An Analysis on Influence of the Realty Rents Brought by Urban Railway System: A Case Study of Guangzhou MTR 2nd Line
Qingwen Deng
Abstract
Open-access reader
Qingwen Deng
Abstract
Open-access reader
This paper took 215 samples along the Guangzhou metro line 2 as an example to research the impact of urban rail system on realty rental prices. Method of hedonic price model was employed to calculate the range of subway influencing the surrounding reality rental. Three conclusions can be drawn up: 1) Metro has no influence on the samples of the central zone, while it contributes to surrounding realty rental prices increment of the peripheral area; 2) For the peripheral area, rental houses are influenced within 1.5 km. Realty rental prices have a significantly positive correlation with the distance of rental house away from the nearest subway station; 3) Average appreciation rate of monthly rents in the impact range reaches to 52.37%. Furthermore, residential monthly rents of house within 0.5 km, 0.5 - 1 km, and 1 - 1.5 km of subway stations are separately 56.9%, 49.2%, and 51% higher than monthly rents of houses located outside the affected area. Based on the result above, several points of tactic advice to generate higher return in rentals for investors and to rent a proper house for tenants have been put forward.
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This paper took 215 samples along the Guangzhou metro line 2 as an example to research the impact of urban rail system on realty rental prices. Method of hedonic price model was employed to calculate the range of subway influencing the surrounding reality rental. Three conclusions can be drawn up: 1) Metro has no influence on the samples of the central zone, while it contributes to surrounding realty rental prices increment of the peripheral area; 2) For the peripheral area, rental houses are influenced within 1.5 km. Realty rental prices have a significantly positive correlation with the distance of rental house away from the nearest subway station; 3) Average appreciation rate of monthly rents in the impact range reaches to 52.37%. Furthermore, residential monthly rents of house within 0.5 km, 0.5 - 1 km, and 1 - 1.5 km of subway stations are separately 56.9%, 49.2%, and 51% higher than monthly rents of houses located outside the affected area. Based on the result above, several points of tactic advice to generate higher return in rentals for investors and to rent a proper house for tenants have been put forward.
Key concepts: Economic rent, Renting, Hedonic pricing, Agricultural economics, Rental housing, Business, Range (aeronautics), Transport engineering