authorities, and complicated registration procedures. The CWG’s MPCA programs have been instrumental in reaching the vulnerable households in areas most affected by the conflict and where the SSN coverage remains limited. Over a million conflict-affected households have been reached with the MPCA since the start of the conflict with ISIS. The short-term MPCA aid programs, however, will require a more permanent solution and eventual integration in some form with the government’s SSN programs to continue reaching the vulnerable households affected by the conflict.

As an initial step, this paper proposes an analytical pseudo-PMT (PPMT) tool to bridge the targeting differences between the government SP program and the MPCA. The PPMT uses proxies that are common to both the humanitarian and the government CTP targeting formulas and provides each MCNA beneficiary’s probability of being eligible for the government’s CT program under different expansion scenarios. When applied to the existing humanitarian beneficiary database, the results suggest a strong source of referrals to the government’s SP system. Under a smaller program, targeting the poorest 15 or 18 percent nationally, between 24 to 54 percent of the existing humanitarian database would be available for referral to the government’s SSN programs with 90 to 50 percent (high and low) referral confidence levels. For a large program such as targeting the poorest 35 percent nationally, the referral rates increase to 40 to 73 percent for high and low referral confidence levels. Given a large proportion of the humanitarian database that could potentially be referred to MoLSA’s social protection programs, the results suggest a sequencing of smaller numbers with a high degree of likelihood to qualify could be referred first, with larger numbers being referred later when budgets expand.

The MCNA households that are likely to be referred first, i.e., those with a high degree of likelihood (90 percent) under a smaller program expansion (targeting the poorest 18 percent nationally), are noticeable across several demographic and economic indicators. Majority of the early referrals are likely to come from urban centers such as Mosul, Tikrit and Ramadi with large concentration of IDPs and rural areas that experienced the conflict most - Shirqat, Tel Afar, and Baiji. Significant number of these households are headed by a female member (30 percent) and appear to have larger household sizes (8 members on average). They are also characterized by significant prevalence of disability and chronic illness among the head of the household. High unemployment, low income and expenditures but relatively high level of debt are other recognized characteristics among this group.<sup>15</sup> This initial analysis, however, has been based on probabilistic estimates from two different sources of data. Moreover, just because a household is likely to be eligible does not necessarily mean they are willing to be referred. Households with perceived ISIS affiliation may mean some households do not want to enter the formal government social protection system.

To confirm the promising referral percentages from the desk analysis, but also determine the percentage of likely households who are also willing to be referred, a light field test is proposed. Under this test, the same households would be asked the full set of questions required to construct full MoLSA and VM/MCNA scores. This would provide stronger evidence of the apparent overlap between the two targeting systems. Moreover, willingness and perception questions could be asked to assess the combination of likely eligibility and willingness to be referred, which will ultimately determine how many potential MoLSA beneficiaries could come from the humanitarian database.

> 15 While the focus of the paper has been how close the PPMT scores are to the full PMT scores and how to overcome the difference, a more flexible ranking approach discussed in Annex D can be another alternative.

21