scholarly journals Evaluating the Impact of Urban Blue Space Accessibility on Housing Price: A Spatial Quantile Regression Approach Applied in Changsha, China

2021 ◽  
Vol 9 ◽  
Author(s):  
Huang Tuofu ◽  
He Qingyun ◽  
Yang Dongxiao ◽  
Ouyang Xiao
Keyword(s):  
Quantile Regression ◽  
House Prices ◽  
Housing Prices ◽  
Proximity Effects ◽  
Utilization Efficiency ◽  
Hedonic Model ◽  
Property Value ◽  
Value Analysis ◽  
Different Types ◽  
The Impact

Urban nature spaces are increasingly recognized as essential urban features providing crucial amenities to the residents’ health and well-being. While many studies have been conducted focusing on the influence of green spaces on house prices, very few have explored the impact of urban blue spaces. In this study, we analyzed the proximity effects of different types and sizes of urban blue spaces on property value in Changsha metropolis, China, and examined the spatial quantile effect across different housing prices. A two-stage instrumental method (2SLS) hedonic model was employed to evaluate the impact of different types of urban blue space: river (mainstream and tributary), wetland park, and lakes (large, medium, and small). Spatial quantile regression (SQR) was then used to measure the spatial effect of accessibility on various house price ranges. The 2SLS results show that, except for small-sized lakes, proximity to blue spaces significantly increases property value. Analysis of the SQR model reveals that proximity to major blue spaces increases the marginal willingness-to-pay among homebuyers of high-priced properties, while ordinary blue spaces are more attractive to buyers of low- and medium-priced houses. This may be broadly related to the level of education, utility, and sensitivity to ecosystem services across income groups. Based on these findings, we recommend that urban planners adopt different strategies to promote space utilization efficiency. This is one of the few studies that analyze the capitalization of blue space accessibility in house prices across different quantiles. By categorizing blue spaces and employing the SQR model, this study found the effect of blue spaces on housing prices to be heterogeneous, providing new perspectives to the existing literature.

Has tourism driven house prices in Germany? Time-varying evidence since 1870

2021 ◽  
pp. 135481662110088
Author(s):  
Sefa Awaworyi Churchill ◽  
John Inekwe ◽  
Kris Ivanovski
Keyword(s):  
World War Ii ◽  
Historical Data ◽  
House Prices ◽  
Housing Prices ◽  
Time Varying ◽  
Data Set ◽  
Time Series Modelling ◽  
The Impact ◽  
Tourism Flows ◽  
Non Parametric

Using a historical data set and recent advances in non-parametric time series modelling, we investigate the nexus between tourism flows and house prices in Germany over nearly 150 years. We use time-varying non-parametric techniques given that historical data tend to exhibit abrupt changes and other forms of non-linearities. Our findings show evidence of a time-varying effect of tourism flows on house prices, although with mixed effects. The pre-World War II time-varying estimates of tourism show both positive and negative effects on house prices. While changes in tourism flows contribute to increasing housing prices over the post-1950 period, this is short-lived, and the effect declines until the mid-1990s. However, we find a positive and significant relationship after 2000, where the impact of tourism on house prices becomes more pronounced in recent years.

scholarly journals Investigating the Impact of Airport Noise and Land Use Restrictions on House Prices: Evidence from Selected Regional Airports in Poland

2019 ◽  
Vol 11 (2) ◽  
pp. 412 ◽  
Author(s):  
Jacek Batóg ◽  
Iwona Foryś ◽  
Radosław Gaca ◽  
Michał Głuszak ◽  
Jan Konowalczuk
Keyword(s):  
Land Use ◽  
Environmental Sustainability ◽  
House Prices ◽  
Policy Implications ◽  
Property Value ◽  
Property Prices ◽  
Value Loss ◽  
Housing Submarkets ◽  
Regional Airports ◽  
The Impact

