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Jobs, skills and the extractive industries: a review and situation analysis

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Abstract

Host governments and communities commonly expect that the extractive industries provide jobs and contribute to skills development, especially in Sub-Saharan African countries where many young people join local labour markets in record numbers every year. This article reviews the literature and offers an empirically informed situation analysis on the demand and supply characteristics of the jobs and skills associated with the sector. Against this background, it discusses some challenges and implications for skills development interventions and offers some insights from the E4D/SOGA programme.

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Notes

  1. E4D/SOGA is an initiative of the E4D Programme (Employment for Sustainable Development in Africa), implemented by GIZ and commissioned by the German Federal Ministry for Economic Cooperation (BMZ), with co-funding from the UK Department for International Development (DfID), the Norwegian Agency for Development Cooperation (Norad), Royal Dutch Shell, Rio Tinto, Tullow Oil and Quoniam Asset Management GmbH. E4D/SOGA pursues a demand-led approach to skills development and includes activities that support entrepreneurship and self-employment. For details, see: https://www.giz.de/en/worldwide/31947.html (last accessed 18 December 2018).

  2. Raw Talk (now High Grade) interview with British Environmentalist, Tom Burke, 17 January 2019. See: http://tomburke.co.uk/2019/01/17/climate-change-and-the-extractives-raw-talks-with-tom-burke/ (last accessed 17 January 2019).

  3. For example, this argument is incorporated in the AfDB and BMGF (2015) report on leveraging natural resources to accelerate human development in Africa.

  4. A more recent analysis confirms the conclusions drawn in the early 2000s (Baumann 2018).

  5. See also Venables (2007) on the natural versus human capital argument. Venables makes the important point that the usual dichotomy of ‘skilled’ versus ‘unskilled’ labour that economic growth theories have assumed for their modelling is too sharp to fully understand the incentives versus disincentives of resource-endowed economies to invest in and acquire knowledge and skills.

  6. See several studies (re-)published in Lederman and Maloney (2007).

  7. A similar conclusion was drawn by Hujo (2012).

  8. Literacy rates of nearly 100% were reached within one generation.

  9. To the author’s knowledge, a similar story line applies to the success of certain industrial activities in former mining regions in Germany.

  10. See also Wright and Czelusta (2007).

  11. For the Chilean experience, see also Crowson (2009).

  12. Lederman and Xu (2007) purport that such general ‘production knowledge’ could be measured in terms of a country’s stock of technical workers, where this stock signals a country’s comparative advantage in making things out of different types of materials. However, this knowledge is not easily transferred across borders.

  13. See Powell and McGrath’s work on VET in the South African context and the role of Further Education Colleges in increasing the employability of youth from poorer and more marginalised backgrounds (2019).

  14. The remaining percentage shares go towards payments to governments, investor returns and spending on social investment. See Östensson (2018).

  15. See Östensson (2019) for a critique of this argument.

  16. This differs from the historical context where in the past resource extraction would have required a substantial workforce, e.g. the nineteenth century coal industry.

  17. This section relies on the author’s observations drawn from working in, and with representatives from the sector.

  18. For example, see Total E&P (2014) available here: https://unctad.org/meetings/en/Presentation/12-OILGASMINE%20Special%20Event%2015-16%20Oct%202014-HAMMANN-2-en.pdf (last accessed 18 February 2019).

  19. The author has conducted respective labour demand assessment for the industry, presenting industry representatives with a multi-country reference framework to map out and explain typical training and industry career paths.

  20. See also Cordes et al. (2016).

  21. Nearly 40% of those working in mining and quarrying also participate in subsistence agriculture.

  22. See: https://www.igfmining.org/formalizing-artisanal-and-small-scale-mining-for-inclusive-sustainable-development/ (last accessed 25 January 2018).

  23. There are different definitions of core and soft skills and what these entail – ranging from foundational core skills such as numeracy, literacy, the ability to learn independently, self-motivation, self-discipline, etc., to soft skills such as being able to communicate effectively, critical, creative and innovative thinking, and interpersonal and social skills of working in teams and acting with integrity.

  24. Historical references frequently mention early-day mining nomads actively exploring and producing in Latin America, North America, Australia and elsewhere.

  25. See: https://www.opito.com (last accessed 30 January 2019).

  26. ILO (2007) defines transferable skills as ‘employable skills which can be used productively in different jobs, occupations, industries’. They comprise core skills and vocational–technical skills, where these are further broken down into, ‘traditional’ core skills (communication and social) and ‘new’ core skills (learning, cognitive and personal), as well as ‘general’ and ‘specific’ vocational/technical skills. Transferable skills are sometimes also referred to as portable skills. See, for example, Östensson (2019).

  27. Author’s observation based on discussions with industry experts.

  28. For example, Östensson (2018) highlights lower transport costs and greater exposure to international competition limiting opportunities for local suppliers to the extractive industries as well as downstream processing. Nowadays, specialised labour and state-of-the-art technology are also travelling more easily, thus reducing the need for local innovation. See also Crowson (2009) for the limits of drawing on historical cases compared to today’s mining industry.

  29. These results have prompted the more ambitious Sustainable Development Goals (SDGs), adopted in 2015, to emphasise quality education (Goal 4). The SDGs have also elevated the attention paid to vocational–technical training, responding to labour market needs and offering opportunities for taking up self-employment. There is also a goal on decent work, i.e. quality jobs (Goal 8).

  30. See Edwards (2018) for a fundamental critique of the Human Capital Index.

  31. The other three indicators are (i) the probability of survival to age five, (ii) adult survival rate (fraction of 15-year olds that will survive to age 60), and (iii) the proportion of children who are not stunted.

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Acknowledgements

The author received funding from the E4D/SOGA (Employment and Skills for Eastern Africa) Programme, financed by the German Federal Ministry for Economic Cooperation (BMZ), the UK Department for International Development (DfID), the Norwegian Agency for Development Cooperation (Norad) and Royal Dutch Shell. The article draws on experiences with the E4D/SOGA Programme, implemented by GIZ (Gesellschaft für Internationale Zusammenarbeit) in Eastern African since 2015. Many thanks to Svenja Brachmann, Olle Östensson, Sven Renner, Iris Rotzoll and two anonymous peer reviewers for their helpful comments on earlier drafts.

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  1. Non-resident Research Associate, United Nations University World Institute for Development Economics Research, Helsinki, Finland

    Evelyn Dietsche

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Dietsche, E. Jobs, skills and the extractive industries: a review and situation analysis. Miner Econ 33, 359–373 (2020). https://doi.org/10.1007/s13563-020-00219-2

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