1. Background

Leaving no one behind (LNOB) was the central, transformative promise of the 2030 Agenda for Sustainable Development and its Sustainable Development Goals. LNOB meant 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) had developed a user-friendly diagnostic tool called Leave No One Behind (LNOB) platform. The tool was 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 used 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 took 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 Tonga Multiple Indicator Cluster Survey (MICS) from 2019. In addition to replicating the results hosted in LNOB platform, participants would 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 Survey upon availability.

2. 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 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.

3. Target Audience

The statistical training drew participation from technical officials and specialists in ministries, departments and agencies, academia, think-thanks, research institution and the United Nations system entities. The Tonga Statistics Department along with the United Nations Resident Coordinator’s Office were key partners of ESCAP in organizing this training. 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 helpful to follow the instructions. Participants would need to follow pre-training guidelines for installing and preparing the R Studio environment and obtain relevant data. It might be beneficial, but is not required, for participants to review basic R skills available online through tutorials.

4. Organization and Participation

The statistical training was organized physically at the Tonga Statistics Department Conference Room, Nuku’alofa, Tonga, on 8-9 March 2023. The meeting was conducted in English. The tentative programme of the training is on the Event Programme tab.