Communication: a Human Constant?

Information exchange through language and other forms of advanced communication sets human beings apart from every other species. In the digital age, mobile networks amplify and expand our reach — we can communicate via voice, texts and photos anytime, anywhere. At Juvo, we’ve noticed a striking pattern in the process of examining global mobile usage data: across the world, communication is equally valued, independent of wealth.

Our data science team examined the relationship between how much individuals around the world spend on mobile communication every month and the average rate that they earn money (per-capita GDP). It turns out that the rate of mobile communication consumption closely follows income in 16 countries, across four continents. In other words, human beings value communication equally, regardless of wealth, race, culture, or religion.

Figure 1: Communication is universally important. Data from 16 countries across 4 continents shows that about 1–2% of income is spent on mobile airtime.

The fact that communication is equally valued across disparate regions and circumstances may have important, immediate real-world implications. Per-capita GDP is a well-known indicator of economic performance, and since mobile consumption follows it so closely, it too can be used as economic indicator. In fact, since mobile consumption is relatively easy to measure and can be reliably tracked on a weekly basis, it may more accurately describe the current state of an economy, compared to other, lagging indicators.

An immediate example of how mobile consumption may be helpful in gauging economic activity is by taking note of the Cayman Islands, which is clearly an outlier. One reasonable explanation for this anomaly is that per capita GDP doesn’t represent the typical income and is skewed towards a relative handful of extremely wealthy individuals.

Acknowledgements: This work was done in collaboration with Juvo’s Data Science and Data Engineering Teams. Special thanks to Monica Rogati for helpful discussions and Theo Arguna for figure design.

Methodology: We examined the monthly active user population across several mobile networks. For our data, we utilized “prepaid” users, who regularly visit their local mobile provider, paying for services e.g., on a daily, weekly or monthly basis. The plot is the result of nearly a billion anonymized data points from tens of millions of individuals.

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