Call data can track economic change, unemployment

Call data can track economic change, unemployment
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Highlights

Mobile phone data can track economic change and provide rapid insight into employment levels as people\'s communications patterns change when they are not working, says a new study from Massachusetts Institute of Technology.

New York: Mobile phone data can track economic change and provide rapid insight into employment levels as people's communications patterns change when they are not working, says a new study from Massachusetts Institute of Technology.


Without a commute or workspace, most people will make a higher portion of their calls from home -- and they make fewer calls, the study found. The researchers believe the phone data closely aligns with standard unemployment measures, and may allow analysts to make unemployment projections two to eight weeks faster than those made using traditional methods.


"Using mobile phone data to project economic change would allow almost real-time tracking of the economy, and at very fine spatial granularities ... both of which are impossible given the current methods of collecting economic statistics," said study co-author David Lazer.


The study's starting point was an automotive plant in Europe that closed in 2006, leaving about 1,100 workers unemployed in a town of roughly 15,000 people. The researchers found that in the months following layoffs, the total number of calls made by laid-off individuals dropped by 51 per cent compared with working residents, and by 41 percent compared with all phone users.


The number of calls made by a newly unemployed worker to someone in the town where they had worked fell by five percentage points, and even the number of individual cellphone towers needed to transmit the calls of unemployed workers dropped by around 20 per cent.


"Individuals who we believe to have been laid off display fewer phone calls incoming, contact fewer people each month, and the people they are contacting are different," said co-author Jameson Toole. The study was published in the Journal of the Royal Society Interface.


Having the information about the layoffs allowed the researchers to build an algorithm that, by analysing phone-use patterns, assigns a probability that someone has become unemployed.

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