A simple model of a speculative housing market

We develop a simple model of a speculative housing market in which the demand for houses is influenced by expectations about future housing prices. Guided by empirical evidence, agents rely on extrapolative and regressive forecasting rules to form their expectations. The relative importance of these competing views evolves over time, subject to market circumstances. As it turns out, the dynamics of our model is driven by a two-dimensional nonlinear map which may display irregular boom and bust housing price cycles, as repeatedly observed in many actual markets. Complex interactions between real and speculative forces play a key role in such dynamic developments.     

An alternative method for identifying booms and busts in the Euro area housing market

This article develops a model-based method to detect booms and busts in the Euro area housing market. A model is constructed and tested, whereby the user cost rate, a demographic variable, unemployment rate, disposable income, debt-to-income ratio and housing stock are fundamental variables significantly explaining house price (HP) developments. Booms/busts are identified as episodes when the HP index exceeds the levels implied by those economic fundamentals. Furthermore, a cross-check with boom/bust episodes based on other methods is carried out to substantiate the results, while the ability of the model in predicting booms/busts in real time is also tested.     

Is the relationship between monetary policy and house prices asymmetric across bull and bear markets in South Africa? Evidence from a Markov-switching vector autoregressive model

This paper examines asymmetries in the impact of monetary policy on the middle segment of the South African housing market from 1966:M2 to 2011:M12. We use Markov-switching vector autoregressive (MS-VAR) model in which parameters change according to the phase of the housing cycle. The results suggest that monetary policy is not neutral as house price growth decreases substantially with a contractionary monetary policy. We find that the impact of monetary policy is larger in bear regime than in bull regime; indicating the role of information asymmetry in reinforcing the financial constraint of economic agents. As expected, monetary policy reaction to a positive house price shock is found to be stronger in the bull regime. This suggests that the central bank reacts more in bull regime in order to prevent potential crisis related to the subsequent bust in house prices bubbles which are more prominent in bull markets. These results substantiate important asymmetries in the dynamics of house prices in relation to monetary policy, vindicating the advantages of generating regime dependent impulse response functions.     

Nonlinearity and nonstationarity in international art market prices: evidence from Markov-switching ADF unit root tests

This study investigates the presence (or lack thereof) of nonlinear dynamics and nonstationarity in international art market prices using quarterly data for the period 1990–2011. We first test whether art market price indices follow stochastic trends or whether they are stationary by means of linear unit root tests. Next, we estimate the Markov regime-switching ADF model and test whether the linear or the nonlinear regime-switching model provides a better characterization of the global art market price series. We find that all art market price indices (except for Drawings) exhibit nonlinearity. To our knowledge, our study is the first one in the literature to suggest that a nonlinear (Markov regime-switching) model provides a better characterization of the behavior of price dynamics in international art markets. In particular, our findings indicate that the market for the overall global art market, paintings, old masters, sculptures, photographs, prints, and contemporary art might indeed be stationary while exhibiting nonlinear regime-switching properties. On the other hand, the market for drawings and the Nineteenth century art are found to be nonstationary. Overall, despite the common ground of a regime-switching framework, we still find that the sub-segments of the art market have their own inner regime switching dynamics and hence they can evolve differently overtime.     

Markov regime-switching Beta-t-EGARCH

We suggest a Markov regime-switching (MS) Beta-t-EGARCH (exponential generalized autoregressive conditional heteroscedasticity) model for U.S. stock returns. We compare the in-sample statistical performance of the MS Beta-t-EGARCH model with that of the single-regime Beta-t-EGARCH model. For both models we consider leverage effects for conditional volatility. We use data from the Standard Poor’s 500 (S&P 500) index and also a random sample that includes 50 components of the S&P 500. We study the outlier-discounting property of the single-regime Beta-t-EGARCH and MS Beta-t-EGARCH models. For the S&P 500, we show that for the MS Beta-t-EGARCH model extreme observations are discounted more for the low-volatility regime than for the high-volatility regime. The conditions of consistency and asymptotic normality of the maximum likelihood estimator are satisfied for both the single-regime and MS Beta-t-EGARCH models. All likelihood-based in-sample statistical performance metrics suggest that the MS Beta-t-EGARCH model is superior to the single-regime Beta-t-EGARCH model. We present an application to the out-of-sample density forecast performance of both models. The results show that the density forecast performance of the MS Beta-t-EGARCH model is superior to that of the single-regime Beta-t-EGARCH model.     

