scholarly journals The Unequal Impact of Natural Landscape Views on Housing Prices: Applying Visual Perception Model and Quantile Regression to Apartments in Seoul

2020 ◽  
Vol 12 (19) ◽  
pp. 8275
Author(s):  
Hyejin Lee ◽  
Byoungkil Lee ◽  
Sangkyeong Lee
Keyword(s):  
Visual Perception ◽  
Quantile Regression ◽  
Housing Prices ◽  
Housing Price ◽  
Value Added ◽  
Wealth Inequality ◽  
Ordinary Least Squares ◽  
Hedonic Price ◽  
Natural Landscape ◽  
Perception Model

Natural landscape views have positive sides, such as providing restorative effects to urban residents, and negative sides, such as deepening wealth inequality. Previous studies have mainly focused on the positives and rarely on the negatives. From this perspective, this study aimed to analyze the unequal impact of natural landscape views on housing prices for apartments in Seoul. We proposed a visual perception model to analyze natural landscape views and, based on a hedonic price model, we used ordinary least squares and quantile regression to estimate the marginal impacts on housing prices. The results show that: (1) natural landscape views had positive impacts on housing prices, but their impacts did not reach the level of structural and locational characteristics such as apartment area and the distance to subway stations; (2) natural landscape views had different marginal impacts by housing price range and, in particular, had much higher value-added effects on higher-priced apartments, meaning that if old apartment complexes are redeveloped into high-rise ones, the improvement in natural landscape views generates great profit for apartment owners and intensifies wealth inequality; (3) the geographic information system-based visual perception model effectively quantified the natural landscape views of wide areas and is thus applicable for the rigorous analysis of various landscape views.

scholarly journals Heterogeneity Analysis of Urban Rail Transit on Housing with Different Price Levels: A Case Study of Chengdu, China

Land ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1330
Author(s):  
Pengyu Ren ◽  
Zhaoji Li ◽  
Weiguang Cai ◽  
Lina Ran ◽  
Lei Gan
Keyword(s):  
Housing Prices ◽  
Housing Price ◽  
Ordinary Least Squares ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Hedonic Price ◽  
Least Squares Regression ◽  
Price Levels ◽  
Urban Rail ◽  
The Impact

The impact of urban rail transit on housing prices has attracted the extensive attention of scholars, but few studies have explored the heterogeneous impact of rail transit on housing prices with different price levels. To solve this problem, we adopted the hedonic price model based on ordinary least squares regression as a supplementary method of quantile regression to study the heterogeneous impact of the Chengdu Metro system on low-, middle-, and high-priced housing. The result shows that the housing price rises first, then falls with the distance from the housing to the nearest subway station. Besides, the influence of transportation accessibility on low-, middle-, and high-priced housing decreases progressively. This research can provide a reference for the government’s transportation planning and decision-making.

International Real Estate Review

2020 ◽  
Vol 23 (3) ◽  
pp. 417-432
Author(s):  
Yen-Jong Chen ◽  
◽  
Cheng-Kai Hsu ◽  
Keyword(s):  
Urban Areas ◽  
Housing Prices ◽  
Housing Price ◽  
Hedonic Price ◽  
Rapid Transit ◽  
Transit Oriented Development ◽  
Transaction Data ◽  
Hedonic Price Models ◽  
Transit Accessibility ◽  
Different Types

Constructing multimodal stations is one of the considered ways to implement transit-oriented development (TOD), with the goal of synergizing land use and transportation to promote both greater transit accessibility and sustainability in urban areas. Improvements in such accessibility have led to an uplift in land value and housing prices. These price changes have been primarily studied by analyzing the effects of proximity to stations of a single line or multi-line mass rapid transit (MRT) system. However, little attention has been paid to investigating the effects of different types of multimodal MRTs and railway joined stations. The aim of this study is to investigate the different types of multimodal stations in Kaohsiung City, Taiwan. We use publicly available housing transaction data to construct hedonic price models. The results show that in the Kaohsiung MRT stations, an increase of 100 m in distance from the stations results in a TWD 258,000 decrease in the average housing price. The housing price elasticity with respect to a 1% increase in distance from these stations is -0.067%.

