08 Apr Global Hunger Index and need to rectify the methodology
Global Hunger Index and need to rectify the methodology – Today Current Affairs
The SDG(Sustainable Development Goals ) 2, “zero hunger,” aims to end hunger from all countries by 2030. However, there are severe inequalities in the distribution of wealth, poverty, and hunger between the developed and the underdeveloped world. The State of Food Security and Nutrition in the World (SOFI) 2020 by the Food and Agriculture Organization (FAO) says 690 million people in the world, that is, 8.9% of the world’s population, are hungry, and the world is not going to achieve the SDG by 2030, in the ordinary course. Setbacks in food production, violence, conflict, and economic downturns may be cited as a few reasons for the same. In addition to the above, the COVID-19 pandemic can add up to 130 million people to the proportion of the undernourished.
Identifying the magnitude, distribution, and risk factors of hunger can help us adopt evidence-informed actions to combat the socio-economic evil. The Global Hunger Index (GHI) is a composite index that tries to measure hunger across the globe, jointly published annually by two European non-governmental organisations, namely Concern Worldwide and Welthungerhilfe. Calculating the global hunger score requires four component indicators: undernourishment, child wasting, child stunting, and child mortality (Concern Worldwide 2021). The FAO, UNICEF, UNIGME, and World Bank are the raw data providers. They use a pre-specified differential weighting of the indicators after standardizing each using the highest recorded value since 1988. The final GHI score ranging between o and 100 is used to rank the participant nations on an ordinal scale. They also propose a categorical GHI severity scale for classifying countries based on the final score having five classes with unequal class width, namely low, moderate, serious, alarming, and extremely alarming hunger. The Hindu Analysis
The standardization uses historically highest values over two decades as the denominators for all variables included in the index, that is, 80%, 70%, 30%, and 35% for malnourishment, child stunting, child wasting, and child mortality, respectively. Hence, any nation with a near-peak historical incidence of hunger-related events in the subdomains will gain the maximum score if they improve in the same subdomain. However, using such historical peaks for standardizing a variable can bring in certain biases. For example, they used 70 to standardize the proportion of stunted children, which is almost 30% higher than the highest present-day value of child stunting (Burundi, 54%). However child mortality is almost 200% higher than the highest present-day child mortality. Hence, we believe the standardization procedure can favor a few nations unduly, which fails the purpose of an unbiased ranking. Although the GHI may capture a historical perspective, it lacks robustness in comparing the present-day world. Consequently, we propose normalizing the variables using the maximum and the minimum value instead of standardizing them with a figure unrelated to the variable’s distribution to improve their comparability. Today Current Affairs
Moreover, not all child mortality is due to food insecurity, which is the same for malnutrition, wasting, and stunting. The original index uses a differential weight of 33.3% each for undernourishment and child mortality and 16.6% for child stunting and child wasting. The predictive value of these four indicators can vary considerably between developed and underdeveloped nations. However, there is a lack of quality literature to assign what proportion of these variables occur due to hunger. Hence, we decided to adopt the same weightage used in the original index.
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Methodology
We used the same data published by Concern Worldwide and Welthungerhilfe in their peer-reviewed report: 2021 GHI. However, instead of standardizing the variables using their historic peak, we normalize them by subtracting the minimum from the corresponding score and dividing it by the range of the variable. The normalized global hunger score is calculated as a weighted average of the four normalized component indicators using the same weights as used in the calculation of the original index. The first 18 countries were not reclassified, as the report does not provide any exact data figures.
We also did a sensitivity analysis by comparing the distribution of the original hunger index and the normalized hunger index scores with the human development index (HDI) and gross national income (GNI) per capita. Since the unequal distribution of income across a nation can predict food scarcity and hunger of most of its population, we also compared the hunger indices with a distribution of Gini coefficients. We used Charles Spearman’s correlation since all these distributions were non-normal. The human development report provided us with the HDI and GNI per capita data. We extracted Gini indices from the web portal of the United Nations Statistics Division.
outcomes : The Hindu Analysis
As many as 12 countries did not change their ranks in the normalized Global Hunger Index (n-GHI). Of the remaining 89, ranks of 27 nations have moved up or down by five or more ranks (Table 1). All the 89 countries that changed their ranks are shown in Figure 1. Most of the nations who lost their ranks belong to Africa, though a few are from Asia and South America. Among the four component indicators, we found that the proportion of malnutrition has the most significant coefficient of variation (96.2%) while under-five stunting has the least, in the 2021 data. The Hindu Analysis
We compared the hunger indices with the HDI scores and the per capita GNI. The normalized index correlates more to the HDI and GNI per capita than the original standardized GHI. We did not find a statistically significant correlation between the hunger scores and the Gini coefficients, though normalization improved Spearman’s coefficient in magnitude.
Discussions : The Hindu Analysis
The first global hunger ranking was published in 2006. Since then, 16 rankings have been published altogether, and it has gained the reputation as a tool that compares scarcity of food across the world. As discussed earlier, the GHI uses four component indicators that form a cascade of hunger ranging from malnutrition to death, though not everyone dies of hunger. The most straightforward surrogate measure of hunger is malnutrition. Here, the index adds three other parameters that are highly collinear with malnutrition.
Nevertheless, the GHI ranking, being on a non-interval, non-ratio scale, will not be affected considerably due to the collinearity of the component indicators. Furthermore, we did not change the differential weighting used in the original GHI due to a lack of quality evidence.
The original GHI used constants to standardize, which has no relation to the present-day distribution of the variable. Here, higher child mortality would be viewed less seriously than the proportion of stunted children as the former used a larger denominator to standardize. However, normalization removes all such biases, and hence, in the n-GHI, the final score depends solely on the distribution of the variables as it uses the range of the variable to standardize. That means only if a nation performs well compared to others in the distribution, it will get a better rank. Thus, normalisation provides more justice to the present-day data.
Many African nations had higher malnourishment and under-five mortality than Asia, Europe, and the Americas. However, the higher denominators diluted their scores post standardisation, resulting in comparatively better ranks. Here, in the n-GHI, normalisation took off the undue advantage of such a methodological bias, which resulted in most of them losing their ranks. The most proximal adverse effect of food scarcity is malnourishment than the other component indicators like stunting or wasting. Hence, nations with a higher malnourished population must be penalised more in the ranking. Though the original GHI captures a historical perspective, it is of little use in a cross-sectional view to compare the present-day world. Hence, normalization improves the robustness of the index for being used as a tool for comparison.
Poor income is not the effect of hunger; instead, it is one of the many causes predisposing to food unavailability. Since we are measuring a phenomenon that is hard to measure due to data quality issues, it would be prudent to compare an individual’s purchasing power, an elementarily available and rigorously reviewed data, with an effect of poor income, that is, hunger. The GNI per capita expressed as purchasing power parity of the dollar equalizes the purchasing power of different national currencies by eliminating the price difference among them. Our proposed modification in the calculation of the GHI resulted in an index that is better correlated to national income and the achievements in human development.
Logical thinking leads us to believe that inequality in income distribution results in a higher proportion of the poor and hungry population. However, we got a statistically insignificant correlation of the hunger index with Gini coefficients, even after normalization, which means either the world has achieved more equity in food distribution than in income distribution or the GHI is not prudent enough to capture hunger from the data available. However, our optimism makes us accept the former postulate.
As a concluding remark, there is gross uncertainty at the global level in predicting how much variability in the component indicators is explained by food scarcity. Though generating such a piece of evidence is cumbersome as the proportion can vary from region to region, such an exercise will improve the criterion validity of the ranking.
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