Behavioural drivers of agricultural resilience: Evidence from Nigeria’s NG-CARES social protection programme in Zamfara State

Abstract

This study applies a theory-driven approach to assess the impact of Nigeria Community Action for Resilience and Economic Stimulus (NG-CARES) programme, focusing on result area 2 (RA 2), which targets agricultural productivity and food security among smallholder farming households in Zamfara State, northwestern Nigeria. Implemented in response to pandemic-induced disruptions, RA 2 aimed to improve on-farm productivity and food access through the provision of agricultural inputs, climate-smart technologies, and extension services. A mixed-methods approach was employed using a quasi-experimental design based on cross-sectional household survey data from 723 respondents across four Local Government Areas. The analytical framework integrates the theory of planned behaviour (TPB), social cognitive theory (SCT), and the NG-CARES theory of change to examine behavioural, institutional, and economic pathways linking programme participation to welfare outcomes. Programme impacts were estimated using endogenous treatment effect (ETE) and augmented inverse probability weighting (AIPW) models. Results show that NG-CARES participation significantly increased yield by 34–37 % (kg ha^-1), farm income by 86–87 % (₦ ha^-1), and reduced household food insecurity scores by 0.64 points on the household food insecurity access scale (HFIAS), with all effects statistically significant at the 1\,\% level. The study provides empirical evidence of the behavioural impact of NG-CARES in fragile rural contexts. It emphasises the importance of incorporating behavioural insights into programme design, highlights the usefulness of integrated econometric tools for evaluating non-randomised interventions and stresses the need for gender-sensitive strategies to enhance inclusion. The policy recommendations are to scale up behavioural-informed input support systems, enhance extension platforms, institutionalise routine impact evaluations and target female farmers more effectively in order to inform adaptive programme design.