IDEAS home Printed from https://ideas.repec.org/p/gra/wpaper/19-02.html
   My bibliography  Save this paper

Multilevel proficiency comparisons with an application to educational outcomes in PISA

Author

Listed:
  • Ricardo Martínez

    () (Department of Economic Theory and Economic History, University of Granada.)

  • Antonio Villar

    () (Department of Economics, Universidad Pablo de Olvide.)

Abstract

We propose in this paper a general framework for evaluation problems in which the outcome range of the variable can be partitioned into a series of levels that may have different meaning or importance, as they may represent qualitatively different results. Measures of poverty, excellence, inclusion or overall performance indicators are particular cases of this type of problems. We focus on the case of additive functions, to facilitate the discussion. This framework is applied to the analysis of educational poverty, excellence and overall performance of 15-year old students, according to the PISA 2015 data for all 68 participating countries and large economies. The analysis provides insights on the differences between countries that are not captured by the average test scores. In addition, we find out that the measures we propose result in rankings of countries different from that of the test scores.

Suggested Citation

  • Ricardo Martínez & Antonio Villar, 2019. "Multilevel proficiency comparisons with an application to educational outcomes in PISA," ThE Papers 19/02, Department of Economic Theory and Economic History of the University of Granada..
  • Handle: RePEc:gra:wpaper:19/02
    as

    Download full text from publisher

    File URL: http://www.ugr.es/~teoriahe/RePEc/gra/wpaper/thepapers19_02.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Barbara Mueller & Stefan C. Wolter, 2011. "The Consequences of Being Different - Statistical Discrimination and the School-to-Work Transition," CESifo Working Paper Series 3345, CESifo.
    2. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    3. François Bourguignon & Satya Chakravarty, 2003. "The Measurement of Multidimensional Poverty," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 1(1), pages 25-49, April.
    4. Baulch, Bob & Masset, Edoardo, 2003. "Do Monetary and Nonmonetary Indicators Tell the Same Story About Chronic Poverty? A Study of Vietnam in the 1990s," World Development, Elsevier, vol. 31(3), pages 441-453, March.
    5. Albarrán, Pedro & Ortuño, Ignacio & Ruiz-Castillo, Javier, 2011. "The measurement of low- and high-impact in citation distributions: Technical results," Journal of Informetrics, Elsevier, vol. 5(1), pages 48-63.
    6. Antonio Villar, 2017. "Lectures on Inequality, Poverty and Welfare," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-319-45562-4, December.
    7. Atkinson, Anthony B., 1970. "On the measurement of inequality," Journal of Economic Theory, Elsevier, vol. 2(3), pages 244-263, September.
    8. Saccone Donatella, 2008. "Educational Inequality and Educational Poverty. the Chinese Case in the Period 1975-2004," Department of Economics and Statistics Cognetti de Martiis. Working Papers 200808, University of Turin.
    9. Kathrin Bertschy & M. Alejandra Cattaneo & Stefan C. Wolter, 2009. "PISA and the Transition into the Labour Market," LABOUR, CEIS, vol. 23(s1), pages 111-137, March.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    social evaluation; education; poverty; excellence; PISA; OECD countries.;

    JEL classification:

    • H7 - Public Economics - - State and Local Government; Intergovernmental Relations
    • I2 - Health, Education, and Welfare - - Education
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • J1 - Labor and Demographic Economics - - Demographic Economics

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:gra:wpaper:19/02. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Angel Solano Garcia.). General contact details of provider: http://edirc.repec.org/data/dtugres.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.