Desalination for Food Security in Tunisia: Harnessing Renewable Energy to Address Water Scarcity and Climate Change by Using ARDL Approach and VECM Technical

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This study employs the Autoregressive Distributed Lag (ARDL) model to investigate the short-term and long-term effects of independent variables, including Agricultural output (A), Renewable energy consumption (REC), Non-renewable energy consumption (NREC), CO2E emissions, Climate change (CC) and Financial (FD), on food security (FS) in Tunisia during the 1990–2023 period. After confirming the stationarity of the variables and the existence of long-run cointegration, the ARDL model was employed. The short-term ARDL estimates revealed mixed results. While some variables had positive effects, others exhibited negative influences on FS. For instance, A positively impacted FS, while REC, NREC, CO2E, CC, and FD had negative effects. The long-term ARDL analysis indicates that A, NREC, CC, and FD have significant effects on FS. A and NREC positively influence FS, while CC and FD have negative impacts. REC’s effect on FS is uncertain due to its marginal significance, and CO2E shows no significant relationship with FS in the long run. This study provides valuable insights into the short-term and long-term relationships between FS and its influencing factors. The findings can inform policy decisions and future research in this area.