Consequences of increased farm resilience on food security in Tajikistan

Unprecedented climate change, socio-economic shocks, and political conflict exacerbate food insecurity. Worsened conditions and increased vulnerability now give prominence to improving farm resilience to withstand shocks. This article aims to analyse the effect of farm resilience on food security outcomes in Tajikistan. Using panel data collected in 12 districts in the Khatlon Province of Tajikistan from 2015 to 2023, the study has the following. (a) measure farm resilience determinants (pillars) through adaptive capacity, transformation capacity, and robustness; (b) estimate the relationship between resilience pillars and food security outcomes; (c) cluster farm households based on the level of resilience pillars; and (d) estimate the effect of farm resilience on food security outcomes. The study first measures farm resilience pillars using Principal Component Analysis (PCA). Next, Latent Profile Analysis (LPA) is used to classify farm households into three resilience categories: “Low Resilience”, “Medium Resilience”, and “High Resilience”. The estimation strategy involves making causal claims using LPA and Propensity Score Matching (PSM) techniques. Our results suggest a positive relationship between farm resilience and food security outcomes. Our findings also confirm that “High Resilience” and “Medium Resilience” profiles experience better dietary diversity, higher fruit and vegetable consumption, or decreased household hunger, compared to the “Low Resilience” profile. Such a positive relationship underlines the importance of strengthening farm resilience. Further development agendas for Tajikistan should consider resilience thinking, especially in shock-prone zones. Objectives: (a) measure farm resilience determinants (pillars) through adaptive capacity, transformation capacity, and robustness; (b) estimate the relationship between resilience pillars and food security outcomes; (c) cluster farm households based on the level of resilience pillars; and (d) estimate the effect of farm resilience on food security outcomes. The study first measures farm resilience pillars using Principal Component Analysis (PCA). Next, Latent Profile Analysis (LPA) is used to classify farm households into three resilience categories: “Low Resilience”, “Medium Resilience”, and “High Resilience”. The estimation strategy involves making causal claims using LPA and Propensity Score Matching (PSM) techniques. Our results suggest a positive relationship between farm resilience and food security outcomes. Our findings also confirm that “High Resilience” and “Medium Resilience” profiles experience better dietary diversity, higher fruit and vegetable consumption, or decreased household hunger, compared to the “Low Resilience” profile. Such a positive relationship underlines the importance of strengthening farm resilience. Further development agendas for Tajikistan should consider resilience thinking, especially in shock-prone zones.