scholarly journals Value-added in higher education: ordinary least squares and quantile regression for a Colombian case

2017 ◽  
Vol 37 (3) ◽  
pp. 30-36
Author(s):  
Jose D Bogoya ◽  
Johan M Bogoya ◽  
Alfonso J Peñuela
Keyword(s):  
Higher Education ◽  
Quantile Regression ◽  
Least Squares ◽  
Value Added ◽  
Ordinary Least Squares ◽  
Independent Variables ◽  
State Tests ◽  
Socioeconomic Stratum ◽  
The Mean ◽  
Lineal Regression

Colombia applies two mandatory National State tests every year. The first, known as Saber 11, is applied to students who finish the high school cycle, whereas the second, called Saber Pro, is applied to students who finish the higher education cycle. The result obtained by a student on the Saber 11 exam along with his/her gender, and socioeconomic stratum are our independent variables while the Saber Pro outcome is our dependent variable.We compare the results of two statistical models for the Saber Pro exam. The first model, multi-lineal regression or ordinary least squares (OLS), produces an overall well fitted result but is highly inaccurate for some students. The second model, quantile regression (QR), weight the population according to their quantile groups. OLS minimizes the errors for the students whose Saber Pro result is close to the mean (a process known as estimation in the mean) while QR can estimate in the -quantile for every . We show that QR is more accurate than OLS and reveal the unknown behavior of the socioeconomic stratum, the gender, and the initial academic endowments (estimated by the Saber 11 exam) for each quantile group.

scholarly journals The House Price Dynamics and the Macro-Economy: an Empirical Perspective of UAE

2019 ◽  
Vol 2 (1) ◽  
pp. 28-33
Author(s):  
Yahya Hamad Al Zaabi ◽  
Genanew Bekele
Keyword(s):  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Housing Price ◽  
Future Research ◽  
Hedonic Price ◽  
Policy Makers ◽  
Empirical Perspective ◽  
House Condition ◽  
Internal And External Factors

Objective: The paper aims to examine house price drivers in Dubai, addressing the effect of internal and external factors afecting house prices   Design/methedology/approach: Using the Hedonic price model, the study examined the implications of house size (space), the availability of bathrooms, bedrooms, waterfronts, and pool and cell phone towers within residential area as auxiliary determinant factors to housing price within developed cities by using the Hedonic Modelling. Also, study highlight the effect of the green strategies that been followed by developer on the housing prices.   Findings: The study is expected to reveal results with significant ramifications for researchers, practitioners and policy makers. From a policy perspective, there is an obvious interest in understanding whether the price of housing is affected by different attributes differently along its distribution.   Research limitations/implications: The data used in this study could be limited, and depends on information to be provided by the Dubai Land Department. There is a room for future research to include more data (such as on other house attributes such as house condition, plot numbers and configuration).

CONSTRUCTING HOUSING PRICE INDEX FOR TERRACED PROPERTIES IN JOHOR BAHRU, MALAYSIA

2021 ◽  
Vol 19 (17) ◽  
Author(s):  
Wendy Wen Xin Lim ◽  
Burhaida Burhan ◽  
Mohd Lizam Mohd Diah
Keyword(s):  
Price Index ◽  
Housing Prices ◽  
Housing Price ◽  
Hedonic Price ◽  
Property Market ◽  
Price Variation ◽  
Vector Property ◽  
Hedonic Price Analysis ◽  
Housing Price Index ◽  
Housing Attributes

Housing is a country’s biggest asset. Hence, the pattern of the housing price index (HPI) is an important topic to gain insight into the housing market while identifying the prevailing housing issues. The determinants of housing price vary for each city and state based on the different characteristics in each location. Accordingly, HPI should consider the property’s quality differences. Besides, national HPI is insufficient and restricted to the housing price at the state level. Thus, the study focused on constructing a specified HPI model for different cities, districts, and states. Effective HPI can give parties a better idea of the current property market situation and act as an analytical tool in managing the sector. Specifically, the study aims to examine the relationship between the heterogeneity housing attributes and housing prices of the terraced properties in Johor Bahru, Malaysia. Additionally, the study provides detailed information on the key determinants of the housing price variation in Johor Bahru. Hedonic price analysis is useful in constructing HPI, expressing housing price as a function of vector property characteristics. Furthermore, HPI is constructed based on the yearly indices and by pooling the data into certain periods. The results show the percentage of variance explained by the factors of HPI for the terraced properties in Johor Bahru. Correspondingly, the underlying correlation between the tested housing attributes with the housing price is explained through the analysis results.

