Development of an Integrated Econometric-Atmospheric Model for Forecasting Climate Impacts on Nigerian Agriculture and Food Security: Divergent Zone-Specific Trends and Yield Declines
Keywords:
Climate change, Agricultural Forecasting, Econometric Modeling, Food Security, Nigeria, Agro-Ecological Zones, Integrated AssessmentAbstract
Climate change poses an escalating threat to Nigeria's agricultural systems and food security, yet existing forecasting approaches lack integration of atmospheric and economic dimensions at localized scales. This study developed and applied an integrated econometric-atmospheric model to forecast climate change impacts on agriculture and food security across Nigeria's four major agro-ecological zones (Sudan Savanna, Northern Guinea Savanna, Southern Guinea Savanna, and Forest zone) for 2025–2050. The research employed Panel ARDL, Panel VAR, and fixed effects regression, combined with SARIMA models and downscaled CMIP6 projections under RCP4.5 and RCP8.5. Historical climate and agricultural data (1990–2025) were analyzed to generate zone-specific forecasts. Results revealed divergent climate trends: the Sudan Savanna is warming at 0.42°C per decade with declining rainfall (-12.4 mm/decade); the Northern Guinea Savanna is warming at 0.38°C per decade with declining rainfall (-8.6 mm/decade); the Southern Guinea Savanna is warming at 0.31°C per decade with increasing rainfall (+15.8 mm/decade); and the Forest zone is warming at 0.28°C per decade with increasing rainfall (+22.4 mm/decade). Temperature increases showed significant negative effects on yields across all zones (p < 0.001). Climate shocks explain 18.8–38.6 percent of forecast error variance. Under RCP8.5 by 2050, maize yields in the Northern Guinea Savanna are projected to decline by 20.8 percent, prices to increase by 47.7 percent, and household purchasing power to decline by 34.4 percent. The integrated model achieved superior forecast accuracy (MAPE of 8.4 percent for yields, 5.8 percent for prices) compared to models without climate forecasts (p < 0.001). The study concludes that temperature increase is the dominant variable affecting crop yields, requiring urgent adaptation including irrigation expansion, climate-informed extension services, and social protection programs targeting northern hotspots.
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Copyright (c) 2026 Tope Rufus Oziegbe, Rufus Temidayo Akinnubi

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