Taxing CO2 emissions and its ancillary health benefits: a computable general equilibrium analysis for Tunisia

Abstract

Since the middle of the last century, Tunisia has embarked on an ambitious trade reform program aimed at improving its integration in the world economy, boosting growth through valorizing comparative advantages, and reducing unemployment among its population. However, and despite the positive role that trade may play in improving growth through better allocation of domestic resources and lower costs of imported equipments and raw materials, the risk is to amplify output in sectors intensive in energy in a country where energy is still subsidized. Introducing pollution abatement taxation has been suggested as a way to achieve ancillary benefits from reduced local air toxics. The highest level of local air pollution is found in heavily populated cities where labor is concentrated and where labor health is believed to have been significantly impacted. The objective of this paper is to address this important issue. It identifies the optimal and ‘no regrets’ pollution abatement tax on a net welfare function, which integrates both net health benefits and adjustment costs. The paper uses a Dynamic Computable General Equilibrium (CGE) model for the assessment that allows the health benefits to feed back into the economy. A health effects sub-model takes the local air emissions output from the CGE model and assesses the implications for ambient air concentration levels and health effects. The results suggest an ‘optimal’ abatement rate in 2020 of around 25% of CO2 reduction compared with the baseline 2020 emissions. However, the most significant impact concerns the relatively small aggregate cost of pollution abatement in terms of forgone real average growth rate of GDP between 2010 and 2020 for the trade scenario with ‘optimal’ climate policy. Finally, the major consequence of pollution abatement policies is the reduction of production generated by polluting activities against a higher production of less-polluting activities.