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The value of park and green space as reflected by house prices in Taiwan

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  • Peddy PiYing Lai

Abstract

An attractive environment is likely to influence house price. We have high regard for the quality of living environment and living function. Especially, one of the crucial factors of choosing residence is the construct of public facilities that provide much service, such as park, school and green space. The aim of this study was to find the effect of parks and green space on housing price. The research used hedonic price model and geographic information system (GIS) to evaluate the effect of parks and green space in Kaohsiung in Taiwan.The result shows that housing price is determined by the effect of different characteristics. For parks and green space, the more close to parks and green space is, the higher total price is. When the transaction cases surround more parks, the value of property would go up. This situation leads to higher price on transaction cases. When land use zoning is non-residential kind with the purpose of residential type, the total price would raise. The total price of townhouse is higher than apartment, condominium and mansion. There is a negative correlation between building age and total price.However, there is a different result that the effect of difference distance of parks and green space within 500 meter radius on transaction cases. We found that the distance of parks and green space within 500 meter radius is not main factor on transaction cases. The existing and quantity of parks and green space is the main reason for transaction cases. We infer that this is the reason why the result did not fit the expected outcome. The housing price would become higher when it is close to green space

Suggested Citation

  • Peddy PiYing Lai, 2017. "The value of park and green space as reflected by house prices in Taiwan," ERES eres2017_353, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2017_353
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    References listed on IDEAS

    as
    1. Clifford Lipscomb & Michael Farmer, 2005. "Household diversity and market segmentation within a single neighborhood," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 39(4), pages 791-810, December.
    2. Joachim Zietz & Emily Zietz & G. Sirmans, 2008. "Determinants of House Prices: A Quantile Regression Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 37(4), pages 317-333, November.
    3. Kolbe, Jens & Wüstemann, Henry, 2014. "Estimating the value of Urban Green Space: A hedonic pricing analysis of the housing market in Cologne, Germany," SFB 649 Discussion Papers 2015-002, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
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    More about this item

    Keywords

    Geographic information system%28GIS%29; Hedonic Price Mode; Housing Price; Park and Green space;
    All these keywords.

    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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