12 research outputs found
Spatial and Temporal House Price Diffusion in the Netherlands: A Bayesian Network Approach
Get PDFFollowing the 2007-08 Global Financial Crisis, there have 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 Bayesian graphical vector autoregression (BG-VAR). This network approach enables a data driven identification of the most dominant provinces where house price shocks may largely diffuse through the housing market and it is suitable for analysing the complex spatial interactions between house prices. Using temporal house price volatilities for owner-occupied dwellings, the results show evidence of house price diffusion pattern in distinct sub-periods from different provincial housing sub- markets in the Netherlands. We observed particularly prior to the crisis, diffusion of temporal house price volatilities from Noord-Holland
Diffusion and Risks of House Prices in the Netherlands
Get PDFThe rate of home-ownership has increased significantly in many countries over the past decades. One motivating factor for this increase has been the creation of wealth through the accumulation of housing equity, which also forms the basic tenet of the asset-based welfare system. In generating the home equity, house price developments play an important role. Generally, house prices show an increasing trend over long time period, however, there are short term negative appreciations that may have inherent risks for the housing equity. Following the 2007-08 Global Financial Crisis (GFC), for example, the collapse of house prices has caused many recent home buyers to run into negative equity. Some housing researchers and experts have suggested that a better understanding of the spatial diffusion mechanisms of house prices will aid resuscitating the housing market after the GFC. Others also advocated adopting insurance schemes to protect the home equity that yields the welfare benefits. Unfortunately, however, little research insight exists on the Dutch house price diffusion process, although there are empirical results for countries such as the UK, US and China, where the contexts differ from the Netherlands. Furthermore, the current existing home-value insurance scheme in the literature is found to be less efficient and eliminates only up to 50% of the house price risks. This dissertation covers important aspects of house price diffusion and risks in the Netherlands. The aim is to better understand the diffusion mechanism and the risks of house prices, while it also contributes to the measurement of these housing risks. More specifically, there are three objectives: first, to discover the diffusion mechanism of house prices in the Netherlands and the pattern particularly from the capital Amsterdam; second, to examine the spatial distribution of the house price risk; and third, to investigate the efficiency of the index-based home-value insurance for reducing the house price risk in the Dutch context.A+BE | Architecture and the Built Environment No 3 (2018)OLD Housing System
Introduction
Get PDFThe rate of home-ownership across Europe and in many countries has increased significantly in recent decades. This is partly because most governments have promoted home-ownership as part of an asset-based welfare system with the notion that home-ownership will generate wealth for households through the accumulation of housing equity. Changes in house prices play an important role in the generation of the housing equity and the wealth inherent in home-ownership. In general, house prices change in cycles of upward and downward trends. Each of these cycles may be driven by different sets of fundamental determinants and by the prevailing conditions in the wider economy. Over the long term, home-owners usually accumulate significant housing equity, yielding welfare benefits. However, even periods of brief house price decline can erode the value of housing equity accrued over several years. Following the 2007-08 Global Financial Crisis (GFC), for example, the severe decline in house prices caused many recent home-owners to run into negative equity. Figures from Statistics Netherlands show that following the GFC, in the Netherlands alone the total wealth in residential properties declined from e738,449 million in 2009 to e721,018 million by the end of 2012. In effect, home-ownership involves significant financial risk, which can adversely affect the balance sheets of households. These risks require a better understanding and proper measurements. However, it is also important to first understand house price dynamics, which significantly affect the process of equity generation. A thorough understanding of house price dynamics is necessary if we are to identify innovative ways of insuring against the risks associated with home-ownership
General conclusions
Get PDFSince the 2007-2008 Global Financial Crisis (GFC), a great deal of research has been conducted in various countries into the dynamics and risks associated with house prices in an attempt to find innovative ways of reducing these risks and resuscitating a depressed housing market. This dissertation contributes to that literature by providing comprehensive analyses of the spatial diffusion and risks associated with house prices in the Netherlands. It also studies the efficiency and loss coverage of home-value insurance in the context of the Dutch housing market and suggests modifications to the index-based insurance scheme that would minimise the residual idiosyncratic risks for home-owners. The dissertation innovatively adopts empirical methods that combine standard statistical analyses with more complex and recent econometric models.
The contributions of the dissertation are presented in five main chapters. Four of these chapters have already been published separately in international journals and one is under review. Chapter 2 provided a general overview of the Dutch housing market and the risks involved in home-ownership. Chapters 3, 4 and 5 were devoted to the diffusion mechanism of house prices in the Netherlands. Chapter 5 also dealt in part with house price risks, while Chapter 6 focused on the house price risks and home-value insurance. Each chapter has provided a detailed conclusion on each aspect of the research questions addressed in this dissertation. This concluding chapter summarises the main findings of the dissertation as a whole. The limitations of the analyses are discussed, together with potential applications for its findings and directions for further research
Home-value insurance and idiosyncratic risks of residential property prices
Get PDFThe recent Global Financial Crisis has reawakened home-owners to the need for protecting their home-equities from possible future house price decline. This paper re-examines the Shiller and Weiss (1999) home-value insurance scheme and proposes a modification that eliminates a large proportion of the idiosyncratic sale price risks of residential properties. Using data between 1995 and 2014 for Amsterdam, the proposed insurance policy shows a higher pay-out efficiency, a higher loss coverage and a greater pay-out probability than the original Shiller and Weiss (1999) scheme. The new home-value insurance policy thus provides better protection for the property sale price risks
Detecting spatial and temporal house price diffusion in the Netherlands: A Bayesian network approach
Get PDFFollowing the 2007-08 Global Financial Crisis, there have 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 Bayesian graphical vector autoregression (BG-VAR). This network approach enables a data driven identification of the most dominant provinces where house price shocks may largely diffuse through the housing market and it is suitable for analysing the complex spatial interactions between house prices. Using temporal house price volatilities for owner-occupied dwellings, the results show evidence of house price diffusion pattern in distinct sub-periods from different provincial housing sub-markets in the Netherlands. We observed particularly prior to the crisis, diffusion of temporal house price volatilities from Noord-Holland
Detecting spatial and temporal house price diffusion in the Netherlands: A Bayesian network approach
No full textFollowing 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.</p
Risks and interrelationships of subdistrict house prices: the case of Amsterdam
Get PDFThis 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.OLD Housing System
Risks in home-ownership: a perspective on the Netherlands
Get PDFPurpose: Risk in home-ownership from mortgage providers’ perspectives within the euro zone has received more attention than individual home owner’s perspectives in the literature following the financial crisis in 2007/2008. The purpose of this paper is to explore the risk factors in home-ownership from the individual household’s perspectives within the owner-occupied housing sector of the Netherlands.
Design/methodology/approach: The paper adopted a broader review of extant literature on the different concepts and views on risk in home-ownership. These concepts are unified into a framework that enhances our understanding of the perceived sophisticated risk within the owner-occupied sector in the Netherlands.
Findings: From the perspective of the home owner, two main types of risks were identified: mortgage default and property price risk. The paper has unearthed a quantum number of factors which underline the above risks. The mortgage default risk factors include the initial amount of mortgage loan taken out, the future housing expenses and the income development of the owner-occupier. Family disintegration is also identified as one of the main causes of mortgage default in the Netherlands. Property price risk is influenced by income, 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
Amsterdam house price ripple effects in The Netherlands
Get PDFPurpose: 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 long-run convergence between the Amsterdam and regional house prices. Using the real house prices for second-hand 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. 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.OLD Housing System
