(2011a) note increased maize production and productivity as among the program’s achievements. The Ministry of Agriculture and Food Security (MoAFS) figures on crop production since the 2005/06 agricultural season have implied that the country has consistently enjoyed a maize surplus over its annual requirements estimated at 2.1 metric tons (Chinsinga, 2012).

Despite the reported progress, the national absolute poverty rate of 52.4 percent in 2004/05 declined only marginally to 50.7 percent in 2010/11. The trends in rural poverty followed a similar pattern: a rate of 55.9 percent in 2004/05 vs. 56.6 percent in 2010/11.<sup>2</sup> Income inequality, as measured by the GINI coefficient, increased from 0.39 in 2004/05 to 0.45 in 2010/11 (Malawi NSO, 2012)<sup>3</sup> . Stagnant poverty levels, increasing income equality, and the FISP accounting for 8.2 percent and 62 percent of the national budget and agriculture budget, respectively during the 2009/10 agricultural season (Lunduka et al., forthcoming) raise questions on the effectiveness of the program in targeting poor households and alleviating poverty and food insecurity in a sustainable fashion. These concerns have been raised in the past (Ricker-Gilbert and Jayne, 2011; Holden and Lunduka, 2010), and Ricker-Gilbert and Jayne (2012) document that major returns from subsidized fertilizer accrue almost exclusively to households at the top of the maize production and value of total crop output distributions.

Against this background, this paper uses data from the Third Integrated Household Survey (IHS3) 2010/11 and follows Galasso and Ravallion (2005) and Stifel and Alderman (2005) in analyzing the decentralized beneficiary targeting performance of FISP during the 2009/10 agricultural season. Since the program’s inception, this is the first comprehensive targeting assessment that is based on nationally-representative household survey data and that empirically documents the relative effectiveness of CBT, compared to targeting at higher levels of program administration, in reaching the intended beneficiaries. We follow alternative empirical approaches to the evaluation of the targeting performance for the purpose of testing the robustness of our findings.

In line with Galasso and Ravallion (2005), we estimate the national targeting coefficient as the difference between the share of the eligible population participating in the program (coverage) and the share of the non-eligible population participating in the program (leakage). Alternatively, we follow the approach of Stifel and Alderman (2005), account for differential transfer values across the beneficiary population, and define the national targeting coefficient as the difference between the average value of the input subsidy among the eligible population and the average value of the input subsidy among the non-eligible population, expressed as a share of the average value of the input subsidy among the eligible population.

> 2 The Second Integrated Household Survey (IHS2), and the Third Integrated Household survey (IHS3) inform the 2004/05 and 2010/11 poverty rates, respectively. The difference between the 2004/05 and 2010/11 national (and rural) absolute poverty rates is not statistically significant.

> 3 The World Bank Africa Region was the source of technical assistance provided to the Malawi National Statistical Office (NSO) for the official statistics on poverty and inequality in 2004/05 and 2010/11.

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