in factorial distribution may translate into a reduction of personal income disparities (and thus a negatively sloped GIC), as capital incomes may be more concentrated among the rich groups of the country.<sup>14</sup> Asset prices, including real estate prices, will likely drop sharply. Moreover, those who have borrowed in foreign currency suddenly experience a rise in real debt. Finally, transfers from the government are not distributionally neutral as some groups, for example retirees, receive proportionally more than others. A change in transfer amounts, and coverage, caused by budgetary difficulties can thus change the distribution.

Using the microsimulation model, it is possible to untangle these multiple effects and study their individual separate impacts. Consider first the adjustments in the labor market. Unskilled workers displaced from jobs in non‐tradable services are among those who lose the most: their welfare is almost halved; before the crisis the average consumption for a displaced worker was around 9,700 USD but with the oil shock it declined to around 6,000 USD.<sup>15</sup> Although the impact is clearly large for individual displaced workers, the consequences for the overall distribution depend on the number of displaced workers and whether they were initially concentrated in a specific part of the distribution. About 100,000 unskilled workers, around 0.1 percent of total employed workers, move back to agriculture sectors because of the shock. These are not randomly selected, as some will have a higher probability of moving than others. Nevertheless, as shown in Figure 2, they are coming from all parts of the distribution. They tend to be aged above 40 and, in most cases, males with at most junior secondary or secondary education, but they are not necessarily poorer.<sup>16</sup> For these reasons, the impact on the overall distribution is muted as shown by the GIC 1, the dashed line in Figure 3.<sup>17</sup>

> 14 Note, however, that this effect cannot be currently assessed given the data limitations of the available household survey where income from capital is not accurately measured.

> 15 Because of the segmentation, two separate wages are clearing the rural (agriculture) and urban (non‐agriculture) segments. The urban premium, i.e. the ratio of the wage of unskilled workers in non‐agriculture sectors over that of unskilled workers in agriculture is initially equal to 1.3. A labor migration function allows for some imperfect mobility across segments and this, together with sectoral demand for labor, determines the shift in the urban premium shown in Table 1.

> 16 Moving workers are identified using a probit estimation, as explained in the methodological section, see the Appendix for more details.

> 17 The line ‘GIC 1’ in the figure almost overlaps with the horizontal straight line that intercepts the vertical axis at ‐6.9. This horizontal line represents the average percentage welfare loss, i.e. the loss that everyone would incur were the shock uniformly distributed. The case represented by GIC 1 takes into account the losses of displaced unskilled workers, but the impact is minor, visible only because of the small blips on the GIC 1 line.

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