Impacts of the 2014-16 drop in oil prices on child poverty in Chad and options for a policy response: Analysis using a recursive dynamic CGE model with fully integrated microsimulations

In 2003, Chad became a producer and exporter of crude oil. Its annual real GDP growth, negative in 1999 and 2000, became positive again with the beginning of oil related activities and reached a peak of 33.63% in 2004. However, the drastic drop in oil prices of around 80% between June 2014 and January 2016, have heavily impeded growth and poverty alleviation efforts in Chad. This is while, child poverty headcount ratio is already very high and above the national average. This study therefore aims to assess the impacts of this crisis on child monetary poverty, and to explore some policy responses that would specifically reduce poverty amongst children. To this end, a recursive dynamic Computable General Equilibrium model is used, with fully integrated microsimulations. It results from the study that, in the event the crisis had not occurred, the poverty headcount ratio for children would have dropped considerably. With the crisis, for the whole population, additional number of poor reached 1,146,025 individuals in 2018 and increased to 1,506,177 people in 2025: an increase of 23.1% and 28.8%, respectively. The share of children in this additional number is between 55 and 59% throughout the considered period: i.e. 628,427 more poor children in 2018 and 884,528 in 2025. Five response options are simulated: first, the pilot social safety nets implemented in 2018. It consists in allocating cash transfers to some poor households in three regions of the country. The other four options are exploratory policies, including cancellation of tariffs or VAT on food, and two options to broaden the scope of social safety nets to all households housing poor children. It arises from simulations that the latter two options are most effective and efficient for alleviating poverty. The study therefore suggests some modalities to implement such a program.