Local parameters of housing prices: a case study of the Melbourne residential property market

Housing as an aspect of consumption and as an asset is important to both the economy and
individuals. Due to this, housing price performance has drawn significant attention from policy
makers, investors, home owners and researchers. House prices are often reported on a country,
city and local level. At a country and city level, there have been extensive studies on house
prices and macroeconomic determinants that show house price movements are closely related
to a common set of macroeconomic variables and market specific conditions. At a local level,
there has been an improved understanding of housing markets assisted by identifying and
understanding individual factors influencing housing decisions, including transportation,
neighbourhood characteristics, social characteristics, schools and planning regulations. At a
local level, existing studies focused on examining one or two factors of house price
performance of a city or a suburb, with nominal attention to elaborating the combination of all
factors and how those factors would have a different effect in different locations, especially
locations that are close to each other.

This research is aimed at identifying and examining house price determinants at a local level
to understand why house prices vary across different locations and the factors influencing such
price differentiation. This research has adopted explanatory mixed research methods (QUAN
-> QUAL) where quantitative analysis is used in the first stage to examine the Melbourne
housing market and its performance at different levels. The research found there were certain
periods where local house prices do not perform in line with either country, city or other local
housing markets. Interestingly, suburbs located next to each other could have a difference in
price performance over time. Based on the quantitative results, eight representative case studies
(four pairs) that had different price performance histories were selected across different
locations of Metropolitan Melbourne and compared in pairs namely: Hawthorn vs Kew;
Broadmeadows vs Glenroy; Altona Meadows vs Laverton and Box Hill vs Mont Albert. This
research further examined the relationship between each case study and macroeconomic
variables such as interest rate, household income, GDP etc. and concluded that macroeconomic
factors overall had a limited effect on local house price performance.

The results are also in line with suggestions from the literature review that there is a degree of
price heterogeneity in regional housing markets and that housing markets at a sub-national
level are highly segmented. Regional and local house prices can deviate from their equilibrium
values for certain periods of time and the deviation can be driven by specific circumstances
rather than national factors. Therefore, a national housing price model would fail to represent
housing price dynamics of regional cities. This research has extended the theory and further
concluded that the macroeconomic factors had an overall limited effect on local house price
performance. The results also highlighted house prices were segmented at the local level and
the local house price difference is unexplainable by macroeconomic factors. It is suggested that
microeconomic factors could be the key to local house price differences.
This research has then used qualitative analysis of in-depth interviews to understand the
phenomenon resulting from quantitative data and investigates factors influencing local house
price differentiation for each case study. It has cross examined factors including transportation,
neighbourhood characteristics, social characteristics, schools and planning regulations. Based
on qualitative analysis, this research has found each local factor can contribute to the
performance of house price directly or co-effect with other factors. However, the results varied
between locations and each factor contributed differently to local house price performance
depending on the nature and characteristics of the suburb. Based on the results from interviews
from each case study, this research cross examined local factors with price measurements to
further demonstrate the effect of each factor on median house price performance, average
annual price returns and price volatility.
The findings concluded that median house prices are positively affected by high ranking
schools and better neighbourhood environments. If two locations comprise different socio
economic demographics, median house prices are positively affected by higher socio economic
demographic as people with high socio economic demographics would pay a premium to live
in a location with similar social background to themselves. Median house price is also
positively affected by a combination of factors, such as high ranking schools and transportation.
For example, if a suburb does not provide a high ranking school, then the location that can
provide direct transportation access to a high ranking school located in nearby suburbs would
attract more demand.
The median house prices are negatively affected by neighbourhood environment factors such
as low quality of street appeal or being located in close proximity to an undesirable facilities
(e.g. industrial sites). In addition, if a location comprises a low socio economic demographic,
then median house prices are adversely affected. The median house prices are also negatively
affected by a combination of factors, such as social and school factors. Low socio economics
would put pressure on school factors as parents would try to avoid living in a location that has
low socio economic demographic because they would want their children to go to the same
schools as other children who have a similar social background. Although school in this case,
does not have a direct negative effect on house prices, the hesitation from parents for a location
with low socio economic demographics would adversely affect demand for that location.
Unlike the number of factors affecting median house price performance, the number of factors
that were identified to influence average annual price returns and price volatility in this research
are rather limited. This research concluded no single factor explains the difference in average
annual price returns, rather a combination of two factors – planning regulations and
transportation. If local council encourages high density development for a location, then that
location would have a development opportunity which will lead to a higher price return because
the land is worth more if multi-unit dwellings can be built for that piece of land. This research
found such development potential tends to be closely linked with transportation. From a price
volatility point of view, if there are undesirable facilities such as industrial sites developed in
a nearby location, then the proximity to undesirable facilities would have an adverse effect on
median house prices and further affect price volatility. For example, Laverton North
experienced rapid industrial development due to the opening of the Western Ring Road and as
result Laverton, a nearby suburb experienced a more volatile price performance. The impact
seems to have affected purchasing activity. Demand from owner occupiers was diminished by
the proximity to industrial activity, whereas investors continue to purchase property as a
consequence of the negative impact on prices which in turn resulted in improved yield returns.
Most importantly, in order to provide a comprehensive understanding of local house price
differences, this research cross referenced the census data with interview results and further
triangulated the outcomes with price correlation results, and found the significant differences
in local house price performance between two locations for a particular period of time could
be the result of changing local factors. For example, a change in neighbourhood facilities
including proximity to undesirable industrial sites would decrease the demand for that location
and further influence price volatility. Furthermore, a positive change in socio demographics
would increase the demand for that location and hence positively affect price growth. If a
suburb experienced an increase in the concentration of high socio demographic population, a
restrictive planning policy limiting high density development would also positively affect price growth.
In addition, for other suburbs, change in local planning policy to encourage high
density development may increase house prices and enhance price growth.
This research is aimed at examining the interrelationship between local determinants and
housing prices, not quantifying the impact of each determinants on housing price movement.
Nevertheless, the findings from this research form an important insight into local house price
determinants, in particular, it lends strong support to the hypothesis that microeconomic factors
cause local price differentiation. The multidisciplinary approach to the study reflected the
complexity of household decisions and the way submarkets are segmented based on a variety
of microeconomic factors. This research provides a platform for understanding the influences
on buyers and investors’ decision making based on historical data and ultimately improves the
understanding of key price determinants at a local level. A better understanding of the
relationship between local factors and house price performance will help buyers and investors
to identify and address issues that were attributable to residential property market performance
and so make better investment decisions.