Welcome to the fourth issue in the 15th volume of the International Journal of Housing Markets and Analysis. This issue contains ten research papers from nine different countries where there have also been a diverse range of research objectives, methodologies and findings. The countries and regions are not limited to a select few, therefore including both developed and developing countries to provide a cross section of the various challenges. The first paper from Kuwait examines the operation of the housing market in a country recognised as a major oil producer, is sensitive to geo-political events and has unusual demographic characteristics. The methodology used an error-correction model and was based on analysing housing market dynamics and also the level of sensitivity in the housing market in relation to major local and regional events. The findings confirmed the market is relatively volatile with evidence of mean-reverting behaviour. However, when smoothing is undertaken there are more consistent findings in alignment with underlying fundamentals. The paper also examined the response of the market to seven regional and local events, where “domestic legislation directly concerned with housing” was identified as the single event that resulted in a consistent significant response.
The second paper from Portugal investigates the effect from a surge in tourism short-term rentals (STR) on housing prices in the two large metropolitan statistical areas municipalities. The methodology used a difference-in-differences (DiD) model by using a feasible generalised least squares estimator in a seemingly unrelated regression equation model. The findings confirmed the liberalisation of tourism STR had a significant impact on housing prices in municipalities where a higher percentage of housing was transferred to tourism. In turn this led to a leftward shift of the housing supply and a subsequent increase in housing prices, where these price increases were much higher than observed in previous studies. In other words, the consequence of allowing property owners to transfer the use of real estate from housing to other services (namely, tourism) was extreme housing price increases primarily due to inelastic housing supply. Also it was noted that municipalities with higher exposure to STR exhibited low housing elasticities, indicating that adjustments to supply shocks in low elasticity markets were undertaken via price increases.
This third paper from China identifies and examines barriers hindering the supply and demand of “continuing care retirement communities” (CCRCs) with the objective of identifying effective senior housing policy measures to facilitate CCRC developments. The study focussed on Shanghai being a large global city and experiencing a rapid increase in ageing population and higher demand for senior housing. The methodology used a multiple-case study approach where four representative CCRC development cases in Shanghai were examined. This was accompanied by interviews with experienced CCRC development managers and also a questionnaire survey of CCRC residents. The main supply barriers were identified as operation management experience, financial risks and a shortage of senior housing policy support. However, the existence of traditional Chinese family-oriented culture and also affordability were not the main demand barriers of CCRCs in Shanghai. With reference to housing investors, future successful CCRC development should be based on partnering with experienced professional eldercare management companies, provision of high-quality medical professionals, trained care personnel and quality facilities, as well as intensive capital flows to cater for land, construction and operating costs.
The fourth paper from Malaysia examines the causal impact of international immigration inflows on housing prices at the state level from 2007 to 2018. The methodology used hedonic regression including both fixed effects and first differencing approaches to estimate the impact of immigration inflows on house prices. The approach addressed potential endogeneity of immigrants’ choices of destination states by using a shift-share instrument variable approach. The findings showed that a 1% increase in immigration inflows was associated with an increase of 10.2% (first difference) and 13.4% (fixed effects) in house prices. Furthermore, the economic impact was larger in magnitude than observed in developed countries. Contrary to earlier studies that show immigration inflows to be associated with native flight, these findings supported the attraction effects hypothesis where immigration inflow is positive and significantly related to native inflows.
This fifth paper from Iran proposes a practical model for the production of new homes according to demand. Following an analysis of inhabitants’ priorities and preferences, the paper then presents a programming model for housing construction projects. The methodology is based on the use of theoretical studies, a case study strategy, market analysis, linear planning and classic procedures. The case study investigates the preferences of applicants and estimates building productions based on feedback and needs. The primary outcome of this research is a home-building program designed around the particular requirements of the population and also regional characteristics. Another outcome is the ability to simulate the model in any global location where a housing crisis exists.