In this paper, we investigate the influence of airport operation on property prices. In this research, we apply spatial hedonic regression and a difference-in-differences approach to address the introduction of new land use restrictions on property prices. We use data on housing transactions from two housing submarkets around regional airports in Poland. The results suggest that the introduction of land use restrictions impacts property prices. In general, as expected, more rigid restrictions translate into higher discounts in property prices. This research contributes to the limited knowledge on the impact of the introduction of land use restrictions on property prices, as most previous papers have focused solely on the impact of noise. These findings must be treated with caution, as some estimates were not statistically significant, mainly due to limited sample size. The research has important policy implications. Growing airports in Poland face tensions between economic and environmental sustainability. Currently, airports in Poland are obliged to limit their environmental impact by creating limited use areas related to the aircraft related noise while being responsible for property value loss related to these restrictions. As a consequence, most regional airports face significant compensations to property owners.

scholarly journals Multiscale Effects of Multimodal Public Facilities Accessibility on Housing Prices Based on MGWR: A Case Study of Wuhan, China

2022 ◽  
Vol 11 (1) ◽  
pp. 57
Author(s):  
Lingbo Liu ◽  
Hanchen Yu ◽  
Jie Zhao ◽  
Hao Wu ◽  
Zhenghong Peng ◽  
...  
Keyword(s):  
Public Service ◽  
House Prices ◽  
Housing Prices ◽  
Positive Influence ◽  
Policy Formulation ◽  
Public Facility ◽  
Factors Affecting ◽  
Public Facilities ◽  
Geographically Weighted Regression Model ◽  
The Impact

The layout of public service facilities and their accessibility are important factors affecting spatial justice. Previous studies have verified the positive influence of public facilities accessibility on house prices; however, the spatial scale of the impact of various public facilities accessibility on house prices is not yet clear. This study takes transportation analysis zone of Wuhan city as the spatial unit, measure the public facilities accessibility of schools, hospitals, green space, and public transit stations with four kinds of accessibility models such as the nearest distance, real time travel cost, kernel density, and two step floating catchment area (2SFCA), and explores the multiscale effect of public services accessibility on house prices with multiscale geographically weighted regression model. The results show that the differentiated scale effect not only exists among different public facility accessibilities, but also exists in different accessibility models of the same sort of facility. The article also suggests that different facilities should adopt its appropriate accessibility model. This study provides insights into spatial heterogeneity of urban public service facilities accessibility, which will benefit decision making in equal accessibility planning and policy formulation for the layout of urban service facilities.

scholarly journals Asymmetric and Spatial Non-Stationary Effects of Particulate Air Pollution on Urban Housing Prices in Chinese Cities

2020 ◽  
Vol 17 (20) ◽  
pp. 7443
Author(s):  
Biao Sun ◽  
Shan Yang
Keyword(s):  
Real Estate ◽  
Quantile Regression ◽  
Housing Prices ◽  
Spatial Relationship ◽  
Well Being ◽  
Urban Housing ◽  
Real Estate Market ◽  
Economic Losses ◽  
Full Account ◽  
The Impact

Fine particulate matter(PM2.5) pollution will affect people’s well-being and cause economic losses. It is of great value to study the impact of PM2.5 on the real estate market. While previous studies have examined the effects of PM2.5 pollution on urban housing prices, there has been little in-depth research on these effects, which are spatially heterogeneous at different conditional quantiles. To address this issue, this study employs quantile regression (QR) and geographically weighted quantile regression (GWQR) models to obtain a full account of asymmetric and spatial non-stationary effects of PM2.5 pollution on urban housing prices through 286 Chinese prefecture-level cities for 2005–2013. Considerable differences in the data distributions and spatial characteristics of PM2.5 pollution and urban housing prices are found, indicating the presence of asymmetric and spatial non-stationary effects. The quantile regression results show that the negative influences of PM2.5 pollution on urban housing prices are stronger at higher quantiles and become more pronounced with time. Furthermore, the spatial relationship between PM2.5 pollution and urban housing prices is spatial non-stationary at most quantiles for the study period. A negative correlation gradually dominates in most of the study areas. At higher quantiles, PM2.5 pollution is always negatively correlated with urban housing prices in eastern coastal areas and is stable over time. Based on these findings, we call for more targeted approaches to regional real estate development and environmental protection policies.

