Pub Date : 2021-08-10DOI: 10.1108/jerer-03-2020-0020
Sviatlana Engerstam
PurposeThis study examines the long term effects of macroeconomic fundamentals on apartment price dynamics in major metropolitan areas in Sweden and Germany.Design/methodology/approachThe main approach is panel cointegration analysis that allows to overcome certain data restrictions such as spatial heterogeneity, cross-sectional dependence, and non-stationary, but cointegrated data. The Swedish dataset includes three cities over a period of 23 years, while the German dataset includes seven cities for 29 years. Analysis of apartment price dynamics include population, disposable income, mortgage interest rate, and apartment stock as underlying macroeconomic variables in the model.FindingsThe empirical results indicate that apartment prices react more strongly on changes in fundamental factors in major Swedish cities than in German ones despite quite similar development of these macroeconomic variables in the long run in both countries. On one hand, overreactions in apartment price dynamics might be considered as the evidence of the price bubble building in Sweden. On the other hand, these two countries differ in institutional arrangements of the housing markets, and these differences might contribute to the size of apartment price elasticities from changes in fundamentals. These arrangements include various banking sector policies, such as mortgage financing and valuation approaches, as well as different government regulations of the housing market as, for example, rent control.Originality/valueIn distinction to the previous studies carried out on Swedish and German data for single-family houses, this study focuses on the apartment segment of the market and examines apartment price elasticities from a long term perspective. In addition, the results from this study highlight the differences between the two countries at the city level in an integrated long run equilibrium framework.
{"title":"Long run apartment price dynamics in Swedish and German cities","authors":"Sviatlana Engerstam","doi":"10.1108/jerer-03-2020-0020","DOIUrl":"https://doi.org/10.1108/jerer-03-2020-0020","url":null,"abstract":"PurposeThis study examines the long term effects of macroeconomic fundamentals on apartment price dynamics in major metropolitan areas in Sweden and Germany.Design/methodology/approachThe main approach is panel cointegration analysis that allows to overcome certain data restrictions such as spatial heterogeneity, cross-sectional dependence, and non-stationary, but cointegrated data. The Swedish dataset includes three cities over a period of 23 years, while the German dataset includes seven cities for 29 years. Analysis of apartment price dynamics include population, disposable income, mortgage interest rate, and apartment stock as underlying macroeconomic variables in the model.FindingsThe empirical results indicate that apartment prices react more strongly on changes in fundamental factors in major Swedish cities than in German ones despite quite similar development of these macroeconomic variables in the long run in both countries. On one hand, overreactions in apartment price dynamics might be considered as the evidence of the price bubble building in Sweden. On the other hand, these two countries differ in institutional arrangements of the housing markets, and these differences might contribute to the size of apartment price elasticities from changes in fundamentals. These arrangements include various banking sector policies, such as mortgage financing and valuation approaches, as well as different government regulations of the housing market as, for example, rent control.Originality/valueIn distinction to the previous studies carried out on Swedish and German data for single-family houses, this study focuses on the apartment segment of the market and examines apartment price elasticities from a long term perspective. In addition, the results from this study highlight the differences between the two countries at the city level in an integrated long run equilibrium framework.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":"2007 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82579470","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 : 2021-07-12DOI: 10.1108/JERER-07-2020-0046
F. Eren, J. Henneberry
PurposeThe continuation of globalisation and liberalisation processes has prompted the restructuring of many national and local property markets. The research examines the evolution of Istanbul's retail property market to identify how global and local agents engage with one another to produce a unique “glocalized” outcome.Design/methodology/approachThe morphogenetic approach is adapted and applied to analyse the dynamics of market change. The focus is on the character and behaviour of national and international market actors and how they interact with the wider political economy. The research uses a combination of elite interviews, document analysis and corporate case studies to obtain empirical evidence.FindingsThe liberalisation of the Turkish economy heralded the entry of the first international companies into Istanbul's retail property market in the 1990s. International involvement expanded rapidly after 2004, accelerating the process of market re-structuring. However, while the number of global buy-outs increased, the expansion of local property companies–and the establishment of some international/national corporate partnerships–was even more marked. This resulted in a “glocalised” market with a strong and distinctive local culture.Originality/valueIstanbul has been a major centre of trade for millenia. This is the first substantive analysis of the recent restructuring of the city's retail property market. Previous research on market maturity and market evolution has paid limited attention to the dynamics of change. The paper describes the use of a process-based theoretical framework (morphogenesis) that was explicitly designed to analyse structural shifts in socio-economic conditions through an examination of the characteristics and behaviours of the actors involved.
