Measuring poverty in an age of continuous disruption

By Mohamed Shahudh

ON OCT. 17, the world marked the International Day for the Eradication of Poverty. It is also a moment to reflect on the tools we have used to measure poverty over decades of relative stability: can they still see the poor in an era where crises overlap and move fast — and see them in time to act?

Global poverty measurement has already undergone an important transformation. In 2015, all 193 UN Member States adopted the Sustainable Development Goals, which recognize both monetary poverty and poverty in all its dimensions. This broadened the approach under the Millennium Development Goal, whose main poverty target relied largely on an international income threshold. A monetary measure asks whether a household has sufficient resources to meet its minimum basic needs, while a multidimensional approach complements this by capturing overlapping and often slower-moving deprivations in education, healthcare and the other essentials of a dignified life. Around 50 countries now use a national Multidimensional Poverty Index (MPI) alongside their monetary measure. These are strong foundations.

Yet these measures largely remain unconnected to systems that can detect larger trends and trigger timely action. The World Bank’s Global Insights on Social Registries finds that 62 countries had operational social registries covering 1.1 billion people in 2024, but only 29 extend them beyond social protection to employment, health, education, or subsidies. Measurement and delivery therefore often remain separate, limiting governments’ ability to act before a temporary shock becomes lasting poverty.

These stakes are clearly visible in the 2026 Global MPI, published this month by UNDP and the Oxford Poverty and Human Development Initiative, which counts 1.2 billion people across 108 countries in acute multidimensional poverty, 41% in Asia and the Pacific. Nearly two thirds live in middle-income countries, giving a powerful reminder that growth alone does not end entrenched deprivation.

Similar poverty levels also hide different needs. Vietnam’s Northern Uplands and Central Highlands have the same poverty rate, yet poverty in the Uplands stems primarily from poor health, while in the Highlands it stems from missed schooling. Addressing these needs requires a different mix of income support, public services, and infrastructure, which will need to be designed jointly by national and subnational governments and directly targeting these deficits. Seeing this complexity early enough to act will be increasingly central to ending poverty.

The Philippines has built its own dual approach to tracking poverty. Its statistical system has tracked monetary poverty for decades; a newly updated national MPI now shows which disadvantages households face together. Monetary poverty fell from 18.1% of Filipinos in 2021 to 9.7% in 2025, while 12.8% were multidimensionally poor in 2024. Education accounts for 40.7% of the index and housing, water, and sanitation for 31.3%. At least two in three poor families face both deprivations, strengthening the case for education and infrastructure programs designed and delivered together by national and local governments.

Three global forces are set to test these foundations in the coming months. The energy shock and El Niño are already reinforcing each other, with major forecasters expecting average inflation of 5.6% to 5.9% this year while growth is expected to range between 3.3% to 3.7%, eroding purchasing power particularly for the below 30% in Philippines. Meanwhile, an FT analysis this month shows that a hiring slowdown in the global call center industry, which first appeared in high-income countries, has now reached middle-income countries, with employment already 5.3% below its 2023 peak, complicating the outlook for outsourced digital services. All of this strengthens the case for casting a wider net, closing blind spots, and shifting towards anticipatory poverty monitoring.

Three priorities can move this forward in the Philippines.

First, enhance the interoperability of poverty information systems. A recent PIDS study identifies roughly 1.5 million households captured by the Community-Based Monitoring System that no active social protection program covers, alongside more than 1.1 million seniors aged 70 and over who remain unenrolled in social pensions. An integrated system — linking survey, social-protection, labor, education, health, and disaster records — could help identify such households sooner and bring them onto formal registries. The E-Governance Act of 2025 already encourages similar integration and data-driven policymaking; poverty data should be among the first connected.

Second, link evidence on deprivation to budgets. The national MPI draws on the Community-Based Monitoring System and offers locally specific evidence for national and local decisions. Nationally, it can inform established mechanisms such as Program Convergence Budgeting, through which lead and participating agencies coordinate targets and funding requirements. Local governments can use the same evidence to find vulnerable households, direct budgets to the most pressing needs, and track whether conditions improve.

Third, bring digital disruption into poverty monitoring. Internet-access data should be combined with frequently updated indicators on displacement, vacancies, wages, and skills demand. These early signals can guide reskilling and employment support, and help move workers towards the higher-value roles AI can also create.

The dual approach has given the Philippines a strong foundation to see who is poor and what they lack. It now needs a faster, more connected and anticipatory layer, one that sees change as it happens, to cover the blind spots that a confluence of fast-moving crises creates. As one of the most vulnerable countries globally, the Philippines needs to close these gaps to tackle poverty in all its forms and ensure growth’s dividends reach all corners of society.

Sources:

Financial Times, Oct. 8, 2026. “The AI Shift: The long-predicted decline in call center jobs has finally begun”  https://www.ft.com/content/d6417373-a80b-4716-a31e-9c0de08fbe88?syn-25a6b1a6=1

UNDP and OPHI, 2026 Global Multidimensional Poverty Index: Statistical Update, Oct. 12, 2026 https://hdr.undp.org/content/2026-global-multidimensional-poverty-index#/indicies/MPI

Growth Forecasts for the Philippines from Asian Development Bank’s Asian Development Outlook (September 2026), World Bank East Asia and Pacific Economic Update (October 2026), and the IMF World Economic Outlook (October 2026).

Philippines Institute for Development Studies: Who Suffers Most When Oil Prices Spike? https://pidswebs.pids.gov.ph/CDN/document/pidspn2609.pdf