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Guest Blog: Beyond SDG indicators: Exploring the role of IA in implementing the sustainable development goals

'Guest blog by Laszlo Pinter reproduced with permission of The Integrated Assessment Society'
Laszlo Pinter, Professor, Central European University, Hungary, and Senior Fellow, International Institute for Sustainable Development, Canada Integrated assessment has been conceived as a field specialized in tackling real world science-policy problems that are technically and politically complex and carry significant risk and uncertainty. Already used in challenging global policy processes covering, for example, biodiversity and climate change, IA is seen as well-positioned to support the implementation of sustainable development goals (SDGs).

In order to explore this proposition, TIAS held two webinars in early 2016. The first event on February 2 covered the IA /SDG interface from the conceptual and strategic point of view through talks by Mark Levy, Deputy Director of the Center for International Earth Science Information Network  (CIESIN) at Columbia University; David O’Connor, former Chief of the Policy Analysis and Networks Branch at UN DESA during the SDG negotiations and currently with World Resource Institute’s SDG Delivery Team; and Enrico Giovannini, former OECD Chief Statistician and Minister of Labour in Italy and presently professor at the  University of Rome ‘Tor Vergata’.

The second webinar on April 12 looked at IA tools that could support SDG implementation and transition planning with Paul Lucas, Researcher from the Sustainable Development and International Climate Policy unit at the Netherlands Environmental Assessment Agency; Marco Sanchez-Cantillo, Senior Economics Officer at the Development Policy and Analysis Division of UN-D ESA and Matteo Pedericini, Director of Planning at the Millennium Institute.

Overall rationale for linking SDGs and IA

The rationale for organizing the two events was the fact that the SDG agenda gave rise to a revived interest in measurement and indicators as instruments for tracking progress (United Nations Economic and Social Council 2015).

While the interest is not new, the political momentum behind the goals created a context within which indicators play an important role, in contrast with cases when sustainability-related indicator systems are developed based on priori assumptions about their use without formal expectations of a policy process. According to current thinking, indicators will play key roles in the governance of global goals from diagnosing baselines to specifying targets and tracking progress. They are seen as essential for turning broad, often qualitatively expressed SDGs into tangible targets that can be monitored, quantified and reported on, not unlike those used in the measurement, reporting, and verification (MRV) mechanisms of other widely accepted international regimes such as the UN Framework Convention on Climate Change (UNFCCC) (United Nations Climate Change Secretariat 2014).

However, while indicators answer some important questions about status and performance, SDG implementation will require more than that: it will need the grounding of target setting, strategy development, program planning and delivery in evidence projected into the future. For that indicators are a must, although not only as discrete metrics but as elements of analytic frameworks and integrated assessment models (IAMs) suitable for studying SDG implementation options in real-world settings.

Going beyond business as usual in measurement

As pointed out by Marc Levy, a fundamental difference between the earlier Millennium Development Goals (MDGs) and SDGs is the latter’s full coverage of human aspirations. With this radically wider scope comes not simply a larger set of issues, but a different mode of operation where data is not simply a technical detail in progress reporting but is used for navigating a complex, interconnected issue landscape across different disciplines, time horizons, scales and interests. The SDGs call for a new mode of analytics where data and analysis are as intertwined as the issues themselves and span the entire policy cycle from visioning to implementation, performance reporting, and adaptive learning.

Enrico Giovannini reminded the audience that new uses of data are intrinsically linked with a transformation of what data is collected, and how it is collected, accessed and presented.
By the time of the approval of the SDGs in September 2015, a data revolution was well under way, manifested through countless grassroots indicator initiatives, legitimized by highlevel political events such as the OECD’s World Fora series on Measuring the Progress of Societies, and backed up by a UN Statistical Commission-led effort on SDG indicators.

As a key element of the data revolution, technical advances in measuring the elements and determinants of well-being are in sync with the broader ambitions of the SDGs. Giovannini
challenged the audience to imagine a Republic of Well-being as a fictitious country, fully dedicated to pursuing the SDGs, and laying out a roadmap that could lead to its realization.

Besides making sure its national accounts cover wealth in a comprehensive sense (not only economic but also social and natural capital), the Republic of Well-being would also have a
governance system that operates without structural siloes, making use of cross-sector strategies and integrated policy assessments.

