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This paper aims to examine house price drivers in Dubai, addressing nonlinearity and heterogeneity.

The study applies a combination of linear and nonlinear, as well as quantile regression, specifications to address these concerns and better explain the real-world phenomenon.

The study shows the double-log quantile regression approach is an overarching description of house price drivers, confirming that not only the price of housing and its determinants are non-linearly related but also that their relationship is heterogeneous across house price quantiles. The findings reveal the prevalence of sub-market differentials in house price sensitivity to house attributes such as size (in square meters), location and type of house, as well as government laws. The study also identifies the peaks and deflation, as well as the rebounding nature of the house price bubble in Dubai.

The data used are limited, in that information on only a few house attributes was available. Future research should include data on other house attributes such as house quality, zip codes and composition.

The findings of this study are expected to suggest results with significant ramifications for researchers, practitioners and policy makers. From a policy perspective, there is an obvious interest in understanding whether the price of housing is affected by different attributes differently along its distribution.

This study allows policy makers, developers and buyers of higher-priced houses to behave differently from buyers of lower-priced or medium-priced houses.

Methodologically, it demonstrates alternative linear and nonlinear, as well as quantile regression, specifications to address two increasing concerns in the house price literature: nonlinearity and heterogeneity. Unlike most other studies, this study used a rich data (140,039 day-to-day transactions of 10 years’ pooled data). The Dubai housing market presents an interesting case. UAE (Dubai, in particular) is named as the second-hottest marketplace for global residential property investors, ahead of Singapore, the UK and Hong Kong (Savills plc, 2015).

This paper aims to assess the long-run drivers and short-term dynamics of real house prices in Sweden for 1986Q1 to 2016Q4. More specifically, the author examines the extent to which real house prices are determined by affordability, demographics and asset price factors.

The author conducts a cointegration analysis and applies a vector autoregression model to examine the long- and short-run responsiveness of Swedish real house prices to a number of key categories of fundamental variables.

The empirical results indicate that house prices will increase in the long run by 1.04 per cent in response to a 1 per cent increase in household real disposable income, whereas real after-tax mortgage interest and real effective exchange rates show average long-term effects of approximately – 8 and – 0.7 per cent, respectively. In addition, the results show that the growth of real house prices is affected by growth in mortgage credit, real after-tax mortgage interest rates and disposable incomes in the short run, whereas the real effective exchange rate is the most significant determinant of Swedish real house appreciation.

The impact of the two lending restrictions been implemented after the financial crisis – the mortgage cap in October 2010 and the amortization requirement in June 2016 – are ineffective to stabilize the housing market. This suggests that macroprudential measures designed to ease pressure on housing prices and reduce risks to financial stability need to focus on these fundamentals and address the issues of tax deductibility on mortgage rates and the gradual implementation of debt-to-income limits to contain mortgage demand and improve households’ resilience to shocks.

This study aims to explore the issue of residential price in Malaysia from a supply-side perspective. The views are directly obtained from medium and small-scale developers in Malaysia.

We used the semi-structured interview for analysis purpose. The samples are from property developers (medium and small-scale developers) and a single respondent from the Malaysian National House Buyers Association. We used the judgmental sampling method to choose respondents for this study. The interview results went through content analysis in order to derive common themes, resulting in the identification of four main themes.

First, developers view that the residential market is growing at a good pace, albeit slowly. However, the issue of unaffordability and construction costs remains to haunt the progress of property development in Malaysia. Second, from supply-side perspectives, there are several main reasons why the residential prices in Malaysia are uncontrollable: (1) costs of construction, (2) taxes, (3) existing units, (4) location and (5) urbanization. The third theme is the government support in catering to the needs and wants of middle- and lower-income earners. Most respondents agreed that the government has been providing low-cost houses supported by various incentives. Finally, on price control strategies for residential units, recommended suggestions are as follow: embracing different methods of construction styles, promote the uses of local materials instead of relying on imported materials, continuously review rules and regulations, provide more incentives and to build partnerships between the government and private companies on affordable housing projects.

The research is expected to present solid findings and claimsseveral significant contributions, especially policy-wise. We believe this contribution will enrich the existing literature on residential market. The present study is also predicted to produce noteworthy findings to all stakeholders in the real-estate industry, such as potential home buyers and existing house owners to housing developers, marketers and government policy regulators, as well as academic institutions.

This study is expected to enrich the existing literature available in the context of real-estate finance such as property price and property policy in emerging economies like Malaysia. One distinguishing factor which differentiates this study from others in the literature is the feedbacks obtained from medium and small-scale developers, therefore deemed to be more solid and reliable. The current research in real-estate finance is mainly focused on empirical analysis and we believe this study will offer a breakthrough view on the matter of residential market in Malaysia.

