Pub Date : 2021-06-24DOI: 10.1108/jerer-11-2020-0057
M. Doszyń
PurposeThe purpose of this paper is to present how prior knowledge about the impact of real estate features on value might be utilised in the econometric models of real estate appraisal. In these models, price is a dependent variable and real estate features are explanatory variables. Moreover, these kinds of models might support individual and mass appraisals.Design/methodology/approachA mixed estimation procedure was discussed in the research. It enables using sample and prior information in an estimation process. Prior information was provided by real estate experts in the form of parameter intervals. Also, sample information about the prices and features of undeveloped land for low-residential purposes was used. Then, mixed estimation results were compared with ordinary least squares (OLS) outcomes. Finally, the estimated econometric models were assessed with regard to both formal criteria and valuation accuracy.FindingsThe OLS results were unacceptable, mostly because of the low quality of the database, which is often the case on local, undeveloped real estate markets. The mixed results are much more consistent with formal expectations and the real estate valuations are also better for a mixed model. In a mixed model, the impact of each real estate feature could be estimated, even if there is no variability in the sample information. Valuations are also more precise in terms of their consistency with market prices. The mean error (ME) and mean absolute percentage error (MAPE) are lower for a mixed model.Originality/valueThe crucial problem in econometric property valuation is that it involves the unreliability of databases, especially on undeveloped, local markets. The applied mixed estimation procedure might support sample information with prior knowledge, in the form of stochastic restrictions imposed on parameters. Thus, that kind of knowledge might be obtained from real estate experts, practitioners, etc.
{"title":"Prior information in econometric real estate appraisal: a mixed estimation procedure","authors":"M. Doszyń","doi":"10.1108/jerer-11-2020-0057","DOIUrl":"https://doi.org/10.1108/jerer-11-2020-0057","url":null,"abstract":"PurposeThe purpose of this paper is to present how prior knowledge about the impact of real estate features on value might be utilised in the econometric models of real estate appraisal. In these models, price is a dependent variable and real estate features are explanatory variables. Moreover, these kinds of models might support individual and mass appraisals.Design/methodology/approachA mixed estimation procedure was discussed in the research. It enables using sample and prior information in an estimation process. Prior information was provided by real estate experts in the form of parameter intervals. Also, sample information about the prices and features of undeveloped land for low-residential purposes was used. Then, mixed estimation results were compared with ordinary least squares (OLS) outcomes. Finally, the estimated econometric models were assessed with regard to both formal criteria and valuation accuracy.FindingsThe OLS results were unacceptable, mostly because of the low quality of the database, which is often the case on local, undeveloped real estate markets. The mixed results are much more consistent with formal expectations and the real estate valuations are also better for a mixed model. In a mixed model, the impact of each real estate feature could be estimated, even if there is no variability in the sample information. Valuations are also more precise in terms of their consistency with market prices. The mean error (ME) and mean absolute percentage error (MAPE) are lower for a mixed model.Originality/valueThe crucial problem in econometric property valuation is that it involves the unreliability of databases, especially on undeveloped, local markets. The applied mixed estimation procedure might support sample information with prior knowledge, in the form of stochastic restrictions imposed on parameters. Thus, that kind of knowledge might be obtained from real estate experts, practitioners, etc.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86546025","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}
Pub Date : 2021-06-22DOI: 10.1108/jerer-10-2020-0053
A. M. Cunha, Júlio Lobão
PurposeThis paper explores the real estate price determinants at four geographical levels: in the European Union as a whole, in the 28 European Union countries, in one European Union country (Portugal) and in 25 Portuguese metropolitan statistical areas (MSAs).Design/methodology/approachThe authors run two time series regression models and two panel data regression models with observations of potential real estate price determinants and House Price Indices collected from Eurostat.FindingsThe results show that price determinants, such as gross domestic product (GDP), interest rates, housing starts and tourism, are statistically significant, but not in all the four geographical levels of analysis. The results also confirm the autoregressive characteristic of real estate prices, with the last period price change being the most important determinant of current period real estate price change.Practical implicationsForecasting real estate prices can be made more effective by knowing that each geographical level of analysis implies different price determinants and that momentum is an important determinant in real estate returns.Originality/valueTo the best of the authors knowledge, this is the first study to develop and test a real estate price equilibrium model at several different geographical levels of the same political space.
