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This paper aims to use Markov switching vector auto regression (MSVAR) methods to examine UK house price cycles in UK regions at NUTS1 level. There is extensive literature on UK regional house price dynamics, yet empirical work focusing on the duration and magnitude of regional housing cycles has received little attention. The research findings indicate that the regional structure of UK exhibits that UK house price changes are best described as two large groups of regions with marked differences in the amplitude and duration of the cyclical regimes between the two groups.

MSVAR principal component analysis NUTS1 data are used.

The housing cycles can be divided into two super regions based on magnitude, duration and the way they behave during recession, boom and sluggish periods. A north-south divide, a uniform housing policy and a monetary policy increase the diversion among the regions.

Markov switching needs high-frequency data and long time spans.

Questions a uniform housing policy in a heterogeneous housing market. Questions the impact of monetary policy on a heterogeneous housing market. The way the recovery of the housing market varies among regions depends on regional economic performance, housing market structure and the labour market. House price convergence, beta-convergence.

No such work has been done looking at duration and magnitude of regional housing cycles. A new econometric method was used.

Reviews a number of contributions to migration analysis. Discusses some of the rudiments of migration modelling before turning attention to specific applications. Pays particular attention to articles which have modelled the interaction between labour and housing markets.

Increasing regional wealth disparities have been explained by the role of agglomeration economies and the concentration of skilled mobile human capital. This paper aims to draw out the role of the housing market by considering the differential experience of Germany and the UK.

The empirical analysis is based on the comparison of regional house price trends in Germany and UK-based annual data from 1991 to 2015.

Regional house price inequality is found to have increased in both countries with the spatial concentration of skilled human capital. However, the main conclusion is that there are differential paths to regional house price inequality explained by the parameters of each country’s housing market.

The research is the first to compare and explain differential regional house price trends across countries.

This paper develops a new decomposition method of the housing market variations to analyse the housing dynamics of the Australian eight capital cities.

This study reviews the prior research on analysing the housing market variations and classifies the previous methods into four main models. Based on this, the study develops a new decomposition of the variations, which is made up of regional information, home‐market information and time information. The panel data regression method, unit root test and F test are adopted to construct the model and interpret the housing market variations of the Australian capital cities.

This paper suggests that the Australian home‐market information has the same elasticity to the housing market variations across cities and time. In contrast, the elasticities of the regional information are distinguished. However, similarities exit in the west and north of Australia or the south and east of Australia. The time information contributes differently along the observing period, although the similarities are found in certain periods.

This paper introduces the housing market variation decomposition into the research of housing market variations and develops a model based on the new method of the housing market variation decomposition.

Concerning migration on a national level, two phenomena emerge: people migrating from one region to another and people moving from the countryside to the cities. The geographical shift of the population between regions in a country is a slow process. In Sweden, only a few percent of the population migrate yearly. Nevertheless, migration has caused and still causes considerable redistribution of the population toward the metropolitan regions in Sweden. This section will emphasize general trends in population concentration through urbanization and migration in Sweden and compare these trends with changes in other countries.

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.

In this chapter, we aim to analyze the housing market development in Czechia, in particular the development of housing prices over the last 25 years. We quantify and discuss three distinct periods of excessive growth of regional Czech housing prices, identified through the formation of large positive GAPs – (1) before the entrance of Czechia to the European Union (EU), (2) at the onset of the Global Financial Crisis GFC, (3) in 2021. In all these periods, we identify significant differences among regions. We find that GAPs above 15% may be considered an indication of unsustainable long-term housing price growth that will be followed by a correction.

We then employ fixed effect panel data model to determine the drivers of flat and house prices in 14 Czech regions. Our results show that wage growth, migration and crime rate are significant factors affecting the prices of both flats and houses. Nevertheless, the impact of GDP per capita and job market indicators differs between flats and houses. Moreover, we find that higher migration into the region increases the difference between the prices of houses and flats, while increasing GDP per capita growth and crime rate mitigate this difference significantly.

