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To explore the state of this conditional Granger causality when other cities are not factors, we investigate housing market networks in China's major cities by using a combination of conditional Granger causality and network analysis.

Although housing market networks have been well discussed for different countries, the question of housing market networks in China's major cities based on the conditional causality perspective has yet to be answered.

We discover that second-tier cities are more influential than first-tier cities. Although the connectivity of the primary housing market is more complex than the diversified connectivity observed in the secondary housing market, both markets are scale-free networks that exhibit high stability. Moreover, we reveal that geographic conditions and economic development jointly determine the housing market's modular hierarchical structure. Our results provide meaningful information for both Chinese policymakers and investors.

By excluding the influence of other cities, our conditional Granger causality identifies the true casual relation between cities' housing markets. Moreover, it is the first paper to consider the primary housing market and secondary housing market separately. Specifically, Chinese prefer new house rather than second-hand house from both speculative and self-housing. Generally speaking, the new house price is lower than the second-hand house price since the new house is off-plan property. Therefore, understanding the difference between primary and secondary housing markets will provide useful information for both policymakers and speculators.

The purpose of this paper is to investigate the response of transaction volume in Hong Kong’s housing market to public land auctions.

An event study approach with the use of regression analyses was adopted for the empirical study.

Fewer pre-event transactions in the secondary housing spot market come with greater dispersion in the pre-event forecasts of land auction outcomes. Unexpected auction outcomes were also found to minify the post-event transaction volume in the secondary housing spot market, with negative unexpected outcomes exerting a stronger downward force.

These findings are contrary to the empirical evidence commonly found in most financial literature on stock transaction volume around corporate earnings announcements with an assumption of negligible transaction costs. Imperfect market structure, differences in sellers’ and buyers’ characteristics and short-sale restriction may explain the disparity.

Price in the secondary housing market is more sensitive to negative unexpected land auction outcomes. The analysis results of the current study attest that the impact exerted by the negative unexpected auction outcomes on transaction volume in the housing spot market is stronger than that of positive unexpected auction outcomes.

Unlike price and return, transaction volume has not received substantial academic attention in property research. In particular, within the existing small body of transaction volume research, the impact of information events on trading activities has been largely ignored.

The aim of this paper is to present estimation results of hedonic price models as well as housing price indices for the Warsaw secondary market.

Three direct methods of constructing a hedonic price index and four indices that allow for quality adjustment are presented. The paper also discusses theoretical issues related to the estimation and interpretation of hedonic models.

It is shown that the imputation and the time dummy variable indices are subject to less variation than the characteristic price index. It is also shown that in comparison to the mean and the median, hedonic indices are less variable, which can be interpreted as partial control for quality changes in dwellings sold.

As this research project represents one of the first attempts of hedonic modelling applied to the Polish housing market, its results may be employed by appraisers to gain insight into behaviour of the Warsaw housing market. Practical implications focus on reliable measurement of house price dynamics in Poland. This paper supplies an appropriate methodology for addressing this question and offers empirical solutions.

Employment of hedonic models for construction of quality‐adjusted housing price indices has not yet been explored in Poland. The theoretical and practical aspects of hedonic indices presented in the paper open promising directions for the development of Polish statistics of real estate prices.

The purpose of this paper is to provide a dating system for the Italian residential real estate market from 1927 to 2019 and investigate its interaction with credit and business cycles.

To detect the local turning point of the Italian residential real estate market, the authors apply the honeycomb cycle developed by Janssen et al. (1994) based on the joint analysis of house prices and the number of transactions. To this end, the authors use a unique historical reconstruction of house price levels by Baffigi and Piselli (2019) in addition to data on transactions.

This study confirms the validity of the honeycomb model for the last four decades of the Italian housing market. In addition, the results show that the severe downsizing of the housing market is largely associated with business and credit contraction, certainly contributing to exacerbating the severity of the recession. Finally, preliminary evidence suggests that whenever a price bubble occurs, it is coincident with the start of phase 2 of the honeycomb cycle.

To the best of the authors’ knowledge, this is the first time that the honeycomb approach has been tested over such a long historical period and compared to the cyclic features of financial and real aggregates. In addition, even if the honeycomb cycle is not a model for detecting booms and busts in the housing market, the preliminary evidence might suggest a role for volume/transactions in detecting housing market bubbles.

The aim of this paper is to assess whether the inclusion of the rental housing market affect the dynamics of the real business cycles (RBCs).

For this investigation, the authors model and estimate two dynamic stochastic general equilibrium (DSGE) versions for the US economy, one with and one without the presence of residential rent.

The findings provide evidence that the inclusion of the rental housing market can improve the assessment of public policies and the projection of scenarios in the face of sudden macroeconomic shocks. The addition of this secondary housing market augments the effect of total factor productivity (TFP) shock on output and consumption. In addition, it increases the effect of the credit shock on the demand for housing. The latter highlights the role of credit for the real estate market. Therefore, the authors recommend that analysts and macro-prudential authorities consider adding it to their models.

The findings provide evidence that the inclusion of the rental housing market can improve the assessment of public policies and the projection of scenarios in the face of sudden macroeconomic shocks.

