# RECORD 18a3ce8a193301208557e0d6f2d027166917cb25
# TITLE: Impact of ground source heat pumps on house sales prices in Finland
# YEAR: 2023.0  VENUE: Energy Efficiency  DOI: 10.1007/s12053-023-10084-x
# AUTHORS: J. Vimpari
# PAGES: 13  CANDIDATE TABLE PAGES (1-based): [8, 9, 10]
# ABSTRACT: Buildings contribute to approximately 28% of global energy-related emissions. Heat pumps are a key technology for decarbonising the heating emissions of buildings. This study focuses on ground source heat pumps (GSHP), which are increasingly used in colder regions. Since, for an average home, the capital expenditure of GSHP can be an order of magnitude higher than that of traditional heating, it is important to understand whether GSHP has an impact on house transaction prices. A hedonic price model was constructed to estimate the sales prices of detached houses, where heating type is the main variable of interest. The hedonic analysis revealed that for detached houses, GSHP had a statistically significant positive impact of 5.33% on house sales prices. Further analysis puts the premium in the context of housing prices in different locations in Finland. An average house in the Helsinki Metropolitan Area (HMA) could cover the required capital expenditure of a GSHP system with the sales price premium, whereas in other areas in Finland, 5 years of energy savings are required on top of the premium. Hence, in locations with lower housing prices, the house must be owned for a longer period to recoup the investment costs. This is important to understand when national energy aid policies are planned to accelerate investments in heat pumps.


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https://doi.org/10.1007/s12053-023-10084-x
SHORT COMMUNICATION
Impact of ground source heat pumps on house sales prices 
in Finland
Jussi Vimpari
Received: 25 May 2022 / Accepted: 14 January 2023 
© The Author(s) 2023
Abstract  Buildings contribute to approximately 
28% of global energy-related emissions. Heat 
pumps are a key technology for decarbonising the 
heating emissions of buildings. This study focuses 
on ground source heat pumps (GSHP), which are 
increasingly used in colder regions. Since, for an 
average home, the capital expenditure of GSHP can 
be an order of magnitude higher than that of tradi-
tional heating, it is important to understand whether 
GSHP has an impact on house transaction prices. A 
hedonic price model was constructed to estimate the 
sales prices of detached houses, where heating type 
is the main variable of interest. The hedonic analy-
sis revealed that for detached houses, GSHP had a 
statistically significant positive impact of 5.33% on 
house sales prices. Further analysis puts the pre-
mium in the context of housing prices in different 
locations in Finland. An average house in the Hel-
sinki Metropolitan Area (HMA) could cover the 
required capital expenditure of a GSHP system with 
the sales price premium, whereas in other areas in 
Finland, 5  years of energy savings are required on 
top of the premium. Hence, in locations with lower 
housing prices, the house must be owned for a longer 
period to recoup the investment costs. This is important 
to understand when national energy aid policies are 
planned to accelerate investments in heat pumps.
Keywords  Heat pump · House prices · Hedonic 
model · Energy prices · Housing market
Introduction
Buildings contribute to approximately 28% of global 
energy-related emissions (IEA, 2020a). In the USA, 
20% of the nation’s greenhouse gas emissions come 
from heating, cooling and powering households 
(Goldstein et al., 2020). In Germany, private house-
holds’ energy consumption causes approximately 
31% of Germany’s total CO2 emissions (Destatis, 
2021; Ritchie & Roser, 2020). In the UK, heating in 
the residential sector accounts for approximately 21% 
of CO2 emissions (National Statistics, 2020a, b). In 
Finland, building heating and electricity consumption 
caused 36% of all emissions, of which roughly two-
thirds were from heating (SYKE, 2020).
Heat pumps are a key technology for decarbonis-
ing the heating sector. Currently, only 5% of global 
heat is delivered with heat pumps, but this may tri-
ple by 2030, and eventually, heat pumps could cover 
90% of the global space and water heating needs for 
low emissions (IEA, 2020b). Ram et al. (2019) cal-
culated that by 2050, over €7 trillion will be invested 
into individual heat pumps that heat or cool buildings. 
Currently, the European Commission (2022) and its 
J. Vimpari (*) 
Department of Built Environment, Real Estate Economics, 
Aalto University, P.O. Box 11000 (Otakaari 1B), Aalto, 
FI‑00076 Espoo, Finland
e-mail: jussi.vimpari@aalto.fi
/ Published online: 23 January 2023


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on heating costs, as older buildings that are in a bad 
condition have lower energy efficiency.
