Local parameters of housing prices: a case study of the Melbourne residential property market
Creators: name: Xu, Yixin
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 330403
subject: Housing markets, development and management
classificationCode: 380302
subject: Macroeconomic theory
classificationCode: 380304
subject: Microeconomic theory

description: Housing as an aspect of consumption and as an asset is important to both the economy and<br>individuals. Due to this, housing price performance has drawn significant attention from policy<br>makers, investors, home owners and researchers. House prices are often reported on a country,<br>city and local level. At a country and city level, there have been extensive studies on house<br>prices and macroeconomic determinants that show house price movements are closely related<br>to a common set of macroeconomic variables and market specific conditions. At a local level,<br>there has been an improved understanding of housing markets assisted by identifying and<br>understanding individual factors influencing housing decisions, including transportation,<br>neighbourhood characteristics, social characteristics, schools and planning regulations. At a<br>local level, existing studies focused on examining one or two factors of house price<br>performance of a city or a suburb, with nominal attention to elaborating the combination of all<br>factors and how those factors would have a different effect in different locations, especially<br>locations that are close to each other.<br><br>This research is aimed at identifying and examining house price determinants at a local level<br>to understand why house prices vary across different locations and the factors influencing such<br>price differentiation. This research has adopted explanatory mixed research methods (QUAN<br>-&gt; QUAL) where quantitative analysis is used in the first stage to examine the Melbourne<br>housing market and its performance at different levels. The research found there were certain<br>periods where local house prices do not perform in line with either country, city or other local<br>housing markets. Interestingly, suburbs located next to each other could have a difference in<br>price performance over time. Based on the quantitative results, eight representative case studies<br>(four pairs) that had different price performance histories were selected across different<br>locations of Metropolitan Melbourne and compared in pairs namely: Hawthorn vs Kew;<br>Broadmeadows vs Glenroy; Altona Meadows vs Laverton and Box Hill vs Mont Albert. This<br>research further examined the relationship between each case study and macroeconomic<br>variables such as interest rate, household income, GDP etc. and concluded that macroeconomic<br>factors overall had a limited effect on local house price performance.<br><br>The results are also in line with suggestions from the literature review that there is a degree of<br>price heterogeneity in regional housing markets and that housing markets at a sub-national<br>level are highly segmented. Regional and local house prices can deviate from their equilibrium<br>values for certain periods of time and the deviation can be driven by specific circumstances<br>rather than national factors. Therefore, a national housing price model would fail to represent<br>housing price dynamics of regional cities. This research has extended the theory and further<br>concluded that the macroeconomic factors had an overall limited effect on local house price<br>performance. The results also highlighted house prices were segmented at the local level and<br>the local house price difference is unexplainable by macroeconomic factors. It is suggested that<br>microeconomic factors could be the key to local house price differences.<br>This research has then used qualitative analysis of in-depth interviews to understand the<br>phenomenon resulting from quantitative data and investigates factors influencing local house<br>price differentiation for each case study. It has cross examined factors including transportation,<br>neighbourhood characteristics, social characteristics, schools and planning regulations. Based<br>on qualitative analysis, this research has found each local factor can contribute to the<br>performance of house price directly or co-effect with other factors. However, the results varied<br>between locations and each factor contributed differently to local house price performance<br>depending on the nature and characteristics of the suburb. Based on the results from interviews<br>from each case study, this research cross examined local factors with price measurements to<br>further demonstrate the effect of each factor on median house price performance, average<br>annual price returns and price volatility.<br>The findings concluded that median house prices are positively affected by high ranking<br>schools and better neighbourhood environments. If two locations comprise different socio<br>economic demographics, median house prices are positively affected by higher socio economic<br>demographic as people with high socio economic demographics would pay a premium to live<br>in a location with similar social background to themselves. Median house price is also<br>positively affected by a combination of factors, such as high ranking schools and transportation.<br>For example, if a suburb does not provide a high ranking school, then the location that can<br>provide direct transportation access to a high ranking school located in nearby suburbs would<br>attract more demand.<br>The median house prices are negatively affected by neighbourhood environment factors such<br>as low quality of street appeal or being located in close proximity to an undesirable facilities<br>(e.g. industrial sites). In addition, if a location comprises a low socio economic demographic,<br>then median house prices are adversely affected. The median house prices are also negatively<br>affected by a combination of factors, such as social and school factors. Low socio economics<br>would put pressure on school factors as parents would try to avoid living in a location that has<br>low socio economic demographic because they would want their children to go to the same<br>schools as other children who have a similar social background. Although school in this case,<br>does not have a direct negative effect on house prices, the hesitation from parents for a location<br>with low socio economic demographics would adversely affect demand for that location.<br>Unlike the number of factors affecting median house price performance, the number of factors<br>that were identified to influence average annual price returns and price volatility in this research<br>are rather limited. This research concluded no single factor explains the difference in average<br>annual price returns, rather a combination of two factors – planning regulations and<br>transportation. If local council encourages high density development for a location, then that<br>location would have a development opportunity which will lead to a higher price return because<br>the land is worth more if multi-unit dwellings can be built for that piece of land. This research<br>found such development potential tends to be closely linked with transportation. From a price<br>volatility point of view, if there are undesirable facilities such as industrial sites developed in<br>a nearby location, then the proximity to undesirable facilities would have an adverse effect on<br>median house prices and further affect price volatility. For example, Laverton North<br>experienced rapid industrial development due to the opening of the Western Ring Road and as<br>result Laverton, a nearby suburb experienced a more volatile price performance. The impact<br>seems to have affected purchasing activity. Demand from owner occupiers was diminished by<br>the proximity to industrial activity, whereas investors continue to purchase property as a<br>consequence of the negative impact on prices which in turn resulted in improved yield returns.<br>Most importantly, in order to provide a comprehensive understanding of local house price<br>differences, this research cross referenced the census data with interview results and further<br>triangulated the outcomes with price correlation results, and found the significant differences<br>in local house price performance between two locations for a particular period of time could<br>be the result of changing local factors. For example, a change in neighbourhood facilities<br>including proximity to undesirable industrial sites would decrease the demand for that location<br>and further influence price volatility. Furthermore, a positive change in socio demographics<br>would increase the demand for that location and hence positively affect price growth. If a<br>suburb experienced an increase in the concentration of high socio demographic population, a<br>restrictive planning policy limiting high density development would also positively affect price growth.<br>In addition, for other suburbs, change in local planning policy to encourage high<br>density development may increase house prices and enhance price growth.<br>This research is aimed at examining the interrelationship between local determinants and<br>housing prices, not quantifying the impact of each determinants on housing price movement.<br>Nevertheless, the findings from this research form an important insight into local house price<br>determinants, in particular, it lends strong support to the hypothesis that microeconomic factors<br>cause local price differentiation. The multidisciplinary approach to the study reflected the<br>complexity of household decisions and the way submarkets are segmented based on a variety<br>of microeconomic factors. This research provides a platform for understanding the influences<br>on buyers and investors’ decision making based on historical data and ultimately improves the<br>understanding of key price determinants at a local level. A better understanding of the<br>relationship between local factors and house price performance will help buyers and investors<br>to identify and address issues that were attributable to residential property market performance<br>and so make better investment decisions.<br>