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Efficiency Analysis with Educational Data: How to Deal with Plausible Values from International Large-Scale Assessments

Author

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  • Juan Aparicio

    (Center of Operations Research (CIO), University Miguel Hernandez of Elche (UMH), 03202 Elche, Spain)

  • Jose M. Cordero

    (Department of Economics, University of Extremadura (UEX), 06006 Badajoz, Spain)

  • Lidia Ortiz

    (Center of Operations Research (CIO), University Miguel Hernandez of Elche (UMH), 03202 Elche, Spain)

Abstract

International large-scale assessments (ILSAs) provide several measures as a representation of educational outcomes, the so-called plausible values, which are frequently interpreted as a representation of the ability range of students. In this paper, we focus on how this information should be incorporated into the estimation of efficiency measures of student or school performance using data envelopment analysis (DEA). Thus far, previous studies that have adopted this approach using data from ILSAs have used only one of the available plausible values or an average of all of them. We propose an approach based on the fuzzy DEA, which allows us to consider the whole distribution of results as a proxy of student abilities. To assess the extent to which our proposal offers similar results to those obtained in previous studies, we provide an empirical example using PISA data from 2015. Our results suggest that the performance measures estimated using the fuzzy DEA approach are strongly correlated with measures calculated using just one plausible value or an average measure. Therefore, we conclude that the studies that decide upon using one of these options do not seem to be making a significant error in their estimates.

Suggested Citation

  • Juan Aparicio & Jose M. Cordero & Lidia Ortiz, 2021. "Efficiency Analysis with Educational Data: How to Deal with Plausible Values from International Large-Scale Assessments," Mathematics, MDPI, vol. 9(13), pages 1-16, July.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:13:p:1579-:d:588681
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    References listed on IDEAS

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    1. Aparicio, Juan & Cordero, Jose M. & Ortiz, Lidia, 2019. "Measuring efficiency in education: The influence of imprecision and variability in data on DEA estimates," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    2. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    3. Hatami-Marbini, Adel & Emrouznejad, Ali & Tavana, Madjid, 2011. "A taxonomy and review of the fuzzy data envelopment analysis literature: Two decades in the making," European Journal of Operational Research, Elsevier, vol. 214(3), pages 457-472, November.
    4. Waldo, Staffan, 2007. "On the use of student data in efficiency analysis--Technical efficiency in Swedish upper secondary school," Economics of Education Review, Elsevier, vol. 26(2), pages 173-185, April.
    5. Joseph L. Schafer, 2003. "Multiple Imputation in Multivariate Problems When the Imputation and Analysis Models Differ," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 57(1), pages 19-35, February.
    6. Aparicio, Juan & Cordero, Jose M. & Pastor, Jesus T., 2017. "The determination of the least distance to the strongly efficient frontier in Data Envelopment Analysis oriented models: Modelling and computational aspects," Omega, Elsevier, vol. 71(C), pages 1-10.
    7. José Manuel Cordero & Daniel Santín & Rosa Simancas, 2017. "Assessing European primary school performance through a conditional nonparametric model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 364-376, April.
    8. Kristof De Witte & Mika Kortelainen, 2013. "What explains the performance of students in a heterogeneous environment? Conditional efficiency estimation with continuous and discrete environmental variables," Applied Economics, Taylor & Francis Journals, vol. 45(17), pages 2401-2412, June.
    9. Aparicio, Juan & Cordero, Jose M. & Gonzalez, Martin & Lopez-Espin, Jose J., 2018. "Using non-radial DEA to assess school efficiency in a cross-country perspective: An empirical analysis of OECD countries," Omega, Elsevier, vol. 79(C), pages 9-20.
    10. Thieme, Claudio & Prior, Diego & Tortosa-Ausina, Emili, 2013. "A multilevel decomposition of school performance using robust nonparametric frontier techniques," Economics of Education Review, Elsevier, vol. 32(C), pages 104-121.
    11. Agasisti, Tommaso & Zoido, Pablo, 2019. "The efficiency of schools in developing countries, analysed through PISA 2012 data," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    12. Ganzeboom, H.B.G. & de Graaf, P.M. & Treiman, D.J. & de Leeuw, J., 1992. "A standard international socio-economic index of occupational status," WORC Paper 92.01.001/1, Tilburg University, Work and Organization Research Centre.
    13. Eva Crespo-Cebada & Francisco Pedraja-Chaparro & Daniel Santín, 2014. "Does school ownership matter? An unbiased efficiency comparison for regions of Spain," Journal of Productivity Analysis, Springer, vol. 41(1), pages 153-172, February.
    14. Cordero, Jose M. & Polo, Cristina & Santín, Daniel & Simancas, Rosa, 2018. "Efficiency measurement and cross-country differences among schools: A robust conditional nonparametric analysis," Economic Modelling, Elsevier, vol. 74(C), pages 45-60.
    15. José-Manuel Sáez-López & María-Concepción Domínguez-Garrido & María-del-Castañar Medina-Domínguez & Fuensanta Monroy & Raúl González-Fernández, 2021. "The Competences from the Perception and Practice of University Students," Social Sciences, MDPI, vol. 10(2), pages 1-12, January.
    16. Maarten Marsman & Gunter Maris & Timo Bechger & Cees Glas, 2016. "What can we learn from Plausible Values?," Psychometrika, Springer;The Psychometric Society, vol. 81(2), pages 274-289, June.
    17. Kevin Macdonald, 2008. "PV: Stata module to perform estimation with plausible values," Statistical Software Components S456951, Boston College Department of Economics, revised 25 Oct 2023.
    18. Justo de Jorge Moreno & Daniel Santín, 2010. "Determinantes de la eficiencia educativa en la Unión Europea," Hacienda Pública Española / Review of Public Economics, IEF, vol. 193(2), pages 131-156, June.
    19. 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.
    20. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
    21. Francesco Avvisati & François Keslair, 2014. "REPEST: Stata module to run estimations with weighted replicate samples and plausible values," Statistical Software Components S457918, Boston College Department of Economics, revised 21 Mar 2024.
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    2. Henriques, C.O. & Chavez, J.M. & Gouveia, M.C. & Marcenaro-Gutierrez, O.D., 2022. "Efficiency of secondary schools in Ecuador: A value based DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PA).

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