Real House Price Changes Research Articles

Common factors and spatial dependence: an application to US house prices

This article considers panel data models with cross-sectional dependence arising from both spatial autocorrelation and unobserved common factors. It proposes estimation methods that employ cross-sectional averages as factor proxies, including the 2SLS, Best 2SLS, and GMM estimations. The proposed estimators are robust to unknown heteroskedasticity and serial correlation in the disturbances, unrequired to estimate the number of unknown factors, and computationally tractable. The article establishes the asymptotic distributions of these estimators and compares their consistency and efficiency properties. Extensive Monte Carlo experiments lend support to the theoretical findings and demonstrate the satisfactory finite sample performance of the proposed estimators. The empirical section of the article finds strong evidence of spatial dependence of real house price changes across 377 Metropolitan Statistical Areas in the US from 1975Q1 to 2014Q4.

Identification and Estimation of Spatial Autoregressive Models with Common Factors

This paper considers panel data models with cross-sectional dependence arising from both spatial autocorrelation and unobserved common factors. It proposes estimation methods that employ cross-sectional averages as factor proxies, including the 2SLS, Best 2SLS, and GMM estimations. The proposed estimators are robust to unknown heteroskedasticity and serial correlation in the disturbances, unrequired to estimate the number of unknown factors, and computationally tractable. The paper establishes the asymptotic distributions of these estimators and compares their consistency and efficiency properties. Extensive Monte Carlo experiments lend support to the theoretical findings and demonstrate the satisfactory finite sample performance of the proposed estimators. The empirical section of the paper finds strong evidence of spatial dependence of real house price changes across 377 Metropolitan Statistical Areas in the US from 1975Q1 to 2014Q4.

The run-up to the global financial crisis: A longer historical view of financial liberalization, capital inflows, and asset bubbles

Using forecast error and sensitivity analyses with a vector error correction model for the US economy, we find that the specific exogenous shocks that contributed to the run-up to the global financial crisis of 2007–2009 vary across the three time periods (1980–1988; 1989–1997; and 1998–2006) that are known for distinctive historical events. Deregulation in the 1980s and capital inflows in the early and mid-1990s triggered by the collapse of the European exchange rate mechanism contributed significantly to changes in real house prices. However, capital inflows after the Asian financial crises in 1997 were driven in large part by rising asset prices. Thus, there were interesting changes in the nature of exogenous shocks and directions of causality through the three sub-periods. These results are robust even after controlling for the exogenous global factors partly determining short-run changes in capital flows, asset prices, and per capita real GDP. We conclude that all of the short run changes in response to financial deregulation starting in the 1980s, surges in capital inflows in the early 1990s, and people's expectation of ever-rising asset prices in the late 1990s and early 2000s culminated in the crisis of 2007–2009.

A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence

SummaryAn understanding of the spatial dimension of economic and social activity requires methods that can separate out the relationship between spatial units that is due to the effect of common factors from that which is purely spatial even in an abstract sense. The same applies to the empirical analysis of networks in general. We use cross‐unit averages to extract common factors (viewed as a source of strong cross‐sectional dependence) and compare the results with the principal components approach widely used in the literature. We then apply multiple testing procedures to the de‐factored observations in order to determine significant bilateral correlations (signifying connections) between spatial units and compare this to an approach that just uses distance to determine units that are neighbours. We apply these methods to real house price changes at the level of Metropolitan Statistical Areas in the USA, and estimate a heterogeneous spatio‐temporal model for the de‐factored real house price changes and obtain significant evidence of spatial connections, both positive and negative. Copyright © 2015 John Wiley & Sons, Ltd.

Housing booms and media coverage

This article analyses news media coverage of the housing market. Building on theories of media influence where word of mouth is the final mechanism of opinion change but media initiate discourse, I examine the relationship between news media and the recent UK house price boom. Over 30 000 articles on the UK housing market from the period 1993 to 2008 are analysed, and it is found that media Granger-caused real house price changes, suggesting the media may have influenced opinions on the housing market. However, media sentiment on the housing market did not change with the secular increase in house prices in the 2000s, suggesting that the media did not contribute to the UK’s housing boom and may have helped constrain it.

