scholarly journals Amsterdam house price ripple effects in The Netherlands

2017 ◽  
Vol 10 (3) ◽  
pp. 331-345 ◽  
Author(s):  
Alfred Larm Teye ◽  
Michel Knoppel ◽  
Jan de Haan ◽  
Marja G. Elsinga
Keyword(s):  
The Netherlands ◽  
Granger Causality ◽  
House Prices ◽  
House Price ◽  
Housing Markets ◽  
Wealth Effects ◽  
Ripple Effect ◽  
Content Type ◽  
Long Run ◽  
Lag Effect

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 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.

House prices and unemployment: an empirical analysis of causality

2019 ◽  
Vol 12 (1) ◽  
pp. 148-164 ◽  
Author(s):  
Manuchehr Irandoust
Keyword(s):  
Granger Causality ◽  
Financial Stability ◽  
Structural Breaks ◽  
House Prices ◽  
House Price ◽  
Cross Sectional ◽  
Content Type ◽  
Unemployment Rates ◽  
Long Run ◽  
Panel Granger Causality

Purpose This paper aims to examine whether there exists a long-run causal relationship between house prices and unemployment rates for eight major European countries. Design/methodology/approach The bootstrap panel Granger causality approach that accounts for cross-sectional dependence, slope heterogeneity and structural breaks is used to detect the direction of causality. Findings The empirical findings for the overall panel support the presence of unidirectional causality running from house prices to unemployment. Practical implications The findings are not only important for households but also for policymakers concerned with economic and financial stability. Originality/value There are only a limited number of studies that have investigated the direct link between house prices and employment or unemployment. Given the increased importance of labor market variables, particularly the choice of the unemployment rate as a key indicator in designing forward guidance and the increased financial stability concerns regarding house price dynamics, it is important to better understand the causal linkages between house prices and unemployment rates. To the best of the author’s knowledge, this paper is the first to apply the bootstrap panel Granger causality approach to examine the relationship between house prices and unemployment rates.

Housing market networks in China's major cities: a conditional causality approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lu Yang ◽  
Nannan Yuan ◽  
Shichao Hu
Keyword(s):  
Housing Market ◽  
Granger Causality ◽  
House Price ◽  
Housing Markets ◽  
Content Type ◽  
Scale Free ◽  
Second Tier ◽  
The Difference ◽  
Secondary Housing Market ◽  
Market Networks

PurposeTo explore the state of this conditional Granger causality when other cities are not factors, we investigate housing market networks in China's major cities by using a combination of conditional Granger causality and network analysis.Design/methodology/approachAlthough housing market networks have been well discussed for different countries, the question of housing market networks in China's major cities based on the conditional causality perspective has yet to be answered.FindingsWe discover that second-tier cities are more influential than first-tier cities. Although the connectivity of the primary housing market is more complex than the diversified connectivity observed in the secondary housing market, both markets are scale-free networks that exhibit high stability. Moreover, we reveal that geographic conditions and economic development jointly determine the housing market's modular hierarchical structure. Our results provide meaningful information for both Chinese policymakers and investors.Originality/valueBy excluding the influence of other cities, our conditional Granger causality identifies the true casual relation between cities' housing markets. Moreover, it is the first paper to consider the primary housing market and secondary housing market separately. Specifically, Chinese prefer new house rather than second-hand house from both speculative and self-housing. Generally speaking, the new house price is lower than the second-hand house price since the new house is off-plan property. Therefore, understanding the difference between primary and secondary housing markets will provide useful information for both policymakers and speculators.

scholarly journals Club convergence of house prices: Evidence from China’s ten key cities

2015 ◽  
Vol 29 (24) ◽  
pp. 1550181 ◽  
Author(s):  
Hao Meng ◽  
Wen-Jie Xie ◽  
Wei-Xing Zhou
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Economic Recession ◽  
Housing Markets ◽  
Extensive Study ◽  
Ripple Effect ◽  
Chinese Stock Market ◽  
Price Growth ◽  
Chinese Housing Market

