Search results

This paper aims to explore the drivers behind the accuracy of self-reported home valuations in the Warsaw (Poland) housing market.

In order to achieve the research goal, firstly, unique data on subjective residential property values estimated by their owners were compared with market-justified ones. The latter was calculated using geographically weighted regression, which allowed for taking into account spatially heterogeneous buyers' housing preferences. An ordered logit model was then used to identify the factors influencing the probability of the occurrence of bias towards over or undervaluation.

The results of the study revealed that, on average, homeowners overvalued their properties by only 1.94%, and the fraction of interviewees estimating their properties accurately ranges from 20% to 68%, depending on the size of the margin of error adopted. The drivers of the valuation bias variation were the physical, locational and neighbourhood attributes of the property as well as the personal characteristics of the respondents, for which their age and employment situation played a key role.

In contrast to previous studies, this is the first to examine drivers behind the accuracy of self-reported home valuations in a Central and Eastern Europe country. In addition, this work is the first to consider heterogeneous housing preferences when calculating objective property values.

This study aims to investigate the impact of international diversification on the value and operating efficiency of European real estate firms.

The study is conducted using a panel fixed effects regression model to estimate the relationship of international diversification with firm value and operating efficiency. International diversification is mainly measured via the negative of the Herfindahl–Hirschman Index (HHI) using property-level data. Firm value and operating efficiency are proxied by financial ratios observed annually from 2002 to 2021 at the firm level.

The results demonstrate that international diversification has a negative effect on firm value. Additionally, it lowers operating efficiency by weakening a firm's ability to generate operating earnings from its assets. By examining whether the reduction in operating efficiency is due to the rental income channel or the capital gains channel, the authors find strong statistical evidence that international diversification negatively impacts capital gains. International diversification is negatively associated with net gains from property valuations (unrealized capital gains) and net profits from property disposals (realized capital gains).

The empirical analysis is limited to Europe.

This paper extends the geographical diversification literature. While existing literature focuses on domestic diversification within the United States, this paper explores the effects of international diversification on European real estate firms. To the extent of the authors' knowledge, this is the first paper to examine the impact of geographical diversification on capital gains.

The purpose of this paper is to investigate the role of distinct types of heating technology and their price impact in German residential real estate markets, considering a wide range of other housing market determinants. The authors aim to test and to verify specifically, whether the obsolescence of heating technology leads to a significant price discount and whether higher technological standards (and environmental friendliness) come with a price premium on the market.

The authors create housing market models for rental and sales segments by constructing generalized additive models with explicit multi-layered spatial components. To elaborate a profound and contemporary answer using these models, the authors perform large-sample regression analyses based on more than 400,000 observations covering German residential properties in 2015.

First and foremost, the heating system indeed shows significant explanatory importance for measuring housing rents and purchasing price. Second, the authors find that it makes a difference whether clean “green” technologies are implemented or whether “brown” systems with obsolete technology or fossil energy sources is on hand. Ultimately, the authors conclude that while low energy consumption indeed comes with a price premium, this needs to be interpreted together with the property’s heating type, as housing markets seem to outweigh the “green premium” by “brown discounts” if low energy consumption figures are powered by a certain type of heating technology system.

Aside of a possible omitted variable bias, the main research limitation is constituted by the integration of asking prices in the analysis, as actual transaction prices are not systematically transparent on national level in Germany. Limitations are discussed at the end of the paper.

This work supports investors who face the challenge of making environmental- and energy-related decisions as well as appraisers who deliver financial fundamentals for such. Third, the paper supports both asset managers as well as investment strategists in argumentation pro-environmental investments beyond all ecological necessity.

This paper contributes to the current discussion on climate change and the eclectic role of real estate in this context. The authors deliver evidence on pricing effects as a measure of socioeconomic acceptance of progressive heating technology and environmental friendliness as an imperative of twenty-first century societies.

This is the first study on “green premiums” or “brown discounts” that includes heating technology as a potential and distinct driver of value and rents. It is a contemporary contribution and delivers original information on the quantitative impact of contemporary and anachronistic technology in heating to researchers as well as investors and appraisers.

The aim of this paper is to introduce a framework that helps to identify strategic themes on which real estate investors form their strategies. A holistic approach to strategic management in real estate management has enjoyed popularity in corporate real estate research, while similar research has been lacking from the investor-based real estate management.