The Impact of Neighborhood Characteristics on Housing Prices-An Application of Hierarchical Linear Modeling

2012 ◽  
Vol 1 (2) ◽  
pp. 31-44
Author(s):  
Lee Chun Chang ◽  
Hui-Yu Lin
Keyword(s):  
Empirical Study ◽  
Hierarchical Linear Modeling ◽  
House Prices ◽  
Housing Prices ◽  
Neighborhood Characteristics ◽  
Linear Modeling ◽  
Hierarchical Linear Modelling ◽  
Neighborhood Characteristic ◽  
Linear Modelling ◽  
The Impact

Housing data are of a nested nature as houses are nested in a village, a town, or a county. This study thus applies HLM (hierarchical linear modelling) in an empirical study by adding neighborhood characteristic variables into the model for consideration. Using the housing data of 31 neighborhoods in the Taipei area as analysis samples and three HLM sub-models, this study discusses the impact of neighborhood characteristics on house prices. The empirical results indicate that the impact of various neighborhood characteristics on average housing prices is different and that the impact of house characteristics on house prices is also moderated by neighborhood characteristics.

Constitutes Model of Housing Prices and Analysis of the Reasons for High Prices in China

2013 ◽  
Vol 459 ◽  
pp. 674-679
Author(s):  
Jing Lian Huang ◽  
Ya Jing Liu
Keyword(s):  
House Prices ◽  
Housing Prices ◽  
Construction Costs ◽  
Analytic Hierarchy ◽  
Model Based ◽  
Cost Impact ◽  
Different Types ◽  
Calculation Results ◽  
Five Elements ◽  
Acquisition Costs

By the study of changes in housing prices in Chines domestic during 1997-2009, we establish a Chinese house prices constitution model based on Analytic Hierarchy Process. The model is including five elements, namely, land acquisition costs, construction costs, the state's tax policy, developers expected profits and cost of sales, which does not consider regional differences. Because China has a vast territory, the regional economic development is uneven and housing prices are quite different, we select the typical city to modify the model based on different types of urban land cost impact on house prices. Meanwhile,we analyze the affect of the five elements to house prices changes. Further,we taking into the influence of land to the house prices of different types of urban, and the justifiability of land prices are analyzed and evaluated quantitatively. According to the calculation results, analyzing the reasons of high house prices in China and some suggestions are given.

scholarly journals A new Mass Rapid Transit (MRT) line construction and housing wealth: Evidence from the Circle Line

2017 ◽  
Vol 1 (1) ◽  
pp. 64 ◽  
Author(s):  
Mi Diao ◽  
Yi Fan ◽  
Tien Foo Sing
Keyword(s):  
House Prices ◽  
Phase 1 ◽  
Housing Prices ◽  
Wealth Effects ◽  
Housing Wealth ◽  
Rapid Transit ◽  
Treatment Zone ◽  
Housing Wealth Effects ◽  
The Impact ◽  
Mass Rapid Transit

This study uses the opening of the new Mass Rapid Transit (MRT) in stages between 2010 and 2012 in Singapore as the exogenous event to empirically test the impact of the new Circle Line (CL) on housing wealth. Applying a "differences-in-differences" approach to the non-landed private housing transaction data covering the period from 2009 to 2013, we find that the average housing prices increase by 1.6% in the post-opening of the CL. We find significant capitalization of the new CL into housing prices, especially households living within a 400-meter radius (the treatment zone) from the closest MRT stations on the CL. The treatment effects that are measured by the “marginalwillingness to pay” for houses located within the treatment zone is 13.2% relative to houses located outside the treatment zone. The new CL opening creates an estimated S$1.23 billion housing wealth effects for households living in close proximity to the CL MRT stations. However, we do not find significant "anticipative" effects on house prices in the six-month window prior to the opening of CL. The strongest treatment effect is found after the opening of the phase 1 of CL, and the treatment intensity declines in phases 2 and 3 of the CL opening.

