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This study aims to know to what extent do the commercial and residential estate markets move together in different economies? Do the shocks originating in one of these markets spillover to the other markets?

The authors apply a modified version of the dynamic factor model to commercial and residential real estate prices in the Euro area, Hong Kong, Singapore and the USA. This modified dynamic factor model decomposes price growth in these two real estate markets into common, spillover and idiosyncratic components.

The results show significant heterogeneity in the relative importance of different components in the evolution of commercial and residential price growth across different economies. The findings suggest that the spillover from the residential to commercial real estate market dominates the spillover from the commercial to real estate market for all the economies in our sample. The authors also find that the common component accounts for a large fraction of the price movements in the residential markets in the European Union (EU) area and the USA, whereas spillover and common components together explain more than two-thirds of the variations in Hong Kong and Singapore. The results suggest that the role of spillover from one market to another increased significantly during the financial crisis of 2008–2009.

This paper contributes to the existing literature on how the transmission of shocks takes place across commercial and residential real estate markets. The transmission of shocks can take place in two directions in the proposed framework. There may be a direct spillover from a shock from one market to another. This corresponds to a shock to the idiosyncratic component affecting the other idiosyncratic component. In this paper, the authors are mainly interested in indirect spillover where the shock would transmit from the idiosyncratic factor to the common factor, and then from the common factor to the other idiosyncratic factor.

The home is a substantial investment for most individual investors but the assessment of risk and return of residential real estate has not been well explored yet. The existing real estate pricing literature using a CAPM-based model generally suggests very low risk and unexplained excess returns. However, many academics suggest the residential real estate market is unique and standard asset pricing models may not fully capture the risk associated with the housing market. The purpose of this paper is to extend the asset pricing literature on residential real estate by providing improved CAPM estimates of risk and required return.

The improvements include the use of a levered β which captures the leverage risk and Lin and Vandell (2007) Time on Market risk premium which captures the additional liquidity risk of residential real estate.

In addition to presenting palatable risk and return estimates for a national real estate index, the results of this paper suggest the risk and return characteristics of multiple cities tracked by the Case Shiller Home Price Index are distinct.

The results show higher estimates of risk and required return levels than previous research, which is more consistent with the academic expectation that housing performs between stocks and bonds. In contrast to most previous studies, the authors find residential real estate underperforms based on risk, using standard financial models.

This research aims to identify the statistically significant characteristics of a hedonic model to explain the pricing of residential properties in two cities in Pakistan.

The research methodology applies extreme bounds analysis and the least absolute shrinkage and selection operator. Estimators of efficient pricing were measured via stochastic frontier analysis.

The study findings show that the market valuation of residential properties in Islamabad and Rawalpindi is systematically related to numerous factors, including property location, neighborhood characteristics, environmental characteristics, structural characteristics and administrative qualities of local housing societies. The authors also find statistical evidence that suggests that residential estate properties in the two cities are overpriced in the sense that the market transaction prices tend to be higher than the fair prices of the properties in the two cities.

In Pakistan, the term “real estate” is used rather synonymously with the word “investment.” The findings of this research will help investors to identify the measurable factors that affect the transaction prices of residential real estate. These identifications will facilitate the development of strategic plans toward achieving sustainable rates of return in residential real estate markets.

The residential real estate sector in Pakistan is constantly changing. There are myriad causes for these changes, including changes in social structure, cultural attitudes and technology. Customary methods for forecasting market prices for residential properties have been rendered unreliable because of the dynamics of the market. This study will contribute to the understanding of the changing dynamics of residential real estate pricing.

Although Pakistan's residential real estate market is growing very rapidly, there is little published research identifying the drivers of this growth. This study covers these aspects to fill the theoretical gap in a real estate context.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

To investigate whether additional information of the permanent news flow, especially reporting intensity, can help to increase transparency in housing markets, this study aims to examine the relationship between news coverage or news sentiment and residential real estate prices in Germany at a regional level.

Using methods in the field of natural language processing, in particular word embeddings and dictionary-based sentiment analyses, the authors derive five different sentiment measures from almost 320,000 news articles of two professional German real estate news providers. These sentiment indicators are used as covariates in a first difference fixed effects regression to investigate the relationship between news coverage or news sentiment and residential real estate prices.

The empirical results suggest that the ascertained news-based indicators have a significant positive relationship with residential real estate prices. It appears that the combination of news coverage and news sentiment proves to be a reliable indicator. Furthermore, the extracted sentiment measures lead residential real estate prices up to two quarters. Finally, the explanatory power increases when regressing on prices for condominiums compared with houses, implying that the indicators may rather reflect investor sentiment.

To the best of the authors’ knowledge, this is the first paper to extract both the news coverage and news sentiment from real estate-related news for regional German housing markets. The approach presented in this study to quantify additional qualitative data from texts is replicable and can be applied to many further research areas on real estate topics.

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.

Based on a monthly data set between July 2011 and December 2019, this study adopts a cointegration analysis.

This study finds that household non-mortgage loans do play a significant role in driving residential real estate prices in China.

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.