{"title":"The determinants of real estate prices in a European context: a four-level analysis","authors":"A. M. Cunha, Júlio Lobão","doi":"10.1108/jerer-10-2020-0053","DOIUrl":"https://doi.org/10.1108/jerer-10-2020-0053","url":null,"abstract":"PurposeThis paper explores the real estate price determinants at four geographical levels: in the European Union as a whole, in the 28 European Union countries, in one European Union country (Portugal) and in 25 Portuguese metropolitan statistical areas (MSAs).Design/methodology/approachThe authors run two time series regression models and two panel data regression models with observations of potential real estate price determinants and House Price Indices collected from Eurostat.FindingsThe results show that price determinants, such as gross domestic product (GDP), interest rates, housing starts and tourism, are statistically significant, but not in all the four geographical levels of analysis. The results also confirm the autoregressive characteristic of real estate prices, with the last period price change being the most important determinant of current period real estate price change.Practical implicationsForecasting real estate prices can be made more effective by knowing that each geographical level of analysis implies different price determinants and that momentum is an important determinant in real estate returns.Originality/valueTo the best of the authors knowledge, this is the first study to develop and test a real estate price equilibrium model at several different geographical levels of the same political space.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75127073","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}
Pub Date : 2021-06-14DOI: 10.1108/JERER-09-2020-0050
Cath Jackson, A. Orr
Purpose The importance of real estate’s sustainability rating has increased significantly. Studies undertaken in 2007 and 2016 show that, at acquisition, the rating rose from 7th to 3rd most important attribute. This shift in priorities parallels the RICS embracing the 10 principles of the UN Global Compact (RICS, 2015). However, while sustainability value premia appear common in some international markets, the picture is mixed and drivers and mechanisms lack empirical investigation. The literature reveals potential barriers to investors fulfilling both sustainability and financial objectives. The purpose of this study is explore these potential barriers. Design/methodology/approach Focus groups with real estate fund managers, sustainability managers and acquisitions surveyors are undertaken to explore the adoption and implementation of environmental sustainability policies. This reveals a series of barriers to implementation and these are then explored in greater depth through a series of interviews with fund managers. This layered, qualitative approach is designed to provide detailed knowledge of practical and conceptual sustainability issues within the UK real estate market. Findings Key drivers underpinning the adoption of sustainability policies are revealed and barriers to implementation are found to relate to data on investment performance, valuation methodologies and prohibitive capex. Further, the heterogeneous, opaque and slow-moving nature of the market is prohibitive and intervention is encouraged to overcome the lack of financial viability that hinders improvements. Originality/value Research is dominated by highly aggregated quantitative data on sustainability within commercial real estate markets. The qualitative approach used here adds new insights and value to the understanding of the embeddedness of sustainability in real estate investment decision-making.
