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Measuring the Efficiency of Education and Technology via DEA approach: Implications on National Development

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  • Huan Xu

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China
    School of Public Administration, South China University of Technology, Guangzhou 510641, China)

  • Fangtao Liu

    (School of Public Policy and Management, Tsinghua University, Beijing 100084, China)

Abstract

The aim of this paper is to provide a new approach for assessing the input–output efficiency of education and technology for national science and education department. We used the Data Envelopment Analysis (DEA) method to analyze the efficiency sharing activities in education and technology sector, and classify input variables and output variables accordingly. Using the panel data in the education and technology sector of 53 countries, we found that the countries with significant progress in educational efficiency and technological efficiency mainly concentrated in East Asia, especially in Japan, Korea, Taiwan and some other developing countries. We further evaluate the effect of educational and technological efficiencies on national competitiveness, balanced development of the country, national energy efficiency, export, and employment. We found that the efficiency of science and technology has an effect on the balanced development of the country, but that of education has played a counter-productive role; Educational efficiency has a large role and related the country’s educational development. In addition, using the panel data analysis, we showed that educational and technological efficiency has different degrees of contributions to the development from 2000 to 2014. It mainly depends on the economic development progress and the push for the education and technological policy. The proposed approach in this paper provides the decision-making support for the education and technological policy formulation, specially the selection of the appropriate education and technological strategies for resource allocation and process evaluation.

Suggested Citation

  • Huan Xu & Fangtao Liu, 2017. "Measuring the Efficiency of Education and Technology via DEA approach: Implications on National Development," Social Sciences, MDPI, vol. 6(4), pages 1-13, November.
    • Handle: RePEc:gam:jscscx:v:6:y:2017:i:4:p:136-:d:117763
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    References listed on IDEAS

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    1. Shawna Grosskopf & Kathy J. Hayes & Lori L. Taylor, 2014. "Efficiency in Education: Research and Implications," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 36(2), pages 175-210.
    2. Seema Sharma & V. J. Thomas, 2008. "Inter-country R&D efficiency analysis: An application of data envelopment analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 483-501, September.
    3. Aristovnik, Aleksander & Obadić, Alka, 2014. "Measuring relative efficiency of secondary education in selected EU and OECD countries: the case of Slovenia and Croatia," MPRA Paper 63936, University Library of Munich, Germany.
    4. Jose Manuel Cordero-Ferrera & Francisco Pedraja-Chaparro & Javier Salinas-Jimenez, 2008. "Measuring efficiency in education: an analysis of different approaches for incorporating non-discretionary inputs," Applied Economics, Taylor & Francis Journals, vol. 40(10), pages 1323-1339.
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    Cited by:

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    2. Lipeng Chen & Yang Yu & Amsalu K. Addis & Xiao Guo, 2022. "Empirical Assessment and Comparison of Educational Efficiency between Major Countries across the World," Sustainability, MDPI, vol. 14(7), pages 1-17, March.
    3. Milica Jovanović & Gordana Savić & Yuzhuo Cai & Maja Levi-Jakšić, 2022. "Towards a Triple Helix based efficiency index of innovation systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2577-2609, May.

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