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Assessing the effect of high performance computing capabilities on academic research output

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Listed:
  • Amy Apon
  • Linh Ngo
  • Michael Payne
  • Paul Wilson

Abstract

This paper uses nonparametric methods and some new results on hypothesis testing with nonparametric efficiency estimators and applies these to analyze the effect of locally available high performance computing (HPC) resources on universities’ efficiency in producing research and other outputs. We find that locally available HPC resources enhance the technical efficiency of research output in Chemistry, Civil Engineering, Physics, and History, but not in Computer Science, Economics, nor English; we find mixed results for Biology. Our research results provide a critical first step in a quantitative economic model for investments in HPC. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Amy Apon & Linh Ngo & Michael Payne & Paul Wilson, 2015. "Assessing the effect of high performance computing capabilities on academic research output," Empirical Economics, Springer, vol. 48(1), pages 283-312, February.
    • Handle: RePEc:spr:empeco:v:48:y:2015:i:1:p:283-312
    DOI: 10.1007/s00181-014-0833-7
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    References listed on IDEAS

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    4. Kneip, Alois & Simar, Léopold & Wilson, Paul W., 2008. "Asymptotics And Consistent Bootstraps For Dea Estimators In Nonparametric Frontier Models," Econometric Theory, Cambridge University Press, vol. 24(6), pages 1663-1697, December.
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    10. Abdelaati Daouia & Léopold Simar & Paul W. Wilson, 2017. "Measuring firm performance using nonparametric quantile-type distances," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 156-181, March.
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    Cited by:

    1. Craig A. Stewart & Claudia M. Costa & Julie A. Wernert & Winona Snapp-Childs & Marques Bland & Philip Blood & Terry Campbell & Peter Couvares & Jeremy Fischer & David Y. Hancock & David L. Hart & Harm, 2023. "Use of accounting concepts to study research: return on investment in XSEDE, a US cyberinfrastructure service," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3225-3255, June.
    2. Wilson, Paul W., 2018. "Dimension reduction in nonparametric models of production," European Journal of Operational Research, Elsevier, vol. 267(1), pages 349-367.
    3. Léopold Simar & Paul W. Wilson, 2023. "Another look at productivity growth in industrialized countries," Journal of Productivity Analysis, Springer, vol. 60(3), pages 257-272, December.
    4. Kneip, Alois & Simar, Léopold & Wilson, Paul W., 2022. "Conical FDH Estimators of General Technologies, with Applications to Returns to Scale and Malmquist Productivity Indices," LIDAM Discussion Papers ISBA 2022024, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

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    More about this item

    Keywords

    Efficiency; Frontier; Nonparametric; Inference; C12; C14; C44; H52;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • H52 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Education

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