Exploring the Relationship Between Yearly Incomes and Commute Times: A Study in Boulder, Colorado

This study delves into an intriguing correlation between the yearly incomes and the commute time in Boulder, Colorado, aiming to find an unusual correlation that illuminates socioeconomic dynamics within our community. Leveraging datasets that were sourced from the US Census Bureau’s Census API for the year 2021, this research focuses on income brackets ranging from under 10k to over 200k, which will be compared against commute durations spanning from less than 5 minutes to over 90. Employing logarithmic scales for better precision, this study utilizes bar charts to visually represent the data and discern potential correlations. Observations indicated a discernible relationship between higher incomes and shorter commute times which in turn may show citizens socioeconomic status influencing their transportation choices and residential locations.

Introduction

Boulder, Colorado, known for its interesting socio economic landscape encompassing both low income students and post grad residents as well as its higher income demographics, presents an intriguing case study for examining the intersection between financial prosperity and commuting patterns. With the advent of 20021 marking a pivotal point in our history as communities gradually transitioned back to in-person work post COVID, the study turns its sights on this opportune moment to examine the interplay between yearly incomes and commute durations. The underlying hypothesis before the study took place posits an inverse correlation, where higher incomes correlate to shorter commute times, showing both economic capacity and preferences of residents. This could be due to the fact that as people get nicer jobs, they make more money, which allows them to move to nicer areas that are in locations they want, as well as being able to have the means to get to work any way they want. Typically this involved purchasing their own vehicles rather than having to walk, bike, or take public transportation.

Methods

To study the potential in this hypothesis, the expansive dataset within the Census API provided by the Census Bureau was utilized to develop insights on Boulder’s demographic and Economic makeup. By segmenting income data into several discrete brackets ranging from just under 10k to over 200k, as well as commute times from under 5 minutes to over 90, the analysis attempts to examine the shapes of the graphs and how they compare to each other. Bar charts seemed like the best way to achieve this goal because even if they didn’t have the same number of points, the relative graph shapes should be enough to tell. Additionally, logarithmic scales were employed to each of the graphs. This was to allow a proper examination of shapes where smaller percentage differences didn’t matter as much.

Findings

This initial look at the data suggests that people with higher incomes tend to have shorter commute times.

We can see when examining these graphs that there are both more high income jobs and lower commute times. This supports the idea that there’s a correlation between having more money and spending less time traveling to work. It was noticed that there are more high-income families in Boulder, and they seem to have shorter commute times which tells us that people who earn more money might choose to live closer to where they work. This connection found between higher incomes has important implications. It suggests that where people live and how they get to work are influenced by how much money they, or their family makes. This additionally may influence urban planners and policymakers at local government levels. By understanding these connections, we can work towards creating cities where everyone has equal access to transportation and affordable housing.

Conclusion

This study sheds light on the interesting correlation between familial incomes and resident commutes in Boulder, Colorado. We can see that people with higher most likely spend less time commuting, possibly because they can afford to live closer to work. If this research were to continue it would be important to look into several other factors. The first would be to see how efficient the transit systems are and the average distance of residents from their jobs. It would be interesting to see commutes in larger communities that have very spread out roads and businesses. It would also be interesting to see these statistics in other college towns around the country. For some, much less of the community is made up of college students and in others it is the majority of the population. The difference in these factors would definitely change the results.