Leveraging global value chains in support of the Sustainable Development Goals?

22 November 2016

What are the key knowledge gaps which need to be filled if developing economies are to successfully leverage global value chains (GVCs) to meet the Sustainable Development Goals (SDGs)?


An increasing number of people in an increasing number of economies are producing for global export markets. But the growth of exports in itself may not deliver widespread development and assist in the attainment of the Sustainable Development Goals (SDGs). The issue is thus not whether to participate in global markets but how to do so in ways which foster development.

More than two-thirds of global trade now occurs within global value chains (GVCs), that is, producing, importing, and exporting intermediate (semi-finished products) which are then incorporated into final products. Much of this GVC trade occurs within what are termed “governed GVCs,” that is GVCs where key lead firms and other actors (such as civil society organisations) determine who does what in the chain.

The structure and functioning of these chains affects who gains and who loses in these global production systems. So, the key policy challenge is to ensure that the nature of these chains is such that they assist in meeting the SDGs. Whilst some positive development spillovers from GVC expansion flow naturally out of the operations of markets, there is abundant evidence that without complimentary policies, these positive outcomes will be restricted.

Filling knowledge gaps are a lever for continuous improvement

The ambitious nature of the SDGs makes new demands on policy, providing new opportunities to widen and deepen the potentially positive role which GVCs may play in fostering broad-based global development. But without an adequate knowledge base, policy will be ill-informed, and, hence, suboptimal. The pervasiveness of these knowledge gaps is unsurprising, given that the SDGs have only just been agreed. Filling these knowledge gaps effectively will of course be contextual – their nature, and the degree of detail required will naturally vary with circumstances, sector, and over time.

Successful business strategies in the corporate world have shown how identifying knowledge gaps, collecting data, and then using these data to benchmark performance over time, sector, and space can be used to “stretch” performance to achieve targeted objectives. A particularly important part of this experience is that well-designed data-capturing activities play an important role in involving stakeholders in processes which lead to the effective implementation of policy.

But, crucially, with filling key data gaps comes the realisation that in varying degree, all indicators are imperfect. Moreover, many are often difficult to capture because of their proprietary nature, but also because many activities in the informal sector are unrecorded. Hence there is no perfect data template. So it is not just that the nature of data capture is necessarily contextual, but also that it requires careful interpretation before policy lock-in and policy implementation.

Filling knowledge gaps for the SDGs: Some examples

Each of the 17 SDGs is replete with knowledge gaps; each of the SDGs, to varying degrees, are affected by the structure of GVCs. Hence the focused task is to identify those policy-relevant knowledge gaps which are central to GVCs and SDGs and which can feasibly be filled. Below are two examples of how the knowledge gaps in the attainment of individual SDGs can be filled, identifying the key stakeholders involved, the types of data required, and the strengths and weaknesses of specific sets of data.

Reduce inequality within and among countries (SDG 10)

Three primary measures of equality are affected by the structure of GVCs. The first is the distribution of incomes within the GVC itself; for example, between workers, owners, and managers. The second is a comparison between those employed within the GVCs, and those operating outside GVCs, and the third is between workers, owners, and managers employed in the GVCs, but involved in different economies. These various distributional issues, the key knowledge gaps, and the strengths and weaknesses of different data are illustrated in Table 1.

Table 1: Levels of equality (SDG 10)

Reliable, sustainable and modern energy (SDG 7); Resilient infrastructure (SDG 9); Sustainable consumption and production (SDG 12); Climate Change (SDG 13)

Energy is essential to life. At the most basic level, it provides the calories to fuel existence (SDG 1). But energy also provides the scope for raising productivity (SDG 12), enhancing infrastructure (SDG 9), and meeting the challenges of climate change (SDG 13).

GVCs are frequently very intensive in their utilisation of energy, and often in unrecognised ways. For example, the gains from improving energy efficiency in cassava- and maize-processing are dwarfed by energy loss in chain logistics such as the transport of raw materials, intermediate inputs, and final products. Similarly, the energy footprint in chains which are global in nature – shipping intermediates and final products within and across countries – can often be very substantial. A further issue in the energy footprint of GVCs arises in their role of misrepresenting the “decoupling” of production from energy use. Many Northern economies have experienced energy decoupling in that the energy-GDP ratio has fallen. However, what has often in fact happened is that the energy (and water and pollution) components of their value chains have been shifted through the medium of GVCs to other economies, predominantly in the South.

