Introduction

This report serves as an introductory guide for public finance staff to navigate the complexities of poverty definition, measurement, and its application in policy. Addressing poverty was identified as the highest priority among cross-cutting challenges for public spending in low- and middle-income countries (LMICs) in a 2025 survey of finance ministries. The primer focuses on poverty as a lack of monetary resources and household consumption levels, defining it primarily as material well-being. It aligns with the global Sustainable Development Goals (SDGs), particularly SDG 1, which aims to eliminate extreme poverty—reducing it to 3%—and halve nationally set poverty levels for men, women, and children. It also highlights the importance of social protection coverage and domestic revenue mobilisation (DRM) as critical enablers for poverty reduction frameworks.

Poverty definition and measurement

Poverty is defined by setting a minimum threshold or ‘poverty line’ based on living standards. While high-income countries typically use income-based measures, low-income countries (LICs) and LMICs predominantly adopt a consumption-based approach. This includes actual expenditures on goods and services, alongside the value of in-kind consumption such as home-grown produce. To ensure consistent rankings, total resources are adjusted for household size and composition using equivalence scales. For instance, a per capita approach divides total resources by the number of residents, whereas the modified OECD scale applies specific weights to adults (1.0 for the first, 0.5 for subsequent) and children (0.3). These adjustments reflect economies of scale within the household, such as shared housing and energy costs.

International poverty lines are established by the World Bank based on country classifications. As of 2021 purchasing power parity (PPP), the thresholds are set at $3.00 for LICs, $4.20 for LMICs, and $8.30 for upper-middle-income countries. Poverty is further disaggregated by age, gender, and disability. Global estimates reveal a stark disparity in child poverty, with the ‘extreme child poverty’ rate at 16.8% in 2022, compared to an adult rate of 6.6%. The report also introduces alternative approaches such as the Multidimensional Poverty Index (MPI), which assesses deprivations in education, health, and living standards, and the Multidimensional Poverty Measure (MPM), which incorporates monetary poverty as an additional dimension.

Applying poverty to public finance

Fiscal policy’s direct influence on households is assessed through ‘fiscal incidence’ analysis. This methodology identifies who receives transfers and services and who pays taxes. The Commitment to Equity (CEQ) approach is a robust framework used to measure the net effect of fiscal policy on material well-being. Hypothetical data indicates that while the overall poor may receive 22% of transfers, they may still contribute 16% of all direct taxes. Furthermore, the poorest deciles often face slightly higher effective tax rates (ETRs) due to flat taxes such as property taxes. In some contexts, the truly non-poor contribute a greater proportion of taxes relative to their population share, yet the poor may still pay a substantial proportion of direct taxes, which can hinder optimal poverty reduction.

The report underscores the impact of ‘catastrophic health spending’, where out-of-pocket payments dramatically reduce disposable income for essentials. In 20 of 30 surveyed LMICs, these payments accounted for over half of all health expenditures in 2022. Additionally, the primer notes that while fuel subsidies and VAT exemptions on food are often intended to help the poor, they frequently have ‘pro-rich’ profiles. Fuel subsidies mostly flow to those using petrol directly, while VAT exemptions primarily benefit formal supermarket users rather than the rural poor who rely on informal retail, local markets, and barter.

Taking lessons forward

To improve policy formation, the primer recommends the use of micro-simulation models. These tools allow policy-makers to test iterations of potential changes in rules or allocations to quantify who would ‘gain’ (receive more) or ‘lose’ (receive less or pay more) from reforms. However, these models are often static and do not account for behavioural changes. For broader macro-economic impacts, such as energy subsidy reforms affecting all sectors, a Computable General Equilibrium (CGE) model is preferred. The report concludes that finance ministries should move away from treating poverty as a technical ‘black box’ and instead integrate national poverty metrics directly into evaluation, policy-making, and resource allocation processes. This involves improving data sources through the integration of household surveys with administrative data, satellite imagery, and ‘big data’.