The global downturn induced by the COVID-19 pandemic has slowed and even reversed progress towards the SDGs in many areas, with vulnerable and socially disadvantaged people particularly affected. Targeted policy measures to ensure that no one is left behind require accurate, timely and disaggregated data. Although the 2030 Agenda calls for a data-driven approach to sustainable development, many international organisations and countries recognise that persistent data gaps are a major hurdle, particularly when it comes to the most disadvantaged groups. The PARIS21 Statistical Capacity Monitor features around 100 indicators that can help countries and organisations to quickly and easily analyse their statistical capacity and effectively allocate funds where they are most needed.

aerial view of people walking along a pavement with long shadows

A lack of data is a particular risk to the most disadvantaged

It is no coincidence that the people who are most likely to be left behind are also those who feature less prominently in data and statistics. Some sources of data collection, for example household surveys, administrative data and civil registrations, may inadvertently miss out or underrepresent hard-to-reach populations such as rural households, people living in temporary or precarious conditions such as slums, or refugees. In addition, data may also not be disaggregated to the extent necessary to show gender, ethnicity or disability for example, preventing policy makers from effectively targeting these groups. Furthermore, over the last two years, the COVID-19 pandemic has impinged on national statistical offices’ data collection activities, making the task of accurately capturing the situations of diverse populations even harder. As the world emerges from over two years of pandemic, signs that the most vulnerable have been worst affected are everywhere:

  • Domestic and gender-based violence rose during lockdowns;1
  • the burden of unpaid work increased disproportionately for women, who were also more likely to lose their paid employment;2
  • 1.6 billion workers in the informal economy were badly affected by COVID lockdown measures;3
  • refugee populations and slum dwellers were at greater risk of contracting COVID and other diseases due to an inability to socially distance and limited access to healthcare;4
  • disabled people, who are more likely to work in informal sectors or unemployed, suffered from a lack of social protection as well as being more impacted by their support interventions or medical care being interrupted.5

Inequality and data gaps are a particular concern in Asia-Pacific

In UNESCAP’s most recent SDG progress report, Under-Secretary General Armida Salsiah Alisjahbana notes widening inequality and increasing numbers of vulnerable populations in the region such as women, rural households and poorer households. The report also highlights the link between data gaps and inequality, particularly with regards to SDG 2: Zero Hunger, as well as the fact that there is a pervasive lack of gender data for the region.6 Many countries in Asia-Pacific have enjoyed robust growth and economic development over the past few years, but there is growing recognition that more support should be given to disadvantaged groups in order for progress to be widespread.7

The Statistical Capacity Monitor can help countries to understand and address data gaps

Statistical capacity refers to a nation's ability to collect, analyse, and disseminate high-quality data about its population and economy. But for different countries and regions, improving their statistical capacity starts with understanding their own statistical systems and being able to diagnose as precisely as possible their particular challenges. The PARIS21 Statistical Capacity Monitor (SCM) was developed in 2019 and provides 97 indicators to assess the maturity and progress of national statistical systems using measurable indicators grouped along the statistics value chain: planning, production, dissemination, use, investment, and measuring cross-cutting areas such as co-ordination, innovation, and governance. Data for the indicators come from different sources, including collaborative work with partner institutions such as the World Bank, Open Data Watch, the IMF, and indicators are constructed with a variety of different techniques (self-reported surveys, manual collection or desk research, web-scraping and machine learning techniques). Some SCM indicators have been anchored to the monitoring framework conducted by UNESCAP over previous years. In the context of Asia-Pacific, for example, the use of the SCM can aid analysis of progress of the Asia-Pacific region over time and in comparison with other regions. The selection of certain indicators showcases the variety of methods and sources utilised in the SCM. Data on use, openness, coverage, dissemination and investment provide a snapshot of country and regional performance. Improving a country’s statistical capacity is far more than a bureaucratic exercise, it is central to being able to locate and tell stories about the lives of those who feature less prominently in data. PARIS21’s Statistical Capacity Monitor strives to meet the needs of international organisations and national governments in supporting the development of the statistical systems that are crucial in understanding progress towards the SDGs.



1. UN Women, The Shadow Pandemic: Violence against women during COVID-19

2. OECD (2021), Caregiving in Crisis: Inequality in paid and unpaid work during COVID-19,

3. UN (2021), The Sustainable Development Goals Report 2021,

4. UN (2021), The Sustainable Development Goals Report 2021, page 48,

5. Wong, J et al (2022), Employment Consequences of COVID-19 for People with Disabilities and Employers

6. UNESCAP report

7. Alisjahbana, A (2022) Asia and the Pacific SDG Progress Report, Foreword page 9


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