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HESS – Higher Education for Smart Specialisation. Identification and Analysis of Dedicated ESF Funding in the Programming Period 2014 to 2020

Author

Listed:
  • Julia Bachtrögler-Unger
  • Anna Burton

    (WIFO)

  • Maria Riegler

    (WIFO)

  • Fabian Unterlass

    (WIFO)

Abstract

The goal of this research is to explore ESF funding relevant to Higher Education for Smart Specialisation (HESS) in the 2014-2020 programming period. In particular, a keyword string search methodology is applied to the (completed) Kohesio dataset to identify HESS-relevant projects. Based on the co-occurrence of pre-defined keywords concerning human capital development and smart specialisation processes, almost 71,400 projects out of 739,514 unique ESF pro-jects with sufficient information are identified as relevant to the HESS context, which refers to 18.1 percent of corresponding ESF co-funding amounts. In addition to the evaluation of keyword occurrence and combinations, detailed exploratory analyses concerning national and regional differences, thematic intervention fields and the special role of Higher Education Institutions among beneficiaries are conducted to provide more information on the nature of HESS-relevant projects. Significant differences were identified between countries in terms of the share of HESS-relevant funding, taking values between less than 1.5 and 53.1 percent. These differences, however, have to be interpreted before the background of the methodology applied and its sensitivity to input data. Overall, the aim of this report is to give an overview of HESS-relevant ESF allocations as a starting point for further detailed (qualitative) studies and for informing 2021-2027 programming.

Suggested Citation

  • Julia Bachtrögler-Unger & Anna Burton & Maria Riegler & Fabian Unterlass, 2022. "HESS – Higher Education for Smart Specialisation. Identification and Analysis of Dedicated ESF Funding in the Programming Period 2014 to 2020," WIFO Studies, WIFO, number 70372, April.
    • Handle: RePEc:wfo:wstudy:70372
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