Is housing the business cycle? Evidence from US cities

Ghent, Andra C.; Owyang, Michael T.

doi:10.1016/j.jue.2009.11.001

Cited by 102 publications

(67 citation statements)

References 39 publications

(33 reference statements)

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“…However, Flavin and Nakagawa (2008) document that investing in larger houses does not reduce risk, while Kallberg et al (1996) show that smaller property offers impactful diversification benefits for investment portfolios with high return aspirations. On the other hand, Cannon et al (2006) explain housing returns by volatility, price level and stock-market risk, and Ghent and Owyang (2010) investigate supply and demand to explain movements in the housing market.…”

Section: Illustrationmentioning

confidence: 99%

Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency, Arbitrage Opportunity, and Anomaly

2017

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Both stochastic dominance and Omegaratio can be used to examine whether the market is efficient, whether there is any arbitrage opportunity in the market and whether there is any anomaly in the market. In this paper, we first study the relationship between stochastic dominance and the Omega ratio. We find that second-order stochastic dominance (SD) and/or second-order risk-seeking SD (RSD) alone for any two prospects is not sufficient to imply Omega ratio dominance insofar that the Omega ratio of one asset is always greater than that of the other one. We extend the theory of risk measures by proving that the preference of second-order SD implies the preference of the corresponding Omega ratios only when the return threshold is less than the mean of the higher return asset. On the other hand, the preference of the second-order RSD implies the preference of the corresponding Omega ratios only when the return threshold is larger than the mean of the smaller return asset. Nonetheless, first-order SD does imply Omega ratio dominance. Thereafter, we apply the theory developed in this paper to examine the relationship between property size and property investment in the Hong Kong real estate market. We conclude that the Hong Kong real estate market is not efficient and there are expected arbitrage opportunities and anomalies in the Hong Kong real estate market. Our findings are useful for investors and policy makers in real estate.

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Section: Illustrationmentioning

confidence: 99%

Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency, Arbitrage Opportunity, and Anomaly

2017

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“…Besides this, there exists a couple of other studies that have looked into the effect of real house prices on per capita economic growth at the provincial-level in South Africa using 1 See for instance, Leamer (2007), Fisher (2007), (Silos, 2007), Goodhart and Hofmann (2008), , Álvarez et al, (2010), Bulligan (2010), Bandt et al, (2010), Ferrara and Koopman (2010), , Ferrara and Vigna (2010), Ghent and Owyang (2010), Iacoviello (2010), Iacoviello and Neri (2010), Iacoviello and Pavan (forthcoming), Kiyotaki et al, (2011), Cinquegrana (2012, Kydland et al, (2012),. Note, however, there also exists a few studies, such as: Benhabib et al (1991), Greenwood and Hercowitz (1991), McGrattan, et al, (1997), Gomme et al (2001), Davis and Heathcote (2005), Iacoviello (2002Iacoviello ( , 2005 which had also emphasized the role of housing on business cycle way before the recent financial crisis.…”

Section: Introductionmentioning

confidence: 99%

Housing and the business cycle in South Africa

Aye

Balcılar

Bosch

et al. 2014

Journal of Policy Modeling

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This paper examines the housing-output growth nexus in South Africa by accounting for the time variation in the causal link with a bootstrapped rolling Granger non-causality test. We use quarterly data on real gross domestic product, real house prices, real gross fixed capital formation and number of building plans passed. Our data span 1971Q2-2012Q2. Using full sample bootstrap Granger causality tests, we find a uni-directional causality from output to number of building plans passed; a uni-directional causality from real house price to output and a bi-directional causal link between residential investment and output. However, using parameter stability tests, we show that estimated VARs are unstable, thus full-sample Granger causality inference may be invalid. Hence, we use a bootstrap rolling window estimation to evaluate Granger causality between the housing variables and the growth rate.In general, we find that the causality from housing to output and, vice versa, differ across different sample periods due to structural changes. Specifically speaking, house price is found to have the strongest causal relationship with output compared to residential investment and number of building plans passed, with real house price showing predictive ability in all but one downward phase of the business cycle during this period.