When a location is controlled, the GSHP premium 
drops dramatically. This is expected because in the 
dataset, GSHP houses had a larger market share in 
cities with higher prices (see Tables 2 and 3). Adding 
the lower-level, time-varying neighbourhood charac-
teristics did not have a significant effect on either the 
performance or the estimates. When building char-
acteristics were added, the performance increased by 
approximately 0.22 in both regression models, but the 
price premiums also decreased. This change was then 
further analysed by excluding first age, then condi-
tion and then both from the final model. The perfor-
mance remained high, but interestingly, these exclu-
sions decreased the price premium. This suggests that 
GSHP houses did not have some unseen conditional 
effect that accounted for the estimated GSHP price 
premium.
Further analysis was conducted by estimating how 
the premiums had developed over time and in differ-
ent cities. Two regression models are created with 
interaction variables, see Table 6.
There positive premiums have been quite consist-
ent since 2010, when the heating costs also started 
to increase more rapidly than housing prices, as pre-
sented in Fig. 1. However, the positive housing price 
developments were fuelled by higher loans and very 
low interest rates. Since heating costs are paid by 
available income rather than the debt that is used for 
buying the house itself, the increasing trend in pre-
miums could be linked to the ratio between avail-
able income and energy costs. Figure 3 presents the 
indexed development of electricity prices and district 
heating (oil is excluded given the high volatility), 
as well as wages and salaries in Finland (Statistics 
Finland, 2021b,  d). Up until the financial crisis in 
2007–2009, heating costs and wages followed each 
other. However, since the financial crisis, there has 
been a clear and growing gap between these indexes. 
Regarding the municipality interaction variable, 6 
municipalities have a statistically significant positive 
price premium with quite a bit of volatility between 
the size of the premium.
Economic return of GSHP in detached houses
The total economic and environmental performance 
of GSHP was estimated for an average detached 
house in Finland. At the end of 2020, the average 
selling price of an old, detached house in HMA 
was 3 369 €/sqm and in the rest of Finland, it was 
1 497 €/sqm (Statistics Finland, 2021b). Based on 
Table 4   Hedonic OLS 
regression estimates of log 
sales prices
Statistically significant at 
***1% level, **5% level, 
*10% level. AGSHP true/
false, i.e. other heating 
types as one category. 
BEvery heating type as own 
category, direct electricity 
omitted. The following 
categorical variables are 
omitted: condition = decent, 
lot_ownership = own
GSHPA
Heating ­typeB
Coefficient
SE
Coefficient
SE
Intercept
12.6308***
0.1405
12.6097***
0.1404
C(GSHP)[T.True]
0.0519***
0.0060
C(heating_type)[T.district_heating]
0.0126***
0.0046
C(heating_type)[T.GSHP]
0.0474***
0.0062
C(heating_type)[T.oil]
 − 0.0228***
0.0041
Sqm
0.0039***
0.0000
0.0039***
0.0000
Age
 − 0.0051***
0.0001
 − 0.0049***
0.0001
Distance to CBD
 − 0.0161***
0.0015
 − 0.0160***
0.0015
C(condition)[T.excellent]
0.3189***
0.0200
0.3170***
0.0200
C(condition)[T.good]
0.1800***
0.0037
0.1791***
0.0037
C(condition)[T.poor]
 − 0.2987***
0.0080
 − 0.2995***
0.0080
C(lot_ownership)[T.rented]
 − 0.0561***
0.0040
 − 0.0593***
0.0041
Sale year and month fixed effects
Yes
Postcode fixed effects
Yes
Neighbourhood characteristics
Yes
N
19,008
Adj. R2
0.851
0.851
4
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building data statistics, the average house in HMA 
was constructed in 1984 and has a living area of 181 
sqm (Statistics Finland, 2021c). The correspond-
ing house in the rest of Finland was constructed in 
1972 and has an area of 143 sqm. Using the above 
square metre prices, the respective values of these 
houses were estimated at €609 789 and €214 071. 
Thus, the premium of 5.33% would indicate a price 
premium of €32 484 in HMA and €11 404 in the 
rest of Finland.
