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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.

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.

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.

There is a general consensus that residential submarkets exist, but the basis upon which these are specified remains the subject of debate. The purpose of this paper is to model data on different residential locations in Ghana to show how the submarkets have performed over the past 16 years.

The paper employs hedonic modelling based on 3,250 sale transactions and 1,130 rental transactions from 1992 to 2007.

The results demonstrate that five residential real estate characteristics – location, detached, landscaping quality, gross internal areas and plot size – predominate in the explanation of both rental and transactions prices across all submarkets. They also highlight points of variation between the submarkets. An understanding of the impact of these features on residential price and rent is important for capital and rental valuation.

This paper analyses historic performance of the residential market, both at the aggregate and disaggregate level to place the housing market in an investment context.

The purpose of this paper is to evaluate the impact of macroeconomic condition and real estate price trend on the amount of residential loan.

The paper using a sample of 16 European Countries for the time period 2007–2015 evaluates the impact of change in the gross domestic product (GDP) growth and the inflation rate on the amount of residential loans. The analysis is performed by using a vector autoregressive (VAR) and generalized VAR approach for the full sample and for each country considered.

For a short-term horizon, shocks to mortgages, the house price index (HPI) and the GDP have a positive effect on the GDP, a shock to the amount of mortgages has a positive effect on the mortgage supply and a shock to the GDP has a negative effect on HPI. The main results for the long-term horizon are that a GDP shock has a positive and persistent effect on the amount of mortgages, a shock to HPI has a negative and persistent effect on mortgages and a shock to the amount of mortgages seems to have no persistent effect on the GDP or the HPI. Moreover, the analysis shows that a spillover risk among countries exists and a GDP shock in a European area has an effect on the GDP, real estate prices and residential mortgages in almost all European countries.

Results obtained show that both macroeconomic and housing prices shocks matter for the real estate lending and the effect are different in the short- and in the medium–long-term horizon. Results are also different country by country and they are affected by the level of financial development of the country.

The paper studies a lending crisis period and evaluates for the European market the impact of shock on macro-variables for mortgages focusing the attention for the first time only on residential mortgages.

This research aims to focus on the emerging determinants for the Australian residential property market subsequent to the Global Financial Crisis 2008.

Quantitative models built on secondary data were tested on three residential property markets comprising metropolitan Melbourne and two key suburbs in the state of Victoria. The relationship between the house price performances and various leading Australian economic indicators was assessed.

As a result of the increasing relevance of Asia Pacific private wealth in the Australian residential property market, non-traditional determinants such as residential tourism have emerged as significant in the Melbourne residential property market.

The result of this study can provide a better understanding on the relationship between the Australian residential property market and both the existing and emerging leading economic indicators.

A better understanding of foreign investment activities will assist policymakers to effectively manage inflated Australian residential property market without compromising the steady flow of foreign real estate investment.