Mobile Data Traffic is Correlated with GDP

Analysys Mason estimates that a 100 percent increase in mobile data traffic translates into a 0.98 percent impact on gross domestic product. That is a correlation, not necessarily causation, as always is the case for economic impact studies. 

But that is the problem with all efforts to quantify the economic impact of any particular innovation, product or industry. We might estimate impact, but we cannot prove the causal relationship of any single input when results (economic growth, for example) is caused by multiple inputs.

Consider that, in addition to the volume of mobile data traffic, the capacity of undersea cables, home broadband adoption, use of information technology,  transportation systems, energy supplies, broadband speed, educational attainment, household wealth, housing density, business activity levels, ethnicity and age can be correlated with gross domestic product as well. 

It is impossible to clearly separate the impact of each input when determining countrywide economic output. During the Covid pandemic, we discovered correlations between risk factors and deaths. But correlation is not causation. 

One might argue for a correlation between electricity consumption and GDP, for example. 

Among OECD member countries, for example, gross domestic product increases by 1.7 percent per year. Electricity use increased by 0.9 percent per year between 2015 and 2040. In non-OECD countries, GDP increases by 3.8 percent per year, and electricity use increases by two percent  per year over the same period, according to the U.S. Energy Information Administration. 

The point is that there is a correlation between electricity usage and GDP. 

source: Our World in Data 

Higher GDP is associated with higher energy consumption. 

source: EIA 

The other problem is that if one were to try and add up all the claimed economic benefits caused by each input or industry, the results would not comport with reality. The claimed output would vastly exceed reality. 

“We find that a 10 percent increase in the fraction of the population ages 60+ decreases the growth rate of GDP per capita by 5.5 percent,” the RAND Corp. has found. “Two-thirds of the reduction is due to slower growth in the labor productivity of workers across the age distribution, while one-third arises from slower labor force growth.”

Transportation might be correlated with about five percent of GDP as well.  

The point is that better communications and connectivity always are assumed to correlate with better GDP outcomes. We can disagree about the magnitude of such correlations while assuming there is a correlation. 

But neither can we accurately measure the specific causation of any single input.