Various measures of the “targeting performance” of antipoverty programs have been widely used to inform policy discussions. These measures are typically interpreted by both analysts and policy makers as indicators of a program’s performance in “...directing benefits toward poorer members of the population” (Coady, Grosh and Hoddinott, 2004a, p.81). Comparisons of such measures across different programs have informed public choices on which programs should be scaled up and which should be dropped.<sup>2</sup> As in any situation in which measurement is used to inform policy, “the indicators need to be related to the overall policy problem, with an explicit formulation of the objective and constraints” (Atkinson, 1995, p.31). It is widely agreed that the objective of this class of public programs is to reduce poverty, subject to the relevant constraints, including those related to the information available and the behavior of relevant agents, as well as resources. Better targeting is not seen as desirable in its own right, but rather as an instrument for reducing poverty.

Do the measures of targeting used in policy discussions provide useful indicators for this policy problem? The most widely used measures quantify some aspect of how well a given program concentrates its benefits on the poor, which is essentially what “targeting” has come to mean. An example is the share of transfers going to the poor. Cornia and Stewart (1995) have been influential in arguing that measurement practices and policy discussions have put too high a weight on avoiding one type of error—the “Type 1 error” of having (ineligible) non-poor participants—relative to the “Type 2 error” of incomplete coverage of the poor.<sup>3</sup> Cornia and Stewart did not present data linking these aspects of targeting performance to poverty outcomes (though they do point to this as an important direction for further research). However, the literature warns us against assuming that better targeting, as assessed by standard measures, will necessarily enhance a program’s total impact on poverty.<sup>4</sup> A number of factors cloud the relationship between targeting performance and total impact on poverty, including

> 2 Early empirical studies by Mateus (1983) and Grosh (1992) were influential in arguing the case for finer targeting.  The meta studies of Grosh (1994) and Coady et al. (2004a,b)  have provided the most comprehensive comparative data on program performance based on targeting measures.

> 3 The distinction between these two errors goes back to Weisbrod (1970) who called them “vertical-” and “horizontal target efficiency.” Cornia and Stewart (1995) used the terms “E-mistakes” and “F-mistakes;” Smolensky et al., (1995) called them “errors of inclusion” and “errors of exclusion.” The literature on social welfare policy in developed countries has also suggested that coverage of the poor is given little weight by standard measures of targeting.  See, for example, the results of Duclos (1995) on the implications of incomplete take up of Britain’s welfare benefits for measures of targeting.  However, the relationship between these problems and overall impacts on poverty has received little attention.

> 4 For an overview of the arguments and evidence see van de Walle (1998).

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