Real house prices are growing strongly: Percentage change in real house price indexes from Q1-2008 to Q4-2018, s.a.

Purpose – The purpose of this paper is to analyse how London Interbank Offered Rate Index (LIBOR) and the spread between LIBOR and the base rate of interest as set by the Bank of England (BoE) influences the variation in house prices in the UK. Design/methodology/approach – This paper uses monthly data over a long time series, since 1986, to investigate the relationships between house price and LIBOR. Data are drawn from several different sources to include housing, financial and macro-economic variables. The time series is sub-divided into a series of splines based on stages in the economic and property market cycle. Both value-based and percentage change models are developed. Findings – The results show that BoE base/LIBOR margin variable has a strong positive and significant effect on house price; however, the percentage change model infers a weaker and inverse relationship. The spline analysis re-emphasised the significance of the BoE base/LIBOR margin variable. Where variation between base rates and LIBOR is reduced, a significant positive effect can be observed in the average house price; however, where significant variation exists, the BoE base/LIBOR margin has little effect and LIBOR itself becomes a significant driver. Research limitations/implications – The results highlight that the predictive qualities of the BoE base/LIBOR margin, as the contribution of this margin to the explanation of house price, exceeds both the base rate and LIBOR variables individually. Also highlighted is the contribution of unemployment to the explanation of house price. In both the value and percentage change models, unemployment is shown as a negative and highly significant contributor. Originality/value – Previous papers have demonstrated the important linkage between house price and interest rates, the originality in this paper lies in examining the impact of LIBOR and the spreads between LIBOR and base rate as key variables influencing variation in UK house prices.

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The resilience and realignment of house prices in the era of Covid-19*

Journal of European Real Estate Research ◽

10.1108/jerer-11-2020-0055 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

John V. Duca ◽

Martin Hoesli ◽

Joaquim Montezuma

Keyword(s):

Design Methodology ◽

House Prices ◽

House Price ◽

Behavioral Factors ◽

Content Type ◽

Downward Pressure ◽

Price Indexes ◽

Price Appreciation ◽

The Usa ◽

Rate Environment

Purpose The study aims to analyze the effects of the Covid-19 pandemic on house prices. Design/methodology/approach The authors start by discussing the possibility that house price indexes may not fully incorporate the effects of the pandemic as of yet. Against the background of the pandemic, the authors then analyze economic and behavioral effects affecting house prices. The authors also discuss how the linkages between tourism and house prices have been affected. The authors further present evidence of an emerging shift in preferences from urban locations to more peripheral ones. Findings The authors report variance in the evolution of house prices across countries at the onset of the pandemic, with locations depending heavily on tourism showing slower price appreciation while appreciation has firmed in other places. The authors argue that the resilience of house prices is not only because of the low-interest rate environment and government efforts to support firms and households, but also behavioral factors. In some locations, the price of condominiums has declined relative to the price of detached houses. This could indicate that wealthier households are seeking more space and larger units as a result of the crisis. There is also evidence of a downward pressure on rents, leading to increased price–rent ratios in the USA. Originality/value By considering both economic and behavioral factors, this paper provides for a better understanding of the resilience and realignment of house prices at the onset of the Covid-19 pandemic.

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

Environment and Planning A Economy and Space ◽

10.1177/0308518x21988942 ◽

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.

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Assessing the impacts of Airbnb listings on London house prices

Environment and Planning B Urban Analytics and City Science ◽

10.1177/23998083211001836 ◽

2021 ◽

pp. 239980832110018

Author(s):

James Todd ◽

Anwar Musah ◽

James Cheshire

Keyword(s):

Random Effects ◽

Rapid Growth ◽

House Prices ◽

Housing Prices ◽

House Price ◽

Positive Association ◽

Sharing Economy ◽

Local Context ◽

Fixed And Random Effects ◽

The World

Over the course of the last decade, sharing economy platforms have experienced significant growth within cities around the world. Airbnb, which is one of the largest and best-known platforms, provides the focus for this paper and offers a service that allows users to rent properties or spare rooms to guests. Its rapid growth has led to a growing discourse around the consequences of Airbnb rentals within the local context. The research within this paper focuses on determining impact on local housing prices within the inner London boroughs by constructing a longitudinal panel dataset, on which a fixed and random effects regression was conducted. The results indicate that there is a significant and modest positive association between the frequency of Airbnb and the house price per square metre in these boroughs.

