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.

Asymmetric sensitivities of house prices to housing fundamentals: evidence from UK regions

2019 ◽  
Vol 12 (3) ◽  
pp. 442-455 ◽  
Author(s):  
Huthaifa Alqaralleh
Keyword(s):  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Housing Affordability ◽  
Star Model ◽  
Content Type ◽  
Macroeconomic Variables ◽  
North West ◽  
Country Level ◽  
The North

Purpose This paper aims to examine asymmetries in the house price cycle and to understand the dynamic of housing prices, incorporating macroeconomic variables at regional and country level, namely, housing affordability, the unemployment rate, mortgage rate and inflation rate. Design/methodology/approach To highlight significant differences in the asymmetric patterns of house prices between regions, the STAR model is adopted. Findings The authors highlight significant differences in the asymmetric patterns of house prices between regions, in which some areas showed asymmetric response over the housing cycle; here the LSTAR model outperforms other models. In contrast, some regions (the South West and the North West) showed symmetric properties in the tails of the cycle; therefore, the ESTAR model was adopted in their case. Practical implications Being limited to a few fundamentals, this study opens an avenue for further research to investigate this dynamic using in addition such demand-supply factors as land supply, construction cost and loans made for housing. These findings can also be used to examine whether other models such as ARIMA, exponential smoothing or artificial neural networks can more accurately forecast housing prices. Originality/value The present paper aims to highlight housing affordability as a cause of asymmetric behaviour in house prices. Put differently, the authors seek to understand the dynamics of housing prices with other fundamentals incorporating macroeconomic variables in regions and country level data as a means of achieving a more concise result.

House prices and associated risks are rising globally

2019 ◽  
Keyword(s):  
Real Estate ◽  
House Prices ◽  
Housing Markets ◽  
Global Property ◽  
Financial Flows ◽  
Content Type ◽  
Real Estate Markets ◽  
Emerging Nations ◽  
Property Prices ◽  
The World

Subject Global property prices. Significance House prices have surged in the last five years, mostly in high-income economies where demand has rebounded after falling in the aftermath of the 2008-09 recession. Adjusted for inflation, house prices rose steadily across the world between 2013 and 2018, raising concerns about the downside risks associated with overvaluations. Impacts Housing markets are difficult to tune; lenient policies aimed at supporting immediate activity will increase longer-run risks. Real estate markets are becoming more synchronised, and more exposed to common downside risks if global financial flows drop. Cities and financial centres in advanced and emerging nations are most exposed as they enjoy more flows of volatile capital.

scholarly journals Liquidity, interest rates and house prices in the euro area: a DSGE analysis

2016 ◽  
Vol 9 (1) ◽  
pp. 4-25 ◽  
Author(s):  
Margarita Rubio ◽  
José A. Carrasco-Gallego
Keyword(s):  
Interest Rates ◽  
Monetary Union ◽  
Euro Area ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Dsge Model ◽  
Content Type ◽  
The Core ◽  
Dynamic Stochastic

Purpose This study aims to build a two-country monetary union dynamic stochastic general equilibrium (DSGE) model with housing to assess how different shocks contributed to the increase in housing prices and credit in the European Economic and Monetary Union. One of the countries is calibrated to represent the core group in the euro area, while the other one corresponds to the periphery. Design/methodology/approach In this paper, the authors explore how a liquidity shock (or a decrease in the interest rate) affects house prices and the real economy through the asset price and the collateral channel. Then, they analyze how a house price shock in the periphery and a technology shock in the core countries are transmitted to both economies. Findings The authors find that a combination of an increase in liquidity in the euro area coming from the common monetary policy, together with asymmetric house price and technology shocks, contributed to an increase in house prices in the euro area and a stronger credit growth in the peripheral economies. Originality/value This paper represents the theoretical counterpart to empirical studies that show, through macroeconometric models, the interrelation between liquidity and other shocks with house prices. Using a DSGE model with housing, the authors disentangle the mechanisms behind these empirical findings.

