Gentrification in the Bay Area

Authors: Yessica Ramirez, Cameron McKenzie, Leilani Rains

Advisor: Ryan Moruzzi

Background

The Bay Area is an area that has been undergoing much recent change such as an increase in population size and a drastic change in average household income. This wealth increase has gone to a small percentage of people in the Bay, leaving those who have lived in the area working ordinary jobs competing with others with much more capital [3]. These changes in wealth and increase in population comes at the cost of others and displacing those who have lived in the area. For us, we define an area undergoing gentrification as the process of wealthier individuals/families moving into an area, renovating housing, luring new enterprises, generally displacing present residents, and changing the character of a poor neighborhood. We wanted to understand, quantify, and measure characteristics of this process to determine what areas in the Bay are being gentrified.

We gathered and utilized data from IPUMS*. We included data from the American Community Survey (ACS) from 2009-2019. The city we focused on was Oakland, CA, but only because of the robust data we had access to. Other cities of interest were Inglewood, CA and Hayward, CA, though we did not carry out the analysis for those cities. Oakland is the largest city in Alameda County and is one of the most ethnoracially diverse cities in the country. It seems as though this extremely diverse area has been undergoing change (gentrification) and we are interested in measuring that change. Others have measured gentrification using a similar and more in-depth analysis to what we did (see [1]), though they did not overlay a racial component. We set out to incorporate race into our measure of gentrification since we feel this component is an important aspect that is usually left out. In our analysis of gentrification, we incorporated average home prices, average household income, educational attainment, and race. We say that an area is experiencing gentrification if:

• The percentage of homes valued over 500K has been increasing.

• The average household income has been steadily increasing.

• The average educational attainment has been steadily increasing.

And the racial component we wanted to incorporate is:

• The percentage of the population identifying as those identifying as Black or Hispanic has been decreasing.

We chose to focus on the changes in population of those identifying as Black or Hispanic since usually gentrification occurs when these populations are displaced.

*IPUMS USA collects, preserves and harmonizes U.S. census microdata and provides easy access to this data with enhanced documentation.

Analysis

For our study of gentrification in Oakland, CA, we gathered data on average home value, average household income, average educational attainment, and percentage of the population identifying as Black from the IPUMS website [4]. The data we used was from the American Community Survey (ACS) 5-year samples. The multi-year samples do contain data from the previous 5 years, meaning the 2009 ACS contains data from 2004-2009. We used overlapping data in hopes of gaining an accurate picture of Oakland. Also, we note that although the 2009 ACS 5-year sample contains aggregated data from the previous 5-years, the dollar amounts are adjusted for inflation to 2009, and so will refer to this as data for 2009. Similarly, 2011, 2013, 2015, 2017, and 2019.

We focused on these attributes to quantify gentrification because of the connection between higher paying jobs, education, and home value. People who attain higher degrees typically have a higher income and therefore are able to pay more for a home. The average educational attainment is measuring the percentage of the population who have a Bachelor's degree or higher, which we denote as having a 4+ year degree. In the analysis, we provide scatter plots and line plots. For the scatter plots, we fit a best fit line and provide the coefficient of determination. The coefficient of determination of our best fit line tells us how closely the data follows that line. Below, we have the plots of the data we gathered.

Conclusion

We believe that from our measurements and data above, Oakland is undergoing gentrification. This is due to an increase of the percentage of average family income, education level, and average home value. We were very surprised to see that the percentage of the population identifying as White has also been steady and fairly constant since 2009. This was counterintuitive to us because of who we traditionally associate as the “gentrifiers'' and who we traditionally associate this process of gentrification being taken out on. We were not able to dig into this revelation and are very interested in further studying who is being displaced and who is doing the displacing.

The overlaying of a racial component to gentrification is much more involved than we initially believed. It is more nuanced and subtle. Because of this, what we want to do in a future analysis is to include the voices of residents in the areas we are analyzing. The qualitative data that we could gather would add a deeper and more rich perspective to the study of gentrification. We are able to add the perspective of gentrification from those that may be feeling that process taking place, coupling that voice with the quantitative data.

We want to also incorporate and study more areas. One city of great interest to us was studying Hayward, CA. The limiting factor was the data that we could find and access. With the many recent housing developments in Hayward going up on Mission Blvd, a street that runs through and perpendicular to downtown Hayward, we believe this is an area that is ripe for gentrification, or is already being gentrified. Gathering qualitative and quantitative data to study gentrification in Hayward would illuminate if our thoughts are correct.

Last, we want to study the city policies that could help current residents against the aspects of gentrification. We are able to advocate for certain policies to be put in place, or advocate to get rid of policies that may be inviting gentrification. For example, areas that have no rent stabilization or rent control policies seem to be experiencing more gentrification. This is the action part of our research that would help many in the Bay who are feeling the effects of this process of gentrification.

References

[1] SF Bay Area- Gentrification and Displacement, https://www.urbandisplacement.org/maps/sf-bay-area-gentrification-and-displacement/, Accessed on November 8th, 2021

[2] DeBolt, David, Oakland’s population grew by 50,000 over the past decade, 2020 Census data shows., August 18th, 2021 https://oaklandside.org/2021/08/18/oaklands-population-grew-by-50000-over-the-past-decade-2020-census-data-shows/, Accessed on May 4th, 2022

[3] Gentrification and Neighborhood Revitalization: WHAT’S THE DIFFERENCE,

https://nlihc.org/resource/gentrification-and-neighborhood-revitalization-whats-differenc, Accessed on October 15th, 2021

[4] U.S. Census Bureau. 2009, 2011, 2013, 2015, 2019 American Community Survey Data, Retrieved from https://usa.ipums.org/usa/, Accessed on October 18th, 2021