Structural Breaks and the Convergence of Regional House Prices

Chien, Mei-Se

doi:10.1007/s11146-008-9138-y

Cited by 67 publications

(55 citation statements)

References 41 publications

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“…En general, los trabajos sobre convergencia han estado guiados por el uso de metodologías para el análisis de series de tiempo (ver Alexander & Barrow, 1994;Berg, 2002;Chien, 2008;Cook, 2005;Ho et al, 2007;Meen, 1999), y en los últimos años por aquellas desarrolladas para estructuras de panel (Zhang & Morley, 2014;Zhang & Liu, 2009). Estas últimas han adquirido relevancia debido a la creciente disponibilidad de datos temporales para diferentes niveles geográficos.…”

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Regional Relationships in New Housing Prices in Colombia

2015

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Regional Relationships in New Housing Prices in Colombia

2015

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“…These results are available upon request from the authors. 4 Studies such as Chien (2010) and Canarella et al, (2010) have applied endogenous-two-structural-break test developed by Lumsdaine and Papell (1997) and Lee and Straizicich (2003) given that their data plots suggested two breaks. 5 Standard economic theory and intuition suggest that different regional house prices should not move together, since house prices depend mostly on local housing market supply and demand factors, which, in turn, tend to differ substantially between regions due to differences in regional economic and demographic environments.…”

Section: Literature Reviewmentioning

confidence: 99%

‘Ripple’ Effects in South African House Prices

Balcılar¹,

Beyene

Gupta³

et al. 2012

Urban Studies

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This paper analyzes the so-called "ripple" effect of house prices in large-, medium-and smallsized houses of five major metropolitan areas of South Africa, namely, Cape Town, Durban Unicity, Greater Johannesburg, Port Elizabeth/Uitenhage and Pretoria, based on available quarterly data covering the period of 1966:Q1 to 2010:Q1. Following the extant literature, we contextualize the issue as a unit root problem, with one expecting the ratios of metropolitan house price to national house price to exhibit stationarity to an underlying trend value, if there is diffusion in house prices. Using Bayesian and non-linear unit root tests, besides the standard linear tests of stationarity with and without structural break, we find overwhelmingly support of the existence of robust ripple effects. Also factor analysis conducted suggested that the ripple effects originate in Cape Town for the large housing segment, and in Durban for the mediumand small-sized houses.

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“…Using the threshold regression method with an asymmetric adjustment process about the stationary attractor, Cook (2003) re-examines the stationarity of regional house price ratios and supports that stationarity exists in a number of regions of the UK. Hereafter, Chien (2010) and Canarella et al (2012) use the Lagrange multiplier (LM) unit root tests with one and two structural breaks of Strazicich (2003, 2004) to examine the existence of ripple effects. Chien (2010) is unable to reject the existence of the ripple effect in regional house prices in Taiwan, while the empirical results of Canarella et al (2012) show that the tests of the 'ripple effect' have conflicting evidence in the U.S. (Seslen, 2004).…”

Section: Introductionmentioning

confidence: 99%

“…Hereafter, Chien (2010) and Canarella et al (2012) use the Lagrange multiplier (LM) unit root tests with one and two structural breaks of Strazicich (2003, 2004) to examine the existence of ripple effects. Chien (2010) is unable to reject the existence of the ripple effect in regional house prices in Taiwan, while the empirical results of Canarella et al (2012) show that the tests of the 'ripple effect' have conflicting evidence in the U.S. (Seslen, 2004). What causes this?…”

Section: Introductionmentioning

confidence: 99%

“…The above empirical literature has examined the non-linearity of house markets, with some using unit root tests of MTAR or employing structural breaks to explore the ripple effects of regional house prices (Cook, 2003;Chien, 2010;Canarella et al, 2012), and some applying threshold cointegration and asymmetric ECM to examine the non-linearity of house prices (Abelson et al 2005;Posedel and Vizek, 2010). This current paper employs the smooth transition regression (STR, Chan and Tong, 1986;Teräsvirta and Anderson, 1992;Granger and Teräsvirta, 1993;Teräsvirta, 1994) model to investigate non-linear ripple effects among regional house prices in Taiwan.…”

Section: Introductionmentioning

confidence: 99%

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The Non-linear Ripple Effect of Housing Prices in Taiwan: A Smooth Transition Regressive Model

Chien¹

2013

Proceedings of the 20th Annual European Real Estate Society Conference - Vienna, Austria

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Different from past research of regional house prices, this paper employs the smooth transition regression (STR) model to investigate the ripple effects among regional house prices in Taiwan. The aim of this paper is to test whether a smooth transition regression model, which is capable of capturing this non-linear behaviour, shows a better characterisation of regional house prices than a linear model. Our main findings are as follows. First, the results reveal that there is a mixture of linear and smooth non-linear ripple effects in Taiwan's regional house prices. If there is enough time to adjust, then the non-linear behavior in house prices will exist, causing a non-linear ripple effect for the regional house prices. Second, a large portion of the variance in Taiwan's overall house price changes is associated with Taipei's house price changes, and Kaohsiung's house price changes do not effectively impact Taiwan's overall house price changes. Third, strong evidence shows that the STR models capture the smooth non-linear ripple effects of regional house prices in Taipei and Taichung, and several features identify the superiority of the non-linear estimation. When compared with Taichung, there is a faster speed of transition between the regimes in Taipei. Fourth and finally, the estimated transition parameter value, revealing the halfway point between two regimes, is lower in Taipei and implies that a change in Taipei's house prices can more easily cause a non-linear "ripple out" change in Taiwan's overall house prices.

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Structural Breaks and the Convergence of Regional House Prices

Abstract: Regional house prices, Ripple effect, Structural break, R11, R21,

Cited by 67 publications

References 41 publications

Regional Relationships in New Housing Prices in Colombia

Regional Relationships in New Housing Prices in Colombia

‘Ripple’ Effects in South African House Prices

The Non-linear Ripple Effect of Housing Prices in Taiwan: A Smooth Transition Regressive Model

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