This study aims to focus on two-way interaction between monetary policy and house prices in emerging economies.

This study uses panel structural vector autoregressive model.

The results show that real house prices decrease in response to a contractionary monetary policy shock. However, relative to advanced economies, the reaction of the prices is limited in emerging economies, pointing out the structural differences in emerging economies including the small size of the mortgage market and the lack of a well-functioning secondary market in housing finance. This study further finds that monetary policy is tightened in response to a positive shock to house prices. However, this response is also weak when compared to that response in advanced economies.

These findings suggest that house price developments should not be prior target for monetary policies in emerging economies unless they become problem for financial stability or inflationary concerns.

Using a sample of inflation targeting emerging countries, this study contributes to the literature by conducting both panel setting and single-country analysis to explore the two-way dynamic relationships between the monetary policy and housing market in emerging economies.

The purpose of this paper is to review the housing sector of Turkey and present the housing development strategies developed by government enterprises for the urban poor in Turkey as successful examples.

The methodology of the paper is descriptive. First of all, the literature on housing finance systems and sources of housing finance are stated. Then, the paper reviews housing finance systems applied in Turkey in the past to solve housing problems. Later, it describes current housing strategy to solve housing problems of low- and middle-income groups and also presents this strategy as a successful model to other countries. Moreover, mortgage law and the current situation of the Turkish housing sector are discussed within the study.

As a result of economic normalization achieved after 2002, mortgage loans extended by commercial banks have increased in Turkey. Besides, governmental institutions, such as Housing Development Administration of Turkey (HDAT) and Istanbul Public Housing Corporation (KIPTAS), apply very extensive projects to allow low- and middle-income groups to have their dwellings. In 2007, the Turkish Parliament enacted mortgage law and defined rules and actors of the mortgage sector. However, as a consequence of economic deterioration in the world economy, mortgage loan receivables-backed securities could not be issued to public yet. Public issuance of mortgage loan receivables-backed securities in the future are expected to direct more long-term funds to the housing sector and also to provide an additional investment instrument for the individual and institutional investors.

The housing production and finance models developed by the HDAT and KIPTAS can be good models for the solution of housing problems of urban poor in other countries.

The purpose of this paper is to present a framework for the assessment of the fundamental value of house prices in the largest Ukrainian cities, as well as to identify the thresholds, the breach of which would signal a bubble.

House price bubbles are detected using two approaches: ratios and regression analysis. Two variants of each method are considered. The authors calculate the price-to-rent and price-to-income ratios that can identify a possible overvaluation or undervaluation of house prices. Then, the authors perform regression analyses by considering individual multi-factor models for each city and by using a within regression model with one-way (individual) effects on panel data.

The only pronounced and prolonged period of a house price bubble is the one that coincides with the Global Financial Crisis. The bubble signals produced by these methods are, on average, simultaneous and in accordance with economic sense.

The framework described in this paper can serve as a model for the implementation of a tool for detecting house price bubbles in other countries with emerging, small and open economies, due to adjustments for high inflation and significant dependence on reserve currencies that it incorporates.

A tool for measuring fundamental house prices and a bubble indicator for housing markets will be used to monitor the systemic risks stemming from the real estate market. Thus, it will help the National Bank of Ukraine maintain financial stability.

The framework presented in this research will contribute to the enhancement of the systemic risk analysis toolkit of the National Bank of Ukraine. Therefore, it will help to prevent or mitigate risks that might originate in the real estate market.

The authors show how to implement an instrument for detecting house price bubbles in Ukraine. This will become important in the context of the after-war reconstruction of Ukraine, with mortgages potentially becoming the main tool for the financing of the rebuilding/renovation of the residential real estate stock.

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.

This study aims to investigate Feng Shui elements that can influence housing selection and property pricing in the Malaysian housing market.

A structured questionnaire encompassing 26 Feng Shui elements, which were shortlisted based on relevant previous studies, was distributed to prospective homebuyers in the Klang Valley region. The elements were inferred and ranked according to frequency, significance and importance scores. Kruskal–Wallis ANOVA tests were used to assess the ratings provided by the different respondent groups, while Spearman's rank correlation tests were utilised to measure the degree of agreement or disagreement among each pair of the ethnic group.

The results obtained indicate the following as the five most influential elements: orientation, main entrance, street location, house number and living room. Despite a multiethnic and multicultural society in Malaysia, Spearman's rank correlation tests showed that there are no differences in the prioritisation of Feng Shui elements between three distinct ethnic groups (Malay, Chinese and Indian). However, the distribution scores are statistically different between the groups. Comparing income level with Feng Shui inclinations, the three most frequently considered elements across the three income groups consistently include orientation, main entrance and street location.

The findings of this study are expected to provide guidance to property stakeholders (developers, real estate agencies, architects, local authorities) in their future development projects. For homebuyers, this study serves as a property Feng Shui checklist for home selection and investment.

This study explored the association of Feng Shui principles to housing selection and property pricing based on cultural and income factors. These findings provide useful insights for designing and positioning of residential properties in both primary and secondary housing markets in Malaysia and beyond.