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The STEM requirements of “Non-STEM” jobs: Evidence from UK online vacancy postings
ARTICLE

Economics of Education Review Volume 70, Number 1, ISSN 0272-7757 Publisher: Elsevier Ltd

Abstract

Are employers in “non-STEM” occupations (e.g. "Graphic Designers, Economists") interested in STEM (Science, Technology, Engineering, and Mathematics) graduates because of the knowledge and skills they acquired through their STEM education (e.g. "“C++”, “Systems Engineering”") or simply because of their problem solving and analytical abilities? This is an important question in the UK where less than half of STEM graduates work in STEM occupations, and where this apparent leakage from the “STEM pipeline” is often considered as a wastage of resources. To address it, this paper goes beyond the discrete divide of occupations into STEM vs. non-STEM: using UK online vacancy postings, we measure STEM requirements at the level of jobs, by classifying each posting as either STEM or non-STEM based on its job description text instead of its occupation identifier. We find that 35% of all STEM jobs belong to non-STEM occupations, and that 15% of all vacancies posted in non-STEM occupations are in fact STEM jobs. Moreover, STEM jobs are associated with higher wages within both STEM and non-STEM occupations.

Citation

Grinis, I. (2019). The STEM requirements of “Non-STEM” jobs: Evidence from UK online vacancy postings. Economics of Education Review, 70(1), 144-158. Elsevier Ltd. Retrieved June 18, 2021 from .

This record was imported from Economics of Education Review on June 3, 2019. Economics of Education Review is a publication of Elsevier.

Full text is availabe on Science Direct: http://dx.doi.org/10.1016/j.econedurev.2019.02.005

Keywords

References

View References & Citations Map
  1. Baayen, R. H. (2008). Analyzing Linguistic Data: A Practical Introduction to Statistics Using R. Cambridge University Press.
  2. Benoit, K., & Nulty, P. (2015). Quanteda: Quantitative analysis of textual data. R package version 0.7.2-1.
  3. BIS (2014). ‘Research into the need for and capacity to deliver STEM related apprenticeship provision in England’. BIS Research Paper Number 171.
  4. Bosworth, D., Lyonette, C., Wilson, R., Bayliss, M., & Fathers, S. (2013). ‘The supply of and demand for high-level STEM skills’. UKCES Evidence Report 77.
  5. Carnevale, A., Jayasundera, T., & Repnikov, D. (2014). ‘Understanding online job ads data: A technical report’. George Town University.
  6. Chevalier, A. (2012). ‘To be or not to be... a scientist?’. IZA Discussion Paper No. 6353.
  7. Department for Innovation Universities, and Skills (2009). The demand for Science, Technology, Engineering and Mathematics (STEM) skills.
  8. Feinerer, I., Hornik, K., & Meyer, D. (2015). tm: Text mining package. R package version 0.6-2.
  9. Feinerer, I., Hornik, K., & Meyer, D. (2008). ‘Text mining infrastructure in R’. Journal of Statistical Software, 25(5).
  10. Fellows, I. (2014). wordcloud: Word clouds. R package version 2.5.
  11. Forth, J., & Mason, G. (2006). ‘Do ICT skill shortages hamper firms’ performance? Evidence from UK benchmarking surveys’. National Institute of Economic and Social Research.
  12. Gagolewski, M., & Tartanus, B. (2016). R package stringi: Character string processing facilities.
  13. General Assembly & Burning Glass Technologies. (2015). ‘Blurring lines: How business and technology skills are merging to create high opportunity hybrid jobs’.
  14. Greenwood, C., Harrison, M., & Vignoles, A. (2011). ‘The labour market value of STEM qualifications and occupations’. Royal Academy of Engineering, Department of Quantitative Social Science, Institute of Education.
  15. Grinis, I. (2017). ‘The STEM requirements of “Non-STEM” jobs: Evidence from UK vacancy postings and Implications for skills & knowledge shortages’. SRC Discussion Paper No. 69.
  16. Harrison, M. (2012). ‘Jobs and growth: the importance of engineering skills to the UK economy’. Royal Academy of Engineering Econometrics of Engineering Skills Project.
  17. Hornik, K. (2015). Nlp: Natural language processing infrastructure. R package version 0.1–8.
  18. Levy, C.; Hopkins, L., Shaping up for innovation: are we delivering the right skills for the 2020 knowledge economy?. (2010) The Work Foundation: London.
  19. Manning, C.D., Raghavan, P., & Schutze, H. (2009). An Introduction to Information Retrieval.
  20. Mason, G. (2012). ‘Science, Engineering and Technology Technicians in the UK Economy’. National Institute of Economic and Social Research.
  21. Mellors-Bourne, R., Connor, H., & Jackson, C. (2011). ‘STEM graduates in non STEM jobs’. BIS Research Paper number 30.
  22. Reamer, A. (2013). ‘Using real-time labor market information on a nationwide scale’. Jobs For the Future.
  23. Rothwell, J. (2014). ‘Still searching: Job vacancies and STEM skills’. Brookings.
  24. Rothwell, J. (2013). ‘The hidden STEM economy’. Brookings.
  25. Sanchez, G. (2013). Handling and Processing Strings in R. Berkeley: Trowchez Editions.
  26. Sigelman, M. (2016). ‘Why the STEM gap is bigger than you think’.
  27. UK Commission for Employment and Skills (2016). ‘Working futures: 2014–2024’. UKCES Evidence Report 100.
  28. UK Commission for Employment and Skills (2015). ‘Reviewing the requirement for high level STEM skills’. UKCES Evidence Report 94.
  29. Wickham, H. (2015). Stringr: Simple, consistent wrappers for common string operations. R package version 1.0.0.
  30. Wilson, R. (2009). ‘The demand for STEM graduates: some benchmark projections’. Council for Industry and Higher Education.

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