The purpose of this study is to conduct a thorough empirical investigation of the intricate relationship between urban housing sales prices and land supply prices in China, with the aim of elucidating the underlying economic principles governing this dynamic interplay.

Using monthly data of China, the authors use the asymmetry nonlinear autoregressive distributed lag (NARDL) model to test for nonlinearity in the relationship between land supply price and urban housing prices.

The empirical results confirm the existence of an asymmetric relationship between land supply price and urban housing prices. The authors find that land supply price has a positive and statistically significant impact on urban housing prices when land supply is increasing. Policymakers should strive to strike a balance between safeguarding residents’ housing rights and maintaining market stability.

Although the asymmetric effect of land supply price has been identified as a significant contributor in this study, it is important to note that the research primarily relies on time series data and focuses on analysis at the national level. Although time series data offer a macroscopic perspective of overall trends within a country, they fail to adequately showcase the structural variations among different cities.

To ensure a stable housing market and meet residents’ housing needs, policymakers must reexamine current land policies. Solely relying on restricting land supply to control housing prices may yield counterproductive results. Instead, increasing land supply could be a more viable option. By rationally adjusting land supply prices, the government can not only mitigate excessive growth in housing prices but also foster the healthy development of the housing market.

First, the authors have comprehensively evaluated the impact of land supply prices in China on urban housing sales prices, examining whether they play a facilitating or mitigating role in the fluctuation of these prices. Second, departing from traditional linear analytical frameworks, the authors have explored the possibility of a nonlinear relationship existing between land supply prices and urban housing sales prices in China. Finally, using an advanced NARDL model, the authors have delved deeper into the asymmetric effects of land supply prices on urban housing sales prices in China.

The purpose of this paper is twofold. First, the authors investigate the main drivers of house prices in the Hong Kong housing market. Second, further research is undertaken to confirm the existence of house price overvaluation, which has driven the market into a bubble episode.

First, the authors propose a theoretical framework to identify the fundamentals of the market. In the second step, they decompose house prices into fundamentals, frictions and bubble episodes for a better understanding of the evolution of house prices during the period 1996(Q3)-2013(Q3).

The results of this paper suggest an eventual possible correction of up to 46 per cent of house prices with respect to their 2013(Q3) level.

The originality of this paper is to use the procedure developed by Glindro and Delloro (2010) to analyse the Hong Kong housing market. The contribution of this paper also modifies the original Glindro and Delloro’s (2010) approach by including the Christiano and Fitzgerald (2003) filter to decompose house prices.

The purpose of this paper is to analyse how London Interbank Offered Rate Index (LIBOR) and the spread between LIBOR and the base rate of interest as set by the Bank of England (BoE) influences the variation in house prices in the UK.

This paper uses monthly data over a long time series, since 1986, to investigate the relationships between house price and LIBOR. Data are drawn from several different sources to include housing, financial and macro-economic variables. The time series is sub-divided into a series of splines based on stages in the economic and property market cycle. Both value-based and percentage change models are developed.

The results show that BoE base/LIBOR margin variable has a strong positive and significant effect on house price; however, the percentage change model infers a weaker and inverse relationship. The spline analysis re-emphasised the significance of the BoE base/LIBOR margin variable. Where variation between base rates and LIBOR is reduced, a significant positive effect can be observed in the average house price; however, where significant variation exists, the BoE base/LIBOR margin has little effect and LIBOR itself becomes a significant driver.

The results highlight that the predictive qualities of the BoE base/LIBOR margin, as the contribution of this margin to the explanation of house price, exceeds both the base rate and LIBOR variables individually. Also highlighted is the contribution of unemployment to the explanation of house price. In both the value and percentage change models, unemployment is shown as a negative and highly significant contributor.

Previous papers have demonstrated the important linkage between house price and interest rates, the originality in this paper lies in examining the impact of LIBOR and the spreads between LIBOR and base rate as key variables influencing variation in UK house prices.

The purpose of this paper is to provide perspective on whether and why global metro house prices have become more synchronized, and perspective on the limited implications of this for investing in international real estate.

This paper reviews main findings from the literature on house price determination, reviews the emerging literature on global synchronization, and provides graphs to illustrate main points and trends.

House prices have become somewhat more synchronized likely reflecting greater correlation in long-term interest rates and macroeconomic cycles related to trends in globalization and international portfolio diversification. Nevertheless, this trend has not been continuous, reflecting that house prices depend on other fundamentals, which are not uniform across areas. Theory and evidence indicate that the more common are fundamentals, the more synchronized are house price cycles and the more substitution effects may matter. Also, real estate markets that are open to immigration and foreign investment have become more sensitive to shifts in the international demand for property by migrants or investors.