Using the methodology presented by Vimpari 
(2021), the actual energy consumption of these build-
ings was estimated based on the floor area, construc-
tion year and location. For the rest of Finland, the 
city of Kuopio (located in the centre of Finland) was 
used as a reference point, as the climate is colder and 
Table 5   Sensitivity analysis of regression estimates
Statistically significant at ***1% level, **5% level, *10% level, standard errors in parenthesis. AGSHP true/false, i.e. other heating 
types as one category. BEvery heating type as own category, direct electricity omitted
GSHPA
1
2
3
4
4a
4b
4c
C(GSHP)[T.True]
0.2175***
0.0976***
0.0898***
0.0519***
0.0555***
0.0363***
0.0374***
(0.0140)
(0.0096)
(0.0094)
(0.0060)
(0.0064)
(0.0067)
(0.0076)
Sale year and month fixed 
effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Postcode fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
Neighbourhood character-
istics
Yes
Yes
Yes
Yes
Yes
Building characteristics
Yes
Yes
Yes
Yes
  Exclude age
Yes
Yes
Yes
  Exclude condition
Yes
Yes
  Exclude age and condi-
tion
Yes
N
19,008
Adj. R2
0.1309
0.6179
0.6332
0.8507
0.8282
0.8119
0.7609
Heating ­typeB
1
2
3
4
4a
4b
4c
C(heating_type)[T.district_
heating]
0.0661***
0.0394***
0.0353***
0.0126***
0.0262***
0.0121**
0.0338***
(0.0089)
(0.0071)
(0.0070)
(0.0046)
(0.0049)
(0.0051)
(0.0057)
C(heating_type)[T.GSHP]
0.2023***
0.0810***
0.0762***
0.0474***
0.0436***
0.0297***
0.0184**
(0.0142)
(0.0097)
(0.0096)
(0.0062)
(0.0066)
(0.0069)
(0.0077)
C(heating_type)[T.oil]
 − 0.1354***  − 0.0832***  − 0.0710***  − 0.0228***  − 0.0564***  − 0.0305***  − 0.0874***
(0.0089)
(0.0064)
(0.0063)
(0.0041)
(0.0043)
(0.0046)
(0.0051)
Sale year and month fixed 
effects
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Postcode fixed effects
Yes
Yes
Yes
Yes
Yes
Yes
Neighbourhood character-
istics
Yes
Yes
Yes
Yes
Yes
Building characteristics
Yes
Yes
Yes
Yes
  Exclude age
Yes
Yes
Yes
  Exclude condition
Yes
Yes
  Exclude age and condi-
tion
Yes
N
19,008
Adj. R2
0.1480
0.6228
0.6368
0.8510
0.8303
0.8124
0.7658
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heating requirements are higher compared to HMA, 
which is in the south. Oil was used as the current heat-
ing system. Table 7 presents details regarding current 
heating costs and emissions, as well as the numbers 
of whether GSHP is the heating system. Additionally, 
some details of GSHP are provided, together with key 
financial parameters, such as the payback period and 
the internal rate of return (IRR). The heating costs 
and emissions are higher for the building in the rest of 
Finland, even though they are 21% smaller. The loca-
tions in a colder region, as well as an older construc-
tion year with worse insulation, are the reasons for 
this. However, savings from GSHP are larger for the 
building in HMA, a key reason being that the coef-
ficient of performance for GSHP is higher in southern 
Finland and electricity (distribution) prices are lower. 
Heating costs and emissions in HMA are reduced by 
approximately 71% and 94%, respectively, compared 
to the buildings in the rest of Finland, with 58% and 
93%, respectively. In both cases, the payback period 
for the investment was approximately 10 years with-
out considering the potential sales price premium. 
The lifecycle investment performance (IRR) was 
slightly better for the building in HMA.
