Housing Bubble Research Articles

Health Impact Assessment in protected areas: a proposal for urban contexts in Brazil.

The use of Health Impact Assessment (HIA) in the establishment of an urban protected area can enhance the positive impacts and mitigate the negative impacts resulting from its implementation. Brazil hosts some of the most important biodiversity hotspots in the world and the HIA may benefit biodiversity and human health. These areas are commonly created without any preceding survey to assess their impacts on health. Protected areas located in urban zones are essential to maintain environmental balance and quality of life in cities. It promotes positive impacts on health, providing ecosystem services and salutogenic benefits. However, they can generate negative impacts such as the violation of human rights, property speculation, spread of vectorial diseases, and psychosocial stress. Based on the identification of the potential impacts of urban protected areas on health and best practices, this qualitative and exploratory study justifies the use of HIA in urban protected areas, especially in the Brazil, and indicates the main elements for the construction of a methodological approach to contribute to the Sustainable Development Goals and one of its alternatives, the Buen Vivir approach.

House Prices and Consumption: A New Instrumental Variables Approach

We introduce a novel Bartik-like instrument for house prices consisting of the local composition of housing characteristics interacted with aggregate changes in the marginal prices of these characteristics. Using household-level panel data, we estimate elasticities of nondurable consumption expenditures with respect to house prices of around 0.1. These consumption effects are concentrated among the young and those most likely to be facing tight borrowing constraints. A decomposition shows that identifying variation in the instrument is associated with times and locations where house prices have varied the most: during the housing bust of the mid-2000s and in the western United States. (JEL D12, E21, G51, R21, R31)

Did Mortgage Investors Price Regional Housing Bubbles? A Tale of Two Markets

Did Mortgage Investors Price Regional Housing Bubbles? A Tale of Two Markets

Reassessing the Role of Supply and Demand on Housing Bubble Prices

Reassessing the Role of Supply and Demand on Housing Bubble Prices

A Decade and 5 Years Later: The 2008 Housing Bubble and the Nigerian Economy

A Decade and 5 Years Later: The 2008 Housing Bubble and the Nigerian Economy

PSY 검정을 활용한 지역별 아파트가격 거품과 원인에 대한 분석

This study examines the timing of the boom and bust of bubbles in South Korea’s apartment market by region using the test developed by Phillips et al. (2015a, 2015b). The study also identifies the factors causing housing bubbles using ordinary least squares (OLS) and probit models. The sample covers the period from January 2000 to June 2022, comprising 270 monthly observations. The main results of this study are as follows. First, the generalized sup Augmented Dickey–Fuller test results indicate that housing bubbles partially existed in all five regions. Second, the bubble date stamping shows some differences across regions. Third, OLS results indicate that although housing bubbles are inversely related to the loan-to-deposit ratio (LDR), interest rate (IR), and stock index (SI), they are positively associated with the producer price index (PPI), the exchange rate of US dollar to Korean won (ER), and the total amount of interim payment in the construction sector (TIP). Fourth, probit results suggest that the probability of housing bubbles is influenced by PPI, LDR, IR, SI, ER, and TIP in order of magnitude.

Improving the Process of Early-Warning Detection and Identifying the Most Affected Markets: Evidence from Subprime Mortgage Crisis and COVID-19 Outbreak-Application to American Stock Markets.

Stock-market-crash predictability is of particular interest in the field of financial time-series analysis. Famous examples of major stock-market crashes are the real-estate bubble in 2008 and COVID-19 in 2020. Several studies have studied the prediction process without taking into consideration which markets might be falling into a crisis. To this end, a combination analysis is utilized in this manuscript. Firstly, the auto-regressive estimation (ARE) algorithm is successfully applied to electroencephalography (EEG) brain data for detecting diseases. The ARE algorithm is employed based on state-space modelling, which applies the expectation-maximization algorithm and Kalman filter. This manuscript introduces its application, for the first time, to stock-market data. For this purpose, a time-evolving interaction surface is constructed to observe the change in the surface topology. This enables tracking of the stock market's behavior over time and differentiates between different states. This provides a deep understanding of the underlying system behavior before, during, and after a crisis. Different patterns of the stock-market movements are recognized, providing novel information regarding detecting an early-warning sign. Secondly, a Granger-causality time-domain technique, called directed partial correlation, is employed to infer the underlying interconnectivity structure among markets. This information is crucial for investors and market players, enabling them to differentiate between those markets which will fall in a catastrophic loss, and those which will not. Consequently, they can make successful decisions towards selecting less risky portfolios, which guarantees lower losses. The results showed the effectiveness of the use of this methodology in the framework of the process of early-warning detection.

