The effects of renewable energy and agriculture on 〖CO〗_2 emissions in Morocco: An approach to S-VAR modelling

Abstract

This paper aims to assess the impact of agriculture and renewable energy on  emission in Morocco during the period 1990 - 2020. In this regard, using R Software, the Structural Vector Autoregressive model (SVAR) is estimated to identify the short-run relationship that links our variables. The causality analysis as defined by Granger shows the existence of a two-way causal relationship between agriculture, renewable energy and  emissions. The results obtained, from the impulse response function analysis shows that agriculture increases  emissions while renewable energy reduces it. Therefore, the Government of Morocco should encourage the use of renewable energy and strengthen the management of agriculture to curb climate change and achieve the goal of sustainable development.