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 An Assessment of the Functioning of Shopping Centres in Central‑Eastern Europe on the Example of “Posnania Mall” in Poznań (Poland) and “Grand Mall” in Varna

2021 ◽  
Vol 15 (3) ◽  
pp. 99-113
Author(s):  
Sławomir Palicki ◽  
Stoyan Stoyanov ◽  
Ivo Kostov ◽  
Tsvetelina Atanasova ◽  
Patrycjusz Ostrowski
Keyword(s):  
Real Estate ◽  
Large Scale ◽  
Local Development ◽  
Real Estate Market ◽  
The European Union ◽  
Market Reactions ◽  
Shopping Centre ◽  
Shopping Centres ◽  
Central Eastern ◽  
The Impact

The article explores the issue of the function of shopping centres, in particular the analysis of the impact of their presence on society and the local development of cities and regions. Regarding the empirical aspect, the examples of Poznań (Poland) and Varna (Bulgaria) will be presented. As a result of similar socio‑economic conditions and joining the European Union at almost the same moment, all comparative studies reflecting preferences and market reactions seem both viable and interesting. In addition, the two cities chosen for the studies occupy a similar place in the hierarchy of the settlement network in their countries. They are large, well‑developed centres that attract the attention of investors from various segments of the real estate market. The research is part of the modelling of preferences of shopping centre customers areas, which in particular supports the investment decisions of developers operating in the analysed real estate market, and at the same time permits a diagnosis of social satisfaction. A derivative of the research is also the reconstruction of the effects of the functioning of large‑scale shopping malls in two Central‑Eastern European countries.

scholarly journals Cap rates and risk: a spatial analysis of commercial real estate

2018 ◽  
Vol 35 (1) ◽  
pp. 25-43
Author(s):  
Florian Unbehaun ◽  
Franz Fuerst
Keyword(s):  
Real Estate ◽  
Risk Perceptions ◽  
Large Scale ◽  
Risk Premia ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Data Series ◽  
Large Set ◽  
Content Type ◽  
The Impact

Purpose This study aims to assess the impact of location on capitalization rates and risk premia. Design/methodology/approach Using a transaction-based data series for the five largest office markets in Germany from 2005 to 2015, regression analysis is performed to account for a large set of asset-level drivers such as location, age and size and time-varying macro-level drivers. Findings Location is found to be a key determinant of cap rates and risk premia. CBD locations are found to attract lower cap rates and lower risk premia in three of the five largest markets in Germany. Interestingly, this effect is not found in the non-CBD locations of these markets, suggesting that the lower perceived risk associated with these large markets is restricted to a relatively small area within these markets that are reputed to be safe investments. Research limitations/implications The findings imply that investors view properties in peripheral urban locations as imperfect substitutes for CBD properties. Further analysis also shows that these risk premia are not uniformly applied across real estate asset types. The CBD risk effect is particularly pronounced for office and retail assets, apparently considered “prime” investments within the central locations. Originality/value This is one of the first empirical studies of the risk implications of peripheral commercial real estate locations. It is also one of the first large-scale cap rate analyses of the German commercial real estate market. The results demonstrate that risk perceptions of investors have a distinct spatial dimension.

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.

scholarly journals Valuation methods for the housing market: Evidence from Budapest

2016 ◽  
Vol 66 (3) ◽  
pp. 527-546 ◽  
Author(s):  
Dávid Kutasi ◽  
Milán Csaba Badics
Keyword(s):  
Neural Network ◽  
Real Estate ◽  
Large Scale ◽  
Housing Prices ◽  
Market Price ◽  
Housing Price ◽  
Real Estate Market ◽  
Hedonic Regression ◽  
Valuation Methods ◽  
Valuation Method

Different valuation methods and determinants of housing prices in Budapest, Hungary are examined in this paper in order to describe price drivers by using an asking price dataset. The hedonic regression analysis and the valuation method of the artificial neural network are utilised and compared using both technical and spatial variables. In our analyses, we conclude that according to our sample from the Budapest real estate market, the Multi-Layer Preceptron (MLP) neural network is a better alternative for market price prediction than hedonic regression in all observed cases. To our knowledge, the estimation of housing price drivers based on a large-scale sample has never been explored before in Budapest or any other city in Hungary in detail; moreover, it is one of the first papers in this topic in the CEE region. The results of this paper lead to promising directions for the development of Hungarian real estate price statistics.

