# RECORD 07441798ac5873fe53746864fd3cf3231a87b056
# TITLE: Impact of infill development on prices of existing apartments in Finnish urban neighbourhoods
# YEAR: 2018.0  VENUE: nan  DOI: 10.3846/ijspm.2018.1540
# AUTHORS: Hannele Ahvenniemi; K. Pennanen; Antti Knuuti; A. Arvola; Kauko Viitanen
# PAGES: 11  CANDIDATE TABLE PAGES (1-based): [6, 7]
# ABSTRACT: Popularity of infill development is increasing because of the environmental benefits and cost saving potential it provides, which relate to the possibility to use existing infrastructure and services. However, the impact of infill development on value of existing properties has not been studied to a sufficient extent. Therefore, the aim of our study is to analyse whether infill development affects the prices of existing apartments. We carried out statistical analysis based on data from seven case neighbourhoods, and prices of more than 6000 housing transactions from one decade. The results of our analysis do not support the hypothesis of infill development affecting positively existing housing prices, but neither did the study show a significant negative effect. Both amenity effect and negative externalities may provide explanations as to why property values do not change due to infill development.


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Copyright © 2018 The Author(s). Published by VGTU Press
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unre-
stricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
International Journal of Strategic Property Management
ISSN 1648-715X / eISSN 1648-9179
2018 Volume 22 Issue 3: 157–167
https://doi.org/10.3846/ijspm.2018.1540
*Corresponding author. E-mail: hannele.ahvenniemi@aalto.fi
IMPACT OF INFILL DEVELOPMENT ON PRICES OF EXISTING 
APARTMENTS IN FINNISH URBAN NEIGHBOURHOODS
Hannele AHVENNIEMI1,*, Kyösti PENNANEN1, Antti KNUUTI1,  
Anne ARVOLA1, Kauko VIITANEN2
1 VTT Technical Research Centre of Finland, Espoo, Finland
2 Department of Real Estate, Planning and Geoinformatics, Aalto University School of Engineering, Espoo, Finland
Received 21 October 2015; accepted 27 June 2017
Abstract. Popularity of infill development is increasing because of the environmental benefits and cost saving potential it 
provides, which relate to the possibility to use existing infrastructure and services. However, the impact of infill develop-
ment on value of existing properties has not been studied to a sufficient extent. Therefore, the aim of our study is to ana-
lyse whether infill development affects the prices of existing apartments. We carried out statistical analysis based on data 
from seven case neighbourhoods, and prices of more than 6000 housing transactions from one decade. The results of our 
analysis do not support the hypothesis of infill development affecting positively existing housing prices, but neither did the 
study show a significant negative effect. Both amenity effect and negative externalities may provide explanations as to why 
property values do not change due to infill development.
Keywords: infill development, housing prices, urban neighbourhood, property value, price development.
Supplementary material associated with this article can be found, in the online version, at https://doi.org/10.3846/ijspm.2018.1540
Introduction
Because of the challenges posed by growing cities more 
focus today is put on developing existing neighbourhoods 
with infill development (for example Ooi & Le, 2013; Haa-
land & Bosch, 2015). Several studies have shown the envi-
ronmental benefits of infill construction or transit orient-
ed development, such as decreasing energy consumption 
and related smaller carbon footprint from transport (for 
example Clark, 2013; Nahlik & Chester, 2014; Glaeser & 
Kahn, 2010). Another observed benefit of infill develop-
ment is the cost-effectiveness, as the already existing in-
frastructure allows developing a neighbourhood with only 
moderate investment (Nykänen et al., 2012; Biddle, Ber-
toia, Greaves, & Stopher, 2006).
Even if a large number of economic and environmen-
tal benefits of infill development have been proven, and 
promoting infill development has been presented as one 
of the targets of the housing policy of the national gov-
ernment of Finland (Ministry of the Environment, 2016), 
new housing development is often, however, opposed by 
residents of the neighbourhood. Resistance to infill devel-
opment might occur when residents fear that the com-
munity does not benefit from the development or, even 
worse, the new development might have a negative impact 
by worsening the amenities of the neighbourhood or by 
resulting in negative value development of existing dwell-
ings (for example Matthews, Bramley, & Hastings, 2015). 
Even if fear of decreasing property values is a common 
reason behind the claims in planning practice, the impact 
of new development on existing housing has not been suf-
ficiently studied (Seppälä, 2013).