A Two Stage Approach to Spatiotemporal Analysis with Strong and Weak Cross-Sectional Dependence

An understanding of the spatial dimension of economic and social activity requires methods that can separate out the relationship between spatial units that is due to the effect of common factors from that which is purely spatial even in an abstract sense. The same applies to the empirical analysis of networks in general. We are able to distinguish between cross-sectional strong dependence and weak dependence. Strong dependence in turn suggests that there are common factors. We use cross unit averages to extract common factors and contrast this to a principal components approach widely used in the literature. We then use a multiple testing procedure to determine significant bilateral correlations (signifying connections) between spatial units and compare this to an approach that just uses distance to determine units that are neighbours. We apply these methods to real house price changes at the level of Metropolitan Statistical Areas in the USA, and estimate a heterogeneous spatiotemporal model for the de-factored real house price changes and obtain significant evidence of spatial connections, both positive and negative.

Do house price developments spillover across euro area countries? Evidence from a global VAR

This paper empirically assesses the prospects for house price spillovers in the euro area, where co-movement in house prices across countries may be particularly relevant given a general trend with monetary union toward increasing linkages in trade, financial markets, and general economic conditions. A global VAR is estimated for three housing demand variables (real house prices, real per capita income, and the cost of borrowing, captured by a real long-term interest rate) on the basis of quarterly data for 7 euro area countries (Belgium, Germany, Ireland, Spain, France, Italy and the Netherlands), which together comprise nearly 90% of euro area GDP, over the period 1971–2009. The results suggest limited house price spillovers in the euro area, albeit with evidence of some overshooting in the first year after the shock, followed by a long run aggregate euro area impact of country-specific changes in real house prices related in part to the country’s economic weight. This contrasts with the impacts of a shock to domestic long-term interest rates, causing a permanent shift in house prices after 2–3 years. Underlying this aggregate development are rather heterogeneous house price spillovers at the country level, with a strong importance for weights – either economic or geographic – in governing their general magnitude. More generally, the impact of financing costs on house prices appears to have grown though time.

House prices, Economic Output, and Inflation Interactions in Iran

Many economic theories indicate that house price changes should have real effect on the economy and vice versa. This study investigates the existence of causality among house prices, economic growth, and inflation in Iran using the Toda and Yamamoto approach during the period 1990:1–2008:3. The results show that there is evidence of a significant multidirectional link between house prices, and the macroeconomic factors. The causality tests confirm that GDP and CPI Granger cause house prices, and feedback effects are observed for house prices and GDP. This paper finds no evidence of Granger causality of real house price changes to CPI.

A spatio-temporal model of house prices in the USA

This paper provides an empirical analysis of changes in real house prices in the USA using State level data. It examines the extent to which real house prices at the State level are driven by fundamentals such as real per capita disposable income, as well as by common shocks, and determines the speed of adjustment of real house prices to macroeconomic and local disturbances. We take explicit account of both cross-sectional dependence and heterogeneity. This allows us to find a cointegrating relationship between real house prices and real per capita incomes with coefficients ( 1 , − 1 ) , as predicted by the theory. We are also able to identify a significant negative effect for a net borrowing cost variable, and a significant positive effect for the State level population growth on changes in real house prices. Using this model we then examine the role of spatial factors, in particular, the effect of contiguous states by use of a weighting matrix. We are able to identify a significant spatial effect, even after controlling for State specific real incomes, and allowing for a number of unobserved common factors. We do, however, find evidence of departures from long run equilibrium in the housing markets in a number of States notably California, New York, Massachusetts, and to a lesser extent Connecticut, Rhode Island, Oregon and Washington State.

