# RECORD b34f2af5cff586af9757e0b66b7191bb692373e4
# TITLE: Determinants of New Condominium Prices near MRT Orange Line Stations: Case study of Estimating Housing Affordability in Bangkok, Thailand
# YEAR: 2025.0  VENUE: Hong Kong Journal of Social Sciences  DOI: 10.55463/hkjss.issn.1021-3619.64.29
# AUTHORS: Pornraht Pongprasert
# PAGES: 13  CANDIDATE TABLE PAGES (1-based): [9]
# ABSTRACT: This research aims to analyze the factors influencing the pricing of condominium projects along the Mass Rapid Transit (MRT) Orange Line, an electric train expected to start operations in 2025. As the main heavy rail line connecting the Eastern Bangkok suburbs with the city’s New Central Business District (New CBD), the Orange Line has significant implications for urban development. To promote land development opportunities, Bangkok’s city plan has undergone changes along the Orange Line corridor, particularly on the Ramkhamhaeng Road, which is anticipated to drive up land prices.This study examines how condominium prices may fluctuate when various factors are considered, such as proximity to MRT stations, main roads, expressway access points, private facilities, operator reliability, and the cost of common areas. The research equips real estate developers with a comprehensive understanding of these determinants to guide project development and pricing strategies aligned with market conditions. Condominium buyers can leverage accurate pricing information to make informed decisions, while real estate investors can incorporate these insights into their investment strategies. Additionally, the Revenue Department could use the data to inform land tax policies. The hedonic price model was used to determine the factors influencing the prices of condominiums along the Orange Line. The research samples are 28 brand-new condominium properties that are located only one kilometer away from the MRT stations of the Orange Line, and most of them are new condominiums that were constructed in less than 5 years. A total of 17 factors, grouped into three categories—locational, physical, and neighborhood characteristics—were evaluated using regression analysis. The findings reveal that three key factors significantly impact the prices of condominium units: floor level, distance from the train station, and distance from department stores.


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香港社會科學學報 
HONG KONG JOURNAL OF SOCIAL SCIENCES 
最新第64 期 (2024 年秋/冬季) 
  Vol. 64 Autumn/Winter 2024 
  Copyright: © 2025 by the authors. HKJSS 
This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution 
License (https://creativecommons.org/licenses/by-nc-nd/4.0/) 
Available online at www.hkjoss.com 
Research article
 https://doi.org/10.55463/hkjss.issn.1021-3619.64.29 
Determinants of New Condominium Prices near MRT Orange Line Stations: 
Case study of Estimating Housing Affordability in Bangkok, Thailand 
Pornraht Pongprasert1 
 *, Rungsee Benjaanunphong2 
1Department of Real Estate Business, Thammasat Business School, Thammasat University, Thailand 
2Pricewaterhouse Coopers ABAS Ltd., Bangkok, Thailand 
* Correspondence: pоrnrаht@tbs.tu.ac.th
Abstract:
This research aims to analyze the factors influencing the pricing of condominium
projects along the Mass Rapid Transit (MRT) Orange Line, an electric train expected
to start operations in 2025. As the main heavy rail line connecting the Eastern
Bangkok suburbs with the city’s New Central Business District (New CBD), the
Orange Line has significant implications for urban development. To promote land
development opportunities, Bangkok’s city plan has undergone changes along the
Orange Line corridor, particularly on the Ramkhamhaeng Road, which is anticipated
to drive up land prices. This study examines how condominium prices may fluctuate
when various factors are considered, such as proximity to MRT stations, main roads,
expressway access points, private facilities, operator reliability, and the cost of
common areas. The research equips real estate developers with a comprehensive
understanding of these determinants to guide project development and pricing
strategies aligned with market conditions. Condominium buyers can leverage
Keywords:  
Central Business District (CBD),  
Mass Rapid Transit (MRT) Orange 
Line,  
condominium prices,  
housing affordability,  
Bangkok  
Article History: 
Received: October 14, 2024 
Revised: November 12, 2024 
Accepted: January 15, 2025 
Published: February 6, 2025 


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  327 
kilometers, the closest was 150 meters from Police 
Station and the farthest was 4.2 kilometers, the closest 
was 120 meters from Fire Station and the farthest was 
4 kilometers, the closest was 120 meters from Fire 
Station and the farthest was 4 kilometers, the minimum 
number of units was 196 units and the maximum 
number of units was 1,942 units, the minimum number 
of floors was 8 floors and the maximum number of 
floors was 61 floors, the minimum number of carpark 
was 30 percents and the maximum number of floors 
was 55 percents, facilities include a fitness center, 
swimming pool, and co-working space and not 
include, the project owner is a listed company and a 
non-listed company, the minimum fees was 33 baht 
per sq.m. per month (around 0.95 USD per sq.m. per 
month)  and the maximum fees was 60 baht per sq.m. 
per month (around 1.72 USD per sq.m. per month), the 
Floor Area Ratio (FAR) in the land maps range from 
2.5 to 7. 