House price dynamics under lower leverage: the case of metropolitan cities in India

PurposeThis paper aims to examine the dynamics of house prices in metropolitan cities in an emerging economy. The purpose of this study is to characterise the house price dynamics and the spatial heterogeneity in the dynamics.Design/methodology/approachThe author explores spatial heterogeneity in house price dynamics, using data for 35 Indian cities with a million-plus population. The research methodology uses panel econometrics allowing for spatial heterogeneity, cross-sectional dependence and non-stationary data. The author tests for spatial differences and analyses the income elasticity of prices, the role of construction costs and lending to the real estate industry by commercial banks.FindingsLong-term fundamentals drive the Indian housing markets, where wealth parameters are stronger than supply-side parameters such as construction costs or availability of financing for housing projects. The long-term elasticity of house prices to aggregate household deposits (wealth proxy) varies considerably across cities. However, the elasticity estimated at 0.39 is low. The highest coefficient is for Ludhiana (1.14), followed by Bhubaneswar (0.78). The short-term dynamics are robust and show spatial heterogeneity. Short-term momentum (lagged housing price changes) has a parameter value of 0.307. The momentum factor is the crucial dynamic in the short term. The second driver, the reversion rate to long-term equilibrium (estimated at −0.18), is higher than rates reported from developed markets.Research limitations/implicationsThis research applies to markets that require some home equity contributions from buyers of housing services.Practical implicationsStakeholders can characterise stable housing markets based on long-term fundamental value and short-run house price dynamics. Because stable housing markets benefit all stakeholders, weak or non-existent mean reversion dynamics may prompt the intervention of policymakers. The role of urban planners, and local and regional governance, is essential to remove the bottlenecks from the demand side or supply side factors that can lead to runaway prices.Originality/valueExisting literature is concerned about the risk of a housing bubble due to relaxed credit norms. To prevent housing market bubbles, some regulators require higher contributions from home buyers in the form of equity. The dynamics of house prices in markets with higher owner equity requirements vary from high-leverage markets. The influence of wealth effects is examined using novel data sets. This research, documents in an emerging market context, the observations cited in low-leverage developed markets such as Germany and Japan.

Lenders’ pricing strategy: Do neighborhood risks matter?

AbstractThis article explores the different pricing strategies of lenders who originate both government‐sponsored enterprise (GSE) and non‐GSE loans. We find that conditional on loan and borrower characteristics and some observable local economic factors, mortgage rates on GSE loans vary significantly across regions. However, we observe no sizable regional variation in loan amounts or default risk. By contrast, the mortgage rates on non‐GSE loans depend almost entirely on borrowers and loan characteristics. In addition, we find that spatial variations in GSE mortgage rates are highly responsive to regional prepayment risk. Our results are robust to various controls for neighborhood characteristics, including regional‐level bank competition, borrower accessibility to mortgages, and household income levels. Overall, the findings offer a novel insight into how lenders adjust pricing strategies in response to a changing lending environment. The results provide implications relating to the present and imminent dangers of housing bubbles and the intensified refinancing wave following the COVID‐19 pandemic.

Commercial‐to‐residential land‐use conversion and residential recentralization in large cities

AbstractI examine the long‐term impact of a real estate bubble on the land‐use patterns of Tokyo and Osaka from 1980 to 2003 and find that fluctuations in land prices reflected changing demand for commercial land relative to that for residential land, which, in turn, affected housing supply and residential location choices. During the real estate bubble, land developers favored commercial over residential development because the perceived productive value of commercial land increased sharply. Thus, daytime population in central cities increased and residential population fell. During the economic downturn, however, the demand for commercial space fell, houses were favored by land developers and residents were recentralized. My causal estimates show that the commercial‐to‐residential land‐use conversion can explain approximately 9% to 16% of the housing starts after the bubble burst in Tokyo and Osaka, and their populations would have been reduced by 2% to 3% otherwise. The effect is more prominent in their central business districts. My findings provide a novel explanation for the recent changes in central neighbourhoods.

Determinants of Residential Investment Growth Rate in the US Economy (1992–2019)

ABSTRACT The leading role of residential investment in the business cycles is a robust stylized fact for the US economy. The housing bubble of the 2000s has increased interest in the macroeconomic relevance of this expenditure. However, there is still controversy surrounding its determinants. This article is an attempt to fulfill this gap. We propose to combine mortgage interest rate and house price inflation — two of the most relevant variables according to the literature — in a single index: houses’ own-rate of interest. This index represents the real cost of buying houses, so we expect a negative relationship with the growth rate of residential investment. Regarding the US economy from 1992 to 2019, we find a unidirectional negative correlation between houses’ own-rate of interest and residential investment growth rate in the long run. In the short-run adjustment process, we report no statistically significant effect of residential investment growth rate on houses’ own- rate of interest. Our results are robust to lag order specification and show that houses own-rate of interest explains more than half of the variability of residential investment rate of growth.

