26th Annual European Real Estate Society Conference最新文献

{"title":"Huff Inspired Gravity Model in Valuation of homes near Scenic lands -- A geographically weighted regression based hedonic model","authors":"Jay Mittal, Sweta Byahut","doi":"10.15396/eres2019_242","DOIUrl":"https://doi.org/10.15396/eres2019_242","url":null,"abstract":"This research uses a hedonic Price modelling framework to assess the marginal implicit price effect of conservation easements (CE) lands on single family houses in Worcester, MA. The house price premium is anticipated with the growing visual accessibility from home to conservation easements lands. The CE lands of interest here are voluntarily protected, privately owned, scenic lands and are based in the urbanized area of City of Worcester, MA. The premium, and the visual accessibility was measured using the transaction of the surrounding homes, and homes spatial relationship with the CE lands. These protected CE lands are perpetually protected with natural, historic, and scenic characteristics that are attractive to the environmental amenity seekers. The home premiums as capitalized due to the visual accessibility of protected lands was measured using a combined weighted measure of ‘view’ and ‘proximity.' This was developed using the Huff's gravity model inspired index -- Gravity Inspired Visibility Index (GIVI). First, a detailed digital elevation model (DEM) raster with all view obstructing buildings and physicals structures stitched an the topography surface was generated and then the views and distances from homes to scenic lands were used to generate the GIVI, using the Viewshed analysis in ArcGIS. The geographically weighted regression (GWR) based hedonic model was then employed to measure the combined effect of both -- distance and view of scenic lands from each homes. Both the global (adjusted R sq =0.52, AICc =29,828) and the geographically weighted regression (GWR) models (adjusted R sq = 0.59, AICc =29,729) estimated the price effect, and the GWR model outperformed the global model. The results from the GWR model indicated an average 3.4% price premium on the mean value of homes in the study area. The spatial variation in home premiums (as percentage values) was also found clearer and more spatially clustered in the GWR model. The highest premium value for select homes in the sample was found to be as high as 34.6% of the mean home price. This is a significant effect of visual accessibility to the preserved scenic lands for land conservation. This research offers a useful framework for evaluating the effect of land protection for land use planning, land conservation and for real estate valuation purposes. It also offers useful insights for conservation agencies, local governments, professional planners, and real estate professionals for prioritizing land sites with scenic views.","PeriodicalId":152375,"journal":{"name":"26th Annual European Real Estate Society Conference","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127369354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Big Is the Airbnb Rent Premium? The Case of Sydney","authors":"Miriam Steurer, R. Hill, Norbert Pfeifer","doi":"10.15396/eres2019_243","DOIUrl":"https://doi.org/10.15396/eres2019_243","url":null,"abstract":"The rapid expansion of Airbnb has led to concerns that it is crowding-out long-term rentals. We consider how strong is the incentive for landlords to switch properties to Airbnb. The Airbnb rent premium is defined here as the ratio of what a landlord can charge on Airbnb versus inthe long-term rental market. Using hedonic regression methods applied to micro-level data on long-term rentals (about a million observations) and Airbnb listings (about 190,000 observations), we calculate the size of the Airbnb rent premium for all the properties in our datasets. On average we find that landlords can earn about 90 percent more per week on Airbnb than in the long-term rental market. The premium is even larger for properties with three or more bedrooms. We find some evidence of a higher Airbnb premium in more expensive postcodes, and those with a higher Airbnb density. We also find that the Airbnb rent premium decreases slightly from 2015 to 2017.","PeriodicalId":152375,"journal":{"name":"26th Annual European Real Estate Society Conference","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133766027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risks in International Real Estate Investment: The Case of Central and Eastern Europe","authors":"Kateryna Kurylchyk","doi":"10.15396/eres2019_334","DOIUrl":"https://doi.org/10.15396/eres2019_334","url":null,"abstract":"International real estate diversification provides significant benefits which are inevitably associated with considerable risks and costs. This requires a thorough analysis of options in order to take account of substantial uncertainty and foreignness implied by international investment per se, as well as the real estate market risks inherent in foreign countries. These factors are intensified by economic distresses and make real estate investors use more discretion in their operations abroad. A similar situation has been observed in Central and Eastern Europe (CEE) after the events of 2008. In the face of downturn, market players have become cautious about investing in this region and shifted their investments away from many once booming markets. In other words, the crisis resulted in an increased perception of risk and a change towards more selective investment strategies in CEE, with international investors unprepared to take high country risks even though property risks may be low. Hence, relatively more importance is attached to country risks vs. property specifics and gains when making investment decisions. Among numerous academic papers on real estate investment risks and decision-making factors in the international context, there are only few undertaken for the CEE countries. This study has been motivated by the perceived shortage of research on real estate markets and investment