Watts Poverty Index
Also known as: Watts Index, Watts Poverty Measure, Log Shortfall Poverty Index
The Watts index, proposed by Harold Watts in 1968, was the first poverty measure to be sensitive to the distribution of income among the poor, anticipating the axiomatic poverty-measurement literature by nearly a decade. It averages, over the whole population, the natural logarithm of the ratio of the poverty line to each poor person's income. Because the log gives ever-larger weight to incomes near zero, the Watts index satisfies the strong transfer principles that the headcount and the linear poverty gap fail, and Buhong Zheng's 1993 axiomatic characterization established it as the smallest distribution-sensitive measure satisfying a natural set of axioms.
Key highlights
- Satisfies the strong transfer axiom and transfer sensitivity, so it genuinely reflects inequality and the severity of deprivation among the poor.
- Was the first distribution-sensitive poverty measure and has a clean axiomatic characterization (Zheng 1993) as a minimal such measure.
- Additively decomposable across subgroups, enabling poverty profiles, and central to Watts-based poverty-dominance and TIP-curve analysis.
- Underpins exact growth-redistribution and elasticity results, making it analytically convenient for policy decompositions.
Intuition
This section is available to Pro members. Upgrade to Pro
How it works
This section is available to Pro members. Upgrade to Pro
When to use it
Use the Watts index when distributional concern among the poor is central and you want a measure with strong axiomatic credentials — it satisfies monotonicity, the transfer axiom, transfer sensitivity, subgroup decomposability, and continuity, and it underlies clean poverty-dominance and growth-decomposition results. It is especially appropriate for evaluating policies that target the poorest of the poor, where a measure insensitive to the distribution below the line (such as the headcount or linear gap) would miss the point. Report it alongside the headcount and FGT measures for a fuller picture. The chief practical caution is that the index needs strictly positive welfare values, so it is typically computed on consumption rather than income, and recorded zeros or negatives must be censored at a small floor before logs are taken.
Strengths & limitations
- Satisfies the strong transfer axiom and transfer sensitivity, so it genuinely reflects inequality and the severity of deprivation among the poor.
- Was the first distribution-sensitive poverty measure and has a clean axiomatic characterization (Zheng 1993) as a minimal such measure.
- Additively decomposable across subgroups, enabling poverty profiles, and central to Watts-based poverty-dominance and TIP-curve analysis.
- Underpins exact growth-redistribution and elasticity results, making it analytically convenient for policy decompositions.
- Undefined for non-positive incomes because it takes logarithms, requiring censoring at a positive floor that can materially affect the value.
- Highly sensitive to incomes near zero, so measurement error or misreporting at the bottom of the distribution can dominate the index.
- Expressed in log-welfare units, it is less directly interpretable to non-specialists than the headcount or the per-capita poverty gap.
- Like all unidimensional money-metric measures it depends on an exogenous poverty line and ignores non-income dimensions of deprivation.
Common pitfalls
This section is available to Pro members. Upgrade to Pro
Applications
This section is available to Pro members. Upgrade to Pro
Frequently asked
How does the Watts index differ from the FGT squared poverty gap?
Both are distribution-sensitive and satisfy the transfer axiom, but they use different curvature. The squared poverty gap (FGT alpha = 2) weights the squared normalized shortfall, which is bounded between zero and one and grows quadratically. The Watts index weights the log of the line-to-income ratio, which is unbounded and grows ever faster as income approaches zero, so Watts gives stronger weight to extreme deprivation. Watts is also the natural welfare measure behind several exact decomposition and dominance results, whereas the squared gap is more directly interpretable as a normalized quantity.
Why must incomes be strictly positive for the Watts index?
Because the index takes the natural logarithm of income, ln(z/y_i), which is undefined at zero and undefined (or complex) for negative values, and which diverges to infinity as income approaches zero. Surveys frequently record zero or negative incomes (for example, business losses or no recorded earnings), so in practice analysts either use consumption — which is rarely non-positive — or censor income at a small positive floor before computing the index. The chosen floor should be reported, since it influences the contribution of the poorest.
Is the Watts index decomposable across population subgroups?
Yes. Because it is a population-weighted average of individual contributions, total poverty equals the sum over subgroups of the subgroup population share times the subgroup Watts index. This additive decomposability lets analysts apportion national poverty to regions or demographic groups, exactly as with the FGT family, and is one of the axioms in Zheng's characterization of the measure.
Sources
- 1.Zheng, B. (1993). An axiomatic characterization of the Watts poverty index. Economics Letters, 42(4), 347–353.
You have read it. What now?
Cite this page
ScholarGate. (2026, June 22). Watts Poverty Index. ScholarGate. https://scholargate.app/economics/watts-poverty-index