Conservation agriculture‐based sustainable intensification improves technical efficiency in Northern Bangladesh: The case of Rangpur

Abstract

AbstractThe dissemination of conservation agriculture (CA) technologies has become the objective of a growing number of projects aimed at reducing food insecurity in vulnerable areas of the world. While many studies have found that CA increases farm productivity, little is known about the components of the productivity gains related to CA adoption. CA is a knowledge‐intensive technology, and it is expected to affect both technical efficiency (TE) and input productivity positively. Using cross‐sectional farm‐level data of 220 maize farmers in Bangladesh, we measure the impact of CA on farmers' TE. We first apply propensity score matching (PSM) to create comparable counterfactual groups of CA and non‐CA farmers. Then, we use a stochastic frontier with correction for self‐selection bias to analyse TE. Finally, we fit a stochastic meta‐frontier (SMF) model to the data and use it to compare TE across the two farmer groups. The analysis showed that CA farmers exhibit greater TE levels than non‐CA farmers. This can be attributed to enhancements in farm management, leading to 8% and 9% increases in their productivity and TE, respectively. Thus, there is a case for policymakers to strengthen programs delivering CA technologies that improve food security in Bangladesh.