This article is part of the World Economic Forum's Geostrategy platform
All stable countries are alike, but all unstable countries become unstable in their own ways.
The Wilson Center paper Forecasting Instability: The Case of the Arab Spring and the Limitations of Socioeconomic Data questions whether economic and socioeconomic trends alone could have held the keys to predicting the instability in the Middle East and North Africa (MENA) region that began in late 2010. It posits that an over-reliance on economic data can lead to misguided predictions.
The best analysts are adept at identifying “structural factors” – the long-term, root causes that lead to unrest and revolutions. These factors consist of economic decline, growing inequality, corruption, political repression, and failing infrastructure and social services, among others.
The “black swans” or spontaneous occurrences that trigger destabilizing events, however, are by definition virtually unpredictable.
The rapidity with which societal forces shook much of the MENA region in 2010 and 2011 surprised most experts, but they were most surprised by the timing and the unexpected catalyst – the self-immolation of a poor fruit vendor in central Tunisia in late 2010 – and not by the underlying conditions. These were well known and written about for years.
Glowing economic story
“Judging by economic data alone, the revolutions of the 2011 Arab Spring should have never happened. The numbers from the decades before had told a glowing story: the region had been making steady progress toward eliminating extreme poverty, boosting shared prosperity, increasing school enrollment, and reducing hunger, child and maternal mortality,” a World Bank article from 2015 concluded.
Strong economic growth is a red herring for predicting stability; similarly, low economic growth is not always associated with instability. What aggregated and topline numbers neglect are nuances and wealth distribution, along with public satisfaction, services, health care, clean water, affordable housing, and political views.
Superb post-mortem analysis has been done to examine the causes behind the Arab revolutions that began in late 2010.
Some studies point to specific causes, such as income inequality, unemployment, corruption, or purely political issues such as repressive and unresponsive regimes. Others suggested that many structural factors over a long period merged with spontaneous events that prompted the unrest and revolutions.
Yet, perhaps no other economic indicator has been more analyzed as being the proximate cause for the Arab Spring revolts than high and persistent rates of youth unemployment.
On the eve of the unrest, in 2010, the International Labour Organization (ILO) published data indicating that unemployment among Arab youth was the highest in the world.
Youth unemployment was mostly concentrated among the educated. Somewhat paradoxically, with decreasing levels of absolute poverty and increasing levels of education, youth unemployment in the MENA region generally is higher than in other regions; young people appear less motivated to accept unattractive jobs at the bottom end of labour markets that do not match their skills.
This combination of relatively high levels of education and an inability to find work helped create that potent recipe for instability.
This assessment is incontrovertible, but high youth unemployment had been a regular feature of Arab economies for years. Average Arab youth unemployment rates in 2009 had barely changed from the high rates in 2000 and in some cases were marginally lower.
Corruption as a trigger
Next to youth unemployment, corruption in government and among the elite has been touted as a primary cause of the unrest, especially when combined with real and perceived income and wealth inequality.
As in Tunisia, the conditions in Egypt made the country ripe for revolution. In the preceding decade, corruption in the country had essentially given up any pretence of subtlety. The connected and affluent built gated communities, while most Egyptians lived in "informal" housing and shanties. Egyptians had had enough by 2011.
As with other indicators, however, government corruption is usually necessary but insufficient for fuelling public grievances, as it works in concert with other negative socioeconomic trends.
Similarly, based on multiple analyses of data, there was no strong direct causal influence of income inequality on the Arab uprisings.
As with solely relying on socioeconomic data and trends to approximate political stability in a country, aggregated data that include political as well as social and security issues still fall short of predicting widespread unrest or a government’s demise.
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What is needed, therefore, are short-term indicators that analysts and policymakers can view to get a better sense of pending unrest and instability.
No single indicator will answer those questions, but two in particular can at least begin to approximate rising short-term vulnerability: food prices and opinion surveys.
These indicators are, of course, imperfect, but they can provide a level of diagnosticity, given their timeliness (as in the case of food prices), or relatively up-to-date public perceptions that provide insight not to be gleaned from crude data.
More than 50% of the food consumed in the MENA region is imported, making it the largest food-importing region in the world, according to a World Bank study, and Egypt is the world’s single largest wheat importer.
This dependence on food imports makes many in the MENA region highly vulnerable to changes in global food prices. Wheat is the main source of daily calorie intake in Egypt, for example, and any uptick in prices or availability of wheat and bread directly impacts virtually every family. Even with heavily subsidized prices, the country’s dependence on imports during a time of sharply rising prices wreaked havoc on Egypt’s poor and vulnerable population.
Widespread protests and violence in Iran at the end of 2017 and into early 2018 demonstrate the visceral impact of rising food prices.
In a short period of time, the price of eggs had risen by some 40% and prices for poultry had gone up sharply as well.
Iranians have many reasons to protest, but the quickness with which protests erupted over the sharp rise in food prices is further evidence that analysts and policymakers need to carefully watch these price movements.
Public opinion surveys that show rising levels of dissatisfaction with the quality of life can be important indicators.
Throughout much of the Middle East, the deterioration in life satisfaction was not captured in macroeconomic data, household financial surveys, or in standard indicators of inequality, but was evident in perceptions data from value surveys.
There was a notable rise in the incidence of dissatisfaction in a number of areas considered crucial to quality of life. Absolute poverty was low and the level of income inequality was, in the aggregate, moderate during the 2000s. Instead, the unhappiness was associated with deteriorating government services, widespread corruption, and lack of fairness.
Public opinion surveys are in many ways similar to macroeconomic statistics; they develop over time, and many responses are consistent from one year to the next. However, the speed of change in public opinion can prove diagnostic in tracking looming instability, particularly if opinions had changed little over a period of years.
Of course, not all surveys are created equally. Methodologies can vary greatly, and to be useful, they need to be timely, in order to accurately track sentiments on issues dear to the hearts of the public. But with the right focus on key socioeconomic concerns and if conducted well, surveys can peer behind official economic statistics to get a sense of public perception.
As in many elections, it’s often less about the data a politician or ruler can point to and rather, how the public perceives its lot.
The beauty of data is that it provides definitive signposts. Socioeconomic data can highlight broad trends in stark relief and frame an analyst’s approach to a problem. Accurately forecasting events based on aggregating reams of data will consistently fall short, however.
It is perhaps too soon to tell whether big data exploitation can provide the final ingredient for forecasters, but the complexity of societies and markets suggests that this, too, will have its limitations. A fortune teller can always predict your mortality, just not the date and time.