A recent study by the MIT Senseable City Lab has used cellphone data to map both social and physical segregation within Singapore. To start, they used residential sale prices as a proxy for socioeconomic status. They then used call and text records (presumably it was all anonymous) from 1.8 million cellphone users in Singapore (2011) to map who interacted with who. Pictured above is one of those mappings.
What they discovered was evidence of a "rich club effect." In other words, the richer the person the less likely they were to interact with people outside of their socioeconomic band. The study calls this their communication segregation index.
A similar phenomenon was noted as people moved around Singapore. (This is the study's physical segregation index.) People tend to spend time in spaces alongside people with similar socioeconomic attributes. However, they did notice that this tends to wane during the day as people move around the city -- presumably for work and other such things.
I think it would be interesting to get a bit more granular about the findings in order to try and see, among other things, if certain public spaces are more successful than others at encouraging a broader socioeconomic mix. And it's probably only a matter of time before we start using tools like this to plan our cities. For more on the study, click here.
Image: MIT Senseable City Lab
Since 2005, LSE Cities (London School of Economics) has been collecting comparative data on how global cities perform in terms of key spatial, socioeconomic, and environmental indicators.
This is their latest data matrix:
To be clear, it is not a ranking of cities. It is intended to help us better understand how different cities around the world are performing.
Depending on how you're consuming this post, the text may be difficult to read. So here's what each column represents, moving from left to right:
Current population in the administrative city (millions)
Current population in the urban agglomeration (millions)
Average hourly population growth of urban agglomeration 2015 to 2030 (people per hour)
Administrative city area (km2)
Average density of built-up administrative area (people/km2)
GDP per capita in urban area ($, PPP)
Percentage of country's GDP produced by the metro region
Population under 20 (%)
Murder rate (homicides per 100,000 inhabitants)
Percentage of daily trips made by public transport
Percentage of daily trips made by walking & cycling
Car ownership rate (per 1,000 inhabitants)
CO2 emissions (tonnes per capita)
If you'd prefer to download a full PDF of the chart, click here.
I was talking about this with my friend Evgeny Tchebotarev last night:
The transfer of sovereignty over Hong Kong (also known as the handover) happened at midnight on July 1, 1997. At the time, Hong Kong had a population of about 6.5 million people and China had a population of about 1.23 billion people. But Hong Kong punched well above its weight class and its GDP as a percentage of mainland China's GDP was about 18.4% (see above). In other words, Hong Kong represented about 0.53% of the population, but almost 1/5 of China's economic output. Today, well as of 2018, this number has declined to 2.7% (again, see above). Hong Kong still possesses a number of structural benefits compared to mainland China, but its position as a global financial center is not guaranteed.
Graph: Investopedia