Our contribution to this research field is to examine, 
by using case studies, whether new housing developments 
affect the value of existing apartments in Finnish neigh-
bourhoods. Earlier studies, which are presented in sec-
tion 1, mainly focus on different type of real estate mar-
ket (metropolitan cities in the U.S. and Asia) or different 
housing types (such as single-family houses) and therefore 
our research is among the first ones to study the impact of 
infill development on value of dwellings in Nordic urban 
neighbourhoods.


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162
H. Ahvenniemi et al. Impact of infill development on prices of existing apartments in Finnish urban neighbourhoods
where the dependent variable P is sales price (1000€) per 
m². The independent variables are explained in Table 2. 
Epsilon (ε) stands for normally distributed error term.
The analysis was carried out separately for the seven 
cases. The studied point in time varied, depending on the 
timing of the infill development: we used transactions up 
to five years before and after infill development. A long 
enough time period before and after was chosen to ensure 
that 1) the expectations due to new developments would 
not yet have affected the prices in the “before” groups and 
2) the potential effects could be observed in the “after” 
groups. As the number of transactions per year remained 
rather small, in most cases we used transactions from a 
two-year period (in few cases it was necessary to study a 
three-year period). The sale prices were adjusted for infla-
tion using the Consumer Price Index, and with 2012 as 
the base year.
Table 2. Independent variables and mean values for the neighborhoods
Variable
Description
Mean
(N = 2762)
Min
Max
SD
CONDITION
Condition of the dwelling (0 = bad, 1 = average, 
3 = good)
1.754
0
3
1.13
ELEVATOR
Dummy for the elevator (0 = no, 1 = yes)
0.485
0
1
0.499
ROOMS
Number of rooms, excl. kitchen
2.373
1
6
0.962
FLOOR
Floor number/ number of total floors
0.645
0.1
1
0.281
SEA
Distance to the sea cost (m)
3 120
22
11 340
3 718
CBD
Distance to the city centre (railway station) (m)
9 881
2 951
21 124
4 894
GREEN
Distance to parks or green areas (m)
174.5
0
609
142
TREAT
Dummy for the treatment group (0 = control group, 1 = treatment group)
AFTER
Dummy for the “after infill development” cases (0 = before, 1 = after)
Table 3. Mean values of prices and on-sale days for treatment and control groups
PRICE/m2 (thousand €)
On-sale time
N
Before
After
Before
After
Before
After
Case 1
Treatment
1.919
2.384
59.4
62.8
61
100
Control
1.879
2.430
68.8
70.8
58
109
Case 2
Treatment
2.104
2.940
43.2
53.2
117
221
Control
2.027
2.910
39.1
44.5
54
120
Case 3
Treatment
1.631
2.260
47.6
41.3
79
67
Control
1.835
2.296
35.9
69.9
40
70
Case 4
Treatment
1.612
2.396
66.2
35.8
51
41
Control
1.741
2.605
47.2
46.9
149
68
Case 5
Treatment
2.802
4.436
30.6
72.3
45
138
Control
2.747
4.676
33.0
42.0
115
230
Case 6
Treatment
1.674
2.593
47.5
47.9
146
228
Control
2.140
2.949
44.7
43.7
28
44
Case 7
Treatment
1.184
1.758
45.6
59.3
36
116
Control
1.250
2.076
73.0
41.9
117
94
3. Result
Price development of both case neighbourhoods and ref-
erence neighbourhoods was analysed by examining the 
average sale prices before and after infill development. Av-
erage sale prices and average duration of apartments being 
on sale are shown in Table 3. A general price increase can 
be observed in all treatment and control groups indicating 
that both groups follow the rising price trend of housing 
transactions in the capital area of Finland. Also, changes 
in on-sale times give indication on the development of the 
housing market in each treatment and control neighbour-
hood. Longer on-sale time might lead into larger discount 
and hence, lower sale price. However, as the prices are 
consistently higher in the “after” cases but on-sale times 
vary largely (taking both larger and smaller values than in 
the “before” cases), no consistent logic between the sale 
prices and on-sale time can be observed.


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International Journal of Strategic Property Management, 2018, 22(3): 157–167
163
Figure 1 illustrates the development of average non-de-
flated sale prices in case neighbourhood 1 (Karakallio), in 
the corresponding reference neighbourhood (Viherlaakso) 
and the sale prices of new apartments in the case neigh-
bourhood. For comparison, also the price index of a larger 
surrounding area is presented. The graph illustrates how the 
price development in the case and the reference neighbour-
hood is very similar during the whole studied time frame, 
and the development of prices in both neighbourhoods also 
follow the development of the price index of the wider area. 
Similar graphs for the seven case neighbourhoods are pre-
sented in the Supplementary Appendix 1.
