6.1: Explanation of main results
Comparing the results between the expanded dataset, which includes all tracts within one mile of a treatment station, to the limited dataset, which contains strictly tracts that contain a treatment station, allows for a better, broader analysis of the trends and spillover effects.
Median household income was negative and statistically significant in both datasets.
Gross rent as a share of median household income increased in both data sets, but the coefficient was much more extensive and statistically significant in the limited dataset. The share of commuters traveling to work in single-occupancy vehicles was slightly positive but insignificant in the expanded case, while the limited dataset showed a negative, significant effect. Finally, the share of residents identifying as Hispanic or Latino decreased in both data sets but was only statistically significant in the limited case.
In summary, the data show that the implementation of transit-oriented housing development leads to lower-income residents moving into the treatment area but also exasperates displacement of the Hispanic community. While trends are also apparent at the limited level in the share of commuters traveling to work in single-occupancy vehicles and the gross median rent as a share of household income, these two variables do not pass the crucial parallel trends test as clearly as median income and the Hispanic share of the population variables do.
6.2: Comparison to Existing Literature
This thesis contributes to the previously existing literature by reinforcing that each community is unique and that it is impossible to generalize how these developments will play out. It is, however, to draw comparisons between the results of this study and the conclusions reached by similar studies. For example, Jones and Ley (2016) discovered signs of gentrification in Vancouver after implementing pro-TOD policies. The situations in Denver and Vancouver are similar except for the affordability requirement in Denver. It is possible that the impacts of transit-oriented development in Denver were more favorable for the community due to the affordability requirement. Debrezion et al.’s 2006 conclusion that proximity to rail stations
The Washington, D.C. analysis conducted by Dawkins and Moeckel (2016) is structurally similar to the developments in Denver and yields similar results. The analysis in Washington D.C.
revealed improved access to transit and little to no displacement of low-income individuals. This similarity suggests that an affordability requirement in TOD helps avoid gentrification. While this analysis does not calculate total changes in welfare, as does Balboni et al. (2021), similarities still arise. In their analysis, transit-oriented gentrification was avoided, and residents benefited from improved public transit access. Improvements in Denver’s treatment neighborhoods represent a similar benefit: residents have more transportation options and use expensive modes like private cars less frequently.
6.3: Modern policy implications
Residents of Denver made headlines in late 2020 when they voted in favor of Ballot Initiative 2A, which added 0.25% to the local sales tax rate and established one of the first Climate Protection Funds (CPF) in the United States. Denver’s CPF generates more than $40 million annually and serves to help finance the city’s aggressive climate plan by supporting climate adaptation projects, investing in low-carbon infrastructure, and fostering a green job market, along with other endeavors. Notably, the bill approved by voters states that the CPF
“should, over the long term, endeavor to invest fifty percent (50%) of the dedicated funds directly in the community with a strong lens toward equity, race, and social justice” (Office of Climate Action, Sustainability, and Resiliency, 2021).
The average person of color lives in a census tract with a higher average surface temperature than their white, non-Hispanic counterparts in 169 of the largest 175 cities in the United States (Hsu et al., 2021, Climate Central, 2021). In Denver, the arid summers result in a situation where mid-afternoon temperatures vary by as much as +20 degrees Fahrenheit, depending on which neighborhood an individual lives in. Geologists and climate scientists predict that by 2080, Colorado will look and feel more like the state’s much warmer neighbor to the southwest, Arizona (Talsma et al., 2022). This climate trajectory is also predicted to disproportionately impact low-income and majority-minority communities the hardest, a trend that is consistent throughout the literature.
Denver’s recently published five-year CPF plan lists low-carbon housing and transportation projects as acceptable uses for the newly generated tax revenue. A record-breaking spending package on housing is currently addressing the city's affordable housing shortage. In addition, the region is simultaneously developing the country's most extensive voter-approved transit expansion program. These two construction booms provide a
unique opportunity to accomplish two goals simultaneously by investing in intelligent, transit-oriented development projects.
Despite the strong signaling from voters about their willingness to fund and support the city’s transition to a cleaner environment, many lifelong Denverites remain skeptical or even in opposition to this program. The city’s rapid growth and skyrocketing property prices caused some residents to believe that CPF investments in their neighborhoods would lead to gentrification and the eventual displacement of them and their neighbors. Alfonso Espino, a community activist in a predominantly Latino neighborhood in north Denver, responded to a New York Times interview by saying, “It’s always just felt more like it’s a whole front. Not for us, you know. It is for the people that are coming” when asked about potential CPF investments in his area (Penney, 2020). The city’s long legacy of historical injustices cannot be fixed overnight, and it must work diligently to regain the trust of its disenfranchised residents. This analysis shows that including certain economic protections, such as affordable housing requirements, may help the city on its journey towards social and environmental equity.
