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, such as performance monitoring and decision making. However, the determination of an appropriate weighting method is a significant problem in the creation of composite indices. Weighting methods significantly affect the results of composite indicators in a benchmarking context. Subjective weighting processes 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 in the subjective judgements of the experts who construct composite indices. 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 scarcity of natural resources already constrains economic growth and food security. The climate-related conditions will profoundly affect those countries that are least resilient. The national food security and climate-related performance scores are politically sensitive for governments. Both are essential for incentivising progress towards global targets. Moreover, the policymakers are seeking a working guide to improving their targeting and monitoring efforts for food security.

The Economist Intelligence Unit's (EIU) panel of experts uses a subjective weighting of indicators in the GFSI model. The subjective assessment of sensitive indicators may negate trust in the dimensions and overall score and ranks. An objective weighting approach to the NRR component of the GFSI may provide an evidence-based understanding of a country's progress in the management of natural resource risks and build the confidence of countries in the reliability of the index. No studies yet have explored the effect of an objective weighting of the new NRR component of the GFSI on country scores and ranks. 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 set of 113 countries was analysed using a principal component analysis (PCA) to derive objectively weighted NRR scores and ranks. The objectively weighted NRR scores were then used to adjust the overall GFSI scores and ranks. The Kaiser-Meyer-Olkin (KMO) test was 0.682, indicating that the PCA was suitable for analysing the GFSI data. A paired t-test showed that on average, the objectively weighted NRR scores were lower than the subjectively weighted scores. However, a Spearman's correlation indicated that the objectively and subjectively weighted NRR ranks were strongly correlated (rho = 0.831). The study concluded that the NRR ranks and the adjusted overall GFSI rank of countries would change slightly if an objective weighting technique was applied to the NRR component of the GFSI. However, the subjectively (GFSI model) and objectively (PCA model) weighted NRR ranks were highly correlated, indicating that the subjectively weighted GFSI model was not strongly statistically biased. The findings implied that the subjective weighting of the NRR component of the GFSI may still provide relatively fair country scores and ranks for comparison purposes. However, the existence of subjectivity in the weighting of the NRR component may affect the trustworthiness of the GFSI results among governments and policymakers. An objective weighting of the NRR component could overcome the subjectivity of EIU's weighting approach, improving the reliability of the NRR component of the GFSI and building greater trust.