R. (2001). Alternative methods to examine hospital efficiency: data envelopment analysis and stochastic frontier analysis. Health Care Management Science, 4(2), 103-115.
Johanson, B. L. (2013). Deterministic and Stochastic Analyses to Quantify the Reliability of Uncertainty Estimates in Production Decline Modelling of Shale Gas Reservoirs, Degree's Thesis, Colorado School of Mines, Texas A&M University.
Johnes, J. (2006). Data envelopment analysis and its application to the measurement of efficiency in higher education. Economics of Education Review, 25(3), 273-288.
Kao, C. & Liu, S. T. (2009). Stochastic data envelopment analysis in measuring the efficiency of Taiwan commercial banks. European Journal of Operational Research, 196(1), 312-322.
Khan, I. U., Ali, S. & Khan, H. N. (2018). Market concentration, risk-taking, and efficiency of commercial banks in Pakistan: An application of the two-stage double bootstrap DEA. Business and Economic Review, 10(2), 65-95.
Libby, R. (1976). Man versus model of man: the need for a nonlinear model. Organizational Behavior and Human Performance, 16(1), 23-26.
Marinho, A. & Araújo, C. A. S. (2021). Using data envelopment analysis and the bootstrap method to evaluate organ transplantation efficiency in Brazil. Health Care Management Science 1-13.
Maghyereh, A. I. & Awartani, B. (2012). Financial integration of GCC banking markets: A non-parametric bootstrap DEA estimation approach. Research in International Business and Finance, 26(2), 181-195.
Medova, E. A. & Smith, R. G. (2005). A framework to measure integrated risk. Quantitative Finance, 5(1), 105-121.
Mellenbergh, G., Ader, H. & Hand, D. (2008). Advising on research methods: A consultant's companion. Netherlands: Johannes van Kessel Publishing.
Moradi-Motlagh, A., Valadkhani, A. & Saleh, A. S. (2014). Rising efficiency and cost saving in Australian banks: a bootstrap approach. Applied Economics Letters (ahead-of-print), 1-6.
Munisamy, S. & Danxia, W. (2013). Ranking efficiency of Asian container ports: A bootstrapped frontier approach. International Journal of Shipping and Transport Logistics, 5(6), 668-690.
Murillo?Zamorano, L. R. (2004). Economic efficiency and frontier techniques. Journal of Economic Surveys, 18(1), 33-77.
Sadjadi, S. J. & Omrani, H. (2010). A bootstrapped robust data envelopment analysis model for efficiency estimating of telecommunication companies in Iran. Telecommunications Policy, 34(4), 221-232.
Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. New York: CRC press.
Simar, L. (1992). Estimating efficiencies from frontier models with panel data: a comparison of parametric, non-parametric and semi-parametric methods with bootstrapping. Journal of Productivity Analysis, 3(1-2), 171-203.
Simar, L. & Wilson, P. W. (2000). A general methodology for bootstrapping in nonparametric frontier models. Journal of Applied Statistics, 27(6), 779-802.
Simar, L. & Wilson, P. W. (2008). Statistical inference in nonparametric frontier models: Recent developments and perspectives. The Measurement of Productive Efficiency and Productivity Growth, 421-521.
Slovic, P., Fleissner, D. & Bauman, W. S. (1972). Analyzing the use of information in investment decision making: A methodological proposal. The Journal of Business, 45(2), 283-301.
Staat, M. (2001). The effect of sample size on the mean efficiency in DEA: Comment. Journal of Productivity Analysis, 15(2), 129-137.
Stewart, C., Matousek, R. & Nguyen, T. N. (2016). Efficiency in the Vietnamese banking system: A DEA double bootstrap approach. Research in International Business and Finance, 36, 96-111.
Tsolas, I. E. (2021). Firm Credit Scoring: A Series Two-Stage DEA Bootstrapped Approach. Journal of Risk and Financial Management, 14(5), 214.
Walden, J. B. (2006). Estimating vessel efficiency using a bootstrapped data envelopment analysis model. Marine resource economics, 21(2), 181.
Xue, M. & Harker, P. T. (1999). Overcoming the inherent dependency of DEA efficiency scores: A bootstrap approach. Unpublished Working Paper, Wharton Financial Institutions Center, University of Pennsylvania.
Zakaria, S., Salleh, M. & Hassan, S. (2014). A Bootstrap Data Envelopment Analysis (BDEA) approach in Islamic banking sector: A method to strengthen efficiency measurement. Paper read at Industrial Engineering and Engineering Management (IEEM) 2014.
