Income or housing costs and predicts revitalization

Four years ago, researchers at MIT’s Media Lab developed a computer vision system that can analyze street-level photos taken in urban neighborhoods in order to gauge how safe the neighborhoods would appear to human observers.

Now, in an attempt to identify factors that predict urban change, the MIT team and colleagues at Harvard University have used the system to quantify the physical improvement or deterioration of neighborhoods in five American cities.

In work reported today in the Proceedings of the National Academy of Sciences, the system compared 1.6 million pairs of photos taken seven years apart. The researchers used the results of those comparisons to test several hypotheses popular in the social sciences about the causes of urban revitalization. They find that density of highly educated residents, proximity to central business districts and other physically attractive neighborhoods, and the initial safety score assigned by the system all correlate strongly with improvements in physical condition.

Perhaps more illuminating, however, are the factors that turn out not to predict change. Raw income levels do not, and neither do housing prices.

“So it’s not an income story — it’s not that there are rich people there, and they happen to be more educated,” says César Hidalgo, the Asahi Broadcasting Corporation Associate Professor of Media Arts and Sciences and senior author on the paper. “It appears to be more of a skill story.”

“That’s the first theory we found support for,” adds Nikhil Naik, a postdoc at MIT’s Abdul Latif Jameel Poverty Action Lab and first author on the new paper. “And the second theory was the the so-called tipping theory, which says that neighborhoods that are already doing well will continue to do better, and neighborhoods that are not doing well will not improve as much.”

While the researchers found that, on average, higher initial safety scores did indeed translate to larger score increases over time, the relationship was linear: A neighborhood with twice the initial score of another would see about twice as much improvement. This contradicts the predictions of some theorists, who have argued that past some “tipping point,” improvements in a neighborhood’s quality should begin to accelerate.

The researchers also tested the hypothesis that neighborhoods tend to be revitalized when their buildings have decayed enough to require replacement or renovation. But they found little correlation between the average age of a neighborhood’s buildings and its degree of physical improvement.

Joining Naik and Hidalgo on the paper are Ramesh Raskar, an associate professor of media arts and sciences, who, with Hidalgo, supervised Naik’s PhD thesis in the Media Lab, and two Harvard professors: Scott Kominers, an associate professor of entrepreneurial management at the Harvard Business School, and Edward Glaeser, an economics professor.