Measuring change in poverty

Measuring change in poverty
By Dr Sono Khangharani, Ghias M Khan and Zulfiqar Halepoto
http://www.dawn.com/2008/09/15/ebr11.htm


The most frequent questions asked include, who are the poor? How many poor are there? Where do they live and what is their social and economic profile?

In order to answer these questions, the Rural Support Programmes (RSP), with the help of Grameen Foundation, US , have developed a poverty scorecard.

The scorecard has been developed as a tool to measure change in poverty in an effective way and to support the management of development programmes in microfinance and also in other development sectors. It is also a useful tool for social investors that need to measure their results according to the triple bottom line objectives --- financial, social and environmental results.

The poverty scorecard uses the 2001 Pakistan Integrated Household Survey to construct an easy-to-use, objective poverty scorecard that estimates the likelihood that a participant has expenditure below the national poverty line. It uses 10 simple indicators that field workers can quickly collect and verify.

Scores can be computed by hand on paper in real time. With 90 per cent confidence, estimates of groups’ overall poverty rates are accurate to within +/–1.1 percentage points. The poverty scorecard can help programme’s target services, track changes in poverty over time, and report on poverty rates.

The poverty scorecard is based on existing national expenditure surveys from which 10 indicators are selected as proxy for poverty. The indicators are quantitatively summarised through a statistical procedure - adding up 10 non-negative positive integers’ - to give a score, which represents a probability of being poor. The indicators are simple and inexpensive to collect as well as easily verifiable, such as selected housing features and ownership of consumer items (e.g. type of latrine and roof, radios, kitchen material, etc.).

Proper selection of indicators is relevant; however, their weighting is astonishingly not crucial. The accuracy depends on the recentness and quality of the national expenditure. The low-tech scorecard is derived from Pakistan’s 2004-2005 Household Income and Expenditure Survey (Ahmed, 2004). The indicators were selected to be:

* inexpensive to collect, easy to answer, and simple to verify; strongly correlated with poverty; liable to change as poverty status changes over time.

All scorecard weights are non-negative integers. Scores range from 0 (most-likely poor) to 100 (least-likely poor). Field workers can compute scores by hand in real time.

A participant’s score corresponds to a “poverty likelihood”, that is, the probability of being poor. The share of all participants who are poor is the average poverty likelihood. For participants over time, progress is the change in their average poverty likelihood.

By construction, the scorecard is accurate in that, on average, the estimated poverty likelihoods of individuals and the overall poverty rate of groups are equal to the true values. The scorecard is also accurate for targeting in that poor people are concentrated among low scores and non-poor people are concentrated among high scores.

Precision was measured by bootstrapping a hold-out sample. The 90 per cent confidence intervals for estimated poverty likelihoods are about +/–5 percentage points, and the 90 per cent interval for estimated overall poverty rates is +/–1.5 percentage points.

About 1,500 potential poverty indicators were prepared for the 15,503 households from the 2004-2005 PHIES were used to construct the scorecard. Broadly, the indicators cover:

Household and housing characteristics (such as cooking fuel and type of floor); individual characteristics (such as age and highest grade completed) ; household consumption (such as milk and meat) ; household durable goods (such as electric fans and stoves).

Many indicators are similar in terms of their link with poverty. For example, households with a flush toilet connected to public sewerage are also more likely than other households to have piped water. If a scorecard already includes “flush toilet connected to public sewerage”, then “piped drinking water” is superfluous. Thus, many indicators strongly linked with poverty are not in the scorecard because similar indicators are already included.

The scorecard also aims to measure changes in poverty through time. Thus, some powerful indicators (such as education of the female head/spouse) that are unlikely to change as poverty changes were omitted in favour of slightly less-powerful indicators such as the presence of a radio) that are more likely to change. None of the consumption indicators (such as “In the past two weeks, did anyone in the household eat any tomatoes”) were selected because they cannot be directly observed nor verified.

Finally, some indicators were not selected because they are difficult to collect (“Have you received or contributed to Zakat, Usher, or Nazrana?”), difficult to compute, (“what is the ratio of adults to children in the household?”) or too sensitive (“who decides whether the female head/spouse uses contraception?”).

The scorecard is an easy-to-use, inexpensive tool for identifying the poor could improve targeting and speed progress out of poverty. The scorecard which is built and tested using data on 15,503 households from the 2004-2005 PIHS is calibrated to estimate the likelihood of being poor (expenditure below the official line) or very poor (poorest half of the poor).

The poverty scorecard has been used by the Sindh RSPs Consortium to estimate the likelihood of being poor of more than 400,000 households in more than 110 union councils of Sindh. For individual poverty likelihoods (whether poor or very poor), estimates are within 10 percentage points of the true value with 90 per cent confidence. For a group’s overall poverty rate (again, whether poor or very poor), estimates are within 1.1 percentage points of the true value.