scholarly journals FACTOR ANALYSIS ON HEDONIC PRICING MODEL ON OPEN SPACE AFFECTING THE HOUSING PRICE IN MELAKA AND SEREMBAN

2018 ◽  
Vol 16 (6) ◽  
Author(s):  
M. Zainora Asmawi ◽  
Mohammad Abdul Mohit ◽  
Norzailawati Mohd Noor ◽  
Alias Abdullah ◽  
Tuminah Paiman
Keyword(s):  
Factor Analysis ◽  
Open Space ◽  
House Price ◽  
Housing Price ◽  
Hedonic Pricing ◽  
Residential Area ◽  
Pricing Model ◽  
Kuala Lumpur ◽  
Hedonic Pricing Model ◽  
The Relationship

Open spaces near residential area often labelled as development constraint since each residential development must provide 10 percent of open space from the total acreage according to Malaysia planning guidelines. Kuala Lumpur has noticeable lost in open space in residential area and this issue might happen with other neighbourhood states such as Negeri Sembilan and Melaka. Therefore, the purpose of this study is to find the resident perspective on the importance of open space while purchasing their housing property. As such, the aim of the research is to study and examine the characteristics of relationship between public openspaces and residential property value using GIS-Hedonic pricing modelling in the selected residential area in Seremban and Melaka. To find the gist of this study, factor analysis has been used to sum the hedonic pricing model output. Seremban and Melaka respondents have chosen the Importance of the House attributes in influencing the house price and Importance of open space following factors in influencing the house price. The research examined the relationship between the open space and house price at selected area in Seremban and Ayer Keroh. As found in the literature reviews, it validates that the relationship established in a positive pattern.

scholarly journals FACTOR ANALYSIS ON HEDONIC PRICING MODEL ON OPEN SPACE AFFECTING THE HOUSING PRICE IN MELAKA AND SEREMBAN

2018 ◽  
Vol 16 ◽  
Author(s):  
M. Zainora Asmawi ◽  
Mohammad Abdul Mohit ◽  
Noorzailawati Mohd Noor ◽  
Alias Abdullah ◽  
Tuminah Paiman
Keyword(s):  
Factor Analysis ◽  
Open Space ◽  
House Price ◽  
Housing Price ◽  
Hedonic Pricing ◽  
Residential Area ◽  
Pricing Model ◽  
Kuala Lumpur ◽  
Hedonic Pricing Model ◽  
The Relationship

Open spaces near residential area often labelled as development constraint since each residential development must provide 10 percent of open space from the total acreage according to Malaysia planning guidelines. Kuala Lumpur has noticeable lost in open space in residential area and this issue might happen with other neighbourhood states such as Negeri Sembilan and Melaka. Therefore, the purpose of this study is to find the resident perspective on the importance of open space while purchasing their housing property. As such, the aim of the research is to study and examine the characteristics of relationship between public openspaces and residential property value using GIS-Hedonic pricing modelling in the selected residential area in Seremban and Melaka. To find the gist of this study, factor analysis has been used to sum the hedonic pricing model output. Seremban and Melaka respondents have chosen the Importance of the House attributes in influencing the house price and Importance of open space following factors in influencing the house price. The research examined the relationship between the open space and house price at selected area in Seremban and Ayer Keroh. As found in the literature reviews, it validates that the relationship established in a positive pattern.

scholarly journals A SPATIAL ANALYSIS ON GIS-HEDONIC PRICING MODEL ON THE INFLUENCE OF PUBLIC OPEN SPACE AND HOUSE PRICE IN KLANG VALLEY, MALAYSIA

2016 ◽  
Vol XLI-B8 ◽  
pp. 829-836
Author(s):  
A. M. Zainora ◽  
M. N. Norzailawati ◽  
P. Tuminah
Keyword(s):  
Open Space ◽  
Price Change ◽  
House Price ◽  
Value Added ◽  
Hedonic Pricing ◽  
Pricing Model ◽  
Hedonic Pricing Model ◽  
Public Open Space ◽  
Klang Valley ◽  
The Relationship

Presently, it is noticeable that there is a significant influence of public open space about house price, especially in many developed nations. Literature suggests the relationship between the two aspects give impact on the housing market, however not many studies undertaken in Malaysia. Thus, this research was initiated to analyse the relationship of open space and house price via the techniques of GIS-Hedonic Pricing Model. In this regards, the GIS tool indicates the pattern of the relationship between open space and house price spatially. Meanwhile, Hedonic Pricing Model demonstrates the index of the selected criteria in determining the housing price. This research is a perceptual study of 200 respondents who were the house owners of double-storey terrace houses in four townships, namely Bandar Baru Bangi, Taman Melawati, Subang Jaya and Shah Alam, in Klang Valley. The key research question is whether the relationship between open space and house price exists and the nature of its pattern and intensity. The findings indicate that there is a positive correlation between open space and house price. Correlation analysis reveals that a weak relationship (rs < 0.1) established between the variable of open space and house price (rs = 0.91, N = 200, p = 0.2). Consequently, the rate of house price change is rather small. In overall, this research has achieved its research aims and thus, offers the value added in applying the GIS-Hedonic pricing model in analysing the influence of open space to the house price in the form of spatially and textually.