The sixth paper from Lithuania identifies external factors with the largest impact on housing prices. The outcomes from this study will assist policymakers to select the most appropriate decisions to stabilise the real estate market. The methodology was based on an econometric analysis including a stationary test, Granger causality test, correlation analysis, linear and non-linear regression models, threshold regression and autoregressive distributed lag models. The data set included 137 external factors that can be grouped together as macroeconomic, business, financial, real estate market, labour market indicators and expectations. The findings confirm the level of housing price depends largely on macroeconomic indicators including gross domestic product (GDP) growth and consumer spending. Furthermore, the cash and deposits of households were the most important indicators attributed to the group of financial indicators. The impact of financial, business and labour market indicators on housing price varies and is dependent on the actual stage of the economic cycle.
The seventh paper from Australia examines higher education as it is one of the largest export sectors in the Australian economy where purpose-built student accommodation (PBSA) has emerged as a new asset class. As of 2020 there were still approximately 400,000 onshore international students and 135,000 offshore students despite the commencement of the COVID pandemic. At the same time various universities remain optimistic about the future level of overseas student returns to Australia. This study examines the investment potential of the PBSA sector over the long term where active PBSA investors remain focused on the long-term fundamentals of the student market. The methodology involved expert interviews with directors of property investment companies and a private family trust investor in tandem with multiple case studies of in-campus and off-campus PBSAs. The findings confirmed the existence of a positive and consistent demand trend and sustained rental growth, predominantly supported by an increased number of international students over the long term. It was argued that to maximise the level of rental growth there should be self-contained studio type accommodation with quality facilities and social support provided. In addition, the operators should regularly monitor the needs of students and provide a superior living experience.
The eighth paper from China examines the level of impact that land supply has housing prices and whether heterogeneity exists in different regional spaces. Although economic fundamentals are accepted as determining factors affecting housing fundamentals at the city level, the relationship between housing price and land supply is not fully understood. The methodology is based on analysing data relating to land supply and housing prices in Nanchang from 2010 to 2018. The approach constructed a vector autoregressive model incorporating one external factor and four internal factors associated with land supply to examine the dynamic effects and spatial heterogeneous of land supply on housing prices via a regression analysis. In addition, the methodology analysed the spatial heterogeneous of housing prices. The main findings were:
the interaction between land supply and housing price is extremely complex due to the significant differences in the study area;
the variables relating to land supply produced both positive and negative effects on housing price where the actual effect varies in each region; and
residential land and GDP were the two main factors leading to spatial heterogeneity in housing price.
The ninth paper from Vietnam examines countries without national property insurance to assess how their experience affects behaviour towards higher risk flood prone property. The methodology was based on a unique data set that captures the flood experiences of home owners who search for new housing, as well as examining the premiums or discounts on homes considered to be at risk. The approach uses hedonic property modelling to estimate the influence from their experience on values. The findings confirm that experiences play a strong role in convincing buyers about the actual risks associated with climate change and sea level rise, however it anticipated that demand side behavioural changes will continue. This outcome differs in contrast to more developed markets where insurance may be subsidised and any negative effect on value dissipates within a few years. It was concluded that increasing attention should be placed upon climate risk; however, the results in developed countries have been biased due to insurance provided by government and/or emergency funding.
The tenth paper from Sweden aims to measure the level of gentrification and the relationship between gentrification and housing values. The methodology used Getis-Ord statistics to identify and quantify gentrification in different residential areas based on a case study of Stockholm. With this approach the level of gentrification is measured in two dimensions, namely income and population. In the second stage a traditional hedonic pricing model was used with the intention of explaining future housing price levels. The findings showed the parameter estimate is statistically significant, suggesting that gentrification contributes to higher housing values in gentrified areas and near gentrified neighbourhoods. The possible spillover effect of house prices attributed to gentrification by income and population was similar in both the hedonic price and treatment effect models. According to the hedonic price model the proximity to the gentrified area increased housing value by approximately 6–8%. The spillover effect on price distribution appeared to be consistent and stable in gentrified areas.
Prospective authors are welcome to engage with the editor prior to submission to ensure their paper is in an acceptable format for publication. This includes ensuring the submitted paper conforms to the author guidelines for the journal which can reduce the time the paper spends in the double-blind review process. Please contact the editor directly if I can be of assistance prior to submission and/or discuss the procedure for admission into the review process. If you are interested in submitting a research paper or reviewing potential publications, please contact the editor direct at ijhma@ijhma.com.
