IDEAS home Printed from https://ideas.repec.org/a/rss/jnljms/v3i4p8.html
   My bibliography  Save this article

An Analysis of Bank Efficiency and Stock Prices Using Data Envelopment and Stochastic Frontier Analysis Models

Author

Listed:
  • Owen Jakata
  • Farikayi K. Mutasa

Abstract

This study investigated how stock prices and bank efficiency are linked to shareholder value creation. In this study two models Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) are applied to estimate bank efficiency. A comparative efficiency analysis of the two models, DEA and SFA was done and it was concluded that the two methods are consistent in terms of the results that were obtained. The difference between DEA and SFA efficiency scores is due to the presence of measurement error in DEA model and due to the functional form of the SFA model. The two methods are used jointly to provide complementary information. The banks were ranked in terms of efficiency scores and CBZ and FBC were ranked number one and two respectively. In this study sensitivity analysis was used to determine which factors between bank efficiency, log Total Assets, ROE and ROA have the greatest influence on stock prices. The results show that bank efficiency has the greatest influence on stock prices as compared to the traditional accounting measures of performance. We conclude that any improvements in bank efficiency will result in improvements in shareholders value which is inferred in improved stock prices.

Suggested Citation

  • Owen Jakata & Farikayi K. Mutasa, 2014. "An Analysis of Bank Efficiency and Stock Prices Using Data Envelopment and Stochastic Frontier Analysis Models," International Journal of Management Sciences, Research Academy of Social Sciences, vol. 3(4), pages 280-292.
    • Handle: RePEc:rss:jnljms:v3i4p8
    as

    Download full text from publisher

    File URL: http://rassweb.org/admin/pages/ResearchPapers/Paper%208_1497254267.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Saadet Kasman & Adnan Kasman, 2011. "Efficiency, Productivity and Stock Performance: Evidence from the Turkish Banking Sector," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 58(3), pages 355-372, September.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. Fotios Pasiouras & Aggeliki Liadaki & Constantin Zopounidis, 2008. "Bank efficiency and share performance: evidence from Greece," Applied Financial Economics, Taylor & Francis Journals, vol. 18(14), pages 1121-1130.
    4. Elena Beccalli & Barbara Casu & Claudia Girardone, 2006. "Efficiency and Stock Performance in European Banking," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 33(1‐2), pages 245-262, January.
    5. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    6. Richmond, J, 1974. "Estimating the Efficiency of Production," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(2), pages 515-521, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vaneet Bhatia & Sankarshan Basu & Subrata Kumar Mitra & Pradyumna Dash, 2018. "A review of bank efficiency and productivity," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 557-600, November.
    2. Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
    3. Philippe K. Widmer & Peter Zweifel, 2008. "Public Good Provision in a Federalist Country: Tiebout Competition, Fiscal Equalization, and Incentives for Efficiency in Switzerland," SOI - Working Papers 0804, Socioeconomic Institute - University of Zurich, revised Dec 2010.
    4. Muliaman Hadad & Maximilian Hall & Karligash Kenjegalieva & Wimboh Santoso & Richard Simper, 2011. "Banking efficiency and stock market performance: an analysis of listed Indonesian banks," Review of Quantitative Finance and Accounting, Springer, vol. 37(1), pages 1-20, July.
    5. W. Cooper & C. Lovell, 2011. "History lessons," Journal of Productivity Analysis, Springer, vol. 36(2), pages 193-200, October.
    6. Roland Banya & Nicholas Biekpe, 2018. "Banking efficiency and its determinants in selected frontier african markets," Economic Change and Restructuring, Springer, vol. 51(1), pages 69-95, February.
    7. Cheng, Xiaomei & Bjørndal, Endre & Lien, Gudbrand & Bjørndal, Mette, 2015. "Productivity Development for Norwegian Electricity Distribution Companies 2004-2013," Discussion Papers 2015/27, Norwegian School of Economics, Department of Business and Management Science.
    8. Luis R. Murillo-Zamorano & Juan Vega-Cervera, "undated". "The Use of Parametric and Non Parametric Frontier Methods to Measure the Productive Efficiency in the Industrial Sector. A Comparative Study," Discussion Papers 00/17, Department of Economics, University of York.
    9. Christopoulos, Apostolos G. & Dokas, Ioannis G. & Katsimardou, Sofia & Spyromitros, Eleftherios, 2020. "Assessing banking sectors’ efficiency of financially troubled Eurozone countries," Research in International Business and Finance, Elsevier, vol. 52(C).
    10. Cheng, Xiaomei & Bjørndal, Endre & Bjørndal, Mette, 2015. "Malmquist Productivity Analysis based on StoNED," Discussion Papers 2015/25, Norwegian School of Economics, Department of Business and Management Science.
    11. Hai-Dang Nguyen & Thanh Ngo & Tu DQ Le & Huong Ho & Hai T.H. Nguyen, 2019. "The Role of Knowledge in Sustainable Agriculture: Evidence from Rice Farms’ Technical Efficiency in Hanoi, Vietnam," Sustainability, MDPI, vol. 11(9), pages 1-10, April.
    12. Resti, Andrea, 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 & Finance, Elsevier, vol. 21(2), pages 221-250, February.
    13. Tim J. Coelli, 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 219-245, December.
    14. Holvad, Torben, 2020. "Efficiency analyses for the railway sector: An overview of key issues," Research in Transportation Economics, Elsevier, vol. 82(C).
    15. Amir Moradi-Motlagh & Ali Salman Saleh, 2014. "Re-Examining the Technical Efficiency of Australian Banks: A Bootstrap DEA Approach," Australian Economic Papers, Wiley Blackwell, vol. 53(1-2), pages 112-128, June.
    16. Kennedy, J. & Smith, A.S.J., 2003. "Assessing the efficient cost of sustaining Britain’s rail network: perspectives based on Zonal comparisons," Cambridge Working Papers in Economics 0317, Faculty of Economics, University of Cambridge.
    17. Hakan Güneş & Dilem Yıldırım, 2016. "Estimating Cost Efficiency of Turkish Commercial Banks under Unobserved Heterogeneity with Stochastic Frontier Models," ERC Working Papers 1603, ERC - Economic Research Center, Middle East Technical University, revised Mar 2016.
    18. Qayyum, Abdul & Ahmad, Munir, 2006. "Efficiency and Sustainability of Micro Finance," MPRA Paper 11674, University Library of Munich, Germany.
    19. Apostolos Christopoulos & Ioannis Dokas & Sofia Katsimardou & Eleftherios Spyromitros, 2022. "The Malmquist Productivity measure for UK-listed firms in the aftermath of the global financial crisis," Operational Research, Springer, vol. 22(2), pages 1617-1634, April.
    20. Murillo-Zamorano, Luis R. & Vega-Cervera, Juan A., 2001. "The use of parametric and non-parametric frontier methods to measure the productive efficiency in the industrial sector: A comparative study," International Journal of Production Economics, Elsevier, vol. 69(3), pages 265-275, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rss:jnljms:v3i4p8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Danish Khalil (email available below). General contact details of provider: http://www.rassweb.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.