Investigating housing supply and monetary policy under global economic turbulence

This research has contributed to literature by identifying the impacts of monetary policy and global economic turbulence on the supply side of the housing sector under a vector error correction model. The research outcomes provided policy makers with an insight to change Australia's housing shortage and declining housing affordability.

The cost of housing : more than just dollars

Australians were recently awarded the dubious honour of building the largest homes in the world. Our new homes are now seven percent larger than those in the United States and nearly three times larger than those in the United Kingdom. At the same time, the price of an average residential property is now five times what it was 20 years ago. Although incomes have risen over the same period, they have not kept pace with rising house prices. In terms of disposable income, the cost of housing has almost doubled. While traditional housing affordability is measured in terms of house prices and incomes, a broader and more encompassing perspective also indicates that we can no longer ‘afford’ to build houses as we have done in the past. The environmental impact of modern Australian housing is significant. Australians have resisted the need for increased urban density as their capital city populations grow and new houses have been built on the outskirts of the existing cities, encroaching on the greenwedge and agricultural lands, destroying and degrading existing fauna and flora. The houses built have increased carbon emissions because of their size, embodied energy and reliance on the motor car. This paper discusses the environmental ‘affordability’ of current Australian housing and argues that this must be considered alongside traditional affordability criteria so that a more holistic approach to the issues is adopted.

Energy efficiency rating systems for housing : an Australian perspective

Purpose – The purpose of this paper is to examine current trends in energy efficiency ratings and consider their likely impact on the Australian housing market.

Design/methodology/approach – The research is yet to be conducted; however a mixed method is proposed which is grounded on the theoretical model of consumer behaviour within housing markets. This model has been tested and demonstrated to be useful in predicting buyer behaviour.

Findings – Established theories of buyer perception indicate the introduction of energy efficiency rating systems will have an effect on the level of house prices.

Research limitations/implications – This research is focussed on housing in Australia but also has implications for other global housing markets which are addressing sustainability.

Practical implications – Outputs of this research have implications for policy makers, real estate agents and valuers.

Social implications – Increasing energy costs is likely to restructure the way housing markets operate with regard to sustainability and energy efficiency rating systems and also how they are understood.

Originality/value – This research will be in the Australian context utilising international modeling. As mandatory energy efficiency ratings have not been introduced, this research will be original.

A panel error correction approach to explore spatial correlation patterns of the dominant housing market in Australian capital cities

Purpose - A panel error correction model has been developed to investigate the spatial correlation patterns among house prices. This paper aims to identify a dominant housing market in the ripple down process. Design/methodology/approach - Seemingly unrelated regression estimators are adapted to deal with the contemporary correlations and heterogeneity across cities. Impulse response functions are subsequently implemented to simulate the spatial correlation patterns. The newly developed approach is then applied to the Australian capital city house price indices. Findings - The results suggest that Melbourne should be recognised as the dominant housing market. Four levels were classified within the Australian house price interconnections, namely: Melbourne; Adelaide, Canberra, Perth and Sydney; Brisbane and Hobart; and Darwin. Originality/value - This research develops a panel regression framework in addressing the spatial correlation patterns of house prices across cities. The ripple-down process of house price dynamics across cities was explored by capturing both the contemporary correlations and heterogeneity, and by identifying the dominant housing market.

A benchmark study on housing defects in Victoria, Australia

The construction industry consists of many small businesses employing less than five people. A challenge to the construction industry is to ensure that the many small firms and sub-contractors keep producing quality housing to meet the needs of their customers and clients. In attempts to continually improve the quality of housing various policies and mechanisms have been adopted. These have included industry sponsored quality programs and industry administered builder registration. However, these attempts have failed because of consumer mistrust of industry-sponsored programs. In addition, these mechanisms have been introduced in isolation and not as a part of an integrated industry initiative that includes education and training from the trade to tertiary level construction management courses. This work contributes to knowledge through a detailed on-going study of housing quality and defects. This research identifies the common forms of defects, which occur in housing and their incidences. The overall aim of this paper is to report the identification of defects in housing and the establishment of benchmarks (or a baseline) for the incidence defects in various functional elements within a house. It also suggests the areas where defects are likely to occur. From the knowledge gained from the study, industry and governments may make informed decisions of where resources may be directed to the areas where it will be most beneficial both to the house builder and the end user (customer). For this to occur the findings of this research will be disseminated into the housing industry and eventually integrated into tertiary courses in building and construction
management.

