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.

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.

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 Land price dynamics in a large Australian urban housing market

2014 ◽  
Vol 7 (1) ◽  
pp. 42-60 ◽  
Author(s):  
Greg Costello
Keyword(s):  
Housing Market ◽  
Price Change ◽  
House Price ◽  
Housing Markets ◽  
Urban Housing ◽  
Price Dynamics ◽  
Data Set ◽  
Content Type ◽  
Hedonic Price Analysis ◽  
Spatial Disaggregation

Purpose – Housing is a composite asset comprising land and improved components varying as proportions of total value over space and time. Theory suggests land and improvements (structures) are unique goods responding differently to economic stimuli. This paper aims to test the expectation of different overall house price changes in response to variation in land and improved components. Design/methodology/approach – House price dynamics are decomposed to analyse the influence of land and structure components for the city of Perth, Australia both at aggregate level and for spatially defined housing sub-regions, sample period 1995-2010. Findings – Values of land and improvements on that land evolve differently over time and are significantly influenced by the magnitude of land leverage. The study extends previous research through extensive spatial disaggregation of a larger more detailed data set than previously used in studies of this type confirming significant variation in land leverage ratios, overall price change and growth rates for land and improvements in sub-regional markets defined by spatial criteria. Research limitations/implications – The results suggest an important role for policy development with respect to housing affordability and supply side regulation of land in large urban housing markets. Practical implications – The results suggest important implications for hedonic price analysis of housing markets. The inclusion of land leverage variables in hedonic regression could remove coefficient bias associated with omitted location amenity variables. Originality/value – The paper adapts methodology from previous studies but extends previous literature through detailed analysis of a large Australian housing market (Perth) enabling extensive spatial disaggregation of the sample and providing greater insight to spatial variation of land leverage than in previous studies.

scholarly journals Volume effects in the London housing market

2018 ◽  
Vol 11 (3) ◽  
pp. 586-602 ◽  
Author(s):  
Steve Cook ◽  
Duncan Watson
Keyword(s):  
Housing Market ◽  
House Price ◽  
Housing Markets ◽  
Price Volatility ◽  
Financial Assets ◽  
Asymmetric Adjustment ◽  
Related Factors ◽  
Content Type ◽  
Alternative Housing ◽  
Volume Effects

Purpose This paper aims to extend existing research in relation to both the importance of volume effects within housing markets and the specific behaviour of the London housing market. A detailed borough-level examination is undertaken of the relationships between volume, house prices and house price volatility. Support for alternative housing market theories, the degree of heterogeneity in house price behaviour across boroughs and the extent to which housing displays differing properties to other financial assets are examined. Design/methodology/approach Correlation analyses, causality testing and volatility modelling are undertaken in extended forms which synthesise and extend approaches within the housing, economics and finance literatures. The various modelling and testing techniques are supplemented via the use of alternative variable transformations to evaluate housing market behaviour in detail. Findings Novel findings are provided concerning both volume effects within housing markets generally and the specific properties of London housing market. Evidence concerning bubbles, the volatility-reducing effects of volume, the importance of geographical and price-related factors underlying the relationship between volume and both house price growth and volatility and the presence of asymmetric adjustment in the London housing market are all provided. The extent and nature of the support available for alternative housing market theories are evaluated. Originality/value The volatility-reducing effects of volume within housing markets, along with volume effects and the presence of asymmetric adjustment within the London housing market are examined for the first time. New empirical evidence on the support for alternative housing market theories and the differing empirical characteristics of housing relative to other financial assets are presented.

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.

scholarly journals Speculative housing markets and rent control: insights from nonlinear economic dynamics

2021 ◽  
Author(s):  
Noemi Schmitt ◽  
Frank Westerhoff
Keyword(s):  
Housing Market ◽  
Housing Stock ◽  
House Price ◽  
Housing Markets ◽  
Market Model ◽  
Market Dynamics ◽  
Rent Control ◽  
Forecasting Accuracy ◽  
Expectation Formation ◽  
Rent Level

AbstractWe propose a novel housing market model to explore the effectiveness of rent control. Our model reveals that the expectation formation and learning behavior of boundedly rational homebuyers, switching between extrapolative and regressive expectation rules subject to their past forecasting accuracy, may create endogenous housing market dynamics. We show that policymakers may use rent control to reduce the rent level, although such policies may have undesirable effects on the house price and the housing stock. However, we are also able to prove that well-designed rent control may help policymakers to stabilize housing market dynamics, even without creating housing market distortions.

A multifractal detrended fluctuation analysis of housing market: a role of financial crises in developed economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syed Ali Raza ◽  
Nida Shah ◽  
Muhammad Tahir Suleman ◽  
Md Al Mamun
Keyword(s):  
Financial Crisis ◽  
Housing Market ◽  
Market Efficiency ◽  
House Price ◽  
Fluctuation Analysis ◽  
Content Type ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Long Run ◽  
Before And After

