Real estate development in the city of Athens during the financial crisis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maria Nikitidou ◽  
Fragiskos Archontakis ◽  
Athanasios Tagkalakis
Keyword(s):  
Financial Crisis ◽  
Real Estate ◽  
Structural Characteristics ◽  
House Prices ◽  
Real Estate Market ◽  
Structural Factors ◽  
Data Set ◽  
Content Type ◽  
Capital Financing ◽  
The City

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.

A post-global financial crisis (GFC) framework for strategic planning, assessment and management decision making for US sustainable commercial real estate

2017 ◽  
Vol 35 (6) ◽  
pp. 589-618 ◽  
Author(s):  
Pernille Hoy Christensen
Keyword(s):  
Decision Making ◽  
Financial Crisis ◽  
Real Estate ◽  
Performance Indicators ◽  
Institutional Investors ◽  
Global Financial Crisis ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Content Type ◽  
Sustainability Initiatives

Purpose The purpose of this paper is to understand both the facts and the values associated with the breadth of issues, and the principles related to sustainable real estate for institutional investors. Sustainable real estate is a growing sector within the commercial real estate industry, and yet, the decision-making practices of institutional investors related to sustainability are still not well understood. In an effort to fill that gap, this research investigates the post-global financial crisis (GFC) motivations driving the implementation of sustainability initiatives, the implementation strategies used, and the predominant eco-indicators and measures used by institutional investors. Design/methodology/approach This paper presents the results of a three-round modified Delphi study conducted in the USA in 2011-2012 investigating the nature of performance measurements and reporting requirements in sustainable commercial real estate and their impact on the real estate decision-making process used by institutional investors. Two rounds of in-depth interviews were conducted with 14 expert panelists. An e-questionnaire was used in the third round to verify qualitative findings. Findings The key industry drivers and performance indicators influencing institutional investor decision making were associated with risk management of assets and whether initiatives can improve competitive market advantage. Industry leaders advocate for simple key performance indicators, which is in contrast to the literature which argues for the need to adopt common criteria and metrics. Key barriers to the adoption of sustainability initiatives are discussed and a decision framework is presented. Practical implications This research aims to help industry partners understand the drivers motivating institutional investors to uptake sustainability initiatives with the aim of improving decision making, assessment, and management of sustainable commercial office buildings. Originality/value Building on the four generations of the sustainability framework presented by Simons et al. (2001), this research argues that the US real estate market has yet again adjusted its relationship with sustainability and revises their framework to include a new, post-GFC generation for decision making, assessment, and management of sustainable real estate.

Foreign investment in Australian residential properties

2019 ◽  
Vol 12 (2) ◽  
pp. 166-180 ◽  
Author(s):  
Hassan F. Gholipour ◽  
Hooi Hooi Lean ◽  
Reza Tajaddini ◽  
Anh Khoi Pham
Keyword(s):  
Real Estate ◽  
Foreign Investment ◽  
House Prices ◽  
Real Estate Market ◽  
Housing Development ◽  
Housing Construction ◽  
Annual Data ◽  
Content Type ◽  
Residential Properties ◽  
The Impact

Purpose The purpose of this study is to examine the impact that foreign investment in existing houses and new housing development has on residential house prices and the growth of the housing construction sector. Design/methodology/approach The analysis is based on a panel cointegration method, estimated using annual data for all Australian states and territories spanning the period of 1990-2013. Findings The results indicate that increases in foreign investment in existing houses do not significantly lead to increases in house prices. On the other hand, a 10 per cent increase in foreign investment for housing development decreases house prices by 1.95 per cent. We also find that foreign real estate investments have a positive impact on housing construction activities in the long run. Originality/value Existing studies used aggregate foreign real estate investment in their analyses. As foreign investment in existing houses and foreign investment for housing development have different impacts on the demand and supply sides of housing market, it is crucial that the analysis of the effects of foreign investment in residential properties on real estate market is conducted for each type differently.

Volatility causality and contagion in international securitized real estate markets

2018 ◽  
Vol 11 (2) ◽  
pp. 244-168 ◽  
Author(s):  
KimHiang Liow ◽  
Qing Ye
Keyword(s):  
Financial Crisis ◽  
Real Estate ◽  
Portfolio Management ◽  
Real Estate Market ◽  
Market Volatility ◽  
Content Type ◽  
Real Estate Markets ◽  
The Us ◽  
High Volatility ◽  
Empirical Investigations