Table 2. Summary of descriptive data (compiled by the authors) 
No. 
Variable codes (unit) 
Mean 
S.D.
Min 
Max 
1 
Dist. Train (m.) 
324.64 
317.25 
0.00 
950.00 
2 
Dist. Road (m.) 
65.54 
188.22 
0.00 
900.00 
3 
Dist. Exp (m.) 
2,378.93 
1,682.80 
280.00 
6,000.00 
4 
Dist. New CBD (m.) 
7,397.50 
6,050.26 
230.00 
20,700.00 
5 
Dist. Dep (m.) 
1,143.21 
1,183.19 
150.00 
4,500.00 
6 
Dist. Con (m.) 
262.50 
247.81 
0.00 
900.00 
7 
Dist. Market (m.) 
933.93 
648.93 
300.00 
3,400.00 
8 
Dist. Hospital (m.) 
2,204.29 
1,200.21 
70.00 
4,700.00 
9 
Dist. Police (m.) 
2,691.07 
960.91 
150.00 
4,200.00 
10 
Dist. Fire (m.) 
2,332.88 
949.70 
120.00 
4,000.00 
11 
No. Unit (units) 
991.54 
562.68 
196.00 
1,942.00 
12 
No. Floor (floors) 
27.04 
13.48 
8.00 
61.00 
13 
Car Park (percentage) 
43.89 
7.93 
30.00 
55.00 
14 
Facilities 
0.93 
0.26 
0.00 
1.00 
15 
Brand 
0.71 
0.46 
0.00 
1.00 
16 
Fee (the baht) 
47.50 
8.88 
33.00 
60.00 
17 
FAR 
5.46 
1.41 
2.50 
7.00 
4.2 
Empirical Results 
To determine condominium pricing, the researcher 
collected data on three variables: the number of floors 
and distance from the MRT station. and the distance 
from the retail centers. Using the ordinary least squares 
method (OLS), a sample of 28 projects was analyzed 
to determine the statistical significance of each 
variable. The following equation was used in this 
study:  
Price = C + β1Floor + β2Dist. Train + β3Dist. Dep 
Table 3. The result of the regression analysis (compiled by the authors) 
Variables 
Coefficient 
t 
VIF 
Un. Std. B 
Std. Error 
Std. B 
Constant 
-862,990.71
867,065.95 
-1.00*
1.03 
Physical characteristics 
of buildings 
Floor 
113,861.30 
24,185.98 
  0.57 
  4.71** 
Location Features 
Dist. Train 
4,313.71 
1,019.81 
   0.51 
   4.23** 
1.01 
Dist. Dep 
640.05 
274.31 
   0.28 
  2.33* 
1.02 
Note: R-Square = 0.66, Adjusted R-Square = 0.62; F = 5.44, Durbin-Watson (D.W.) 2.30 
*p-value < 0.05, **p-value < 0.01
Based on the data analysis findings in accordance 
with Table 3, the research results of the variables 
influencing condominium prices reveal hidden costs 
that have an impact on the price of condominiums in 
Orange Line real estate developments. The predicted 
R-Square value of the linear model for this instance is
0.66 or 66.1%, reliable at explaining changes in price.
It can be described as the price of a condominium
increases by 113,861.30 baht (3,265.03 USD) as the
number of floors increases by one. The project’s
distance from the MRT station was one meter longer 
but not more than 1 km, which resulted in a 4,313.71 
baht (123.70 USD) rise in the price of the 
condominium. The price of the condominium 
increased by 640.05 baht (18.35 USD) because of a 
one-meter increase in the distance between the 
department store and the condominium. This can be 
expressed as follows:  


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Pongprasert & Benjaanunphong. Determinants of New Condominium Prices near MRT Orange Line’s Stations: Case study of Estimating the 
Housing Affordability in Bangkok, Thailand, Vol. 64 Autumn/Winter 2024 
Price = -862,990.71 + (β1=113,861.30) Floor + 
(β2=4,313.71) Dist. Train + (β3=640.05) Dist. Dep  
In addition, condominium prices can be estimated 
using the following equation, which substitutes for the 
average of several factors: 
Price = -862,990.71 + 113,861.30 (27.04) + 4,313.71 
(324.64) + 640.05 (1,143.21) 
The price = 4,347,933.22 baht (124,679.07 USD) 
This can be explained by the fact that condominium 
Projects along the Orange Line generally have 27.04 
floors, are located 324.64 meters from the MRT 
station, and are located 1,143.21 meters from the 
department stores. The price per unit is expected to be 
4,347,933.22 baht (124,679.07 USD). The exchange 
rate was obtained from the Bank of Thailand (BOT) on 
November 25, 2024, : :1 USD = 34.8730.  
