# I. Introduction

Improved targeting has the potential to significantly increase the poverty impact of welfare spending in Sri Lanka. In 2002, 42 percent of all transfers provided by Samurdhi (the country’s main social safety net program) were received by the poorest 20 percent of households.<sup>2</sup> By 2012, this had slipped to 39 percent (World Bank, 2016c). Recognizing this, the government is currently conducting a review of the rules by which households are selected into welfare programs. The results of this paper are intended to inform that review.

A proxy means test (PMT) is an index of observable and verifiable household characteristics that serves as a proxy for household welfare. The PMT is commonly used to target social safety net programs in situations where verifiable income data are not available. Since the PMT essentially ranks households by welfare level, the same formula can be used for targeting a range of different welfare programs, adopting different eligibility cutoff scores for each program and possibly adding other criteria as well.<sup>3</sup> In this way, the PMT can serve as the basis for targeting of a range of different welfare programs. Having a common targeting approach for various programs, based on a single PMT score, ensures consistency of targeting across programs, minimizes overlaps, and provides a basis for future harmonization of programs.

An earlier study by Narayan and Yoshida (2005) developed a PMT formula for Sri Lanka based on a household survey collected during 1999‐2000.<sup>4</sup> Sri Lanka has developed rapidly since then, however, and as the country has transitioned to middle income status, the poverty rate per the (official) national poverty line has fallen from 22.7 percent in 2002 to 4.1 percent in 2016. Due to these major demographic and structural changes, and to incorporate areas of the country not covered in the earlier work, this paper presents a PMT formula based on data from the 2016 round of the Household Income and Expenditure Survey (HIES). We benchmark the PMT to the targeting performance of the PMT for the Samurdhi program, which currently determines eligibility solely based on self‐reported income. We find that switching to a PMT could significantly improve the targeting performance of Samurdhi.

This paper examines only the PMT method, although we recognize that this is one of many targeting methods used around the world (Alatas et al., 2012; Alkire and Seth, 2013; Klasen and Lange, 2015; Brown et al., 2016; Diamond et al., 2016; Sabates‐Wheeler et al. 2015; Del Ninno and Mills, 2015; Kydd and Wylde, 2011). This is because our goal is to inform the efforts of the Sri Lankan government, which already distributes Samurdhi transfers based on self‐reported income and is in the process of updating this system, a component of which is to replace self‐reported income with a vector of household attributes to identify beneficiaries (World Bank, 2016d).

> 2 The Samurdhi program provides monthly cash benefits to almost 1.5 million families, and accounts for over 80% of Sri Lanka’s cash transfer spending. The program also provides other assistance to its beneficiaries, including microfinance, housing, and banking services.

> 3 For instance, the disability benefit would need to include criteria relating to severity of disability.

> 4 Although the survey was nationally representative, data for the Northern and Eastern regions, affected by conflict at the time, were excluded for the purposes of the paper due to concerns about data quality.

2