<![CDATA[Purpose: This study aims to examine the relationship between government spending and agricultural output in Zimbabwe, while also evaluating the effects of macroeconomic variables such as inflation, carbon emissions, rainfall, population growth, and temperature on agricultural output. Methods: The Autoregressive Distributed Lag (ARDL) model was employed using time-series data from 1980 to 2022. Data were sourced from the World Bank and the IMF. Diagnostic tests, including stationarity checks, cointegration analysis, and stability assessments (CUSUM and CUSUMSQ), were conducted to ensure the robustness of the model. Results: The findings reveal significant short- and long-run relationships between government spending and agricultural output. Government expenditure, rainfall, and population positively influenced agricultural productivity, whereas inflation and carbon emissions had a negative effect. The ARDL model explains 95% of the variation in agricultural output, indicating a strong model fit and predictive power. Conclusion: The Autoregressive Distributed Lag (ARDL) model demonstrated a positive relationship between government spending and agricultural output in both the short and long terms. Based on the results, the study concluded that sustained government support through subsidies, grants, and other resources has the potential to enhance agricultural productivity in Zimbabwe over time. Limitations: The study is limited by the availability and quality of historical data, which may constrain the precision of certain estimates. Contributions: This research assists the Ministry of Lands, Agriculture, Fisheries, Water, and Rural Development in developing targeted interventions to enhance the performance and resilience of Zimbabwe's farmers and agribusinesses. The findings can help the Reserve Bank of Zimbabwe align its policies with the evolving needs of farmers, especially post-COVID-19 and amid the Russia-Ukraine conflict.]]>