House price,mortgage premium,and business fluctuations

This paper investigates the transmission mechanism of mortgage premium to characterize the relationship between the housing market and business cycle for the U.S. We find that mortgage premium is crucial for the amplification and propagation of the model to match the main properties of U.S. housing market and business cycles. The counterfactual analysis suggests that had the Federal Reserve raised the interest rate in 2003Q1, it would have curbed the housing market boom before the crisis, yet failed to alleviate the precipitous decline in housing market activity after the crisis. Moreover, the pre-emptive monetary policy aimed to contain the housing market boom can effectively lower volatilities of major economic aggregates; however, it also exerts a significantly negative effect on the levels of these economic aggregates. Thus, using monetary policy to stabilize asset price inflation involves a trade-off between the volatility and the level of economic activity.     

The nonlinear effects of expected and unexpected components of monetary policy on the dynamics of REIT returns

This paper examines empirically whether the expected and unexpected components of monetary policy have nonlinear impacts on the dynamics of REIT returns. Empirical results find the nonlinear response of REIT returns to expected and unexpected components of monetary policy. The unexpected component of monetary policy plays a more prominent role in influencing REIT returns than does the expected component of monetary policy. Specifically, unexpected contractionary monetary policy has a significantly adverse impact on REIT returns, and the adverse effect in a bust market is stronger than in a boom market. In addition, the unexpected monetary policy will also affect the boom-bust dynamics of REIT returns through its effect on the time-varying transition probability matrix. The tightening of the expected and unexpected components of monetary policy will enhance the probability that the REIT market will stay in the bust regime.     

Markets contagion during financial crisis: A regime-switching approach

Within a Markov regime-switching VAR framework, we investigate the contagion effects among the stock market, real estate market, credit default market, and energy market covering the most recent financial crisis period when markets experience regime shifts. The results demonstrate that the watershed of regimes occurs around the start of the subprime crisis in 2007, after which the “risky” regime dominates the evolution of market chaos. During the financial crisis, excluding their own shocks, stock market shock and oil price shock are the main driving forces behind the credit default market and stock market variations, respectively. The energy market also appears to be more responsive to the stock market movements than the shocks originating from housing and credit markets. However, the impacts from the credit default market on the real estate market are not significant as expected.     

The recent boom–bust cycle: The relative contribution of capital flows, credit supply and asset bubbles

We use an estimated open economy DSGE model with financial frictions for the US and the rest of the world to evaluate various competing explanations about the recent boom–bust cycle. We find that the savings glut hypothesis is insufficient for explaining all aspects of the boom in the US. Relatively strong TFP growth and expansionary monetary policy are also not able to explain fully the volatility of corporate and in particular residential investment. We identify bubbles in the stock and housing market as crucial. Concerning the downturn in 2008/2009, the fall in house prices and residential investment only plays a minor role. Mortgage defaults have more explanatory power, especially in a specification of the model with a segregated equity market. Finally, the bursting of the stock market bubble was at least as important in this recession as in 2001. Because of various negative shocks hitting the economy at the same time in 2008/2009 and continued positive technology growth, not only the real interest rate declined but inflation fell rapidly and left insufficient room for monetary policy to play a similar stabilising role as in previous recessions.     

Bernanke versus Taylor: a post mortem

Our analysis sheds light on the issue of whether the monetary policy contributed to the recent housing boom and bust. We have estimated and analysed a model that allows a comparison between the actual policy and several alternative Taylor rules. When the Taylor rule path was computed using revised data and the deflator for the GDP, we found a notable impact on key housing market variables, supporting Taylor’s critique of the Fed policy. However, the bulk of our evidence suggests that the policy as it would have been conducted under our real-time Taylor rules would not have had any significant impact on the housing market variables. This conclusion is robust with regard to the price index used as well as the relative weights used on the inflation and output gaps.     

Responses of international stock markets to oil price surges: a regime-switching perspective

We propose an enhanced regime-switching model to investigate the relationships between oil price surges and stock market cycles in five oil-dependent countries. Our model accounts for the joint effects of the West Texas Intermediate (WTI) and Brent oil markets and simultaneously captures asymmetry, volatility persistence and regime shifts contained in the underlying financial data. We find that stock market returns strongly exhibit a regime-switching behaviour, but they react differently to the increases in the price of oil. More precisely, the conditional volatility of studied stock markets during the bear market phases is found to be less affected by oil price surges than during the bull market phases. Whether the effects of oil shocks are positive or negative depends greatly on the degree of reliance on imported oil, the share of the cost of oil in the national income and the degree of improvement in energy efficiency of a given country. Finally, the relatively opposite effects of the WTI and Brent oil markets suggest the potential of substitution between them as well as the necessity of a diversification strategy of oil supply sources.     