The results from the difference-in-difference hedonic 
regression are reported in Table 4. The following obser-
vations can be drawn from the regression results: Being 
located in a neighbourhood in which infill development 
takes place (TREAT) does not seem to provide higher 
prices compared to the control neighbourhood. In most 
cases the effect is insignificant, and in one of the cases with 
significant effect, the effect is the opposite, and the prices 
are higher in the control neighbourhood. Furthermore, as 
was observed also in Table 3, prices are constantly higher 
after infill development (AFTER) which is in line with the 
price trend of the whole capital area. The most interesting 
0
50
100
150
200
250
300
350
400
0
500
1 000
1 500
2 000
2 500
3 000
3 500
4 000
4 500
5 000
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Price index
Price, €/m² 
Year
Case 1 (Karakallio ‐ Espoo)
Karakallio (CN)
New apartments (CN)
Viherlaakso (RN)
Price index for the area
Infill development
Figure 1. Case 1: Mean values of sale prices (by m2) of old apartments in the case 
neighbourhood (CN), the reference neighbourhood (RN), new apartments in the 
case neighbourhood and the price index in the area
Table 4. Results of the difference-in-difference hedonic regression analyses of the seven cases
Case 1
Case 2
Case 3
Case 4
Case 5
Case 6
Case 7
CONDITION
0.0991***
(0.0149)
0.120***
(0.0181)
0.0750**
(0.0236)
0.050**
(0.0187)
0.1360***
(0.0187)
0.0541**
(0.0180)
0.0758***
(0.0011)
ELEVATOR
0.0695 
(0.0401)
0.0079
(0.0422)
0.1287
(0.1104)
0.0161
(0.0446)
–0.1336**
(0.0492)
–0.0249
(0.0436)
0.0253
(0.0256)
ROOMS
–0.2708***
0.0161
–0.2565***
(0.0189)
–0.2929***
(0.0250)
–0.2427*
(0.0216)
–0.091***
(0.0019)
–0.2384***
(0.0187)
–0.2798***
(0.0157)
FLOOR
–0.0617
(0.05654)
0.1484*
(0.0633)
0.0852
(0.0709)
0.0438
(0.0657)
0.2984***
(0.0074)
–0.0107
(0.0675)
0.1189**
(0.0399)
SEA
–0.00031 
(0.00075)
–0.00070***
(0.00019)
0.0017**
(0.005519
–0.00019
(0.00021)
–0.00076***
(0.00019)
–0.0003**
(–0.00010)
4.677e–5
(8.573e–5)
CBD
0.00051
(0.00069)
0.000132*
(0.000629)
–0.0016**
(0.0005349)
0.00023
(0.0002)
0.00017**
(6.175e–5)
0.00010
(9.64e–5)
–0.0002**
(7.082e–5)
GREEN
0.00049***
(0.00012)
–0.000495**
(0.000185)
1.089e–6
(0.6365e–3)
0.00004
(0.00016)
–0.00018
(0.00023)
7.77e–5
(0.0001)
–5.349e–5
(0.00015)
TREAT
0.2943**
(0.1074)
0.1873
(0.1094)
0.7863*
(0.3022)
–0.0244
(0.1102)
0.2010*
(0.100)
–0.7073**
(0.2201)
0.4244*
(0.1981)
AFTER
0.5759***
0.0508
0.756***
(0.0751)
0.4324***
(0.0757)
0.8114***
(0.0504)
1.847***
(0.0574)
0.8183***
(0.1171)
0.8264***
(0.0321)
TREAT*AFTER
–0.0953
(0.0692)
–0.0298
(0.0905)
0.0641
(0.0852)
–0.1545
(0.0857)
–0.2703**
(0.1018)
0.1426
(0.1310)
–0.1597*
(0.0770)
Multiple R2
0.6885
0.6012
0.7302
0.7499
0.7855
0.664
0.8112
The dependent variable is price (thousand €) per m2. The significance levels are ***<0.001, **<0.01, *<0.05. The standard errors of coefficients are 
reported in brackets.


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164
H. Ahvenniemi et al. Impact of infill development on prices of existing apartments in Finnish urban neighbourhoods
information is provided by the variable TREAT*AFTER. 
This variable shows the effect of being located in both the 
treatment group and the “after” group. However, the ef-
fect remains insignificant in most cases. Only in case 5, 
the variable shows a more significant effect, but the effect 
is opposite to our assumption, suggesting lower prices for 
apartments being located in the treatment neighbourhood 
(after treatment). The specific nature of the case 5 neigh-
bourhoods however suggests that the results do not neces-
sarily indicate a negative price effect of infill development; 
In case 5, the treatment and control neighbourhoods are 
located on an island, which implies that attributes such as 
location close to the sea and high floor number are highly 
valued by the residents (as is also shown by the results 
of the regression analysis). Even more importantly, the 
on-going construction of a new metro line with a metro 
station in the central area of the island (which is also the 
location of the control neighbourhood) has supposedly, 
already since several years, provided a price premium for 
apartments located nearby.
