scholarly journals EPC Labels and Building Features: Spatial Implications over Housing Prices

2021 ◽  
Vol 13 (5) ◽  
pp. 2838
Author(s):  
Alice Barreca ◽  
Elena Fregonara ◽  
Diana Rolando
Keyword(s):  
Real Estate ◽  
Spatial Data ◽  
Housing Stock ◽  
Housing Prices ◽  
Energy Performance ◽  
Ordinary Least Squares ◽  
Real Estate Market ◽  
Hedonic Price ◽  
Spatial Error ◽  
The Impact

The influence of building or dwelling energy performance on the real estate market dynamics and pricing processes is deeply explored, due to the fact that energy efficiency improvement is one of the fundamental reasons for retrofitting the existing housing stock. Nevertheless, the joint effect produced by the building energy performance and the architectural, typological, and physical-technical attributes seems poorly studied. Thus, the aim of this work is to investigate the influence of both energy performance and diverse features on property prices, by performing spatial analyses on a sample of housing properties listed on Turin’s real estate market and on different sub-samples. In particular, Exploratory Spatial Data Analyses (ESDA) statistics, standard hedonic price models (Ordinary Least Squares—OLS) and Spatial Error Models (SEM) are firstly applied on the whole data sample, and then on three different sub-samples: two territorial clusters and a sub-sample representative of the most energy inefficient buildings constructed between 1946 and 1990. Results demonstrate that Energy Performance Certificate (EPC) labels are gaining power in influencing price variations, contrary to the empirical evidence that emerged in some previous studies. Furthermore, the presence of the spatial effects reveals that the impact of energy attributes changes in different sub-markets and thus has to be spatially analysed.

Research on the Impacts of Real Estate on Economic Growth: A Theoretical Model-Based Analysis

2018 ◽  
Vol 06 (04) ◽  
pp. 1850025
Author(s):  
Xiaoxi ZHANG ◽  
Lu GUO
Keyword(s):  
Economic Growth ◽  
Real Estate ◽  
Low Income ◽  
Housing Prices ◽  
Well Being ◽  
Real Estate Market ◽  
The Real ◽  
The Real Estate ◽  
Pillar Industry ◽  
The Impact

As the pillar industry of China’s economy, the real estate sector has a significant impact on macroeconomic growth. We assume that the first stage of economic actors’ working lives is a low-income one, while their second stage is a high-income one. Then, relying on an Overlapping-Generations Model, we analyze how, via real estate, the behaviors of different income groups affect the macroeconomy. The results show that when the supply of real estate market fluctuates then this has an impact on economic growth, but the extent of the impact depends on the relationship between the real estate and the consumer markets. We also find that when economic actors more greatly prefer their current situations of well-being, no matter whether there takes place or not a new increase in real estate stocks, a negative correlation will exist in the relation between real estate stocks and their prices. Lastly, we come to the conclusion that increases in property taxes can effectively reduce housing prices, but the impact of transaction taxes on housing prices can still not be determined.

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.

Algorithm of real estate mass appraisal with inequality restricted least squares (IRLS) estimation

2020 ◽  
Vol 13 (2) ◽  
pp. 161-179
Author(s):  
Mariusz Doszyń
Keyword(s):  
Real Estate ◽  
Least Squares ◽  
Econometric Model ◽  
A Priori ◽  
Ordinary Least Squares ◽  
Real Estate Market ◽  
Negative Consequences ◽  
Content Type ◽  
Low Efficiency ◽  
The Impact

Purpose The purpose of this paper is to present an algorithm of real estate mass appraisal in which the impact of attributes (real estate features) is estimated by inequality restricted least squares (IRLS) model. Design/methodology/approach This paper presents the algorithm of real estate mass appraisal, which was also presented in the form of an econometric model. Vital problem related to econometric models of mass appraisal is multicollinearity. In this paper, a priori knowledge about parameters is used by imposing restrictions in the form of inequalities. IRLS model is therefore used to limit negative consequences of multicollinearity. In ordinary least squares (OLS) models, estimator variances might be inflated by multicollinearity, which could lead to wrong signs of estimates. In IRLS models, estimators efficiency is higher (estimator variances are lower), which could result in better appraisals. Findings The final effect of the analysis is a vector of the impact of real estate attributes on their value in the mass appraisal algorithm. After making expert corrections, the algorithm was used to evaluate 318 properties from the test set. Valuation errors were also discussed. Originality/value Restrictions in the form of inequalities were imposed on the parameters of the econometric model, ensuring the non-negativity and monotonicity of real estate attribute impact. In case of real estate, variables are usually correlated. OLS estimators are then inflated and inefficient. Imposing restrictions in form of inequalities could improve results because IRLS estimators are more efficient. In the case of results inconsistent with theoretical assumptions, the real estate mass appraisal algorithm enables having the obtained results adjusted by an expert. This can be important for low quality databases, which is often the case in underdeveloped real estate markets. Another reason for expert correction may be the low efficiency of a given real estate market.