Changes in international house price synchronization stem from variation in two categories of key drivers of house prices. The first are traditional supply and demand fundamentals. The second include international capital flows and immigration. Both sets of factors are sensitive to the economic environment and public policy. Increased synchronization of business cycles, the Euro currency union, and more common monetary policy strategies and tactics have fostered greater correlation of real interest rates across countries, which tend to increase house price synchronization. These effects can be amplified by the tendency for property owners to use extrapolative expectations of future house prices.

Shifts in prospective returns and the synchronization of international property returns not only on arbitrage of general property price differentials but also on underlying factors driving those differentials. Investors need to be mindful of the risks that metro prices sometimes reflect bubble-builder dynamics that can give rise to over-shooting of house prices. Observing simple correlations and changes in those correlations does not do away with the need for careful analysis of property investment, and if anything, warrant analysis of both how and why one may observe changes in the extent to which international house prices is synchronized.

Despite the rise of globalization and of new technologies, the author has seen substantial divergences in house prices emerge across gateway cities and metros in less vibrant areas within countries. These reflect not only the impact of stronger income and population in more tech, educated and global oriented cities but also changes in the demand for amenities toward more culturally appealing cities, often – but not exclusively in – warmer or coastal areas where the supply elasticity of housing is often limited. Further complicating investment decisions are potential shifts in housing or immigration policy that can notably affect the demand for housing.

The paper provides practical perspective on why different groups of international cities have seen their house prices become more sychronized. Nevertheless, increased synchronization has occurred within an elite set of major cities, but in an environment house prices have diverged across gateway cities and metros in less vibrant areas within countries. The paper helps investors make sense of some recent patterns and recent prospects for investing in international real estate.

This study aims to build a two-country monetary union dynamic stochastic general equilibrium (DSGE) model with housing to assess how different shocks contributed to the increase in housing prices and credit in the European Economic and Monetary Union. One of the countries is calibrated to represent the core group in the euro area, while the other one corresponds to the periphery.

In this paper, the authors explore how a liquidity shock (or a decrease in the interest rate) affects house prices and the real economy through the asset price and the collateral channel. Then, they analyze how a house price shock in the periphery and a technology shock in the core countries are transmitted to both economies.

The authors find that a combination of an increase in liquidity in the euro area coming from the common monetary policy, together with asymmetric house price and technology shocks, contributed to an increase in house prices in the euro area and a stronger credit growth in the peripheral economies.

This paper represents the theoretical counterpart to empirical studies that show, through macroeconometric models, the interrelation between liquidity and other shocks with house prices. Using a DSGE model with housing, the authors disentangle the mechanisms behind these empirical findings.

The purpose of this paper to provide a discussion of the empirical evidence and contributing factors of the synchronization of house prices globally.

The author reviewed the main studies on house price synchronization and conducted an empirical analysis using OECD house price indices. A discussion of the contributing factors of synchronization, with a focus on the demand and supply dimensions is provided, and synchronization across both countries and cities is examined.

Housing markets globally have become more synchronized; this is particularly clear for cities. The sustained demand for places that are attractive for financial motives and for lifestyle and sometimes climate along with the fact that such places tend to be supply-constrained is likely to lead to more synchronization across markets.

The conclusions are important for investors seeking to diversify their housing holdings internationally. The discussion should also benefit policy-makers.

To date, very scarce evidence exists on the synchronization of house prices globally. By surveying the results contained in previous studies and providing a thorough discussion of the possible drivers of house price synchronization, this study contributes to a better understanding of this important topic.

This study aims to analyze the impact of COVID-19 on housing price within four major metropolitan areas in Texas: Austin, Dallas, Houston and San Antonio. The analysis intends to understand economic and mobility drivers behind the housing market under the inclusion of fixed and random effects.

This study used a linear mixed effects model to assess the socioeconomic and housing and transport-related factors contributing to median home prices in four major cities in Texas and to capture unobserved factors operating at spatial and temporal level during the COVID-19 pandemic.

The regression results indicated that an increase in new COVID-19 cases resulted in an increase in housing price. Additionally, housing price had a significant and negative relationship with the following variables: business cycle index, mortgage rate, percent of single-family homes, population density and foot traffic. Interestingly, unemployment claims did not have a significant impact on housing price, contrary to previous COVID-19 housing market related literature.

Previous literature analyzed the housing market within the first phase of COVID-19, whereas this study analyzed the effects of the COVID-19 throughout the entirety of 2020. The mixed model includes spatial and temporal analyses as well as provides insight into how quantitative-based mobility behavior impacted housing price, rather than relying on qualitative indicators such as shutdown order implementation.