Dynamic analysis of house price diffusion across Asian financial centres

The aim of this paper is to explore effects of macroeconomic variables on house prices and also, the lead-lag relationships of real estate markets to examine house price diffusion across Asian financial centres. The analysis is based on the Global Vector Auto-Regression (GVAR) model estimated using quarterly data for six Asian financial centres (Hong Kong, Tokyo, Seoul, Singapore, Taipei and Bangkok) from 1991Q1 to 2011Q2. The empirical results indicate that the global economic conditions play significant roles in shaping house price movements across Asian financial centres. In particular, a small open economy that heavily relies on international trade such as – Singapore and Tokyo - shows positive correlations between economy’s openness and house prices, consistent with the Balassa-Samuelson hypothesis in international trade. However, region-specific conditions do play important roles as determinants of house prices, partly due to restrictive housing policies and demand-supply imbalances, as found in Singapore and Bangkok.

House price dynamics and their reaction to macroeconomic changes

This article applies a three-regime Markov switching model to investigate the impact of the macroeconomy on the dynamics of the residential real estate market in the US. Focusing on the period between 1960 and 2011, the methodology implemented allows for a clearer understanding of the drivers of the real estate market in “boom”, “steady-state” and “crash” regimes. Our results show that the sensitivity of the real estate market to economic changes is regime-dependent. The paper then proceeds to examine whether policymakers are able to influence a regime switch away from the crash regime. We find that a decrease in interest rate spreads could be an effective catalyst to precipitate such a change of state.

House price dynamics in Panama City

In this paper, we analyze the drivers of the housing markets in Panama City. To the best of our knowledge, no formal academic analysis has been documented on the Panamanian housing market. In this paper, we outline key unique characteristics of the market and provide a brief review of broader economic indicators and housing market literature. Using a unique dataset comprising property-level information over 2007–2014, we employ a hedonic modeling framework to analyze the impacts of certain amenities and drivers that may affect housing values. The results indicate several unique features of the Panamanian housing market.

House price dynamics and bank herding: European empirical evidence

This paper investigates the behavior of residential property and examines the linkages between house price dynamics and bank herding behavior. The analysis presents evidence that irrational behaviour may have played a significant role in several countries, including; United Kingdom, Spain, Denmark, Sweden and Ireland. In addition, we also provide evidence indicative of herding behaviour in the European residential mortgage loan market. Granger Causality tests indicate that non-fundamentally justified prices dynamics contributed to herding by lenders and that this behaviour was a response by the banks as a group to common information on residential property assets. In contrast, in Germany, Portugal and Austria, residential property prices were largely explained by fundamentals. Furthermore, these countries show no evidence of either irrational price bubbles or herd behaviour in the mortgage market. Granger Causality tests indicate that both variables are independent.

Granger causality among house price and macroeconomic variables in Victoria

This study analyses the dynamic causality of four macroeconomic variables on house prices. The four macroeconomic variables have interrelationships with house prices in certain lagged terms, but these relationships are not always the same as the notions put forward in prior research. The relationships are detected to be unstable in the three observation periods. The instability of these relationships would cause difficulty in predicting house prices in the market, especially for policy makers and market participants.

Identifying house price diffusion patterns among Australian state capital cities

Prior research supports the proposition that house price diffusion shows a ripple effect along the spatial dimension. That is, house price changes in one region would reflect in subsequent house price changes in other regions, showing certain linkages among regions. Using the vector autoregression model and the impulse response function, this study investigates house price diffusion among Australia's state capital cities, examining the response of one market to the innovation of other markets and determining the lagged terms for the maximum absolute value of the other markets' responses. The results show that the most important subnational markets in Australia do not point to Sydney, rather towards Canberra and Hobart, while the Darwin market plays a role of buffer. The safest markets are Sydney and Melbourne. This study helps to predict house price movement trends in eight capital cities.

The ripple effect in house price fluctuations in Australia

The differences in economy, society, demography and geography in different regions are main reasons which cause disparities in regional house prices. Three theories, namely ripple effect hypothesis, convergence and efficient market hypothesis, are used to examine price fluctuations in spatial dimension amongst eight housing markets in Australian state capital cities.

Can investors hedge residential price dynamics of Australia's capital cities?

The study described in this paper focuses on testing the short-run and
long-run relationships between house price and consumer price indices in Australia’s capital cities from 1998 to 2008. The autoregressive distributed lag model is adopted to obtain the estimates of the short-run relationships, while the error correction model is used to investigate the long-run relationships. The t-statistic is used to compute the significance of these relationships. The research results give no evidence that house price indices are correlated with consumer price indices in the short run. However, the long-run relationships between house and consumer price indices exist in most of the cities.

House price bubble estimations in Australia's capital cities with market fundamentals

This paper investigates the existence of house price bubbles in Australia's eight capital cities in recent years by using quantitative analyses including Johansen cointegration test, Granger causality test, impulse response and Chow forecast test. While interactions between house prices and market fundamentals are discussed in long-run and causal estimations, shocks from the market fundamentals to house prices are investigated in generalized impulse response analyses. Findings from estimating house price bubbles for eight capital cities suggest that there was an obvious house price bubble in Perth, while a slight house price bubble occurred in Sydney. In contrast, house prices in Adelaide and Darwin can be explained very well by market fundamentals, while house prices in Melbourne, Brisbane, Hobart and Canberra were undervalued in the study period.