{"title":"The embeddedness of sustainability in real estate investment decision-making","authors":"Cath Jackson, A. Orr","doi":"10.1108/JERER-09-2020-0050","DOIUrl":"https://doi.org/10.1108/JERER-09-2020-0050","url":null,"abstract":"Purpose \u0000The importance of real estate’s sustainability rating has increased significantly. Studies undertaken in 2007 and 2016 show that, at acquisition, the rating rose from 7th to 3rd most important attribute. This shift in priorities parallels the RICS embracing the 10 principles of the UN Global Compact (RICS, 2015). However, while sustainability value premia appear common in some international markets, the picture is mixed and drivers and mechanisms lack empirical investigation. The literature reveals potential barriers to investors fulfilling both sustainability and financial objectives. The purpose of this study is explore these potential barriers. \u0000 \u0000Design/methodology/approach \u0000Focus groups with real estate fund managers, sustainability managers and acquisitions surveyors are undertaken to explore the adoption and implementation of environmental sustainability policies. This reveals a series of barriers to implementation and these are then explored in greater depth through a series of interviews with fund managers. This layered, qualitative approach is designed to provide detailed knowledge of practical and conceptual sustainability issues within the UK real estate market. \u0000 \u0000Findings \u0000Key drivers underpinning the adoption of sustainability policies are revealed and barriers to implementation are found to relate to data on investment performance, valuation methodologies and prohibitive capex. Further, the heterogeneous, opaque and slow-moving nature of the market is prohibitive and intervention is encouraged to overcome the lack of financial viability that hinders improvements. \u0000 \u0000Originality/value \u0000Research is dominated by highly aggregated quantitative data on sustainability within commercial real estate markets. The qualitative approach used here adds new insights and value to the understanding of the embeddedness of sustainability in real estate investment decision-making.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76685724","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}
Pub Date : 2021-06-10DOI: 10.1108/JERER-11-2019-0043
Zhenyu Su, P. Taltavull
Purpose This paper aims to analyse the risk and excess returns of the Spanish real estate investment trusts (S-REITs) using various methods, though focusing primarily on the Fama-French three-factor (FF3) model, over the period from 2007Q3 to 2017Q2. Design/methodology/approach The autoregressive distributed lag model is used for the empirical analysis to test long-term stable relationships between variables. Findings The findings indicate that the FF3 model is suitable for the S-REITs market, better explaining the S-REITs’ returns variation than the traditional single-index capital asset pricing model (CAPM) and the Carhart four-factor model. The empirical evidence is reasonably consistent with the FF3 model; the values for the market, size and value are highly statistically significant over the analysis period, with 68.7% variation in S-REITs’ returns explained by the model. In the long run, the market factor has less explanatory power than the size and value factors; the positive long-term multiplier of the size factor indicates that small S-REIT companies have higher returns, along with higher risk, while the negative multiplier of the value indicator suggests that S-REITs portfolios prefer to allocate growth REITs with low book-to-market ratios. The empirical findings from a modified FF3 model, which additionally incorporates Spain’s gross domestic product (GDP) growth rate, two consumer price index (CPI) macro-factors and three dummy variables, indicates that GDP growth rate and CPI also affect S-REITs’ yields, while investment funds with capital calls have a small influence on S-REITs’ returns. Practical implications The regression results of the standard and extended FF3 model can help researchers understand S-REITs’ risk and return through a general stock pattern. Potential investors are given more information to consider the new Spanish investment vehicle before making a decision. Originality/value The paper uses standard techniques but applies them for the first time to the S-REIT market.