Zakaria, S. & Islam, S. M. (2019). Financial Risk Management in Banking: Evidence from Asia Pacific. Routledge.
Zenti, R. & Pallotta, M. (2000). Risk analysis for asset managers: Historical simulation, the bootstrap approach and value at risk calculation. Paper read at EFMA 2001 Lugano Meetings.
Zhang, Y. & Bartels, R. (1998). The effect of sample size on the mean efficiency in DEA with an application to electricity distribution in Australia, Sweden and New Zealand. Journal of Productivity Analysis, 9(3), 187-204.
Allen, P. G. & R. Fildes. (2001). Econometric Forecasting. In Principles of Forecasting. US: Springer, 303-362.
Alonso, A. M., Peña, D. & Romo, J. (2006). Introducing model uncertainty by moving blocks bootstrap. Statistical Papers, 47(2), 167-179.
Al-Rashidi, A. (2016). Data envelopment analysis for measuring the efficiency of head trauma care in England and Wales (Doctoral dissertation, Salford University).
Antunes, J., Hadi-Vencheh, A., Jamshidi, A., Tan, Y. & Wanke, P. (2024). Cost efficiency of Chinese banks: Evidence from DEA and MLP-SSRP analysis. Expert Systems with Applications, 237, 121432.
Arjomandi, A. (2011). Efficiency and Productivity in Iran's Financial Institutions. PhD, School of Economics, Faculty of Commerce, University of Wollongong. Armstrong, J. S. 2001. Judgmental bootstrapping: Inferring experts’ rules for forecasting. In Principles of Forecasting. US: Springer, 171-192.
Assaf, A. G. & Agbola, F. W. (2011). Modelling the performance of Australian hotels: A DEA double bootstrap approach. Tourism Economics, 17(1), 73-89.
Assaf, A. G., Barros, C. P. & Matousek, R. (2011a). Productivity and efficiency analysis of Shinkin banks: Evidence from bootstrap and Bayesian approaches. Journal of Banking & Finance, 35(2), 331-342.
———. 2011b. Technical efficiency in Saudi banks. Expert Systems with Applications, 38(5), 5781-5786.
Assaf, A. & Matawie, K. (2010). Improving the accuracy of DEA efficiency analysis: A bootstrap application to the health care foodservice industry. Applied Economics, 42(27), 3547-3558.
Atkinson, S. E. & Wilson, P. W. (1995). Comparing mean efficiency and productivity scores from small samples: A bootstrap methodology. Journal of Productivity Analysis, 6(2), 137-152.
Banker, R. D. (1993). Maximum likelihood, consistency and data envelopment analysis: A statistical foundation. Management Science, 39(10), 1265-1273.
Banker, R. D. & Morey, R. C. (1986). The use of categorical variables in data envelopment analysis. Management Science, 32(12), 1613-1627.
Barros, C. P., Dumbo, S. & Wanke, P. (2014). Efficiency determinants and capacity issues in Angolan Insurance Companies. South African Journal of Economics, 82(3), 455-467.
Brázdik, F. 2004. Stochastic Data Envelopment Analysis: Oriented and Linearized Models. Working paper series. Charles University. Center for Economic Research and Graduate Education, Charles University, Prague, and the Economics Institute of the Academy of Sciences of the Czech Republic.
Casu, B. & Molyneux, P. (2003). A comparative study of efficiency in European banking. Applied Economics, 35(17), 1865-1876.
Chortareas, G. E., Girardone, C. & Ventouri, A. (2013). Financial freedom and bank efficiency: Evidence from the European Union. Journal of Banking & Finance, 37(4), 1223-1231.
Cotter, J. & Dowd, K. (2006). Estimating financial risk measures for futures positions: A non-parametric approach. SSRN 994523.
Cummins, D. J., Weiss, M. A. & Zi, H. (2003). Economies of Scope in Financial Services: A DEA Bootstrapping Analysis of the US Insurance Industry. The Wharton School, University of Pennsylvania.
Davison, A. C. (1997). Bootstrap Methods and Their Application. New York: Cambridge University Press.
Dia, M., Golmohammadi, A. & Takouda, P. M. (2020). Relative Efficiency of Canadian Banks: A Three-Stage Network Bootstrap DEA. Journal of Risk and Financial Management, 13(4), 68.
