Event Title

An econometric analysis of suburban park access in the United States

Advisor(s)

Patrick Kearney; Illinois Mathematics and Science Academy

Discipline

Behavioral and Social Sciences

Start Date

21-4-2021 9:30 AM

End Date

21-4-2021 9:45 AM

Abstract

This project examines the correlation between economic income and park availability for suburban areas of the United States. As economic differences become more drastic, the effects of income on lives becomes increasingly important, especially for less considered, but still important and appreciated aspects of life, like park accessibility. To do this, this project uses the R programming language, data gathered from the United States census, as well as data gathered from open park datasets. Regions are divided by zip code, meaning the socioeconomic status for any zip code is an average, and data is not compiled on the individual level. Only suburban areas are used, as space for parks is a larger obstacle in cities than in suburban areas; rural areas are unlikely to have parks at all, which would skew the results. Still, there is enough socioeconomic spread in suburbs to provide legitimate and useful data. Additionally, because parks are likely built based on the number of people who would use them, population density of the area is taken into account. The purpose of this project is to reflect on the tendencies and patterns of government spending on areas with lower income levels.

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Apr 21st, 9:30 AM Apr 21st, 9:45 AM

An econometric analysis of suburban park access in the United States

This project examines the correlation between economic income and park availability for suburban areas of the United States. As economic differences become more drastic, the effects of income on lives becomes increasingly important, especially for less considered, but still important and appreciated aspects of life, like park accessibility. To do this, this project uses the R programming language, data gathered from the United States census, as well as data gathered from open park datasets. Regions are divided by zip code, meaning the socioeconomic status for any zip code is an average, and data is not compiled on the individual level. Only suburban areas are used, as space for parks is a larger obstacle in cities than in suburban areas; rural areas are unlikely to have parks at all, which would skew the results. Still, there is enough socioeconomic spread in suburbs to provide legitimate and useful data. Additionally, because parks are likely built based on the number of people who would use them, population density of the area is taken into account. The purpose of this project is to reflect on the tendencies and patterns of government spending on areas with lower income levels.