Purpose This paper aims to investigate volatility causality and return contagion on nine international securitized real estate markets by appealing to Markov-switching (MS) regime approach, from July 1992 to June 2014. Design/methodology/approach An MS causality interaction model (Psaradakis et al., 2005), an MS vector auto-regression mode (Krolzig, 1997) and a multivariate return contagion model (Dungey et al., 2005) were used to implement the empirical investigations. Findings There exist regime shifts in the volatility causality pattern, with the volatility causality effects more pronounced during high volatility periods. During high volatility period, real estate markets’ causality interactions and inter-linkages contribute to strong spillover effect that leads to extreme volatility. However, there is relatively limited return contagion evidence in the securitized real estate markets examined. As such, the US financial crisis might probably be due to cross-market interdependence rather than contagion. Research limitations/implications Because international investors incorporate into their portfolio allocation not only the long-run price relationship but also the short-run market volatility connectedness and return correlation structure, the results of this MS causality and contagion study have provided valuable information on the evaluation of regime-dependent securitized real estate market risk, as well as useful guidance on asset allocation and portfolio management decisions for institutional investors. Practical implications Financial crisis is one of the key determinants of cross-market volatility interactions. Portfolio managers should be alerted of the observation that the US and the other developed securitized real estate markets are increasingly sharing “common market cycles” in recent years, thereby diminishing the diversification benefits. For policymakers, this research indicates that the volatilities of the US securitized real estate market could be helpful to predict those of other developed markets. It is also important for them to pay attention to those potential risk factors behind the amplified causality, contagion and volatility spillover at times of crisis. Finally, a wider implication for policymakers is to manage the transmission channels through which global stock market return and volatility shocks can affect the local economies and domestic financial markets, including securitized real estate markets. Originality/value Real estate investments have emerged to show low correlation with stocks and bonds and contributed to portfolio optimization. With real estate that can serve as a type of consumption commodity and an investment tool, the risk-return profile of real estate is different from that of the underlying stock markets. Therefore, the performance and investment dynamics and real estate-stock link are not theoretically expected to be similar, that requires separate empirical investigations. This paper aims to stand out from the many papers on the same or similar topics in the application of the three MS methodologies to regime-dependent real estate market integration.

Artificial intelligence algorithms to predict Italian real estate market prices

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Luca Rampini ◽  
Fulvio Re Cecconi
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Artificial Neural Network ◽  
Real Estate ◽  
House Prices ◽  
Housing Prices ◽  
Real Estate Market ◽  
Content Type ◽  
Two Cities ◽  
Artificial Neural

PurposeThe assessment of the Real Estate (RE) prices depends on multiple factors that traditional evaluation methods often struggle to fully understand. Housing prices, in particular, are the foundations for a better knowledge of the Built Environment and its characteristics. Recently, Machine Learning (ML) techniques, which are a subset of Artificial Intelligence, are gaining momentum in solving complex, non-linear problems like house price forecasting. Hence, this study deployed three popular ML techniques to predict dwelling prices in two cities in Italy.Design/methodology/approachAn extensive dataset about house prices is collected through API protocol in two cities in North Italy, namely Brescia and Varese. This data is used to train and test three most popular ML models, i.e. ElasticNet, XGBoost and Artificial Neural Network, in order to predict house prices with six different features.FindingsThe models' performance was evaluated using the Mean Absolute Error (MAE) score. The results showed that the artificial neural network performed better than the others in predicting house prices, with a MAE 5% lower than the second-best model (which was the XGBoost).Research limitations/implicationsAll the models had an accuracy drop in forecasting the most expensive cases, probably due to a lack of data.Practical implicationsThe accessibility and easiness of the proposed model will allow future users to predict house prices with different datasets. Alternatively, further research may implement a different model using neural networks, knowing that they work better for this kind of task.Originality/valueTo date, this is the first comparison of the three most popular ML models that are usually employed when predicting house prices.

scholarly journals International Real Estate Review

2007 ◽  
Vol 10 (2) ◽  
pp. 113-130
Author(s):  
Benoit Julien ◽  
◽  
Paul Lanoie ◽  
Keyword(s):  
Real Estate ◽  
Negative Impact ◽  
House Prices ◽  
Real Estate Market ◽  
Data Set ◽  
Long Run ◽  
Before And After ◽  
Short Run ◽  
Noise Barrier ◽  
The Impact

This paper provides the first study on the impact of noise barriers on the price of adjacent houses based on a repeat sale analysis (RSA). RSA allows us to empirically examine the differential between the prices of houses sold before and after an event that may have affected their value, and after other relevant variables such as the evolution of the real estate market and major renovations performed on the house are controlled. This paper focuses on the neighborhood of Laval, a suburb of Montreal, where a large noise barrier was built in 1990 along a highway. The data set contains transaction information on 134 houses that were sold at least twice from 1980–2000. The empirical result will show that the noise barrier induced a decrease of 6% in the house prices in our sample in the short run, while it had a stronger negative impact of 11% in the long run.