The latest global financial tsunami and its follow-up global economic recession has uncovered the crucial impact of housing markets on financial and economic systems. The Chinese stock market experienced a marked fall during the global financial tsunami and China’s economy has also slowed down by about 2%–3% when measured in GDP. Nevertheless, the housing markets in diverse Chinese cities seemed to continue the almost nonstop mania for more than 10 years. However, the structure and dynamics of the Chinese housing market are less studied. Here, we perform an extensive study of the Chinese housing market by analyzing 10 representative key cities based on both linear and nonlinear econophysical and econometric methods. We identify a common collective driving force which accounts for 96.5% of the house price growth, indicating very high systemic risk in the Chinese housing market. The 10 key cities can be categorized into clubs and the house prices of the cities in the same club exhibit an evident convergence. These findings from different methods are basically consistent with each other. The identified city clubs are also consistent with the conventional classification of city tiers. The house prices of the first-tier cities grow the fastest and those of the third- and fourth-tier cities rise the slowest, which illustrates the possible presence of a ripple effect in the diffusion of house prices among different cities.

scholarly journals A dynamic model for housing price spillovers with an evidence from the US and the UK markets

2018 ◽  
Vol 2 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Alper Ozun ◽  
Hasan Murat Ertugrul ◽  
Yener Coskun
Keyword(s):  
New York ◽  
Real Estate ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Housing Markets ◽  
Content Type ◽  
Real Estate Markets ◽  
Country Level ◽  
The Us

Purpose The purpose of this paper is to introduce an empirical model for house price spillovers between real estate markets. The model is presented by using data from the US-UK and London-New York housing markets over a period of 1975Q1-2016Q1 by employing both static and dynamic methodologies. Design/methodology/approach The research analyzes long-run static and dynamic spillover elasticity coefficients by employing three methods, namely, autoregressive distributed lag, the fully modified ordinary least square and dynamic ordinary least squares estimator under a Kalman filter approach. The empirical method also investigates dynamic correlation between the house prices by employing the dynamic control correlation method. Findings The paper shows how a dynamic spillover pricing analysis can be applied between real estate markets. On the empirical side, the results show that country-level causality in housing prices is running from the USA to UK, whereas city-level causality is running from London to New York. The model outcomes suggest that real estate portfolios involving US and UK assets require a dynamic risk management approach. Research limitations/implications One of the findings is that the dynamic conditional correlation between the US and the UK housing prices is broken during the crisis period. The paper does not discuss the reasons for that break, which requires further empirical tests by applying Markov switching regime shifts. The timing of the causality between the house prices is not empirically tested. It can be examined empirically by applying methods such as wavelets. Practical implications The authors observed a unidirectional causality from London to New York house prices, which is opposite to the aggregate country-level causality direction. This supports London’s specific power in the real estate markets. London has a leading role in the global urban economies residential housing markets and the behavior of its housing prices has a statistically significant causality impact on the house prices of New York City. Social implications The house price co-integration observed in this research at both country and city levels should be interpreted as a continuity of real estate and financial integration in practice. Originality/value The paper is the first research which applies a dynamic spillover analysis to examine the causality between housing prices in real estate markets. It also provides a long-term empirical evidence for a dynamic causal relationship for the global housing markets.

Long-run drivers and integration in interprovincial Canadian housing price relations

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vijay Kumar Vishwakarma
Keyword(s):  
Housing Market ◽  
Granger Causality ◽  
Global Financial Crisis ◽  
Housing Prices ◽  
Housing Price ◽  
Housing Markets ◽  
Content Type ◽  
Stochastic Trend ◽  
Long Run ◽  
Long Run Equilibrium

Purpose 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). Design/methodology/approach 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. Findings 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. Practical implications 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. Originality/value 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.

