1# RECORD 0a4917c7f444817b4974629ac2f7d58ef2f993212# TITLE: The Hedonic Method in Evaluating Apartment Price: A Case of Ho Chi Minh City, Vietnam3# YEAR: 2020.0 VENUE: nan DOI: 10.13106/jafeb.2020.vol7.no6.5174# AUTHORS: H. Nguyen; H. Phan; T. Van Tran; Thang Kiem Viet Tran5# PAGES: 8 CANDIDATE TABLE PAGES (1-based): [6]6# ABSTRACT: The study examines factors affecting apartment prices in the real estate market of Ho Chi Minh City, Vietnam. The study uses primary data based on surveys of customers who have traded successfully, and collects transaction data from real estate trading companies that are the top investors in Ho Chi Minh City real estate market. The collected data include 384 observations in a total of 24 districts, detailing that each district surveyed on a minimum of four projects, each project carried out a survey on a minimum of four apartments. The survey collected 339 valid questionnaires for analysis and model testing. This study employs multivariate regression with the data of 339 observations. The research results reveal that five significant factors affect positively the price of apartments in Ho Chi Minh City – apartment area, toilet and bedroom, apartment floor, reference price, and apartment interior. Besides, there are three significant factors affecting negatively the price of apartments – next price trend, distance to city center, and potential building. From the results, the research proposes solutions in the pricing of apartments in the real estate market in Ho Chi Minh City – better information system, a real estate transaction index, and stricter management of small brokerage activities.789===== PAGE 1 (score 19, numeric-paren 0, table-words 3, var-words 13) =====1011Ha Minh NGUYEN, Hung Quoc PHAN, Tri Van TRAN, Thang Kiem Viet TRAN / 12Journal of Asian Finance, Economics and Business Vol 7 No 6 (2020) 517 – 524135171451715Print ISSN: 2288-4637 / Online ISSN 2288-464516doi:10.13106/jafeb.2020.vol7.no6.517171First Author and Corresponding Author. Associate Professor, 18President, Ho Chi Minh City Open University, Vietnam [Postal 19Address: 97 Vo Van Tan Street, Ward 6, District 3, Ho Chi Minh City, 20700000, Vietnam] Email: ha.nm@ou.edu.vn212Heineken 22Vietnam 23Brewery 24Limited 25Company, 26Vietnam. 27Email: phanquoc.hung@heineken.com 283Ho Chi Minh Youth Union, Ho Chi Minh City Open University, 29Vietnam. Email: tri.tv@ou.edu.vn304Lecturer, Faculty of Business Administration, Ho Chi Minh City Open 31University, Vietnam. Email: thang.tkv@ou.edu.vn32© Copyright: The Author(s)33This is an Open Access article distributed under the terms of the Creative Commons Attribution 34Non-Commercial License (http://Creativecommons.org/licenses/by-nc/4.0/) which permits 35unrestricted noncommercial use, distribution, and reproduction in any medium, provided the 36original work is properly cited.37The Hedonic Method in Evaluating Apartment Price: 38A Case of Ho Chi Minh City, Vietnam39Ha Minh NGUYEN1, Hung Quoc PHAN2, Tri Van TRAN3, Thang Kiem Viet TRAN440Received: March 07, 2020 Revised: April 04, 2020 Accepted: May 01, 202041Abstract42The study examines factors affecting apartment prices in the real estate market of Ho Chi Minh City, Vietnam. The study uses primary data 43based on surveys of customers who have traded successfully, and collects transaction data from real estate trading companies that are the top 44investors in Ho Chi Minh City real estate market. The collected data include 384 observations in a total of 24 districts, detailing that each 45district surveyed on a minimum of four projects, each project carried out a survey on a minimum of four apartments. The survey collected 46339 valid questionnaires for analysis and model testing. This study employs multivariate regression with the data of 339 observations. The 47research results reveal that five significant factors affect positively the price of apartments in Ho Chi Minh City – apartment area, toilet and 48bedroom, apartment floor, reference price, and apartment interior. Besides, there are three significant factors affecting negatively the price 49of apartments – next price trend, distance to city center, and potential building. From the results, the research proposes solutions in the 50pricing of apartments in the real estate market in Ho Chi Minh City – better information system, a real estate transaction index, and stricter 51management of small brokerage activities.52Keywords : Hedonic Method, Price, Apartments, Real Estate, Vietnam53JEL Classification Code: D04, D12, D40, D90541. Introduction55Ho Chi Minh City is the most densely populated city 56in Vietnam, and is also an important economic cultural 57and educational hub of the nation. Located in the transition 58zone between the Southeast and Southwest of Vietnam, 59Ho Chi Minh City today consists of 19 inner districts and 60five suburban districts, with a total area of 2,095.06 km². 61According to the 2014 census of the Bureau of Population 62Statistics, the city population had reached 7,955,000. 