ESCAP holds Technical R Training on LNOB analysis in the Philippines

 

On 13-14 December 2022, ESCAP conducted a two-day hybrid statistical training in the Philippines in collaboration with the Philippine Statistics Authority (PSA). The aim of the training was to build national capacity to strengthen the evidence base through “Leaving No One behind’ analysis on SDG indicators.

The training was attended by close to 40 people, among them statisticians and technical specialists representing PSA, the National Economic Development Authority (NEDA) and the Department of Science and Technology – Food and Nutrition Research Institute (DOST-FNRI).

On the first day, the training covered SDG 7 with a focus on access to clean and affordable energy. Trainees explored the inner workings of the statistical LNOB code that feeds cutting-edge results on inequality at national and sub-national levels to the ESCAP LNOB platform. In addition to reproducing results, trainees also had an opportunity to see how trees would change based on model parameters.

After mastering the statistical code, the trainees on the second day focused on two other indicators currently available on the ESCAP LNOB platform, including completion of secondary education (SDG 4.4) and prevalence of intimate partner violence against (SDG 5.2). To showcase the versatility of the code, ESCAP trainers took participants to alternative data sets and jointly produced novel results for malnutrition-related outcomes based on National Nutrition Survey 2015 and employment-related outcomes based on Labour Force Survey 2020.

At the end of the training, participants had obtained a strong new tool to help them design inclusive and effective policies that leave no one behind and evaluate progress over time.

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1. 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 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 Philippines Demographic and Health Survey (DHS) from 2017. In addition to replicating the results hosted in LNOB platform, participants learned how to operationalize the LNOB methodology on indicators other than those currently available on the platform and to carry out LNOB analysis, suing other nationally representative surveys such as National Nutrition Survey (2015) and Labor Force Survey (2020).

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 had data and identified 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. 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 were needed to follow the instructions. We recommended that participants follow our guidelines for installing and preparing the R Studio environment before the training begins. 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.

4. Organization and Participation

The statistical training was organized physically at the Novotel Manila Araneta City in Manila, on 13-14 December 2022. Local transportation for participants was covered by ESCAP. The meeting was conducted in English. The tentative programme of the training is available on the Programme tab.  

Manila, Philippines