What do the SDGs mean for IA

The interest in the SDGs – and indeed sustainable development in earlier days - grew out of a political recognition that poverty eradication and economic development cannot be sustained without seriously and systematically addressing their social and environmental conditions. Even though they were not developed with an explicit conceptual framework in mind, the SDGs are tightly interlinked. David O’Connor pointed to the need for viewing the SDGs as an interconnected network of targets and to consider the implications for policy making and analysis. The challenge for policy making is that goals and targets alone don’t tell us what type and what level of effort is required to achieve them, and how much progress in one important target (e.g., on water) is sufficient to achieve another (e.g., on health).  policymakers need to find the SDG(s) directly relevant for their portfolio, and placing it in the center, analyze their interlinkages – dependencies or reinforcements - with other goals and targets, defining a manageable subsystem of goals and targets in the overall SDG framework (Weiss et al. 2014).

According to O’Connor the implications for strategic planning and policy implementation includes starting with a big-picture perspective of interrelationships, examining goals from multiple perspectives and building broad ownership through joint planning and coordination. Integrated assessment models and scenarios can be used to map interdependencies between the goals, point to possible synergies and tradeoffs and help ensure progress is coherent.

IA tools for SDG support

In order to realize the potential contribution of IA to SDG delivery, there is a need for turning the potential into tools, practice and results. Given the wide range of thematic and policy contexts and evolving decision-maker needs on the one hand and the diversity of IA tools and approaches on the other, an exploration of options has started. The three approaches and set of tools showcased in the webinar underscore the earlier point that the investments made in the IA community over the last years in preparing contributions, e.g., for thematic global assessments, represent a solid starting point for supporting SDG implementation from global to national and lower regional and local levels.
Advanced exploratory work is happening in terms of modelling tools, application of model results to analyze implementation scenarios, and modes of interaction with social actors. The tools discussed by the three presenters represented three different approaches: first, expanding mainstream economic models (CGE) to ‘external’ environmental and social issues that are beyond the coverage of standard macroeconomic models (Marco SanchezCantillo); second, using a suite of linked integrated models (IMAGE, GLOBIO etc.) organized around a coherent conceptual framework with drivers, impacts and responses (Paul Lucas); and third, working with self-contained integrated models (iSDG), built on the platform of an earlier already established core (Threshold 21) (Matteo Pedericini).

IA models can help formalize the interlinkages between the SDGs as a network of targets and explore relationships between alternative policy pathways and their impacts on SDG indicators and targets as they unfold over time. This can involve using macroeconomic and complementary noneconomic model results to identify effective national development strategies that take a wider range of SDGs into account. It can also involve testing the performance and impact of a suite of policy or behavioural options on a wider range of interrelated SDG areas. This can not only help assess distance to target at the end of the implementation period, but also point out synergies and tradeoffs. Alternatively, backcasting can be used to construct alternative implementation pathways to a common desirable target but involving different suites of strategies, tradeoffs and synergies.

Overall, at this stage of IA modelling the emphasis is on interaction with policymakers to make sure IA and modelling responds to specific needs and builds capacity in countries to use models and model results. IAMS can help make goals, targets and indicators transparent, as well as identify tradeoffs and synergies, cross-scale and cross-sectoral connections, inertia, and the level of effort required to achieve targets and uncertainties. As Lucas pointed out, IA modelling results to date seem to point to the importance of understanding how far piecemeal measures can go, and where the need for transformation is.

The two webinars underscored the need for indicators in SDG implementation but then going beyond this with the use of analytics that IA can provide. Initiatives such as ‘The
World in 2050’and the growing number of national SDG implementation programs indicate increasing interest in the potential of SDGs.

References
United Nations Climate Change Secretariat. (2014) Handbook on Measurement, Reporting and Verification for Developing Country Partners. Bonn: United Nations Climate Change Secretariat. Available at: https://unfccc.int/files/national_reports/annex_i_natcom_/application/pdf/non-annex_i_mrv_handbook.pdf
United Nations Economic and Social Council. (2015) Report of the Inter-Agency and Expert Group on Sustainable Development Goal Indicators. E/CN.3/2016/2. Available at: http://unstats.un.org/unsd/statcom/47th-session/documents/2016-2-IAEG-SDGs-E.pdf

Weiss, N. et al. (2014), Cross-sectoral integration in the Sustainable Development Goals: a nexus approach, SEI Discussion Brief.For more details on and recordings of the two SDG webinars are available at: www.tiasweb.info/webinars/

Comments

  1. Very rich insights. Developing the concept of interlinkages and the beneficial impact of progress in one field, contributing to another, is a key insight I derive from this discussion, giving a new meaning to the benefit of measurement. Thanks Lazlo and Felix. Keep me in the loop for future webinars, as this has practical implications for the linkages from global to local with regional and national levels in between. Loy MARS Practitioners Network, Myanmar and India

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