63However, if taking unregistered residents into account, the 64actual population of the city exceeds 10 million. Thanks 65to favorable natural conditions, Ho Chi Minh City now 66becomes an important transportation hub of Vietnam and the 67Southeast Asia, including roads, railways, waterways and 68airways. Ho Chi Minh City also plays the most crucial roles 69in the fields of education, media, sports and entertainment.70But Ho Chi Minh City is facing the problems any large 71city with high population growth rate has to deal with, which 72is housing demands for its residents in the city. However, the 73key challenge here, when real estate markets such as houses, 74apartments, rooms for rent, hotels, etc. can still provide 75for residents or tourists wishing to buy or rent, is that the 76investors or owners of these properties keep increasing their 77selling or renting rates excessively, following no rules at all. 78This causes great difficulties for those who really need to 79buy or rent houses and apartments, and intend to settle down 80permanently in Ho Chi Minh City. 81Besides, there were some scientific studies such as 82one by Cebula (2009), with 591 observations in Historic 83Landmark district during 2001-2005, assessing the impact 84of 24 independent variables on housing prices. Another 85research by Eda (2003) in Ankara, using cross data of 244 868788===== PAGE 6 (score 21, numeric-paren 13, table-words 1, var-words 6) =====8990Ha Minh NGUYEN, Hung Quoc PHAN, Tri Van TRAN, Thang Kiem Viet TRAN / 91Journal of Asian Finance, Economics and Business Vol 7 No 6 (2020) 517 – 5249252293Table 4: Results of OLS regression analysis94A95Model 196Model 297B98Significance99B100Significance101Constant102-0.1891030.267104-0.1571050.297106DIS107-0.059***1080.000109-0.065***1100.000111FLO1120.047***1130.0001140.031***1150.000116TIME-USED1170.0121180.3111190.0151200.162121RE-PRICE1220.565***1230.0001240.464***1250.000126FUR1270.324***1280.0001290.324***1300.000131VIEW1320.0561330.3971340.0451350.443136IN-ENVI137-0.0111380.875139-0.0201400.759141INVEST1420.0091430.8991440.0271450.666146LEG1470.0091480.897149-0.0711500.281151ULSTRUCTURE152-0.145**1530.044154-0.167***1550.009156TREND157-0.0831580.133159-0.091*1600.065161WCBR1620.379***1630.000164SQUA1650.016***1660.000167Significance (Sig.)168.000169.000170R171.910a172.929a173R Square174.829175.863176Adjusted R Square177.823178.8581794.3.1. Variable “ULSTRUCTURE” (potential works):180Model 1 has a statistical significance of 5% and Model 1812 is 1%, acting inversely to the initial expectation of 182the study. According to Ratchatakulpat et al. (2009), the 183larger the construction with supermarkets and surrounding 184infrastructure, the higher the total value of the apartment. 185However, this result reflects the true nature of the apartment 186market in Ho Chi Minh City when the owner of the 187apartment surveyed did not appreciate the presence of grand 188structures and construction in the future. The problems 189concerned buyers have: the status of legal documents, time 190of project completion, the size of the project leading to delay 191in compensation, etc.; all these make this factor not highly 192appreciated.1934.3.2. Variable “DIS” (distance from one project to the 194center):195Both models have a statistical significance of 1%, in line 196with the initial expectations. Even the study by Luc (2014) 197shows the same expected results. Among all the expectations 198of investors, speculators, or buyers in general, the distance 199from the project to the city center plays a key role in their 200purchase decision. Projects located near the center always 201attract buyers due to the convenience to commune, study, 202work, etc.2034.3.3. Variable “FLO” (number of floors of 204apartments):205Both models have a statistical significance of 1%, in line 206with the initial expectations. According to Rosen (1974), 207apartment floors tend to be proportional to the total value of 208real estate in the same project. In fact, when buying a house 209or a land plot, buyers do not care about this factor, but when 210they are involved in an apartment project, their interest in the 211higher floor will be taken into account. Basically, the higher 212the apartment is located, the greater its total value compared 213to the apartment in the same area and with the same view on 214a lower floor. One of the reasons is due to access to fresher 215air, better health, and more beautiful apartment view.2164.3.4. Variable “RE-PRICE” (reference price):217Both models have a statistical significance level of 1%, as 218initially expected. Nguyen et al. (2012) studied the issue of 219house renting price in Can Tho city. This clearly shows that 220the reference price before deciding to buy or sell apartments 221has a certain impact on the total value. If the initial reference 222223224===== PAGE 7 (score 17, numeric-paren 0, table-words 2, var-words 13) =====225226Ha Minh NGUYEN, Hung Quoc PHAN, Tri Van TRAN, Thang Kiem Viet TRAN / 227Journal of Asian Finance, Economics and Business Vol 7 No 6 (2020) 517 – 524228523229price of the apartment is high compared to others in the 230same segment, time and quality, then when making the next 231transaction, the apartment