# RECORD 0893ce95f4ec80e891e9cf83dfb029d633e4a22d
# TITLE: HEDONIC REGRESSION ANALYSIS IN DETERMINING THE EFFECT OF GREEN ON HIGH RISE RESIDENTIAL
# YEAR: 2022.0  VENUE: PLANNING MALAYSIA  DOI: 10.21837/pm.v20i21.1114
# AUTHORS: Lizawati Abdullah; T. Mohd
# PAGES: 11  CANDIDATE TABLE PAGES (1-based): [8]
# ABSTRACT: In predicting house price, there are many influential variables, and each variable is identified as a price determinant. Theoretically, variables are divided into categories, namely locational and neighbourhood attribute, structural attribute, time attribute, and environment attribute. Green element is one of the attributes as describe under environment category. The attribute is important as other variables which significantly explained how people willing to pay intangible variable. The relationship between property price and attribute needs to be examined to understand the influence of the green element on property price. Thus, this research attempts to demonstrate the independent variables correlated to the house price, including the green variable, by using hedonic regression analysis. Hedonic regression analysis is a well-known approach in determining the relationship between two or more variables. Green element represents the green-rated obtained by the housing scheme as evidence that the building possesses sustainable characteristics. The cost of green is relatively high than a conventional building. A dataset of 934 house price transactions with 14 variables was analysed. From the analysis, it is concluded that green has a significant effect on the house price. The result was interpreted by the β coefficient of 0.065 explained in hedonic regression analysis. It signifies that green can add premium to the house price. House price results from multiple determinants represented by house attributes and the findings confirm that one of the environment attributes do give effect on the house price in Malaysia property market.


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1 Senior Lecturer at Universiti Teknologi MARA Perak Branch. Email: lizaw327@uitm.edu.my 
PLANNING MALAYSIA: 
Journal of the Malaysian Institute of Planners 
VOLUME 20 ISSUE 2 (2022), Page 310 – 320 
HEDONIC REGRESSION ANALYSIS IN DETERMINING THE 
EFFECT OF GREEN ON HIGH RISE RESIDENTIAL 
 
Lizawati Abdullah1, Thuraiya Mohd2 
 
1,2Department of Built Environment Studies and Technology,  
Faculty of Architecture, Planning and Surveying,  
UNIVERSITI TEKNOLOGI MARA, PERAK BRANCH, MALAYSIA 
 
 
Abstract 
 
In predicting house price, there are many influential variables, and each variable 
is identified as a price determinant. Theoretically, variables are divided into 
categories, namely locational and neighbourhood attribute, structural attribute, 
time attribute, and environment attribute. Green element is one of the attributes 
as describe under environment category. The attribute is important as other 
variables which significantly explained how people willing to pay intangible 
variable.  The relationship between property price and attribute needs to be 
examined to understand the influence of the green element on property price. 
Thus, this research attempts to demonstrate the independent variables correlated 
to the house price, including the green variable, by using hedonic regression 
analysis. Hedonic regression analysis is a well-known approach in determining 
the relationship between two or more variables. Green element represents the 
green-rated obtained by the housing scheme as evidence that the building 
possesses sustainable characteristics. The cost of green is relatively high than a 
conventional building. A dataset of 934 house price transactions with 14 variables 
was analysed. From the analysis, it is concluded that green has a significant effect 
on the house price. The result was interpreted by the β coefficient of 0.065 
explained in hedonic regression analysis. It signifies that green can add premium 
to the house price. House price results from multiple determinants represented by 
house attributes and the findings confirm that one of the environment attributes 
do give effect on the house price in Malaysia property market. 
 
 
Keywords: House price, green, house variables, hedonic regression analysis 
 
 


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PLANNING MALAYSIA 
Journal of the Malaysia Institute of Planners (2022) 
 
