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The global financial and economic crisis resulting from the US housing crisis has shown that house prices can have far-reaching consequences for the real economy. For macroprudential supervision, it is, therefore, necessary to identify house price bubbles at an early stage to counteract speculative price developments and to ensure financial market stability. This paper aims to develop an early warning system to signal speculative price bubbles.

The results of explosivity tests are used to identify periods of excessive price increases in 18 industrialized countries. The early warning system is then based on a logit and an ordered logit regression, in which monetary, macroeconomic, regulatory, demographic and private factors are used as explanatory variables.

The empirical results show that monetary developments have the highest explanatory power for the existence of house price bubbles. Further, the study reveals currently emerging house price bubbles in Norway, Sweden and Switzerland.

The results implicate a new global housing boom, particularly in those countries that did not experience a major price correction during the global financial crisis.

The ordered logit model is an advanced approach that offers the advantage of being able to differentiate between different phases of a house price bubble, thereby allowing a multi-level assessment of the risk of speculative excesses in the housing market.

The purpose is to review what is known about property bubbles and their causes.

The method has been to review the literature on bubbles in the property and other asset markets to examine their likely causes and whether there are specific aspects of the property market that make it more prone to bubbles.

The property market has features that make it susceptible to bubbles, particularly inelasticity in supply and the absence of short selling. Bubbles can develop where there are heterogeneous beliefs. The way in which property tends to be financed helps to facilitate bubbles and transmit their effects onto the wider economy.

The collapse in property prices after the financial crisis of 2008, like previous bubble collapses, has inflicted serious damage on the wider economy through losses of banks' capital, reductions in lending, and increased risk aversion. Understanding why bubbles exist offers the potential to devise policies to limit the impact of their collapse.

Much of the literature on asset bubbles is based on securities markets. It is important to recognise the differences between the property market and securities markets, particularly how investment is financed.

The purpose of this paper is to report the results of a study concerning how fundamental-motivated investors, and their subsequent impact on the path of prices, affect the severity of price bubbles in an experimental laboratory asset market.

In a laboratory experiment, asset markets are manipulated by systematically replacing inexperienced human traders with automated traders programmed to submit bids and asks at fundamental value.

When traders in a market are automated to invest on fundamentals, deviations from fundamental value are initially suppressed, but reappear when automated traders cease to influence prices. A significant reduction in the severity of the resulting bubble may be attributed to the interaction of automated traders and humans through the initial path of prices when controlling for changes in liquidity. This reduction corresponds to reduced autocorrelation in the time series of returns.

This paper represents the first attempt (to the authors’ knowledge) to extend the intervention approach of the seminal paper by Smith et al. (1988) to systematically study the extent to which manipulation of initial path of prices impacts the formation and magnitude of bubbles in the laboratory.

The purpose of this paper is to clarify the concept of bubble, what it means to explain a bubble and propose a list of bubble indicators.

The paper is based on a literature review and some philosophical ideas to derive conclusions for the problems studied.

A price bubble should be defined only in relation to the development of prices: a dramatic increase immediately followed by a dramatic fall. The traditional definition in terms of prices not determined by fundamentals is problematic primarily because the concept “fundamentals” is vague. A bubble can never be explained by a single factor, but is the result of the interaction of a number of factors. The explanatory factors proposed are used to derive a set of indicators working as warning signals whether a dramatic increase in prices will be followed by a dramatic fall. The list developed covers, for example, interest costs in relation to household incomes, the elasticity of supply, price expectations and credit conditions.

Both the explanatory framework and the list of indicators should be seen as preliminary and the starting point for further development through empirical testing.

A developed list of bubble indicators could be useful for a number of actors, e.g. banks and authorities responsible for monitoring financial stability.

The contribution is a clearer and more useful concept of bubble, a clearer separation of the question whether bubbles exist and how they should be explained. The proposed list of indicators goes far beyond earlier indicators.

The purpose of this paper is to detect the existence of price bubbles and examine the possible contributing factors that associate with price bubble occurrences in China agricultural commodity markets.

Using recently developed rolling window right-side augmented Dickey–Fuller test, we first detect the dates of price bubbles in China's two important agricultural commodity markets, namely corn and soybeans. Then, we use a penalized maximum likelihood estimation of a multinomial logistic model to estimate the contributing factors of price bubbles in both markets, respectively.

Results from the bubble detection indicate that price bubbles account for 5.48% (3.91%) of the studied periods for corn (soybeans). More importantly, we find that market liquidity and speculation have opposite effects on the occurrences of bubbles in the corn and soybeans market. World stocks-to-use and exchange rates affect the occurrences of bubbles in a different way for each commodity, as well. Price bubbles are more likely associated with strong economic activity, high interest rates and low inflation levels.

This is the first study considering commodity-specific features into the formation of price bubbles. Through accurately identifying the bubble dates and fixing the estimation bias of rare events models, this study enables us to obtain robust results for each commodity. The results imply that China's corn and soybeans market respond differently to the speculative activity and external shocks from international markets. Therefore, future policy regulations on commodity markets should focus on more commodity-specific factors when aiming at avoiding bubble occurrences.

