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Conditional Cash Transfer Program in the Philippines: Is It Reaching ...

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unprecedented pace? How long can we susta<strong>in</strong> such a huge amount of spend<strong>in</strong>g <strong>in</strong> order for <strong>the</strong>program to have an impact of <strong>the</strong> poor’s lives? Based on o<strong>the</strong>r countries’ experiences, <strong>the</strong> CCTshould be backed by a state policy so that fund<strong>in</strong>g need not rely on external sources as it needs tobe susta<strong>in</strong>ed for a long time. How much more should we borrow to f<strong>in</strong>ance a program this big ascale? <strong>Is</strong> <strong>the</strong>re any more fiscal space <strong>in</strong> which we can accommodate this given <strong>the</strong> already tightbudget that we have?RecommendationsThe conditional cash transfer program, <strong>the</strong> 4Ps, is <strong>in</strong> its fifth year. The current size of <strong>the</strong>4Ps is already significant with 2.3 million family beneficiaries, given that <strong>the</strong> number of poorfamilies is 3.9 million. Before fur<strong>the</strong>r scal<strong>in</strong>g up, it is essential to assess <strong>the</strong> implementation of<strong>the</strong> Pantawid Pamilya Pilip<strong>in</strong>o <strong>Program</strong> (4Ps) and address <strong>the</strong> concerns about <strong>the</strong> program toensure that <strong>the</strong> extremely poor experience <strong>the</strong> maximum benefits from <strong>the</strong> program. The samewas suggested by Llanto (2008). He noted that it is important to establish empirical evidence that<strong>the</strong> 4Ps program impacts human capital outcomes before contemplat<strong>in</strong>g any rapid expansion.The 4Ps be<strong>in</strong>g implemented on a phased model allows for this generation of empirical evidenceto test crucial program components such as target<strong>in</strong>g and monitor<strong>in</strong>g system.More importantly, it should reconsider how it identifies <strong>the</strong> extremely poor. Target<strong>in</strong>g <strong>the</strong>chronic poor would provide better focus to <strong>the</strong> program. Moreover, to properly identify <strong>the</strong>extremely poor, one needs to utilize more than one reference period to account for <strong>the</strong>movements <strong>in</strong> and out of poverty. Data show that majority of <strong>the</strong> poor <strong>in</strong> 2009 are transient poor,only 47 percent are considered chronic poor (Reyes, et.al. 2011). This important <strong>in</strong>formation wasextracted us<strong>in</strong>g longitud<strong>in</strong>al data obta<strong>in</strong>ed from track<strong>in</strong>g <strong>the</strong> same households for several years.The f<strong>in</strong>d<strong>in</strong>g evidently shows that target<strong>in</strong>g <strong>the</strong> poor based on a s<strong>in</strong>gle reference period andtreat<strong>in</strong>g <strong>the</strong>m as if <strong>the</strong>y are all <strong>the</strong> same would be too narrow a strategy that will not tacklepoverty successfully. <strong>Program</strong>s have to be designed to comprehensively take <strong>in</strong>to account <strong>the</strong>differences among <strong>the</strong> needs of different segments of <strong>the</strong> poor.Moreover, it might be good to review <strong>the</strong> strategy of cover<strong>in</strong>g selected barangays <strong>in</strong> someof <strong>the</strong> municipalities. Limit<strong>in</strong>g coverage to “pockets of poverty” <strong>in</strong> areas where poverty<strong>in</strong>cidence is high based on 2003 small area estimates may lead to significant exclusion. Only 25percent, or 404 municipalities and cities, have poverty <strong>in</strong>cidence greater than or equal to 50percent. The rest, represent<strong>in</strong>g 3 out of every 4 municipality and city, have poverty <strong>in</strong>cidenceless than 50 percent. Limit<strong>in</strong>g survey area to “poorest municipalities” to reduce data collectioncosts may not be <strong>the</strong> most appropriate way s<strong>in</strong>ce this will lead to exclusion of some of <strong>the</strong>extremely poor. O<strong>the</strong>r options such as us<strong>in</strong>g CBMS data already collected by <strong>the</strong> localgovernment units or partner<strong>in</strong>g with local government units <strong>in</strong> implement<strong>in</strong>g CBMS may be a12

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