Diler, M. (2011). Efficiency, Productivity and Risk Analysis in Turkish Banks: A Bootstrap DEA Approach. Journal of BRSA Banking & Financial Markets, 5(2).
Dong, F. & Featherstone, A. M. (2006). Technical and scale efficiencies for Chinese rural credit cooperatives: A bootstrapping approach in data envelopment analysis. Journal of Chinese Economic and Business Studies, 4(1), 57-75.
Dyson, R. G. & Shale, E. A. (2010). Data envelopment analysis, operational research and uncertainty. Journal of the Operational Research Society, 61(1), 25-34.
Efron, B. (1979). Bootstrap methods: Another look at the jack-knife. The Annals of Statistics 7 (1):1-26.
Efron, B. & Tibshirani, R. J. (1994). An Introduction to the Bootstrap. Florida: Chapman & Hall/CRC.
Emrouznejad, A. & Thanassoulis, E. (2010). Performance Improvement Management Software (PIMsoft): A User Guide.
Filippou, M. & Zervopoulos, P. (2011). Developing a short-term comparative optimization forecasting model for operational units’ strategic planning. Greece: Panteion University of Athens, 14.
Fried, H. O., Lovell, C. K. & Schmidt, S. S. (2008). The Measurement of Productive Efficiency and Productivity Growth. UK: Oxford University Press.
Friedman, L. W. & Friedman, H. H. (2013). Bootstrapping: Resampling Methodology. In Encyclopedia of Operations Research and Management Science: Springer, 127130.
Gijbels, I., Mammen, E., Park, B. U. & Simar, L. (1999). On estimation of monotone and concave frontier functions. Journal of the American Statistical Association, 94(445), 220-228.
Gil, A. & Polyakov, Y. (2003). Integrating market and credit risk in fixed income portfolios. Advances in Portfolio Construction and Implementation, 215.
Goldberg, L. R. (1976). Man versus model of man: Just how conflicting is that evidence? Organizational Behavior and Human Performance, 16(1), 13-22.
Gutiérrez, E., Lozano, S. & Furió, S. (2014). Evaluating the efficiency of international container shipping lines: A bootstrap DEA approach. Maritime Economics & Logistics, 16(1), 55-71.
Halkos, G. & Tzeremes, N. (2010). Performance evaluation using bootstrapping DEA techniques: Evidence from industry ratio analysis. MPRA Paper No. 25072 25072.
Halkos, G., Tzeremes, N. G. & Kourtzidis, S. A. (2012). Measuring public owned university departments’ efficiency: A bootstrapped DEA approach. Journal of Economics and Econometrics, 55(2), 1-24.
Hashemi, H., Mousavi, S. M., Tavakkoli-Moghaddam, R. & Gholipour, Y. (2013). Compromise Ranking Approach with Bootstrap Confidence Intervals for Risk Assessment in Port Management Projects. Journal of Management in Engineering, 29(4), 334-344.
Hawdon, D. (2003). Efficiency, performance and regulation of the international gas industry—a bootstrap DEA approach. Energy Policy, 31(11), 1167-1178.
Huang, X., Zhou, H. & Zhu, H. (2009). A framework for assessing the systemic risk of major financial institutions. Journal of Banking & Finance, 33(11), 2036-2049.
Huang and Li. (2001). Stochastic DEA models with different types of input-output disturbances. Journal of Productivity Analysis, 15(2), 95-113.
Jacobs, R. (2001). Alternative methods to examine hospital efficiency: data envelopment analysis and stochastic frontier analysis. Health Care Management Science, 4(2), 103-115.
Johanson, B. L. (2013). Deterministic and Stochastic Analyses to Quantify the Reliability of Uncertainty Estimates in Production Decline Modelling of Shale Gas Reservoirs, Degree's Thesis, Colorado School of Mines, Texas A&M University.
Johnes, J. (2006). Data envelopment analysis and its application to the measurement of efficiency in higher education. Economics of Education Review, 25(3), 273-288.
Kao, C. & Liu, S. T. (2009). Stochastic data envelopment analysis in measuring the efficiency of Taiwan commercial banks. European Journal of Operational Research, 196(1), 312-322.
Khan, I. U., Ali, S. & Khan, H. N. (2018). Market concentration, risk-taking, and efficiency of commercial banks in Pakistan: An application of the two-stage double bootstrap DEA. Business and Economic Review, 10(2), 65-95.
Libby, R. (1976). Man versus model of man: the need for a nonlinear model. Organizational Behavior and Human Performance, 16(1), 23-26.
