Statistical investigation on the relationship between climate change, food availability, agricultural productivity, and economic expansion.

This study examined the connections between Benin's economic expansion, food production, agricultural productivity, and climate change. Using yearly statistics between 1961 and 2021, and R software version 4.2.2, we aim to: (1) Analyze how agricultural added value affects economic expansion; (2) analyze the effects of food production and temperature lagged values on economic growth; (3) investigate the different causality relationships between food production, temperature variation, agricultural added value and economic growth. To achieve these goals, statistical and econometric techniques such as Autoregressive Distributed Lags (ARDL) and the Toda-Yamamoto Granger causality framework were employed. The ARDL model verifies that there is a positive correlation between economic growth and the added value of agriculture based on empirical data. In addition, the Vector Autoregressive (VAR) model highlights the favorable impact of lagged food production values and the adverse effect of temperature fluctuations on economic growth. Granger causality analysis, employing the Toda-Yamamoto approach, unveils unidirectional links between food production and economic growth, as well as between temperature variation and agricultural added value. Interestingly, the study comes to the conclusion that there are no direct causal links between economic expansion and agricultural growth or between economic growth and temperature variance. Notably, bidirectional causality is established between livestock production and both economic growth and agricultural added value. These insights have significant implications for understanding climate change impacts on agriculture and suggest the need for adapted strategies to mitigate climate effects. Future research could focus on evaluating existing policies, exploring social and economic impacts, investigating market dynamics, and utilizing integrated assessment modeling to inform decision-making and foster sustainable economic growth in Benin's agricultural sector.