{"title":"Applying the Fama and French three-factor model to analyze risk/reward in the Spanish REITs: an ARDL approach","authors":"Zhenyu Su, P. Taltavull","doi":"10.1108/JERER-11-2019-0043","DOIUrl":"https://doi.org/10.1108/JERER-11-2019-0043","url":null,"abstract":"\u0000Purpose\u0000This paper aims to analyse the risk and excess returns of the Spanish real estate investment trusts (S-REITs) using various methods, though focusing primarily on the Fama-French three-factor (FF3) model, over the period from 2007Q3 to 2017Q2.\u0000\u0000\u0000Design/methodology/approach\u0000The autoregressive distributed lag model is used for the empirical analysis to test long-term stable relationships between variables.\u0000\u0000\u0000Findings\u0000The findings indicate that the FF3 model is suitable for the S-REITs market, better explaining the S-REITs’ returns variation than the traditional single-index capital asset pricing model (CAPM) and the Carhart four-factor model. The empirical evidence is reasonably consistent with the FF3 model; the values for the market, size and value are highly statistically significant over the analysis period, with 68.7% variation in S-REITs’ returns explained by the model. In the long run, the market factor has less explanatory power than the size and value factors; the positive long-term multiplier of the size factor indicates that small S-REIT companies have higher returns, along with higher risk, while the negative multiplier of the value indicator suggests that S-REITs portfolios prefer to allocate growth REITs with low book-to-market ratios. The empirical findings from a modified FF3 model, which additionally incorporates Spain’s gross domestic product (GDP) growth rate, two consumer price index (CPI) macro-factors and three dummy variables, indicates that GDP growth rate and CPI also affect S-REITs’ yields, while investment funds with capital calls have a small influence on S-REITs’ returns.\u0000\u0000\u0000Practical implications\u0000The regression results of the standard and extended FF3 model can help researchers understand S-REITs’ risk and return through a general stock pattern. Potential investors are given more information to consider the new Spanish investment vehicle before making a decision.\u0000\u0000\u0000Originality/value\u0000The paper uses standard techniques but applies them for the first time to the S-REIT market.\u0000","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83022250","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}
Pub Date : 2021-06-08DOI: 10.1108/JERER-09-2020-0051
Maria Nikitidou, F. Archontakis, Athanasios Tagkalakis
Purpose This study aims to determine how the prices of residential properties in the Greek real estate sector are affected by their structural characteristics and by the prevailing economic factors during recession. Design/methodology/approach Based on 13,835 valuation reports for the city of Athens, covering a period of 11 years (2006–2016), this study develops a series of econometric models, taking into account both structural characteristics of the property market and the macroeconomic relevant variables. Finally, the city of Athens is divided into sub-regions and the different effects of the structural factors in each area are investigated via spatial analysis confirming the validity of the baseline model. Findings Findings show that the size, age, level, parking and storage space can explain the property price movements. Moreover, the authors find evidence that it is primarily house demand variables (e.g. the annual average wage, the unemployment rate, the user cost of capital, financing constraints and expectations about the future course of the house market) that affect house prices in a statistically significant manner and with the correct sign. Finally, using a difference-in-differences approach, this study finds that an increase in house demand (on account of net migration) led to higher house prices in smaller and older than in larger and younger apartments in areas with high concentration of immigrants. Originality/value This study uses a novel data set to help entities, individuals and policy-makers to understand how the recent economic and financial crisis has affected the real estate market in Athens.
{"title":"Real estate development in the city of Athens during the financial crisis","authors":"Maria Nikitidou, F. Archontakis, Athanasios Tagkalakis","doi":"10.1108/JERER-09-2020-0051","DOIUrl":"https://doi.org/10.1108/JERER-09-2020-0051","url":null,"abstract":"\u0000Purpose\u0000This study aims to determine how the prices of residential properties in the Greek real estate sector are affected by their structural characteristics and by the prevailing economic factors during recession.\u0000\u0000\u0000Design/methodology/approach\u0000Based on 13,835 valuation reports for the city of Athens, covering a period of 11 years (2006–2016), this study develops a series of econometric models, taking into account both structural characteristics of the property market and the macroeconomic relevant variables. Finally, the city of Athens is divided into sub-regions and the different effects of the structural factors in each area are investigated via spatial analysis confirming the validity of the baseline model.\u0000\u0000\u0000Findings\u0000Findings show that the size, age, level, parking and storage space can explain the property price movements. Moreover, the authors find evidence that it is primarily house demand variables (e.g. the annual average wage, the unemployment rate, the user cost of capital, financing constraints and expectations about the future course of the house market) that affect house prices in a statistically significant manner and with the correct sign. Finally, using a difference-in-differences approach, this study finds that an increase in house demand (on account of net migration) led to higher house prices in smaller and older than in larger and younger apartments in areas with high concentration of immigrants.\u0000\u0000\u0000Originality/value\u0000This study uses a novel data set to help entities, individuals and policy-makers to understand how the recent economic and financial crisis has affected the real estate market in Athens.\u0000","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77357411","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}
