IDEAS home Printed from https://ideas.repec.org/a/spr/decfin/v47y2024i2d10.1007_s10203-024-00453-1.html
   My bibliography  Save this article

Two-stage super-efficiency model for measuring efficiency of education in South-East Asia

Author

Listed:
  • M. Mujiya Ulkhaq

    (Diponegoro University)

  • Giorgia Oggioni

    (University of Brescia)

  • Rossana Riccardi

    (University of Brescia)

Abstract

This paper aims to measure the efficiency of schools in six South-East Asian countries, taking into account the impacts of information and communication technologies (ICT). The educational institutions of South-East Asia are very dynamic; and to increase their competitiveness at international level, they need to manage their resources in an efficient way. We propose a two-stage super-efficiency model for measuring their efficiency, using 2018 PISA data. In the first stage, the non-parametric data envelopment analysis super-efficiency model is used to rank the schools in this region. Then, a second-stage analysis based on a bootstrapped quantile regression is performed to identify the factors that potentially influence efficiency. We analyze four different scenarios depending on the output considered. In the first stage of the analysis, Singapore has the best performance among the other countries in all scenarios. In the second stage, our results show that ICT is statistically significant as a determinant of efficiency in terms of the ratio of computers connected to the internet. However, the integration of ICT in education is mainly influenced by the socio-economic and educational factors of the analyzed countries. Moreover, concerning the other factors, the lower efficiency schools benefit more from the number of female students than higher efficiency schools. The reverse happens for the proportion of certified teachers.

