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An economic valuation of urban green spaces in Kuala Lumpur city


Citation

A. Samad, Nur Syafiqah and Abdul Samad @ Iammi, Abdul Rahim and Mohd Yusof, Mohd Johari and Tanaka, Katsuya (2018) An economic valuation of urban green spaces in Kuala Lumpur city. Pertanika Journal of Social Sciences & Humanities, 26 (1). pp. 469-490. ISSN 0128-7702; ESSN: 2231-8534

Abstract

An economic value of urban green space (UGS) in Kuala Lumpur (KL) city is estimated in this study. A global model and a local model are formulated based on hedonic price method. The global and local models were analysed with an Ordinary Least Squares (OLS) regression and a Geographically Weighted Regression (GWR) respectively. Both the models were compares to see which model offered a better result. The results of OLS regression illustrated that Titiwangsa and Forest Research Institute Malaysia (FRIM) offer the highest economic value for model 2 and 3 respectively. The results of GWR determined that the economic value of an UGS can be analysed by the region. The GWR result revealed that FRIM provides high economic value to all the residential areas in KL city. However, the economic value of Titiwangsa is not valuable for the residential areas in KL city including Mont Kiara Pines, Jinjang Selatan, Segambut Garden, Bandar Menjalara and Taman Bukit Maluri. As a conclusion, even though Titiwangsa generates the highest economic value, it is only significant at certain residential areas as proved by the local model. In terms of model application, the local model performed better than the global model.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Design and Architecture
Faculty of Economics and Management
Publisher: Universiti Putra Malaysia Press
Keywords: Economic valuation; Geographically weighted regression model; Hedonic pricing model; Urban green space
Depositing User: Nabilah Mustapa
Date Deposited: 18 May 2018 03:43
Last Modified: 18 May 2018 03:43
URI: http://psasir.upm.edu.my/id/eprint/60248
Statistic Details: View Download Statistic

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