House price index (HPI) and Covid-19 pandemic shocks: evidence from Turkey and Kazakhstan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yeşim Aliefendioğlu ◽  
Harun Tanrivermis ◽  
Monsurat Ayojimi Salami
Keyword(s):  
Real Estate ◽  
Price Index ◽  
Housing Prices ◽  
House Price ◽  
Monthly Basis ◽  
Data Set ◽  
House Price Index ◽  
Content Type ◽  
Asymmetric Pricing ◽  
Long Run

Purpose This paper aims to investigate asymmetric pricing behaviour and impact of coronavirus (Covid-19) pandemic shocks on house price index (HPI) of Turkey and Kazakhstan. Design/methodology/approach Monthly HPIs and consumer price index (CPI) data ranges from 2010M1 to 2020M5 are used. This study uses a nonlinear autoregressive distributed lag model for empirical analysis. Findings The findings of this study reveal that the Covid-19 pandemic exerted both long-run and short-run asymmetric relationship on HPI of Turkey while in Kazakhstan, the long-run impact of Covid-19 pandemic shock is symmetrical long-run positive effect is similar in both HPI markets. Research limitations/implications The main limitations of this study are the study scope and data set due to data constraint. Several other macroeconomic variables may affect housing prices; however, variables used in this study satisfy the focus of this study in the presence of data constraint. HPI and CPI variables were made available on monthly basis for a considerably longer period which guaranteed the ranges of data set used in this study. Practical implications Despite the limitation, this study provides necessary information for authorities and prospective investors in HPI to make a sound investment decision. Originality/value This is the first study that rigorously and simultaneously examines the pricing behaviour of Turkey and Kazakhstan HPIs in relation to the Covid-19 pandemic shocks at the regional level. HPI of Kazakhstan is recognized in the global real estate transparency index but the study is rare. The study contributes to regional studies on housing price by bridging this gap in the real estate literature.

scholarly journals Homeownership Rate and Other House Price Determinants Impacts on New House Prices in Colombia

2020 ◽  
pp. 35-50
Author(s):  
Hector Botello-Peñaloza
Keyword(s):  
Real Estate ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Real Estate Market ◽  
The Real Estate ◽  
Homeownership Rate ◽  
Colombian Government ◽  
Price Determinants ◽  
Price Instability

Homeownership remains a preferred form of tenancy in different parts of the world. The attractions of security, stability, investment potential and a sense of pride outweigh the fear of price instability. For this reason, the Colombian government has encouraged in recent years, various demand policies that have sought to promote the increase in the number of homeowners. However, these ideas could have a severe impact on prices in the real estate market. Therefore, this study seeks to examine the effect of homeownership rate on new house prices in an emerging country with low real estate ownership, credit restrictions and average per capita income. The study uses panel data model to examine the influence of housing tenancy and other variables on the variation of housing prices in Colombia. Data were obtained from various sources including the Central Bank of Colombia, Financial Superintendence of Colombia, and National Administrative Department of Statistics of Colombia. The results show that homeownership rates have a positive effect on the price of new homes, which supports the hypothesis of the research. The population growth of the cities is the factor that is most relevant when explaining the price variations.

High house prices may be global systemic risk

2016 ◽  
Keyword(s):  
Interest Rates ◽  
Household Income ◽  
House Prices ◽  
House Price ◽  
Content Type ◽  
Price Boom ◽  
Advanced Economies ◽  
The Us ◽  
Property Markets

Subject The rise in global house prices. Significance In the first quarter of 2015, the global house price index, aggregating prices in 52 countries, was at about the same level as in early 2007, according to IMF data. This recovery has occurred in a period of wage gains in most emerging markets (EMs), but little or no growth in household income across most advanced economies. Living costs excluding housing have stagnated and interest rates have been exceptionally low. Yet US interest rates are rising now and global prices are unlikely to keep falling beyond 2016, while many EMs have slumped into recession. As households are hit by more adverse trends, property markets and the related sectors will be affected. Impacts The EM house price boom will be curbed by slowing income growth and weaker economic prospects. High house-prices-to-household-income ratios and household debt might require the introduction of macroprudential tools. The US housing market will stay affordable compared to its long-term average and to Europe's.