6.4: Limitations
The most significant limitation that restricts the interpretation of the regression results is the five-year average nature of the data. The United States Census Bureau releases five-year averages for smaller geographical areas because they are based on smaller sample sizes and carry the risk of having large margins of error. Additionally, the Bureau cites privacy issues as reasons for restricting access to some data. However, structuring the pre and post-treatment periods in a way that none of the years within the five-year averages overlap at least allows the analysis to ensure that the impact of the independent treatment variable is not lost within the data. Ideally, single-year estimates for each census tract would be utilized to run the same analysis.
Identifying common pre-treatment trends is complicated because the data is subject to a relatively high margin of error. Particularly among the dependent variables of median gross rent as a percentage of household income and the share of single-occupancy vehicle commuters, the data points are so sensitive that even one skewed year may cause complications verifying the common trends assumption. These two variables generally follow similar pre-treatment trends. However, the sensitivity of the sample collection results in insignificant results for all
Testing multiple hypotheses can sometimes complicate the interpretation of regression output results. When multiple hypotheses are tested, as in this analysis, there is a possibility that at least one of the results will be significant due to chance. The probability of observing at least one significant due to chance in this analysis is:
𝑃(𝑎𝑡 𝑙𝑒𝑎𝑠𝑡 𝑜𝑛𝑒 𝑠𝑖𝑔𝑛𝑖𝑓𝑖𝑐𝑎𝑛𝑡 𝑟𝑒𝑠𝑢𝑙𝑡) = 1 − 𝑃(𝑛𝑜 𝑠𝑖𝑔𝑛𝑖𝑓𝑖𝑐𝑎𝑛𝑡 𝑟𝑒𝑠𝑢𝑙𝑡𝑠)
= 1 (1 − 0. 05)4
= 0.1854, an 18.54% chance of observing a falsely significant result. A future analysis that accounts and adjusts for this possibility would add additional credibility to the research design.
6.5: Potential next steps:
The study of the impacts of transit-oriented development is a relatively new field of research, and there are many opportunities for further study. There are several ways to augment this analysis to understand the results better. For example, access to data that differentiates between poor and wealthy individuals, as in the Balboni paper. We see median income decreases in treatment tracts compared to control tracts, but the exact source of this decrease is difficult to pinpoint. It could be that wealthier residents move away as transit-oriented development takes place and that TOD causes the opposite of gentrification. Conversely, it could be that the improved transportation and affordable housing options directly attract lower-income individuals who benefit from these investments the most. The ability to individually tract people who move to and from treatment tracts would assist in this analysis.
From a data perspective, this analysis could be improved by having annual data estimates instead of five-year averages. Although it was possible to isolate the pre and post-treatment effects by excluding values where these two time periods overlapped, the treatment effect may be somewhat diluted. Excluding overlapping periods required eliminating hundreds of potential data points, which annual estimates would solve—augmenting the data set with additional years and furthering the study's credibility. Since this analysis deals with development and neighborhood trends, it would be ideal to revisit this study in 5 to 10 years to understand better how the results hold up over time.
Conducting a similar analysis with affordable housing projects along significant bus routes would also be exciting and could lead to a larger dataset. Light rail stations serve a different purpose than bus stops which could impact the surrounding area in unique ways.
However, bus stations tend to be much smaller, and the impact of bus stop transit-oriented development may be more difficult to isolate than rail stations.
Running this analysis with information about combined rent and transportation burdens would provide valuable insight into the broader economic effects of transit-oriented development on households. One of the primary goals of the Denver Transit-Oriented Development Fund was to assist Denverites who were spending more than 50% of their monthly income on transportation and housing combined. These two categories are consistently the most significant monthly expense for the median American household. Therefore, implementing a policy that lowers rental burden or transportation cost burden independently is not as desirable as a policy that lowers both of these expenditure burdens at the same time.
Finally, adding an investigation into the total population changes for every tract to understand if the shrinking share of Hispanics is due to a displacement of Hispanic individuals or just a faster-growing non-Hispanic population. These two outcomes warrant very different policy responses from an equity point of view. For example, suppose the share of Hispanics is decreasing due to a rapid influx of non-Hispanic individuals, but not because of the displacement of current residents. In that case, policy should focus on improving equitable access to new opportunities in the area. On the other hand, suppose the shrinking share of the Hispanic population is indeed a result of displacement. In that case, city officials should shift their emphasis toward finding ways to promote development that does not come at the expense of long-time residents. This could be by introducing rental protection for long-term residents to ensure that they are not priced out of the market by transit-induced gentrification. This is particularly important in cities like Denver, Austin, and Miami, which have historically faced problems relating to this issue.