Full metadata
Title
Forecasting the 85281 Residential Rental Property
Description
The listing price of residential rental real estate is dependent upon property specific attributes. These attributes involve data that can be tabulated as categorical and continuous predictors. The forecasting model presented in this paper is developed using publicly available, property specific information sourced from the Zillow and Trulia online real estate databases. The following fifteen predictors were tracked for forty-eight rental listings in the 85281 area code: housing type, square footage, number of baths, number of bedrooms, distance to Arizona State University’s Tempe Campus, crime level of the neighborhood, median age range of the neighborhood population, percentage of the neighborhood population that is married, median year of construction of the neighborhood, percentage of the population commuting longer than thirty minutes, percentage of neighborhood homes occupied by renters, percentage of the population commuting by transit, and the number of restaurants, grocery stores, and nightlife within a one mile radius of the property. Through regression analysis, the significant predictors of the listing price of a rental property in the 85281 area code were discerned. These predictors were used to form a forecasting model. This forecasting model explains 75.5% of the variation in listing prices of residential rental real estate in the 85281 area code.
Date Created
2019-05
Contributors
- Schuchter, Grant (Author)
- Clough, Michael (Thesis director)
- Escobedo, Adolfo (Committee member)
- Industrial, Systems & Operations Engineering Prgm (Contributor)
- Barrett, The Honors College (Contributor)
Topical Subject
Resource Type
Extent
17 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2018-2019
Handle
https://hdl.handle.net/2286/R.I.52199
Level of coding
minimal
Cataloging Standards
System Created
- 2019-04-02 12:00:12
System Modified
- 2021-07-15 10:18:27
- 3 years 4 months ago
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