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Measuring and explaining the production efficiency of Spanish universities using a non-parametric approach and a bootstrapped-truncated regression

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  • Manuel Salas-Velasco

    (University of Granada)

Abstract

The identification of environmental factors that explain differences in efficiency is essential for improving the results of public universities. A two-stage, semi-parametric approach with the single and double bootstrap procedure (Algorithm #1 and Algorithm #2) proposed by Simar and Wilson (J Econom 136(1):31–64, 2007) was used in this article for making valid inferences about the impact of environmental factors on university efficiency. A data envelopment analysis (DEA) efficiency estimator was used in the first stage to estimate technical efficiency scores for Spanish public universities. It is common to explore the determinants of (in)efficiency in a second stage. To provide valid inference, Simar and Wilson (2007) suggested a parametric bootstrap of the truncated regression (Algorithm #1). Alternatively, they recommended a bootstrap procedure to obtain bias-corrected technical efficiency scores used in the second-stage truncated regression; valid inference can be obtained by using a second bootstrap procedure applied to the truncated regression (Algorithm #2). Under both algorithms, three environmental factors were statistically significant predictors of efficiency. Our results confirmed that universities with a higher percentage of academics with tenure, outgoing Erasmus students, and state grantees tend to be less inefficient.

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  • Manuel Salas-Velasco, 2020. "Measuring and explaining the production efficiency of Spanish universities using a non-parametric approach and a bootstrapped-truncated regression," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 825-846, February.
    • Handle: RePEc:spr:scient:v:122:y:2020:i:2:d:10.1007_s11192-019-03324-4
    DOI: 10.1007/s11192-019-03324-4
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    Cited by:

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    3. Shih-Pin Chen & Chung-Wei Chang, 2021. "Measuring the efficiency of university departments: an empirical study using data envelopment analysis and cluster analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 5263-5284, June.
    4. Tavares, Rafael Santos & Angulo-Meza, Lidia & Sant'Anna, Annibal Parracho, 2021. "A proposed multistage evaluation approach for Higher Education Institutions based on network Data envelopment analysis: A Brazilian experience," Evaluation and Program Planning, Elsevier, vol. 89(C).
    5. Mehdi Rhaiem & Nabil Amara, 2020. "Determinants of research efficiency in Canadian business schools: evidence from scholar-level data," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 53-99, October.
    6. Lena Malesevic Perovic & Maja Mihaljevic Kosor, 2020. "The Efficiency of Universities in Achieving Sustainable Development Goals," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 22(54), pages 516-516, April.
    7. María-Celia López-Penabad & José Manuel Maside-Sanfiz & Juan Torrelles Manent & Ana Iglesias-Casal, 2020. "Application of the DEA Double Bootstrap to Analyze Efficiency in Galician Sheltered Workshops," Sustainability, MDPI, vol. 12(16), pages 1-21, August.

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    Keywords

    Data envelopment analysis; Bootstrapped-truncated regression; Simar and Wilson; Efficiency measurement; Spanish public universities;
    All these keywords.

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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