Abstract
In the United States (US), low-income workers are being pushed away from city centers where the cost of living is high. The effects of such changes on labor mobility and housing price have been explored in the literature. However, few studies have focused on the occupations and specific skills that identify the most susceptible workers. For example, it has become increasingly challenging to fill the service sector jobs in the San Francisco (SF) Bay Area because appropriately skilled workers cannot afford the growing cost of living within commuting distance. With this example in mind, how does a neighborhood's skill composition change as a result of higher housing prices? Are there certain skill sets that are being pushed to the geographical periphery of a city despite their essentialness to the city's economy? Our study focuses on the impact of housing prices with a granular view of skills compositions to answer the following question: Has the density of cognitive skill workers been increasing in a gentrified area? We hypothesize that, over time, low-skilled workers are pushed away from downtown or areas where high-skill establishments thrive. Our preliminary results show that high-level cognitive skills are getting closer to the city center indicating adaptation to the increase of median housing prices as opposed to low-level physical skills that got further away. We examined tracts that the literature indicates as gentrified areas and found a pattern in which there is a temporal increase in median housing prices and the number of business establishments coupled with an increase in the percentage of skilled cognitive workers.
Highlights
Alfred Marshall defined cluster theory in his book Principles of Economics as “concentration of specialized industries in particular localities” where industries tend to cluster to facilitate resources and human capital flows in cities (Marshall, 1890)
Network visualizations show the dynamics of how different income groups commute to workplaces that we defined as the city’s downtown and Silicon Valley for the Bay Area for the years of 2002 and 2018
We use weighted out-degree networks to capture the changes in the home place of high- and lowincome workers
Summary
Alfred Marshall defined cluster theory in his book Principles of Economics as “concentration of specialized industries in particular localities” where industries tend to cluster to facilitate resources and human capital flows in cities (Marshall, 1890). According to this theory, each city should specialize in the industry best fitted to its natural resources and attract workers with the skills needed for that specialization. One clear example of this theory is the cluster of technology companies and businesses in Silicon Valley, which is home to programmers, engineers, and investors This dynamic occurs at the city level as well, where workers cluster around the job opportunities in the cities’ central business districts (CBDs).
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