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.

An Empirical Analysis of the Effect of Sub-Divisions of American Viticultural Areas on Wine Prices: A Hedonic Study of Napa Valley

2020 ◽  
Vol 15 (3) ◽  
pp. 312-329
Author(s):  
Grant Bartlett Keating
Keyword(s):  
Hedonic Pricing ◽  
Pricing Model ◽  
Price Effect ◽  
Wine Grapes ◽  
Hedonic Pricing Model ◽  
Napa Valley ◽  
Price Effects ◽  
The Individual ◽  
The Impact ◽  
Unique Dataset

AbstractAmerican Viticultural Areas (AVAs) are descriptors of where wine grapes are grown that are designed to capture qualities unique to the wine and to influence its price. Sub-AVAs are sub-divisions of well-known AVAs designed to have the same effect. In this paper, I study the impact of the Napa Valley Sub-AVA system on the pricing and rating of Napa Valley wines. The analysis utilizes a primary hedonic pricing model to isolate both the individual Sub-AVA's price effect and the system's cumulative price effect. This study uses a unique dataset of 5,017 Napa Valley wines reviewed by the Connoisseurs’ Guide to California Wine over the 10-year period from 2004–2013. Estimated price effects persist even after controlling for rating differences, implying that consumers value the wines of sub-AVA's independently of critics’ ratings. These results indicate that Sub-AVAs deliver a more substantial price effect than previous literature has suggested. (JEL Classifications: C01, L10, L66, O13)

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 The Impact of Subway Lines on Residential Property Values in Tianjin: An Empirical Study Based on Hedonic Pricing Model

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Hui Sun ◽  
Yuning Wang ◽  
Qingbo Li
Keyword(s):  
Real Estate ◽  
Property Values ◽  
Northern China ◽  
Hedonic Pricing ◽  
Urban Traffic ◽  
Pricing Model ◽  
Land Rent ◽  
Hedonic Pricing Model ◽  
Real Estate Prices ◽  
The Impact

The construction of subways has an external impact on the urban environment. Among them, the most important acceleration function lies in the property values of housing near subway stations. Tianjin, the largest open coastal city in Northern China, is selected as the subject of the research in this paper by virtue of its unique background. The Hedonic Pricing Model is used in analysing the change in the value of the properties located within 1,000 metres of completed subway line 3 stations. Using the theories of land rent and land location, and a model of the impact of urban traffic on the surrounding real estate prices, we analyse the sphere of influence of Tianjin Metro Line 3 on real estate prices. Finally, the paper stresses the importance of urban construction and subway building and finds that different development strategies should be used according to the characteristics of the subway in various regions of the city.

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 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 Land Pricing Model: Price Re-evaluation Due to the Erosion and Climate Change Effects

2020 ◽  
Vol 12 (4) ◽  
pp. 111-121
Author(s):  
Josef Slaboch ◽  
Lukáš Čechura
Keyword(s):  
Climate Change ◽  
Explanatory Power ◽  
Hedonic Pricing ◽  
Numerical Code ◽  
Pricing Model ◽  
Hedonic Pricing Model ◽  
Climate Change Effects ◽  
Unit Code ◽  
Ecological Unit ◽  
The Impact

The aim of this study is to derive and apply the hedonic approach for determining and updating official land prices with respect to e.g. the impact of climate change that has occurred in the conditions of the Czech Republic in recent years. Pricing using the hedonic method is based on capturing individual factors separately. The evaluated soil ecological unit code consists of a 5-digit numerical code, which expresses the affiliation to the climate region (0-9, see table 1), the main soil unit (0-78), the slope of the land and the orientation to the point of the compass (0-9) and also the depth of the soil profile and skeletality (0-9). The derived hedonic pricing model is estimated using heteroscedasticity corrected estimator. The fitted model shows considerably high explanatory power and together with high parameter significance for majority of dummy variables (soil characteristics) as well as with theoretical and logical consistency represent a tool for new official land price settings in the process of land reevaluation due to the erosion and climate change effects.

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.

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