scholarly journals Using State and Metropolitan Area House Price Cycles to Interpret the U.S. Housing Market

2006 ◽  
Author(s):  
Yolanda K. Kodrzycki ◽  
Nelson Gerew
Keyword(s):  
Housing Market ◽  
Metropolitan Area ◽  
House Price ◽  
The U.S

scholarly journals International Real Estate Review

2018 ◽  
Vol 21 (2) ◽  
pp. 251-274
Author(s):  
Yuming Li ◽  
◽  
Jing Yang ◽  
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
House Price ◽  
Excess Risk ◽  
Single Family ◽  
Price Changes ◽  
The Real Estate ◽  
Long Run ◽  
Short Run ◽  
The U.S

We examine the relation between risk and returns in the U.S. residential housing market. We find that the risk of house price changes and the magnitude relative to the risk of income changes vary with economic conditions. We measure the excess risk of house price changes by adjusting for the risk of income changes and economic variables associated with the real estate and financial sectors of the economy, and find a significant and positive relation between house price changes and excess risk. We also find that excess risk has significantly adverse effects on the short-run momentum and long-run reversal of house price changes across metro areas, thus implying that excess risk induces price rigidity and helps to explain for the serial correlations in price changes in the U.S. single-family housing market.

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.

A systematic analysis of the spatial migration patterns and the linkages between market components in Greater Manchester, United Kingdom

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Le-Vinh-Lam Doan ◽  
Adipandang Yudono
Keyword(s):  
Housing Market ◽  
Metropolitan Area ◽  
Systems Approach ◽  
House Price ◽  
Market Area ◽  
Systematic Analysis ◽  
Migration Patterns ◽  
Content Type ◽  
Price Data ◽  
Large Metropolitan Area

Purpose This paper aims to bring together research on housing market area, submarket and household migration into a systems approach that helps us gain a better understanding of the structure and dynamics of a housing market and identify housing problems for a large metropolitan area. Design/methodology/approach The paper uses a geographic information system (GIS)-based method with simple quantitative techniques, including spatial analysis, location analysis, house price clustering and cross-tabulation. The analysis is based on migration data from the 2011 Census, house price data from the Land Registry in 2011 for Greater Manchester at the ward level and the output areas level. Findings The results show that different submarkets and housing market areas had different patterns of spatial migration and connections with other areas. Through a systematic analysis of migration and house price in combination, it also found a close connection between destination submarkets and the ages of migrants and identified specific problematic patterns for a large metropolitan area. Research limitations/implications The interactions between the owner-occupied sector and the social and private rented sectors are arguably an important omission from the analysis. Also, it is acknowledged that clustering ward units based on price differentials is subject to distortions in terms of specification, size and shape. Moreover, the use of the large samples may result in very small p-values, leading to the problem of the rejection of the predefined hypothesis. Practical implications A systematic analysis of migration and house price in combination may be used to gain a better understanding of the housing market dynamics and identify housing problems systematically for a large metropolitan. It may help to identify low-demand areas, high-demand areas and assist planners with decisions in allocating suitable land for new housing constructions. Social implications The GIS-based method introduced in the paper could be considered as an effective approach to provide a better basis for determining policy interventions and public investment designed to allocate land resources effectively and improve transport systems to change existing problematic migration patterns. Originality/value This paper fills a gap in the international literature in relation to adopting a systems approach that analyses migration and house price data sets in combination to systematically explore migration patterns and linkages and identify housing problems for a large metropolitan area. This systems approach can be applied in any metropolitan area where migration and house price data are available.

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.

Chasing Trends in the U.S. Housing Market

2011 ◽  
Author(s):  
Roy R. P. Kouwenberg ◽  
Remco C. J. Zwinkels
Keyword(s):  
Housing Market ◽  
The U.S

scholarly journals Speculative housing markets and rent control: insights from nonlinear economic dynamics

2021 ◽  
Author(s):  
Noemi Schmitt ◽  
Frank Westerhoff
Keyword(s):  
Housing Market ◽  
Housing Stock ◽  
House Price ◽  
Housing Markets ◽  
Market Model ◽  
Market Dynamics ◽  
Rent Control ◽  
Forecasting Accuracy ◽  
Expectation Formation ◽  
Rent Level

AbstractWe propose a novel housing market model to explore the effectiveness of rent control. Our model reveals that the expectation formation and learning behavior of boundedly rational homebuyers, switching between extrapolative and regressive expectation rules subject to their past forecasting accuracy, may create endogenous housing market dynamics. We show that policymakers may use rent control to reduce the rent level, although such policies may have undesirable effects on the house price and the housing stock. However, we are also able to prove that well-designed rent control may help policymakers to stabilize housing market dynamics, even without creating housing market distortions.

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