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International Journal of Economics and Finance
This paper addresses an empirical puzzle in the housing bubble literature: models of market fundamentals perform poorly in explaining investor exuberance in housing even though, individually, many fundamentals have strong ability to predict explosive growth in real house prices. We explore two plausible sources for the poor performance: missing fundamentals and missing bubble dynamics. To shed light on the relative importance of these sources, we conduct a detailed two-step investigation of the housing markets in ten rich countries using models, methodologies and datasets that are similar to those employed in the existing literature. Our findings consistently show that the predictive ability of models of market fundamentals can be dramatically enhanced once missing dynamics of housing bubbles are properly accounted for. GSADF denotes Generalised Sup Augmented Dickey–Fuller test and SADF denotes Sup Augmented Dickey–Fuller test.
This study examines some key aspect of ten Asian housing markets over the period from 1980 to 2014. Equilibrium or fundamental house price indices are determined by the interaction of supply and demand through panel ordinary least square (OLS) and individual country OLS techniques. On the demand side, the drivers of house price indices include interest rate, demography, and credit availability. On the supply side, domestic liquidity as well as global liquidity have large effects on housing supply. In the short run, rational expectations about changes in fundamentals including income growth, population and stock index explain much of the housing fluctuation. During the housing boom periods, investors seem to overreact to observable changes in fundamentals. Although fundamental factors leave a large share of changes in real estate prices unexplained, actual house price indices are driven largely by demand-side and supply-side fundamentals while the bubble components are driven by the irrational expectations of sustained price increases. The findings suggest changes in, especially for housing overvaluation in the Asian economies. The model of rational expectation explains around 60 percent of changes in house prices. During the last twenty years, some economies such as Hong Kong or Singapore have experienced more volatile than cycling components.
Atlantic Economic Journal, 2017
This paper provides empirical evidence on the interrelation between residential property prices and business cycle relationship by combining panel data and time series methodologies to offer a contextual framework on the residential property prices for 7 advanced OECD economies. Initially, we apply a panel methodological framework using quarterly data over the period 2002-2015 that builds upon the interaction of economic fundamentals with financial variables. Additionally, novel evidence is provided on the detection of property price bubbles that have been manifested in each individual country of the sample through the use of time series methodologies developed by Phillips, Wu and Yu (2011) and Phillips, Shi and Yu (2015). The short-run dynamic panel framework provides a robust exploratory platform shedding light on the determinants of property prices (real gdp, bank credit growth, long-term bond yields and real effective exchange rate) whilst the bubble detection methodologies provide evidence on the impact of credit-driven economies on the propagation of housing booms and can serve as warning signals of potential formation of housing bubbles jointly with economic fundamentals, other factors and methodologies.
SAGE Open , 2021
There is an upward trend in housing prices around the world, and Pakistan is no different either; being a developing county, it is facing a rising population. Due to this, the demand for housing has exceeded its supply and in turn rinsing their prices. This study is the first attempt to identify housing price bubbles in Pakistan from 1972 to 2018. The data are available on an annual basis, and to capture the price volatility, it is converted into a quarterly and monthly format. The Generalized Supremum Augmented Dickey-Fuller (GSADF) test is used to detect multiple bubbles. Monthly data showed more episodes of bubbles than yearly and quarterly data; in each case, it reported two periods of bubble episodes. The results of the house price dynamics suggest a higher return with high risk in the short run.
2017
This paper provides empirical evidence on the interrelation between residential property prices and business cycle relationship by combining panel data and time series methodologies to offer a contextual framework on the residential property prices for 7 advanced OECD economies. Initially, we apply a panel methodological framework using quarterly data over the period 2002-2015 that builds upon the interaction of economic fundamentals with financial variables. Additionally, novel evidence is provided on the detection of property price bubbles that have been manifested in each individual country of the sample through the use of time series methodologies developed by Phillips, Wu and Yu (2011) and Phillips, Shi and Yu (2015). The short-run dynamic panel framework provides a robust exploratory platform shedding light on the determinants of property prices (real gdp, bank credit growth, long-term bond yields and real effective exchange rate) whilst the bubble detection methodologies prov...
