In the next section, we explain the rationale for the PMT as a tool for measuring poverty. In Section III we describe the data and general set‐up of the PMT formula. In Section IV we present results and discuss the selection of the best‐performing models. This section demonstrates that PMT simulations outperform the targeting approach used in the Samurdhi program. Section V presents results of the robustness checks that we conduct on our primary PMT model. The final section presents conclusions and suggested next steps.

# II. The Rationale for a Proxy Means Test

PMT‐based targeting has been adopted in many low‐ and middle‐income countries since the 1990s. Case studies on performance in terms of targeting incidence suggest that the PMT approach has been very successful and outperformed other targeting mechanisms (Grosh, 1994). For example, in Chile and Mexico approximately 90 percent of social assistance reached the bottom 40 percent of the population when a PMT was adopted (Castañeda and Lindert, 2005). Beyond Latin America, Armenia introduced a PMT in 1994 for targeting cash transfers (World Bank, 1999, 2003), Indonesia has adopted PMT for targeting subsidized rice rations and transfers following the removal of fuel subsidies (Sumarto et al., 2000), and Turkey introduced PMT‐based targeting in 2002 (Ayala, 2003). In the South Asia region, PMT‐based targeting systems have been employed in Pakistan and Bangladesh (Sharif, 2009; Hou, 2008).

The PMT determines eligibility for a program based on an index of easily observable household characteristics, such as the quality of the household’s dwelling, ownership of durable goods, demographic structure, and the education and employment status of adult household members (Grosh et al., 2008). Statistical analysis of data from household surveys is normally used to refine the set of indicators included in the index and to estimate their respective weights. Information collected from each program applicant is then used to construct a household‐specific ‘PMT score’, which is a proxy for the family’s relative welfare level in the population. This score is used to determine eligibility for safety net programs and potentially also the level of benefits. A household is eligible for the program if its PMT score falls below a predetermined cutoff score.

Although actual household income is in theory a more accurate measure of welfare (and indeed self‐ reported income is currently used as a main eligibility criterion for the Samurdhi program), it can be difficult to accurately measure or estimate reliably in countries like Sri Lanka, where a large proportion of households are self‐employed or informally employed.<sup>5</sup> The value of informal transfers like gifts and remittances is also difficult to measure. If income self‐declarations are difficult to verify, households have a temptation to understate income in order to qualify for benefits. In cases like Sri Lanka where accurate data on household consumption is also burdensome to collect and difficult to verify, self‐reported consumption faces similar drawbacks as a targeting approach. The PMT offers a way to estimate a household’s welfare level without utilizing self‐declared income or consumption.

> 5In the first quarter of 2016, one=third of all workers were own account workers (Department of Census and Statistics, 2016).

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