Tag Archives: monitoring and accountability

Measuring the SDGs Progress with Data Envelope Analysis

How do you gauge the accomplishments of policy and its failures? While a number of nations are successful in maximizing a socioeconomic welfare function, others are woefully falling short of the optimal frontier. Considering the large number of SDGs and development targets, the accomplishments and failures of nations and their policy performance will always be multidimensional. Once we have agreed on a single measure of such progress, it becomes possible to document numerically how policymakers succeed (or fail) in achieving their goals and communicate them politically.

Data envelopment analysis (DEA), codeveloped by Abraham Charnes and William Cooper in 1978, is ideally suited for the purpose, delivering a metric that evaluates the performance of Decision Making Units DMUs(nations, regions, cities, enterprises, banks, schools, etc.) according to their ability to use inputs, and marshal economic and social policy to attain a spectrum of desired goals. We propose a DEA framework to assess an empirical production function and to serve as an interactive-iterative policy evaluation system for monitoring the multi-dimensional progress various nations make towards
achievement of the SDGs.

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Loss Data Underpinning Disaster Risk Reduction

At present, our understanding of appropriate long-term disaster risk management is limited by the lack of in-depth knowledge on the impacts of disasters. In this regard, recording disaster impacts at detailed level is crucial for informed decision making, using methodologies that allow aggregation over space and in time. Scientific approaches for record disaster losses consistently and accurately are essential to move from undependable evidence driven mainly by media coverage to more systematic and proven datasets on disaster impacts. New partnerships between science and DRR actors are enabling just this.

Disaster loss data recording is the mechanism that links the science of risk assessment to the policy making for reducing disaster risks. Loss data collections are useful, for identifying trends and patterns in the data over time sand for tracking relationships between development and disaster risk (IFRC, 2005). As evidenced in the Global Assessment Report (GAR), loss data, recorded in national and global disaster databases are increasingly being used within risk modelling platforms to guide the decision-making processes of DRR (ISDR, 2013). When combined with ancillary data such as disaster risk
management expenditures or demographic information (Gall et al., 2015), disaster loss data are essential indicators on the relevance of DRR policies in a broader context of development and climate change.

This note discusses the relevance of disaster loss data for evidence based policy in DRR and the main application domains of loss data within the European Union (EU) Member States.

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Monitoring disaster risk reduction targets: the example of INFORM

Disaster risk consists of three elements: hazard, exposure and vulnerability. Risk can be reduced by controlling the frequency and intensity of hazards (e.g. flood protection, slope stabilization), reducing or limiting exposure (e.g. urban planning, urbanization policy, room for rivers to flood in unexposed areas) and reducing vulnerability (e.g. early warning, seismic building codes, contingency and response plans, evacuation). Further, to avoid disasters, society must build resilience to recover quickly after a hazard, mainly through effective response, reduced poverty, risk financing (public or private) and other coping mechanisms.

Accurate measurement of a complex phenomenon as risk is a non-trivial task. Because of its many dimensions, different stakeholders can perceive risk differently. One person’s loss can be another ones gain. Some communities express risk in terms of loss of life and others in financial numbers. Besides this conceptual uncertainty, the various components are not easy to quantify and involve scientific disciplines ranging from natural sciences to social sciences. Due to their nature, some risks can’t be compared on the same scale (e.g. earthquake risk versus droughts).

Nevertheless, there is a need to create multi-hazard risk metrics based on scientific evidence to inform disaster risk reduction policy. One tool that has been used to integrate information from different disciplines and communities is a composite indicator.

This note discusses the opportunities, challenges and strengths of composite indicators to measure progress in disaster risk reduction, and in particular the experience of a recently developed Index for Risk Management – INFORM.

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The UNU-FLORES Nexus Observatory and the Post- 2015 Monitoring Agenda

Recent debates within the UN system, which are also reflected in the Prototype Sustainable Development Report, have called for policy-making that is supported by a strong evidence-base. Making research relevant, timely, accessible and instructive, thus, strengthening science-policy interfaces is one of the key challenges of the 21st century. As much as humans must adapt to a changing world and build resilience (in economic, political, social and environmental terms), transformation and innovation of methods and approaches that are suited to address current and future challenges need to form an integral part if sustainable outcomes are to be achieved. Scientists who have made important contributions towards articulating an analytical framework for sustainable management of environmental resources
have emphasized the role of property rights for resources, such as forests, rivers and livestock pasture (Ostrom, 1990). The literature on institutions has highlighted the challenge of fragmented decisionmaking processes and structures that lead to the creation of silos across disciplines, regions, government departments and ministries. This in turn hinders inclusive and comprehensive approaches
founded on improved understanding of trade-offs and synergies that is necessary for integrated management of environmental resources to occur.

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Measuring Progress on the SDGs: Multi-level Reporting

In September 2015, heads of state will adopt Sustainable Development Goals (SDGs). The goals will chart out a universal holistic framework to help set the world on a path towards sustainable development, by addressing economic development, social inclusion, environmental sustainability, and good governance.

The agenda laid out by the Open Working Group on the SDGs (OWG) in July 2014 is the main basis for the Post-2015 intergovernmental process, which began on 19 January 2015. From now until the September summit, Member States will further review the goals and targets. They will also consider the means of implementation, the nature of a new Global Partnership, and a framework for monitoring and review of implementation.

As underscored by the OWG, the focus of reporting on the SDGs must be at the national level. Each country will choose the indicators that are best suited to track its own progress towards sustainable development. Yet, the Goals also describe a global agenda, including some global public goods that cannot be implemented by any country on its own. Success will require international coordination and collaboration, which in turn requires accountability and monitoring at global level. In addition, regional monitoring and accountability will play a critical role in fostering regional collaboration and coherence in strategies to pursue the SDGs. A fourth and critical level of monitoring occurs in each thematic or epistemic community.

The four levels of monitoring – national, regional, global, and thematic – are laid out in the Secretary-General’s synthesis report. The report calls for “a culture of shared responsibility, one based on agreed universal norms, global commitments, shared rules and evidence, collective action and benchmarking for progress.” This culture of accountability must be particularly strong at the national level, “building on existing national and local mechanisms and processes, with broad, multi-stakeholder participation.”

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Monitoring the Performance of Agriculture and Food Systems

The Sustainable Development Goals (SDGs), targets,and indicators will define global, national, and local aspirations for improving human well-being. Without clear metrics to measure progress and accurate, consistent, and continuous data collection across both time and space, sustainable development will remain an amorphous goal. Metrics are needed to set baselines against which to measure progress; track and predict socioeconomic, nutritional, and ecological change; understand constraints to sustainable development; work successfully with public, private, and NGO partners; and identify appropriate policy measures.

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Reducing child poverty: the importance of measurement for getting it right

It is widely recognised that the reduction of child poverty is crucial for sustainable economic and social development (UNICEF 2014), and the Open Working Group (OWG) on Sustainable Development Goals (SDGs) recognises that growth and development should particularly benefit children (§4). Child-specific
measurement is imperative for addressing poverty and reducing vulnerability (Ben-Arieh 2000) and for the first time newly proposed global goals for poverty reduction make specific reference to children.

Sustainable Development Goal (SDG) 1, Target 2 reads: “By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions” (OWG 2014; 7). This explicit mention of children constitutes an important step forward but also gives rise to questions about the use of indicators and measurement of child poverty. This science digest provides an overview of the academic debate
regarding the complexity of child poverty and the importance of comprehensive child-focused poverty measurement in supporting adequate and effective poverty reduction policies.

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