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Money and credit during normal times and house price booms: evidence from time-frequency analysis

Empirica ◽

10.1007/s10663-019-09457-2 ◽

2019 ◽

Vol 47 (4) ◽

pp. 835-861

Author(s):

Maciej Ryczkowski

Keyword(s):

Great Recession ◽

House Prices ◽

House Price ◽

Industrialized Countries ◽

Time Frequency ◽

The Great Recession ◽

Time Period ◽

Price Boom ◽

The Us ◽

Short Run

Abstract I analyse the link between money and credit for twelve industrialized countries in the time period from 1970 to 2016. The euro area and Commonwealth Countries have rather strong co-movements between money and credit at longer frequencies. Denmark and Switzerland show weak and episodic effects. Scandinavian countries and the US are somewhere in between. I find strong and significant longer run co-movements especially around booming house prices for all of the sample countries. The analysis suggests the expansionary policy that cleans up after the burst of a bubble may exacerbate the risk of a new house price boom. The interrelation is hidden in the short run, because the co-movements are then rarely statistically significant. According to the wavelet evidence, developments of money and credit since the Great Recession or their decoupling in Japan suggest that it is more appropriate to examine the two variables separately in some circumstances.

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A Multilevel Eigenvector Spatial Filtering Model of House Prices: A Case Study of House Sales in Fairfax County, Virginia

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8110508 ◽

2019 ◽

Vol 8 (11) ◽

pp. 508

Author(s):

Lan Hu ◽

Yongwan Chun ◽

Daniel A. Griffith

Keyword(s):

Multilevel Model ◽

House Prices ◽

House Price ◽

Spatial Filtering ◽

Neighborhood Environment ◽

Model Specification ◽

Spatial Effects ◽

Residential Areas ◽

Fairfax County ◽

Eigenvector Spatial Filtering

House prices tend to be spatially correlated due to similar physical features shared by neighboring houses and commonalities attributable to their neighborhood environment. A multilevel model is one of the methodologies that has been frequently adopted to address spatial effects in modeling house prices. Empirical studies show its capability in accounting for neighborhood specific spatial autocorrelation (SA) and analyzing potential factors related to house prices at both individual and neighborhood levels. However, a standard multilevel model specification only considers within-neighborhood SA, which refers to similar house prices within a given neighborhood, but neglects between-neighborhood SA, which refers to similar house prices for adjacent neighborhoods that can commonly exist in residential areas. This oversight may lead to unreliable inference results for covariates, and subsequently less accurate house price predictions. This study proposes to extend a multilevel model using Moran eigenvector spatial filtering (MESF) methodology. This proposed model can take into account simultaneously between-neighborhood SA with a set of Moran eigenvectors as well as potential within-neighborhood SA with a random effects term. An empirical analysis of 2016 and 2017 house prices in Fairfax County, Virginia, illustrates the capability of a multilevel MESF model specification in accounting for between-neighborhood SA present in data. A comparison of its model performance and house price prediction outcomes with conventional methodologies also indicates that the multilevel MESF model outperforms standard multilevel and hedonic models. With its simple and flexible feature, a multilevel MESF model can furnish an appealing and useful approach for understanding the underlying spatial distribution of house prices.