This paper draws on research conducted after the 2004 Indian Ocean Earthquake and Tsunami in Aceh, Indonesia, where more than 100,000 houses were built by various agencies following the massive disaster. The research reveals that the residents in Aceh rarely see their reconstruction houses as ‘complete’ and modify these houses to suit their personal needs and aspirations. The relationships between the global and regional forces that drive reconstruction agency housing procurement and production are explored, and compared with the outcomes of user-initiated modifications to the houses. From the hundreds of houses reviewed, here four houses are discussed in detail, built by the Asian Development Bank, representing a global paradigm, and Bank Mandiri, representing a regional paradigm. These houses were modified and extended to varying degrees by their residents, exemplifying the ways in which reconstruction agencies, perhaps inadvertently, empowered residents by enabling them to improve their own housing. The outcomes of this transformation process underscore the advantages of a hybrid between global and regional styles, and the desire of the reconstruction housing residents to recapture some of the local housing culture and reflect regional housing characteristics.

Between 1997 and 2005, the German government provided owner‐occupied subsidies to fund new private housing construction and stock purchases to increase owner‐occupied housing. The purpose of this paper is to analyse the impact of these subsidies on total housing construction for the 1997‐2007 period using regionalised data. This paper tests for differences between counties and cities and examines whether local participation in housing programs is related to regional migration and fertility. Based on the dynamic results, short‐ and long‐run elasticities with respect to the subsidy program are calculated.

A balanced panel data set is used that covers approximately 95 percent of all German NUTS‐3 regions (counties and independent cities) for the 1997‐2007 period. To control for serial correlation, possible endogenous relationships and omitted variable bias problems, the System Generalised Methods of Moments estimation technique is applied.

A significantly positive impact of subsidised construction is detected in counties with an elasticity of approximately 0.2 in the short run and 0.48‐0.58 in the long run. The elasticities in independent cities are significantly lower, at 0.11 and 0.32‐0.37, respectively. No significant effect of migration on construction was found, in contrast to a significantly positive effect of fertility, especially at the county level. The estimates suggest a significantly negative effect of subsidised stock purchases on total construction.

Tests for other countries using regional data on interest rates, construction costs and housing prices could lead to further insights.

The findings suggest that further owner‐occupied subsidy programs should be geared toward families or larger households. It also seems important to provide sufficient building land to enable households to make use of housing construction subsidies.

This is the first regional paper to examine housing construction elasticities with respect to a subsidisation program for housing construction and stock purchases that was designed for virtually all households in a country. It is also the first paper to test for differences in participation in a large‐scale, national housing program related to migration and fertility.

This paper aims to examine the housing market in Greece after the Global Financial Crisis focussing on regional analysis and urban markets in Athens and Thessaloniki.

The paper uses a data set of over 70,750 property values from 2007 until 2014 incorporating characteristics variables upon which hedonic models are estimated. These form the bases for calculating value indices for mix adjusted houses/apartments by year and region. The indices are used in a panel model in which regional and economic variables are included as independent variables. Using advances in dynamic panel data modelling, a bias-corrected least squares dummy variable corrected (LSDVC) model is applied.

Results indicate the importance of macroeconomic variables in terms of the role of disposable income and significantly different regional effects. Examining the major urban markets, results indicate significant differences in the response of house values to exogenous demand side influences, consistent with the finding of significant regional differences in the LSDVC.

While data on valuations are used that may contain smoothing, the data set covers a large sample of residential properties. As regional economic differences are significant and persistent, housing markets will also behave differently, and hence national policies, unless targeted, will have regionally differentiated effects.

Regional heterogeneity needs to be considered in model estimation.

Policymakers should consider regional differences to improve policy effectiveness.

This is the first paper to use a large sample of residential properties in Greece and apply the LSDVC model to overcome estimation biases.