What factors inﬂuence the price of land in the ACT?
By Annick Theron & Taneesha GriﬃthsMethod

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2. The secondary data of popula>on density wascollected from the Australian Bureau of Sta>s>cs
and the distance from the city was collectedfrom ‘My Boot’.
3. The outliers for land size and price of thedata set were removed and a sca]erplot
graph comparing the land size and UV price
was constructed.
4. The average land price and size
were calculated from the data sets foreach suburb then the price persquare metre was calculated anddisplayed in a bar graph.
5. Graphs were then constructed forthe distance from city, popula>on
density and suburb age vs price permeter.

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Size (meters squared)

Relevance
The central tendency, range, IQR and standard deviation all help when concluding which factors influence
the price of land. They each help us to decide which price of land is the best value for money when adding
in practical factors such as the distance from the city and population density.
The mean helps us to decipher if the land is cheap or expensive for it’s size in correspondence to similar
blocks in other suburbs. It can also help to determine how far away from the city you are than the average
person, the population density of your suburb compared to others and whether your suburb has been
recently developed or been here for many years - all effecting the price of land in some way.
The mode allows us to see which value is the most popular, helping our understanding of how different
factors can influence the price. The median helps to pinpoint exactly where each block of land and stands interms of the value being investigated. While it may be below average in a factor, the median may tell youthat you are in an upper quartile.
The range allows us to see the large difference in variation between values of each factor though the IQR isoften seen as a better measure of spread as it is not affected by outliers. This can help gain a better
understanding as to where a specific factor stands.
The standard deviation are measures of the spread of the data around the mean. It summarises how closeeach observed data value is to the mean value allowing a better insight into each property.
Each of these are factored in to determine the appropriate price for a property.

Popula>on Density of Suburb vsPrice/Meter

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Population Density (people per kilometer squared)

X-axis: x̄: 1584.78 Mode: 1500 Median: 1550 Range: 3908 IQR: 435 σ: 628.10
Y-axis: x̄: 0.63 Mode: 0.4 Median: 0.6 Range: 1.2 IQR: 0.4 σ: 0.26

X-axis: x̄: 752.48 Mode: 450 Median: 769 Range: 1085 IQR: 302 σ: 229.43
Y-axis: x̄: 460.21 Mode: 299 Median: 403 Range: 824 IQR: 240 σ: 176.04
This sca]erplot depicts the rela>onship between the average size and price of proper>es across various suburbs in
the ACT. It shows a weak posi>ve correla>on between price and area of land. The spread of data has an average
price of $460,210 for 752.48m2 of land.

This sca]erplot portrays the link between the popula>on density of a suburb and its corresponding price per square meter of land. Itdisplays an extremely weak, nega>ve correla>on between the two factors. The mode and median and mean appear to be extremely
close for the popula>on density sugges>ng a small IQR compared to the overall range. The standard devia>on shows how spread out
from the mean the data is, therefore elucida>ng the impression of a weak correla>on.

Distance from City - Results

Age of Suburb - Results

Graph 3Graph 4

Price/m2 ($ thousand)

1.The primary data (land size, UV price andsuburb) of each individual property was takenfrom the ‘All Homes’ website. The founda>ondate was researched.

Graph 2Price/m2 ($ thousand)The both the factors of size of land and loca>on of property will eﬀect the price of land.

Size vs Price

Graph 1Distance from City vs Price/Meter

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2025Distance (kilometers)

X-axis: x̄: 9.97 Mode: 13.2 Median: 10.1 Range: 18.5 IQR: 5.8 σ: 4.35
Y-axis: x̄: 0.63 Mode: 0.4 Median: 0.6 Range: 1.2 IQR: 0.4 σ: 0.26

This sca]erplot expresses the connec>on between a suburbs distance from the city and its average price per square meter of land.
There is a moderately strong nega>ve correla>on between the two. It proves that the closer to the city (Canberra CBD) a suburb is, themore expensive the land is. Again, as seen in graph 2, the diﬀerence between the range and IQR on the x-axis are quite large sugges>ng
a large varia>on in some suburbs. The IQR and the standard devia>on are quite close, sugges>ng a much stronger and even correla>onin data.

Price/m2 ($ thousand)Hypothesis

Popula>on Density - Results

Size and Price - Results

Price ($ thousand)Introduc>onThe housing and land market is constantly evolving. There are many factors that inﬂuence the price of landin the ACT. In this inquiry, the factors looked at included the size of land and the loca>on factors. The
loca>on factors consisted of popula>on density, distance from city and age of suburb.
The data was collected in early November 2018 from a random 200 houses for sale in the Australian Capital
Territory on the ’All Homes’ website. For each property, the numerical value used was the UV price. The
unimproved land value (UV) is the dollar ﬁgure a block of land is deemed worth without any buildings orstructures on it. However there is a small issue behind this however. There is a slight inaccuracy with theprimary data collected as it isn’t speciﬁcally the land for sale, it is a property with house on it. The separate
deemed value for the land has been used. Another issue involved with the collec>on of data is that thesample space is quite small. According to the 2016 census, there are 145,229 households in Canberra; only
200 of which are involved in this inquiry.

