Real and Financial Cycles in Euro Area Economies: Results from Wavelet Analysis

2019 ◽  
Vol 239 (5-6) ◽  
pp. 895-916 ◽  
Author(s):  
Michael Scharnagl ◽  
Martin Mandler
Keyword(s):  
Wavelet Analysis ◽  
Euro Area ◽  
Cycle Length ◽  
House Prices ◽  
House Price ◽  
Real Activity ◽  
Economic Cycles ◽  
Real Gdp ◽  
Common Cycles ◽  
Financial Cycles

Abstract We study the within-country dimension of financial cycles in the four largest euro area economies using tools from wavelet analysis. We focus on credit and house price cycles which are most commonly used to represent the financial cycle. With the exception of Germany, the variables contain important common cycles within each country close to the upper bound of business cycle length and beyond which can be interpreted as financial cycles. These cycles are closely linked to domestic cycles in real activity showing financial and real economic cycles as interconnected phenomena. For these common cycles, credit and house prices lag real GDP.

scholarly journals Liquidity, interest rates and house prices in the euro area: a DSGE analysis

2016 ◽  
Vol 9 (1) ◽  
pp. 4-25 ◽  
Author(s):  
Margarita Rubio ◽  
José A. Carrasco-Gallego
Keyword(s):  
Interest Rates ◽  
Monetary Union ◽  
Euro Area ◽  
House Prices ◽  
Housing Prices ◽  
House Price ◽  
Dsge Model ◽  
Content Type ◽  
The Core ◽  
Dynamic Stochastic

Purpose This study aims to build a two-country monetary union dynamic stochastic general equilibrium (DSGE) model with housing to assess how different shocks contributed to the increase in housing prices and credit in the European Economic and Monetary Union. One of the countries is calibrated to represent the core group in the euro area, while the other one corresponds to the periphery. Design/methodology/approach In this paper, the authors explore how a liquidity shock (or a decrease in the interest rate) affects house prices and the real economy through the asset price and the collateral channel. Then, they analyze how a house price shock in the periphery and a technology shock in the core countries are transmitted to both economies. Findings The authors find that a combination of an increase in liquidity in the euro area coming from the common monetary policy, together with asymmetric house price and technology shocks, contributed to an increase in house prices in the euro area and a stronger credit growth in the peripheral economies. Originality/value This paper represents the theoretical counterpart to empirical studies that show, through macroeconometric models, the interrelation between liquidity and other shocks with house prices. Using a DSGE model with housing, the authors disentangle the mechanisms behind these empirical findings.

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.

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.

scholarly journals Assessing the impacts of Airbnb listings on London house prices

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.

A partial and multiple wavelet analysis of tourism and house prices

2020 ◽  
pp. 1-14
Author(s):  
Tsung-Pao Wu ◽  
Hung-Che Wu ◽  
Shu-Bing Liu ◽  
Shun-Jen Hsueh ◽  
Junyan Chen
Keyword(s):  
Wavelet Analysis ◽  
House Prices

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

Empirica ◽  
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.

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

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.

Superstar Cities

2013 ◽  
Vol 5 (4) ◽  
pp. 167-199 ◽  
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)

Learning from House Prices: Amplification and Business Fluctuations

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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