Sustainable food production, forest biodiversity and mineral pricing: Interconnected global issues

摘要

The food production challenges for growing population are the global issue that is highly proliferated in the United Nation Sustainable development Goal (SDG-12) with responsible consumption and production. The goal further emphasized the need to reduce global food waste at retailers, consumers, production, and supply chains level by 2030. This study is in line with the SDG-12 to analyze the relationship between sustainable food production, forest biodiversity, and mineral pricing by using world aggregated data for a period of 1970-2018. The study used different cointegrating regressions, including Fully Modified OLS (FMOLS), Dynamic OLS (DOLS), Canonical Cointegrating Regression (CCR) and ARDL-Bounds testing approach for robust inferences. The results show that forest biodiversity increases carbon emissions due to inadequate land use planning and animal rich biodiversity, while food production is merely carbon associated that supported 'food production footprints' at global scale. Mineral rents and energy demand both increases carbon emissions that substantiate the 'mineral resource curse' hypothesis and energy associated global emissions. Although the result is not supported the `pollution haven' hypothesis and population associated emissions, however, there is a strong evidence of `race-to-the-bottom' hypothesis at global scale. The simulation results suggested that forest biodiversity, food prices, mineral rents, population density, and combustibles and renewables waste will negatively affect the global environment in the form of high mass carbon emissions that sabotaged the United Nation sustainable development agenda. The study emphasized the need to adopt sustainable policy instruments, including advancement in the clean energy resources, cleaner production technologies, sustainable resource management, and conservation of forest biodiversity, which will be helpful to reduce carbon abatement costs at worldwide.