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Unlocking University Efficiency: A Bayesian Stochastic Frontier Analysis

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  • Zaira García-Tórtola

    (Department of Economics, Universitat Jaume I, Castellón, Spain)

  • David Conesa

    (Department of Statistics and Operational Research, Universidad de Valencia, Spain)

  • Joan Crespo

    (Department of Economic Structure, Universidad de Valencia, Spain)

  • Emili Tortosa-Ausina

    (IVIE, Valencia and IIDL and Department of Economics, Universitat Jaume I, Castellón, Spain)

Abstract

In this paper, we analyse the performance of the Spanish public university system over the 2010–2019 period, which was particularly turbulent due to the tight budget constraints imposed on universities. To disentangle the main sources of performance change, we adopt a dynamic approach by decomposing it into efficiency change (catching up) and technical change (shifts in the frontier). In contrast to many studies on Higher Education Institutions (HEIs), we opt for Stochastic Frontier Analysis (SFA), employing the ray production function proposed by Löthgren (1997) to account for the multiple-output nature of HEIs. Additionally, to offer a more detailed examination of uncertainty quantification, we conduct inference within the Bayesian paradigm. Broadly, results point to an overall positive performance change over the entire period, particularly for technical change during 2010–2014. However, there were notable discrepancies across universities, which could be unlocked with certain precision via the posterior distributions of performance and its components.

Suggested Citation

  • Zaira García-Tórtola & David Conesa & Joan Crespo & Emili Tortosa-Ausina, 2024. "Unlocking University Efficiency: A Bayesian Stochastic Frontier Analysis," Working Papers 2024/05, Economics Department, Universitat Jaume I, Castellón (Spain).
  • Handle: RePEc:jau:wpaper:2024/05
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    Keywords

    efficiency; Bayesian; education; stochastic frontier; universities;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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