Pub Date : 2021-05-27DOI: 10.1108/JERER-09-2020-0049
Simen Dalland, R. Hammervold, Henrik Tangen Karlsen, A. Oust, Ole Jakob Sønstebø
Purpose This paper aims to study aggressive bidding strategies in real estate auctions – a structural equation modelling (SEM) approach. Design/methodology/approach The authors use two data sets to study aggressive bidding strategies. First, the results from a survey with 1,803 participants examining real estate auctions are used to identify bidding strategies and related motivations. Second, the authors apply SEM by using data from 1,078 exclusive auction journals from real estate sales in Norway to study both the direct and indirect price effects of the bidding strategies. Findings The authors define four aggressive bidding strategies: high opening bid, high bid increase (jump bids), short acceptance deadline and short response time. The authors find that all four strategies yield a higher sales price. Bidders can actively influence the behaviour of the other participants and cool the potential auction fever, thus reducing the final price premium. Originality/value This paper gives households, investors and policymakers a better understanding of how bidding strategies affect real estate auctions and the final price.
{"title":"Aggressive bidding strategies in real estate auctions – a structural equation modelling (SEM) approach","authors":"Simen Dalland, R. Hammervold, Henrik Tangen Karlsen, A. Oust, Ole Jakob Sønstebø","doi":"10.1108/JERER-09-2020-0049","DOIUrl":"https://doi.org/10.1108/JERER-09-2020-0049","url":null,"abstract":"\u0000Purpose\u0000This paper aims to study aggressive bidding strategies in real estate auctions – a structural equation modelling (SEM) approach.\u0000\u0000\u0000Design/methodology/approach\u0000The authors use two data sets to study aggressive bidding strategies. First, the results from a survey with 1,803 participants examining real estate auctions are used to identify bidding strategies and related motivations. Second, the authors apply SEM by using data from 1,078 exclusive auction journals from real estate sales in Norway to study both the direct and indirect price effects of the bidding strategies.\u0000\u0000\u0000Findings\u0000The authors define four aggressive bidding strategies: high opening bid, high bid increase (jump bids), short acceptance deadline and short response time. The authors find that all four strategies yield a higher sales price. Bidders can actively influence the behaviour of the other participants and cool the potential auction fever, thus reducing the final price premium.\u0000\u0000\u0000Originality/value\u0000This paper gives households, investors and policymakers a better understanding of how bidding strategies affect real estate auctions and the final price.\u0000","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81847640","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}
Pub Date : 2021-05-20DOI: 10.1108/JERER-08-2020-0048
H. Cooke, R. Appel-Meulenbroek, T. Arentze
Purpose This paper aims to identify the importance of individual variables in the corporate real estate (CRE) decision-making process. Design/methodology/approach Nine experts received a posed scenario of a changed business strategy requiring a CRE reduction in individual interviews. Based on their suggested response, a decision network was modelled for each expert using the causal network elicitation technique, incorporating the utilities for decision variables and importance weights for attributes and benefits. The decision model offers a graphical representation of decision-benefit links for the decisions CRE managers make in such a period of decline. Findings Perceived facilitators of CRE dynamic alignment were identified by calculating lift ratios on their perceived importance of the attributes they mentioned during the interviews as nodes in the network that link decisions to benefits. Facilitators included CRE metrics and workplace strategy, while capital expenditure and landlords inhibit alignment processes. The research provides more granular insight into the variables used in CRE decision-making and the factors that facilitate or inhibit the dynamic alignment process. Research limitations/implications The research set a specific scenario for the experts to consider. That could be regarded as small but there was clear evidence of saturation of expert knowledge. Additional face-to-face interviews with the experts may have generated further details on the thought processes of the experts. Practical implications The research provides more granular insight into the variables used in CRE decision-making and the factors that facilitate or inhibit the dynamic alignment process. Thereby providing CRE decision-makers with key elements for a decision model. Originality/value The research technique, causal network elicitation technique, uses semi-structured interviews to create decision networks, which is a technique that has not been widely applied to CRE research. The research provides a granular view of what are important inhibitors or facilitators of dynamic alignment of CRE to business strategy.
