• Energy Research

The adoption of Sustainable Development Goals (SDG) in 2015 shifted the attention towards sustainability-related concerns in both developing and developed counties. The aim of this paper is to examine how agricultural productivity – a key driver in achieving many of these SDGs – is affected by carbon emissions, deforestation, renewable energy consumption, natural resources, and regional integration for the ten Association of Southeast Asian Nations (ASEAN) countries. Using the Mean Group (MG) class estimators, able to tackle the cross-sectional dependence in the data, empirical findings reveal that environmental degradation (in the form of CO2 emissions) reduces agricultural productivity in the region. Both the forest area and natural resource variables negatively affect the productivity of the agricultural sector, while the use of renewable energy sources positively contributes to the agricultural sector. However, despite being one of the highest integrated regions in the world, regional integration among the ASEAN members does not boost their agricultural productivity. The causality tests confirm the existence of bidirectional causality between agricultural productivity and renewable energy consumption, and unidirectional causality across a few other variables. Accordingly, the study provides policy recommendations for the governments of ASEAN economies on improving the environmental performance of agriculture and achieving the SDGs by 2030.

Agriculture and the food system emit a considerable amount of Greenhouse Gas (GHG) emissions in the atmosphere. Hence, current researchers, policymakers, and other stakeholders are calling for improving the environmental performance of agriculture. This study utilizes the countries of The Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation (BIMSTEC) to investigate the effect of agriculture value-added, pesticide use, renewable energy adoption, human capital, and economic growth on greenhouse gas emissions. The moderation effect of renewable energy use and human capital is also introduced to see whether they can offset agriculture's emissions in these BIMSTEC economies. Having reported a state-of-the-art literature review, the econometric procedure applies the second-generation unit root tests, panel cointegration and panel quantile regression for three preferred model specifications. The result from the Panel quantile regression method reveals a U-shaped relationship between agriculture value-added and greenhouse gas emissions, suggesting the significance of a small farming system. Human capital has a negative effect, whereas pesticide use has a positive effect on greenhouse gas emissions. Furthermore, the moderation effect of human capital and pesticide use suggests that human capital is not significant enough to offset the effect of pesticide use on the greenhouse gas emissions, whereas the interaction of renewable and pesticide use suggests that renewable energy adoption in the agriculture sector can mitigate the effect of pesticide use on GHG emissions. Finally, the conclusions of the study support the achievement of few sustainable development goals.