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“…A number of papers (Green 1997, Iacoviello 2005, Case et al 2005, Leamer 2007, Iacoviello and Neri 2008, Vargas-Silva 2008a, Ghent 2009, Ghent and Owyang 2009 show a strong link between the housing market and economic activity in the US. Also as indicated by Vargas-Silva (2008a), a large drop in housing starts tend to precede a recession.…”

Section: Literature Reviewmentioning

confidence: 99%

Monetary Policy and Housing Sector Dynamics in a Large-Scale Bayesian Vector Autoregressive Model / Pinigų Politika Ir Būsto Sektoriaus Dinamika Taikant Plataus Masto Bajeso Vektorinį Autoregresinį Modelį

Gupta

Jurgilas²,

Kabundi

et al. 2012

International Journal of Strategic Property Management

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Our paper considers the channel whereby monetary policy, a federal funds rate shock, affects the dynamics of the US housing sector. The analysis uses impulse response functions obtained from a large-scale Bayesian vector autoregressive model that incorporates 143 monthly macroeconomic variables over the period of 1986:01 to 2003:12, including 21 variables relating to the housing sector at the national and four Census regions. We find at the national level that housing starts, housing permits, and housing sales fall in response to the tightening of monetary policy. Housing sales react more quickly and sharply than starts and permits and exhibit more duration. Housing prices show the weakest response to the monetary policy shock. At the regional level, we conclude that the housing sector in the south drives the national findings in the sense that the response patterns in the South most closely match the response patterns in the nation as a whole. The West's responses differs the most from the other regions, especially for the impulse responses of housing starts and permits. Santrauka Straipsnyje nagrinėjama, kokiais kanalais pinigų politika (sukrėtimai dėl federalinių fondų palūkanų normos) veikia JAV būsto sektoriaus dinamiką. Analizei naudojamos reakcijos į impulsus funkcijos, gautos iš plataus masto Bajeso vektorinio autoregresinio modelio, kuris apima laikotarpį nuo 1986 m. sausio mėn. iki 2003 m. gruodžio mėn. ir 143 mėnesinius makroekonominius kintamuosius, įskaitant 21 su būsto sektoriumi susijusį kintamąjį nacionaliniu mastu pagal keturis statistinius regionus (angl. Census regions). Nustatyta, kad, nacionaliniu lygmeniu griežtėjat pinigų politikai, statoma mažiau naujų būstų, išduodama mažiau leidimų gyvenamajai statybai ir parduodama mažiau būstų. Prekybos būstais sektorius reaguoja sparčiau ir aštriau nei naujų statybų ir leidimų sektorius, o reakcija trunka ilgiau. Nustatyta, kad būstų kainos į pinigų politikos sukrėtimus reaguoja menkiausiai. Daroma išvada, kad regioniniu lygmeniu Pietų regiono būstų sektorius labiausiai prisideda prie nacionalinių išvadų tuo požiūriu, jog reakcijos pobūdis Pietuose panašiausias į bendrą nacionalinį reakcijos pobūdį. Vakarų reakcija nuo kitų regionų skiriasi labiausiai, ypač kalbant apie reakcijas į impulsus, susijusias su statomais būstais ir statybų leidimais.

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Is housing the business cycle? Evidence from US cities

Cited by 102 publications

References 39 publications

Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency, Arbitrage Opportunity, and Anomaly

Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency, Arbitrage Opportunity, and Anomaly

Housing and the business cycle in South Africa

Monetary Policy and Housing Sector Dynamics in a Large-Scale Bayesian Vector Autoregressive Model / Pinigų Politika Ir Būsto Sektoriaus Dinamika Taikant Plataus Masto Bajeso Vektorinį Autoregresinį Modelį

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