{"title":"The “glocalisation” of Istanbul's retail property market","authors":"F. Eren, J. Henneberry","doi":"10.1108/JERER-07-2020-0046","DOIUrl":"https://doi.org/10.1108/JERER-07-2020-0046","url":null,"abstract":"PurposeThe continuation of globalisation and liberalisation processes has prompted the restructuring of many national and local property markets. The research examines the evolution of Istanbul's retail property market to identify how global and local agents engage with one another to produce a unique “glocalized” outcome.Design/methodology/approachThe morphogenetic approach is adapted and applied to analyse the dynamics of market change. The focus is on the character and behaviour of national and international market actors and how they interact with the wider political economy. The research uses a combination of elite interviews, document analysis and corporate case studies to obtain empirical evidence.FindingsThe liberalisation of the Turkish economy heralded the entry of the first international companies into Istanbul's retail property market in the 1990s. International involvement expanded rapidly after 2004, accelerating the process of market re-structuring. However, while the number of global buy-outs increased, the expansion of local property companies–and the establishment of some international/national corporate partnerships–was even more marked. This resulted in a “glocalised” market with a strong and distinctive local culture.Originality/valueIstanbul has been a major centre of trade for millenia. This is the first substantive analysis of the recent restructuring of the city's retail property market. Previous research on market maturity and market evolution has paid limited attention to the dynamics of change. The paper describes the use of a process-based theoretical framework (morphogenesis) that was explicitly designed to analyse structural shifts in socio-economic conditions through an examination of the characteristics and behaviours of the actors involved.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":"16 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83822818","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 : 2021-07-06DOI: 10.1108/JERER-03-2021-0015
Mats Wilhelmsson, V. Ceccato
PurposeThis study aims to analyse the effect of gun-related violence on housing values, controlling for the area's crime levels and locational factors. Previous studies that aimed to find a causal connection between crime and housing values used instrument variables to solve the endogeneity problem. Here, the authors have instead been able to take advantage of the fact that shootings have occurred in random time and space. This has made it possible to estimate models to create windows around the shooting (event) and to estimate the causal effects of the shootings. Thus, the authors aim to contribute to the regression discontinuity design method in this context to estimate the short-term effects.Design/methodology/approachUsing the regression discontinuity design method, the authors can estimate the short-term effects of shootings.FindingsFindings from the analysis indicate that shootings directly affect those who are impacted by shootings and indirectly affect the environments where shootings occur. The indirect effect of shootings is momentary as it is capitalised directly in housing values in the immediate area. The effect also appears to be relatively long-term and persistent as housing values have not returned to the price level before the shooting 100–200 days after the shooting. The capitalisation effect is higher the closer one gets to the central parts of the city. On the other hand, the capitalisation effect is not higher or lower in areas with a higher crime rate per capita.Originality/valueThe article contributes to the previous literature in several ways. First and foremost, it provides an explicit analysis of shootings in built-up areas and their hypothesised effect on property prices through the impact on attractiveness and perceived safety. As far as the authors know, no study has analysed this issue on the international level or in Sweden. In this way, the authors aim to develop a study that can provide critical knowledge about one of the adverse effects of shootings. The authors also contribute to the literature by utilising unique data material, which allows the authors to merge information from the police about the exact location of shootings in the Stockholm area with data on sales of apartments in the same residential areas. In addition to the exact location of the shootings (coordinates), the authors also have access to data about whether the shootings led to injuries or deaths. Thus, the authors have separated the effect of shootings and fatal shootings, which has not been done before. Finally, the authors set out to highlight the results as a contribution to the debate on shootings.
