Minnesota is the land of 10,000 lakes (technically 11,842 > 10 acres)! This bold proclamation can be seen everywhere from license plates to tourism pamphlets; it reveals how much water matters to the state on not only a commercial level, but as the very identity of the community. At the heart of Minnesota is the Twin Cities region. This study seeks to identify if a relationship exists between water quality and prices of property with proximity to lakefront. A hedonic pricing method (HPM) was implemented across 5,584 properties located on 75 lakes within the Twin Cities. HPM allowed for controlling of housing factors outside of water quality, while also providing a mechanism for comparing varying degrees of lake water quality against a housing baseline that omitted water features. The generalized least square estimator that was selected based on performance was trained against an extensively cleansed dataset that had both temporal dimensions flattened using aggregate with averages, and spatial dimensions reduced based on distance to water filters. Overall, the results depict a clear picture that there exists a statistically significant relationship between water quality and lakefront property prices in the Twin Cities region.

Last modified

• 12/17/2019

Creator

• David Charles Sedgwick

DOI

• https://doi.org/10.21985/n2-ksmj-d655

Subject

• Data Science

Keyword

• st. paul
• water
• property
• price, lakefront
• linear regression
• minneapolis
• python
• twin cities
• quality
• hedonic pricing method
• minnesota

Date created

• 2019

Related url

•  https://github.com/wickedsedg/PropertyPrices_WaterQuality_thesis

Resource type

• Masters Thesis

Rights statement

• In Copyright

License

• Creative Commons BY Attribution 4.0 International