Age of Suburb vs Price/Meter

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100120Age (years)
X-axis: x̄: 47.95 Mode: 90 Median: 48 Range: 88 IQR: 20 σ: 22.64
Y-axis: x̄: 0.63 Mode: 0.4 Median: 0.6 Range: 1.2 IQR: 0.4 σ: 0.26
This sca]erplot displays the correla>on between the age of a suburb and the price per square meter of land. It reveals that there is a slightly
weak posi>ve correla>on between these variables. It is clear to see on the graph that the mode for the x-axis is 90. The range is extremely
varied at 88 years in diﬀerence though the interquar>le range of 20 shows that the majority of suburbs are around the age of 50, thoughalmost all of them appear below the line of best ﬁt (rather than closer to it) sugges>ng that age isn’t a large factor.

To conclude, this data provides evidence for the leading factors inﬂuencing
the price of land in the Australian Capital Territory. In graph 1, it can be seenthat there is a weak posi>ve correla>on between the size of the block andthe price of the block. Graph 2 shows that the popula>on density of a suburb
has an extremely weak nega>ve correla>on against the price per square
meter of land. As can be seen from graph 3, the further away the suburb wasfrom the city, the average price per square meter of land decreased.
Addi>onal to the distance from the city, the other leading factor was the ageof the suburb which is seen in graph 4. Graph 5 depicts the average price persquare meter of land for every suburb used in the study. It is the founda>onfor graphs 2, 3 and 4. In summa>on, the sta>s>cal data conﬁrmed ourpredic>on of both the factors of size of land and loca>on of property willeﬀect the price of land in the Australian Capital Territory. The leading factors
are the suburb’s distance from Canberra’s CBD and the age of the suburb.
Though, the overall size of the block and the popula>on density of thesuburb had a minimal eﬀect on the price.
Limita>ons with the data included a slight inaccuracy with the primary datacollec>on as it isn’t speciﬁcally the land for sale, it was a property with ahouse on it. A separate deemed value for the land (the unimproved value)
has been used in this experiment which sets a limita>on on the quality of thedata. Another issue involved with the collec>on of data is that the sample
space is quite small. According to the 2016 census, there are 145,229
households in Canberra; only 200 of which were involved in thisinquiry. Improvements for further studies for this inquiry would be gaining amuch larger sample space. The 200 houses used seems too unreliable for aquality result. Using primary data from only blocks of land for sale rather
than the UV value for houses would also improve the quality and accuracy.
Addi>onally, more recent secondary data in popula>on density would havealso helped as the 2016 census may already be very outdated and inaccurate.
In addi>on to this, including all 119 suburbs rather than a sample space of73. Upon researching this ques>on further online, property blog websites‘Planning Tank’ and ‘Home Guru’ both say that loca>on and demographics
aﬀect land value. Addi>onally, physical a]ributes, neighbourhood ameni>es,
supply and demand and economic growth also aﬀect the price of land; all ofwhich could be studied further in another inquiry.

Bibliography

Average Price per Suburb - Results

Average Price per Square Meter of Land

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Ainslie
AmarooArandaBanks
BonnerBraddonBruce
Calwell
Campbell
ChapmanCharnwood
Chiffley
Chisholm
ConderCook
Coombs
Crace
CurtinDeakinDickson
DownerDuffy
DunlopEvatt
FaddenFarrehFisherFloreyFlynn
FordeForrest
Frankli n
GarrenGiralang
GordonGowrieGriffith
HackettHarrison
Higgins
HolderHughesIsaacsJacka
KaleenKambahLathamLyneham
Lyons
Macgregor
MawsonMckellar
MelbaMonash
Narrabundah
Ngunnawal
Nicholls
O'Connor
Oxley
Page
Palmerston
Red Hill
Richardson
Rivet tScullenSpenceSterling
Theodore
Wanniassa
Waramanga
WatsonWeetangera
Yarralumla

Price/m2 ($ thousand)

Graph 5Suburb Namex̄: 0.63 Mode: 0.4 Median: 0.6 Range: 1.2 IQR: 0.4 σ: 0.26
Whilst not a factor answering the ques>on, this bar graph oﬀers insight into the average price per square meter for land in diﬀerent Canberra suburbs. These averages are the evidence upon which the above graphs are based on. The trendline shows us that the average price is$630 per square meter and easily allows us to see which suburbs are on average more expensive than others. The large diﬀerence between the range and the IQR suggests that there are a few outliers . The standard devia>on allows us to summarise how close each observed
data value is to the mean value. The mode though is only just 66% of the average, sugges>ng that there is a very large data range.

Census - Data by Geography [Online] / auth.
Australian Government // Australian Bureau ofSta>s>cs. - 2016. - November 05, 2018. h]p://www.abs.gov.au.
Factors aﬀec>ng Land Value [Online] / auth.
Planning Tank Admin // Planning Tank. - 2017. - 07
November 2018. - h]ps://planningtank.com/urbaneconomics/factors-aﬀec>ng-land-value.
Property Prices [Online] / auth. HomeGuru //HomeGuru. - 2018. - 07 November 2018. h]p://www.homeguru.com.au/house-prices.
Residen>al Sales Search - ACT [Online] / auth. All
Homes // All Homes. - 2018. - November 05, 2018. h]ps://www.allhomes.com.au/ah/search/saleresiden>al?region=canberra-act&district=greaterqueanbeyan-queanbeyan-region-nsw
Suburbs in Australian Capital Territory by distancefrom City [Online] / auth. My Boot // My Boot. 2011. - November 06, 2018. h]p://myboot.com.au/act/50/suburblist.aspx