The effect of an objective weighting of the global food security index’s natural resources and resilience component on country scores and ranking

Abstract

Composite indicators have gained popularity in various research areas. However, the determination of an appropriate weighting method is challenging. Subjective weighting methods are criticised for their potential bias that may reduce stakeholders' trust in the results of a composite index. By contrast, objective weighting processes are perceived to provide unbiased results that may overcome trust issues. The Global Food Security Index (GFSI) is a composite indicator that measures the comparative level of food insecurity for 113 countries. The initial components of the GFSI included the affordability, availability and quality and safety components. In 2017, the GFSI added a fourth component for natural resources and resilience (NRR) as a risk to food security. The Economist Intelligence Unit's (EIU) panel of experts uses a subjective weighting of indicators in the GFSI model. This study set out to assess whether an objective weighting of the NRR component of the GFSI significantly changed the country scores and ranks compared to the subjective weighting process. The GFSI data was analysed using a principal component analysis (PCA) to derive objectively weighted NRR scores and ranks. The objectively and subjectively weighted NRR ranks were strongly correlated (rho = 0.831), implying that the GFSI model was not strongly statistically biased. The study concluded that subjective weighting of the NRR component of the GFSI may still provide relatively fair country scores and ranks. However, an objective weighting of the NRR component could improve the reliability of the NRR component of the GFSI and build greater trust.

Global Food Security Assessment during 1961–2019

“…According to the above analysis of factors affecting food security and equation ( 1), the comprehensive pattern map of the global food system vulnerability was generated. The results of this study are consistent with the results of the Economist Intelligence Unit's (Global Food Security Index 2019) [25]. Shown as Figure 9, the vulnerability (food insecurity) index of the food system in Africa and South Asia gradually increased from 1961 to 2019, especially in Sudan, Botswana, Algeria, etc.…”

“…Due to the occurrence of the COVID-19 pandemic, floods, desert locusts, conflicts, wars, and other disastrous events, the world must work together to ensure the smooth flow of global food trade (Falkendal et al, 2021;Dalin et al, 2019;Lam et al, 2020;Grafius et al, 2020;Friel et al, 2020) [21][22][23][24][25]. Different from previous studies on food security at the national scales, this study can better reveal spatial heterogeneity and identify fragility areas in food systems.…”

“…Proper assessment of food security is of great assistance to planners and administrators [22][23][24]. Many studies have constructed evaluation indexes for food security at various scales and from different perspectives [24][25][26][27][28]. At the global scale, the Global Food Security Index (GFSI) provides a common framework for understanding the root causes of food insecurity by looking at the dynamics of food systems around the world, which is produced by The Economist Intelligence Unit and supported by Corteva Agriscience [25].…”

“…Many studies have constructed evaluation indexes for food security at various scales and from different perspectives [24][25][26][27][28]. At the global scale, the Global Food Security Index (GFSI) provides a common framework for understanding the root causes of food insecurity by looking at the dynamics of food systems around the world, which is produced by The Economist Intelligence Unit and supported by Corteva Agriscience [25]. Grebmer et al [26] used the Global Hunger Index (GHI) to measure changes in the number of hungry people in different regions of the world.…”

Food Security and Transition towards Sustainability

“…Ibukun et al [56], Odhiambo et al [57], Lamichhane et al [58], Vysochyna et al [59], Yao et al [60], Chatterjee et al [61], and Suantika et al [62] used a PCA and PLSR model to estimate the impact of food security and SDGs in different circumstances.…”