Housing price diffusion pattern of Australia's state capital cities

The ripple effect of house prices within metropolitan areas has recently been recognised by researchers. However, it is very difficult to formulate and measure this effect using conventional house price theories particularly in consideration of the spatial locations of cities. Based on econometrics principles of the cointegration test and the error correction model, this research develops an innovative approach to quantitatively examine the diffusion patterns of house prices in mega-cities of a country. Taking Australia's eight capital cities as an example, the proposed approach is validated in terms of an empirical study. The results show that a 1-1-2-4 diffusion pattern exists within these cities. Sydney is on the top tier with Melbourne in the second; Perth and Adelaide are in the third level and the other four cities lie on the bottom. This research may be applied to predict the regional housing market behavior in a country.

Housing price diffusion pattern of Australia's state capital cities

The ripple effect of house prices within metropolitan areas has recently been recognised by researchers. However, it is very difficult to formulate and measure this effect using conventional house price theories particularly in consideration of the spatial locations of cities. Based on econometrics principles of the cointegration test and the error correction model, this research develops an innovative approach to quantitatively examine the diffusion patterns of house prices in mega-cities of a country. Taking Australia's eight capital cities as an example, the proposed approach is validated in terms of an empirical study. The results show that a 1-1-2-4 diffusion pattern exists within these cities. Sydney is on the top tier with Melbourne in the second; Perth and Adelaide are in the third level and the other four cities lie on the bottom. This research may be applied to predict the regional housing market behavior in a country.

Impacts of monetary policies on housing affordability in Australia

Housing affordability has become a major policy issue in many countries across the world since the rapid inflation of house prices. This paper empirically investigates how monetary policies affect housing affordability in Australia from 1998 to 2009. Three primary variables associated with the housing sector and monetary policy, which are money supply, interest rates and house prices, are studied for all eight capital cities in Australia in this research. Shocks of such variables are identified by a structural vector autoregression (SVAR) model with restrictions that are consistent with economic theoretical framework. Based upon the analysis using the structural decomposition of impulse response on quarterly data, it can be discovered that the monetary policy plays an active role in housing affordability via adjustments of money supply and interest rates during the observed period in Australia. The empirical results from this research may be used for decision makers to determine money supply and interest rates from the perspective of housing affordability.

The accuracy of housing forecasting in Australia

Forecasting is an integral part of all business planning, and forecasting the outlook for housing is of interest to many firms in the housing construction sector. This research measures the performance of a number of industry forecasting bodies; this is done to provide users with an indicator of the value of housing forecasting undertaken in Australia. The accuracy of housing commencement forecasts of three Australian organisations – the Housing Industry Association (HIA), the Indicative Planning Council for the Housing Industry (IPC) and BIS-Shrapnel – is examined through the empirical analysis of their published forecasts supplemented by qualitative data in the form of opinions elicited from several industry “experts” employed in these organisations. Forecasting performance was determined by comparing the housing commencement forecast with the actual data collected by the Australian Bureau of Statistics on an ex-post basis. Although the forecasts cover different time periods, the level of accuracy is similar, at around 11-13 per cent for four-quarter-ahead forecasts. In addition, national forecasts are more accurate than forecasts for individual states. This is the first research that has investigated the accuracy of both private and public sector forecasting of housing construction in Australia. This allows users of the information to better understand the performance of various forecasting organisations.