scholarly journals MONETARY LIQUIDITY AND THE BUBBLES IN THE U.S. HOUSING MARKET

2015 ◽  
Vol 19 (1) ◽  
pp. 1-12 ◽  
Author(s):  
I-Chun TSAI
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Asset Bubbles ◽  
Price Bubbles ◽  
Current Period ◽  
Housing Bubbles ◽  
The Mean ◽  
The U.S

Extant studies indicate that the excessive easing of monetary supplies can result in surplus liquidity, which can consequently facilitate the formation of asset bubbles. This study references data on house prices in the U.S. from January 1991 to August 2012 to explore the correlations between monetary liquidity and house price bubbles in the U.S. housing market. Fluctuations in house prices are classified as related to either fundamentals (the mean reversion behavior and responses to information of the current period) or bubbles (self-related behavior). Results show a significant correlation between the formation of housing bubbles and monetary supplies. Long-term easing of monetary supplies can cause housing marketing returns to deviate from fundamentals, which then results in an increase in continuous fluctuations in house prices and the likelihood of the formation of house price bubbles.

A look into German housing markets: A bubble call?

2018 ◽  
Vol 21 (4) ◽  
pp. 289-301
Author(s):  
Jan R. Kim ◽  
Gieyoung Lim
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Housing Markets ◽  
Present Value ◽  
Present Value Model ◽  
Price Bubbles ◽  
Steep Rise ◽  
Value Model ◽  
German Housing Market

The steep rise in German house prices in recent years raises the question of whether a speculative bubble has already emerged. Using a modified present-value model, we estimate the size of speculative house price bubbles in the German housing market. We do not find evidence for positive bubble accumulation in recent years, and interpret the current bullish run as reflecting the correction of house prices that have been undervalued for more than 10 years. With house prices close to their fair values as of 2018:Q1, our answer to the question is, ‘Not yet, but it is likely soon’.

scholarly journals The sources of house price change: identifying liquidity shocks to the housing market

2016 ◽  
Vol 9 (1) ◽  
pp. 98-120 ◽  
Author(s):  
Paloma Taltavull de La Paz ◽  
Michael White
Keyword(s):  
Monetary Policy ◽  
Housing Market ◽  
Error Correction ◽  
House Prices ◽  
Price Change ◽  
Housing Prices ◽  
House Price ◽  
Content Type ◽  
The Uk

Purpose The purpose of this paper is to examine the role of monetary liquidity in house price evolution through examining the Asset (housing) Inflation channel. It identifies the main channels of transmission affecting house prices from monetary supply channels to house price change, examining how the Asset Price channel transmits changes in M1 to housing prices in Spain and the UK. Design/methodology/approach The paper uses Vector Auto Regression (VAR) and Error Correction models to test the Asset Inflation channel in the UK and Spain from 1991 to 2013 in two steps. In the first step, the supply elasticity is estimated through the long-term relationship between house prices and stock supply. The second step estimates a Vector Error Correction (VEC) to explain house price dynamics conditioned on supply reactions. The latter is defined as a long-term inverse demand model where housing prices are controlled by fundamentals in each market. Models allow forecast testing using Choleski impulse responses methodology. Findings Several results are found. In the supply model, both countries show rapid convergence to equilibrium with a larger elasticity of supply in Spain than in the UK but with a short run effect of new supply on prices in the UK. Regarding the Asset Inflation Channel model, the paper finds evidence of the existence of a housing accelerator effect in Spain, but not in the UK where changes in liquidity fully impact house prices in one direction. Research limitations/implications Implications of findings are mainly to forecast the effects of Monetary Policy measures in different economies. Practical implications The model supports the evaluation of different impacts of monetary policy in territories. It shows that the same policy will have different impacts in different housing markets and therefore highlights the importance of examining each market separately to identify the appropriate policy interventions. Originality/value This is the first paper that estimates the impact of the Asset Inflation Channel on house prices that endogenises housing market conditions and compares effects and interrelationships in two different economies.

scholarly journals International Real Estate Review

2020 ◽  
Vol 23 (2) ◽  
pp. 267-308
Author(s):  
Are Oust ◽  
◽  
Ole Martin Eidjord ◽  
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Search Term ◽  
Housing Bubble ◽  
Search Terms ◽  
Search Volume ◽  
Google Search ◽  
The U.S

The aim of this paper is to test whether Google search volume indices can be used to predict house prices and identify bubbles in the housing market. We analyze the data that pertain to the 2006?2007 U.S. housing bubble, taking advantage of the heterogeneous house price development in both bubble and non-bubble states in the U.S. Using 204 housing-related keywords, we test both single search terms and indices that comprise search term sets to see whether they can be used as housing bubble indicators. We find that several keywords perform very well as bubble indicators. Among all of the keywords and indices tested, the Google search volume for ¡§Housing Bubble¡¨ and ¡§Real Estate Agent¡¨, and a constructed index that contains the twelve best-performing search terms score the highest at both detecting bubbles and not erroneously detecting non-bubble states as bubbles. A new housing bubble indicator may help households, investors, and policy makers receive advanced warning about future housing bubbles. Moreover, we show that the Google search outperforms the well-established consumer confidence index in the U.S. as a leading indicator of the housing market.