Regarding other independent variables of our model, 
the impact of structural characteristics of the apartments/
buildings seems as expected: Larger room number leads to 
lower prices per m2 and the good condition of the apart-
ment provides a significant price premium. Higher floor 
number in relation to total floor number has a positive 
significant effect on prices in a few cases but not in all. 
Also surprisingly, access to elevator does not have a signif-
icant effect implying that apartments in low-rise buildings 
might be more preferred than apartments in tall buildings.
The effect shown by the environmental variables are 
somewhat as expected. Decreasing distance to sea has a 
significant positive effect on prices in those neighbour-
hoods which are located close to the coastline, whereas in 
others the impact is insignificant. Distance to CBD has a 
similar effect in two cases but the opposite effect in one 
case (case 5). In case 5 this abnormality can be explained 
by the specific characteristics of the neighbourhood (al-
ready explained earlier), which are likely to affect prices 
more than distance to CBD. Although earlier research has 
suggested a positive price impact of parks and green ar-
eas, our analysis does not show a price premium provided 
by easy access to green areas. In case 1, the effect is even 
against the assumption suggesting that prices are higher 
in locations with longer distances to green areas. This can 
however be explained by the geography of the area; as the 
whole area is surrounded by woods, it is not surprising 
that a location closer to the centre of the area, and closer 
to services (and also further away from the woods), might 
be more preferable.
Conclusions and discussion
Only a rather limited number of studies have examined 
whether infill development affects the prices of existing 
housing. These studies differ from each other regarding 
the type of buildings considered (single-family houses or 
apartments), and most of the studies focus on the U.S. 
housing market covering a rather limited geographic area. 
Thus our study sheds light on a geographic area and a type 
of housing market which has so far been rather undiscov-
ered, regarding the impact that infill development has on 
existing properties. All the selected case neighbourhoods 
are typical urban areas in the capital region of Finland, 
with a large number of residential apartment buildings 
built in the 60s, 70s and 80s. Even though our study is 
based on individual cases, we however do cover the capi-
tal area fairly well with case neighbourhoods spread over 
three cities (Helsinki, Espoo and Vantaa). During those 
years, a similar construction boom took place also in oth-
er European countries, and these buildings are currently 
facing challenges because of increasing renovation need, 
some also being in need of a “facelift”. It has been sug-
gested that infill development can have a crucial role re-
garding these issues, both by contributing to the upgrade 
of the neighbourhood as well as providing housing com-
panies with a solution to finance their renovation. Hence, 
the results of our study are undoubtedly of interest to a 
number of different actors, who might be involved with 
processes related to infill development, ranging from in-
dividual apartment owners to city planners.
Our study examined the effect of infill development on 
the prices of existing apartments by using difference-in-
difference hedonic regression. We carried out the analysis 
for seven case neighbourhoods and appointed reference 
neighbourhoods and analysed whether prices before infill 
development were statistically different from prices after 
in the two neighbourhood groups. Overall, the results 
showed no significant difference in price development. 
Hence the results of our analysis indicate that infill de-
velopment has no significant impact on prices of existing 
apartments. Only in one case a more significant effect of 
being located in the treatment group was observed, but 
in this case the regression analysis suggested a negative 
impact. However, given the specific nature of this neigh-
bourhood (being located on an island and the new metro 
line being built in the control neighbourhood), this result 
should not be considered as indication of a negative price 
effect of infill development.
Our results are in line with most of the previous studies 
which also did not find strong or any correlation between 
infill development and changes in housing prices (Blan-
chard et al., 2008; Zahirovich-Herbert & Gibler, 2014; Pol-
lakowski et al., 2005). Only two studies are contradicting 
with our results suggesting a significant impact (Ooi & 
Le, 2013; Mathur & Ferrell, 2013) but these studies differ 
greatly from our research by the location of the studies 
(Singapore and California) and by the type of housing 
studied (single-family houses in the study by Mathur & 
Ferrell, 2013).
To find explanations for the results, it is important to 
understand the specific nature of the property market. 
Attributes such as purchasing power, size and features of 
the neighbourhood affect the value of residential prop-
erties. Also, the general economic situation and develop-
ment (such as economic recession or depression) affect the