Housing markets’ linkage between China and Taiwan

2019 ◽  
Vol 12 (5) ◽  
pp. 826-848 ◽  
Author(s):  
Mei-Se Chien ◽  
Neng-Huei Lee ◽  
Chih-Yang Cheng
Keyword(s):  
Economic Integration ◽  
House Prices ◽  
Housing Prices ◽  
Housing Markets ◽  
Wealth Effects ◽  
Time Varying ◽  
Consumer Expenditure ◽  
Content Type ◽  
Cross Border ◽  
Cointegration Tests

Purpose This paper aims to examine the linkage of regional housing markets between Taiwan and China as increasing economic integration. Design/methodology/approach Two time-varying estimations of cointegration tests, Gregory and Hansen (1996) cointegration test with structural break and the recursive coefficients of cointegration (Hansen and Johansen, 1993) are applied to trace the possible dynamic linkage of cross-border regional housing prices between Taiwan and China. Findings First, the estimating results of the long-run relationships show that increasing housing prices in Beijing and Shanghai decrease Taipei’s house prices, while Shenzhen and Chengdu have converse effects. The technologies’ levels of Taiwanese industries surrounding the cities in China will affect the direction of the linkage of regional housing prices between the two economies. Second, in light of causalities of these five housing prices’ changes, Beijing and Shanghai lead Taipei and Shanghai leads Chengdu, which, in turn, leads Shenzhen. Finally, the results of time-varying cointegration tests show that some critical economic and political incidents changed the linkages of housing prices between Taipei and the four cities in China. Originality/value Although some empirical works examined the linkages between cross-border house prices in Europe and the USA, study has looked at the linkages of cross-border housing prices between Taiwan and China. This is an interesting topic insofar as house price integration has implications for wealth effects that feed into consumer expenditure in both Taiwan and China. The empirical evidence overall displays the existence of the integration of regional housing markets between Taiwan and China. For the longer-term future, increasing economic integration between China and other Asia countries will result in greater and more diversified cross-border housing markets and pools of investors.

Heterogeneous housing markets: structural implications for pricing and risk

2014 ◽  
Vol 7 (3) ◽  
pp. 383-396 ◽  
Author(s):  
Trond A. Borgersen
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Housing Markets ◽  
Value Added ◽  
Price Risk ◽  
Content Type ◽  
Price Response ◽  
Market Framework ◽  
House Price Risk

Purpose – The purpose of this paper is to compare the structure of risk and the structure of pricing in housing markets where the interaction between segments is taken into account with the structures that come about in a housing market approach that ignores this interplay. Knowing how most empirical assessments of whether housing markets are in or out of equilibrium is related to macroeconomic variables and is ignoring the interplay between segments our aim is to highlight the extent to which a homogeneous market framework underestimates pricing and risk in real housing markets. Design/methodology/approach – Framed in terms of a linearized housing market with two segments, the author derives expressions for house prices and house price risk in three scenarios. The author compares the structure of pricing and the structure of risk in a homogeneous housing market with those of two distinct heterogeneous housing markets where segments are linked as well analyzing as how prices and risk responds to shocks. Findings – The author derives expressions for market segment prices and for the house price index in three distinct housing market scenarios and shows how heterogeneous housing market frameworks produce both expressions for house prices and for house price risk, as well as a response in both risk and prices to shocks to demand, that deviate from those of a homogeneous housing market framework. While significantly underestimating house price risk a homogeneous framework might also be taken by surprise of the price response accompanying shocks to demand. Originality/value – The authors' simplistic expressions for house prices and house price risk provides a framework for bringing two distinct theoretical housing market camps onto the same playing field. The approach shows the value added of taking the interplay between market segments into account when analyzing housing market developments.

scholarly journals Understanding the short- and long-run relationship between vacant allotment and established house prices

2014 ◽  
Vol 10 (2) ◽  
pp. 200-217 ◽  
Author(s):  
Peter Rossini ◽  
Valerie Kupke
Keyword(s):  
Price Index ◽  
House Prices ◽  
House Price ◽  
Content Type ◽  
Land Prices ◽  
Long Run ◽  
Short Run ◽  
A Site ◽  
Urban Land Market

