Background
Leaving no one behind (LNOB) is the central, transformative promise of the 2030 Agenda for Sustainable Development and its Sustainable Development Goals (SDGs). LNOB means moving beyond assessing average and aggregate progress, towards identifying progress for different population groups, including with intersecting vulnerabilities, to ultimately ensure all human beings can fulfil their potential in dignity and equality.
To support governments and the United Nations system in the Asia-Pacific region, the United Nations Economic and Social Commission for Asia and the Pacific (ESCAP) has developed a user-friendly diagnostic tool called Leave No One Behind (LNOB) platform. The tool supports understanding of how various circumstances intersect and create inequalities in access to basic opportunities covered by the Sustainable Development Goals. Building on empirical methodologies such as Classification and Regress Trees (CART) and the Dissimilarity index (D-index), it uses data and statistics at national and sub-national levels to identify groups left furthest behind and the circumstances they share.
In this technical R training, ESCAP took participants through the inner workings of its LNOB platform, using the statistical R code that prepares, analyzes and produces evidence on SDG indicators. In addition, participants had hands-on experience to run the LNOB code on selected SDG or national indicators based on Kyrgyzstan’s latest Multiple Indicator Cluster Survey. Equipped with this knowledge, participants could then analyze inequality based on any other nationally representative household survey.
Training Objectives
The primary objective of this statistical training was to strengthen national capacities in building the evidence base in support of policies that reduce inequality and accelerate the implementation of the SDGs, by making sure that policies and programmes are inclusive and reach the furthest behind and support equal opportunity permitting the full realization of human potential and contributing to shared prosperity.
At the end of this training, technical officials and specialists were able to map out inequalities in access to opportunities and prevalence of barriers for which they have data and identify furthest behind and furthest ahead and quantify the level of inequality at national and sub-national levels through the D-Index. The training also aimed to raise awareness about the important role that NSO plays in enhancing the use of SDG indicators for decision making.
Target Audience
The statistical training drew participation from statisticians and technical specialists at the National Statistical Committee of the Kyrgyz Republic. Technical specialists from other ministries, departments and agencies, academia, think-thanks, research institutions and the United Nations system entities were invited to participate in coordination with the National Statistical Committee of the Kyrgyz Republic. Given the complexity of the code and the short duration of the training, a basic level of understanding of and experience with statistical software programmes such as R, SPSS or Stata were helpful to follow the instructions. Participants were recommended to follow ESCAP guidelines for installing and preparing the R Studio environment before the training begins. It might be beneficial, but is not required, for participants to review basic R skills which can be found by a simple search on the internet.
Organization and Participation