We employ recently developed cross-sectionally robust panel data tests for unit roots and cointegration to find whether house prices reflect house related earnings. We use U.S. data for Metropolitan Statistical Areas, with house price measured by the weighted-repeated-sales index and cash-flows by market tenants' rents. In our full sample period, an error-correction model is not appropriate, i.e. there is a bubble. We then combine overlapping 10-year periods, price–rent ratios, and the panel data tests to construct a bubble indicator. The indicator is high for the late 1980s, early 1990s and since the late 1990s. Finally, evidence based on panel data Granger causality tests suggests that house price changes are helpful in predicting changes in rents and vice versa.
The paper investigates in how far lax monetary policy (defined as deviations from prescriptive monetary policy rules or past trends) and/or financial innovation can be seen as a cause for housing price bubbles in industrialized countries. From a theoretical perspective, it is found that there are hardly any clearly formulated economic models which assign a role to lax monetary policy in bubble formation while there are a number of models which assign a role to financial innovation or liberalization. In the empirical part, the paper first presents cross-country-time-series SUR regressions for a sample of 16 industrialized countries. According to the results, there is no robust significant role for the relevance of loose monetary policy, measured by deviations from the Taylor rule. Instead, deviations from the past trend of the real policy rate affect housing prices, but the size of the effect depends on the regulation and development of the financial sector. In a third step, three case studies of the United States, Austria and the United Kingdom are presented, representing countries which have experienced a) lax monetary policy and a bubble b) lax monetary policy without a bubble and c) no deviation from the Taylor rule and a bubble. The case studies hint that specific changes in regulations played a role for the emergence or absence of bubbles, yet these regulations might not be appropriately covered by standard quantitative indicators for financial market (de-)regulation.
SSRN Electronic Journal, 2000
In this paper, we construct the country-specific chronologies of the house price bubbles for 12 OECD countries over the period 1969:Q1-2010:Q2. These chronologies are obtained using a combination of a fundamental and a filter approaches. The resulting speculative bubble chronology is the one that provides the highest concordance between these two techniques. In addition, we suggest an early warning system based on three alternative approaches: signalling approach, logit and probit models. It is shown that the latter two models allow much more accurate predictions of the house price bubbles than the signalling approach. The prediction accuracy of the logit and probit models is high enough to make them useful in forecasting the future speculative bubbles in housing market. Thus, our method can be used by the policymakers in their attempts to timely detect the house price bubbles and attenuate their devastating effects on the domestic and world economy.
Real Estate Economics, 2008
This article examines the issues encountered in the modeling of market fundamentals during a period of extreme price behavior. The study analyzes the price behavior of the residential property market in Ireland using a number of alternative methodological approaches in the estimation of fundamental market value. Limitations in conventional models such as an inverted demand model are highlighted, in particular, with regard to diagnostic concerns and the static nature of the model. The use of an error correction framework provides more consistent and robust findings. The analysis does appear to indicate that a substantial premium over fundamental values developed in the Irish market during the late 1990s, reaching a peak in 1999 and 2000. However, in recent years, prices have largely been in line with fundamentals.
