An examination of house price bubble in the real estate sector: the case of a small island economy – Fiji

Purpose This paper aims to assess the equilibrium house price in the city of Suva (Fiji) and to analyse the house price bubble in the Fiji housing market. Design/methodology/approach This paper adopts a time series approach to determine the presence of house price bubbles in Fiji over the period from 1988 to 2018. Findings The findings suggest that real income, land cost, building material price, inflation rate, volatility, household size and wealth have a positive impact on house prices, whereas user cost of capital and political disturbances have a negative impact. The findings further indicate that the Fijis’ housing market does not constitute any house price bubble. Practical implications This paper draws policy implications for a small developing state (Fiji) and other similar economies. Originality/value The price bubble in the Fiji housing market is analysed for the first time. This paper develops a comprehensive empirical approach to assess the equilibrium-housing price in Fiji.

The case of housing

This chapter studies the case of housing. The figure of the 'investor-subject', which is key to the critique of financial inclusion policy, highlights the importance of considering the special role of housing for at least two reasons. First, housing is arguably the most important investment that is made by investor-subjects. For example, Individual Development Accounts (IDAs) are supposed to be used for three main aims, namely, paying for training, starting a business, or putting down a deposit on a home. In fact, critics of asset-based welfare claim that this specific policy agenda is focused mainly on boosting home ownership and so there is now a literature that is dubbed 'housing asset-based welfare'. Second, investors often have to borrow on mortgage markets to pay for a home. This highlights that 'borrowing to invest' is a key part of an investor-subject approach. Critics say that 'borrowing to invest' led to record levels of personal indebtedness and fuelled a house price bubble that was one of the triggers for the global financial crisis of 2007–08. For critics, this shows that the financial inclusion agenda contributed directly to the instability within the economy. The chapter argues that financial inclusion need not necessarily lead to a house price bubble and instead might be used to open up debates about the nature of home ownership.

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

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.

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

The 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.