- Background
Leaving no one behind (LNOB) is the central, transformative promise of the 2030 Agenda for Sustainable Development and its Sustainable Development Goals. LNOB means moving beyond assessing average and aggregate progress, towards ensuring progress for all population groups at a disaggregated level.
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 is used to improve the 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 subnational levels to identify groups left furthest behind and the circumstances they share.
In this technical R training, ESCAP will take participants through the inner workings of its LNOB platform, using the statistical R code that prepares, analyzes and produces evidence on 16 SDG indicators based on the Multiple Indicator Cluster Survey (MICS) from selected Pacific Islands including Kiribati, Fiji, Tuvalu and Tonga. In addition to replicating the results hosted on the LNOB platform, participants will also learn how to operationalize the LNOB methodology on indicators other than those currently available on the platform and to carry out LNOB analysis, using other nationally representative surveys such as Household Income Expenditure Surveys of Marshall Islands or Federated States of Micronesia and Labor Force Survey of Cook Islands, upon availability.
- Training Objectives
The primary objective of this statistical training was to strengthen national capacities in building the evidence base to developing policies that reduce inequality of opportunity and accelerate the implementation of the Sustainable Development Goals, by making sure that those left behind are also included.
At the end of the training, technical officials and specialists were able to map out inequalities in access to opportunities and prevalence of barriers and identify circumstances shared by those being left furthest behind and quantify the level of inequality of opportunity at national and sub-national levels through the D-Index.
- Target Audience
The statistical training drew participation from technical officials and specialists from the Pacific Community (SPC) as well as NSOs from Fiji, Kiribati, Papua New Guinea, Samoa, Tuvalu and Tonga. The target audience was expected to reach maximum 25 trainees. 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 and Stata would be needed to follow the instructions. We recommended that participants follow our guidelines for installing and preparing the R Studio environment prior to the training. It might be beneficial, but was not required, for participants to review basic R skills which could be found by a simple search on the internet.
- Organization and Participation