Construction of a Farm-Level Food Security Index: Case Study of Turkish Dairy Farms - Koç, Gökçe; Uzmay, Ayşe (Springer Nature, 2024)
Food security continues to be a global concern and its importance has recently increased for many reasons. Composite food security indices have been widely used to calculate and monitor food security, but farm-level studies are limited. Therefore, the main objective of this study is to construct a Farm-level Food Security Index (FFSI) for dairy farms to assess their contribution to food security, identify potential areas for improvement and guide policy makers. Data were collected from 126 farms in the Thrace Region of Turkey through face-to-face interviews. The FFSI was constructed with four dimensions, briefly called economic, quality, social and natural resources, containing twenty-three variables. Principal component analysis was used for the determination of variable weights, data envelopment analysis for calculating technical efficiency, and the Tobit model for examining the factors influencing FFSI scores. To assess the robustness of the FFSI, Monte Carlo simulations-based uncertainty and sensitivity analysis, dimension extraction approach and Shapley effects sensitivity analysis were performed. With an average score of 56.8, the key result of the FFSI is that dairy farms are using almost half of their potential to fully contribute to food security. Moreover, according to the Tobit model, FFSI scores are significantly affected by the farmer’s age and education level, credit use, livestock unit, fodder crop area and milk marketing channel. The FFSI is robust to weights and sensitive to normalisation, and the social sustainability dimension can cause the largest shift in index scores. Based on these findings, numerous agricultural policy proposals have been developed in this study by identifying the priority areas that need to be addressed to guarantee food security.
Keywords: food securtiy index; composite indicator; uncertainty and sensitivity analysis; Shapley effects