THE ILLUSION OF STABILITY—LOW INFLATION IN A BUBBLE ECONOMY

Econometric studies show that changes in real house prices are strongly autocorrelated in the UK, giving rise to prolonged departures from equilibrium. What happens when arbitrage is ‘broken’ and house prices no longer reflect future fundamentals? Adding a bubble to capture the disequilibrium behaviour picked up by econometricians, we show that a narrow focus on consumer price inflation—while neglecting house price disequilibrium—may for some time create the appearance of stability. But, with the bubble distorting policy and the economy on the way up and wreaking havoc on the banking system when it bursts, this is an illusion. For a bubble economy, new instruments of policy (such dynamic capital requirements and loan‐to‐value limits) are clearly needed—together with clear mandates as to who regulates what.

Do House Price Developments Spill Over Across Euro Area Countries? Evidence from a Global VAR

This paper empirically assesses the prospects for house price spillovers in the euro area, where co-movement in house prices across countries may be particularly relevant given a general trend with monetary union toward increasing linkages in trade, financial markets, and general economic conditions. The application involves a Global VAR for three housing demand variables (real house prices, real per capita disposable income, and the real interest rate) on the basis of quarterly data for 10 euro area countries (Belgium, Germany, Ireland, Spain, France, Italy, the Netherlands, Austria, Portugal and Finland) over the period 1989-2007. The results suggest limited house price spillovers in the euro area, with evidence of some overshooting in the first 1-3 years after the shock, followed by a long run aggregate euro area impact of country-specific changes in real house prices related in part to the country's economic weight. This contrasts with the impacts of a shock to domestic long-term interest rates, with the latter causing a permanent shift in house prices after around 3 years. Underlying this aggregate development are rather heterogeneous house price spillovers at the country level, with a strong importance for economic weight in the euro area in governing their general magnitude, while geographic proximity appears to also play a role.

Explaining House Prices in Australia: 1970–2003*

This paper aims to explain changes in real house prices in Australia from 1970 to 2003. We develop and estimate a long‐run equilibrium model that shows the real long‐run economic determinants of house prices and a short‐run asymmetric error correction model to represent house price changes in the short run. We find that, in the long run, real house prices are determined significantly and positively by real disposable income and the consumer price index. They are also determined significantly and negatively by the unemployment rate, real mortgage rates, equity prices and the housing stock. Employing our short‐run asymmetric error correction model, we find that there are significant lags in adjustment to equilibrium. When real house prices are rising at more than 2 per cent per annum, the housing market adjusts to equilibrium in approximately four quarters. When real house prices are static or falling, the adjustment process takes six quarters.

Long-Run Information Diffusion Processes in the Perth Housing Market: 1988–2000

In the period since the influential studies by Case and Shiller (1989, 1990), it has been established that housing markets are characterised by information diffusion patterns determined by informational inefficiencies. In Australia, little work has been completed on the long-term patterns of these inefficiencies. This paper examines a rich data set of transactions for the Perth housing market in the period 1988-2000. The results confirm some significant long-term patterns for real house price changes and some close relationships between these patterns and changes in real interest rates.

Seasonal Influences in Australian Housing Markets

This paper examines the impact of seasonal influences on housing market activity. Empirical tests examine the influence of a quarterly season on the demand for housing and the observed real house price changes. Empirical tests are specifically designed for a ‘short’ time-series, 1988-95. The explanatory power of the statistical tests is improved by ‘stacking’ regional data to perform more robust tests for seasonality. The results confirm significant seasonal influences. The volume of transactions and hence demand is greatest during the first quarter of a year and lowest during the last quarter. The observed real house price changes are highest in the first quarter of a year and lowest during the third quarter.

The Determinants of Urban House Price Fluctuations in Sweden 1968–1994

A restricted error-correction model of real house price changes is estimated on Swedish panel data. In the long-run equation, movements in income, user costs, and construction costs were found to have a significant impact on real house prices. The estimates of the dynamic equation reveals a rich autoregressive structure in real house prices. They also suggest that adjustment toward the long-run relationship is quite rapid. While the results are consistent with speculative behavior, it is also shown that real house price fluctuations are well explained by the development of fundamental demand conditions in this period.