Marinho, A. & Araújo, C. A. S. (2021). Using data envelopment analysis and the bootstrap method to evaluate organ transplantation efficiency in Brazil. Health Care Management Science 1-13.
Maghyereh, A. I. & Awartani, B. (2012). Financial integration of GCC banking markets: A non-parametric bootstrap DEA estimation approach. Research in International Business and Finance, 26(2), 181-195.
Medova, E. A. & Smith, R. G. (2005). A framework to measure integrated risk. Quantitative Finance, 5(1), 105-121.
Mellenbergh, G., Ader, H. & Hand, D. (2008). Advising on research methods: A consultant's companion. Netherlands: Johannes van Kessel Publishing.
Moradi-Motlagh, A., Valadkhani, A. & Saleh, A. S. (2014). Rising efficiency and cost saving in Australian banks: a bootstrap approach. Applied Economics Letters (ahead-of-print), 1-6.
Munisamy, S. & Danxia, W. (2013). Ranking efficiency of Asian container ports: A bootstrapped frontier approach. International Journal of Shipping and Transport Logistics, 5(6), 668-690.
Murillo?Zamorano, L. R. (2004). Economic efficiency and frontier techniques. Journal of Economic Surveys, 18(1), 33-77.
Sadjadi, S. J. & Omrani, H. (2010). A bootstrapped robust data envelopment analysis model for efficiency estimating of telecommunication companies in Iran. Telecommunications Policy, 34(4), 221-232.
Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. New York: CRC press.
Simar, L. (1992). Estimating efficiencies from frontier models with panel data: a comparison of parametric, non-parametric and semi-parametric methods with bootstrapping. Journal of Productivity Analysis, 3(1-2), 171-203.
Simar, L. & Wilson, P. W. (2000). A general methodology for bootstrapping in nonparametric frontier models. Journal of Applied Statistics, 27(6), 779-802.
Simar, L. & Wilson, P. W. (2008). Statistical inference in nonparametric frontier models: Recent developments and perspectives. The Measurement of Productive Efficiency and Productivity Growth, 421-521.
Slovic, P., Fleissner, D. & Bauman, W. S. (1972). Analyzing the use of information in investment decision making: A methodological proposal. The Journal of Business, 45(2), 283-301.
Staat, M. (2001). The effect of sample size on the mean efficiency in DEA: Comment. Journal of Productivity Analysis, 15(2), 129-137.
Stewart, C., Matousek, R. & Nguyen, T. N. (2016). Efficiency in the Vietnamese banking system: A DEA double bootstrap approach. Research in International Business and Finance, 36, 96-111.
Tsolas, I. E. (2021). Firm Credit Scoring: A Series Two-Stage DEA Bootstrapped Approach. Journal of Risk and Financial Management, 14(5), 214.
Walden, J. B. (2006). Estimating vessel efficiency using a bootstrapped data envelopment analysis model. Marine resource economics, 21(2), 181.
Xue, M. & Harker, P. T. (1999). Overcoming the inherent dependency of DEA efficiency scores: A bootstrap approach. Unpublished Working Paper, Wharton Financial Institutions Center, University of Pennsylvania.
Zakaria, S., Salleh, M. & Hassan, S. (2014). A Bootstrap Data Envelopment Analysis (BDEA) approach in Islamic banking sector: A method to strengthen efficiency measurement. Paper read at Industrial Engineering and Engineering Management (IEEM) 2014.
Zakaria, S. & Islam, S. M. (2019). Financial Risk Management in Banking: Evidence from Asia Pacific. Routledge.
Zenti, R. & Pallotta, M. (2000). Risk analysis for asset managers: Historical simulation, the bootstrap approach and value at risk calculation. Paper read at EFMA 2001 Lugano Meetings.
Zhang, Y. & Bartels, R. (1998). The effect of sample size on the mean efficiency in DEA with an application to electricity distribution in Australia, Sweden and New Zealand. Journal of Productivity Analysis, 9(3), 187-204.
Published
2023-11-12
How to Cite
Zakaria, S. (2023). The Need to go Beyond Deterministic Data Envelopment Analysis (DEA): A Comparative Analysis with Bootstrapping DEA in Risk Management Efficiency Measurements. Information Management and Business Review, 15(4(SI)I), 433-446. https://doi.org/10.22610/imbr.v15i4(SI)I.3618
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Copyright (c) 2023 Shahsuzan Zakaria
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