Modeling short- and long-term climatic and non-climatic drivers of wheat yield in Somalia (1986–2019): Evidence from an ARDL approach

This study empirically investigates the short- and long-term impacts of climatic and non-climatic factors on wheat yield in Somalia from 1986 to 2019, a region facing severe food insecurity exacerbated by climate variability and prolonged conflict. Utilizing the Autoregressive Distributed Lag (ARDL) modeling approach, robust for small sample sizes and mixed orders of integration, we establish a significant long-run cointegrating relationship. Long-run analysis indicates a positive, albeit modest, impact of CO2 emissions on wheat yield, consistent with the CO2 fertilization effect, yet caution is warranted given the concurrent negative effects of other climatic stressors. Crucially, short-run results reveal that both increasing temperature and rainfall significantly reduce wheat yield, suggesting that erratic precipitation and extreme heat events pose immediate threats to production. Interestingly, political instability showed a counter-intuitive positive short-run coefficient, highlighting the complex and possibly localized dynamics of conflict on agriculture in Somalia that demand further nuanced investigation. This finding departs from conventional literature emphasizing conflict’s detrimental role in food systems. The study’s novel contribution lies in providing the first comprehensive quantitative analysis for Somalia, integrating a broad spectrum of drivers within a dynamic framework. This offers critical empirical evidence for policymakers and international partners, underscoring the urgent need for climate-smart agricultural adaptations, improved water management, and sustained peacebuilding efforts to build a resilient and food-secure future for Somalia.