Furthermore, the Durbin-Watson (D.W.) value is 
2.30, falling between 1.5 and 2.5, meaning that 
autocorrelation is not an issue for this linear model 
(Durbin and Watson, 1951).  
The level or magnitude of the correlation can be 
determined by examining the data in the Correlation 
Analysis table, which studies the relationship between 
two or more variables. If the correlation coefficient is 
closer to 1 or 1, indicating a strong degree of 
relationship, the number of correlation coefficients is 
used. On the other hand, if the value is around zero, it 
indicates little to no relationship. When the correlation 
coefficient for every subject was less than 0.8, it was 
considered acceptable to conduct additional analyses.  
The Variance Inflation Factor (VIF) estimator's 
variance, which is used to determine the severity of the 
issue, is displayed in the table based on the data. 
Because none of the three exceeded 10, they all fell 
within the set of parameters that could have been used 
in the research.  
Compared to previous studies, this study found the 
same findings as those of Lind and Hwang (2003) and 
Thamrongsrisook (2011), that the number of floors in 
the condominium project has a positive impact on the 
prices of condominium units. Similarly, the key 
research outcomes of Des Rosiers et al. (1996), Bible 
and Hsieh (2011), and Kulkosa (2016) are that the 
significant factor of the distance between the 
condominium project and the MRT station affects the 
price of the condominium. In addition, this research 
outcome found a similar significant factor of distance 
between the condominium project and department 
store, which affects the price of condominium units 
(Kulkosa, 2016). 
5. Conclusion and Recommendations
The growth in condominium prices along the mass
transit station in Bangkok, Thailand, is continuously 
increasing. Prices tend to grow rapidly, and they are 
difficult to predict, especially the prices of 
condominiums in the proximity of urban rail transit 
stations in Bangkok CBD. If they are much higher, 
fewer people can afford to rent or purchase to live near 
the transit stations. This study aims to identify the 
factors affecting the prices of condominiums along the 
MRT Orange Line, the newest urban transit line in 
Bangkok. In the research outcome, it is found that 3 
variables affecting to the price of condominiums along 
the MRT Orange Line. These are the floor levels in the 
condominium project, the distance between the 
condominium project and MRT station, and the 
distance between the condominium project and 
department store. All of these factors have a positive 
impact on condominium prices.  
If condominiums along the MRT Orange Line have 
a lower number of floors (low-rise condominium 
projects), are not located at the closest distance to the 
MRT station (but within walkable distance), and are 
located farther from the department store, the price 
would be cheaper, and more people can afford the 
price of residences located near MRT stations.  
Additionally, real estate developers interested in 
developing high-rise residential projects along the 
Orange Line train, such as Rama 9, Ramkhamhaeng, 
Lam Sali, and Min Buri, can use these research 
findings as a guide to determine the preliminary selling 
price and conduct marketing strategy analysis. 
Planning includes determining the best site for the 
project, calculating how many stories the building will 
need, 
and 
effectively 
marketing 
and 
pricing 
condominiums to meet demand. Customers who want 
to buy condominiums near the Orange Line train for 
speculative purposes or habitation will benefit from 
this. The research outcomes can be used as a basis for 
choosing a project that best fits their financial 
situation, and can provide them with the current 
market prices for the condominiums along the Orange 
Line train, allowing them to compare them properly to 
other projects. The ability to use the data to analyze 
trends in the reasonableness of the company's profits 
through the costs that the company has expected to 
invest and the sales revenue that the company expects 
to receive is advantageous to investors who spend 
shares of real estate development companies that have 
plans to invest in real estate projects along the Orange 
Line. To collect land taxes, the Revenue Department 
will benefit from using the data to examine the value 
of condominiums along the Orange Line. 
Authors’ Contributions 
Conceptualization, 
P.P.; 
methodology, 
P.P.; 
software, R.B.; validation, P.P.; formal analysis, P.P.; 
investigation, C.N.; resources, A.C.; data collection, 
R.B.; data curation, R.B.; writing—original draft
preparation, all authors contributed equally; writing—
review 
and 
editing, 
P.P.; 
visualization, 
R.B.;
 328