Finally, the number of years of energy savings 
on top of the price premium required to cover the 
capital expenditure of GSHP was calculated. In 
HMA, 0 years of energy savings plus the price pre-
mium cover the investment costs, whereas 5  years 
are needed in the rest of Finland. This highlights the 
relationship between the investment costs of a GSHP 
system and housing prices. The relative investment 
Table 6   Interaction variable estimations for GSHP houses
Interaction variable for sale year:GSHP true
Interaction variable for municipality:GSHP true
Coefficient
SE
Coefficient
SE
Intercept
12.6364***
0.1405
Intercept
12.5322***
0.1624
C(GSHP)[T.True]:C(sale_year)[1999]
 − 0.0186
0.0514
C(GSHP)[T.True]:C(municipality)[Espoo]
0.0932***
0.0142
C(GSHP)[T.True]:C(sale_year)[2000]
 − 0.0317
0.0570
C(GSHP)[T.True]:C(municipality)[Helsinki]
0.0374**
0.0155
C(GSHP)[T.True]:C(sale_year)[2001]
0.0574
0.0434
C(GSHP)[T.True]:C(municipality)[Kuopio]
0.0162
0.0340
C(GSHP)[T.True]:C(sale_year)[2002]
 − 0.0147
0.0415
C(GSHP)[T.True]:C(municipality)[Lahti]
0.0641***
0.0223
C(GSHP)[T.True]:C(sale_year)[2003]
 − 0.0157
0.0406
C(GSHP)[T.True]:C(municipality)[Oulu]
0.0783***
0.0176
C(GSHP)[T.True]:C(sale_year)[2004]
0.0654*
0.0357
C(GSHP)[T.True]:C(municipality)[Tampere]
0.0319**
0.0133
C(GSHP)[T.True]:C(sale_year)[2005]
0.0836***
0.0288
C(GSHP)[T.True]:C(municipality)[Turku]
0.0430***
0.0148
C(GSHP)[T.True]:C(sale_year)[2006]
0.0226
0.0283
C(GSHP)[T.True]:C(municipality)[Vantaa]
0.0235
0.0198
C(GSHP)[T.True]:C(sale_year)[2007]
0.0037
0.0296
Sale year and month fixed effects
Yes
C(GSHP)[T.True]:C(sale_year)[2008]
0.0555*
0.0298
Postcode fixed effects
Yes
C(GSHP)[T.True]:C(sale_year)[2009]
0.0311
0.0338
Neighbourhood characteristics
Yes
C(GSHP)[T.True]:C(sale_year)[2010]
0.0853***
0.0287
Building characteristics
Yes
C(GSHP)[T.True]:C(sale_year)[2011]
0.0990***
0.0250
N
19,008
C(GSHP)[T.True]:C(sale_year)[2012]
0.0499**
0.0235
Adj. R2
0.851
C(GSHP)[T.True]:C(sale_year)[2013]
0.0190
0.0227
C(GSHP)[T.True]:C(sale_year)[2014]
0.0417*
0.0219
C(GSHP)[T.True]:C(sale_year)[2015]
0.0315*
0.0191
C(GSHP)[T.True]:C(sale_year)[2016]
0.0624***
0.0189
C(GSHP)[T.True]:C(sale_year)[2017]
0.0771***
0.0182
C(GSHP)[T.True]:C(sale_year)[2018]
0.0846***
0.0175
Sale year and month fixed effects
Yes
Postcode fixed effects
Yes
Neighbourhood characteristics
Yes
Building characteristics
Yes
N
19,008
Adj. R2
0.851
4
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Fig. 3   Development of 
heating costs and wages in 
Finland
0
50
100
150
200
250
300
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
Index (1999=100)
District Heang
Electricity
Wages andSalary
Table 7   Overall economic 
and environmental analysis 
of GSHP in an average 
detached house
HMA
Other Finland
Average detached house
  Price (€/sqm)
3 369
1 497
  Average construction year
1 984
1 972
  Average floor area (sqm)
181
143
  Price, average detached house (€)
609 789
214 071
  Energy consumption (MWh p.a.)
35
38
  Heating costs, oil (€ p.a.)
3 500
3 800
  Heating emissions, oil (kg CO2-ekv p.a.)
10 300
11 200
GSHP investment
  Heat pump investment Cost (€)
26 000
22 000
  Heat peak power demand (kW)
17
14
  GSHP peak power demand (kW)
13
11
  Borehole production (kWh/metre)
100
90
  Heating costs, GSHP (€ p.a.)
1000
1600
  Heating emissions, GSHP (kg CO2-ekv p.a.)
600
800
  Savings on heating costs (€ p.a.)
2500
2200
  Reduced emissions (kg CO2-ekv p.a.)
9 700
10 400
  Payback period (a)
10,4
10,0
  IRR
10,9%
9,9%
GSHP premium
  Mean (5.33%)
32 484
11 404
  Lower bound (4.08%)
24 886
8 736
  Upper bound (6.61%)
40 302
14 148
Years to cover investment cost minus price premium
  Mean (5.33%)
0,0
4,8
  Lower bound (4.08%)
0,5
6,0
  Upper bound (6.61%)
0,0
3,6
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