Achieving the Sustainable Development Goals: Where The IDM Fits

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In September 2015, 193 member states of the United Nations agreed an ambitious, holistic roadmap to achieve a sustainable and prosperous future for people and planet, the 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDGs). Leaders also committed to leave no one behind in achieving the Goals by 2030.

The 17 Global Goals for Sustainable Development include 169 targets, and 230 indicators to measure progress.  Gender equality is well integrated in the SDG indicator framework, with 53 gender-related indicators, plus an overarching call to disaggregate data wherever possible. However, currently, 71.7% of these gender-related indicators lack either adequate data or accepted international standards for measurement.  This is a concern as these gaps may lead to indicators being dropped from the SDG indicator framework when this is reviewed in 2020.

The 2030 Agenda cannot be achieved without good data about the nature and scale of issues affecting individuals in their diversity, and the effectiveness of our actions to address them. This includes capturing the multiple and intersecting ways in which disability, age, gender, rural/urban location and more overlap to deepen inequality and marginalisation. When data is blind to the impact of gender on individuals’ lives, we can inadvertently reinforce barriers to gender equality. It is also much more difficult to develop well-targeted policies and programs to address the barriers individuals face.

The IDM provides a relevant complementary tool to help reveal who is poor, in what ways and to what extent, and provide basic data on 15 key dimensions of economic and social life to support better targeting of policies and programs. The IDM presently aligns with some 25% of the 53 gender-related indicators, so data collected by the IDM can also contribute data relevant to monitor the SDGs.  The IDM provides disaggregated data for some at risk gender-related indicators. It can also provide disaggregated data for indicators that do not currently specifically require this, consistent with the overall call for disaggregated data wherever possible.

The wording of Goal 1 – ‘To end poverty in all its forms everywhere’ – anticipates a move beyond income-based, household-level measurement of poverty. However, when the initial SDG indicators were agreed, there was not a globally agreed methodology for individual-level, multidimensional poverty measurement. The IDM offers one approach to strengthening global poverty data collection and capturing information at an individual level, which is critical to measuring progress towards the SDGs.

Closing the gender data gap by investing in more and better gender statistics and promoting greater use of available gender data is essential to realising the transformative potential of the SDGs. Individual, intersectional and intrahousehold measurement will improve the accuracy of global data on inequality and poverty, and provide evidence for more effective action towards transformative change.