The research design consists of two main parts: 1) formulating propositions based on existing literature and 2) attempting to validate the propositions through a qualitative interview study with major real estate owners in Finland.

The main finding is that the current real estate investors reflect the transient nature of competitive advantages and assess their strategies accordingly. The companies consider the traditional profitability and revenue growth aspects of their business but also a more long-term future growth dimension. As an outcome, the investors base their strategies on eight strategic themes which are “Innovation”, “ESG”, “Marketing and sales”, “Financial management”, “Leasing management and tenant satisfaction”, “Competitive environment and portfolio management”, “Outsourcing and strategic partnerships” and “Cost and operation optimization”.

This paper opens opportunities for future research concerning different strategies in real estate investment business and their impacts.

The presented framework provides support for real estate investors to create real estate management strategy or to evaluate their current strategy and to recognize operational actions and decisions that are relevant for their strategy.

This paper provides an extension to corporate real estate (CRE) literature by showing that the CRE theories are adaptable to real estate investment and provide value for their strategic management. This paper also contributes to real estate investment literature by providing a well-founded and empirically contested strategic management framework, the IREM framework, for identifying strategic themes on which real estate investors form their strategies.

Contrary to the traditional technology project perspective, real estate investors see building-specific renewable energy (on-site energy) investments as part of the property and as something affecting the property’s ability to produce a (net) cash flow. This paper aims to show the value-influencing mechanism of on-site energy production from a professional property investors’ perspective.

The value-influencing mechanism is presented with a case study of a prime logistics property located in the Helsinki metropolitan area, Finland. The case study results are compared with the results of a survey answered by over 70 property valuation professionals in the Finnish real estate market.

Current valuation practice supports the presented value-creation mechanism based on the capitalisation of the savings generated by a building’s own energy production. Valuation professionals see benefits beyond decreased operating expenses such as enhanced image and better saleability. However, valuers acted more conservatively than expected when transferring these additional benefits to the cash flows of the case property.

Because the savings in operating expenses can be capitalised into the property value, property investors should consider on-site energy production when the return of on-site energy exceeds the return of the property. This enhances the profitability of on-site energy, especially in urban areas with low initial yields.

This is the first research paper to open the value-influencing mechanism of on-site energy production from a professional property investors’ perspective in commercial properties and to confirm it from a market study.

The most commonly observed risk averse behavior in the commercial real estate market is loss aversion on the part of investors; i.e., investors are more sensitive to prospective losses than to prospective gains. This observation leads to the natural question : Does the market rationally anticipate investors' loss aversion? If not, then does loss aversion become stronger in a relatively illiquid market? The answer to these questions provides strategically important implications to institutional investors. We propose to explore the impact of loss aversion on the commercial real estate market by testing two competing hypotheses : (1) the rational market expectation hypothesis and (2) the liquidity spiral hypothesis. The rational market expectation hypothesis holds that the market rationally anticipates investors' behavioral loss aversion. As a result, the interaction between lagged market liquidity and loss aversion does not have an impact on the probability of property sales. On the other hand, the liquidity spiral hypothesis holds that the interaction between market liquidity and loss aversion has an impact on the probability of property sales due to the self-fulfilling feedback effect between loss aversion and market liquidity. In the context of REITs' property transactions, we find partial evidence for the liquidity spiral hypothesis : private market liquidity and stock market liquidity each has an additional impact on the sale probability of property.

The purpose of this study is to investigate how the degree of overpricing (DOP) and other variables are associated with the time on the market (TOM) and the final selling price (SP) for residential properties in the Paphos urban area.

The hedonic pricing model was used to examine the association of TOM and SP with various factors. The association of the independent variable of DOP and other independent variables with the two dependent variables of TOM and SP were investigated via ordinary least squares (OLS) regression models. In the first set of models the dependent variable was TOM and in the second set of models the dependent variable was SP. A sample of N = 538 completed transactions from Q1 2008 to Q2 2019 was used to estimate the optimum DOP that a seller must apply on the current market value of a property in order to achieve highest SP price in the shortest TOM.

The results of this study also suggest that the degree of overpricing in thin and less transparent markets is higher than that in transparent markets with high property transaction volumes. In mature markets like the USA and the UK where the actual sold prices are published, the DOP is around 1.5% which is much lower than the 11% DOP identified in this study.

