Impact of Adopting Strategies to Cope with Climate Change on the Technical Efficiency of Wheat Farmers in Sistan Region-Iran

Abstract

The negative and destructive impact of climate change on the efficiency and productivity of agricultural inputs has been demonstrated in many regions of the world, particularly in arid and semi-arid areas. In this context, the adoption of innovative strategies to increase farmers' flexibility and adaptability to climate change has increased. Hence, understanding the impact of climate adaptation strategies on agricultural efficiency and yields is crucial. This study examined the effects of climate change adaptation strategies, input utilization, and external factors beyond farmers' control on technical efficiency using the Endogenous Modified Stochastic Frontier (EMSF) model. Data were collected from 265 questionnaires distributed among wheat farmers during the 2022-2023 cultivation period, using a stratified random sampling approach. The climate adaptation strategy index was formulated using the Principal Component Analysis (PCA) technique. The PCA revealed that changes in farm size (0.812), adaptation of conservation tillage (0.797), and adjustments in planting dates (0.619) were the most influential factors. Conversely, rainwater harvesting (0.219) and biofertilizer application (0.327) emerged as the adaptation strategies with the lowest factor loadings among farmers. In this study, the average technical efficiency of wheat farmers was calculated to be 82%. The model estimation results showed that labor input, chemical pesticides, chemical fertilizers, water, and machinery significantly and positively contribute to wheat production efficiency. Additionally, the implementation of climate adaptation strategies by farmers reduces technical inefficiency. Variables such as education level, farming experience, access to climate information, and access to credit also effectively reduce technical inefficiency.

Keywords

• logit regression
• principal components analysis
• socio-economic characteristics
• stochastic frontier model