scholarly journals 'Being in the market': the UK house-price bubble and the intended structure of individual pension investment portfolios

2009 ◽  
Vol 10 (3) ◽  
pp. 331-359 ◽  
Author(s):  
G. L. Clark ◽  
R. Duran-Fernandez ◽  
K. Strauss
Keyword(s):  
House Price ◽  
Price Bubble ◽  
The Uk ◽  
Investment Portfolios ◽  
House Price Bubble

Good Inflation, Bad Inflation: The Housing Boom, Economic Growth and the Disaggregation of Inflationary Preferences in the UK and Ireland

2009 ◽  
Vol 11 (3) ◽  
pp. 461-478 ◽  
Author(s):  
Colin Hay
Keyword(s):  
Monetary Policy ◽  
House Price ◽  
Private Debt ◽  
Price Inflation ◽  
Mortgage Interest ◽  
Price Bubble ◽  
Housing Boom ◽  
Time Inconsistent ◽  
The Uk ◽  
House Price Bubble

This article presents a comparative analysis of the determinants, sustenance and broader macroeconomic consequences of the ultimately unsustainable housing boom in Ireland and the UK in recent years. It examines, in particular, the role played by ostensibly depoliticised monetary policy in both contexts in the development of a house price bubble that has served to fuel consumer-led growth. It assesses the viability, sustainability and reproducibility of the private debt-financed consumer boom that house price inflation has generated. In the process it draws attention to the increasingly differentiated character of both government inflationary preferences and counter-inflationary performance—with the shift to official measures of inflation that exclude mortgage interest repayments and, in the UK at least, to the covert re-politicisation of monetary policy. It concludes by suggesting that governments may well not have time-inconsistent inflationary preferences so much as sectorally specific inflationary preferences. This might be summarised in terms of the aphorism: ‘retail price inflation bad, house price inflation good’.

House price drivers in Dubai: nonlinearity and heterogeneity

2017 ◽  
Vol 10 (3) ◽  
pp. 384-409 ◽  
Author(s):  
Genanew Bekele Worku
Keyword(s):  
Quantile Regression ◽  
House Price ◽  
Interesting Case ◽  
Future Research ◽  
Policy Makers ◽  
Content Type ◽  
Price Bubble ◽  
Linear And Nonlinear ◽  
Rich Data ◽  
The Uk

Purpose This paper aims to examine house price drivers in Dubai, addressing nonlinearity and heterogeneity. Design/methodology/approach The study applies a combination of linear and nonlinear, as well as quantile regression, specifications to address these concerns and better explain the real-world phenomenon. Findings The study shows the double-log quantile regression approach is an overarching description of house price drivers, confirming that not only the price of housing and its determinants are non-linearly related but also that their relationship is heterogeneous across house price quantiles. The findings reveal the prevalence of sub-market differentials in house price sensitivity to house attributes such as size (in square meters), location and type of house, as well as government laws. The study also identifies the peaks and deflation, as well as the rebounding nature of the house price bubble in Dubai. Research limitations/implications The data used are limited, in that information on only a few house attributes was available. Future research should include data on other house attributes such as house quality, zip codes and composition. Practical implications The findings of this study are expected to suggest results with significant ramifications for researchers, practitioners and policy makers. From a policy perspective, there is an obvious interest in understanding whether the price of housing is affected by different attributes differently along its distribution. Social implications This study allows policy makers, developers and buyers of higher-priced houses to behave differently from buyers of lower-priced or medium-priced houses. Originality/value Methodologically, it demonstrates alternative linear and nonlinear, as well as quantile regression, specifications to address two increasing concerns in the house price literature: nonlinearity and heterogeneity. Unlike most other studies, this study used a rich data (140,039 day-to-day transactions of 10 years’ pooled data). The Dubai housing market presents an interesting case. UAE (Dubai, in particular) is named as the second-hottest marketplace for global residential property investors, ahead of Singapore, the UK and Hong Kong (Savills plc, 2015).

scholarly journals Empirical Analysis of House Price Bubble: A Case Study on Malaysia

2016 ◽  
Vol 11 (12) ◽  
pp. 127
Author(s):  
Fong Kean Yan ◽  
Yap Lya Keng ◽  
Kwek Kien Teng
Keyword(s):  
Gross Domestic Product ◽  
House Prices ◽  
House Price ◽  
Domestic Product ◽  
Price Bubble ◽  
Long Run ◽  
Residential Properties ◽  
Short Run ◽  
Per Capita ◽  
House Price Bubble

The main objective of this research is to investigate the relationship between house price with macroeconomics variables - Gross Domestic Product per capita, inflation rate, Base Lending Rate and amount of household loan disbursed for purchase of residential properties. We try to use these variables to examine if they could trigger a housing bubble to burst in Malaysia. Granger Causality results show that there is univariate relationship from house price to Gross Domestic Product per capita. Though house price and other macroeconomics variables do not Granger–cause each other in short run, but these variables are cointegrated in the long run, i.e. there is no evidence of house price bubble in Malaysia. We suggest that soaring house prices in Malaysia is being supported by the large inflow of foreign funds into the housing sector and the unresponsive supply of houses.

scholarly journals The Regional Pattern of the U.S. House Price Bubble – An Application of SPC to City Level Data

2015 ◽  
Vol 66 (2) ◽  
Author(s):  
Julia Freese
Keyword(s):  
Asset Price ◽  
House Price ◽  
Statistical Process ◽  
Asset Price Bubbles ◽  
Price Bubbles ◽  
Ewma Control Chart ◽  
Price Bubble ◽  
Level Data ◽  
Starting Point ◽  
House Price Bubble

AbstractThe recent U.S. house price bubble and the subsequent deep financial crisis have renewed the interest in reliable identification methods for asset price bubbles. While there is a growing number of studies focussing on the detection of U.S. regional bubbles, estimations of the likely starting points in different local U.S. markets are still rare. Using regional data from 1990 to 2010 methods of Statistical Process Control (SPC) are used to test for house price bubbles in 17 major U.S. cities. Based on the EWMA control chart we also present estimations of the likely starting point of the regional bubbles. As a result, we find indications of house price bubbles in all 17 considered cities. Interestingly enough, the recent bubble was not a homogeneous event since regional starting points range from 1996 to 2002.

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