Determinants of housing prices from an urban economic point of view: evidence from Hungary

2019 ◽  
Vol 12 (1) ◽  
pp. 2-31 ◽  
Author(s):  
Norbert Czinkan ◽  
Áron Horváth
Keyword(s):  
Population Growth ◽  
Housing Stock ◽  
Housing Prices ◽  
Housing Price ◽  
Ordinary Least Squares ◽  
Point Of View ◽  
City Size ◽  
Economic Point ◽  
Content Type ◽  
Urban Economic

Purpose The purpose of the paper is to investigate a cross section of Hungarian settlement-level unit housing prices with a special emphasis on measuring the effect of population and its growth, along with accessibility to the centre of an aggregated spatial unit such as a micro-region, county or region, for the period of 2001-2011. Design/methodology/approach The analysis uses cross-sectional ordinary least squares techniques with Moulton-corrected standard errors. The estimation is guided by the implications of a simplified monocentric urbanized area framework following the model of DiPasquale and Wheaton (1996), and the econometric model is augmented with population growth rate at the settlement level to bridge the theory explaining rents and data base containing prices instead. Findings The location is a key factor in determining housing prices: living 10 min further from the centre results in 11 per cent cheaper housing. When estimating bid-rent curves, results show that it is crucial to control for city size and the income effect. The elasticity of housing price with respect to city size is 0.09 according to our preferred model. Population growth has an asymmetric impact on housing prices: municipalities with positive expected population growth have higher prices today. Practical implications Estimating the quantitative relationship between commuting time and housing price is crucial for a cautious infrastructure development. The benefits of improved roads and faster access could be capitalized in appreciating the housing stock. Estimating the slope of the bid-rent curve is one possible ex ante quantification of the benefits of a public development. Originality/value One contribution of this research is providing empirical evidence to surprisingly limited applied work in the field of (monocentric) urban models using data from the CEE region. Second, to the best of the authors’ knowledge, this is the first study to investigate Hungarian settlement-level unit prices from an urban economic point of view.

scholarly journals THE EFFECTS OF A SHOPPING MALL ON HOUSING PRICES: A CASE STUDY IN HANGZHOU

2018 ◽  
Vol 23 (1) ◽  
pp. 65-80 ◽  
Author(s):  
Ling Zhang ◽  
Jiantao Zhou ◽  
Eddie C. M. Hui ◽  
Haizhen Wen
Keyword(s):  
Housing Prices ◽  
Housing Price ◽  
Shopping Mall ◽  
Hedonic Price ◽  
Shopping Malls ◽  
Time Dimension ◽  
Positive Effects ◽  
The Impact ◽  
Positive Effect

There are few studies on the externalities of shopping malls affecting the housing market. This study aims to discuss two issues: (1) What is the intensity of the impact of a shopping mall? (2) When does the external influence of a shopping mall begin to reveal itself? The West Intime Shopping Mall in Hangzhou offers a unique situation to research the questions. By dividing the study area into nine blocks, using hedonic price theory, and the price gradient approach with housing price data from 2011 to 2015, we found that in the space dimension, the mall exerted a significantly positive effect on the housing prices of nearby blocks. With the increase in distance from the mall, the positive effect decreased. There were more significantly positive effects in blocks far away from the city center. In the time dimension, the effects of West Intime did not reveal themselves until the mall had started to operate and gradually matured over time, implying that the mall did not have the obvious expected impact on housing prices before the mall had begun operating.

scholarly journals Temporal and Spatial Effects of Urban Center on Housing Price — A Case Study on Hangzhou, China

2018 ◽  
Vol 5 (1) ◽  
pp. 89 ◽  
Author(s):  
Luhong Chu ◽  
Haizhen Wen
Keyword(s):  
Rapid Development ◽  
Housing Prices ◽  
Housing Price ◽  
Urban Land ◽  
Urban Housing ◽  
Spatial Effects ◽  
Hedonic Price ◽  
Urban Center ◽  
Center City ◽  
The Impact

