IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v39y2024i1d10.1007_s00180-022-01278-5.html
   My bibliography  Save this article

Evaluating countries’ performances by means of rank trajectories: functional measures of magnitude and evolution

Author

Listed:
  • Francesca Fortuna

    (Roma Tre University)

  • Alessia Naccarato

    (Roma Tre University)

  • Silvia Terzi

    (Roma Tre University)

Abstract

Countries’ performance can be compared by means of indicators, which in turn give rise to rankings at a given time. However, the ranking does not show whether a country is improving, worsening or is stable in its performance. Meanwhile, the evolutionary behaviour of a country’s performance is of fundamental importance to assess the effect of the adopted policies in both absolute and comparative terms. Nevertheless, establishing a general ranking among countries over time is an open problem in the literature. Consequently, this paper aims to analyze ranks’ dynamic by means of the functional data analysis approach. Specifically, countries’ performances are evaluated by taking into account both their ranking position and their evolutionary behaviour, and by considering two functional measures: the modified hypograph index and the weighted integrated first derivative. The latter are scalar measures that are able to reflect trajectories behaviours over time. Furthermore, a novel visualisation technique based on the suggested measures is proposed to identify groups of countries according to their performance. The effectiveness of the proposed method is shown through a simulation study. The procedure is also applied on a real dataset that is drawn from the Government Effectiveness index of 27 European countries.