Information and adjustment in a local housing market

Existing studies on bubbles have been mainly concerned with investigating the stationarity properties of stock prices and market fundamentals. We develop a new method of testing for bubbles that relates the bubble component of stock prices to the probability of bursting in the context of the Weibull distribution. There were several eruptions and subsequent collapses of seeming bubbles over the past three decades: 1987 (Black Monday), 2000 (information technology (IT) boom) and 2007 (housing market boom). Using US monthly data for the S&P 500 and NASDAQ series, we have found that the S&P 500 series contained an explosive bubble only during the boom of the housing market that occurred before the 2007 global economic crisis, and the NASDAQ market contained an explosive bubble during the surge of stock prices peaking in 1987 and 2007, although our stationarity tests fail to detect the bubbles. No bubble was found in both the S&P and NASDAQ series during the 2000 IT boom. Our evidence corroborates the criticism that the traditional unit root and cointegration tests may not be able to detect some important class of bubbles.     

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.     

Consumption,housing collateral and the Canadian business cycle

How important are collateral constraints for reproducing salient features of the data? To address this question, we estimate two nested versions of a New Keynesian model: one with collateralized household debt and the frictionless version of the same model. Both versions of the model are fit to Canadian data using Bayesian methods. We argue that the presence of collateral constraints improves the performance of the model in terms of overall goodness of fit. Housing collateral helps to generate a positive correlation between consumption and house prices. Moreover, housing collateral induced spillovers boosted consumption growth during the housing market boom‐bust cycles of the late 1980s and early 2000s.     

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.     

Will euro area house prices sharply decrease?

The long-term euro area house price equilibrium and its short-term dynamics are estimated by means of a panel error correction model. The estimates show that the short-term dynamics are essentially driven by the autoregressive term (persistence), disposable income and mortgage loans, whereas interest rates have little effect. The long-term house price equilibrium is mainly driven on the demand side by disposable income, interest rates, and mortgage loans, whereas costs (mostly land) drive the equilibrium on the supply side. The unprecedented long-lasting boom in house prices from 1997 to 2007 is thus essentially explained by a favourable macroeconomic development caused by the EMU effect and a glut of global savings. The bust phase of euro area house prices began in 2007, and the current house price might return to its equilibrium level in 2014. According to the most realistic scenario, euro area house prices will experience a smooth and soft landing in 2016 and then begin an increasing phase that will be pulled upwards by a higher equilibrium price. However, a deflationary scenario cannot be excluded if the current credit squeeze is not solved, particularly in the peripheral euro area member states.     

OPPORTUNISTIC MATCHING IN THE HOUSING MARKET*

We construct a model of the housing market in which agents differ in their flow values while searching. Agents enter the market relaxed (with high flow values) but move to a desperate state (low flow values) at a Poisson rate if they have not already transacted. We characterize the equilibrium steady‐state matching pattern and the joint distribution of price and time to sale (for sellers). The expected price conditional on time to sale falls with time spent on the market, whereas the conditional variance of price first rises and then falls with time on the market.     

A joint analysis of market indexes in credit default swap,volatility and stock markets

This paper analyses the joint dynamics of the CDS, volatility and stock markets using both VAR and Markov regime-switching VAR models with market index data. It shows that the joint behaviour of the three markets is better characterized by the Markov model with two regimes corresponding to low- and high-volatile market conditions. The relationship between changes in the market indexes under a regime is consistent with theory and persistent; the information transmission process of shocks to the markets is similar for the two regimes with a more important role for CDS shock; and the volatility in the money market is an important determinant of regime-switching. The findings have practical implications, particularly for hedging strategies with market indexes under different market conditions.     

House price dynamics: Evidence from Beijing

To study the house price dynamics in China, this paper extends the traditional life-cycle model by incorporating land supply, regime shifts and government regulation factors. The models are estimated with an error correction framework using quarterly data from 2000 to 2007 in Beijing. The conclusions are as follows. (1) There exits a stable co-integration relationship between house price and fundamentals; land supply and financial regimes are also important determinants of long-run equilibrium house prices. (2) Short-run dynamics depend on changes of fundamentals and the adjustment process of housing market. Land supply has a significant impact on house price fluctuations while demand factors such as user costs, income and residential mortgage loan have greater influences. The adjustment speed of real house prices to the long-run equilibrium has been reduced significantly since 2005 which means exogenous shocks can cause prolonged deviation of real house prices from the equilibrium level.     

Boom in,bust out: Young households and the housing price cycle

The UK experienced a major residential real estate boom–bust cycle from the mid-1980s to the mid-1990s, accompanied by unprecedented shifts in the owner occupancy rate of young households. Previous empirical analyses have pointed toward income changes and financial deregulation as the likely causes of this episode, with little to say about the differential effects on various age groups. We show that, in a life-cycle model with income heterogeneity and credit constraints, the observed co-movements of housing prices and owner occupancy rates can be explained as an equilibrium response to income and credit market shocks. Our findings suggest that the financial liberalisation of the early 1980s was crucial for the unparalleled increase in the owner occupancy rate of young households during the boom.