Mauritius’s residential real estate sector has undergone an increase in foreign investment over the past decades. This study aims to establish if the increasing level of foreign real estate investments (FREI) has increased land demand and land prices. The study also aims to depict whether the relation between FREI and land prices prevails at an aggregate and/ or a regional level.

Data from 26 regions, classified as urban, rural and coastal is collected on an annual basis over the period 2000 to 2019, and a dynamic panel regression framework, namely, an autoregressive distributed lag model, is used to take into account the dynamic nature of land price modeling.

The findings show that, at the aggregate level, in the long-term, FREI does not have a significant influence on land prices, while in the short term, a positive significant relationship is noted between the two variables. A regional breakdown of the data into urban, rural and coastal was done. In the long term, only in coastal regions, a positive significant link was observed, whereas in urban and rural regions FREI did not influence land prices. In the short term, the positive link subsists in the coastal regions, and in rural regions also land prices are positively affected by FREI.

Unlike other studies which have used quite general measures of FREI, the present research has focused on FREI mainly undertaken in the residential real estate market and how these have affected residential land prices. This study also contributes to research on the determinants of land prices which is relatively scarce compared to research on housing prices.

This paper aims to examine the influence of Covid-19, current war and other factors on the dynamics of real estate prices in Ukraine from 2019Q2 to 2022Q4. More specifically, the authors examine the extent of the influence of Covid-19 and war on the real estate market in Ukraine.

The authors monitor and accumulate information flows from the existing real estate market with their subsequent in-depth math-stat processing to examine dynamics and drivers of Ukrainian real estate prices evolution.

The study finds that the Ukrainian residential property market has experienced an average growing trend from June 2019 to December 2022, despite the strong influence of pandemic and war. The analysis shows that the impact of these factors varies across different regions and property types, with some areas and property types being more affected than others. The study also identifies the main drivers of the market evolution, including cost-sensitive factors such as floor level, overall area, housing conditions and geographical location.

This research is oriented to analyze evolution of residential property market in Ukraine in 2019–2022 years characterized by influence of such disturbing factors as pandemic and military actions.

Results gained are essential for any type of Ukrainian residential market analytics implementation including but not limited to investment analysis, valuation services, collateral, insurance and taxation purposes, etc. In broader sense, it can be also useful for comparison with same type market development in other geographical arears.

Initial data base collected and constantly monitored covers all different regions of the country that gives a broad view on the overall market development influenced by pandemic and war.

The lack of a reliable database of the purchase and sale of residential properties remains one of the biggest obstacles in obtaining reliable data on their market value. This considerably complicates the process of carrying out a valuation and reduces the accuracy and reliability of the results of such work. This is especially important for market which evolves in times of unrest being influenced by such strongly disturbing factors as pandemic and military actions. The originality of the study lies in the development of a complete probabilistic processing of the initial database, which provides a reliable and accurate assessment of the market evolution. The results achieved could be used by various stakeholders, such as property owners, investors, valuers, insurers, regulators and other interested customers, to make informed decisions and mitigate risks in the turbulent Ukrainian real estate market.

The real estate industry is an e‐commerce anomaly. Although the overall growth of ecommerce is driven by the business‐to‐business sector, the majority of real estate e‐commerce is derived from its retail‐oriented residential sector. This study examines the structure of residential and commercial real estate websites, with the goal of determining whether some patterns of content might increase the quality and quantity of information available to buyers and sellers thereby contributing to the disparity between residential and commercial real estate e‐commerce growth. The results of the research show residential real estate websites offer richer informational content than commercial real estate websites. No significant differences are found for the user friendliness and functionality (ie ancillary services) provided by residential and commercial real estate websites.

Sustainability represents innovative elements in determining the profitability of real estate investments, among other factors, including the green component in real estate. Evidence from the literature has pointed out that incorporating green features into residential buildings can reduce operational costs and increase the building’s value. Although green real estate is considered the future trend of choice, it is still being determined whether prospective buyers are willing to accept the extra cost of green residential investment. Therefore, this study aims to investigate the effect of housing attributes and green certification on residential real estate prices.

The impact of the housing attribute and green certification in the residential sectors was assessed using a transaction data set comprising approximately 861 residential units sold in Selangor, Malaysia, between 2014 and 2022. Linear and quantile regression were used in this study by using SPSS software for a robust result.

The findings indicate that the market price of residential properties in Malaysia is influenced by housing attributes, transaction types and Green Building Index certification. The empirical evidence from this study suggests that green certification significantly affects the sales price of residential properties in Malaysia. The findings of this research will help investors identify measurable factors that affect the transaction prices of green-certified residential real estate. These identifications will facilitate the development of strategic plans aimed at achieving sustainable rates of return in the sustainable residential real estate market.

Specifically, this research will contribute to achieving area 4 of the 11th Malaysia Plan, which pertains to pursuing green growth for sustainability and resilience. This will be achieved by enhancing awareness among investors and homebuyers regarding the importance of green residential buildings in contributing to the environment, the economy and society.

The regression model for housing attributes and green certification on house price developed in this study could offer valuable benefits to support and advance Malaysia in realising its medium and long-term goals for green technology.