{"title":"What effect does gun-related violence have on the attractiveness of a residential area? The case of Stockholm, Sweden","authors":"Mats Wilhelmsson, V. Ceccato","doi":"10.1108/JERER-03-2021-0015","DOIUrl":"https://doi.org/10.1108/JERER-03-2021-0015","url":null,"abstract":"PurposeThis study aims to analyse the effect of gun-related violence on housing values, controlling for the area's crime levels and locational factors. Previous studies that aimed to find a causal connection between crime and housing values used instrument variables to solve the endogeneity problem. Here, the authors have instead been able to take advantage of the fact that shootings have occurred in random time and space. This has made it possible to estimate models to create windows around the shooting (event) and to estimate the causal effects of the shootings. Thus, the authors aim to contribute to the regression discontinuity design method in this context to estimate the short-term effects.Design/methodology/approachUsing the regression discontinuity design method, the authors can estimate the short-term effects of shootings.FindingsFindings from the analysis indicate that shootings directly affect those who are impacted by shootings and indirectly affect the environments where shootings occur. The indirect effect of shootings is momentary as it is capitalised directly in housing values in the immediate area. The effect also appears to be relatively long-term and persistent as housing values have not returned to the price level before the shooting 100–200 days after the shooting. The capitalisation effect is higher the closer one gets to the central parts of the city. On the other hand, the capitalisation effect is not higher or lower in areas with a higher crime rate per capita.Originality/valueThe article contributes to the previous literature in several ways. First and foremost, it provides an explicit analysis of shootings in built-up areas and their hypothesised effect on property prices through the impact on attractiveness and perceived safety. As far as the authors know, no study has analysed this issue on the international level or in Sweden. In this way, the authors aim to develop a study that can provide critical knowledge about one of the adverse effects of shootings. The authors also contribute to the literature by utilising unique data material, which allows the authors to merge information from the police about the exact location of shootings in the Stockholm area with data on sales of apartments in the same residential areas. In addition to the exact location of the shootings (coordinates), the authors also have access to data about whether the shootings led to injuries or deaths. Thus, the authors have separated the effect of shootings and fatal shootings, which has not been done before. Finally, the authors set out to highlight the results as a contribution to the debate on shootings.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":"29 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78767665","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 : 2021-07-06DOI: 10.1108/jerer-01-2021-0007
E. Trevillion
PurposeThe purpose of this paper is to outline the benefits of using system dynamics modelling as a research tool to understand the dynamics of commercial property markets in the UK and their long-term behaviour. It highlights areas for future work.Design/methodology/approachThis is a concept paper that outlines a simple systems model of rental change in UK commercial property markets as a way of illustrating how a systems approach can be used to describe and model the market. The model concentrates on the user market and offers a view of market operation, according to which development activity is initiated by demand (linked to economic growth) and to which supply responds by producing development.FindingsThe model demonstrates how a systems approach can be used to model the impact of a wide range of market variables on rental growth. The approach allows non-linear modelling of the complex relationships and behavioural factors that are difficult to include in existing econometric models of the market. It highlights where existing knowledge is deficient, especially with regard to price elasticity of demand, the relationship between economic activity and take up, the potential impact of redevelopment on the supply of new property and rental growth and response times of various parts of the market development process to market signals. It outlines where further research is needed to incorporate real market data.Originality/valueDespite the wide application of the systems theory to business and other related areas, its use in commercial property research has been limited and has not gained much traction as a research tool. The work represents one of a very few studies applying the systems theory to the UK commercial property market.
