Targeting the poorest: An assessment of the proxy means test methodology
The purpose of this study is to help DFAT staff, their counterparts in partner governments and others working in the field of social protection to better understand the strengths and weaknesses of a targeting methodology known as the proxy means test (PMT). As social protection practitioners search for effective ways to target poor people in developing countries, proxy means testing has become increasingly popular. The methodology estimates household income by associating indicators or 'proxies' with household expenditure or consumption. This study assesses its accuracy, objectivity, transparency and ease of implementation.
Proxy means testing uses multivariate regression to correlate certain proxies, such as assets and household characteristics, with poverty and income. This study assesses regression accuracy in Bangladesh, Indonesia, Rwanda and Sri Lanka and finds that the PMT has high in-built errors, especially at relatively low levels of coverage (20% of the population and below). Exclusion and inclusion errors vary between 44% and 55% when 20% of the population is covered and between 57% and 71% when 10% is covered.
Part of the reason for this is the imperfect correlation between multiple proxies and household consumption. Additionally, the PMT methodology is based on national household survey data that represent 'reality' at one point in time and are inherently inaccurate to varying degrees. Other issues are sampling errors in household surveys and assumptions made in applying the PMT, which increase the arbitrary nature of the methodology yet affect whether individual households receive social protection benefits.
The PMT is expensive to administer and has associated social and political costs. There is evidence that it can generate social conflict and stigmatise beneficiaries. Politically, the methodology–as with all other forms of poverty targeting–is less likely to be popular because it excludes the middle class and those who are better-off. However, this study's findings show that the PMT is inherently inaccurate, especially at low levels of coverage. Targeting the Poorest does not provide an in-depth assessment of other targeting methods or formally compare them with the PMT methodology. It suggests, however, that other methods used to develop social protection schemes–which do not directly target poor people–may be better at including intended beneficiaries and avoiding the pitfalls of the PMT.