These and similar differing elements can be measured with varying levels of accuracy in GVCs (Table 2). The energy intensity of production can be measured within production processes in individual links in the chain. Less easily, attempts can be made to measure the energy intensity of the whole chain, including logistics and international transport. Equally challenging to measure is the extent to which the energy-GDP ratio in a given economy is disguised through the outsourcing of energy-intensive processes to other economies. A further category of sustainable energy concerns lies in access to energy. Grid-based systems are often inaccessible in regions outside major cities, and this is one advantage of renewable energy sources. On the other hand, renewable energy sources may be intermittent and may disfavour those without access to grid-based infrastructure.

Table 2: Reliable, sustainable, modern energy (SDG 7); Resilient infrastructure (SDG 9); Sustainable consumption and production (SDG 12); Climate Change (SDG 13); Oceans and marine (SDG 14); Forestry and biodiversity (SDG 15)

Turning data into action

Policy which is not evidenced-based can be counterproductive, with severe unwanted (and unexpected) outcomes. On the other hand, data in itself does not change the world, although the process of data collection can mobilise awareness and action. The challenge is to embed the filling of knowledge gaps into a process of policy formation and implementation which contributes to the attainment of the SDGs.

This necessarily involves engaging with the primary actors who have the power to determine the structure of production, distribution, and innovation. In the context of GVCs, seven sets of actors play key roles.

  • International agencies (such as the WTO) and international agreements (such as the North American Free Trade Agreement) play important roles in determining market access. These trade regimes affect the structure of GVCs across sectors, space, and time and have important distributional outcomes. Each of these organisations need to be aware of how their actions affect the manner in which GVCs contribute to the SDGs.
  • Nation states, both in exporting and importing countries, set the parameters of production and market access. How do their actions affect the extent to which different SDGs are met and who gains and loses from participation in GVCs?
  • Lead firms play a critical role – perhaps the most important role – in determining the manner in which GVCs reinforce or undermine the attainment of the SDGs. Many of these lead firms express a willingness to support SDGs, but are largely ignorant of the impact of their operations on SDG outcomes.
  • Supplier and user firms in GVCs play similar, but subsidiary roles in the attainment of SDGs, and many of the larger supplier and user firms play a “lead firm role” with regard to their own value chains. Here, too, knowledge gaps are widespread.
  • Workers, sometimes operating as individuals but particularly when working collectively, can play an important role in holding their owners and managers to account in actions which affect the attainment of SDGs. The effective collection of micro-data in firms and farms which is necessary to support competitiveness in global markets can often act as a form of awareness raising and mobilisation amongst these workers. But in other cases, workers need positive support in their attempts to understand the nature and determinants of the distributional outcomes in GVCs.
  • Civil society organisations play key roles in the structuring of GVCs. In many sectors, particularly those selling into final markets, and especially into higher-income final markets, their concerns with fair trade, workers’ rights, and the environment meet the needs of many of the SDGs. However, often their efforts are under-informed or misinformed, driven as much by prejudice and hearsay as a detailed understanding of what is happening on the ground in GVC.
  • In some sectors, public-private partnerships are the predominant actors in addressing the SDGs, particularly in the provision of global public goods such as in the treatment of neglected tropical diseases. Often these are large-scale top-down initiatives which fail to adequately recognise what is happening in the nether regions of their value chains. Here, too, knowledge gaps can be widely observed.

The SDGs, GVCs, knowledge gaps, and stakeholder alignment

Putting the puzzle together requires a number of different pieces of the jigsaw to be assembled. First, policy at all levels must be evidence-based if it is to be effective. Second, an adequate policy response requires the recognition that that many of the SDGs make demands for new information, for which existing knowledge capturing systems are not appropriately focused. Third, knowledge comes in various forms and in varying degrees of detail. Context in knowledge generation is critical. Fourth, GVCs play a dominating role in global trade. Because they cut across sectors and countries, and because they involve a range of stakeholders, they require varied datasets which span systems rather than data about discrete links within production systems. Fifth, a range of stakeholders are involved – in the collection of data, in the analysis of this data and, most importantly, in the actions which are required to deliver the SDGs.

In some cases, there are win-win gains across GVCs which will drive the generation of appropriate knowledge, the analysis of knowledge, the generation of policies, and the implementation of defined actions. In these cases, the key parties in the chain have common interests and can readily work together. This can be described as a process of “stakeholder alignment.” But in other cases, stakeholders have conflicting interests and access to knowledge of specific sorts is the basis for the differential power in GVCs. The challenge of leveraging GVCs in the attainment of the SDGs in these cases will not be simple. But as in the case of “stakeholder-aligned GVCs,” access to knowledge will be a core element in the struggle to make progress on the SDGs.

This piece is based on an issue paper entitled “Inclusive and Sustainable Growth: The SDG Value Chains Nexus” published by ICTSD, which discusses SDG- and GVC-relevant knowledge gaps in greater detail.

Author: Raphael Kaplinsky, Honorary Professorial Fellow, Science Policy Research Unit, University of Sussex.

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