We tested for evidence of stock price bubbles in the Malaysian stock market from 1978 to 2004. Four different tests were used namely excess volatility tests, unit root/co-integration tests, duration dependence tests, and the intrinsic bubbles model. All four tests indicate that during the sample period, there was evidence of stock price bubbles. All tests results conform to the theoretical literature on asset price bubbles except for the results on the intrinsic bubbles model, which concludes that Malaysian investors under react to information on dividends. We find this result hardly surprising as anecdotal evidence does indicate that Malaysian investors place more importance on capital gains as compared to dividends. Although we do not go into a debate on whether authorities should be prick the bubble to stem its negative effects, we argue that transparent information dissemination will ensure that the stock market becomes more efficient in pricing stocks.

This paper aims to investigate the presence of a housing bubble using Swedish data from 1986Q1-2016Q4 by using various methods.

First, the authors use affordability indicators and asset-pricing approaches, including the price-to-income ratio, price-to-rent ratio and user cost, supplemented by a qualitative discussion of other factors affecting house prices. Second, the authors use cointegration techniques to compute the fundamental (or long-run) price, which is then compared with the actual price to test the degree of Sweden’s housing price bubble during the studied period. Third, they apply the univariate right-tailed unit root test procedure to capture bursting bubbles and to date-stamp bubbles.

The authors find evidence for rational housing bubbles with explosive behavioral components beginning in 2004. These bubbles do not continuously diverge but instead periodically revert to their fundamental value. However, the deviation is persistent, and without any policy correction, it takes decades for real house prices to return to equilibrium.

The policy implication is that monetary policy designed to contain mortgage demand and thereby prevent burst episodes in the housing market must address external imbalances, as revealed in real exchange rate undervaluation. It is unlikely that current policies will stop the rise of house prices, as the growth of mortgage credit, improvement in Sweden’s international competitiveness and the path of interest rates are much more important factors.

The purpose of this paper is to test for bubbles in the US hard red spring (HRS) wheat market from 2004 to 2014, with particular focus on 2007-2008 when the market experienced record-high price volatility.

The authors apply a recently developed bubble testing procedure to cash, rolling nearby futures contract, and individual futures contract prices of HRS wheat sampled at daily, weekly, and monthly frequencies. Two critical value (CV) sequences are derived to date-stamp bubbles, one from Monte Carlo simulations, and the other from recursive wild bootstrap procedure.

The authors find that regardless of the price series adopted, sampling frequency chosen, or CVs used, bubbles account for only a small fraction of the HRS wheat price behavior during 2004-2014. However, much sharper differences are detected regarding the key policy question of bubble behavior during 2007-2008. Individual futures contract prices during this period suggest only a minimal number of bubble days, while rolling nearby futures and cash prices indicate bubbles lasting much longer. Since theory suggests that prices for individual futures contracts are more likely to provide a clearer test of bubble components, the authors conclude there is little evidence that the spike in spring wheat prices to $25 per bushel in 2007-2008 was a bubble.

This paper is the first in the literature to examine the sensitivity of bubble testing to different types of data, sampling frequencies, and inference procedures.

This paper aims to explore principal drivers affecting prices in the Australian housing market, aiming to detect the presence of housing bubbles within it. The data set analyzed covers the past two decades, thereby including the period of the most recent housing boom between 2012 and 2015.

The paper describes the application of combined enhanced rigorous econometric frameworks, such as ordinary least square (OLS), Granger causality and the Vector Error Correction Model (VECM) framework, to provide an in-depth understanding of house price dynamics and bubbles in Australia.

The empirical results presented reveal that Australian house prices are driven primarily by four key factors: mortgage interest rates, consumer sentiment, the Australian S&P/ASX 200 stock market index and unemployment rates. It finds that these four key drivers have long-term equilibrium in relation to house prices, and any short-term disequilibrium always self-corrects over the long term because of economic forces. The existence of long-term equilibrium in the housing market suggests it is unlikely to be in a bubble (Diba and Grossman, 1988; Flood and Hodrick, 1986).

The foremost contribution of this paper is that it is the first rigorous study of housing bubbles in Australia at the national level. Additionally, the data set renders the study of particular interest because it incorporates an analysis of the most recent housing boom (2012-2015). The policy implications from the study arise from the discussion of how best to balance monetary policy, fiscal policy and macroeconomic policy to optimize the steady and stable growth of the Australian housing market, and from its reconsideration of affordability schemes and related policies designed to incentivize construction and the involvement of complementary industries associated with property.

The authors' paper aims to deal with the question whether speculative bubbles are present in agricultural commodity prices.

The authors apply a regime switching regression model to test the hypothesis that agricultural prices contain periodically collapsing bubbles. Using daily futures prices for six agricultural commodities, the authors calculate net convenience yields from which price fundamentals are derived.

The authors discover pronounced deviations between observed prices and their fundamental values. However, they do not find evidence for the presence of periodically and partially collapsing speculative bubbles for five of six commodities. Except for soybeans, the signs and the significance of the estimated coefficients are not entirely in line with the predictions of the theoretical model.

The authors' study adds to the heated discussion on the impact of speculative behavior on agricultural commodity prices. So far, most contributions in the literature either use theoretical arguments for the (non‐) existence of bubbles or apply indirect tests which are plagued by low statistical reliability. In contrast, the authors apply a direct test. They find that the outcome of empirical bubble tests depends on the considered bubble type and on the testing procedure. In view of these ambiguities, definite statements on the presence of speculative bubbles as well as demands for limitations of speculative positions in commodity futures markets should be carefully reconsidered.