<em>With the acceleration of urbanization and the rapid development of real estate, people pay more and more attention to the change of urban housing prices. Over time, the change of city center will inevitably affect the urban land or housing prices, which is reflected in the spatial distribution of urban land or housing prices. Therefore, this article attempts to explore the impact of urban center on housing prices from the perspective of multi-center city and study separately from two aspects of time and space. This paper takes the six main urban districts of Hangzhou as the research scope. At the time level, we select the residential data from 2007 to 2015 to construct models respectively based on the hedonic price theory and find that the influence of different urban center on housing price shows a certain change with time. On the spatial level, this paper choses the residential data in 2012 to construct geographic weighted regression model and the result shows that the impact of three centers on housing prices shows a certain degree of spatial heterogeneity.</em>

scholarly journals The Impact of Micro-Level Influencing Factors on Home Value: A Housing Price-Rent Comparison

2018 ◽  
Vol 10 (12) ◽  
pp. 4343 ◽  
Author(s):  
Nana Cui ◽  
Hengyu Gu ◽  
Tiyan Shen ◽  
Changchun Feng
Keyword(s):  
Influencing Factors ◽  
School Quality ◽  
School Attendance ◽  
Housing Prices ◽  
Housing Price ◽  
Living Environment ◽  
Hedonic Price ◽  
Micro Level ◽  
Employment Center ◽  
The Impact

The housing sales market in China has flourished and gained considerable interest, while the housing rental market has lagged behind and been ignored over the past two decades. With the acceleration of urbanization, the housing rental demand is rising rapidly. Exploring and comparing the influencing factors on housing sale prices and rental prices has significance for sustainable urban planning and management. Using house purchase transaction and rent transaction data in 2017, as well as the average housing price and rent data in 2016 in Beijing, China, this paper compares the spatial distribution and it employs the hedonic price model and quantile regression model to quantify the average and distributional effects of micro-level influencing factors on housing prices and housing rents. Results show that housing prices and housing rents both have a decentralized distribution with multiple centers, but rents of residential communities with high housing prices may not necessarily be high. Both homeowners and renters prefer properties with good structural, locational, and neighborhood characteristics, as well as a good school attendance zone, whereas they still differ in terms of preferences. Homeowners prefer a higher-quality living environment. Renters are more concerned with proximity to an employment center and public transit convenience. Moreover, the price premium of school quality for homeowners exceeds the premium for renters. Higher-priced homeowners or renters differ in the preferences from lower-priced homeowners or renters. Higher-priced homeowners and higher-priced renters are more willing to live in property with a larger number of bedrooms, proximity to a major employment center, park, or school, as well as a location in a school attendance zone with higher school quality.

Spatio-Temporal Hedonic Price Model to Investigate the Dynamics of Housing Prices in Contexts of Urban Form and Transportation Services in Toronto

2018 ◽  
Vol 2672 (6) ◽  
pp. 21-30 ◽  
Author(s):  
Jason Hawkins ◽  
Khandker Nurul Habib
Keyword(s):  
Urban Form ◽  
Housing Stock ◽  
Housing Prices ◽  
Housing Price ◽  
Central Business District ◽  
Hedonic Price Model ◽  
Hedonic Price ◽  
Single Family ◽  
Price Model ◽  
Spatio Temporal

A spatio-temporal hedonic price model is developed for the Greater Toronto area to examine the effects of urban configurations and proximity to transit services on housing price. A spatial Durbin panel model is utilized to account for both spatial and temporal autocorrelation. This model is shown to have advantages through its ability to reduce the number of explanatory variables required to obtain a strong fit with empirical data. Analysis is completed for the period of 1996 to 2017 and distinctions are made in housing stock between single-family houses, townhouses, and condominiums. It is shown that heterogeneities exist between the hedonic representations of each dwelling type and that separate models should be employed for each. In all cases, the average income of the community, its distance to the central business district (CBD), and population and employment density are found to be significant factors in the determination of price.

Sign in / Sign up

Export Citation Format

Share Document