scholarly journals House Price Beliefs And Mortgage Leverage Choice

2018 ◽  
Vol 86 (6) ◽  
pp. 2403-2452 ◽  
Author(s):  
Michael Bailey ◽  
Eduardo Dávila ◽  
Theresa Kuchler ◽  
Johannes Stroebel
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Heterogeneous Beliefs ◽  
The Other ◽  
Cross Sectional ◽  
Financial Decisions ◽  
The Relationship ◽  
The U.S

Abstract We study the relationship between homebuyers’ beliefs about future house price changes and their mortgage leverage choices. Whether more pessimistic homebuyers choose higher or lower leverage depends on their willingness and ability to reduce the size of their housing market investments. When households primarily maximize the levered return of their property investments, more pessimistic homebuyers reduce their leverage to purchase smaller houses. On the other hand, when considerations such as family size pin down the desired property size, pessimistic homebuyers reduce their financial exposure to the housing market by making smaller downpayments to buy similarly-sized homes. To determine which scenario better describes the data, we investigate the cross-sectional relationship between house price beliefs and mortgage leverage choices in the U.S. housing market. We use plausibly exogenous variation in house price beliefs to show that more pessimistic homebuyers make smaller downpayments and choose higher leverage, in particular in states where default costs are relatively low, as well as during periods when house prices are expected to fall on average. Our results highlight the important role of heterogeneous beliefs in explaining households’ financial decisions.

scholarly journals Is the Australian housing market in a bubble?

2018 ◽  
Vol 13 (1) ◽  
pp. 77-95 ◽  
Author(s):  
Justine Wang ◽  
Alla Koblyakova ◽  
Piyush Tiwari ◽  
John S. Croucher
Keyword(s):  
Interest Rates ◽  
Housing Market ◽  
House Prices ◽  
National Level ◽  
Policy Implications ◽  
Data Set ◽  
Content Type ◽  
Housing Boom ◽  
Housing Bubbles

Purpose 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. Design/methodology/approach 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. Findings 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). Originality/value 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.

scholarly journals The role and significance of planning in the determination of house prices in Australia: Recent policy debates

2021 ◽  
pp. 0308518X2198894
Author(s):  
Peter Phibbs ◽  
Nicole Gurran
Keyword(s):  
Land Use ◽  
Housing Market ◽  
Land Use Planning ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Evidence Base ◽  
Urban Housing ◽  
Price Inflation ◽  
Depth Analysis

On the world stage, Australian cities have been punching above their weight in global indexes of housing prices, sparking heated debates about the causes of and remedies for, sustained house price inflation. This paper examines the evidence base underpinning such debates, and the policy claims made by key commentators and stakeholders. With reference to the wider context of Australia’s housing market over a 20 year period, as well as an in depth analysis of a research paper by Australia’s central Reserve Bank, we show how economic theories commonly position land use planning as a primary driver of new supply constraints but overlook other explanations for housing market behavior. In doing so, we offer an alternative understanding of urban housing markets and land use planning interventions as a basis for more effective policy intervention in Australian and other world cities.

A multifractal detrended fluctuation analysis of housing market: a role of financial crises in developed economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syed Ali Raza ◽  
Nida Shah ◽  
Muhammad Tahir Suleman ◽  
Md Al Mamun
Keyword(s):  
Financial Crisis ◽  
Housing Market ◽  
Market Efficiency ◽  
House Price ◽  
Fluctuation Analysis ◽  
Content Type ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Long Run ◽  
Before And After

Purpose This study aims to examine the house price fluctuations in G7 countries by using the multifractal detrended fluctuation analysis (MF-DFA) for the years 1970–2019. The study examined the market efficiency between the short-term and long-term in the full sample period, before and after the global financial crisis period. Design/methodology/approach This study uses the MF-DFA to analyze house price fluctuations. Findings The findings confirmed that the housing market series are multifractal. Furthermore, all the markets showed long-term persistence in both the short and long-term. The USA is identified as the most persistent house market in the short run and Japan in the long run. Moreover, in terms of efficiency, Canada is identified as the most efficient house market in the long run and the UK in the short run. Finally, the result of before and after the financial crisis period is consistent with the full sample result. Originality/value The contribution of this study in the literature is fourfold. This is the first study that has examined the house prices efficiency by using the MF-DFA technique given by Kantelhardt et al. (2002). Previously, the house market prices and efficiency has been investigated using generalized Hurst exponent (Liu et al., 2019), Quantile Regression Approach (Chae and Bera, 2019; Tiwari et al., 2019) but no study to the best of the knowledge has been done that has used the MF-DFA technique on the housing market. Second, this is the first study that has focused on the house markets of G7 countries. Third, this study explores the house market efficiency by dividing the market into two periods i.e. before and after the financial crisis. The study strives to investigate if the financial crisis determines the change in the degree of market efficiency or not. Finally, the study gives valuable insights to the investors that will help them in their investment decisions.

scholarly journals Are There Any Housing Bubbles in Turkey?