Pressacademia, 2018
Purpose-Housing markets are linked to macroeconomic and financial stability. The creation of different financial instruments on residence, the presentation of residence as an assurance, the impact of residence prices on saving and consumption through the wealth effect are some of the housing market and general economic interactions. Developments in the residential sector must be carefully monitored for financial stability. The residential sector has usually played an important role in the global economy and financial sector bubbles. It has been observed that the wealth effect created by the housing bubble surpasses the effect of the stock bubble and that the housing bubble explosion causes more economic devastation compared to the other assets bubbles. While housing markets are increasingly buried in financial markets, the connections between them have strengthened. Such a situation can cause financial crises as a way of extinguishment of a housing bubble. In the case of housing bubbles, bank balance sheets are generally more affected by real estate and it is more likely that the decline in real estate prices are transmitted to the other sectors of the economy with the credit channel. When the housing price bubble burst, the collapse in the financial system is also reflected in the real sector. In this study, with reference to the real housing price index and the real rent price index, it has been investigated whether there is the housing bubble in Turkey. Methodology-Sup ADF and Generalized SADF (GSADF) tests were used to determine the asset of bubbles and to determine when the housing bubbles had occured. The data set obtained in the study extends from January 2010 to November 2017. Findings-The results reveal empirical evidence on the absence of speculative bubbles in the Turkish housing market. Conclusion-There is no data with reference to housing price to say that there is the housing bubble in Turkey during the period under study. Turkey blocked the creation of the housing bubble in the period under review with corrections through its internal dynamics.
Journal of Asian Economics, 2013
This study uses a newly developed bubble detection method (Phillips, Shi and Yu, 2011) to identify real estate bubbles in the Hong Kong residential property market. Our empirical results reveal several positive bubbles in the Hong Kong residential property market, including one in 1995, a stronger one in 1997, another one in 2004, and a more recent one in 2008. In addition, the method identifies two negative bubbles in the data, one in 2000 and the other one in 2001. These empirical results continue to be valid for the mass segment and the luxury segment. However, the method finds a bubble in early 2011 in the overall market as well as in the mass segment but not in the luxury segment. This result suggests that the bubble in early 2011 in the Hong Kong real estate market came more strongly from the mass segment under the demand pressure from end-users of small-to-medium sized apartments. † We thank Dong He, Cho-hoi Hui, Peter Phillips and the participants of the 2012 SKBI Annual Conference for their comments on the paper.
SSRN Electronic Journal, 2000
This paper examines the evidence of real estate bubbles within Singapore's private residential market from 1978 to 2004. The determinants of real estate bubbles are also examined. The analysis generates two principle conclusions. First, using unit root tests and cointegration tests, we found evidence of explosive characteristics in the property price index as well as the accommodation index indicating the presence of real estate bubbles in the Singapore private residential market. However, in conducting a robustness check using the variance bounds test, fundamental property prices were just as volatile as actual observed prices. Therefore, evidence of real estate bubbles in Singapore's private residential market is inconclusive. Second, using polynomial distributed lag analysis, it was found that increases in domestic credit growth and growth in the Straits Times Index (STI) are related to the increase in the percentage deviation between actual property prices and calculated fundamental values. Real interest rates and Gross Domestic Product (GDP) growth were not significantly related to the deviation between actual and fundamental real estate prices.
2013
We investigate the cross-sectional distribution of house prices in the Greater Tokyo Area for the period 1986 to 2009. We find that size-adjusted house prices follow a lognormal distribution except for the period of the housing bubble and its collapse in Tokyo, for which the price distribution has a substantially heavier right tail than that of a lognormal distribution. We also find that, during the bubble era, sharp price movements were concentrated in particular areas, and this spatial heterogeneity is the source of the fat upper tail. These findings suggest that, during a bubble period, prices go up prominently for particular properties, but not so much for other properties, and as a result, price inequality across properties increases. In other words, the defining property of real estate bubbles is not the rapid price hike itself but an increase in price dispersion. We argue that the shape of cross sectional house price distributions may contain information useful for the detection of housing bubbles.
Economic Modelling, 2001
This paper attempts to conduct an empirical study for detecting misspecification errors and rational bubbles in the residential housing markets of Hong Kong. We focus on a fundamental model that defines market fundamental price as a sum of the expected present value of rental income, discounted at a constant rate of return. Testable implications for detecting misspecification errors andror price bubbles are explored through the flow and stock approaches. In addition, the paper attempts to identify the amount of misspecification and bubble components in the property price data of Hong Kong.
