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A panel error correction model has been developed to investigate the spatial correlation patterns among house prices. This paper aims to identify a dominant housing market in the ripple down process.

Seemingly unrelated regression estimators are adapted to deal with the contemporary correlations and heterogeneity across cities. Impulse response functions are subsequently implemented to simulate the spatial correlation patterns. The newly developed approach is then applied to the Australian capital city house price indices.

The results suggest that Melbourne should be recognised as the dominant housing market. Four levels were classified within the Australian house price interconnections, namely: Melbourne; Adelaide, Canberra, Perth and Sydney; Brisbane and Hobart; and Darwin.

This research develops a panel regression framework in addressing the spatial correlation patterns of house prices across cities. The ripple-down process of house price dynamics across cities was explored by capturing both the contemporary correlations and heterogeneity, and by identifying the dominant housing market.

Studies into ripple effects have previously focused on the interconnections between house price movements across cities over space and time. These interconnections were widely investigated in previous research using vector autoregression models. However, the effects generated from spatial information could not be captured by conventional vector autoregression models. This research aimed to incorporate spatial lags into a vector autoregression model to illustrate spatial‐temporal interconnections between house price movements across the Australian capital cities.

Geographic and demographic correlations were captured by assessing geographic distances and demographic structures between each pair of cities, respectively. Development scales of the housing market were also used to adjust spatial weights. Impulse response functions based on the estimated SpVAR model were further carried out to illustrate the ripple effects.

The results confirmed spatial correlations exist in housing price dynamics in the Australian capital cities. The spatial correlations are dependent more on the geographic rather than the demographic information.

This research investigated the spatial heterogeneity and autocorrelations of regional house prices within the context of demographic and geographic information. A spatial vector autoregression model was developed based on the demographic and geographic distance. The temporal and spatial effects on house prices in Australian capital cities were then depicted.

This paper aims to examine the integration of housing markets in Canada by examining housing price data (1999–2016) of six metropolitan areas in different provinces, namely, Calgary, Vancouver, Winnipeg, Toronto, Montreal and Halifax. The authors test for cointegration, driver cities of long-run relationships, long-run Granger causality and instantaneous causality in light of the global financial crisis (GFC) (2007–2008).

The authors use Johansen’s system cointegration approach with structural breaks. Moving average representation is used for common stochastic trend(s) analysis. Finally, the authors apply vector error correction model-based Granger causality and instantaneous causality.

Cities’ housing prices are in long-run equilibrium. Post-crisis Canadian housing markets became more integrated. The Calgary, Vancouver, Toronto and Montreal markets drive the Canadian housing market, leading all cities toward long-run equilibrium. Strong long-run Granger causality exists, but the authors observe no instantaneous causality. Price information takes time to disseminate, and long-run price adjustments play a significant role in causation.

The findings of cointegration increasing after the GFC and strong lead–lag can be used by investors to arbitrage and optimize portfolios. This can also help national and local policymakers in mitigating risk. Incorporating these findings can lead to better price forecasting.

This study presents many novelties for the Canadian housing market: it is the first to use repeat-sales regional pricing indices to test long-run behaviors, conduct common stochastic trend analyzes and present causality relations.

Informal dwellings describe makeshift lodgings made from temporary materials, such as plastic, corrugated iron, sheeting, packing cases, or wood. These units allow low-income groups to informally occupy land and create their habitable space in a phased manner. This article focuses on elements of the urban morphology, such as density, accessibility, and operating assortment of informally built areas in the southern region of Montenegro.

The author examines the urban morphologies of four urban areas, whose informality is traditionally viewed as markers of decline and despair. Using observations, questionnaires, and semi-structured interviews, the investigator maps dwellings in Ulcinj, Budva, Tivat, and Herceg Novi neighbourhoods. The researcher interrogated participants about land distribution during the construction of sheds, buildings' outline and orientation toward the street, and activities performed in their dwellings, such as living, working, and accommodating relatives and guests. This methodology tests the hypothesis, formulated as a deeper understanding of urban morphology for examining the interweaving of informally built settlements with the rest of the city.

A cartographic investigation is used to reframe customary rights of low-income populations to land inclusion and their place in the city. The results clearly show that the location and lifestyle are designed to obfuscate the vulnerable populations from the public view, disconnected from policymaking, and ignored by urban planning projects. However, the interviewees' destinations orientation away from the downtowns represents the possibility of reconfiguring existing urban planning practices. For creating alternative urbanisation, the orientation of less visible neighbourhoods presents a model for building regulations embedded in social forces and cultural habits of all social and ethnic groups.

This study did not address the implementation of social hosing policies and the logistical limitations of realising them by the local and national governments. During firework, the author encountered dwellers outside four studied low-income neighbourhoods in the south region of Montenegro. Mapping morphological elements of these generally small clusters of informal built units are left for future research. Future studies could examine how informality is performed in Montenegro by moderate and high-income groups as an assemblage of different power relationships and urban practices.

The argument is based on counter urbanism as the orientation and destination of less visible neighbourhoods for creating building regulations embedded in social forces and cultural habits of all social and ethnic groups. This study showed that the urban morphology of informality in the coastal cities of Montenegro lays the ground for alternative urban planning practices based on the different interconnection of districts. The outcome is a strong link between different social and ethical groups through self-building practices.

In coastal cities of Montenegro, Roma, Ashkali, and Egyptian live with other low-income groups in unsanitary settlements characterised by poor living conditions, low-quality illegally built housing, no plumbing or sewage systems, and overcrowded urban areas. Mapping morphological elements of less visible urban areas propose shifting from top-down urban planning policies to a participatory model of developing urban areas.