Real Estate Bubble Resolution with Chinese Characteristics: Integrate Fragmented Vacant Resources

The bursting of Japan's real estate bubble in the late 1990s has directly brought a devastating blow to the Japanese economy. Nowadays, China is enjoying the dividend brought by the rapid growth of the real estate industry. At the same time, we must always be vigilant against the possible harm of the bursting of the real estate bubble. This paper focuses on how to integrate the fragmented vacant resources of real estate to resolve the real estate bubble with Chinese characteristics and realize the soft landing of the real estate bubble, so as to avoid the impact of the concentrated burst of the real estate bubble on the economy.

Prospecting Housing Bubbles in Malaysia

Abstract There have been extensive studies pertaining on bubble detection in literature, though very few investigate the Malaysian residential property market. The inflated housing market, however, has sparked widespread public anxiety and there has been a proliferation of comments and forecasts about the presence of housing bubbles in Malaysia throughout the last decade. The purpose of this paper is to assess the housing bubbles in Malaysia by using empirical models in detecting Malaysian residential property bubbles. This research employed the Markov Switching (MS) model to investigate the housing bubbles for the Malaysian residential property market. The findings revealed Malaysian housing prices to be relatively stable over the period 2010 to 2019, with states of upheaval occurring only during short-lived periods. Overall, Malaysian housing prices were generally steady between 2010 and 2019, albeit this has shifted slowly in recent years as economic turmoil faded. This study provides empirical results to explain the situation of Malaysian house prices in the recent years.

Australia’s fiscal surplus: Child of a credit and real estate boom

AbstractFor several years leading up to the 2008 financial crisis, Australia registered a public surplus, and this was generally interpreted as the result of responsible fiscal policy. However, since the outbreak of that crisis, no such fiscal balance has again been attained, giving rise to a range of explanations from the political incapacity of governments to the weak economic behaviour characterising the post-crisis era. Noteworthy in any case is that analysts have failed to cite the importance of a factor that was key to reaching pre-crisis surpluses: the vertiginous growth of private debt. This work argues that it was precisely the intense granting of bank loans and consequent increased demand from the private sector that boosted economic activity and led to the generation of public income sufficient to feed the fiscal surpluses of that period. Indeed, according to the proposals of Wynne Godley, this would have been the only way to register a public surplus in a context of current account deficits, typical of the Australian economy. This paper considers whether Australian private debt played a significant role in achieving fiscal surplus by way of a review of the Australian real estate boom and public accounts from the 1990s onward, also estimating an econometric model of autoregressive vectors to explore the link between these two variables. The results obtained appear to corroborate the hypothesis: severe private borrowing contributed to Australia’s fiscal surpluses. This finding has significant implications for budgetary policy.

Exploring Cryptocurrency: How do individual behaviors in the financial world affect the potential of economic bubbles?

Cryptocurrency has made waves recently with its absurd increase in prices and volume. In this paper, I sought to understand, fundamentally, what factors could have helped its rise to the top. On the other hand, large ascents like this in the past have shown to be fatal, such as the housing market bubble of 2008. It struck me that cryptocurrency seemed to be heading down a similar path, especially with its unpredictable volatility and lack of practical usage in daily life. I explored some of the behavioral trends that are prevalent in finance, and used them to understand the 2008 bubble. I then further explored cryptocurrency behavior to draw comparisons, which were not lacking. By understanding what was behind cryptocurrency’s incredible rise and what behaviors and trends may factor into its volume, I was able to come to the conclusion that cryptocurrency is an asset class that treads dangerously along the lines of forming bubbles.

The Relationship between Monetary Policy and the Housing Bubble

Will monetary policy affect the price of housing and thus lead to a housing bubble? It is well known that the Fed's monetary policy decisions affect the U.S. and the world economy, guiding the direction of the economy through monetary policy adjustments. The real estate market has a huge volume and monetary policy has a profound impact on it. Loose monetary policy can lead to a boom in the real estate market, but too much of a boom can lead to a crisis. This article examines whether monetary policy affects housing bubbles by analyzing the views of Ben S. Bernanke and John B. Taylor and modeling the data to examine whether monetary policy causes housing bubbles.

