IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-18-00636.html
   My bibliography  Save this article

Resource allocation with Time Series DEA applied to Brazilian Federal Saving banks

Author

Listed:
  • Thyago C. C. Nepomuceno

    (Sapienza University of Rome)

  • Ana Paula C. S. Costa

    (Universidade Federal de Pernambuco, Department of Production Engineering)

Abstract

One limitation in the economic analysis of efficiency and productivity is the impossibility to determine whether a service organization has reached their optimum output-to-input configuration, i.e. whether efficient units could be more efficient or whether inefficient units have reached their maximum potential and could not improve their performance. In this work, the usage of time series data instead of cross-sectional data from different DMUs is motivated to avoid this problematic of comparing units which might significantly differ in their internal structure (production technology) even presenting similar input/output levels. From the optimum output-to-input ratio, resource lacks (with respect to projected goals) and slacks can be determined for each decision unit evaluated individually. The case of Brazilian Federal Saving banks is presented as an empirical application of the methodology.

Suggested Citation

  • Thyago C. C. Nepomuceno & Ana Paula C. S. Costa, 2019. "Resource allocation with Time Series DEA applied to Brazilian Federal Saving banks," Economics Bulletin, AccessEcon, vol. 39(2), pages 1384-1392.
  • Handle: RePEc:ebl:ecbull:eb-18-00636
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2019/Volume39/EB-19-V39-I2-P131.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. H. David Sherman & Joe Zhu, 2006. "Service Productivity Management," Springer Books, Springer, number 978-0-387-33231-4, November.
    2. Daraio, Cinzia & Kerstens, Kristiaan & Nepomuceno, Thyago & Sickles, Robin C., 2019. "Empirical Surveys of Frontier Applications: A Meta-Review," Working Papers 19-005, Rice University, Department of Economics.
    3. Tecles, Patricia Langsch & Tabak, Benjamin M., 2010. "Determinants of bank efficiency: The case of Brazil," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1587-1598, December.
    4. Joe Zhu, 2014. "Quantitative Models for Performance Evaluation and Benchmarking," International Series in Operations Research and Management Science, Springer, edition 3, number 978-3-319-06647-9, December.
    5. Mette Asmild & Joseph Paradi & Vanita Aggarwall & Claire Schaffnit, 2004. "Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry," Journal of Productivity Analysis, Springer, vol. 21(1), pages 67-89, January.
    6. Emrouznejad, Ali & Yang, Guo-liang, 2018. "A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 4-8.
    7. Wanke, Peter & Barros, Carlos P. & Faria, João R., 2015. "Financial distress drivers in Brazilian banks: A dynamic slacks approach," European Journal of Operational Research, Elsevier, vol. 240(1), pages 258-268.
    8. Staub, Roberta B. & da Silva e Souza, Geraldo & Tabak, Benjamin M., 2010. "Evolution of bank efficiency in Brazil: A DEA approach," European Journal of Operational Research, Elsevier, vol. 202(1), pages 204-213, April.
    9. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    10. Hampf, Benjamin, 2016. "Efficiency and Productivity Measurement with Persistent Benchmarks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 92493, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    11. Benjamin Hampf, 2016. "Efficiency and productivity measurement with persistent benchmarks," Economics Bulletin, AccessEcon, vol. 36(3), pages 1715-1721.
    12. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2006. "Introduction to Data Envelopment Analysis and Its Uses," Springer Books, Springer, number 978-0-387-29122-2, November.
    13. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    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. Aziz KUTLAR & Ali KABASAKAL & Adem BABACAN, 2015. "Dynamic Efficiency of Turkish Banks: a DEA Window and Malmquist Index Analysis for the Period of 2003-2012," Sosyoekonomi Journal, Sosyoekonomi Society, issue 23(24).
    2. Alqahtani, Faisal & Mayes, David G. & Brown, Kym, 2017. "Islamic bank efficiency compared to conventional banks during the global crisis in the GCC region," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 58-74.
