Green growth of cereal food production under the constraints of agricultural carbon emissions: A new insights from ARDL and VECM models

Abstract The aim of this study is to investigate the green growth of cereal food production under the constraints of agricultural carbon emissions and area sown. A qualitative time-series data from 1985 to 2018 was used to analyze the Autoregressive distributed lag (ARDL), vector error correction model (VECM), and Novel dynamic ARDL models. The empirical results of the long-run and short-run nexus show that the increasing in area sown and food production index resulting to increase cereal food production. While agricultural carbon emission only confirms short-run significant negative effect and predicts that the decreasing agricultural carbon emissions will support to the increase of cereal food production. The novel dynamic ARDL model revealed that in long-run 10% positive change in agricultural carbon emission decreases cereal food production and a 10% decrease in agricultural carbon emission will steadily increase cereal food production. Besides, the VECM model results predict that bidirectional Granger causality runs from area sown and food production index to the cereal food production while unidirectional Granger causality exists from cereal food production to agricultural carbon emissions. Overall, conclusion the agricultural carbon emissions and area sown are accountable for reducing cereal food productivity. By switching from chemical fertilizers to organic fertilizers, farmers can enhance farm productivity in a healthy and sustainable environment.