Our paper proceeds as follows. Section 2 provides a comprehensive description of pre-crisis situation in Tunisia including trends in poverty, composition of labor markets and individual and household characteristics that make the Tunisian population more susceptible to COVID-19. Section 3 describes the data and the empirical methodology to simulate the impacts of COVID-19 on labor income and consumption. It also discusses the magnitude of impacts in the presence of mitigation measures. Section 4 presents our results under two scenarios. Section 5 concludes and provides policy implications of our results.

We rely on the latest round of data available of the national household survey or EBCNV implemented in 2015. EBCNV 2015 is a quinquennial survey which is the eight survey of its kind carried out by the National Institute of Statistics. The seven preceding surveys were carried out in 1968, 1975, 1980, 1985, 1990, 1995, and 2005. The realization of these surveys coincides with the preparatory work for the Development Plans. The survey on the budget, consumption and household standard of living in 2015 covers data on Household expenditure and acquisitions during the survey period, Consumption food and nutritional situation of households, and Household access to community health and education services. While the National Institute of Statistics (INS) has conducted a household budget survey more recently in 2019, the official estimates are not yet published, and the data are not yet widely available and do not collect the consumption data.

# **2. Pre-Crisis Situation: Poverty and Labor Markets**

Poverty had declined in Tunisia in the pre-COVID-19 period, but significant disparities remained. The poverty headcount rate declined between 2010 and 2015 from 20.5 to 15.2 percent in the country as a whole (Figure 2, panel A). Nevertheless, significant disparities existed between urban and rural areas, and between coastal regions (where most economic activities are concentrated) and interior regions. Extreme poverty is predominantly a rural phenomenon. Moreover, a considerable share of the population in rural and lagging areas remains vulnerable<sup>4</sup> to fall back into poverty. About 49 percent of rural residents were vulnerable in 2015 as opposed to 21 percent of urban residents. In fact, the vulnerability in the poorest regions remains very high despite the decrease in poverty. For example, half of the population in the Central West region is vulnerable compared to one tenth in the Grand Tunis area.

Overall, economic growth has been pro-poor but the decline in inequality was rather modest. Inequality, as measured by the Gini coefficient, has declined over time, especially between 2010 and 2015 from 40.4 to 36.5. Figure 2, panel B shows the growth incidence curve (GIC) for Tunisia, which displays the annualized increase in consumption per capita by percentile of the consumption distribution (the left side of the horizontal axes is the poorest and the right side is the richest). It is observed that the poorest observed

> 4 We use the methodology in Atamanov and Lopez-Acevedo (2018) to examine the level and trend of vulnerability in Tunisia between 2000 and 2015. Using this methodology, the poverty and vulnerability lines in 2015 defined below are 2.7 TND per day and 6.1 TND per day, respectively, which translates into 986 TND per year and 2,227 TND per year. Note that the official extreme and upper poverty lines stood at 1,035 TND per year and 1,706 TND per year in 2015, respectively. The population with consumption per capita below US$3.4 2011 PPP per day per capita is defined as poor. The population with consumption per capita between US$3.4-US$7.7 2011 PPP per day can be defined as vulnerable. The population with consumption per capita between US$7.7-US$15.8 2011 PPP per day can be defined as secure. And the population with consumption above US$15.8 2011 PPP per day belongs to the middle class.

5