    3. Nahia Mourad & Assem Tharwat, 2019. "Mixed Stochastic Input Oriented Data Envelopment Analysis Model," Working Papers hal-02144705, HAL.
    4. Adriel Martins de Freitas Branco & Alexandre Pereira Salgado Junior & Patrícia Benites Cava & Eduardo Falsarella Junior & Marco Antônio Alves de Souza Junior, 2017. "Efficiency of the Brazilian Banking System in 2014: A DEA-SBM Analysis," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(5), pages 1-2.
    5. Kottas, Angelos T. & Madas, Michael A., 2018. "Comparative efficiency analysis of major international airlines using Data Envelopment Analysis: Exploring effects of alliance membership and other operational efficiency determinants," Journal of Air Transport Management, Elsevier, vol. 70(C), pages 1-17.
    6. Yang, Guo-liang & Fukuyama, Hirofumi & Chen, Kun, 2019. "Investigating the regional sustainable performance of the Chinese real estate industry: A slack-based DEA approach," Omega, Elsevier, vol. 84(C), pages 141-159.
    7. Francisco Javier Santos Arteaga & Debora Di Caprio & David Cucchiari & Josep M Campistol & Federico Oppenheimer & Fritz Diekmann & Ignacio Revuelta, 2021. "Modeling patients as decision making units: evaluating the efficiency of kidney transplantation through data envelopment analysis," Health Care Management Science, Springer, vol. 24(1), pages 55-71, March.
    8. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.
    9. Taleb, Mushtaq & Khalid, Ruzelan & Ramli, Razamin & Ghasemi, Mohammad Reza & Ignatius, Joshua, 2022. "An integrated bi-objective data envelopment analysis model for measuring returns to scale," European Journal of Operational Research, Elsevier, vol. 296(3), pages 967-979.
    10. Jradi, Samah & Bouzdine Chameeva, Tatiana & Aparicio, Juan, 2019. "The measurement of revenue inefficiency over time: An additive perspective," Omega, Elsevier, vol. 83(C), pages 167-180.
    11. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    12. Nyankomo Marwa, 2014. "Efficiency and Profitability of Tanzanian saving and Credit Cooperatives: Who is a Star?," Journal of Economics and Behavioral Studies, AMH International, vol. 6(8), pages 658-669.
    13. Sarmento, Joaquim Miranda & Renneboog, Luc & Verga-Matos, Pedro, 2017. "Measuring highway efficiency : A DEA approach and the Malquist index," Other publications TiSEM 23264815-321e-45a3-83ee-9, Tilburg University, School of Economics and Management.
    14. Mohamed Dia & Amirmohsen Golmohammadi & Pawoumodom M. Takouda, 2020. "Relative Efficiency of Canadian Banks: A Three-Stage Network Bootstrap DEA," JRFM, MDPI, vol. 13(4), pages 1-25, April.
    15. Halkos, George & Petrou, Kleoniki Natalia, 2018. "Assessment of national waste generation in EU Member States’ efficiency," MPRA Paper 84590, University Library of Munich, Germany.
    16. Tatiana Bencova & Andrea Bohacikova, 2022. "DEA in Performance Measurement of Two-Stage Processes: Comparative Overview of the Literature," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 111-129.
    17. Avkiran, Necmi Kemal, 2015. "An illustration of dynamic network DEA in commercial banking including robustness tests," Omega, Elsevier, vol. 55(C), pages 141-150.
    18. Lam, Chor Man & Hsu, Shu-Chien & Alvarado, Valeria & Li, Wing Man, 2020. "Integrated life-cycle data envelopment analysis for techno-environmental performance evaluation on sludge-to-energy systems," Applied Energy, Elsevier, vol. 266(C).
    19. Fazıl Gökgöz & Mustafa Taylan Güvercin, 2018. "Investigating the total factor productivity changes in the top ICT companies worldwide," Electronic Commerce Research, Springer, vol. 18(4), pages 791-811, December.
    20. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.

    More about this item

    Keywords

    Resource Allocation; Data Envelopment Analysis; Time Series; Organizational Performance; Bank and Financial Institutions; Human Resource Management; Brazil.;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • G2 - Financial Economics - - Financial Institutions and Services

    Statistics

    Access and download statistics

    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:ebl:ecbull:eb-18-00636. 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: John P. Conley (email available below). General contact details of provider: .

    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.