Indirect Measures: a scorecard (objective) and perception (subjective) based poverty Sajjad Zohir Lecture # 5 GED-ERG Training Workshop on Measuring Poverty 9 – 11 May 2015

What is it we want to achieve? Brief on the sample frame so that you may pursue those in the afternoon classes Understanding the criteria for choosing one or more variables over which a ‘threshold’ is defined. Understanding an ‘objective’ measure of poverty – the case of score card (and a mention of proxy means test) Understanding a subjective measure of poverty – perception-based poverty using pair-wise comparison – linked to Mr. Faizuddin Ahmed’s class Few general issues (quick test)

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Proxy means test “Much of their success in targeting the poor has to do with their local level presence and knowledge as well as efficient management information systems funded by donors (World Bank, 2007). These NGO driven targeting strategies which are often labour-intensive and community based are not always possible for large government bureaucracies to adopt let alone implement.” Proxy Means Tests: identify the extreme poor based on a formula derived from household survey data. This method of targeting involves using observable and verifiable household or individual characteristics in a formal algorithm to proxy household welfare. These variables are selected based on their ability to predict welfare as measured by, for instance, consumption expenditure of households. The administrative difficulties associated with sophisticated means tests used by most public safety net programs in Bangladesh, and the inaccuracy of the results due to the problems with measuring income also provide a strong rationale for employing proxy means tests. Like means tests, proxy means tests can be costly relative to other forms of household level targeting (e.g. community-based targeting methods). However, they tend to produce the lowest errors of inclusions and thus are considered good investments.

Proxy means test - efficiency The targeting efficiency of the PMTF depends on these following four key features. -First, the variables chosen to estimate the model should be very good predictors of consumption (so that a substantial proportion of the variation in consumption is explained by the regression model). -Second, the proxies used should be relatively few but easy to measure and verify. -Third, the model should achieve a reasonable level of targeting accuracy such that under coverage, leakage and coverage rates associated with the model are at acceptable levels. -Fourth, the incidence of beneficiaries should be acceptable, i.e. the PMT should be able to rank selected beneficiaries mostly in the bottom end of the consumption distribution. A variable to proxy welfare, say, consumption per capita; a database that allows you identify limited set of variables that can explain better the variation in pc consumption, the predicted value (a score that uses the coefficients of the estimated equation, rounded up), the prediction error (type I and II) for different groups (say, quintile) are then used ex ante to design programs. Programs can also be evaluated with those variables without having to get into details of consumption data.

Poverty measures – the broader canvass HIES that permits reliable estimates at division/zone levels Local administrative officer, grassroot organizations combined Q-Q method to identify poor for centuries and the same apply for the NGOs/MFIs 10 questions scorecards for application by local organizations PMT for design and evaluation of support programs targeting households Small Area Estimation, using census and HIES for geographic targeting Entry of multi- dimensionality, with HIES remaining as the basis Decline in authority of local NGOs call for removing discrepancies in distant observations – thus, Perception surveys continue Any guess on the future of HIES?

Poverty Score Card

Perception

The poverty scorecard here differs from “proxy means tests” (Coady, Grosh, and Hoddinott, 2002) in that it is tailored to the capabilities and purposes not of national governments but rather of local, pro-poor organizations. The feasible poverty measurement options for local organizations are typically subjective and relative (such as participatory wealth ranking by skilled field workers) or blunt (such as rules based on land- ownership or housing quality) Bootstrapping is a nonparametric technique of estimating the standard error of a parameter estimate using repeated samples from the original data. This is done by sampling with replacement.