Finding the Best Indicators to Identify the Poor

Proxy-means testing (PMT) is a method used to assess household or individual welfare level based on
a set of observable indicators. The accuracy, and therefore usefulness of PMT relies on the selection
of indicators that produce accurate predictions of household welfare. In this paper I propose a method
to identify indicators that are robustly and strongly correlated with household welfare, measured by
per capita consumption. From an initial set of 340 candidate variables drawn from the Indonesian
Family Life Survey, I identify the variables that contribute most significantly to model predictive
performance and that are therefore desirable to be included in a PMT formula. These variables span
the categories of household private asset holdings, access to basic domestic energy, education level,
sanitation and housing. A comparison of the predictive performance of PMT formulas including 10,
20 and 30 of the best predictors of welfare shows that leads to recommending formulas with 20
predictors. Such parsimonious models have similar predictive performance as the PMT formulas
currently used in Indonesia, although these latter are based on models of 32 variables on average.