Purpose This study aims to examine the house price fluctuations in G7 countries by using the multifractal detrended fluctuation analysis (MF-DFA) for the years 1970–2019. The study examined the market efficiency between the short-term and long-term in the full sample period, before and after the global financial crisis period. Design/methodology/approach This study uses the MF-DFA to analyze house price fluctuations. Findings The findings confirmed that the housing market series are multifractal. Furthermore, all the markets showed long-term persistence in both the short and long-term. The USA is identified as the most persistent house market in the short run and Japan in the long run. Moreover, in terms of efficiency, Canada is identified as the most efficient house market in the long run and the UK in the short run. Finally, the result of before and after the financial crisis period is consistent with the full sample result. Originality/value The contribution of this study in the literature is fourfold. This is the first study that has examined the house prices efficiency by using the MF-DFA technique given by Kantelhardt et al. (2002). Previously, the house market prices and efficiency has been investigated using generalized Hurst exponent (Liu et al., 2019), Quantile Regression Approach (Chae and Bera, 2019; Tiwari et al., 2019) but no study to the best of the knowledge has been done that has used the MF-DFA technique on the housing market. Second, this is the first study that has focused on the house markets of G7 countries. Third, this study explores the house market efficiency by dividing the market into two periods i.e. before and after the financial crisis. The study strives to investigate if the financial crisis determines the change in the degree of market efficiency or not. Finally, the study gives valuable insights to the investors that will help them in their investment decisions.

Transportation systems’ impacts on the Vilnius housing market

2019 ◽  
Vol 57 (2) ◽  
pp. 418-431 ◽  
Author(s):  
Virgilija Vasiliene-Vasiliauskiene ◽  
Aidas Vasilis Vasiliauskas ◽  
Rišard Golembovskij ◽  
Ieva Meidute-Kavaliauskiene ◽  
Edmundas Kazimieras Zavadskas ◽  
...  
Keyword(s):  
Housing Market ◽  
Housing Markets ◽  
Transportation System ◽  
Transportation Systems ◽  
Sustainable Urban Development ◽  
Quantitative Methodology ◽  
Analytic Hierarchy ◽  
Content Type ◽  
System Factors ◽  
Hierarchy Process

Purpose The purpose of this paper is to develop a better understanding of how transportation system factors affect city housing markets. The goal was to show that identifying these factors alone is not enough without also examining their effects and variations according to the housing location. Design/methodology/approach Transportation system factors were identified by conducting a thorough literature review. The factors’ relevance was tested using a quantitative methodology and a sample of 317 Vilnius residents. This city was next divided into three zones, and data collected from 18 real estate experts was subjected to qualitative analysis. The analytic hierarchy process was then applied to identify transportation system factors’ level of impact and dynamics by the housing location. Findings The results show that the factors affect the housing market in question but that these effects vary by the housing location and the most critical factors differ for each city zone. Research limitations/implications Only data on Vilnius were used. Further research is needed to compare transportation factors’ dynamics in multiple cities. Practical implications Priorities in transportation system improvements should be assessed to facilitate sustainable urban development and enhance the residents’ quality of life. Housing market regulations can only be successful if investment in transportation systems is allocated purposefully and coherently. Originality/value This research went beyond identifying transportation system factors by employing a broad, systematic approach to clarifying potential options for regulating housing markets through transportation system projects.

Rent or buy, what are the odds? Analysing the price-to-rent ratio for housing types within the Northern Ireland housing market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniel Lo ◽  
Michael James McCord ◽  
John McCord ◽  
Peadar Thomas Davis ◽  
Martin Haran
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Main Property ◽  
Property Market ◽  
Important Indicator ◽  
Content Type ◽  
Rental Market ◽  
Price Series ◽  
The Relationship

Purpose The price-to-rent ratio is often regarded as an important indicator for measuring housing market imbalance and inefficiency. A central question is the extent to which house prices and rents form part of the same market and thus whether they respond similarly to parallel stimulus. If they are close proxies dynamically, then this provides valuable market intelligence, particularly where causal relationships are evident. Therefore, this paper aims to examine the relationship between market and rental pricing to uncover the price switching dynamics of residential real estate property types and whether the deviation between market rents and prices are integrated over both the long- and short-term. Design/methodology/approach This paper uses cointegration, Wald exogeneity tests and Granger causality models to determine the existence, if any, of cointegration and lead-lag relationships between prices and rents within the Belfast property market, as well as the price-to-rent ratios amongst its five main property sub-markets over the time period M4, 2014 to M12 2018. Findings The findings provide some novel insights in relation to the pricing dynamics within Belfast. Housing and rental prices are cointegrated suggesting that they tend to move in tandem in the long run. It is further evident that in the short-run, the price series Granger-causes that of rents inferring that sales price information unidirectionally diffuse to the rental market. Further, the findings on price-to-rent ratios reveal that the detached sector appears to Granger-cause those of other property types except apartments in both the short- and long-term, suggesting possible spill-over of pricing signals from the top-end to the lower strata of the market. Originality/value The importance of understanding the relationship between house prices and rental market performance has gathered momentum. Although the house price-rent ratio is widely used as an indicator of over and undervaluation in the housing market, surprisingly little is known about the theoretical relationship between the price-rent ratio across property types and their respective inter-relationships.

A look into German housing markets: A bubble call?

2018 ◽  
Vol 21 (4) ◽  
pp. 289-301
Author(s):  
Jan R. Kim ◽  
Gieyoung Lim
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Housing Markets ◽  
Present Value ◽  
Present Value Model ◽  
Price Bubbles ◽  
Steep Rise ◽  
Value Model ◽  
German Housing Market

The steep rise in German house prices in recent years raises the question of whether a speculative bubble has already emerged. Using a modified present-value model, we estimate the size of speculative house price bubbles in the German housing market. We do not find evidence for positive bubble accumulation in recent years, and interpret the current bullish run as reflecting the correction of house prices that have been undervalued for more than 10 years. With house prices close to their fair values as of 2018:Q1, our answer to the question is, ‘Not yet, but it is likely soon’.

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