The study investigates the impacts of climate change on global agricultural trade. It aims to analyze how temperature and precipitation, along with proposed macroeconomic factors such as agricultural productivity, tariff rate, exchange rate, price and technological innovations influence the worldwide trade balance of agricultural products.
The research employs the Panel Quantile ARDL model using a two-step ECM with a pooled means group (PMG) specification technique. Data spanning 23 years (2000–2022) from 166 countries is analyzed, incorporating climatic variables (temperature and precipitation) and economic factors to determine their effects on agricultural trade.
The study reveals that the average annual temperature significantly affects global agricultural trade, with a positive impact on exports up to a certain threshold, beyond which the relationship becomes detrimental. This indicates a nonlinear, inverted U-shaped relationship, where regions with moderate temperature increases can benefit, but excessive warming harms trade performance. Agricultural total factor productivity and technological innovations consistently enhance agricultural exports, with a stronger impact observed in countries with higher export-to-import ratios. On the other hand, factors like higher tariff rates and unfavorable relative world prices hinder trade competitiveness, especially in net-exporting regions. Precipitation levels alone were found to have an insignificant effect, suggesting that temperature is a more critical climatic variable influencing agricultural trade dynamics.
Policymakers should promote precision agriculture, boost productivity and adjust trade policies to strengthen export performance and food security. Given that climate and economic shocks affect net-exporting and net-importing regions differently, tailored strategies are essential to ensure trade resilience and climate equity.
This research uniquely applies a global-level quantitative analysis to agricultural trade and climate change, introducing a quadratic relationship between climatic variables and trade dynamics. It addresses gaps in existing literature by using extensive, real-world data rather than projections.
