2.5. Analytical frameworks for skills policy

2.5.Analytical frameworks for skills policy

Apart from industrial policy, reaction to the changing economic and technological environment also saw a more pronounced discussion as regards skills policies. Human capital and skills have for a long-time been recognised as an important prerequisite for economic growth, even if the some authors suggest that the role of different production factors might change when moving through different stages of economic development (Greiner, A., Semmler, W., & Gong, G., 2016). The current academic discussion on the role of skills and human capital in the global economy, while indicating the need for a new perspective, suggests that until now the existing approaches are either based on universalistic theories – i.e. human capital theory; skills bias theory or particularistic theories - notably the varieties of capitalism theory (Lauder, H., Brown, P. and Ashton, D., 2017).

However, link between skills and industrial policies is not straightforward. On the one hand, from earlier discussion it has been evident that skills-focused interventions are usually an integrated element, among many others, of industrial policies. On the other hand, the level of integration between broader skills policies pursued by countries and industrial policies is often weak if at all present. It could be argued, that in many cases sector-specific industrial policy interventions concern skills in a very narrow way – limited both in terms of volume (i.e. number of people to be trained) as well as content (types of skills pursued). On the other hand, for horizontal industrial policy, skills governance interventions might seem too generic, lacking tangible indications of being identified as a pressing bottleneck (such as trade barriers or unfavourable exchange rates) or a visible outcome, such as an attracted FDI, jobs and infrastructure.

Therefore, the approaches to govern as well as analyse skills systems across countries are often rather “soft”. Two primary examples are, firstly, pursuing statistical analysis to understand the way skills (or more broadly) – human capital markets function across countries and secondly, pursuing (qualitative) analysis of skills policies, adopted to influence skills markets and in most cases focusing on skills development - i.e. initial and continuing education and training. In the two sections below, a concise review will be provided of some of the existing work by the European Commission and the OECD in terms of monitoring skills systems and analysing skills policies. For further in-depth discussion on latest skills policy issue a good reference points is the evidence collected and reviewed within the latest annual Development in Americas (DIA) report (IAB, 2017).

2.5.1.Workforce skills (development) systems

Two frameworks, developed at the international level since 2010 can act as a useful guide in monitoring skills systems. The first one, developed between 2011 and 2013 by the OECD and World Bank in cooperation with ETF, ILO and UNESCO. It was developed following a call by leaders of G20 and implementing G20 multi-year action plan on Development, adopted in Seoul summit in November 2010. The second one was developed by the European Commission in 2016 during a review process of skills statistics in the EU.

The OECD-World Bank framework was developed with the aim to act as a guide supporting countries, particularly those at lowest level of development in selecting indicators to monitor and benchmark skills development policies. It is a based on a supply-demand framework and consisting of five main domains and proposing a list of internationally comparable indicators available for majority of countries globally. The five domains include: contextual factors that drive supply and demand for skills; skills acquisition covering investment, stock and distribution of skills; skills requirements covering the demand side; matching of supply and demand in terms of labour market relevance of

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skills; and finally outcomes of skills that reflect the impact on economic performance and employment and social outcomes.

Figure 6: Conceptual framework for indicators of skills (OECD/WB, 2013)

The second framework, focusing on the policy priorities and availability of skills-statistics in the European Union, was also based on a supply-demand framework, but giving more equal emphasis between “flow” and “stock” measures of skills and evaluating the quality and relevance of different statistical measures (European Commission, 2016d)

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Figure 7: Conceptual framework for skills related statistics (European Commission, 2016d)

http://ec.europa.eu/eurostat/web/skills/overview

Both of these frameworks and corresponding types of indicators can be used as an inspiration for and monitoring skills requirements to support the implementation of industrial policies. At the same time, as noted earlier, contemporary industrial policy often requires a deep level of disaggregation of indicators beyond the level of generic industry. This puts substantial burden on the existing statistical systems as regards their ability to generate data at the required level of disaggregation. This becomes even more difficult when data for comparison reasons is needed from different countries. Even more pronounced challenge is acquiring such data for relatively small countries and for relatively large companies, where sample sizes are often too small to be published in order not to disclose the identity of specific companies or individuals.

2.5.2.Workforce skills (development) policies

As regards skills policy interventions, some notable work on their classification has been carried out (but primarily focusing on continuing education and training) as part of the OECD INES network (Borkowsky, A., 2013) – see Figure 5 and the work of the European Commission on adult learning policy (European Commission, 2016a) – see Figure 6. The latter also included a literature review on the effectiveness of different policy interventions.

A major difference between these two frameworks is their practical applicability – the OECD framework has been called a “theoretical framework” due to absence of concrete indicators (data) to implement actual policy monitoring at the OECD level. Conversely, the analysis and monitoring framework developed by the European Union took into account the availability of data, which covers well a large part of the elements within the framework.

A further difference in the development of these frameworks has been the way to identify policy areas for monitoring. The framework developed by OECD was informed by policy experts – identifying policy priorities relevant in their countries, while the framework developed by the European Union was

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based on a broad literature review, with the goal to identify policy interventions that have been researched and their evaluations indicated a certain level of evidence on their effectiveness.

At the same time, limiting the analysis only on those policy interventions that have been proven to work would prohibit reflection and analysis of any innovative measures, that have not been implemented yet or that have been implemented very recently and therefore were still not evaluated.

As can be seen from the mapping of skills oriented policy outcomes, some of these link to the goals of industrial policy in general and such policy in Singapore in particular. Notably two areas – capacity to find (a better) job due to increased employability as well as productivity and innovation outcomes at company level are two important elements/goals target by industrial policy in Singapore. Evidently, skills related interventions could be able to support the achievement of those targets.

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Figure 8: The framework for monitoring adult learning systems (Borkowsky, A., 2013)

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Figure 9: Conceptual framework for the assessment of adult learning policies (European Commission, 2015)

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