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A Professional Premium for LHC Students: Perceptions from within

Author

Listed:
  • Tiziano CAMPORESI
  • Gelsomina CATALANO
  • Massimo FLORIO
  • Francesco GIFFONI

Abstract

More than 36,000 students and post-docs will be involved in experiments at the Large Hadron Collider (LHC) until 2025. Do they expect that their learning experience will have an impact on their professional future? By drawing from earlier salary expectations literature, this paper proposes a framework aiming at explaining the professional expectations of early career researchers (ECR) at the LHC. The model is tested by data from a survey involving 318 current and former students (now employed in different jobs) at LHC. Results from different ordered logistic models suggest that experiential learning at LHC positively correlates with both current and former students’ salary expectations. At least two not mutually exclusive explanations underlie such a relationship. First, the training at LHC gives early career researchers valuable expertise, which in turn affects salary expectations; secondly, respondents recognise that the LHC research experience per se may act as signal in the labour market. Respondents put a price tag on their experience at LHC, a ‘salary premium’ ranging from 5% to 11% in terms of their future salaries compared with what they would have expected without such experience

Suggested Citation

  • Tiziano CAMPORESI & Gelsomina CATALANO & Massimo FLORIO & Francesco GIFFONI, 2016. "A Professional Premium for LHC Students: Perceptions from within," Departmental Working Papers 2016-07, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano, revised 08 Jun 2016.
    • Handle: RePEc:mil:wpdepa:2016-07
    as

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    References listed on IDEAS

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    More about this item

    Keywords

    Research infrastructures; Cost-Benefit Analysis; Human Capital; Expectations; Salary Premium; Large Hadron Collider;
    All these keywords.

    JEL classification:

    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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