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 Property Value, Urban Quality and Maintenance Condition: A Hedonic Analysis in the City of Naples, Italy

2014 ◽  
Vol 11 ◽  
pp. 560-565 ◽  
Author(s):  
Vincenzo del Giudice ◽  
Francesca Torrieri ◽  
Pierfrancesco de Paola
Keyword(s):  
Real Estate ◽  
Public Space ◽  
Urban Space ◽  
Property Values ◽  
Public Spaces ◽  
Real Estate Market ◽  
Property Value ◽  
Standard Requirement ◽  
The Impact ◽  
The City

The article examines the relationship between property value and level of conservation of public urban space. While many studies have examined the effect of proximity of open space, parks, and trees on property value, there has been few examination of how projects of urban revitalization and ordinary and extraordinary maintenances of public spaces can influence property values. While intuition can suggest that a low level of quality and maintenance of a public space can negatively affect property value, even if the standard requirement of public spaces and services are meet, this yet to be empirically proven.We proposes the application of a new econometric models for quantitative analysis of the characteristics of real estate property (Generalized Additive Model), to assess the impact of maintenance condition on property values, due to the better prevision that these functions can obtain in a real estate market context.The control of the formal and logical adequacy of the proposed theoretical model is referred to the case study under analysis, in the city of Naples. The results obtained show that a well preserved urban environment influences property price by approximately 6%. The experimental test of the model has provided results that, by reason of their formal consistency with the results obtained in other contexts, can be considered representative of the effectiveness of the methodology proposed.

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.

The impact of external factors on housing prices in Lithuania

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alina Stundziene ◽  
Vaida Pilinkienė ◽  
Andrius Grybauskas
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Housing Price ◽  
Real Estate Market ◽  
External Factors ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
The Impact

Purpose This paper aims to identify the external factors that have the greatest impact on housing prices in Lithuania. Design/methodology/approach The econometric analysis includes stationarity test, Granger causality test, correlation analysis, linear and non-linear regression modes, threshold regression and autoregressive distributed lag models. The analysis is performed based on 137 external factors that can be grouped into macroeconomic, business, financial, real estate market, labour market indicators and expectations. Findings The research reveals that housing price largely depends on macroeconomic indicators such as gross domestic product growth and consumer spending. Cash and deposits of households are the most important indicators from the group of financial indicators. The impact of financial, business and labour market indicators on housing price varies depending on the stage of the economic cycle. Practical implications Real estate market experts and policymakers can monitor the changes in external factors that have been identified as key indicators of housing prices. Based on that, they can prepare for the changes in the real estate market better and take the necessary decisions in a timely manner, if necessary. Originality/value This study considerably adds to the existing literature by providing a better understanding of external factors that affect the housing price in Lithuania and let predict the changes in the real estate market. It is beneficial for policymakers as it lets them choose reasonable decisions aiming to stabilize the real estate market.

scholarly journals Impact of the Economic Stimulus Measures on Lithuanian Real Estate Market under the Conditions of the COVID-19 Pandemic

2021 ◽  
Vol 32 (5) ◽  
pp. 459-468
Author(s):  
Vaida Pilinkienė ◽  
Alina Stundziene ◽  
Evaldas Stankevičius ◽  
Andrius Grybauskas
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Estate Market ◽  
Substantial Part ◽  
Negative Effects ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Economic Stimulus ◽  
The Impact

The COVID-19 pandemic caused a number of challenges worldwide regarding not only the human health perspective, but also the economic situation. Quarantine, imposed in many countries, forced a substantial part of businesses to close or narrow down their activities, thus leaving corporations and employees without any or with lower income. If national governments had not undertaken any actions to save national economies, the consequences could have been even more devastating. The real estate market is an important part of economy. Instability in the real estate market can cause financial problems, vulnerability of population’s welfare and other negative effects. This research aims to assess the impact of the economic stimulus measures on the real estate market under the conditions of the COVID-19 pandemic in Lithuania. The research methods include comparative analysis, correlation analysis, stationarity test, regression analysis and the ARDL models. The results indicate that the economic stimulus measures only partially contribute to stabilization of the real estate market in Lithuania. The drop in housing prices was 2.9 percent lower because of the economic stimulus in the second quarter of 2020. Maintenance of household cash and deposits as well as lending to business enterprises are the measures that allow to stabilize the real estate market in the shortest time under the conditions of the economic shock. The other governmental support measures are also important, especially if they are aimed at preserving jobs.

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