decision-making factors in CEE, as well as the need for understanding these aspects in order to ensure sound investments in the region. It aims to identify major risks of investing in real estate, with a particular focus on selected CEE countries. The study reviews in the first instance the existing publications on international real estate investment and summarizes common risks and factors affecting relevant decision-making. The complexity of country risk as a composite risk and its components are addressed by creating a country risk framework. Further, real estate investment trends and issues in the CEE markets are discussed, with specific investment risks for the CEE region identified. Finally, the importance of the factors influencing investment decision-making, as perceived by international investors in the region, is studied through a questionnaire survey.Altogether this exploratory research contributes to the understanding of barriers and risks of international real estate investment while assisting investors in improving their perception of opportunities and implications associated with property investments in the CEE region.","PeriodicalId":152375,"journal":{"name":"26th Annual European Real Estate Society Conference","volume":"13 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116775360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AVMs: An international comparison of the opportunities and challenges","authors":"Lynn Johnson, Ronald S. Weberndorfer, Wolfgang Feilmayr, Kauko Viitanen","doi":"10.15396/eres2019_189","DOIUrl":"https://doi.org/10.15396/eres2019_189","url":null,"abstract":"The definition of AVM has been disputed across academia with a number of references excluding the inclusion of human interaction suggesting that models need to work independently from a professional. RICS describe an AVM (2008) ‘as one or more mathematical techniques to provide an estimate of value of a specified property at a specified date, accompanied by a measure of confidence in the accuracy of the result, without human intervention post initiation.’ An AVM is a mathematical model operated through computer software to determine Market Value or Market Rent of a property. There are several types of AVM including Artificial Neural Networks and Multiple Regression Analysis. According to Susskind and Susskind (2015) the professions are becoming antiquated, opaque, no longer affordable and unsustainable in an era of increasingly capable expert systems. This sentiment would appear to be spreading within the real estate world Property Technology or Proptech is now a term which features heavily in real estate press, professional bodies and to some extent academia. RICS, in their 2017 publication on the impact of emerging technologies on the surveying profession and subsequent (2017) paper into the future of valuation, the latter of which considers how the valuation process is undertaken and managed. It identifies two main issues or disruptors, technological developments and changing client expectations, both of which may provide increased pressure for the profession to adopt AVMs in both residential and commercial real estate. As Klaus Schwab, the founder and executive chair of the World Economic forum stated in 2016 there is a revolution which is fundamentally altering the way we live and work it is providing huge opportunities for business growth but also circumstances for disruptive innovation.Most Research on AVMs has explored how they are employed in residential markets (see Boshoff & Kock, 2013). It is apparent that European countries such as Germany, Romania, Netherlands and most recently Sweden have all introduced AVM legislation to ensure quality and assurance within the current valuation processes (European Mortgage Federation, 2017). However, there is little research into implementation of AVMs in commercial real estate. Gilbertson and Preston (2005) believed that this was due to the lack of transparency and accurate data available for commercial property transactions. A salient point established by Boshoff and De Kock (2013) is that many professionals consider commercial valuations as intricate, commercial property is classed as heterogeneous and not easily fungible (in comparison to stocks and shares). Illustrating this complexity, recent research carried out by Amidu and Boyd (2017) suggests that when commercial real estate professionals undertake valuations, they are problem solvers. They tend to use their own tacit knowledge and expertise of markets.There are opportunities and challenges for all involved with commercial real estate va","PeriodicalId":152375,"journal":{"name":"26th Annual European Real Estate Society Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131235012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Why do Natives and non-Natives in the United Kingdom have different Spatial Patterns?","authors":"Olayiwola Oladiran, Anupam Nanda, G. Pouyanne, Stéphane Virol","doi":"10.15396/eres2019_39","DOIUrl":"https://doi.org/10.15396/eres2019_39","url":null,"abstract":"The United Kingdom, like other OECD countries, has attracted a high number of immigrants from around the world in the last half-century. The liberalisation of immigration for commonwealth citizens between 1948 and 1972 and subsequent accession to the European Economic Community afterward set the stage for the heterogeneity of the UK population. Housing is an intrinsic element of an immigrant’s voyage and is typically linked with local and regional spatial patterns. Thus, the UK regional and local spatial dynamics may also be linked to the dynamic forces of immigration waves to the UK in the last half-century. Anecdotal evidence suggests that immigrants in the UK prefer to settle in the South-east of England compared to other regions of the UK. London particularly houses approximately 2.8 million immigrants, which is over 40% of the total immigrant stock, thus, immigrant and ethnic clusters are entrenched and expanding. Literature reveals that factors such as regional economics, regional