Policy will cut the risk of booming house prices

2021 ◽  
Keyword(s):  
Financial Stability ◽  
House Prices ◽  
House Price ◽  
Central Banks ◽  
Price Inflation ◽  
Content Type ◽  
Reserve Bank ◽  
Mortgage Backed Securities ◽  
The Us ◽  
The Government

Significance The government in New Zealand, where the market is particularly buoyant, was the first to react in February. It now requires the Reserve Bank to consider house prices when setting monetary policy. Other governments and central banks have shown little sign of following suit. Impacts Calls are rising for the US Federal Reserve to taper its purchases of mortgage-backed securities, but it will remain cautious. Rising financial stability risks and house price booms increase the risk of insolvency for borrowers and non-performing-loans for banks. Higher house prices add indirectly to consumer price inflation if they push up rents, but this link takes time to materialise.

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.

The user cost of housing in the Baltic states

2017 ◽  
Vol 10 (1) ◽  
pp. 17-34
Author(s):  
Darius Kulikauskas
Keyword(s):  
Real Estate ◽  
Interest Rates ◽  
Housing Prices ◽  
Residential Real Estate ◽  
Baltic States ◽  
Data Set ◽  
Content Type ◽  
Real Estate Markets ◽  
User Costs ◽  
The Baltic

Purpose This paper aims to use the user costs approach to identify the periods of over- and under-valuation in the Baltic residential real estate markets. Design/methodology/approach Three alternative estimates of the user costs of homeownership in the Baltics are computed: one that does not discriminate between the leveraged and unleveraged parts of a house and the other that takes loan-to-value ratios into account. Findings The approach successfully identifies the overheating that took place in the Baltic real estate markets prior to the crisis of 2009 and shows that there is significant upward pressure for the housing prices in the Baltics in the low interest rate environment that became prevalent ever since. Research limitations/implications The paper uses only the current values of the fundamentals to compute the user costs. The framework could be augmented to account for the expected future developments of the fundamentals. Practical implications The macroprudential policy makers should monitor the developments in the Baltic residential real estate markets closely and be ready to act because an increase in the price-to-rent ratios might seem sustainable, given the current low interest rates, but could potentially bring harmful volatility when the monetary policy normalises. Originality/value This paper builds a novel data set on the real estate markets of the Baltic countries and is the first to derive the user costs of homeownership in the region. It is also among the first to identify periods of housing price misalignments from their fundamental values in the Baltic States.

Credit expansion, state ownership and capital structure of Chinese real estate companies

2016 ◽  
Vol 34 (3) ◽  
pp. 263-275 ◽  
Author(s):  
Jianfu Shen ◽  
Xianting Yin
Keyword(s):  
Real Estate ◽  
Capital Structure ◽  
Housing Prices ◽  
Debt Financing ◽  
Credit Expansion ◽  
Content Type ◽  
Real Estate Markets ◽  
Credit Supply ◽  
The Impact ◽  
Expansion Period

Purpose – The purpose of this paper is to explore the impact of the credit expansion in 2009 and 2010 in China on the capital structure of listed real estate companies. Design/methodology/approach – Chinese listed real estate companies are divided into two groups, state-owned and non-state-owned, because their access to credit markets have different priority to state-owned banks that dominate bank lending. The difference-in-differences approach is employed to test the impact of changes in leverage ratios and loan ratios before and after the credit expansion period in state-owned firms and non-state-owned firms. Findings – Using quarterly panel regressions, the authors find that during the credit expansion period, state-owned companies exhibit a relatively greater increase in leverage ratios than non-state-owned firms. State-owned firms have greater increases in book leverage ratios, market leverage ratios and long-term debt ratios by 5.2, 4.9 and 1.1 per cent, respectively. It is also shown that loan ratios have increased more in state-owned firms than non-state-owned firms during the credit expansion period. Research limitations/implications – The paper explores only the impacts of credit expansion on capital structure of listed real estate firms in China. Further studies can be conducted to investigate the impact of credit supply on corporate investment decisions of real estate firms and on real estate markets. Practical implications – The findings can help explain the surge in land and housing prices after 2008 in China. Deng et al. (2015) find that state-owned real estate firms paid more for land price than non-state-owned firms, which contributed to upward pressure on housing prices. This paper shows that such “over-investment” may be due to the increase of debt financing and availability of bank loans to real estate firms. Thus the credit market can affect real estate markets through debt financing at company level. Originality/value – This paper is the first to investigate the impact of credit supply on capital structure of real estate companies, and presents evidence of the importance of credit supply as a determinant of capital structure.

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