Following the 2007-08 Global Financial Crisis, there has been a growing research interest on the spatial interrelationships between house prices in many countries. This paper examines the spatio-temporal relationship between house prices in the twelve provinces of the Netherlands using a recently proposed econometric modelling technique called the Bayesian Graphical Vector Autoregression (BG-VAR). This network approach is suitable for analysing the complex spatial interactions between house prices. It enables a data-driven identification of the most dominant provinces where temporal house price shocks may largely diffuse through the housing market. Using temporal house price volatilities for owner-occupied dwellings from 1995Q1 to 2016Q1, the results show evidence of temporal dependence and house price diffusion patterns in distinct sub-periods from different provincial housing sub-markets in the Netherlands. In particular, the results indicate that Noord-Holland was most predominant from 1995Q1 to 2005Q2, while Drenthe became most central in the period 2005Q3-2016Q1.

Purpose -This paper aims to examine the existence of the ripple effect from Amsterdam to the housing markets of other regions in The Netherlands. It identifies which regional housing markets are influenced by house price movements in Amsterdam.Design/methodology/approach -The paper considers the ripple effect as a lead-lag effect and a longrun convergence between the Amsterdam and regional house prices. Using the real house prices for secondhand owner-occupied dwellings from 1995q1 to 2016q2, the paper adopts the Toda-Yamamoto Granger Causality approach to study the lead-lag effects. It uses the autoregressive distributed lags (ARDL)-Bounds cointegration techniques to examine the long-run convergence between the regional and the Amsterdam house prices. The paper controls for house price fundamentals to eliminate possible confounding effects of common shocks.Findings -The cumulative evidence suggests that Amsterdam house prices have influence on (or ripple to) all the Dutch regions, except one. In particular, the Granger Causality test concludes that a lead-lag effect of house prices exists from Amsterdam to all the regions, apart from Zeeland. The cointegration test shows evidence of a long-convergence between Amsterdam house prices and six regions: Friesland, Groningen, Limburg, Overijssel, Utrecht and Zuid-Holland. The current issue and full text archive of this journal is available on Emerald Insight at: www.emeraldinsight.com/1753-9269.htm Research limitations/implications -The paper adopts an econometric approach to examine the Amsterdam ripple effect. More sophisticated economic models that consider the asymmetric properties of house prices and the patterns of interregional socio-economic activities into the modelling approach are recommended for further investigation.Originality/value -This paper focuses on The Netherlands for which the ripple effect has not yet been researched to the authors' knowledge. Given the substantial wealth effects associated with house price changes that may shape economic activity through consumption, evidence for ripples may be helpful to policy makers for uncovering trends that have implications for the entire economy. Moreover, the analysis controls for common house price fundamentals which most previous papers ignored.

Purpose -The purpose of this paper is to explore the de/motivation variables in the delivery of housing microfinance (HMF) in the low-income housing market in Ghana.Design/methodology/approach -The paper relied on a survey of 125 respondents of microfinance institutions (MFIs) to understand the interactions and effects of these variables on HMF delivery in Ghana. Descriptive and bivariate statistical methods were used to analyse the data.Findings -The findings revealed that both internal and external variables motivate MFIs to engage in the lowincome housing market. These variables are: MFIs desire for expansion, the potential size of the low-income housing market, the market potential for MFIs growth, the availability of local resources, unique features and products of the market, low-income housing offering an opportunity for leveraging resources and the preference for homeownership than rental among individuals in the low-income segment of the population. However, variables such as capital lockup in HMF delivery, high-interest rates in the country, high cost and land prices, high cost and price of building materials, lack of sufficient collaterals and the different interest rates required on HMF loans also served as demotivation in the low-income housing market in Ghana.Research limitations/implications -The paper findings are limited in context to Ghana.Practical implications -The paper, although limited to Ghana, contributes to the much-needed body of knowledge on low-income housing finance in developing countries.Originality/value -The paper is the first of its kind in using empirical data to explore the motivational and demotivational variables in the delivery of HMF in a developing country context such as Ghana.

Purpose The purpose of this paper is to explore the risk factors in homeowners from the individual household’s perspectives within the owner-occupied housing sector of The Netherlands. Risk in home ownership from mortgage providers’ perspectives has received tremendous attention than individual home owner’s perspectives in existing literature following the financial crisis in 2007/2008 within the euro zone. Design/methodology/approach The paper adopted a broader review of extent literature on the different concepts and views on risk in homeownership. These concepts are unified into a framework that enhances our understanding of the perceived sophisticated risk in owner-occupier with focus on The Netherlands. Findings From the perspective of the homeowner, two main types of risks were identified: default payment and property price risk. The paper has unearthed a quantum number of factors which underline the above risks. These factors relate to the initial amount of mortgage loan taken out, the future housing expenses and the income development of the owner-occupier. Family disintegration is identified, as one of the main causes of mortgage default and that of property price risk are mainly influenced by income levels, interest rates and conditions in the social and private rental sectors. Research limitations/implications Findings of the paper are based on review of the extant literature in the context of the Dutch housing market. Possible rigorous situational analysis using other tools are recommended for further research. Originality/value This paper contributes to the much needed body of knowledge in the owner-occupied sector and provides a better understanding of risk in home ownership from the individual perspectives.

This paper uses individual house transaction data from 1995 to 2014 in Amsterdam to explore the risks and interrelationships of the subdistrict house prices. Simple indicators suggest that house prices grow faster and are more risky in the central business district and its immediate surrounding areas than in the peripherals. Furthermore, we observe an over time decreasing intervariations between the subdistrict house price growth rates, whereas we find a lead-lag and house price causal flow from the more central to the peripheral subdistricts.