housing markets, regional labour markets, and urban dynamics are key determinants of regional and metropolitan spatial patterns. Furthermore, individual taste and preferences, socio-economic factors, demographic factors, and socio-cultural factors also play major roles in defining local and neighbourhood patterns. This paper aims to empirically analyse other factors which may be influencing regional and local spatial patterns of natives and non-natives beyond the conventional factors accounted for in literature, and on a multi-generational scale. Using the UK Longitudinal Survey data which captures the demographic, socio-economic, socio-cultural and spatial patterns of natives and non-natives, we model the spatial patterns of UK natives and multiple generations of non-natives. Our core interest is to find out particularly why South-east England and the Greater London areas receive a higher proportion of migrants compared to other parts of the UK despite the affordability challenges in these areas. Furthermore, we analyse the effects of immigrant clusters on the spatial patterns of natives. By analysing the regional and local patterns of immigrants, we can improve insight on the social and economic integration of first and second-generation immigrants. Furthermore, we are able to identify the unique patterns of second-generation immigrants and compare these to natives and to first-generation immigrants in a unique way that has previously not been applied to spatial modelling. Additionally, by mapping the spatial patterns of natives and multiple generations of non-natives, we can link these patterns to housing demand, rents and house prices at regional, metropolitan, local and neighbourhood levels. More fundamentally, the impact of immigrants on the local economy is a highly debatable topic globally, hence the findings will improve insight for policymakers, urban planners, housing economists, and political economists.","PeriodicalId":152375,"journal":{"name":"26th Annual European Real Estate Society Conference","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132721672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"House price and rent developments in Europe after the financial crisis","authors":"Peter Parlasca, Bogdan Marola","doi":"10.15396/eres2019_276","DOIUrl":"https://doi.org/10.15396/eres2019_276","url":null,"abstract":"The presentation will deliver a European picture of developments in residential real estate after the financial crisis. The Eurostat database contains data on House price indices (HPI) at national level for all EU member states. The data starts in 2005 for some countries, and later for the others. From 2010 onwards, the available data allows a comparison encompassing all EU Member states plus Norway and Island.The advantage of the Eurostat data is that it is official data, compiled based on transaction prices and following a harmonised methodology across countries. The objective of this presentation is to show how this database can provide reliable answers to the following questions:How deep was the dip in the EU countries? When did the various countries pass with HPI pre-crisis levels? Who were the best performers in the last decade?The Eurostat database also contains data on the evolution of prices for new and existing dwellings. This presentation will reveal how the Eurostat database can be used to shed light on the analysis of the different patterns of the HPI for new and existing dwellings during the crisis and the following recovery. We show that by taking into account the dynamics of construction activity and sales of new dwellings during and after the crisis, the Eurostat data can be effectively used in the analysis of the evolution of housing markets in the EU in the last decade. A special focus will be on the countries having received a warning from the European Systemic Risk Board (ESRB) at end 2016 having identified these residential real estate markets as a risk for financial stability.Furthermore, we show how this data can be combined with data on rent prices evolution available also in the Eurostat database from the section dedicated to the Harmonized Index of Consumer Prices. One relevant question is: did rent developments between 2008 and 2018 show similar patterns to house prices or were the rents developments much softer? Knowing what the data represents helps for a correct interpretation of the official figures.In summary, these datasets being official statistics published by Eurostat support to analyse both longer-term developments like recoveries after the crisis or latest developments indicating towards overheated residential real estate markets.","PeriodicalId":152375,"journal":{"name":"26th Annual European Real Estate Society Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134383495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Motivations to become a member of a housing cooperative: Comparison of the national characteristics of Sweden, Germany and the USA","authors":"Lena Fahrner, Elisabeth Beusker, Theresa Kotulla","doi":"10.15396/eres2019_118","DOIUrl":"https://doi.org/10.15396/eres2019_118","url":null,"abstract":"Cooperative housing systems vary depending on different aspects for example in which urban context they are formed, which country specific legislation they observe and which purpose they suit. In general, a housing cooperative is a coalition of people, who wants to be shareholders of real estate projects. On one hand, being member of such a legal corporation is a kind of home ownership. The cooperative corporation owns the land and the buildings. On the other hand, members pay a monthly amount to cover the running expenses of all real estates of the cooperative. Summarizing, they live in the cooperative and they run the cooperative. Today, members of housing cooperatives have different motivations to become part of a cooperation. The affordability of the dwelling is just one of the advantages. Urban structures and residential markets change constantly. Furthermore, the expectations of the population