A metafrontier approach and fractional regression model to analyze the environmental efficiency of alternative tillage practices for wheat in Bangladesh

Among alternative tillage practices, conservation tillage (CT) is a prominent greenhouse gas (GHG) mitigation strategy advocated in wheat cultivation, largely because of its low energy consumption and minimum soil disturbance during cultural operations. This paper examines the agricultural production and GHG emission trade-off of CT vis-à-vis traditional tillage (TT) on wheat farms of Bangladesh. Using a directional distance function approach, the maximum reduction in GHG emissions was searched for within all available tillage technology options, while increasing wheat production as much as possible. The underlying institutional, technical, and other socio-economic factors determining the efficient use of CT were analyzed using a fractional regression model. The average meta-efficiency score for permanent bed planting (PBP) and strip tillage (ST) was 0.89, while that achieved using power tiller operated seeders (PTOS) is 0.87. This indicates that with the given input sets, there is potential to reduce GHG emissions by about 11% for ST and PTOS; that potential is 13% for farmers using PTOS. The largest share of TT farmers cultivate wheat at lower meta-efficiency levels (0.65–0.70) compared to that observed with farmers practicing CT (0.75–0.80). Fractional regression model estimates indicate that an optimal, timely dose of fertilizers with a balanced dose of nutrients is required to reduce GHG emissions. To develop climate smart sustainable intensification strategies in wheat cultivation, it is important to educate farmers on efficient input management and CT together. Agricultural development programs should focus on addressing heterogeneities in nutrient management in addition to tillage options within CT.