scholarly journals The Influence of Energy Certification on Housing Sales Prices in the Province of Alicante (Spain)

2020 ◽  
Vol 10 (20) ◽  
pp. 7129
Author(s):  
Maria-Francisca Cespedes-Lopez ◽  
Raul-Tomas Mora-Garcia ◽  
V. Raul Perez-Sanchez ◽  
Pablo Marti-Ciriquian
Keyword(s):  
Real Estate ◽  
Ordinary Least Squares ◽  
Real Estate Market ◽  
European Countries ◽  
Least Squares Regression ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Final Sample ◽  
Energy Labelling ◽  
The Impact

This work examines the implementation of energy labelling by the residential real estate sector. First, it considers the interest by real estate sellers in not publishing energy certification information, and then, it quantifies the impact of the housing’s energy certification on the asking price. The results are compared with those obtained from other studies conducted in distinct European countries. The study’s final sample was collected, including information from 52,939 multi-family homes placed on the real estate market in the province of Alicante (Spain). One-way analysis of variance (ANOVA) was used, as well as an ordinary least squares regression model. This study highlights the fact that, in the current market, owners and sellers have no incentive to reveal the energy certification, since this permits them to sell homes with low energy ratings at prices similar to those of more energy efficient homes. In addition, it was found that homes with better energy ratings (letters A and B) are not sold at higher prices than homes with other rating letters, unlike the case of other European countries that were examined.

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.

scholarly journals Analysis of Urban Residents' Sports Consumption Demand Based on Intercepted Regression Model

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Qing Liu
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Estate Market ◽  
Survey Method ◽  
Real Estate Industry ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Price ◽  
Real Estate Prices ◽  
The Impact

At this stage, broadening the consumer market, upgrading the consumption system and gradually establishing a consumption-led development concept are key factors in promoting high-quality economic development. At the same time, China's macro economy is also experiencing another test. The rapid development of China's real estate market in recent years has attracted a large number of investors, and real estate prices have produced irrational and substantial increases. Behind the boom of the real estate market is a social system crisis driven by profiteering and the growing seriousness of real estate financial bubble. So exploring the mechanism of the influence of real estate prices on the upgrading of residents' consumption is important for the current stage of China. Therefore, it is important to investigate the mechanism of real estate price impact on consumer upgrading for the coordinated development of real estate industry and national economy. In this paper, we analyze and examine the theory on the consumption improvement by the literature survey method. We also summarize the present research on the correlation and the influence mechanism of the real estate price and the consumption improvement and choose the index which reflects the present state of the real estate industry and the consumption of the inhabitant. Besides the input indicators that qualitatively manage the impact of housing prices on the improvement of residents' consumption, we first use the descriptive statistics method to understand the level of the Chinese real estate market and improve consumer spending. Based on this, the descriptive statistical method is applied to define the current state of China's real estate market and the level of improvement in consumption, and to define the standard for improving consumption in China. On the other hand, based on the spatial and spatial spillover points of view, we use spatial analysis framework combined with exploratory spatial data analysis and GIS to investigate spatial correlation between consumption structure and housing price, and accurately reflect the spatial clustering status of the index by drawing. Moran dispersion plot and Lisa cluster plot, then the spatial Darwinian model, are used to investigate the impact of real estate prices on the increase in occupant consumption from a macro perspective.

scholarly journals Public Space, Tourism and Mobility. Projects, Impacts and Tensions in Lisbon’s Urban Regeneration Dynamics

2019 ◽  
pp. 29-56
Author(s):  
João Rafael Santos
Keyword(s):  
Real Estate ◽  
Public Space ◽  
Large Scale ◽  
Central Government ◽  
Public Investment ◽  
Population Decline ◽  
Housing Prices ◽  
Urban Regeneration ◽  
Real Estate Market ◽  
The Impact