2021 ◽  
Author(s):  
Özge Korkmaz ◽  
Ebru Çağlayan Akay ◽  
Hoşeng Bülbül
Keyword(s):  
Housing Market ◽  
House Prices ◽  
Housing Prices ◽  
Housing Price ◽  
Economic Fundamentals ◽  
The Past ◽  
Price Increases ◽  
Long Time ◽  
Housing Bubbles ◽  
Turkish Lira

It is very important that the housing market, which meets the most basic need of people is needed for shelter from the past to the present, has a stable structure. The instability structure of the housing market is generally associated with the presence of housing bubbles. The deviation of housing prices from their basic value and not being able to be explained by economic fundamentals leads to the formation of housing bubbles. Housing bubbles can lead to permanent losses, as it may take a long time to return to normal prices. For Turkey as a developing country, it is important to identify an unstable structure in house prices discuss the basic economic factors related to this. After the global increases in housing prices, inflation, and depreciation in the Turkish lira, Turkey has become the country with the highest housing price increases globally in 2020. In the study, the presence of bubbles in the housing market for Ankara, Izmir, Istanbul, and Turkey in general, was investigated by SADF and GSADF unit root tests for the period 2010:01-2021:02. In this context, the study examines the presence of bubbles in housing prices for Ankara, Izmir, Istanbul, and Turkey in general, which are the three cities with the highest price increases. As a result of the study, the presence of bubbles in the housing market has been determined for Ankara, Istanbul, Izmir, and Turkey in general.

Rent or buy, what are the odds? Analysing the price-to-rent ratio for housing types within the Northern Ireland housing market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniel Lo ◽  
Michael James McCord ◽  
John McCord ◽  
Peadar Thomas Davis ◽  
Martin Haran
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Main Property ◽  
Property Market ◽  
Important Indicator ◽  
Content Type ◽  
Rental Market ◽  
Price Series ◽  
The Relationship

Purpose The price-to-rent ratio is often regarded as an important indicator for measuring housing market imbalance and inefficiency. A central question is the extent to which house prices and rents form part of the same market and thus whether they respond similarly to parallel stimulus. If they are close proxies dynamically, then this provides valuable market intelligence, particularly where causal relationships are evident. Therefore, this paper aims to examine the relationship between market and rental pricing to uncover the price switching dynamics of residential real estate property types and whether the deviation between market rents and prices are integrated over both the long- and short-term. Design/methodology/approach This paper uses cointegration, Wald exogeneity tests and Granger causality models to determine the existence, if any, of cointegration and lead-lag relationships between prices and rents within the Belfast property market, as well as the price-to-rent ratios amongst its five main property sub-markets over the time period M4, 2014 to M12 2018. Findings The findings provide some novel insights in relation to the pricing dynamics within Belfast. Housing and rental prices are cointegrated suggesting that they tend to move in tandem in the long run. It is further evident that in the short-run, the price series Granger-causes that of rents inferring that sales price information unidirectionally diffuse to the rental market. Further, the findings on price-to-rent ratios reveal that the detached sector appears to Granger-cause those of other property types except apartments in both the short- and long-term, suggesting possible spill-over of pricing signals from the top-end to the lower strata of the market. Originality/value The importance of understanding the relationship between house prices and rental market performance has gathered momentum. Although the house price-rent ratio is widely used as an indicator of over and undervaluation in the housing market, surprisingly little is known about the theoretical relationship between the price-rent ratio across property types and their respective inter-relationships.

scholarly journals Measuring heterogeneity of house price developments in Hungary, 1990–2016

2018 ◽  
Vol 68 (3) ◽  
pp. 377-414
Author(s):  
Ádám Banai ◽  
Nikolett Vágó ◽  
Sándor Winkler
Keyword(s):  
Time Series ◽  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Price Indices ◽  
Regional Heterogeneity ◽  
Economic Cycles ◽  
House Price Indices ◽  
Long Time ◽  
Index Family

This study presents the detailed methodology of generating house price indices for the Hungarian market. The index family is an expansion of the Hungarian housing market statistics in several regards. The nationwide index is derived from a database starting from 1990, and thus the national index is regarded as the longest in comparison to the house price indices available so far. The long time series allow us to observe and compare the real levels of house prices across economic cycles. Another important innovation of this index family is its ability to capture house developments by regions and settlement types, which sheds light on the strong regional heterogeneity underlying the Hungarian housing market.

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