IT-Incidents Management & IT-Forensics, 2000
Journal of International Financial Markets, Institutions and Money, 2016
We conduct an econometric analysis of bubbles in housing markets in the OECD area, using quarterly OECD data for 18 countries from 1970 to 2013. We pay special attention to the explosive nature of bubbles and use econometric methods that explicitly allow for explosiveness. First, we apply the univariate right-tailed unit root test procedure of Phillips et al. (2012) on the individual countries price-rent ratio. Next, we use Engsted and Nielsen's (2012) co-explosive VAR framework to test for bubbles. We find evidence of explosiveness in many housing markets, thus supporting the bubble hypothesis. However, we also find interesting differences in the conclusions across the two test procedures. We attribute these differences to how the two test procedures control for cointegration between house prices and rent.
2016
The growth of financial market has taken centre stage in today’s world economy. It takes a quarter of a second to change the whole dynamics of an economy. The moment an asset price bubble and burst occurs, the whole economy may collapse. This paper makes an attempt to investigate the existence of housing price bubble by taking Malaysia as a case study. In Malaysia, the housing market is in its boom, naturally housing prices are sky high. There is no consensus in the literature about what is a housing price bubble. The method applied in this study are the standard time series techniques of cointegration, long-run structural modelling, vector error correction, variance decomposition method. To our knowledge, this is the first study on housing bubble based on demand and supply side variables, for a period of 17 years of data. Our findings tend to indicate that variables are cointegrated and market tends to correct any disequilibrium that exists over time. The results also imply that ho...
Journal of Economic Perspectives, 2005
We construct measures of the annual cost of single-family housing for 46 metropolitan areas in the United States over the last 25 years and compare them with local rents and incomes as a way of judging the level of housing prices. Conventional metrics like the growth rate of house prices, the price-to-rent ratio, and the price-to-income ratio can be misleading because they fail to account both for the time series pattern of real long-term interest rates and predictable differences in the long-run growth rates of house prices across local markets. These factors are especially important in recent years because house prices are theoretically more sensitive to interest rates when rates are already low, and more sensitive still in those cities where the long-run rate of house price growth is high. During the 1980s, our measures show that houses looked most overvalued in many of the same cities that subsequently experienced the largest house price declines. We find that from the trough of 1995 to 2004, the cost of owning rose somewhat relative to the cost of renting, but not, in most cities, to levels that made houses look overvalued.
In this study whether bubbles exist in the three biggest cities housing market, İstanbul (TR10), İzmir (TR31) and Ankara (TR51) which are important parts of Turkish housing market is investigated. Besides, SADF and GSADF unit root tests developed by Phillips et. al. (2011, 2012) is used in order to detect bubbles in the housing market in the period between January-2010 and June-2014. The results show that real estate bubbles do not exist in the Turkish housing market and price increases above the average are experienced only for the short terms, not over the long terms permanently. In this context, efficient market hypothesis is valid for Turkish housing market and it verifies that Turkish housing market experienced the 2008 Mortgage crisis rather slightly than many other countries. These findings indicate stability in the housing market by sustaining its correct house pricing policy after the crisis. Keywords: Real Estate Bubbles, Housing Market, SADF, GSADF, Turkey
This paper examines whether Malaysia is facing an impending housing bubble by using a graphical analysis, logical deduction and two statistical tests. Our research results are robust and supported by a three prone approach: Logical deduction working on the historical price trend based on most recent research findings on bubble; testing the stability of the price cycle and a statistical test modified and formulated in accordance with the Malaysian context to analyze the price trend in the local property market. We show that housing bubble burst is not imminent as yet in Malaysia which is in agreement with Bank Negara Malaysia Report. However, our findings reveal that Malaysia has been experiencing a continuous and increasingly steeper upward movement of house prices without breaks since mid-2009. Exuberant expectation of investment profit seems to be building up continuously, an indication of a strong likelihood of a housing bubble building up. Our findings call for the attention of the government to this development and to take necessary intervention measures.
The Journal of Real Estate Finance and Economics
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