Purpose – The purpose of this paper is to address a key issue fundamental to the operation of land and housing markets, that is, the relationship between land and house prices. The study identifies possible causation between established house and vacant allotment prices using the metropolitan area of Adelaide, Australia as a case study. Design/methodology/approach – A key outcome of the study is the construction of a Site Adjusted Land Price Index against which a Quality Adjusted House Price Index is compared. Findings – The results show that there is a lagged effect of land prices on house prices and that this is significant at an interval of eight lag periods. The results also imply that the lead lag relationship between established house and vacant allotment prices is not unidirectional. This suggests that, while a change in house prices leads to a change in land prices in the short-run, the long-run position is for increasing land prices to lead to a delayed increase in house prices. Research limitations/implications – Rising house prices do not simply and solely reflect a shortage of land. There are suggested effects both immediate from house to land and delayed from land to house, particularly in a rising market. Originality/value – The lead lag relationships of both indexes are tested using Granger causality estimates to assess whether theoretical Ricardian concepts still hold in a modern urban land market.

Separating owner-occupier and investor demands for housing in the Australian states

2019 ◽  
Vol 37 (2) ◽  
pp. 215-232 ◽  
Author(s):  
Le Ma ◽  
Richard Reed ◽  
Jian Liang
Keyword(s):  
Home Ownership ◽  
House Prices ◽  
Supply And Demand ◽  
Housing Markets ◽  
Housing Affordability ◽  
Housing Supply ◽  
Content Type ◽  
Western Countries ◽  
Long Run

PurposeThere has been declining home ownership and increased acceptance of long-term renting in many western countries including Australia; this has created a problem when examining housing markets as there are dual demand and include both owner-occupiers and investors. The purpose of this paper is to examine the long-run relationship between house prices, housing supply and demand, and to estimate the effects of the two types of demand (i.e. owner-occupier and investor) on house prices.Design/methodology/approachThe econometric techniques for cointegration with vector error correction models are used to specify the proposed models, where the housing markets in the Australian states and territories illustrate the models.FindingsThe results highlight the regional long-run equilibrium and associated patterns in house prices, the level of new housing supply, owner-occupier demand for housing and investor demand for housing. Different types of markets were identified.Practical implicationsThe findings suggest that policies that depress the investment demand can effectively prevent the housing bubble from further building up in the Australian states. The empirical findings shed light in the strategy of maintaining levels of housing affordability in regions where owner-occupiers have been priced out of the housing market.Originality/valueThere has been declining home ownership and increased acceptance of long-term renting in many western countries including Australia; this has created a problem when examining housing markets as there are dual demand and include both owner-occupiers and investors. This research has given to the relationship between supply and dual demand, which includes owner-occupation and investment, for housing and the influence on house prices.

scholarly journals The connectedness of house price affordability (HPA) and rental price affordability (RPA) measures

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Graham Squires ◽  
Don Webber ◽  
Hai Hong Trinh ◽  
Arshad Javed
Keyword(s):  
New Zealand ◽  
House Prices ◽  
House Price ◽  
Empirical Work ◽  
Ordinary Least Squares ◽  
Least Square ◽  
Content Type ◽  
Lag Effects ◽  
Long Run ◽  
Lag Variables

Purpose The purpose of this paper is to examine the relationship between house price affordability (HPA) and rental price affordability (RPA) in New Zealand. The cointegration of HPA and RPA is of particular focus given rising house prices and rising rents. Design/methodology/approach The study examines the lead-lad correlation between HPA and RPA. The method uses a generalised least square technique and the development of an ordinary least squares model. Findings The study shows that there is an existence of cointegration and unidirectional statistical causality effects between HPA and RPA across 11 regions in New Zealand. Furthermore, Auckland, Wellington and Canterbury are the three regions in which the results detect the most extreme effects amongst HPA and RPA compared to other places in the country. Extended empirical work shows interesting results that there are lead-lag effects of HPA and RPA on each other and on mortgage rates at the national scale. These effects are consistent for both methods but are changed at individual lead-lag variables and amongst different regions. Originality/value The study empirically provides useful insight for both academia and practitioners. Particularly in examining the long-run effects, cointegration and forecasting of the volatile interactions between HPA and RPA.

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