Modelling the impact of climate change on Nigeria’s agricultural sector: A nonlinear modelling approach

Climate change is posing increasing concerns to agricultural output and food security worldwide. This study explores the asymmetric influences of climatic conditions on Nigeria's agricultural output using yearly time series data from 1986 to 2022. This is based on the fact that climate change manifestations in the agriculture sector come in the form of an increase or decrease in climatic variables such as rainfall or temperature. Therefore, the use of an autoregressive distributed lag (ARDL) approach models the nonlinear relationships between temperature, rainfall and agricultural output. Rainfall and temperature indices capture climate variability relative to baseline levels. The model quantifies both immediate and lagged effects of increasing/decreasing rainfall and temperatures on sectoral performance. Cointegration tests confirm long-run equilibrium associations. The estimated asymmetric error correction model reveals rising temperatures and declining rainfall significantly hamper agricultural GDP in the short run. A 1% temperature increase reduces output by N5.1 billion whereas a 1% fall in rainfall lowers it by N9.7 billion. Long-run climate sensitivities also indicate rainfall variability critically constrains productivity. The negative rainfall coefficients agree with agronomic evidence that water stress and droughts diminish yields. Contrastingly, temperature impacts fade over time. Based on the findings of the study, it therefore recommends the development and promotion of heat and drought-resistant crop and livestock varieties to counter the negative impacts of rising temperatures and declining rainfall on agricultural productivity. Keywords: Climate Change, Agricultural Sector, Nonlinear, Autoregressive Distributed Lag (ARDL) Model.