Estimation of Economic Efficiency of Maize Growers in Northern Khyber Pakhtunkhwa, Pakistan

This study evaluates the economic efficiency of maize growers in Northern Khyber Pakhtunkhwa, Pakistan, with a focus on the two districts of Swat and Buner. A total of 100 maize farmers (50 from each district) were selected using a multi-stage random sampling technique. Primary data were collected through a structured interview schedule. The analysis employed Cobb-Douglas type stochastic production and cost frontier models, estimated using Maximum Likelihood Estimation (MLE) in Stata software. The main production inputs included land, labor, seed, tractor hours, irrigation, urea, DAP, farmyard manure (FYM), and pesticides. Socioeconomic variables, including age, education, farming experience, family size, tenure status, off-farm income, and distance from farm to home, were considered in the inefficiency model. Additionally, climate risk variables — average maximum and minimum temperatures, and rainfall — were analyzed for their impact on technical efficiency. Results revealed that average yield and net return per acre were 680 kg and Rs. 22,437 in Swat, and 638 kg and Rs. 19,413 in Buner. Seed rate, labor, urea, DAP, FYM, and pesticides had significant positive effects on maize output. In contrast, cultivated area, tractor use, and irrigation were statistically insignificant due to their uniform use across terraced and hilly regions. The mean technical efficiency was 0.57, indicating that yields could be improved by 41% using current inputs more effectively. Among climate factors, higher maximum temperatures improved efficiency, while minimum temperatures increased inefficiency; rainfall had no significant effect. Allocative efficiency was 0.67 in Swat and 0.66 in Buner, suggesting potential cost reductions of 29% and 20%, respectively. However, overall economic efficiency remained low (0.32), with no farmer achieving full efficiency. To enhance performance, targeted interventions in farmer education, stakeholder collaboration, and pricing policy are essential, alongside district-specific policy support to address local socio economic variations.