Suggested Citation

  • M. Mujiya Ulkhaq & Giorgia Oggioni & Rossana Riccardi, 2024. "Two-stage super-efficiency model for measuring efficiency of education in South-East Asia," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 47(2), pages 513-543, December.
  • Handle: RePEc:spr:decfin:v:47:y:2024:i:2:d:10.1007_s10203-024-00453-1
    DOI: 10.1007/s10203-024-00453-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10203-024-00453-1
    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/s10203-024-00453-1?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. Fare, Rolf & Grosskopf, Shawna, 1996. "Productivity and intermediate products: A frontier approach," Economics Letters, Elsevier, vol. 50(1), pages 65-70, January.
    2. Klaus Wohlrabe & Félix de Moya Anegon & Lutz Bornmann, 2019. "How Efficiently Do Elite US Universities Produce Highly Cited Papers?," Publications, MDPI, vol. 7(1), pages 1-15, January.
    3. Weihua Guan, 2003. "From the help desk: Bootstrapped standard errors," Stata Journal, StataCorp LP, vol. 3(1), pages 71-80, March.
    4. Daniel Santín & Gabriela Sicilia, 2018. "Using DEA for measuring teachers’ performance and the impact on students’ outcomes: evidence for Spain," Journal of Productivity Analysis, Springer, vol. 49(1), pages 1-15, February.
    5. Zhang, Shaopeng & Wang, Xiaohong, 2022. "Does innovative city construction improve the industry–university–research knowledge flow in urban China?," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    6. Oliver Falck & Constantin Mang & Ludger Woessmann, 2018. "Virtually No Effect? Different Uses of Classroom Computers and their Effect on Student Achievement," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 80(1), pages 1-38, February.
    7. Frýd, Lukáš & Sokol, Ondřej, 2021. "Relationships between technical efficiency and subsidies for Czech farms: A two-stage robust approach," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    8. 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.
    9. Zoghbi, Ana Carolina & Rocha, Fabiana & Mattos, Enlinson, 2013. "Education production efficiency: Evidence from Brazilian universities," Economic Modelling, Elsevier, vol. 31(C), pages 94-103.
    10. Tommaso Agasisti & Giuseppe Munda & Ralph Hippe, 2019. "Measuring the efficiency of European education systems by combining Data Envelopment Analysis and Multiple-Criteria Evaluation," Journal of Productivity Analysis, Springer, vol. 51(2), pages 105-124, June.
    11. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    12. Comi, Simona Lorena & Argentin, Gianluca & Gui, Marco & Origo, Federica & Pagani, Laura, 2017. "Is it the way they use it? Teachers, ICT and student achievement," Economics of Education Review, Elsevier, vol. 56(C), pages 24-39.
    13. Kneip, Alois & Simar, Léopold & Wilson, Paul W., 2015. "When Bias Kills The Variance: Central Limit Theorems For Dea And Fdh Efficiency Scores," Econometric Theory, Cambridge University Press, vol. 31(2), pages 394-422, April.
    14. Le, Minh Hanh & Afsharian, Mohsen & Ahn, Heinz, 2021. "Inverse Frontier-based Benchmarking for Investigating the Efficiency and Achieving the Targets in the Vietnamese Education System," Omega, Elsevier, vol. 103(C).
    15. Manuel Salas‐Velasco, 2020. "Assessing the performance of Spanish secondary education institutions: Distinguishing between transient and persistent inefficiency, separated from heterogeneity," Manchester School, University of Manchester, vol. 88(4), pages 531-555, July.
    16. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    17. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    18. Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, March.
    19. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    20. 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.
    21. B. J. Gajewski & R. Lee & M. Bott & U. Piamjariyakul & R. L. Taunton, 2009. "On estimating the distribution of data envelopment analysis efficiency scores: an application to nursing homes' care planning process," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(9), pages 933-944.
    22. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    23. Cook, Wade D. & Liang, Liang & Zhu, Joe, 2010. "Measuring performance of two-stage network structures by DEA: A review and future perspective," Omega, Elsevier, vol. 38(6), pages 423-430, December.
    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. Akther, Syed & Fukuyama, Hirofumi & Weber, William L., 2013. "Estimating two-stage network Slacks-based inefficiency: An application to Bangladesh banking," Omega, Elsevier, vol. 41(1), pages 88-96.
    2. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    3. Imanirad, Raha & Cook, Wade D. & Aviles-Sacoto, Sonia Valeria & Zhu, Joe, 2015. "Partial input to output impacts in DEA: The case of DMU-specific impacts," European Journal of Operational Research, Elsevier, vol. 244(3), pages 837-844.
    4. Vicente J. Bolós & Rafael Benítez & Vicente Coll-Serrano, 2023. "Continuous models combining slacks-based measures of efficiency and super-efficiency," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(2), pages 363-391, June.
    5. Yung-ho Chiu & Chin-wei Huang & Chung-te Ting, 2012. "A non-radial measure of different systems for Taiwanese tourist hotels’ efficiency assessment," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(1), pages 45-63, March.
    6. Tran, Trung Hieu & Mao, Yong & Nathanail, Paul & Siebers, Peer-Olaf & Robinson, Darren, 2019. "Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis," Omega, Elsevier, vol. 85(C), pages 156-165.
    7. 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.
    8. Nocera Alves Junior, Paulo & Costa Melo, Isotilia & de Moraes Santos, Rodrigo & da Rocha, Fernando Vinícius & Caixeta-Filho, José Vicente, 2022. "How did COVID-19 affect green-fuel supply chain? - A performance analysis of Brazilian ethanol sector," Research in Transportation Economics, Elsevier, vol. 93(C).
    9. Chen, Chien-Ming, 2013. "Super efficiencies or super inefficiencies? Insights from a joint computation model for slacks-based measures in DEA," European Journal of Operational Research, Elsevier, vol. 226(2), pages 258-267.
    10. Christian Hernández-Guedes & Jorge V Pérez-Rodríguez & Casiano Manrique-de-Lara-Peñate, 2024. "Input inefficiencies in the hotel industry. A non-radial directional performance measurement," Tourism Economics, , vol. 30(7), pages 1753-1779, November.
    11. Gerami, Javad & Mozaffari, Mohammad Reza & Wanke, Peter F. & Correa, Henrique L., 2022. "Improving information reliability of non-radial value efficiency analysis: An additive slacks based measure approach," European Journal of Operational Research, Elsevier, vol. 298(3), pages 967-978.
    12. Xu Zhang & Huaping Sun & Taohong Wang, 2022. "Impact of Financial Inclusion on the Efficiency of Carbon Emissions: Evidence from 30 Provinces in China," Energies, MDPI, vol. 15(19), pages 1-15, October.
    13. 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.
    14. Carla Henriques & Clara Viseu & António Trigo & Maria Gouveia & Ana Amaro, 2022. "How Efficient Is the Cohesion Policy in Supporting Small and Mid-Sized Enterprises in the Transition to a Low-Carbon Economy?," Sustainability, MDPI, vol. 14(9), pages 1-55, April.
    15. Victoria Wojcik & Harald Dyckhoff & Marcel Clermont, 2019. "Is data envelopment analysis a suitable tool for performance measurement and benchmarking in non-production contexts?," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 559-595, December.
    16. Raul Moragues & Juan Aparicio & Miriam Esteve, 2023. "Measuring technical efficiency for multi-input multi-output production processes through OneClass Support Vector Machines: a finite-sample study," Operational Research, Springer, vol. 23(3), pages 1-33, September.
    17. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    18. Rezaeiani, M.J. & Foroughi, A.A., 2018. "Ranking efficient decision making units in data envelopment analysis based on reference frontier share," European Journal of Operational Research, Elsevier, vol. 264(2), pages 665-674.
    19. Mergoni, Anna & Soncin, Mara & Agasisti, Tommaso, 2023. "The effect of ICT on schools’ efficiency: Empirical evidence on 23 European countries," Omega, Elsevier, vol. 119(C).
    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

    Bootstrapped quantile regression; Education; South-East Asia; Super-efficiency; Slacks-based measure;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education

    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:spr:decfin:v:47:y:2024:i:2:d:10.1007_s10203-024-00453-1. 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.