September 2025 global poverty update from the World Bank: New data and regional classifications – World Bank Blogs

Report on Methodological Updates to Global Poverty Monitoring and Implications for Sustainable Development Goal 1

Enhanced Data for Monitoring SDG 1.1: Database Expansion and Regional Impact

In a significant update contributing to the accurate monitoring of Sustainable Development Goal 1 (No Poverty), the Platform for International Poverty (PIP) database has been expanded. This enhancement is crucial for tracking progress towards SDG Target 1.1, which aims to eradicate extreme poverty for all people everywhere.

• Data Expansion: The database now includes 55 new country-year datapoints and has revised data for 11 others, bringing the total to over 2,500 observations across 172 countries. This aligns with SDG Target 17.18, which calls for increased availability of high-quality, timely, and reliable data.
• Improved Regional Coverage: The inclusion of new data from Nigeria has substantially improved survey coverage in Sub-Saharan Africa, a key region for achieving SDG 1. Coverage in Western and Central Africa now stands at 85 percent, and for all of Sub-Saharan Africa, it is 56.7 percent for 2024.
• Revised Poverty Estimates: The improved data provides a more precise measure of the challenges in meeting SDG 1. The extreme poverty rate in the Western and Central Africa region has been revised upward from 32.8 percent to 35.7 percent. This revision indicates that an additional 15.6 million people are living in extreme poverty in the region, underscoring the urgency of targeted interventions.

Methodological Advancements in Estimating Poverty for Data-Scarce Regions

To ensure a comprehensive global assessment of SDG 1, a new methodology has been implemented to predict poverty levels in countries lacking recent survey data. This addresses a critical gap in global poverty monitoring.

1. Previous Method: Formerly, countries without survey data were assigned their respective regional poverty rate.
2. New Predictive Model: The current update predicts full welfare distributions for these countries based on a set of variables available across nearly all economies. This more granular approach is applied to 47 economies, which account for less than 3 percent of the world’s population.
3. Impact on Global SDG 1 Assessment: While the overall impact on global poverty figures is not large, this methodological refinement results in a slight increase in the global extreme poverty rate. This is because countries with insufficient data tend to be poorer than their regional averages, and the new model provides a more accurate reflection of their economic conditions, thereby strengthening the integrity of global SDG 1 monitoring.

Revised Regional Classifications and Their Effect on SDG Reporting

The PIP has updated its regional classifications to align with the World Bank’s standard framework. This change promotes consistency in reporting on global development goals, including the SDGs, but also impacts the analysis of regional poverty trends.

• Structural Changes: High-income countries are now integrated into their geographical regions, eliminating the ‘Other High Income’ category and establishing a ‘North America’ region.
• Creation of MENAAP Region: Afghanistan and Pakistan have been moved from the South Asia region to a newly formed region named Middle East, North Africa, Afghanistan and Pakistan (MENAAP).
• Implications for SDG Monitoring: This reclassification directly affects the reported poverty rates and progress towards SDG 1 for the South Asia and the new MENAAP regions. It also highlights significant data gaps that challenge the monitoring of SDG 1, as recent internationally comparable poverty estimates are unavailable for Afghanistan and Pakistan (latest survey 2018). This underscores the critical need for capacity-building in data collection as stipulated in SDG 17.

1. Which SDGs are addressed or connected to the issues highlighted in the article?

• SDG 1: No Poverty

  The article is fundamentally about measuring and understanding global poverty. It directly discusses “extreme poverty,” poverty rates in specific regions like “Western and Central Africa,” and the number of people “living on less than $3 a day.” This aligns perfectly with the primary objective of SDG 1, which is to end poverty in all its forms everywhere.

• SDG 17: Partnerships for the Goals

  The article details the process of improving data collection and statistical methodologies for monitoring poverty. It mentions adding “55 country-year datapoints,” increasing “survey coverage” in Sub-Saharan Africa, and refining prediction methods for countries with missing data. This work is central to the “Data, monitoring and accountability” targets within SDG 17, which emphasize the need for high-quality, timely, and reliable data to track progress on all SDGs.

2. What specific targets under those SDGs can be identified based on the article’s content?

1. SDG 1: No Poverty

   • Target 1.1: By 2030, eradicate extreme poverty for all people everywhere. The article directly addresses this by discussing the “upward revision of extreme poverty” and tracking the “global extreme poverty rate.” The entire purpose of the PIP database update is to more accurately measure progress towards this target.
   • Target 1.2: By 2030, reduce at least by half the proportion of men, women and children of all ages living in poverty in all its dimensions according to national definitions. While the article focuses on international poverty lines, the data collection efforts it describes are essential for this target. Improving “survey coverage” to “85 percent” in Western and Central Africa provides the foundational data needed to measure poverty reduction at regional and national levels.

2. SDG 17: Partnerships for the Goals

   • Target 17.18: By 2020, enhance capacity-building support to developing countries… to increase significantly the availability of high-quality, timely and reliable data. The article is a clear example of this target in action. The update to the PIP database, which “now contains over 2,500 survey-year observations from 172 countries” and significantly improves “survey coverage in Western and Central Africa,” directly contributes to increasing the availability and reliability of poverty data.
   • Target 17.19: By 2030, build on existing initiatives to develop measurements of progress on sustainable development that complement gross domestic product, and support statistical capacity-building in developing countries. The World Bank’s PIP is an existing initiative for measuring progress. The article describes how it is being built upon by changing “how poverty is predicted for countries that do not have a poverty estimate” and revising regional classifications to improve accuracy, thereby supporting statistical capacity for monitoring sustainable development.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

1. Indicators for SDG 1

   • Indicator 1.1.1: Proportion of the population living below the international poverty line. This is explicitly mentioned and measured in the article. For example, it states that extreme poverty in the “Western and Central Africa region” was revised from “32.8 to 35.7 percent,” which is a direct measurement of this indicator. The mention of “people living on less than $3 a day” also refers to a specific international poverty line used for this indicator.

2. Indicators for SDG 17

   • Indicator 17.18.1: Statistical capacity indicator for sustainable development. While not named, this indicator is strongly implied. The entire article describes activities that enhance statistical capacity. The improvement of “survey coverage for Sub-Saharan Africa up to 56.7 percent in 2024” is a tangible measure of increased capacity to collect and report on poverty statistics, which is what this indicator tracks. The expansion of the database to “over 2,500 survey-year observations” is another metric of this capacity.

4. Table of SDGs, Targets, and Indicators

Source: blogs.worldbank.org