<mark>Africa. Projected annual growth rates in Private Consumption per capita from National Expenditure Accounts are provided by World Banks’ Macro Poverty Outlooks. Sectoral GDP growth projections in Agriculture, Industry, and Services are provided by the International Monetary Fund's World Economic Outlook Reports. Observed employment level for 2020 comes from the International Labor Organization for Brazil, Sri Lanka, and South Africa, from OECD for Türkiye and from government estimates for the Philippines. Projected changes in remittances by country are obtained from World Banks’s Migration and Remittances Data. Another input is a set of population projections for 2019 and 2020 based on the World Banks’ Macro Poverty</mark> Outlooks.

# **<mark>3.1 Methodology</mark>**

The model takes the household surveys microdata mentioned above as a starting point. The methodology then allows three main channels of transmission of the 2020 shock: through job losses, labor income changes, and non-labor (remittance) income changes.

Job losses or gains in Agriculture, Industry, and Services in 2020 are taken from observed employment levels from the ILO, OECD, or government estimates and compared to household survey data from previous years. When employment data is not available for a specific year, then job losses or gains by sector, by country, are estimated using elasticity estimates, such as those presented in Section 2. In that case, sectoral GDP growth projections (in Agriculture, Industry, and Services) are combined with the elasticities to provide employment projections.

These job losses/gains per sector then need to be imposed onto the household survey data. To match the new expected 2020 employment levels in each sector, the model has to determine which individuals in the base year household survey will lose (or gain) jobs to reach this new target. A Probit model, applied to each of the three sectors and by formal and informal workers, provides each person in each household survey a probability of employment: where _i_ is a person, _c_ is a country, _s_ is a sector (agriculture, industry, or services) and _f_ is the formality status (formal or informal). _X_ includes sex, age, education level, urban/rural, dependency rate, dummy for member working in public sector, and a dummy for remittances.<sup>14</sup> Workers are ranked by the predicted probability of employment, and those with the lowest employment probability are simulated to lose their job, until total job loss matches the employment projections (or actual values when known) for job loss by sector. For job gains, new workers are chosen among the unemployed according to the probability of being employed in that sector until total job gains match the employment projections by sector (or the actual values when known).

The second main channel of transmission of the 2020 shock is through labor income changes. Workers who are simulated to lose their job experience year-long unemployment and 100% cuts in labor income. In the case of job gains, a new labor income is estimated via a traditional Mincer equation, in which the logarithmic of income is regressed on sex, age, education level, urban/rural,

> 14 The indicator variable of urban area is available for Brazil, South Africa, Sri Lanka, and <mark>Türkiye.</mark>

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