{"title":"Inhibitors and facilitators of corporate real estate dynamic alignment","authors":"H. Cooke, R. Appel-Meulenbroek, T. Arentze","doi":"10.1108/JERER-08-2020-0048","DOIUrl":"https://doi.org/10.1108/JERER-08-2020-0048","url":null,"abstract":"\u0000Purpose\u0000This paper aims to identify the importance of individual variables in the corporate real estate (CRE) decision-making process.\u0000\u0000\u0000Design/methodology/approach\u0000Nine experts received a posed scenario of a changed business strategy requiring a CRE reduction in individual interviews. Based on their suggested response, a decision network was modelled for each expert using the causal network elicitation technique, incorporating the utilities for decision variables and importance weights for attributes and benefits. The decision model offers a graphical representation of decision-benefit links for the decisions CRE managers make in such a period of decline.\u0000\u0000\u0000Findings\u0000Perceived facilitators of CRE dynamic alignment were identified by calculating lift ratios on their perceived importance of the attributes they mentioned during the interviews as nodes in the network that link decisions to benefits. Facilitators included CRE metrics and workplace strategy, while capital expenditure and landlords inhibit alignment processes. The research provides more granular insight into the variables used in CRE decision-making and the factors that facilitate or inhibit the dynamic alignment process.\u0000\u0000\u0000Research limitations/implications\u0000The research set a specific scenario for the experts to consider. That could be regarded as small but there was clear evidence of saturation of expert knowledge. Additional face-to-face interviews with the experts may have generated further details on the thought processes of the experts.\u0000\u0000\u0000Practical implications\u0000The research provides more granular insight into the variables used in CRE decision-making and the factors that facilitate or inhibit the dynamic alignment process. Thereby providing CRE decision-makers with key elements for a decision model.\u0000\u0000\u0000Originality/value\u0000The research technique, causal network elicitation technique, uses semi-structured interviews to create decision networks, which is a technique that has not been widely applied to CRE research. The research provides a granular view of what are important inhibitors or facilitators of dynamic alignment of CRE to business strategy.\u0000","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78275414","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}
Pub Date : 2021-05-07DOI: 10.1108/JERER-07-2020-0044
Gaetano Lisi
Purpose This paper aims to explain the main empirical facts of housing markets, notably the trade-off between housing price and time-on-the-market, the positive correlation between housing price and the number of contracts traded during a given period (i.e. the trading volume) and the existence of price dispersion. Design/methodology/approach This theoretical paper makes use of a search and matching model. Search and matching, indeed, are two fundamental characteristics of the trading process in the housing market, and, thus, the search-and-matching models have become the new economic approach to the analysis of real estate markets. Findings This paper shows that a slightly modified version of the baseline search and matching model à la Mortensen-Pissarides can explain the main empirical facts of housing markets. There are two key mechanisms that allow to achieve this notable goal: a simple formalisation of the (reasonable) assumption that buyers today are potential sellers tomorrow (and vice versa); and the direct relationship between market tightness and house price, derived by the standard matching model and underestimated by the related literature. Research limitations/implications The developed theoretical model only studies the equilibrium conditions. Indeed, it would be interesting to also study the disequilibrium in housing markets. Practical implications The explanation of the main empirical facts of housing markets is embodied in the same and relatively simple theoretical model. Originality/value In addition to the explanation of the main empirical facts of housing markets, the developed theoretical model can generate an upward sloping Beveridge curve in the housing market (the positive relation between home-seekers and vacant houses). Instead, according to a recent criticism in the related literature, a model à la Mortensen-Pissarides inherently generates a (empirically unrealistic) downward sloping Beveridge curve.
