Is There Long-run Convergence among Regional House Prices in the UK?

Holmes, Mark J.; Grimes, Arthur

doi:10.1177/0042098008091489

Cited by 191 publications

(149 citation statements)

References 29 publications

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“…In response, other scholars later used more advanced stationarity test procedures based on his empirical framework to study the ripple effect. For instance, the threshold and momentum threshold autoregressive test procedures were adopted by Cook (2003), while Holmes and Grimes (2008) combined unit root test and principal component analysis to examine the ripple effect for the UK. Canarella et al (2012), also studied the house price ripple effect in the USA by combining the generalised least squares version of the ADF with non-linear unit root tests and other procedures that control for structure breaks.…”

Section: The Empirical Literaturementioning

confidence: 99%

Amsterdam house price ripple effects in The Netherlands

Teye

Knoppel

Haan

et al. 2017

JERER

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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.

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Section: The Empirical Literaturementioning

confidence: 99%

Amsterdam house price ripple effects in The Netherlands

Teye

Knoppel

Haan

et al. 2017

JERER

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“…Long-run convergent property markets equilibrate and remain integrated over a long period of time (Holmes and Grimes, 2008;Cook, 2005;Cotter et al, 2011). Temporal house price diffusion is also sometimes known in the literature as ripple or spillover effect (see Meen, 1999).…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal House Price Diffusion in the Netherlands: A Bayesian Network Approach

Teye¹,

Ahelegbey²

2017

24th Annual European Real Estate Society Conference

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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.JEL classification: C11; C15; C32; C52; R20; R32

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“…Pesaran (2009) supports that the effects of a shock decay more slowly along the geographical dimension as compared to the decay along the time dimension. Moreover, Holmes and Grimes (2008) employ co-integration techniques and argue that all UK regional house prices are driven by a single common stochastic trend and that London exhibits the highest degree of persistence. Finally, Holmes et al (2011), using a pair-wise approach and unit root tests, is investigating regional house price convergence in the US.…”

Section: Introductionmentioning

confidence: 99%

Linear and nonlinear causality in the UK housing market: a regional approach

Kyriazakou¹,

Panagiotidis

2014

Econom. bus. letters

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We examine the causal relationship between 12 UK regional house prices. Our data span from 1983:Q1 to 2012:Q4. The causal linkages both for the first differences and the levels are examined via Granger causality. The former allows us to examine short-run predictability while the latter the long-run. We relax the assumption of linearity and examine nonlinear pair-wise causality following Diks and Panchenko (2006) both for the levels and the first differences. We find that long-run causality among the regions is mainly linear while in the short-run is nonlinear. London's effect on the other regions is found to be mainly nonlinear in the short-run.

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Is There Long-run Convergence among Regional House Prices in the UK?

Cited by 191 publications

References 29 publications

Amsterdam house price ripple effects in The Netherlands

Amsterdam house price ripple effects in The Netherlands

Spatial and Temporal House Price Diffusion in the Netherlands: A Bayesian Network Approach

Linear and nonlinear causality in the UK housing market: a regional approach

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