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

Abstract

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.

Determinants of foreign and domestic non-listed real estate fund flows in India

“…The ARDL has been used by various researchers in real estate for studying housing prices (Arestis et al , 2017; Teye et al , 2017; Ozun et al , 2018); assessing housing related taxation receipts (Smyth and McQuinn, 2016); identifying macro drivers of housing affordability (Worthington and Higgs, 2013); determinants of mortgage defaults (Ngene et al , 2016); studying linkages (volatility spillover effects) between various markets (Liow, 2014; Liow and Schindler, 2017); studying the relationship between residential property and the stock market (Lee, 2017); comparing real estate with other asset classes like bonds and shares (Szumilo et al , 2018); modeling office rents of various markets to understand the intra-market dependence and speed of adjustment toward long-run equilibrium (Mouzakis and Richards, 2007); studying the rental rate for pricing Islamic mortgage rates (Mohd Yusof, Bahlous and Haniffa, 2016) and forecasting real estate pricing (An de Meulen, Micheli and Schmidt, 2014).…”

Forward-looking financial risk management and the housing market in the United Kingdom: is there a role for sentiment indicators?

“…Therefore, it should be no surprise that UK house prices, in general, seem to have risen. Moreover, Ozun, Ertugrul and Coskun (2018) have noted that London has a leading role in the global urban economies residential housing markets, and that the behavior of its housing prices impacts the house prices in other globally important cities (even in New York City). In this context Ozun, Ertugrul and Coskun (2018) have stressed that real estate assets in New York City and London are perceived to be highly liquid investments.…”

“…Moreover, Ozun, Ertugrul and Coskun (2018) have noted that London has a leading role in the global urban economies residential housing markets, and that the behavior of its housing prices impacts the house prices in other globally important cities (even in New York City). In this context Ozun, Ertugrul and Coskun (2018) have stressed that real estate assets in New York City and London are perceived to be highly liquid investments. At this point, it is important to note that Coakley (1994) has argued that during the boom in the 1980s, the additional demand reassured investors that the liquidity of the property market in London and other parts of Great Britain had apparently risen.…”

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“…While some of them like global variables are more effective in one country, some others like macroeconomic and market indicators can be much more important in another country (Erdo gan and Memduho glu, 2019). These variables should be taken into account, but the starting point should be national (macroeconomic and market) indicators because housing prices can be shaped and determined mainly by national variables (Lekander, 2015;Özün et al, 2018). By identifying the variables that affect the housing markets and managing these variables effectively, countries can prevent negative effects on the economies arising from the housing markets, and thus benefit from the stability in the housing market.…”