 
317  
© 2022 by MIP 
Table 5: The model 
Independent 
variables 
Unstandardized Coefficients 
t 
Sig. 
B 
Std. Error 
(Constant) 
9.084 
.105 
86.147 
0.000 
GEORGETOWN 
.067 
.029 
2.322 
.020 
OTHER TOWN 
.097 
.022 
4.346 
.000 
2020 
-.131 
.024 
-5.523 
.000 
2019 
-.077 
.023 
-3.347 
.001 
2018 
-.051 
.027 
-1.847 
.065 
2017 
-.058 
.026 
-2.226 
.026 
TENURE 
.022 
.029 
.745 
.456 
NUMBER OF ROOMS 
-.003 
.014 
-.197 
.844 
HILLVIEW 
-.056 
.026 
-2.131 
.033 
SEAVIEW 
.155 
.023 
6.651 
.000 
FACILITIES 
-.167 
.020 
-8.374 
.000 
SECURITY 
.176 
.039 
4.529 
.000 
OCCUPANCY  
-.077 
.018 
-4.304 
.000 
DEVELOPER  
.180 
.017 
10.535 
.000 
GREEN -GBI 
.065 
.033 
1.987 
.047 
LOGSIZE 
-.080 
.020 
-3.979 
.000 
LOGLEVEL 
.016 
.010 
1.564 
.118 
LOGAGE 
.007 
.019 
.393 
.694 
a. Dependent Variable: LOGPRICE PSM 
Sources: Author’s research (2021) 
 
Table 5 shows the ∝  and 𝛽 coefficient value. Green-GBI variable 
indicates +0.065 coefficients. Other variables such as developer and security 
indicate high coefficient value of 0.180 and 0.176 respectively. All the transform 
variables that were included in the model together with the log form variable, i.e 
floor size, floor level and age of building.  A linear combination form to explain 
𝛽 coefficient is as follows. 
 
LN (Price per square metre) = 
9.084 +0.067(GEORGETOWN) +0.097(OTHERTOWN) -0.131(Y_2020)  
-0.077(Y_2019) -0.051(Y_2018) -0.058(Y_2017) +0.22(TENURE) 
-0.003(ROOMS) -0.056(HILLVIEW) +0.155(SEAVIEW)  
-0.167(FACILITIES) +0.176(SECURITY) -0.077(OCCUPANCY) 
+0.180(DEVELOPER) +0.065(GREEN-GBI) -0.080(LOGSIZE) 
+0.016(LOGLEVEL) +0.007(LOGAGE) 


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Lizawati Abdullah & Thuraiya Mohd 
Hedonic Regression Analysis in Determining the Effect of Green on House Price 
 
© 2022 by MIP 
318 
From this regression analysis, the selection of the GBI certificate 
variable suggests the positive sign of the variable. This shows evidence of support 
by other literature (Evangelista et al., 2019)(Li Zhang et al., 2017)(Jayantha & 
Man, 2013)(Fesselmeyer, 2018)(Limao Zhang et al., 2018) in which the 
discussion reported that there are differences in prices if the property is green or 
GBI certified increased. The beta coefficient is 0.065 and this associates with the 
p value. Therefore, the model obviously shows there is a statistically significant 
change in value if the property is located at Timur Laut District if it is certified 
green. Out of the 18 control variables entered in the model, 13 variables were 
statistically significant. Further, it can be defining trough t values of the 
independent variables.  
 
CONCLUSION 
This paper analyses the green certificate effect on condominium price in Timur 
Laut District in Penang Island. The analysis uses database which comprises of a 
combination of several data including information from condominium 
transaction sale data. The data was compiled and extracted by NAPIC, and it is 
to be used for the purpose of valuation and research related to property. NAPIC 
is an organisation responsible to promote and provide information on property 
market in Malaysia.  
From the analysis done, it is found that green certification relatively 
gives an impact on property price. The percentage of premium if compared to 
non-certified building is about 6.5 per cent. The result is supported by a valuer 
who also estimated about 5-10 of price increment if condominium in Penang is 
green (Abdullah et al., 2018). Hence, the effect might vary according to the 
locality. Property market as well as green building should be explored differently 
in their local context. Even though most of the time green building is associated 
with high cost of construction, but the value of green is not only about cost. It 
represents the market, the demand, and the economics of the property. Value can 
be influenced by other factors.  With more incentive, knowledge and promotion 
given by the government, green development can become the upcoming trend 
and demand.  
Specifically, the contributions of these findings can be explained in 
several contexts. First, this research adds “green” into the residential hedonic 
pricing literature especially from the perspective of local context. It is estimated 
that green can become a common consideration in the hedonic research paradigm. 
Next, this study encourages additional research on the effects of green 
development on housing sector. The results of this research indicated a positive 
and statistically significant premium for transactions with green as a housing 
feature. The findings from this study are parallel with most of green effect studies 
done previously. The biggest challenge here is to educate public on the awareness 
of sustainability and green development. Empirical studies have shown