Practical Guidebook on Data Disaggregation for the Sustainable Development Goals
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Practical Guidebook on Data Disaggregation for the Sustainable Development Goals - Asian Development Bank
PRACTICAL GUIDEBOOK ON DATA DISAGGREGATION FOR THE SUSTAINABLE DEVELOPMENT GOALS
MAY 2021
Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO)
© 2021 Asian Development Bank
6 ADB Avenue, Mandaluyong City, 1550 Metro Manila, Philippines
Tel +63 2 8632 4444; Fax +63 2 8636 2444
www.adb.org
Some rights reserved. Published in 2021.
ISBN 978-92-9262-774-4 (print); 978-92-9262-775-1 (electronic); 978-92-9262-776-8 (ebook)
Publication Stock No. TIM210117-2
DOI: http://dx.doi.org/10.22617/TIM210117-2
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CONTENTS
TABLES, FIGURES, AND BOXES
FOREWORD
To build a road map for people and the planet and to support sustainable social and economic progress worldwide, the 2030 Agenda for Sustainable Development was launched in 2015 as a universal call to action for ending poverty, protecting the planet, and ensuring that all people enjoy peace and prosperity. Through the Agenda’s principle of leaving no one behind
(LNOB), the member states of the United Nations have committed to eradicating poverty in all its forms, ending discrimination and exclusion, and reducing inequalities and vulnerabilities. Understanding which population groups are left behind and designing effective policies require that the Sustainable Development Goal (SDG) indicators be disaggregated by income class, gender, ethnicity, geographic location, disability status, migration status, and other relevant dimensions. However, disaggregation of the SDG indicators imposes significant data requirements and operational challenges for national statistical systems (NSSs).
In many countries, development data are compiled as national, subnational, or city averages, which paints what would seem to be a society-wide picture with respect to specific development targets. However, these aggregate data do not provide adequate information on which segments of a country’s population have made significant progress or have lagged in terms of development. From a policy perspective, the lack of disaggregated data is problematic because there are limited data to guide the design of intervention programs that are meant to appropriately target vulnerable segments of society. On the other hand, where disaggregated data are available, evidence suggests that the most vulnerable groups are likely to benefit less from the development process than the rest of the population, contributing to widening inequalities within countries. Worryingly, during periods of uncertainty such as the ongoing coronavirus disease (COVID-19) pandemic, sparse data suggest that the poor and other vulnerable groups also tend to be at greater risk of social and economic exclusion.
In 2017, the Asian Development Bank (ADB) designed the technical assistance project Data for Development to strengthen the capacity of national statistics offices (NSOs) in the Asia and Pacific region to meet the increasing data demands for SDG monitoring and effective policy making. One component of the project focuses on providing guidance on how NSSs can enhance the compilation of disaggregated data for development. As part of this initiative, statisticians from ADB’s Statistics and Data Innovation Unit within the Economic Research and Regional Cooperation Department worked with the Statistics Division of the United Nations Department of Economic and Social Affairs (UN DESA) and other development partners to draft this practical guidebook that can be used by staff of NSOs and other organizations that compile SDG indicators and other data for development. In particular, the guidebook provides tools to collect, compile, analyze, and disseminate disaggregated data. Also, it provides background materials regarding issues and experiences of countries regarding data