Investing in gold or REIT index in Turkey: evidence from global financial crisis, 2018 Turkish currency crisis and COVID-19 crisis

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Levent Sumer ◽  
Beliz Ozorhon
Keyword(s):  
Financial Crisis ◽  
Real Estate ◽  
Exchange Rates ◽  
Economic Crisis ◽  
Global Financial Crisis ◽  
Currency Crisis ◽  
Free Fall ◽  
Real Estate Market ◽  
Content Type

Purpose Under the current Coronavirus Disease 2019 (COVID-19) pandemic circumstances where the gold prices are increasing and the stocks are in free fall, this research aims to compare the returns of gold prices and Turkish real estate investment trust (T-REIT) index by covering the 2008 global financial crisis, 2018 Turkish currency crisis and 2020 COVID-19 pandemic-based economic crisis periods and examine the effects of the returns of gold and the T-REIT index on each other, a research area that has been limited in the literature. Design/methodology/approach For the empirical analysis, vector auto regression model was used, and Augmented Dickey–Fuller and Granger causality tests were also conducted. The average returns were compared with the coefficient of variation analysis. Findings The results of the study exhibited that except for the 2008 global financial crisis period, 2018 Turkish currency crisis and 2020 COVID-19 pandemic-based economic crisis, the T-REIT index performs better than gold prices, but it is a riskier instrument, and both investment instruments do not affect the returns of each other. The segmentation of both instruments recommends the fund managers including both tools for diversification of a portfolio. Research limitations/implications In Turkey, gold prices are valued based on the fluctuations of the global gold prices, as well as the Turkish Lira/US Dollar currency exchange rates. The effect of the exchange rates may be considered in future studies, and the study may be conducted based on the USD values of the T-REIT index and global gold prices. Further studies may also include the comparison between the T-REIT index returns and a set of commodities such as the Goldman Sachs Commodity Index. This study covered only the first five months of 2020 to analyze the COVID-19 pandemic-based economic crisis initial effects, and a successor study is also recommended by including more new data of the post-COVID-19 pandemic and comparing both results. Practical implications The results of the research are expected to contribute to the REIT literature and give insight to investors about their investment choices while including both investment tools in their portfolio, especially for the future conditions of the new COVID-19 pandemic-based economic crisis. Social implications The study may provide insight for individuals, especially those who are considering possible investment options in the Turkish real estate market in the post-COVID-19 pandemic crisis. Originality/value Gold and real estate have always been considered as important investment instruments. Gold is commonly accepted as a safe haven in the literature, and the REITs are considered as long-term investment instruments by many scholars. While gold prices increase in the windy periods, the returns of real estate investments have more cyclical movements based on mostly the macroeconomic conditions and its integration with stock markets, yet the real estate is a common long-term investment tool, especially because of the regular income it generates for the retirement years. By covering three crisis periods including the COVID-19 pandemic-based economic crisis effects, making research about two important investment tools would contribute to the literature, especially in which the studies in this area were very limited.

Energy performance certificates in the Turin real estate market

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

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

Non-mortgage loans in the Chinese residential real estate market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kerry Liu
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Cointegration Analysis ◽  
Residential Real Estate ◽  
Mortgage Loans ◽  
Data Set ◽  
Monthly Data ◽  
Content Type ◽  
Real Estate Prices

Purpose From January 2021, the potential flow of Chinese household non-mortgage loans, including business loans and short-term consumption loans to the residential real estate market, has attracted the attention of the regulatory authorities. This study aims to examine the effects of household non-mortgage loans on the Chinese residential real estate market. Design/methodology/approach Based on a monthly data set between July 2011 and December 2019, this study adopts a cointegration analysis. Findings This study finds that household non-mortgage loans do play a significant role in driving residential real estate prices in China. Originality/value While many studies have examined the Chinese real estate market and its linkage with the financial system and the economy, this study is the first of its kind in the academic literature that exclusively focusses on the role of non-mortgage loans in real estate prices, and makes an original contribution.

Financial distress determinants among SMEs: empirical evidence from Sweden

2020 ◽  
Vol 47 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman
Keyword(s):  
Financial Crisis ◽  
Financial Distress ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Binary Logistic Regression ◽  
Data Availability ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
The Global Financial Crisis

PurposeThe purpose of this study is to empirically investigate determinants of financial distress among small and medium-sized enterprises (SMEs) during the global financial crisis and post-crisis periods.Design/methodology/approachSeveral statistical methods, including multiple binary logistic regression, were used to analyse a longitudinal cross-sectional panel data set of 3,865 Swedish SMEs operating in five industries over the 2008–2015 period.FindingsThe results suggest that financial distress is influenced by macroeconomic conditions (i.e. the global financial crisis) and, in particular, by various firm-specific characteristics (i.e. performance, financial leverage and financial distress in previous year). However, firm size and industry affiliation have no significant relationship with financial distress.Research limitationsDue to data availability, this study is limited to a sample of Swedish SMEs in five industries covering eight years. Further research could examine the generalizability of these findings by investigating other firms operating in other industries and other countries.Originality/valueThis study is the first to examine determinants of financial distress among SMEs operating in Sweden using data from a large-scale longitudinal cross-sectional database.

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