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Superstar Cities

American Economic Journal Economic Policy ◽

10.1257/pol.5.4.167 ◽

2013 ◽

Vol 5 (4) ◽

pp. 167-199 ◽

Cited By ~ 98

Author(s):

Joseph Gyourko ◽

Christopher Mayer ◽

Todd Sinai

Keyword(s):

Metropolitan Area ◽

Metropolitan Areas ◽

House Prices ◽

Aggregate Demand ◽

House Price ◽

Lower Income ◽

Local Factors ◽

The Past ◽

Long Run ◽

Price Appreciation

We document large long-run differences in average house price appreciation across metropolitan areas over the past 50 years, and show they can be explained by an inelastic supply of land in some unique locations combined with an increasing number of highincome households nationally. The resulting high house prices and price-to-rent ratios in those “superstar” areas crowd out lower income households. The same forces generate a similar pattern among municipalities within a metropolitan area. These facts suggest that disparate local house price and income trends can be driven by aggregate demand, not just changes in local factors such as productivity or amenities. (JEL R11, R23, R31, R52)

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Learning from House Prices: Amplification and Business Fluctuations

The Review of Economic Studies ◽

10.1093/restud/rdaa079 ◽

2020 ◽

Author(s):

Ryan Chahrour ◽

Gaetano Gaballo

Keyword(s):

House Prices ◽

House Price ◽

Price Increase ◽

Land Prices ◽

Business Fluctuations ◽

Nominal Rigidity ◽

Supply Shocks ◽

Residential Investment ◽

Amplification Loop ◽

Initial Price

Abstract We formalize the idea that house price changes may drive rational waves of optimism and pessimism in the economy. In our model, a house price increase caused by aggregate disturbances may be misinterpreted as a sign of higher local permanent income, leading households to demand more consumption and housing. Higher demand reinforces the initial price increase in an amplification loop that drives comovement in output, labor, residential investment, land prices, and house prices even in response to aggregate supply shocks. The qualitative implications of our otherwise frictionless model are consistent with observed business cycles and it can explain the economic impact of apparently autonomous changes in sentiment without resorting to non-fundamental shocks or nominal rigidity.

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Saving Behavior and Housing Wealth Evidence from German Micro Data

Jahrbücher für Nationalökonomie und Statistik ◽

10.1515/jbnst-2017-0118 ◽

2018 ◽

Vol 238 (6) ◽

pp. 501-539

Author(s):

Sören Gröbel ◽

Dorothee Ihle

Keyword(s):

House Prices ◽

House Price ◽

Wealth Effect ◽

Housing Wealth ◽

Price Shocks ◽

Household Level ◽

Underlying Causes ◽

Saving Behavior ◽

Housing Wealth Effect ◽

Important Position

Abstract Housing property is the most important position in a household’s wealth portfolio. Even though there is strong evidence that house price cycles and saving patterns behave synchronously, the underlying causes remain controversial. The present paper examines if there is a wealth effect of house prices on savings using household-level panel data from the German Socio-Economic Panel for the period 1996-2012. We find that young homeowners decrease their savings in response to unanticipated house price shocks, whereas old households hardly respond to house price changes. Although effects are relatively low in magnitude, we interpret this as evidence of a housing wealth effect.

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International Real Estate Review

International Real Estate Review ◽

10.53383/100147 ◽

2012 ◽

Vol 15 (1) ◽

pp. 1-42

Author(s):

Heeho Kim ◽

◽

SaeWoon Park ◽

Sun Hye Lee ◽

◽

...

Keyword(s):

House Prices ◽

House Price ◽

Bank Lending ◽

Government Policies ◽

High Price ◽

Subprime Crisis ◽

Long Run ◽

Short Run ◽

Price Escalation ◽

Housing Submarket

This paper studies the abnormal price behavior of Kangnam, a premium (high price) housing submarket in Seoul, Korea, which addresses the correlation between house prices, bank lending, and other factors, including income. Kangnam experienced the most dramatic price escalation during the study period (1999-2009) despite Korean government policies to stabilize house prices in 2005 and the U.S. subprime crisis in 2008. The empirical result shows that even though the house price in a premium market is, to some degree, positively influenced by income, it is not affected by bank lending in the short-run while negatively affected in the long-run. This suggests that a premium housing submarket has a peculiar price dynamics of its own unlike the other submarkets which seem to comply more or less with our notion of a general economic theory, especially in terms of house prices and bank lending.

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