{"title":"The Mortensen-Pissarides model and the empirical facts of housing markets","authors":"Gaetano Lisi","doi":"10.1108/JERER-07-2020-0044","DOIUrl":"https://doi.org/10.1108/JERER-07-2020-0044","url":null,"abstract":"\u0000Purpose\u0000This paper aims to explain the main empirical facts of housing markets, notably the trade-off between housing price and time-on-the-market, the positive correlation between housing price and the number of contracts traded during a given period (i.e. the trading volume) and the existence of price dispersion.\u0000\u0000\u0000Design/methodology/approach\u0000This theoretical paper makes use of a search and matching model. Search and matching, indeed, are two fundamental characteristics of the trading process in the housing market, and, thus, the search-and-matching models have become the new economic approach to the analysis of real estate markets.\u0000\u0000\u0000Findings\u0000This paper shows that a slightly modified version of the baseline search and matching model à la Mortensen-Pissarides can explain the main empirical facts of housing markets. There are two key mechanisms that allow to achieve this notable goal: a simple formalisation of the (reasonable) assumption that buyers today are potential sellers tomorrow (and vice versa); and the direct relationship between market tightness and house price, derived by the standard matching model and underestimated by the related literature.\u0000\u0000\u0000Research limitations/implications\u0000The developed theoretical model only studies the equilibrium conditions. Indeed, it would be interesting to also study the disequilibrium in housing markets.\u0000\u0000\u0000Practical implications\u0000The explanation of the main empirical facts of housing markets is embodied in the same and relatively simple theoretical model.\u0000\u0000\u0000Originality/value\u0000In addition to the explanation of the main empirical facts of housing markets, the developed theoretical model can generate an upward sloping Beveridge curve in the housing market (the positive relation between home-seekers and vacant houses). Instead, according to a recent criticism in the related literature, a model à la Mortensen-Pissarides inherently generates a (empirically unrealistic) downward sloping Beveridge curve.\u0000","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89792109","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}
Pub Date : 2021-05-05DOI: 10.1108/JERER-04-2020-0025
G. Morri, U. Perini, Rachele Anconetani
Purpose The paper aims to investigate the performance determinants of European non-listed private equity real estate funds between 2001 and 2014. Design/methodology/approach Using a sample of 363 funds collected from the Inrev database, the analysis evaluated the impact of fees and other intrinsic characteristics of these funds, such as leverage, size and duration, on the funds’ performance, intending to enhance the understanding underlying their relationship. Findings The findings show a negative relationship between the return of the funds and redemption fee, performance fee and management fee. Conversely, marketing fees have a positive effect on performance. When analyzing the investment style, the results reveal inhomogeneous behaviors of leverage on funds’ performance. This variable has a positive impact on the return in core funds, while there is a negative relationship in value-added investments. Finally, the emphasis on the global financial crisis shows that the effects of the independent variables on the performance do not significantly change in different economic cycles. Practical implications The practical implication of the research is to understand whether an investor can direct its resources in a fund, leveraging on certain intrinsic characteristics that can be observed a priori. Originality/value Even if there is a considerable body of literature on determinants of performance in European non-listed real estate funds, little research has analyzed the role of fees in driving their results. Besides, this paper takes advantage of observations from different investment styles to emphasize the impact of higher or lower risk profiles and from the full economic cycle to understand the effects of the crisis period.
