_Table 12: North Macedonia – Random loss shock_ <!-- Start of picture text --> Random Shock<br>Targeting → Household<br>Eligibility ↓<br>PMT Ex-<br>Means PMT Post<br>Means Perfect Imperfect ante or<br>Orginal Testing PMT Ex- PMT Post Shock or<br>Expansion Testing (Ex- Universal Loss Loss Perfect<br>Beneficiaries (Post Shock ante Shock Pefect Loss<br>Ante Poor) Indicator Indicator Loss<br>Poor) Indicator<br>Budget ↓ Indicator<br>(1a) (1b) (2) (3) (4) (5) (6) (7) (8) (9) (10)<br>Poverty Rate Pre-shock: 0.169; Post-shock: 0.256<br>(1) 0.09% GDP -0.014 -0.010 -0.019 -0.015 -0.013 -0.013 -0.014 -0.015 -0.016 -0.015 -0.015<br>(2) 1.0% GDP -0.042 -0.038 -0.081 -0.064 -0.024 -0.045 -0.038 -0.024 -0.028 -0.030 -0.030<br>Poverty Gap Sqr. Pre-shock: 3.523; Post-shock: 32.396<br>(1) 0.09% GDP -2.860 -5.666 -3.513 -3.817 -3.294 -2.926 -3.038 -3.533 -3.280 -3.660 -3.404<br>(2) 1.0% GDP -3.989 -13.951 -6.361 -12.499 -5.435 -5.478 -5.114 -7.668 -7.523 -7.428 -6.910<br>Gini Pre-shock: 0.330; Post-shock: 0.439<br>(1) 0.09% GDP -0.014 -0.017 -0.016 -0.015 -0.014 -0.014 -0.015 -0.016 -0.014 -0.016 -0.016<br>(2) 1.0% GDP -0.029 -0.045 -0.047 -0.050 -0.024 -0.038 -0.034 -0.030 -0.030 -0.032 -0.031<br>Coverage<br>(1) Average Transfer $ 1,409.8 $ 1,622.6 $ 344.3 $ 210.8 $ 44.2 $ 345.5 $ 210.9 $ 114.5 $ 156.1 $ 96.3 $ 86.6<br>(2) Average Transfer $ 15,041.3 $ 8,038.0 $ 3,673.7 $ 2,248.8 $ 471.3 $ 3,685.7 $ 2,249.8 $ 1,221.8 $ 1,646.1 $ 1,027.5 $ 924.3<br> (1) 15,457<br>Beneficiaries 17,790 72,839 118,990 567,743 72,601 118,937 219,010 160,677 260,437 289,491<br>(2) 33,290<br>Ex-ante poor 0.15 0.15 1.00 1.00 1.00 0.59 0.70 0.46 0.33 0.78 0.82<br>Ex-ante non-poor 0.01 0.05 0.00 0.11 1.00 0.08 0.15 0.38 0.28 0.42 0.47<br>Ex-ante Vulnerable 0.02 0.04 0.00 0.10 1.00 0.15 0.26 0.40 0.30 0.49 0.57<br>Post-shock poor 0.11 0.22 0.66 1.00 1.00 0.40 0.49 0.64 0.46 0.85 0.88<br><!-- End of picture text --> Note: impacts are color-coded from dark red (highest impacts) to dark blue (lowest impact). Not all households declare labor income.

# Targeting households vs. individuals

Our simulations provide an equal transfer to each beneficiary household, independent from the household composition. However, although more complex to implement, providing an equal transfer to each individual could in principle deliver higher poverty impacts, because often poorer households tend to be larger in size. We test this hypothesis below.

Differences in impacts reported in Table 13, Table 14 and Table 15 only partially support this hypothesis. In Albania, targeting individuals delivers higher impacts across shocks and coverage scenarios; in North Macedonia, targeting individuals delivers higher impacts for the baseline and proportional shocks, but not for the random loss shock; and in Moldova, targeting households delivers higher impacts across shocks. These country differences would call for a careful analysis of the country-specific demographic, and on how it interacts with the shock. However, in terms of magnitudes, differences appear to remain relatively small (less than a 10 percent difference in poverty impacts), so that in emergency responses efficiency and speed considerations should dictate the choice of covering households vs. individuals.

Note, also, that the choice of targeting households vs. individuals does not seem to significantly impact the rankings in beneficiary selection methods: increasing benefits of current beneficiaries, as well as universal transfers, remain suboptimal strategies, while using the PMT remains a solid option if shocks do not affect substantially welfare rankings, in which case introducing an indicator of who may have been affected by a shock delivers higher impacts. All the results discussed in the previous sections remain therefore valid.

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