scholarly journals A SPATIAL ANALYSIS ON GIS-HEDONIC PRICING MODEL ON THE INFLUENCE OF PUBLIC OPEN SPACE AND HOUSE PRICE IN KLANG VALLEY, MALAYSIA

2016 ◽  
Vol XLI-B8 ◽  
pp. 829-836
Author(s):  
A. M. Zainora ◽  
M. N. Norzailawati ◽  
P. Tuminah
Keyword(s):  
Open Space ◽  
Price Change ◽  
House Price ◽  
Value Added ◽  
Hedonic Pricing ◽  
Pricing Model ◽  
Hedonic Pricing Model ◽  
Public Open Space ◽  
Klang Valley ◽  
The Relationship

Presently, it is noticeable that there is a significant influence of public open space about house price, especially in many developed nations. Literature suggests the relationship between the two aspects give impact on the housing market, however not many studies undertaken in Malaysia. Thus, this research was initiated to analyse the relationship of open space and house price via the techniques of GIS-Hedonic Pricing Model. In this regards, the GIS tool indicates the pattern of the relationship between open space and house price spatially. Meanwhile, Hedonic Pricing Model demonstrates the index of the selected criteria in determining the housing price. This research is a perceptual study of 200 respondents who were the house owners of double-storey terrace houses in four townships, namely Bandar Baru Bangi, Taman Melawati, Subang Jaya and Shah Alam, in Klang Valley. The key research question is whether the relationship between open space and house price exists and the nature of its pattern and intensity. The findings indicate that there is a positive correlation between open space and house price. Correlation analysis reveals that a weak relationship (rs < 0.1) established between the variable of open space and house price (rs = 0.91, N = 200, p = 0.2). Consequently, the rate of house price change is rather small. In overall, this research has achieved its research aims and thus, offers the value added in applying the GIS-Hedonic pricing model in analysing the influence of open space to the house price in the form of spatially and textually.

scholarly journals A model to Estimate the Implicit Values of Housing Attributes by Applying the Hedonic Pricing Method

2017 ◽  
Vol 4 (2) ◽  
Author(s):  
TD Randeniya ◽  
Gayani Ranasinghe ◽  
Susantha Amarawickrama
Keyword(s):  
Sri Lanka ◽  
Housing Prices ◽  
House Price ◽  
Housing Price ◽  
Hedonic Pricing ◽  
Pricing Model ◽  
Urban Neighborhood ◽  
Location Factors ◽  
Property Development ◽  
Housing Attributes

Many scholars focused on the location based attributes rather than the non-location factors in decision making on land prices. Further, new research studies have identified the importance of the non-location attributes with the location factors. Many studies suggest that, many attributes exist which affects the housing price. Since the attributes involved and dominant for a particular case differs from one situation to the other, there cannot be an exact list of attributes. Yet, identification of factors that determine housing price and their relationships and the level of influence have poorly understood in planning and property development in the context of Sri Lanka. This study attempts to address what make householders to decide on housing price and application of hedonic pricing approach to estimate the implicit price of housing attributes in context of Sri Lanka. A sample study of selected fifty (50) single house transactions in Maharagama urban neighborhood area has been utilized to illustrate the applicability of the hedonic pricing model. As a methodology, correlation analysis has been carried out to study the degree of relationship between the housing price and the independent variables. The attributes which correlate with housing prices, the study identified the most significant attributes. A model was developed to estimate the future house price by applying the pricing model which is incorporated with these attributes. A hedonic house price model derived from multiple liner regression analysis was developed for the purpose. The findings reveal that six attributes as design type of the house, distance to the local road, quality of Infrastructure, garden size, number of the bed rooms and property age are contributed to estimate the implicit value of Housing property. The model developed would be used to identify implicit values of houses located in urban neighborhood area of Sri Lanka.

scholarly journals The Housing Price Bubble In A Suburban Georgia Setting: Using The Hedonic Pricing Model In The New South

2012 ◽  
Vol 28 (4) ◽  
pp. 651 ◽  
Author(s):  
Jason Beck ◽  
Joshua Fralick ◽  
Michael Toma
Keyword(s):  
New South ◽  
Housing Price ◽  
Hedonic Pricing ◽  
Price Premium ◽  
Pricing Model ◽  
Font Size ◽  
Hedonic Pricing Model ◽  
Downtown Area ◽  
Price Bubble ◽  
Historic Landmark