The burden of the border: Precarious citizenship experiences in the wake of the Spanish housing crash

Beginning in the late 1990s, Spain experienced major changes in both its population structure and housing market. Between 1998 and 2008, the country’s immigrant population increased nearly 10-fold, from half a million foreign-born residents to five million, with the share of immigrant workers jumping from 2 per cent of all working-age people to 16 per cent. During this period, immigration accounted for the vast majority of Spain’s population growth, and this was reflected in the housing market by significant increases in the construction of new dwellings. However, the situation changed dramatically after the housing crash in 2008. In the wake of the global financial crisis of 2008 and the collapse of the country’s housing bubble, a massive wave of evictions made housing precariousness and displacement salient sociopolitical issues in Spain. Through multiple regression analyses of data from the Spanish Living Conditions Survey, this study shows that households headed by non-European Union citizens were significantly more likely than those headed by Spanish citizens to experience higher levels of housing precariousness and displacement pressure, net of housing arrears and other relevant factors. Non-European Union citizens were also significantly more likely to experience rent overburden and were found to pay higher rents than Spanish citizens for similar dwellings. By putting these results in dialogue with the ethnographic and theoretical literature on housing struggles and everyday bordering, this article argues that the differentially precarious citizenship status of migrants in Spain facilitates housing practices that multiply and thicken urban borders and facilitate rent extraction.

Local context and post‐crisis social venture creation

AbstractResearch summaryWe investigate the effects of local market and government failure on the creation of social ventures in the context of post‐crisis recovery during the period following the dot‐com crisis and ending before the housing bubble burst across all Ohio counties. Drawing on social embeddedness theory, we posit that social venture creation rates vary across local contexts and are higher in communities characterized by market and government failures. Longitudinal contextual data from 88 Ohio counties indicates that situations characterized by failures of both types are especially conducive to the creation of local social enterprises. We address the shortage of longitudinal quantitative studies focused on the emergence of social entrepreneurship and identify conditions where the relationship between local context and social venture creation is important.Managerial summaryThe purpose of this article is to examine how local context affects the rate of social venture creation in the United States. We study these rates in every county in Ohio in the aftermath of a crisis and find that local government responses and local market conditions singly and in combination lead to increased rates of local social venture creation. Fewer social ventures emerge when transfer (welfare) payments are high. However, rates rise in response to high unemployment, even when welfare payments are high, and are greater when welfare payments are low. This means the extent and type of local market and government failures influence the rate of local social venture creation. Findings advance the study of domestic social entrepreneurship in the aftermath of crises.

Swedish public and private housing companies’ access to the capital market for financing energy renovation

The financing of energy efficiency measures and renovations is key to reaching energy efficiency targets for the housing sector. The purpose of this article is to add the Swedish case of how capital market funds have become accessible and used by public and private housing companies, in particular for energy efficiency measures. The core of this article are interviews with representatives of Swedish housing companies made during the spring of 2021 with the purpose of mapping how public and larger private housing companies finance renovation and energy efficiency measures, and to what extent funds from the capital market are used for these purposes. In this article, we have found that capital market funds are commonly used by the Swedish public and the largest private housing companies. Bonds are less costly compared to bank loans, and green bonds are 0.02–0.03 percentage points less costly than conventional bonds. Furthermore, control systems that investigate the values of building portfolios as security for bonds are poor. A conclusion is that governmental control systems over the capital market issuing bonds for the housing market could be needed to avert future housing bubbles.

Long-run mechanism for house price regulation in China: Real estate tax, monetary policy or macro-prudential policy?

China has experienced rapid economic growth in recent decades. The benefits of economic growth are indisputable. However, risks are also generated that can jeopardize the sustainability of economic progress. Real estate bubbles, for example. The rapidly soaring house prices are one of the severe challenges in China in recent years. The real estate tax, monetary policy, and macro-prudential policy are the three main measures of the Chinese government to stabilize house prices. This paper studies the topic of which policy or policy portfolio can be an effective long-run mechanism of house price regulation by incorporating the real estate sector into the Dynamic stochastic general equilibrium (DSGE) model. Three important conclusions are drawn from the numerical simulation analysis based on the data of China. First, employing any policy portfolio can mitigate the fluctuation of house prices more effectively and decrease the loss of social welfare relatively compared to implementing a single policy. Second, the long-run regulating effect of the policy portfolio of monetary policy and macro-prudential policy can suppress the fluctuation of house prices in China while minimizing social welfare loss. Third, whether the real estate tax is combined with monetary policy or macro-prudential policy, the long-run regulating effect is insignificant. The real estate tax cannot be used to regulate house prices in China.