capita consumption levels (from lowest to highest), group them into consumption percentiles for the business as usual and crises scenarios; and plot the annual growth rate of per capita household consumption by percentile between scenarios. We perform this exercise for all households, as well as for specific groups. Each IIC allows us to compare percentage consumption gains or losses across households within the group. Comparisons across groups (e.g. households in KR‐I and South regions) are not straightforward. For instance, given that on average consumption levels are higher in KR‐I than in the South, a household in the 40th percentile of the KR‐I consumption distribution is quite likely to significantly be better off than the 40<sup>th</sup> percentile household in the consumption distribution of the South.

The projected economic decline between business as usual and crises scenarios is expected to translate into lower consumption across the entire distribution and in all regions. This is shown by Figure 4 where Impact Incidence Curves are all below zero. In other words, across the distribution, and in each region, households are estimated to have experienced a negative welfare impact – there were no winners, as the entire distribution suffered welfare losses. However, the reduction would not has been proportionally distributed across deciles and this affects inequality as mentioned before. Per capita household consumption losses are largest among those households at the bottom of the distribution (10th to 40th percentile), with an average loss of almost 16% between business as usual and crises. Households at the very bottom ‐1st to 10th percentiles‐ have been less fortunate than the rest by suffering a 21.5% reduction in welfare.

Consumption losses are estimated to be higher in IS‐affected governorates and KR‐I than other regions across the entire distribution. For instance, the average impact on a household living in an IS‐affected governorate would have been more than double that of the total country (‐27 % vs. ‐13%) and in KR‐I this would have been 5 percentage points higher ‐i.e. ‐18%.

# **Incidence of losses and income mobility**

The IICs provide information about consumption gains or losses incurred by the average household within each percentile of the consumption distribution, and are thus useful in identifying which consumption groups experience relatively larger or smaller changes. However, they can hide a significant amount of heterogeneity in the absolute size of impacts, even among households with very similar baseline or initial per capita household consumption levels.

An alternative is to examine the size of the income change experienced by the households in each consumption group. We do this using matrices constructed by deciles of per capita consumption, keeping the upper and lower limits of each decile fixed at the business as usual consumption levels. In other words, we examine how many households within relative narrowly‐defined groups (i.e. business as usual per capita household consumption deciles) experience a consumption gain or loss between business as usual and crises scenario in 2014 large enough to push them up or down by one consumption decile or more, where consumption deciles are defined on the basis of the business as usual distribution.

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