Determinants of Technical, Allocative, and Economic Efficiencies Among Cotton Producers of Baghlan Province
Abstract
Cotton holds significant importance as an industrial commodity, being in high demand and finding diverse applications across various sectors of the economy. However, its productivity remains low due to technical and managerial inefficiencies. This study addresses the problem of low production efficiency among cotton farmers in Baghlan province, aiming to quantify technical efficiency (TE), allocative efficiency (AE), and economic efficiency (EE) levels and identify their key determinants. The research is based on cross‐sectional primary data collected in 2023 from 132 cotton producers selected through stratified random sampling. The efficiency assessment employs data envelopment analysis (DEA), while the Tobit regression model examines the factors that influence the efficiency of cotton production. The findings reveal that, on average, cotton farmers achieve efficiency levels of 96.8% in TE, 81.7% in AE, and 79.1% in EE. Notably, 90.15% of farmers operate with a TE surpassing 90%, whereas 9.85% exhibit technical inefficiencies. Furthermore, 7.5% of farmers attain EE levels exceeding 90%, while 59.8% exhibit economic efficiencies below 80%. The regression analysis underscores the adverse impact of age and farm size on efficiency. Conversely, work experience, membership in cooperatives, and expertise are found to be positive influencers of efficiency levels. The novelty of this study lies in its finding that high technical skill and economic inefficiency often coexist. This gap, if any, is very poorly covered in the Afghan agricultural literature. To increase the possibility of closing this gap, the study recommends policies that aim to enhance the participation of young farmers, promote agricultural cooperatives, improve financial literacy, and ensure the efficient distribution of inputs. Without these steps, Afghanistan’s cotton sector cannot be transformed into a competitive, sustainable industry.