World Food Day: The Numbers #WFD2014

The cool thing about being in Brussels? Showing up at a lunch meeting across the street from your office and have the chief statistician of the FAO and the director of the WFP Brussels office explain how they arrived at estimating the state of food insecurity in the world. I will talk more about the statistics stuff below, but first off some numbers and facts for the non-econometrics inclined!

[slideshare id=39135785&doc=sofi2014launch16-09-2014final-140916033534-phpapp01]

• According to the FAO, 805 million people (around one in nine) are chronically undernourished today – down from 1015 million in 1990.
• This means that we are close to meeting the Millennium Development Goal on hunger (halving the percentage of food insecure in the world as compared to 1990; we went from 23.4% to 13.5% in developing countries), though far from meeting the World Food Summit goal (halving the absolute number of hungry – this would require 300 million more people to be properly fed). 63 countries have met the MDG goals and 25 countries the WFS targets.
• Latin America and the Caribbean have made the most significant overall progress, whereas Subsaharan Africa, Western and Southern Asia have been lagging behind.
• As a general rule, strong and sustained political commitment was a prerequisite to increasing food security. Much of the progress seen was in countries with well developed (and properly funded) food security policies. Economic growth impacted food security positively, but only where adequate social safety nets were present.

But back to the question – how do you even get to these conclusions?

It was an intriguing question that I hadn’t really considered before – how do you measure food insecurity, seeing as everybody has different nutritional and caloric needs, different incomes and different circumstances? In fact [attention – nerdiness about to happen], instead of using a headcount estimate, they use a probabilistic model – they create a “random” average consumer and try to estimate how likely this consumer is to be food insecure. This estimate is based on indicators of food security in four different dimensions:

1. Food availability, capturing not only quantity, but also quality and diversity of food (indicators: average dietary energy supply adequacy, average value of food production, share of dietary energy supply derived from cereals, roots and tubers, average protein supply, average supply of protein from animal sources)

2. Food access, both physically and economically (indicators: railway and road density, domestic food price index, GDP per capita, prevalence of undernourishment, share of food expenditure of the poor, depth of the food deficit, and prevalence of food inadequacy)

3. Stability of food supply, measuring exposure to food security risks and shocks (indicators: cereal import dependency ratio, percent of arable land equipped for irrigation, value of food imports over total merchandise exports, political stability and absence of violence/terrorism, domestic food price volatility, per capita food production variability, and per capita food supply variability)

and

4. Food utilization, determining the ability to utilize food adequately (indicators: access to improved water sources, access to improved sanitation facilities, percentage of children under 5 years of age affected by wasting, percentage of children under 5 years of age who are stunted, percentage of children under 5 years of age who are underweight, percentage of adults who are underweight, prevalence of anaemia among pregnant women, prevalence of anaemia among children under 5 years of age, prevalence of vitamin A deficiency in the population, prevalence of iodine deficiency).

Once they had all these different indicators, they created the most likely scenario for a typical inhabitant of the country in question (by calculating the cumulative probability that your habitual dietary energy consumption lies below the minimum dietary energy requirement) and then extrapolated this to the number of people in the country. So, say your probability of being food insecure in Riceland is 0.1, and Riceland has 1000 inhabitants, they would be estimated to have 100 hungry people, or to have 10% of their population chronically undernourished. Which, obviously, is the same as the probability estimate, but we think of the two things slightly differently.

What the chief statistician failed to discuss in more detail (probably because of a lack of interest in the audience in statistical finesse), and what is missing on the slides (above) openly available through their website, is the difficulties with some of these indicators.

But, thankfully, they sent out the full slides after the presentation!

So here are some of the concerns: