Adopted by the world leaders at the United Nations Sustainable Development Summit in September 2015, the 17 Sustainable Development Goals (SDGs) came into force on 1 January 2016,embarking on a new journey over the next fifteen years to the common future we want.

While the SDGs are broadly framed as 17 separate elements, Goals inherently interlink with one another making up an indivisible framework to deliver holistic sustainability from a systemic perspective. On the one hand, achieving one Goal or Target may contribute to achieving other Goals or Targets. For example, enhanced food security (Goal 2), full and productive employment and decent work (Goal 8) and reduction of inequality (Goal 10) will reinforce poverty eradication (Goal 1). On the other hand, the pursuit of one goal may conflict with the achievement of another. For example, an increase in agricultural production to help end hunger (Goal 2) can result in an increase in water use for irrigation which may compete with the water demand for achieving universal access to drinking water (Goal 6).

Goals and their associated Targets form a complicated network of interlinkages. Understanding the interlinkages among the Goals and between the Targets can help identify potential synergies and trade-offs. Removing the trade-offs and maximising the synergies are the key element of SDG integration and policy coherence.

SDG integration has already been well-recognised and its implementation requires a major shift from the conventional siloed approach to a systems approach. This is where the challenge lies, for there is neither sufficient knowledge on how the SDGs should or could be integrated, nor any practical tool that can help explore the inherent interlinkages among the Goals and Targets. Some experts and institutions have initiated analysing SDG integration, but huge gaps still remain, particularly in terms of comprehensiveness (covering all the Goals), quantification of the SDG interlinkages and practical case studies at the national level.

To address the existing knowledge gaps, IGES developed a methodology to identify the causal relations between the Targets and quantify them for nine selected countries, namely Bangladesh, Cambodia, China, India, Indonesia, Japan, Republic of Korea, the Philippines and Viet Nam. To enable relevant stakeholders to explore the potential synergies and trade-offs between the Targets, IGES developed the SDG Interlinkages Analysis & Visualisation Tool, a web-based tool for free access through the internet.

Figure 1
Major outputs

Analytical framework for the analysis and visualisation of SDG interlinkages

Source: Zhou and Moinuddin (2017).

Interlinkages can refer to those between goals, between a Goal and relevant Targets, or between Targets, etc. In this project, we focus on the interlinkages between Targets. Interlinkages include direct link between two Targets and indirect link which connects two Targets via a third Target or more intermediate ones. Furthermore, interlinkages can be directional links indicating the causality of two Targets, or undirectional links. In this project, we study direct and causal/directional links between SDG Targets.

Identifying all possible interlinkages between 169 Targets is an extremely difficult task. In this project, the interlinkages between SDG Targets are identified based on the knowledge obtained from international consultation processes on SDG indicators, such as the Inter-Agency and Expert Group on SDG Indicators (IAEG-SDGs), and through literature review (Zhou and Moinuddin, 2017).

The identified interlinkages are further quantified to indicate how strong the links are and whether the targets are linked positively or negatively. Quantification is based on the correlation analysis of the indicator-level time series data. For indicators, the 232 official SDG indicators as adopted by the UN General Assembly in July 2017 was used. The following steps were followed to identify the indicators for corresponding targets:

  • Check the data availability of the 232 indicators from major data sources including UNSD SDG indicators database, the World Bank SDG database, other UN/World Bank databases and other sources;
  • Identification of the best representative indicator for each target;
  • Identified indicators are further screened based on the availability of the time series data.

Correlation analysis was conducted for the identified causal relations between Targets. The correlation coefficients, ranging from [-1, 1], indicate the linear relationship between relevant targets. Positive coefficients represent positive linear relation and negative ones represent negative linear relation. Coefficients with larger absolute value (e.g. 0.9) indicate stronger linear relationship between the targets and those with smaller absolute value (e.g. - 0.2) indicate weaker linear relationship

The development of the SDG indicators at both global and national levels, accumulation of the knowledge on the interlinkages of SDGs, and filling the gaps in trackable data are open-ended processes. With the progress made in these areas, the knowledge and results provided by this work can be upgraded.