To support policy makers' efforts to understand the trade-offs among the 17 SDGs as they develop implementation plans, tools can support the assessment of interlinkages and the implications for policy choices.
Policy Priority Inference incorporates economic theory, behavioral economics, network science, and agent-based modeling.
The SDG Synergies tool involves a participatory, discussion-based scoring process to develop a cross-impact matrix of interactions among SDG targets.
SAVi uses system dynamics and project finance modelling to capture the full costs of environmental, social, economic and governance risks.
The SDGs provide a framework for addressing multiple priorities simultaneously. To support policy makers’ efforts to understand the trade-offs among the 17 Goals as they develop implementation plans, a number of organizations have developed tools for assessing synergies and the implications of each policy choice.
Through its Policy Priority Inference (PPI) project, the Alan Turing Institute, in collaboration with the UN Development Programme (UNDP), is bringing together ideas and methods from computational social sciences in order to help governments understand what policy areas they should prioritize as they design policies to implement the SDGs. The project, announced on 27 May 2020, will model the “socioeconomic mechanisms of the policy-making process through agent-computing simulation and complex networks.” UNDP reports that this tool incorporates a “mix of economic theory, behavioral economics, network science, and agent-based modeling.”
This tool can be used to:
- estimate the relative importance that governments assigned to specific policy issues during a specific time period;
- identify the policy priorities that governments need to set in order to achieve a specific development strategy;
- measure how resilient a development strategy will be to shocks or crises that require a government to reorganize its priorities; and
- review complementarities among policy priorities adopted by different regions at the sub-national level.
This budgeting tool can be used to answer questions related to how long it will take to reach the SDGs, how governments can reallocate their public expenditure to speed implementation, and which synergies among SDGs should be promoted. [Alan Turing Institute news release][Alan Turing Institute impact story]
The Stockholm Environment Institute’s (SEI) SDG Synergies tool involves a participatory, discussion-based scoring process to develop a cross-impact matrix of interactions between all the targets that have been included by policy makers. The process follows three stages: the overall parameters are set, including which targets will be considered and who will be involved; participants score the interactions among the targets; and a network analysis reviews the policy-relevant patterns in the interactions.
On 30 June 2020, SEI launched a website titled, ‘SDG Synergies,’ and will soon pair it with the full interactive tool for policy makers.
The International Institute for Sustainable Development (IISD) has announced that it will use its Sustainable Asset Valuation (SAVi) tool to run “What-If” simulations to demonstrate how this tool can help assess the societal outcomes of green stimulus packages and measures emerging in response to the COVID-19 pandemic. These simulations will be published on IISD’s ‘Sustainable Recovery 2020‘ website, which was launched in June 2020.
SAVi uses system dynamics and project finance modelling to capture the full costs of environmental, social, economic and governance risks. This tool also calculates the dollar value of externalities that result from infrastructure development.