Targeting Poor Students With Proxy Means Test

Proxy Means Test (PMT) is one of the most efficient ways to target the poor. The procedure of PMT is using household characteristic variables, which have a relationship with income, as a proxy for poverty. That is, PMT is a measurement of wealth, that is so to say poverty without using income, consumption or expenditure. In this study, we created the PMT poverty scorecard to be used as a tool for targeting poor student in 10 provinces of Thailand, including Mae Hong Son, Nan, Nakhon Ratchasimi, Udon Thani, Nakhon Phanom, Chiang Rai, Trung, Kanchanaburi, Chanthaburi, and Phuket. We estimated the relationship between these household characteristic variables and student’s average monthly household income per capita by using Ordinary Least Square (OLS) regression separately by province to capture any geographical characteristic in each province. We then turned 11 of household characteristic estimated coefficients into PMT poverty scorecard for each province. The result suggests that overall, PMT poverty targeting works well in 10 provinces of Thailand in terms of low undercoverage rate, high targeting accuracy rate in both poverty and total accuracy, except for Phuket which has a huge leakage rate since its geographical characteristics which are quite different comparing to others. This leakage problem, however, needs to be explored more as student maybe, in fact, actually poor as same as PMT poverty targeting suggested. For policy recommendation, we suggested using PMT as the main poverty targeting approach together with an identification survey of student who has been targeted as poor to increase the efficiency of poverty targeting. Also, we suggested the addition of household characteristic variables in survey questionnaire could lead to an increase in efficiency of PMT poverty targeting in statistical term.