dependency rate, and a dummy indicating if the household has income from remittances. Workers who are employed in Public Administration, Utilities, Health, or Extraterritorial Agencies are protected from facing any job losses or income changes.<sup>15</sup> For all workers that retain their jobs but are not employed in the protected sectors (Public Administration, Utilities, Health, and Extraterritorial Agencies), their labor incomes are adjusted up or down by a single scale factor equal to the percentage change in private consumption per capita of their specific country in 2020.

Next, projected changes in remittances by country are also included in the microsimulations. The percent change in remittances at the national level is applied as a direct percent change in the remittance income of any household that receives this income in the household survey. Changes in other sources of non-labor income different from remittances are not considered because data was not available for all countries. Once all three channels of transmission of the shock are incorporated, household per capita income is calculated by summing up the final income of each household member and dividing by the total number of household members.

We derive the distributional impacts of COVID-19 exploiting heterogeneities in household characteristics in the microdata. The first source of heterogeneity is the difference in the composition of income per-capita by income source. Different shares from each source of income will imply a different effect of the macroeconomic projections for each household. For example, households that do not receive remittances are not affected by the economic shock on remittances. Similarly, household incomes that are derived from pensions, capital income, and public transfers are not affected by the economic shock.

The second source of heterogeneity is the sociodemographic characteristics across households. Households differ by gender of the head of household, by education levels of members, by household composition, etc. Different characteristics will predict a different probability to suffer an unemployment shock, or for those who gain employment their different characteristics will predict different new incomes.

<mark>The third source of heterogeneity is the sector of employment, as job losses by sector vary, whether according to macroeconomic projections or actual available data. Each country faces different sectoral GDP projections or estimates. Workers in four sectors are protected from any shock:</mark> Public Administration, Utilities, Health, and Extraterritorial Agencies.

<mark>This macro-micro simulation model provides several advantages over other methodologies. First, it allows estimating distributional impacts and not only poverty impacts. Second, the use of actual employment data when available (as opposed to using projected employment levels based on past elasticities) partially addresses the potential concern of using past data to predict outcomes, especially during an unprecedented crisis with unique elements, such as the implementation of mobility restrictions.</mark> However, the model also faces some limitations. First, because of the unprecedented nature of the crisis, the estimation of employment probabilities based on pre-crisis household and individual characteristics may have limited predictive power. Second, the model is focused on average annual impacts to ensure consistency between the macro and micro projections. Consequently, it is

> 15 This procedure is not applied in South Africa where there is no detailed information on sector of employment.

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