Copy igh © 2017 The Au ho s. Published by VGTU P ess.
This is an open-access a icle dis ibu ed unde he e ms o he C ea i e Commons A ibu ion-NonComme cial 4.0 (CC BY-NC 4.0)
license, which pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in any medium, p o ided he o iginal au ho and sou ce a e
c edi ed. The ma e ial canno be used o comme cial pu poses.
Sma Specializa ion S a egy and i S
ope a ionaliza ion in he egional policy: caSe Finland
Ja i KaiVo-oJa1, Saku VÄhÄSan anen2, a i Ka ppinen3,
eemu haUKioJa4
1Finland Fu u es Resea ch Cen e, Tu ku School o Economics, Uni e si y o Tu ku
2Regional Council o Sa akun a, Po i, Finland
3School o Managemen , Uni e si y o Tampe e, FI-33014 Tampe een yliopis o,
Tampe e, Finland
4Po i Uni , Tu ku School o Economics, Uni e si y o Tu ku,
P.o. Box 170 (Pohjois an a 11A), FI-28101 Po i, Finland
E-mails: 1[email p o ec ed] (co esponding au ho ); 2[email p o ec ed];
3[email p o ec ed]; 4[email p o ec ed]
Recei ed 6 Feb ua y 2017; accep ed 7 May 2017
abs ac . In he Eu opean Union, sma specializa ion is an impo an concep in
egional policy. I s p ima y aim is o achie e inclusi e and sus ainable economic
g ow h. The e is a lack o con enien egion speci ic measu es o ope a ionalize
sma specializa ion s a egies (S3). The pu pose o he pape is o ind “indices
o sma specializa ion” on a egional le el. We p opose indices ha a e based
on (1) he a e o indus ial di e si ica ion, (2) e ealed compa a i e ad an age
and (3) egions’ o e all ela i e specializa ion. In he empi ical pa , we analyze
sma specializa ion in Finland using s uc u al da a p o ided by S a is ics Finland
o se en y sub- egions (LAU1) and 24 sub-indus ies in manu ac u ing. These
indus ies a e he mos impo an o expo s, p oduc i i y, and egional economic
pe o mance o a small coun y. The ollowing indices a e used in empi ical
e alua ions: He indahl-Hi schman Index (HHI) o egional di e si y, Balassa-
Hoo e Index (BHI) o e ealed compa a i e ad an age, and Region’s Rela i e
Specializa ion Index (RRSI) o agg ega e egional specializa ion di e ences. The
concep o sma specializa ion is ela ed o hese measu es. Index analyses e eal
ha many g owing sub- egions ha e simila compa a i e ad an ages. This means
in e - egional syne gy, and i enables oppo uni ies o s a egic coope a ion be-
ween egions. To de elop sma specializa ion s a egies o Eu ope’s egions, we
need hese kinds o empi ical knowledge-based managemen ools and planning
app oaches.
Keywo ds: sma specializa ion, Finland, manu ac u ing, sub-indus y, LAU1,
He indahl-Hi schman index (HHI), Balassa-Hoo e index (BHI), e ealed com-
pa a i e ad an age, Region’s ela i e specializa ion index (RRSI).
Jel Classi ica ion: B41, C18, C43, D20, D78, F14, F43, F63, H70, I23, I25, I52,
L60, L78, N80, O12, O32, O33, R10, R11, R12, R58, Z18.
Business, ManageMen and educa ion
ISSN 2029-7491 / eISSN 2029-6169
2017, 15(1): 28–41
doi:10.3846/bme.2017.362
29
Business, Managemen and Educa ion, 2017, 15(1): 28–41
1. In oduc ion
The Eu opean Union has a cohesion policy which unde lines in eg a ed and place-
based economic con e gence. The gene al dimensions o Na ional/Regional Resea ch
and Inno a ion S a egies o Sma Specialisa ion (S3 s a egies) a e policy suppo and
in es men s, spa ial s eng hs, compe i i e ad an age and excellence, inno a ion ac i i-
ies, s akeholde s’ pa icipa ion, and expe imen s and e idence-based policy (Eu opean
Commission 2014: 1). We ocus he e on he e idence-based s a egy ools o RIS3.
