Policy Package 1. Level the Playing Field and the Opportunity for Human Development in Lagging Areas
are below the poverty line, just 2.7 percent receive the cash transfer. The lower enrollment rates in Kirkuk and Baghdad, however, do reflect those governorates’ lower poverty incidence. Jordan’s National Aid Fund (NAF) enforces its categorical targeting through home visits by NAF officers to verify eligibility, as well as reviewing the statements and documents provided (World Bank 2007d). Under this design, the geographic distribution of social transfers maps more closely onto the spatial distribution of poverty. Per capita income under the category “other government transfers” (i.e., not social security benefits or pensions) was JD 402 in 2006 in rural areas of Jordan compared with JD 248 in urban areas. Residents of the Amman governorate received JD 194, significantly less than the urban average.22 Tunisia’s Fund of National Solidarity (FSN23) shows how needs-based targeting serves as spatial targeting. The FSN was created in 1992 to finance projects too small to fit into sector ministries’ normal service packages. A national committee used objective criteria to select 1,811 project zones, and local administrations identified projects. The result is that most FSN expenditure takes place in the country’s lagging western and southern areas. Someone’s chance of living in an FSN zone is 13 to 17 times higher than the national average in the lagging regions of Le Kef and Gabès.
Targeting Is Key Better targeting and coverage will therefore make MENA’s SSN programs more powerful instruments for the reduction of spatial disparities. A number of approaches could improve coverage and targeting and enhance programs’ contribution to spatial convergence in living standards. If measuring people’s incomes directly (“means testing”) is difficult and costly, there are proven alternative targeting approaches. • Geographical targeting distributes benefits to people who are identified as likely to be poor or vulnerable on the basis of where they live. This targeting mechanism is cheap and administratively simple, and especially efficient when poverty is highly concentrated and correlated spatially with observable social indicators. The smaller the geographical unit of measurement, the lower the risk of including the nonpoor or excluding the poor. In the Syrian Arab Republic, for example, targeting a transfer by governorate might reduce the national poverty rate by 1.8 percentage points, whereas targeting the same budget by region would only achieve a reduction of 0.6 percentage points. Poverty mapping is, therefore, frequently used to identify target areas. A simulation of geographical targeting using Morocco’s
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