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify; mso-pagination: none;" class="MsoBodyText"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">This study applies a hedonic pricing model to the rapidly developing suburban housing market adjacent to the Savannah Historic Landmark District in the downtown area of Savannah, Georgia. Using OLS estimation, the hedonic pricing model yields results clearly tracing out the magnitude of the time-related housing price premium in the suburban market analyzed for the years from 2005 to 2010. The results also control for internal and external housing characteristics that are capitalized into the real sales prices of the housing transactions analyzed.</span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

scholarly journals A HOUSE PRICE VALUATION BASED ON THE RANDOM FOREST APPROACH: THE MASS APPRAISAL OF RESIDENTIAL PROPERTY IN SOUTH KOREA

2020 ◽  
Vol 24 (3) ◽  
pp. 140-152 ◽  
Author(s):  
Jengei Hong ◽  
Heeyoul Choi ◽  
Woo-sung Kim
Keyword(s):  
Random Forest ◽  
South Korea ◽  
Market Price ◽  
House Price ◽  
Ordinary Least Squares ◽  
Hedonic Pricing ◽  
Set Covering ◽  
Pricing Model ◽  
Data Set ◽  
Hedonic Pricing Model

Mass appraisal is the standardized procedure of valuing a large number of properties at the same time and is commonly used to compute real estate tax. While a hedonic pricing model based on the ordinary least squares (OLS) linear regression has been employed as the traditional method in this process, the stability and accuracy of the model remain questionable. This paper investigates the features of a house price predictor based on the Random Forest (RF) method by comparing it with that of a conventional hedonic pricing model. We used apartment transaction data from the period of 2006 to 2017 in the district of Gangnam, one of the most developed areas in South Korea. Using a data set covering 40% of all transactions in the sample area, we demonstrate that the accuracy of a machine learning-based predictor can be surprisingly high. The average of percentage deviations between the predicted and the actual market price was found to be only around 5.5% in the RF predictor, whereas it was almost 20% in the OLS-based predictor. With the RF predictor, the probability of the predicted price being within 5% of its actual market price was 72%, while only about 17.5% of the regression-based predictions fell within the same range. These results show that, in the practice of mass appraisal, the RF method may be a useful complement to the hedonic models, as it more adequately captures the complexity or non-linearity of actual housing markets.

scholarly journals Determinants of the Price of Housing in the Province of Alicante (Spain): Analysis Using Quantile Regression

2019 ◽  
Vol 11 (2) ◽  
pp. 437 ◽  
Author(s):  
Raul-Tomas Mora-Garcia ◽  
Maria-Francisca Cespedes-Lopez ◽  
V. Raul Perez-Sanchez ◽  
Pablo Marti ◽  
Juan-Carlos Perez-Sanchez
Keyword(s):  
Multivariate Analysis ◽  
Quantile Regression ◽  
Ordinary Least Squares ◽  
Hedonic Pricing ◽  
Average Price ◽  
Pricing Model ◽  
Hedonic Pricing Model ◽  
Adequate Funding ◽  
The Impact ◽  
The Relationship

After almost a decade of crisis, the housing market in Spain shows significant signs of recovery, with increases in both the average price and the number of sales transactions. Housing is the main asset for the majority of households, and it also has the most resources devoted to it, thus, when it comes to buying a residence, people do not only look at the asset’s intrinsic characteristics, but also consider other particularities such as the neighbourhood, accessibility to services, availability of public transport or adequate funding. The study aimed to analyse and quantify the relationship that exists between the asking price of second-hand housing on the market in Alicante and the attributes that characterise them. This was done using a multivariate analysis to estimate a hedonic pricing model by ordinary least squares and a quantile regression to analyse the impact of the characteristics in different price ranges. The results show the segmentation of the prices in the Alicante market, with higher prices in the northern coastal area over the southern and inland comarcas.

scholarly journals Evaluating the Impact of Floods on Housing Price Using a Spatial Matching Difference-In-Differences (SM-DID) Approach

2021 ◽  
Vol 13 (2) ◽  
pp. 804
Author(s):  
Jean Dubé ◽  
Maha AbdelHalim ◽  
Nicolas Devaux
Keyword(s):  
Housing Price ◽  
Hedonic Pricing ◽  
Environmental Amenities ◽  
Sale Price ◽  
Difference In Differences ◽  
Hedonic Pricing Model ◽  
The Difference ◽  
And Control ◽  
The Impact ◽  
The City

Many applications have relied on the hedonic pricing model (HPM) to measure the willingness-to-pay (WTP) for urban externalities and natural disasters. The classic HPM regresses housing price on a complete list of attributes/characteristics that include spatial or environmental amenities (or disamenities), such as floods, to retrieve the gradients of the market (marginal) WTP for such externalities. The aim of this paper is to propose an innovative methodological framework that extends the causal relations based on a spatial matching difference-in-differences (SM-DID) estimator, and which attempts to calculate the difference between sale price for similar goods within “treated” and “control” groups. To demonstrate the potential of the proposed spatial matching method, the researchers present an empirical investigation based on the case of a flood event recorded in the city of Laval (Québec, Canada) in 1998, using information on transactions occurring between 1995 and 2001. The research results show that the impact of flooding brings a negative premium on the housing price of about 20,000$ Canadian (CAN).

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