{"title":"Using system dynamics modelling to understand behaviour in UK commercial property markets","authors":"E. Trevillion","doi":"10.1108/jerer-01-2021-0007","DOIUrl":"https://doi.org/10.1108/jerer-01-2021-0007","url":null,"abstract":"PurposeThe purpose of this paper is to outline the benefits of using system dynamics modelling as a research tool to understand the dynamics of commercial property markets in the UK and their long-term behaviour. It highlights areas for future work.Design/methodology/approachThis is a concept paper that outlines a simple systems model of rental change in UK commercial property markets as a way of illustrating how a systems approach can be used to describe and model the market. The model concentrates on the user market and offers a view of market operation, according to which development activity is initiated by demand (linked to economic growth) and to which supply responds by producing development.FindingsThe model demonstrates how a systems approach can be used to model the impact of a wide range of market variables on rental growth. The approach allows non-linear modelling of the complex relationships and behavioural factors that are difficult to include in existing econometric models of the market. It highlights where existing knowledge is deficient, especially with regard to price elasticity of demand, the relationship between economic activity and take up, the potential impact of redevelopment on the supply of new property and rental growth and response times of various parts of the market development process to market signals. It outlines where further research is needed to incorporate real market data.Originality/valueDespite the wide application of the systems theory to business and other related areas, its use in commercial property research has been limited and has not gained much traction as a research tool. The work represents one of a very few studies applying the systems theory to the UK commercial property market.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":"348 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79709388","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 : 2021-07-01DOI: 10.1108/JERER-12-2020-0059
Franziska Ploessl, Tobias Just, Lino Wehrheim
PurposeThe purpose of this paper is to identify and analyse the news coverage and sentiment of real estate-related trends in Germany. Trends are considered as being stable and long-term. If the news coverage and sentiment of trends underlie cyclicity, this could impact investors’ behaviour. For instance, in the case of increased reporting on sustainability issues, investors may be inclined to invest more in sustainable buildings, assuming that this is of growing importance to their clients. Hence, investors could expect higher returns when a trend topic goes viral.Design/methodology/approachWith the help of topic modelling, incorporating seed words partially generated via word embeddings, almost 170,000 newspaper articles published between 1999 and 2019 by a major German real estate news provider are analysed and assigned to real estate-related trends. Through applying a dictionary-based approach, this dataset is then analysed based on whether the tone of the news coverage of a specific trend is subject to change.FindingsThe articles concerning urbanisation and globalisation account for the largest shares of reporting. However, the shares are subject to change over time, both in terms of news coverage and sentiment. In particular, the topic of sustainability illustrates a clearly increasing trend with cyclical movements throughout the examined period. Overall, the digitalisation trend has a highly positive connotation within the analysed articles, while regulation displays the most negative sentiment.Originality/valueTo the best of the authors’ knowledge, this is the first application to explore German real estate newspaper articles regarding the methodologies of word representation and seeded topic modelling. The integration of topic modelling into real estate analysis provides a means through which to extract information in a standardised and replicable way. The methodology can be applied to several further fields like analysing market reports, company statements or social media comments on real estate topics. Finally, this is also the first study to measure the cyclicity of real estate-related trends by means of textual analysis.
{"title":"Cyclicity of real estate-related trends: topic modelling and sentiment analysis on German real estate news","authors":"Franziska Ploessl, Tobias Just, Lino Wehrheim","doi":"10.1108/JERER-12-2020-0059","DOIUrl":"https://doi.org/10.1108/JERER-12-2020-0059","url":null,"abstract":"PurposeThe purpose of this paper is to identify and analyse the news coverage and sentiment of real estate-related trends in Germany. Trends are considered as being stable and long-term. If the news coverage and sentiment of trends underlie cyclicity, this could impact investors’ behaviour. For instance, in the case of increased reporting on sustainability issues, investors may be inclined to invest more in sustainable buildings, assuming that this is of growing importance to their clients. Hence, investors could expect higher returns when a trend topic goes viral.Design/methodology/approachWith the help of topic modelling, incorporating seed words partially generated via word embeddings, almost 170,000 newspaper articles published between 1999 and 2019 by a major German real estate news provider are analysed and assigned to real estate-related trends. Through applying a dictionary-based approach, this dataset is then analysed based on whether the tone of the news coverage of a specific trend is subject to change.FindingsThe articles concerning urbanisation and globalisation account for the largest shares of reporting. However, the shares are subject to change over time, both in terms of news coverage and sentiment. In particular, the topic of sustainability illustrates a clearly increasing trend with cyclical movements throughout the examined period. Overall, the digitalisation trend has a highly positive connotation within the analysed articles, while regulation displays the most negative sentiment.Originality/valueTo the best of the authors’ knowledge, this is the first application to explore German real estate newspaper articles regarding the methodologies of word representation and seeded topic modelling. The integration of topic modelling into real estate analysis provides a means through which to extract information in a standardised and replicable way. The methodology can be applied to several further fields like analysing market reports, company statements or social media comments on real estate topics. Finally, this is also the first study to measure the cyclicity of real estate-related trends by means of textual analysis.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79890731","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 : 2021-06-29DOI: 10.1108/jerer-01-2021-0004
