Trends in Poverty: The UK in International Perspective - How Rates Mislead and Intensity Matters
Bibliographic record
Abstract
Although a large academic literature has discussed why the poverty rate is a poor summary index of trends in poverty, it is still used in much applied policy analysis.This paper begins by summarizing briefly why poverty intensity is a better measure of poverty.Using Luxembourg Income Study data on trends in poverty since the 1970s in Sweden, Canada, the USA and UK, it demonstrates that in about 40% of year to year comparisons, the conclusion one would draw about trends in relative poverty differs qualitatively if one uses the poverty rate or poverty intensity as the measure.For absolute poverty in the UK, the poverty rate and poverty intensity change in opposite directions every time.Since the choice of index of poverty matters, both for measurement and for analysis, the paper concludes by demonstrating that poverty intensity can be represented graphically by the "Poverty Box", and showing that trends over time, international comparisons and analysis of the impact of changes in the proportion of workless households can all be easily communicated using this tool.As well, poverty trends are extremely sensitive to the distribution of the gains from growth -if only 10% of the income gains of the top decile of the UK and the USA had been transferred to the bottom decile, poverty in both countries in 1994/95 would have been substantially lower than in 1979, instead of substantially higher. Non-Technical Summary Is poverty increasing or decreasing?A large academic literature on the measurement of poverty argues that the poverty rate is a poor summary index of trends in poverty because it ignores the depth of poverty.This can have policy implications -when decreases in the poverty rate are used as the criterion for social policy, administrators who want to demonstrate "success" will always be tempted by the option of "creaming" the poverty population.By redistributing benefits or services away from the very poorest (who are so far below the poverty line they are likely to stay poor anyhow) to those just below the poverty line (who have the greatest chance of being moved over the line) administrators can reduce the poverty rate, even while deepening the deprivation of the worst off -which is surely not a socially desirable outcome.This paper therefore argues that poverty intensity is a better measure of poverty than the poverty rate.It demonstrates that the choice of poverty index matters because they often move in different directions.In the early 1990s, the two indices (poverty rate and poverty intensity) agree on trends in relative poverty in the USA and in Germany, but disagree in Canada, the UK and Sweden.If the poverty line is fixed in real terms, the disagreement is particularly pronounced for the UK, where movements in the poverty rate and in poverty intensity are in different directions in all years examined (1974-79, 1979-86, 1986-91 and 1991-95).Poverty intensity has a straightforward graphical interpretation, since it can be approximated in two dimensions as the area of a rectangle, whose height is the average poverty gap ratio and whose width is the poverty rate.The POVERTY BOX can be used to demonstrate the size of international differences in poverty and the importance of Britain's unique experience of workless households.The UK has by far the biggest increase in worklessness and households without work are the poorest of the poor.Furthermore, the UK is the country for which the poverty rate is the most consistently misleading indicator of poverty trends, so a better index of poverty is particularly important for the UK.As well, the POVERTY BOX can illustrate the sensitivity of poverty to the distribution of the gains from growth -if only 10% of the income gains of the top decile of the UK and the USA had been transferred to the bottom decile, poverty in both countries in 1994/95 would have been substantially lower than in 1979, instead of substantially higher.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".