کوثر قلی پور

Climatic conditions are key determinants of agricultural productivity, affecting both production levels and food security. This study aims to decompose total factor productivity growth in Iran’s agricultural sector by explicitly incorporating climatic variables. True Random Parameters Stochastic Production Frontier (TRP-SPF) model and the Maximum Likelihood method were used to estimate parameters in two scenarios, with and without climate variables which are evaluated by  and  models, respectively. The results showed that the variables of cultivated area, tractors, and technology have a positive and significant impact on production in both models, and the highest effect observed for cultivated area. In the  model, the variables of temperature and precipitation also made significant contributions to higher production. The average technical efficiency in the  model was estimated at 56.5%, and in the model with climatic variables, it decreased to 43.3%. These results confirmed the significant impact of climatic variables on production and suggested that agricultural output could be increased by more than 50% with the same resources and technology, minimizing inefficiency factors and the adverse effects of climatic variables. Decomposition of the Climatic Adjusted Total Factor Productivity (CATFP) index into four components, including climatic effects, scale effects, technical efficiency, and technological progress, revealed that climatic effects have the greatest impact, accounting for 26.4%, while the other three components contributed almost equally to improving productivity. Given the significant impact of climatic variables on agricultural productivity, this study recommends strategies adapting better with climatic conditions of different regions.