Chapter 6: Tunisia: Poorest Households Are the Most Vulnerable 159
and location. The poor, who are more likely to be living in overcrowded conditions, and those with chronic diseases are at greater risk to contract the infection, while those without health insurance (largely the poor and those in informal sectors) are faced with a greater inability to access health care. Those who spend more on food as a share of their consumption expenditure—notably, the poor—will be most affected by price shocks. And workers in tourism and construction are the most vulnerable. Against this backdrop, our analysis combines the labor shock and price shock induced by COVID-19 simultaneously and simulates postpandemic consumption. Our estimates indicate that poverty is expected to increase by 50 percent from the pre-COVID-19 levels under the optimistic scenario and to almost double under the pessimistic scenario, thus reversing the trend of declining poverty over the past decade. At the same time, inequality is expected to increase slightly. In fact, our simulations show that households with per capita consumption in the poorest 20 percent of the distribution will be hit the hardest. Using the postcrisis welfare distribution, this analysis also helps identify the individuals who are expected to fall into poverty as a result of COVID-19. They are likely to disproportionately reside in the Center West and South East regions, and they are more likely to be women, live in large households, be employed without contracts, and lack access to health care. While transfer measures enacted by the government targeted at the poor and the most vulnerable could mitigate some of these negative effects, setbacks to welfare outcomes will persist. These findings underscore that it is extremely important to ensure that economic growth benefits the poor and the vulnerable—and enacting measures to protect this large, vulnerable subgroup should be a top priority for the government.
Notes 1.
In terms of this chapter’s scope, we seek to estimate the impact of COVID-19 and not the determinants of contamination in Tunisia by COVID-19. 2. Refer to Ajwad et al. (2013) for a detailed review. 3. According to the National Institute of Statistics (INS), the national rate translates to 15.2 percent using the 2015 data. Given this, we first update the 2015 data to create a new distribution of consumption and observe a preCOVID-19 (2019) poverty rate. We then use growth projections to identify the distribution of postpandemic consumption and assess impacts on poverty and inequality.
