includes a decline in supply and a decline in household demand for various basic goods. The simulated drop in household demand (except for food and hygiene goods), and public investment is 40 percent compared to the baseline scenario (pre-COVID scenario). The study shows the poverty rate rising to 19.2 percent from the current 15.2 percent, pulling an additional 475,000 individuals below the income poverty line. The economic recession, with a growth rate of -4.4 percent estimated for 2020, is estimated to elevate multidimensional poverty (estimated using a monetary approach) from 13.2 to 15.6 percent.

The UNICEF study showed that the two months of confinement decreed in Tunisia, during March and April 2020, led to a loss of 7% of household income. Poverty is estimated to have increased over the same period from 14% to 18.5%, or nearly half a million new poor. Poverty among children under the age of 18 years would increase from 19% to 25%, or nearly 900,000 poor children. Mitigation measures taken by the government were not found to have significantly countered the increase in poverty. Moreover, the same study shows that a universal allowance of 1 dinar per day (US$0.37) for each child not covered by social security would reduce child poverty by 5 percentage points.

<mark>Measuring real-time impacts of any crisis (financial, pandemics or economic slowdowns) on poverty and inequality is complicated in most countries because of delays in conducting detailed household surveys. As a result, a complementary tool for monitoring crisis impacts through administrative data (e.g., unemployment, school attendance, social benefit applications, etc.) is to assess the potential welfare impacts of crises through simulation tools that can then be used to simulate such impacts on poverty and inequality in short periods of time.</mark> In general, the literature showcases a wide variety of approaches used to quantify the distributional impacts of shocks.<sup>2</sup> In this paper, we follow a methodology similar to that employed by Ajwad, Aran, Azam and Hentschel (2013) and use a hybrid approach that combines the results of macroeconomic projections of a sectoral slowdown of the Tunisian economy over the whole year of 2020 with micro-simulation techniques. Unlike Ajwad, Aran, Azam and Hentschel (2013), however, we introduce the effect of price increase while doing the simulations. In this regard, <mark>our study is different from estimates of IFPRI and UNDP as these are based on CGE modeling and focus much more on the macroeconomic impact of the pandemic, and not so much on the distributional implications of the pandemic, which is the key focus of our simulation exercise.</mark> We focus on quantifying the magnitude of the impacts of COVID-19 on poverty and inequality in Tunisia through the labor income and consumption channels using the Tunisia household budget survey conducted in 2015 entitled _Enquête Nationale sur le Budget, la Consommation et le Niveau de Vie des Ménages_ (henceforth referred to as EBCNV 2015). The objective of this analysis is three-fold: first, to assess the pre-COVID situation in order to identify and profile the subgroups of population that are most vulnerable to getting infected by COVID-19 and impacted by the associated government measures; second, to simulate the impacts of COVID-19 on consumption, poverty and inequality based on sectoral growth performances over the whole year of 2020 and analyze the distribution of individuals expected to fall into poverty due to COVID-19; and finally, to simulate how the impacts would vary with or without mitigation measures adopted by the Tunisian government.<sup>3</sup>

> 2 Refer to Ajwad, Aran, Azam and Hentschel (2013) for a detailed review.

> 3 In terms of scope, we seek to estimate the impact of COVID and not the determinants of contamination in Tunisia by COVID-19, which remains out of scope.

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