E. Çelik, K. Arslanli
PurposeThis paper aims to determine the specific financial ratio's effects on market value and return of assets for Turkish real estate investment trusts (REITs) traded at Istanbul Stock Exchange (ISE). The paper intends to define liquidity ratios, financial structure ratios, return ratios and stock performance ratios related to market value and return of asset.Design/methodology/approachThe study includes 17 REITs traded in ISE. The period of study is specified as the year from 2009 to 2018. Panel data analysis is applied in this study. Dependent variables are current market value and return of assets, independent variables are 12 financial ratios, which are considered to explain the model significantly. These ratios will be calculated from audited year-end balance sheets for specific periods throughout at least ten years as time series. Two different models and hypotheses have been established to identify the financial ratios that affect the market value and return of assets for REITs.FindingsAccording to the results, long-term financial loans/total assets, return of equity and working capital ratio are negatively correlated with market value, while market value/book value and total assets are correlated positively. On the other hand, market value/book value ratio, price/earning ratio, long-term financial loans/total assets and earnings per share are correlated with return of assets. REITs have high levels of financial leverage, especially in foreign currency. The striking point is that REITs hardly ever do not use financial derivatives to hedge their position again currency and interest rate risk. This approach makes the financial structures of REITs vulnerable and fragile against market volatility.Originality/valueIn Turkey, as an example of an emerging market, financial borrowing does not increase the return rates and market value for REITs due to market's idiosyncratic properties. This finding provides substantial insight into how the debt and equity allocation of Turkish REITs should be structured. Also, it has been observed that forward-looking expectations are considered more than the current situation in the market.
{"title":"The idiosyncratic characteristics of Turkish REITs: evidence from financial ratios","authors":"E. Çelik, K. Arslanli","doi":"10.1108/jerer-01-2021-0004","DOIUrl":"https://doi.org/10.1108/jerer-01-2021-0004","url":null,"abstract":"PurposeThis paper aims to determine the specific financial ratio's effects on market value and return of assets for Turkish real estate investment trusts (REITs) traded at Istanbul Stock Exchange (ISE). The paper intends to define liquidity ratios, financial structure ratios, return ratios and stock performance ratios related to market value and return of asset.Design/methodology/approachThe study includes 17 REITs traded in ISE. The period of study is specified as the year from 2009 to 2018. Panel data analysis is applied in this study. Dependent variables are current market value and return of assets, independent variables are 12 financial ratios, which are considered to explain the model significantly. These ratios will be calculated from audited year-end balance sheets for specific periods throughout at least ten years as time series. Two different models and hypotheses have been established to identify the financial ratios that affect the market value and return of assets for REITs.FindingsAccording to the results, long-term financial loans/total assets, return of equity and working capital ratio are negatively correlated with market value, while market value/book value and total assets are correlated positively. On the other hand, market value/book value ratio, price/earning ratio, long-term financial loans/total assets and earnings per share are correlated with return of assets. REITs have high levels of financial leverage, especially in foreign currency. The striking point is that REITs hardly ever do not use financial derivatives to hedge their position again currency and interest rate risk. This approach makes the financial structures of REITs vulnerable and fragile against market volatility.Originality/valueIn Turkey, as an example of an emerging market, financial borrowing does not increase the return rates and market value for REITs due to market's idiosyncratic properties. This finding provides substantial insight into how the debt and equity allocation of Turkish REITs should be structured. Also, it has been observed that forward-looking expectations are considered more than the current situation in the market.","PeriodicalId":44570,"journal":{"name":"Journal of European Real Estate Research","volume":"47 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89182920","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 : 2021-06-24DOI: 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":"29 1","pages":""},"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":"459 1","pages":""},"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.
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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":"67 1","pages":""},"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}
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