{"title":"Performance determinants of European private equity real estate funds","authors":"G. Morri, U. Perini, Rachele Anconetani","doi":"10.1108/JERER-04-2020-0025","DOIUrl":"https://doi.org/10.1108/JERER-04-2020-0025","url":null,"abstract":"\u0000Purpose\u0000The paper aims to investigate the performance determinants of European non-listed private equity real estate funds between 2001 and 2014.\u0000\u0000\u0000Design/methodology/approach\u0000Using a sample of 363 funds collected from the Inrev database, the analysis evaluated the impact of fees and other intrinsic characteristics of these funds, such as leverage, size and duration, on the funds’ performance, intending to enhance the understanding underlying their relationship.\u0000\u0000\u0000Findings\u0000The findings show a negative relationship between the return of the funds and redemption fee, performance fee and management fee. Conversely, marketing fees have a positive effect on performance. When analyzing the investment style, the results reveal inhomogeneous behaviors of leverage on funds’ performance. This variable has a positive impact on the return in core funds, while there is a negative relationship in value-added investments. Finally, the emphasis on the global financial crisis shows that the effects of the independent variables on the performance do not significantly change in different economic cycles.\u0000\u0000\u0000Practical implications\u0000The practical implication of the research is to understand whether an investor can direct its resources in a fund, leveraging on certain intrinsic characteristics that can be observed a priori.\u0000\u0000\u0000Originality/value\u0000Even if there is a considerable body of literature on determinants of performance in European non-listed real estate funds, little research has analyzed the role of fees in driving their results. Besides, this paper takes advantage of observations from different investment styles to emphasize the impact of higher or lower risk profiles and from the full economic cycle to understand the effects of the crisis period.\u0000","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88557408","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}
Pub Date : 2021-03-22DOI: 10.1108/JERER-01-2020-0003
S. Toivonen
Purpose The purpose of this paper is to study the user experiences of the futures wheel method to investigate its suitability to advance futures thinking in the real estate field. Design/methodology/approach The user experiences of the futures wheel method are investigated through questionnaire answers of 114 master’s level students and real estate experts taking part in future wheel workshops. Findings The futures wheel method could enhance future-oriented thinking and decision-making in the real estate field. The respondents see futures thinking as an important skill and recognize several advantages concerning the method. Practical implications The futures wheel method bears great potential to be used in the real estate sector and it could be a fruitful addition to the curriculums at different education levels in real estate studies. Social implications Futures thinking is essential when aiming for sustainable decisions in the real estate field which again would benefit the whole surrounding society. Originality/value This paper is the first published paper concentrating on the user experiences of the future wheel method in the real estate sector. The benefits and the disadvantages of the method are investigated but also the attitudes indicating the potential of the method to be successfully adopted in the field are analyzed.
{"title":"Advancing futures thinking in the real estate field","authors":"S. Toivonen","doi":"10.1108/JERER-01-2020-0003","DOIUrl":"https://doi.org/10.1108/JERER-01-2020-0003","url":null,"abstract":"\u0000Purpose\u0000The purpose of this paper is to study the user experiences of the futures wheel method to investigate its suitability to advance futures thinking in the real estate field.\u0000\u0000\u0000Design/methodology/approach\u0000The user experiences of the futures wheel method are investigated through questionnaire answers of 114 master’s level students and real estate experts taking part in future wheel workshops.\u0000\u0000\u0000Findings\u0000The futures wheel method could enhance future-oriented thinking and decision-making in the real estate field. The respondents see futures thinking as an important skill and recognize several advantages concerning the method.\u0000\u0000\u0000Practical implications\u0000The futures wheel method bears great potential to be used in the real estate sector and it could be a fruitful addition to the curriculums at different education levels in real estate studies.\u0000\u0000\u0000Social implications\u0000Futures thinking is essential when aiming for sustainable decisions in the real estate field which again would benefit the whole surrounding society.\u0000\u0000\u0000Originality/value\u0000This paper is the first published paper concentrating on the user experiences of the future wheel method in the real estate sector. The benefits and the disadvantages of the method are investigated but also the attitudes indicating the potential of the method to be successfully adopted in the field are analyzed.\u0000","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2021-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88709157","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}
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