IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v286y2020i3p1187-1196.html
   My bibliography  Save this article

A note on Sigma–Mu efficiency analysis as a methodology for evaluating units through composite indicators

Author

Listed:
  • Tsionas, Mike G.

Abstract

Recent research introduces a methodology for constructing composite indicators, called σ−μ efficiency analysis, illustrating its potential in a case study of world happiness. Building on the landmark research paper, we propose a novel model that allows statistical inference for both weights in the composite indicator as well as inefficiency, fully accounting for outliers in the data and unit-specific heterogeneity in weights. The new techniques are based on Bayesian analysis via Markov Chain Monte Carlo.

Suggested Citation

  • Tsionas, Mike G., 2020. "A note on Sigma–Mu efficiency analysis as a methodology for evaluating units through composite indicators," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1187-1196.
  • Handle: RePEc:eee:ejores:v:286:y:2020:i:3:p:1187-1196
    DOI: 10.1016/j.ejor.2020.03.076
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037722172030309X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2020.03.076?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Geweke, John, 2007. "Interpretation and inference in mixture models: Simple MCMC works," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3529-3550, April.
    2. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2019. "Sigma-Mu efficiency analysis: A methodology for evaluating units through composite indicators," European Journal of Operational Research, Elsevier, vol. 278(3), pages 942-960.
    3. Salvatore Greco & Alessio Ishizaka & Menelaos Tasiou & Gianpiero Torrisi, 2019. "On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 61-94, January.
    4. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages 19-40, Suppl. De.
    5. Greco, Salvatore & Mousseau, Vincent & Slowinski, Roman, 2008. "Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions," European Journal of Operational Research, Elsevier, vol. 191(2), pages 416-436, December.
    6. Doumpos, Michael & Hasan, Iftekhar & Pasiouras, Fotios, 2017. "Bank overall financial strength: Islamic versus conventional banks," Economic Modelling, Elsevier, vol. 64(C), pages 513-523.
    7. Michael Doumpos & Chrysovalantis Gaganis & Fotios Pasiouras, 2016. "Bank Diversification and Overall Financial Strength: International Evidence," Working Papers 1602, University of Crete, Department of Economics.
    8. Salvatore Greco & Alessio Ishizaka & Benedetto Matarazzo & Gianpiero Torrisi, 2018. "Stochastic multi-attribute acceptability analysis (SMAA): an application to the ranking of Italian regions," Regional Studies, Taylor & Francis Journals, vol. 52(4), pages 585-600, April.
    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. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2019. "Sigma-Mu efficiency analysis: A methodology for evaluating units through composite indicators," European Journal of Operational Research, Elsevier, vol. 278(3), pages 942-960.
    2. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2018. "σ-µ efficiency analysis: A new methodology for evaluating units through composite indices," MPRA Paper 83569, University Library of Munich, Germany.
    3. Gaganis, Chrysovalantis & Pasiouras, Fotios & Tasiou, Menelaos & Zopounidis, Constantin, 2021. "CISEF: A composite index of social, environmental and financial performance," European Journal of Operational Research, Elsevier, vol. 291(1), pages 394-409.
    4. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2021. "The ordinal input for cardinal output approach of non-compensatory composite indicators: the PROMETHEE scoring method," European Journal of Operational Research, Elsevier, vol. 288(1), pages 225-246.
    5. Sarah Ben Amor & Fateh Belaid & Ramzi Benkraiem & Boumediene Ramdani & Khaled Guesmi, 2023. "Multi-criteria classification, sorting, and clustering: a bibliometric review and research agenda," Annals of Operations Research, Springer, vol. 325(2), pages 771-793, June.
    6. Figueira, José Rui & Greco, Salvatore & Roy, Bernard, 2022. "Electre-Score: A first outranking based method for scoring actions," European Journal of Operational Research, Elsevier, vol. 297(3), pages 986-1005.
    7. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2019. "The Ordinal Input for Cardinal Output Approach of Non-compensatory Composite Indicators: The PROMETHEE Scoring Method," MPRA Paper 95816, University Library of Munich, Germany.
    8. Peiró-Palomino, Jesús & Picazo-Tadeo, Andrés J. & Tortosa-Ausina, Emili, 2021. "Measuring well-being in Colombian departments. The role of geography and demography," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    9. Chrysovalantis Gaganis & Panagiota Papadimitri & Menelaos Tasiou, 2021. "A multicriteria decision support tool for modelling bank credit ratings," Annals of Operations Research, Springer, vol. 306(1), pages 27-56, November.
    10. Giuliano Resce & Fritz Schiltz, 2021. "Sustainable Development in Europe: A Multicriteria Decision Analysis," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(2), pages 509-529, June.
    11. Cabral, Celso Rômulo Barbosa & Bolfarine, Heleno & Pereira, José Raimundo Gomes, 2008. "Bayesian density estimation using skew student-t-normal mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5075-5090, August.
    12. Arcidiacono, Sally Giuseppe & Corrente, Salvatore & Greco, Salvatore, 2021. "Robust stochastic sorting with interacting criteria hierarchically structured," European Journal of Operational Research, Elsevier, vol. 292(2), pages 735-754.
    13. Alessia Arcidiacono & Gianpiero Torrisi, 2022. "Decentralisation and Resilience: A Multidimensional Approach," Sustainability, MDPI, vol. 14(16), pages 1-25, August.
    14. de Pooter, M.D. & Ravazzolo, F. & Segers, R. & van Dijk, H.K., 2008. "Bayesian near-boundary analysis in basic macroeconomic time series models," Econometric Institute Research Papers EI 2008-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    15. Ana Garcia-Bernabeu & Adolfo Hilario-Caballero & David Pla-Santamaria & Francisco Salas-Molina, 2020. "A Process Oriented MCDM Approach to Construct a Circular Economy Composite Index," Sustainability, MDPI, vol. 12(2), pages 1-14, January.
    16. Vikas Kumar Mishra & Bapi Dutta & Mark Goh & José Rui Figueira & Salvatore Greco, 2021. "A robust ranking of maritime connectivity: revisiting UNCTAD’s liner shipping connectivity index (LSCI)," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(3), pages 424-443, September.
    17. Paolo Liberati & Giuliano Resce, 2022. "Regional Well-Being and its Inequality in the OECD Member Countries," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(3), pages 671-700, September.
    18. David Ardia, 2009. "Bayesian estimation of a Markov-switching threshold asymmetric GARCH model with Student-t innovations," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 105-126, March.
    19. Cinelli, Marco & Kadziński, Miłosz & Gonzalez, Michael & Słowiński, Roman, 2020. "How to support the application of multiple criteria decision analysis? Let us start with a comprehensive taxonomy," Omega, Elsevier, vol. 96(C).
    20. Pereira, Javier & Contreras, Pedro & Morais, Danielle C. & Arroyo-López, Pilar, 2022. "Multi-criteria ordered clustering of countries in the Global Health Security Index," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).

    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:eee:ejores:v:286:y:2020:i:3:p:1187-1196. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.