The effect that technological change will have on income inequality globally can be better understood and predicted by using economic complexity.


Inequality is present in today’s development discussions for two reasons. First, it has been argued that inequality has both increased and decreased since the Industrial Revolution, with conflicting datasets and term definitions. Using World in Data’s (2017) measure of inequality, inequality between country since then, following a surge in the last century, while intra-country inequality has increased in the last decades of the 20th century.

This trend has continued over the last decade: while it is argued that inter-country inequality has decreased in recent years, as argue those who see a decrease in the Global Gini index (The Economist, 2012), the reality is that this index only measures the average for all countries, independent of size or absolute variations. The reality is that inequality has become one of today’s most sensitive “social, economic and political challenges of our time.” (The Economist, 2012).

The second cause for concern is the potential for massive inequality arising from technological change, in what’s commonly referred to as the “Fourth Industrial Revolution”. While technology has great potential to shape employment opportunities and education for good, it can also create a “winner-takes-all” global economic scenario that pushes low-skilled workers and low-income nations out of competitive positions, thus pushing up inequality levels further. This would mean developed nations bringing back manufacturing and industrial jobs from overseas due to their technological advances, reducing the need for low-skill labor. Thus, as Driemeier and Nayyar (2017) argue, these changes will challenge traditional economic growth models, concluding that the risk of rising inequality in the coming decades is high.

This poses a big risk to societies across developed and developing nations. According to the World Economic Forum (2017) there is existing data indicating that unequal societies tend to be more violent, have higher recidivism, suffer from worse mental health and obesity and have lower life expectancies than those with more equal societies. The Fourth Industrial Revolution will fundamentally challenge the idea of work as a way to find meaning in life, and could bring about more social exclusion (World Economic Forum, 2017).

The Future of Work

Economists and policymakers are hard at work to find out what countries might do to be better positioned to face the challenges that will come with technological change. One of the most interesting lines of research is that of “economic complexity”, which measures to what extent knowledge is embedded in the economy of a country (Observatory of Economic Complexity, 2017).

Extensive research has been done into economic complexity as a way of measuring the resilience of a country’s economy: complexity has been proved to be a better predictor for future growth than traditional indicators of GDP, labor and capital (World Policy, 2011), but also for income inequality (Hartmann, Guevara, Figueroa, Aristarán, Hidalgo, 2016).

Economic Complexity

Ricardo Hausmann, one of the leading thinkers in the economic complexity field, recently pondered this question: “What does the future of work hold in store, and how should we prepare for it?”  The piece seemed to point to the use of complexity to understand how a country might be better prepared for these future challenges.

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