نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار، گروه اقتصاد کشاورزی، دانشکده مهندسی زراعی، دانشگاه علوم کشاورزی و منابع طبیعی، ساری، ایران.
2 دکترا، گروه اقتصاد کشاورزی، دانشکده مهندسی زراعی، دانشگاه علوم کشاورزی و منابع طبیعی، ساری، ایران.
3 دانشجوی دکترا، گروهاقتصاد کشاورزی، دانشکده مهندسی زراعی، دانشگاه علوم کشاورزی و منابع طبیعی، ساری، ایران.
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Food security, as one of the main pillars of sustainable development, plays a fundamental role in maintaining the health of society, and economic stability. Therefore, it is essential to pay attention to the factors affecting food security and monitor its future changes. The present study, relying on recurrent neural network (RNN) models, autocorrelation with explanatory lag (ARDL) model, rolling window regression and time series data during the years 1961-2022, estimated the link between the food production index, agricultural imports and exports, consumer price index and agricultural value added and predicted the path of the variables until 2040. Correlation analysis based on neural network and ARDL estimation showed that import growth is in line with the improvement of the food security index and export growth is associated with its weakening, while agricultural value added has a positive effect on the food security index and long-term inflation has a negative effect. The results of the forecast and the baseline, optimistic and pessimistic scenarios showed that strengthening agriculture, controlling inflation and managing imports and exports are the conditions for sustainable food security up to the desired horizon. Also, the results showed that the model used provides an efficient framework for online monitoring and early warning of food security in Iran. It is suggested that policies be set in such a way that imports are accompanied by comprehensive planning. Exports should also be in such a way that the foreign exchange benefits obtained from them are used for the benefit of food security.
کلیدواژهها [English]