Suggested Citation

  • Francesca Fortuna & Alessia Naccarato & Silvia Terzi, 2024. "Evaluating countries’ performances by means of rank trajectories: functional measures of magnitude and evolution," Computational Statistics, Springer, vol. 39(1), pages 141-157, February.
    • Handle: RePEc:spr:compst:v:39:y:2024:i:1:d:10.1007_s00180-022-01278-5
    DOI: 10.1007/s00180-022-01278-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-022-01278-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00180-022-01278-5?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. Philip Yu & Paul Lee & W. Wan, 2013. "Factor analysis for paired ranked data with application on parent–child value orientation preference data," Computational Statistics, Springer, vol. 28(5), pages 1915-1945, October.
    2. Sen, Amartya, 1981. "Public Action and the Quality of Life in Developing Countries," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 43(4), pages 287-319, November.
    3. Alexandre Leblanc, 2010. "A bias-reduced approach to density estimation using Bernstein polynomials," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(4), pages 459-475.
    4. Po-Chin Wu & Chiung-Wen Fan & Sheng-Chieh Pan, 2014. "Does Human Development Index Provide Rational Development Rankings? Evidence from Efficiency Rankings in Super Efficiency Model," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 116(2), pages 647-658, April.
    5. Jiguo Cao & James Ramsay, 2007. "Parameter cascades and profiling in functional data analysis," Computational Statistics, Springer, vol. 22(3), pages 335-351, September.
    6. Goldberger, Arthur S, 1972. "Maximum-Likelihood Estimation of Regressions Containing Unobservable Independent Variables," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(1), pages 1-15, February.
    7. J. Ramsay, 1991. "Kernel smoothing approaches to nonparametric item characteristic curve estimation," Psychometrika, Springer;The Psychometric Society, vol. 56(4), pages 611-630, December.
    8. Miki Malul & Yossi Hadad & Avner Ben‐Yair, 2009. "Measuring and ranking of economic, environmental and social efficiency of countries," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 36(8), pages 832-843, July.
    9. Manuela Cattelan & Cristiano Varin & David Firth, 2013. "Dynamic Bradley–Terry modelling of sports tournaments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(1), pages 135-150, January.
    10. Ana Maria Aguilera & Francesca Fortuna & Manuel Escabias & Tonio Di Battista, 2021. "Assessing Social Interest in Burnout Using Google Trends Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 587-599, August.
    11. Manuel Febrero & Pedro Galeano & Wenceslao González-Manteiga, 2007. "A functional analysis of NOx levels: location and scale estimation and outlier detection," Computational Statistics, Springer, vol. 22(3), pages 411-427, September.
    12. Reiss, Philip T. & Ogden, R. Todd, 2007. "Functional Principal Component Regression and Functional Partial Least Squares," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 984-996, September.
    13. Laurens Cherchye & Erwin Ooghe & Tom Puyenbroeck, 2008. "Robust human development rankings," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(4), pages 287-321, December.
    14. Chen, Yaqing & Dawson, Matthew & Müller, Hans-Georg, 2020. "Rank dynamics for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 149(C).
    15. Noël Veraverbeke & Irène Gijbels & Marek Omelka, 2014. "Preadjusted non-parametric estimation of a conditional distribution function," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(2), pages 399-438, March.
    16. Phillis, Yannis A. & Grigoroudis, Evangelos & Kouikoglou, Vassilis S., 2011. "Sustainability ranking and improvement of countries," Ecological Economics, Elsevier, vol. 70(3), pages 542-553, January.
    17. Lee, Hsing-Chen & Chang, Ching-Ter, 2018. "Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 92(C), pages 883-896.
    18. Francesca Fortuna & Stefano Antonio Gattone & Tonio Di Battista, 2020. "Functional estimation of diversity profiles," Environmetrics, John Wiley & Sons, Ltd., vol. 31(8), December.
    19. Kelley, Judith G. & Simmons, Beth A., 2019. "Introduction: The Power of Global Performance Indicators," International Organization, Cambridge University Press, vol. 73(3), pages 491-510, July.
    20. Yang Zhang & Yu Xiao & Jun Wu & Xin Lu, 2021. "Comprehensive world university ranking based on ranking aggregation," Computational Statistics, Springer, vol. 36(2), pages 1139-1152, June.
    21. López-Pintado, Sara & Romo, Juan, 2011. "A half-region depth for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1679-1695, April.
    22. Kai-yuen Tsui, 1996. "Improvement indices of well-being (*)," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 13(3), pages 291-303.
    23. Samanta, M., 1989. "Non-parametric estimation of conditional quantiles," Statistics & Probability Letters, Elsevier, vol. 7(5), pages 407-412, 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. Rahman, Tauhidur & Mittelhammer, Ron C. & Wandschneider, Philip R., 2011. "Measuring quality of life across countries: A multiple indicators and multiple causes approach," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 40(1), pages 43-52, February.
    2. Christian Genest & Johanna G. Nešlehová, 2014. "A Conversation with James O. Ramsay," International Statistical Review, International Statistical Institute, vol. 82(2), pages 161-183, August.
    3. Prados de la Escosura, Leandro, 2013. "Human development in Africa: A long-run perspective," Explorations in Economic History, Elsevier, vol. 50(2), pages 179-204.
    4. Francesca Fortuna & Alessia Naccarato & Silvia Terzi, 2024. "Country rankings according to well-being evolution: composite indicators from a functional data analysis perspective," Annals of Operations Research, Springer, vol. 342(3), pages 1529-1546, November.
    5. Rob J. Hyndman & Han Lin Shang, 2008. "Rainbow plots, Bagplots and Boxplots for Functional Data," Monash Econometrics and Business Statistics Working Papers 9/08, Monash University, Department of Econometrics and Business Statistics.
    6. Chen, Yaqing & Dawson, Matthew & Müller, Hans-Georg, 2020. "Rank dynamics for functional data," Computational Statistics & Data Analysis, Elsevier, vol. 149(C).
    7. Iñaki Permanyer, 2016. "Measuring Achievement and Shortfall Improvements in a Consistent Way," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(4), pages 758-774, December.
    8. Belalia, Mohamed & Bouezmarni, Taoufik & Leblanc, Alexandre, 2017. "Smooth conditional distribution estimators using Bernstein polynomials," Computational Statistics & Data Analysis, Elsevier, vol. 111(C), pages 166-182.
    9. Claus Thorn Ekstrøm & Andreas Kryger Jensen, 2023. "Having a ball: evaluating scoring streaks and game excitement using in-match trend estimation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 295-311, March.
    10. Mia Hubert & Peter Rousseeuw & Pieter Segaert, 2015. "Multivariate functional outlier detection," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 177-202, July.
    11. Francis,David C. & Kubinec ,Robert, 2022. "Beyond Political Connections : A Measurement Model Approach to Estimating Firm-levelPolitical Influence in 41 Economies," Policy Research Working Paper Series 10119, The World Bank.
    12. Feng, Jianghong & Guo, Ping & Xu, Guangyi & Xu, Gangyan & Ning, Yu, 2024. "An integrated decision framework for resilient sustainable waste electric vehicle battery recycling transfer station site selection," Applied Energy, Elsevier, vol. 373(C).
    13. Fabio Sabatini, 2006. "Social Capital and Labour Productivity in Italy," Working Papers 2006.30, Fondazione Eni Enrico Mattei.
    14. Albino Prada-Blanco & Patricio Sanchez-Fernandez, 2017. "Empirical Analysis of the Transformation of Economic Growth into Social Development at an International Level," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 130(3), pages 983-1003, February.
    15. Aleksandra Maksimovska & Aleksandar Stojkov, 2019. "Composite Indicator of Social Responsiveness of Local Governments: An Empirical Mapping of the Networked Community Governance Paradigm," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(2), pages 669-706, July.
    16. Ufuk Beyaztas & Han Lin Shang, 2021. "A partial least squares approach for function-on-function interaction regression," Computational Statistics, Springer, vol. 36(2), pages 911-939, June.
    17. Md Altab Hossin & Shuwen Xiong & David Alemzero & Hermas Abudu, 2023. "Analyzing the Progress of China and the World in Achieving Sustainable Development Goals 7 and 13," Sustainability, MDPI, vol. 15(19), pages 1-16, September.
    18. Ángeles Sánchez-Domínguez & Maria J. Ruiz Martos, 2013. "Europe 2020 strategy: a strategy for which type of growth?," ThE Papers 13/11, Department of Economic Theory and Economic History of the University of Granada..
    19. Eduardo L. Montoya & Wendy Meiring, 2016. "An F-type test for detecting departure from monotonicity in a functional linear model," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(2), pages 322-337, June.
    20. Ouimet, Frédéric & Tolosana-Delgado, Raimon, 2022. "Asymptotic properties of Dirichlet kernel density estimators," Journal of Multivariate Analysis, Elsevier, vol. 187(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:spr:compst:v:39:y:2024:i:1:d:10.1007_s00180-022-01278-5. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.