Causal effects of immigration inflows on house prices in a traditionally non-destination country

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Woei Chyuan Wong ◽  
Jan-Jan Soon
Keyword(s):  
Fixed Effects ◽  
Positive Impact ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Developed Countries ◽  
Annual Data ◽  
Content Type ◽  
Variable Approach ◽  
The Impact

Purpose The purpose of this study is to examine the causal impact of international immigration inflows on housing prices at the state level in Malaysia from 2007 to 2018. Design/methodology/approach Hedonic regressions using both fixed effects and first difference approaches are used to estimate the impact of immigration inflows on house prices in Malaysia. This study deals with potential endogeneity of immigrants’ choices of destination states in Malaysia by using a shift-share instrument variable approach. Specifically, historical shares of immigrants in a state are used to predict current immigrant inflows to a particular state. The predicted value of immigration flows is then inserted into the house price regression models in place of the actual immigration flows. Findings Using annual data for 14 states from 2007 to 2018, this study documents the positive impact of immigration inflows on house prices in Malaysia. The authors find that a 1% increase in immigration inflows is associated with an increase of 10.2% (first difference) and 13.4% (fixed effects) in house prices. The economic impact is larger in magnitude than that found in developed countries. Contrary to existing studies that find immigration inflows to be associated with native flight, the authors find support for the attraction effects hypothesis, where immigration inflow is positive and significantly related to net native flows. Research limitations/implications The effects of immigration inflows are economically significant, considering that the effects are 10 times larger than those documented in the USA. Policymakers in Malaysia ought to monitor house price trends in immigrant-popular states to ensure that natives are not priced out by new immigrants. Originality/value To the best of the authors’ knowledge, this is perhaps the first study to focus on the relationship between immigration inflows and house prices in Malaysia. Focusing on Malaysia has at least two originality aspects. First, Malaysia is relatively not an immigrant-popular destination. Second, Malaysia has a multiracial and heterogenous society among its natives. The findings, obtained within these two settings, would therefore provide a wider scope of result generalization, and natural experiment grounds for causal implications of our results.

Factors affecting housing prices in Izmir, Turkey: a quantile regression approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Onur Özsoy ◽  
Hasan Şahin
Keyword(s):  
Quantile Regression ◽  
House Prices ◽  
Housing Prices ◽  
Least Square ◽  
Policy Implications ◽  
Content Type ◽  
Factors Affecting ◽  
Ordinary Least Square ◽  
Major Factors ◽  
Quantile Regression Method

Purpose The purpose of this paper is to investigate empirically the main factors that affect the house prices in Izmir, Turkey using the quantile regression and ordinary least square approaches. Design/methodology/approach Sample data about the housing market for Izmir collected from the web pages of various real estate agencies during June 2018. Following this, the quantile regression method is used to estimate all possible effects of variables on each interested quantile to determine the factors that affect house prices to guide the potential consumers, house developers, city planners and the policymakers in Izmir, Turkey. Findings Results show that the age of the house, central heating and parking have no significant effect on prices. The size of the house, the existence of an elevator, fire and security have a positive and significant effect on prices. The number of rooms has lower values for high-priced houses, while the floor, the number of balconies, air conditioning, proximity to schools have a higher value for high-priced houses. The number of toilets, the number of bathrooms and the distance to the hospital have a lower value on the high-priced housing. The value of the distance from the city center and the shopping center is almost uniform in all quantiles and lowers the value of the higher-priced houses. With the exception of the value of the houses in the 10th percentile in Balcova district, the value of the houses in Konak, Balcova and Narlidere is lower prices in Karsiyaka. Originality/value This is the first comprehensive research to determine the major factors that affect house prices in Izmir. The second contribution of this paper is that it includes all possible variables and accordingly derives adequate policy implications, which could be used both by the public housing authority and private housing constructing companies in designing and implementing effective housing policies.

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