Hello! 👋
The journal “Nature” recently started a new “Nature Cities” publication. A lot of its research is interdisciplinary and very timely, dealing with topics such as resilience, climate change and how to understand the impact that these shifts have in people’s lives. For this issue, I’ll be looking at a paper that re-imagines the ways policymakers understand labor networks within large urban areas.
Cities as networks of jobs, skills and movement
One interesting Nature Cities paper I came across recently is “Network constraints on worker mobility”. It talks about thinking of cites as networks of labor markets. The nodes are job positions, connected by edges of workers shifting from a job to another. These job switches happen when two jobs require the same skills, so the edges are not weighted equally. The nodes are also scaled to a job’s popularity. Here’s some examples:
These cities’ networks look somewhat similar, but on a closer look, they are actually pretty different. Each city has different spilts between occupation types and as a result offers workers different job options.
So, how do cities shape workers’ job opportunities? And how do these networks determine the area’s productivity and resilience? Cities with a more densely-connected, similarly-skilled work force has been shown to be more productive and resilient to shocks, often leading to higher earnings:
Although urban labor markets are typically modeled according to their employment by occupation, cities may too be characterized according to their workers’ workplace skills. For example, the economic agglomeration of similar firms within the same city has long been linked to higher earnings and productivity.
Worker Embeddedness
As the researchers find, someone’s level of skill specialization (e.g. surgeons are highly specialized) or embedded-ness in their city’s labor market determines their career and their wages. Embedded-ness includes both skill similarity between two occupations and the share of employment for an occupation in a city:
Workers may more easily transition between occupations with large skill similarity, but only if demand for these similar occupations is not already saturated. Embeddeness accounts for both the network topology in each city, as well as the employment share among similar occupations.
In general, the study finds that workers decrease their embedded-ness over time and that this decrease is associated with higher wages.
Spatial Mobility
This concept of embedded-ness also affects how workers are able to relocate between cities. For this, the paper uses a combined embedded-ness metric for any 2 cities that would represent how similar their labor markets are. Their predictive model shows that incorporating a combined metric explains spatial mobility better than gravity models or employment distributions alone.
The graph below shows the relationship between 2 cities’ combined employment and their total migration (or movement). A higher combined embedded-ness relates to a higher number of migrating people:
So, why does this matter?
For a couple reasons! Thinking about worker as high- or low-skilled does not account for how a worker might shift from one job to another, but looking more closely at the specific set of skills lets us infer more about their job transitions.
Also, migration between two urban centers is usually analyzed with gravity models and large-scale metrics such as size or occupation distributions. Reframing this analysis with metrics such as combined embedded-ness allows us to see when workers move between two similar labor markets across two cities.
Lastly, embedded-ness also allows us to make inferences about a city’s resilience to shocks or overall productivity, comparing broader metrics to different kinds of skillsets clustered in it.
Internet Findings
“Where is all the book data?” - written by Melanie Walsh, talks about BookScan: the most comprehensive, influential and inaccessible book sales database
For Your Reference: Threading Letters - from San Francisco’s Letterform Archive, a history of weaving letters into fabric
“6 ways to use a diary” - from the Re-Noted newsletter, 6 different diaries to try out
Thanks for reading!