10th International Conference on Agricultural Statistics

10th International Conference on Agricultural Statistics

Tracking Household Resilience with Panel Data: Implications for Agri-Food Systems.

Author

OS
Oluwayemisi Abidemi Salufu

Co-author

  • K
    Kabir K. SALMAN
  • S
    Sulaiman A. YUSUF

Conference

10th International Conference on Agricultural Statistics

Format: CPS Paper - ICAS 2026

Keywords: agrifood, economicshocks;, foodsecurity, gmm, householdresilience;, markov chain monte carlo, paneldataanalysis;

Abstract

This paper examines the dynamics of household resilience and its implications for food security within Nigeria’s agri-food systems using four waves of nationally representative LSMS-ISA panel data. Against a backdrop of recurrent economic shocks, climate variability, and market instability, the study moves beyond static analyses by tracking resilience trajectories over time. Employing transition matrices, Markov chain analysis, an Ordered Probit model, and a dynamic Generalized Method of Moments (GMM) framework, the findings reveal that resilience significantly improves food security outcomes but remains uneven, persistent, and strongly path-dependent. Many households are trapped in low-resilience states, with frequent reversals following shocks. Substantial regional heterogeneity emerges, with stronger resilience–food security linkages observed in conflict-affected and structurally vulnerable zones, highlighting the critical role of local institutional and livelihood contexts. By providing novel panel-based evidence linking resilience mobility to agri-food system performance, the study shows that food security outcomes reflect cumulative welfare dynamics rather than contemporaneous shocks alone. The results underscore the need for integrated, resilience-centered policies that combine social protection, climate adaptation, market stabilization, and inclusive rural development to foster shock-responsive and sustainable agri-food systems.

Keywords: Household resilience; Food security; Agri-food systems; Panel data analysis; Nigeria.