The assemblage of informally built urban areas legitimise place in the city that goes against the housing market's dominant logic and exceeds alternative logics of building production. This article outlined the urban morphologies of four urban areas for turning the image of informality away from decline and despair to lessons of urban interconnection. By creating different maps, the author presented a diverse orientation of four case studies based on density, accessibility, and operating assortment.

The purpose of this study is to investigate the Ripple Effect of house prices at an inter-suburban level of analysis in the Sydney metropolitan area. By doing this, more practical information of price transmission can be provided to improve residential real estate purchasing decisions of market participants. Equity from residential real estate is a major component of household wealth and is frequently used to improve and upgrade homes. With the ever-increasing prices of real estate in Sydney making more efficient purchasing decisions can grow this wealth quicker allowing a household to obtain financial related goals at a quicker pace.

Using a two-stage sampling technique strings of adjoining suburbs from different Sydney regions were analysed using a combination of price graphs, Engle–Granger and Johansen co-integration techniques and Granger causality tests.

Pairwise co-integration was lacking throughout the various suburb strings, whereas multivariate co-integration was found in the lower priced areas further from the central business district, as these areas also experience less price volatility. The geographical location of suburbs therefore plays an important role in the ability to predict an individual suburb’s price movements. For a prominent Ripple Effect to exist at this level the best conditions would consist of a singular demand centre with restricted geographical space to which this demand can spread. Causal pathways were subsequently mapped for each suburb string identifying price transmission pathways and confirming support that while the standard Ripple Effect does not exist at an inter-suburban level, it is still possible to predict price movements by considering the price behaviour of surrounding suburbs.

This paper adds to the literature by examining the Ripple Effect across different suburbs in Sydney. This is done via an extensive search through the literature and analysing recent real estate data.

The main aim of this study is to determine the factors that influence the housing demand of households in Erzurum, northeastern Turkey. Housing demand is generally affected by several factors including housing prices, individuals’ income, expectations and choices and so on, as a means of its demographic and socio-psychological contexts.

A questionnaire-based cross-sectional survey was carried out, in which the outcome variable had binary responses such as whether to invest in housing or not. A binary logistic regression analysis was performed to estimate the underlying data.

The questionnaire was conducted in 2,927 households living in Erzurum city center, and 47 per cent of the respondents claimed that they would consider investing in housing in the future. The estimation results reveal that demographic or socio-economic factors that may possibly influence housing demand of the respondents are as follows: household head’s and spouse’s occupation, monthly income, the number of individuals in the family and car ownership.

This paper involves the most comprehensive survey addressing the housing demand in the East Anatolian Region, Turkey. Additionally, this paper aims to contribute to the existing housing literature through establishing the statistical analysis of housing demand in an unstudied territory of the world.

This study aims to investigate the relationship between market share and rent levels to understand the supply structure in the Japanese private rental housing market.

The study calculates the municipal-level market share of a dominant rental housing operator in Japan and ascertained the overall market rent and the dominant operator’s rent premium at the municipal level by using a major web portal’s listing data of rental houses.

The study shows that, as market share increased, overall market rent tends to decrease, and analyzed by market share, there is no significant difference between the rent of the dominant operator and the overall market rent.

The results of the study suggest that dominant operators may have lowered the rent of their own property to prioritize filling vacancies, which, in turn, causes the overall level of market rent to decline. This is an outcome of rental housing operators’ strategy to maximize long-term rental income under sublease contracts with individual owners, which ensures stable rental income for owners regardless of the occupation status of the apartments.

Previous research on regional monopolies in mortgage sales and brokerage businesses in the USA implies that rental housing operators in a position of great influence over the market can control and keep the market rents at high levels, that is, at large costs for consumers. The findings of the study are novel in showing the inverse relationship in the Japanese private rental market.

The purpose of this study is to reveal the dynamics of house prices and sales in spatial and temporal dimensions across British regions.

This paper incorporates two empirical approaches to describe the behaviour of property prices across British regions. The models are applied to two different data sets. The first empirical approach is to apply the price diffusion model proposed by Holly et al. (2011) to the UK house price index data set. The second empirical approach is to apply a bivariate global vector autoregression model without a time trend to house prices and transaction volumes retrieved from the nationwide building society.

Identifying shocks to London house prices in the GVAR model, based on the generalized impulse response functions framework, I find some heterogeneity in responses to house price changes; for example, South East England responds stronger than the remaining provincial regions. The main pattern detected in responses and characteristic for each region is the fairly rapid fading of the shock. The spatial-temporal diffusion model demonstrates the presence of a ripple effect: a shock emanating from London is dispersed contemporaneously and spatially to other regions, affecting prices in nondominant regions with a delay.

The main contribution of this work is the betterment in understanding how house price changes move across regions and time within a UK context.

The purpose of this paper is to first explore whether Australia and the main metropolitan areas demonstrate significant differences in tenure and property type between generational groups. Second, whether the millennial generation is more likely to rent rather than own. Third, if such variation in tenure and property type by millennials is one of individual choice and lifestyle or the impact of housing market inefficiencies.

This paper employs a comparative research approach using secondary data from the Australian Bureau of Statistics (ABS) to consider housing tenure and type distributions across generations as well as through cross-city analysis.

The results show that home ownership is still the dominant tenure in Australia, but private rental is of increasing significance, becoming the tenure of choice for Millennials. Owner occupation is shown to remain and high and stable levels for older generations and while lower in percentage terms for Generation X; this generation exhibits the highest growth rate for ownership. Significant differences are shown in tenure patterns across Australia.

The significance of this paper is the focus on the analysis of generational differences in housing tenure and type, initially for Australia and subsequently by major metropolitan areas over three inter-census periods (2006, 2011 and 2016). It enhances the understanding of how policies favouring ageing in place can contradict other policies on housing affordability with specific impact on Millennials as different generations are respectively unequally locked-out and locked-in to housing wealth.