It was found that buyers are willing to pay more for the same house in a bigger plot than a bigger house in the same plot. The outcome is that smaller houses sell faster at a higher price per square meter than larger houses. Smaller houses are more affordable than larger houses.

There is a large pool of buyers for smaller houses than bigger houses. Higher demand for smaller houses results in a higher price per square meter for smaller houses than the price per square meter for bigger houses. Respectively the TOM for smaller houses is shorter than the TOM for bigger houses.

The database used is unique, from an estate agent located in Paphos that managed to sell more than 27,000 properties in 20 years. This data set is the most accurate information for Cyprus' property transactions.

Real estate is a capital-intensive industry for which the asset values tend to be highly volatile and uncertain. Transaction costs in the industry are therefore high, and transparency for investors may be low. The need to signal reliable estimates of property assets, in the communication to external stakeholders, can therefore be expected to be of extra importance in this sector. The purpose of this paper is to investigate how real estate firms use big four auditors to signal quality.

The authors use Swedish firm level data containing all limited liability real estate companies in the country to determine the determinants of big four auditors. The data set consists of 34,306 observations and is analyzed through logit regressions.

The results show that big four companies are primarily contracted by large and mature companies, rather than new firms or firms with volatile financial records, although the latter could be expected to have a large need to signal quality. The authors also find that firms listed on the stock market and firms targeting public use real estate are more inclined to use big four companies.

Real estate is a capital-intensive industry for which the asset values tend to be highly volatile and uncertain. Transaction costs in the industry are therefore high, and transparency for investors may be low. The need to signal reliable estimates of property assets, in the communication to external stakeholders, can therefore be expected to be of extra importance in this sector. No prior study of this area has been detected.

The study aims to estimate the short- and long-run effects of monetary policy on residential property prices in South Africa. Over the past decades, there has been a monetary policy shift, from targeting money supply and exchange rate to inflation. The shifts have affected residential property market dynamics.

The Johansen cointegration approach was used to estimate the effects of changes in monetary policy proxies on residential property prices using quarterly data from 1980 to 2022.

Mortgage finance and economic growth have a significant positive long-run effect on residential property prices. The consumer price index, the inflation targeting framework, interest rates and exchange rates have a significant negative long-run effect on residential property prices. The Granger causality test has depicted that exchange rate significantly influences residential property prices in the short run, and interest rates, inflation targeting framework, gross domestic product, money supply consumer price index and exchange rate can quickly return to equilibrium when they are in disequilibrium.

There are limited arguments whether the inflation targeting monetary policy framework in South Africa has prevented residential property market boom and bust scenarios. The study has found that the implementation of inflation targeting framework has successfully reduced booms in residential property prices in South Africa.

The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and London-New York housing markets over a period of 1975Q1-2016Q1 by employing both static and dynamic methodologies.

The research analyzes long-run static and dynamic spillover elasticity coefficients by employing three methods, namely, autoregressive distributed lag, the fully modified ordinary least square and dynamic ordinary least squares estimator under a Kalman filter approach. The empirical method also investigates dynamic correlation between the house prices by employing the dynamic control correlation method.

The paper shows how a dynamic spillover pricing analysis can be applied between real estate markets. On the empirical side, the results show that country-level causality in housing prices is running from the USA to UK, whereas city-level causality is running from London to New York. The model outcomes suggest that real estate portfolios involving US and UK assets require a dynamic risk management approach.

One of the findings is that the dynamic conditional correlation between the US and the UK housing prices is broken during the crisis period. The paper does not discuss the reasons for that break, which requires further empirical tests by applying Markov switching regime shifts. The timing of the causality between the house prices is not empirically tested. It can be examined empirically by applying methods such as wavelets.

The authors observed a unidirectional causality from London to New York house prices, which is opposite to the aggregate country-level causality direction. This supports London’s specific power in the real estate markets. London has a leading role in the global urban economies residential housing markets and the behavior of its housing prices has a statistically significant causality impact on the house prices of New York City.

The house price co-integration observed in this research at both country and city levels should be interpreted as a continuity of real estate and financial integration in practice.

The paper is the first research which applies a dynamic spillover analysis to examine the causality between housing prices in real estate markets. It also provides a long-term empirical evidence for a dynamic causal relationship for the global housing markets.