Why are some U.S. cities successful, while others are not? Empirical evidence from
The U.S. population has become increasingly concentrated in large metropolitan areas.
However, there are striking differences in between the performances of big cities:
some of them have been very successful and have been able to pull away from the rest,
while others have stagnated or even declined. The main objective of this paper is
to characterize U.S. metropolitan areas according to their labor-market performance:
which metropolitan areas are struggling and falling behind? Which ones are flourishing?
Which ones are staying resilient by adapting to shocks? We rely on an unsupervised
machine learning technique called Hierarchical Agglomerative Clustering (HAC) to conduct
this empirical investigation. The data comes from a number of sources including the
new Job-to-Job (J2J) flows dataset from the Census Bureau, which reports the near
universe of job movements in and out of employment at the metropolitan level. We characterize
the fate of metropolitan areas by tracking their job mobility rate, unemployment rate,
income growth, population increase, net change in job-to-job mobility and GDP growth.
Our results indicate that the 372 metropolitan areas under examination can be categorized
into four statistically distinct groups: booming areas (67), prosperous mega metropolitan
areas (99), resilient areas (149) and distressed metropolitan areas (57). The results
show that areas that are doing well are predominantly located in the south and the
west. The main features of their success have revolved around embracing digital technologies,
adopting local regulations friendly to job mobility and business creation, avoiding
strict rules on land-use and housing market, and improving the wellbeing of the city’s
population. These results highlight that cities adopting well-targeted policies can
accelerate the return to growth after a shock.
Published on December 18, 2020
In series:OECD Economics Department Working Papersview more titles