regarding their housing conditions change. These are some of the reasons why the motivations to become member of a housing cooperative vary widely. Within this paper different cooperative housing systems in Sweden, Germany and the USA are analyzed and compared. Thereby, the focus is on the motivations of the members. The aim of this research is to illustrate the different motives of people to become part of a housing cooperative in the selected countries. Sweden,","PeriodicalId":152375,"journal":{"name":"26th Annual European Real Estate Society Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125619815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance of Real Estate Investment Trusts In African Real Estate Markets: A Case Study of Nigeria","authors":"D. Dabara, Adebayo Ogunba, John Oyekunle Soladoye, Augustina Chiwuzie","doi":"10.15396/eres2019_36","DOIUrl":"https://doi.org/10.15396/eres2019_36","url":null,"abstract":"Purpose: This study examined the correlations among the structure, conduct and performance of Real Estate Investment Trusts in Nigeria (N-REITs) with a view to providing information that will enhance and guide real estate investment decisions. Design/Methods followed/Approach: The study population consisted of all the three REIT companies in Nigeria namely: Skye Shelter Fund, Union Home REITs and UACN Property Development Company (UPDC) REITs. Secondary data on dividends and share prices of N-REITs; Total Business Revenues (TBR) and Total Individual Expenditure (TIE) on conduct variables were sourced from periodicals of the respective companies covering the period from 2008 to 2016. The data series for the study were analyzed by means of the Granger Causality tests, Kwiatkowski-Phillips-Schimidt-Shin (KPSS) unit root tests, Philip-Perron (PP) unit root tests and the ordinary least square regression (OLS). Findings: The study showed a Herfindahl Hischman Index (HHI) that ranged between 41.81% (recorded in 2010) and 100% recorded in 2008. This suggested a high concentration in the N-REITs industry. Similarly, the study found that the returns on investment in the industry ranged between -0.24% and 22.07%. The Granger Causality Test conducted revealed a bi-directional causal relationship among the structure, conduct and performance of N-REITs.Practical Implication: The study provided essential information for stakeholders in the real estate sector regarding the influence of structure and conduct on the performance of N-REITs. This information will be valuable for equipping asset managers, insurance companies, pension funds as well as individual real estate investors in making informed investment decisions. Originality/Value: This study is unique as it is the first to draw a link between the structure, conduct and performance of REITs in an African emerging real estate market which was hitherto not considered in previous studies.","PeriodicalId":152375,"journal":{"name":"26th Annual European Real Estate Society Conference","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122717978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Behavioral Explanation to Spatial Dependencies in Commercial Real Estate Asset Prices","authors":"P. Das, P. Sinha, J. Freybote, Roland Fuess","doi":"10.15396/eres2019_29","DOIUrl":"https://doi.org/10.15396/eres2019_29","url":null,"abstract":"In this study we provide a behavioral explanation for spatial dependence in commercial property asset pricing. We analyze nearly 6000 hotel transactions in the US between 2001 and 2016 applying temporal spatial autoregression with autoregressive error (T-SARAR) models to test the behavioral explanation. We show that the spatial lags are partially driven by behavioral biases whereas the spatial errors do not exhibit a distinct pattern of association with market conditions which are known to influence the investor behavior. In particular, spatial lags influence future transactions the most when irrational sentiments are the lowest (during periods of unexplained pessimism) or when the rational financial market anxiety is the highest (during periods of economic turmoil).","PeriodicalId":152375,"journal":{"name":"26th Annual European Real Estate Society Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123991250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Kickstarting the energy transition: opportunities, limitations and welfare implications of social landlords’ ambitions","authors":"F. Schilder","doi":"10.15396/eres2019_313","DOIUrl":"https://doi.org/10.15396/eres2019_313","url":null,"abstract":"The Netherlands, like countries throughout Europe, face enormous challenges realizing the goals set in the 2015 Paris agreement. Real estate, and more specifically residential real estate, bears the potential to contribute significantly to realizing climate goals. Towards meeting the Paris agreement goals the Dutch housing market will need to become energy neutral in 2050. Progress in making housing more energy efficient has been slow so far. Possibly as a result of the slow pace of investments in energy efficiency anticipated price decreases following the industrialization of energy solutions are yet to be realized. Housing associations have recently proposed to become the frontrunner in the energy transition on the housing market: economies of scale, a limited number of agents owning roughly 30% of the total housing stock, and fairly deep pockets make good arguments for this ambition. However, this ambition comes at a cost as well: how feasible is kickstarting the energy transition within the sector in charge of housing the lowest income households? What are the necessary conditions to make this kickstart work? And what are broader welfare implications, in terms of (reduced investment potential in) local living conditions, and affordability? Some preliminary findings of a mixed-methods study.","PeriodicalId":152375,"journal":{"name":"26th Annual European Real Estate Society Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127738988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}