price will be calculated from the 232reference price onwards.2334.3.5. Variable “FUR” (apartment interiors):234Both models have a statistical significance of 1%, 235consistent with expectations and also with the research by 236Ratchatakulpat et al (2009). High-end projects, with large 237investment in luxurious branded interiors used in Grade 238A buildings, are always priced higher than projects in the 239mainstream segment with budget furnitures, purely invested 240for the purpose of accommodation. However, currently in 241Ho Chi Minh City, apartment price depends on many factors, 242and the interior of the apartment is only one of the factors 243that have a relative impact.2444.3.6. Variable “WCBR” (number of toilets and 245bedrooms):246Model 1 has a statistical significance of 1%, in line with 247the initial expectations of the study. The more toilets and 248bedrooms the apartment has, the higher the price of that 249apartment in the same project (applicable to all segments 250from mainstream to high-end) according to Melichar et al. 251(2009) and Baek et al. (2019). This is one of the essential 252factors or one of the criteria when choosing an apartment, 253along with other elements like kitchen, balcony, and laundry. 254The number of toilets and bedrooms plays an extremely 255important role: the more toilets and bedrooms, the higher the 256price of apartments.2574.3.7. Variable “SQUA” (apartment area):258Model 2 has a statistical significance of 1%, in line with 259the initial expectation. According to Hoang (2009), the larger 260an apartment is, the higher its price. This is completely true of 261the apartment market in Ho Chi Minh City. The apartments 262that have extra area for balcony, drying area, laundry or 263spacious walkways, will definitely make the apartment feel 264more comfortable and airy than those with small areas with 265fewer amenities.2664.3.8. Variable “TREND” (next price trend):267For Model 2, this variable has a statistical significance of 26810%, in contrast to the initial expectation of the research and 269survey by Luc (2009). This is a big difference between the 270two models when conducting the analysis. This is consistent 271with the study by Celbula (2009) in that if the trend of 272predicting the next price of an apartment increases, then the 273price of apartments will increase. The reason for the change 274that is contrary to the initial expectation, in the results of 275the survey and statistics, is that the number of respondents 276predicting the rise, a plateau or a fall is almost the same 277with the average value of 0.52; 50% of the respondents 278said the price will rise and 50% of the respondents said it 279will not. Respondents, who also carried out transactions in 280the secondary apartment project, did not have an accurate 281answer to the next trend for apartment prices in all segments, 282either mainstream or high-end at the time of the survey.283The following variables are not statistically significant in 284the model: “TIME-USED”, apartment time used; “VIEW”, 285view from the apartment; “IN-ENVI”, utilities provided by 286apartment projects; “INVEST”, reputation of the investor; 287“LEG”, the legal value of the apartment. Regression results 288are expressed in Table 4 as follow:2895. Conclusion and Policy Recommendations2905.1. Conclusion291The study examines the factors affecting apartment 292prices in Ho Chi Minh City, Viet Nam. The main method 293used was the Hedonic method, followed by multivariate 294regression, with data from 339 observations in Ho Chi Minh 295City. The research found five significant factors affecting 296positively the price of apartments in the Ho Chi Minh city 297real estate market: apartment area (+), toilet and bedroom 298(+), apartment floor (+), reference price (+), and apartment 299interior (+). Besides, there are three significant factors 300affecting negatively the price of apartments: price trend 301next (-), distance to city center (-), and potential building (-). 302Finally, the five remaining factors have no effect at all. 3035.2. Policy Recommendations304From the above results, the research proposes the 305following policies:306Completing the information system: Real estate 307transactions on the market today are aggregated and 308statistically analyzed at the trading floors, statistics from the 309investors, relevant ministries and agencies, etc. However, 310the key and important sets of information such as the exact 311transaction price of previous purchases, news of infrastructure 312planning, even the issues of compensation, are important 313aspects related to the transaction which cannot be accessed 314via any formal approaches. Therefore, the formulation of 315an information system covering all information relevant to 316the project and planning will help buyers a great deal when 317deciding to enter the transaction.318Building a real estate transaction index: Like the stock 319market, the real estate market needs a specific and practical 320parameter to assess the impact of the market daily, weekly, 321monthly and annually. Thereby, the buyer will have a more 322