In the wake of severe economic slowdown during the 2008-2015 crisis, and despite continued constraints on public investment in large scale infrastructure, Lisbon is emerging as one of the most attractive destinations in Europe. Tourism has been driving major spatial, functional and social changes, initially in the city’s historical districts, and nowadays exerts impact across a much larger urban and regional area. Tourism, together with new drivers of the real-estate market, is promoting the renovation of formerly vacant or rundown built stock, taking advantage of a rather fragile socio-economic milieu and changing the face of residential, commercial and public space landscapes. Recently upgraded transportation nodes and extensive improvements on public space have also played a meaningful role in this process. Central government and municipality rationale have underpinned its role in providing accessibility, “attractivity”, and “heritage valorisation”, aiming to attract young residents after decades of resident population decline. In contrast to considerable public investment in public space and infrastructure, very limited funding or policy has been targeted at maintaining an affordable housing and real-estate market: thus leaving much of the public investment return to the private sector. Criticism of gentrification and “touristification”, rising housing prices, and pressure on infrastructure is growing accordingly. The paper provides insight into aspects of this process, with a focus on the relational aspects of mobility upgrade, public space renewal and inner-city urban regeneration. Several urban projects are mapped and broadly characterised in their spatial and functional relationship with tourism. An interpretative framework that combines them with the forms of territorialisation and the main conflicts and tensions is offered as a contribution to the ongoing discussion. Conclusions point to the complex and powerful role that public space and mobility infrastructure play in the impact of territorialising tourism: as supports for better qualified, multi-scalar and shared urban spaces and as drivers of a more balanced, diverse and socially-inclusive urban tourism development.

scholarly journals Brownfield Areas and Housing Value: Evidence from Milan

2019 ◽  
Vol 11 (1) ◽  
pp. 60-83
Author(s):  
Lucia Gibilaro ◽  
Gianluca Mattarocci
Keyword(s):  
Real Estate ◽  
Economic Effect ◽  
Housing Prices ◽  
Real Estate Market ◽  
Economic Losses ◽  
Hedonic Price ◽  
City Center ◽  
Housing Value ◽  
Hedonic Price Models ◽  
Transaction Price

Using a transaction price database, in this paper we evaluate the economic effect of abandoned and derelict real estate areas on housing prices in Milan Italy from 1993 to 2016. We find that brownfields are widespread throughout Milan, with larger abandoned and derelict areas prevalent in the suburbs. Standard hedonic price models show that nearby brownfield areas lower housing prices, with stronger effects for larger derelict and abandoned areas. Economic losses are more relevant to houses in the historical city center and are affected by real estate market trends.

Energy performance certificates in the Turin real estate market

2017 ◽  
Vol 10 (2) ◽  
pp. 149-169 ◽  
Author(s):  
Elena Fregonara ◽  
Diana Rolando ◽  
Patrizia Semeraro
Keyword(s):  
Real Estate ◽  
House Prices ◽  
Energy Performance ◽  
Real Estate Market ◽  
Market Liquidity ◽  
Hedonic Model ◽  
Price Variation ◽  
Content Type ◽  
Time On The Market ◽  
The Impact

Purpose The purpose of this paper is to assess the impact of the Energy Performance Certificate (EPC) on the Italian real estate market, focusing on old buildings. The contribution of EPC labels to house prices and to market liquidity was measured to analyze different aspects of the selling process. Design/methodology/approach A traditional hedonic model was used to explain the variables of listing price, transaction price, time on the market and bargaining outcome. In addition to EPC labels, the building construction period and the main features of apartments were included in the model. A sample of 879 transactions of old properties in Turin in 2011-2014 was considered. Findings A first hedonic model let us suppose that low EPC labels (E, F and G) were priced in the market although EPC labels explained only 6-8 per cent of price variation. A second full hedonic model, which included apartment characteristics, revealed that EPC labels had no impact on prices. Originality/value In Italy EPC has been mandatory for house transactions since 2009, so there are few studies on the effect of EPC on the Italian real estate market at least to our knowledge. Furthermore, unusually for the Italian context, in this paper also transaction prices were analyzed, in addition to the more frequently used listing prices.

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