We shall demons a e he use o some egional planning and managemen ools,
which a e sui able o sma specializa ion (S3) analysis and managemen . We expec
hese me hods a e use ul in he egional policy p ocesses o he Eu opean Union. The
EU egions a e acing many challenges o he global economy and global poli ical land-
scape. The spa ial con ex o ou analysis is Finland and i s sub- egions (LAU1). Ea lie ,
Ka ppinen and Vähäsan anen (2015) ha e s udied he esilience o Finnish sub- egions
by ocusing on manu ac u ing indus ies. This means ha ou analysis can be applied
in all he LAU1-le el sub- egions in he Eu opean Union. The e is la ge and g owing
li e a u e on he issue o sma specializa ion (Capello 2014; McCann, O ega-A gilés
2015; Fo ay 2015; Gianelle e al. 2016). In addi ion o he EU, also he OECD has paid
a en ion o his issue in i s epo (OECD 2013). In b oade in e na ional pe spec i e,
sma specializa ion has been seen a policy ele an opic.
Ou amewo k is closely linked o he mains eam hinking o economics. We em-
phasize he iden i ica ion o po en ial domains o specializa ion ha migh be bene icial
o he coun y gi en i s p oduc i e asse s (Fo ay 2011). We ocus on he indus ies, he
mos impo an elemen o Qua e Helix, when analysing sma specializa ion s a egy
in he egional con ex . O he key elemen s o he helix a e he academia, he go e n-
men , and ci il socie y wi h ci izens (see e.g. Fo ay e al. 2009; Fo ay 2011, 2012, 2014,
2015; San onen e al. 2014; Vi kkala e al. 2014; S3 Pla o m 2015; Johnson 2015; Mc-
Cann, O ega-A gilés 2015). The p inciple o compa a i e ad an age1 and he s uc u e
o spa ial economic ac i i y ha e been key opics in he ield o egional economics.
Ou aim is o link hese wo impo an app oaches o he discussion on sma speciali-
za ion s a egy. This c i ical aspec o sma specializa ion has been lacking in many
scien i ic a icles, which ha e analysed and elabo a ed sma specializa ion s a egy in
he Eu opean Union (see e.g. Juce icius, Galbuogiene 2014; Sipilo a 2015; Gule 2015;
Paliokai e e al. 2015; Paliokai e e al. 2016; Gheo ghiu e al. 2016). We shall p o ide
a new empi ical ool package o he analysis o sma specializa ion s a egy in he
Eu opean Union. Measu emen o hese economic issues is impo an o he sma
specializa ion s a egy in EU-coun ies and EU- egions (Gianelle e al. 2016).
1 Compa a i e ad an age is a adi ional concep in he ield o in e na ional ade. We apply he hypo hesis o e-
ealed compa a i e ad an age, which is pa allel o compe i i e ad an age in a egional con ex (see e.g. Thissen
e al. 2013: 34–35).
30
J. Kai o-oja e al. Sma specializa ion s a egy and i s ope a ionaliza ion in he egional policy: case Finland
Poli ical decision-make s in Eu opean Union a e oday e y in e es ed in key suc-
cess ac o s like economic g ow h, jobs, and in es men s (see Eu opean Commission
2017). These economic success ac o s a e always linked o egional economies in he
Eu opean Union. The idea o sma specializa ion can be conside ed a s a egic plan-
ning policy ins umen . Ou mo i a ion is o show how egions in he Eu opean Union
can analyse he ac ual con en s o sma specializa ion policy in hei local ac i i ies. In
he p ac ice o egional economic policy, we can imp o e economic p oduc i i y and
expo success h ough sma specializa ion. We a gue ha sma specializa ion s a egy
mus be based on he knowledge o basic eali ies o egional economy and place-based
indus ial ac i i y/s uc u e.
2. heo e ical amewo k
In scien i ic li e a u e, he concep s o inno a ion, compe i i e ad an age, and spa ial
de elopmen a e closely in e connec ed (Bo seko a e al. 2016). These concep s ha e
a ious common ea u es and a e he subjec o many deba es among p ac ione s and
academics. This a icle ocuses on compe i i e ad an age and spa ial de elopmen , bu
we unde s and ha all kinds o inno a ion ac i i ies a e shaping local economies and
indus ies. Cu en indus ial s uc u es and egional compe i i e ad an ages a e ou pu s
o inno a ion ac i i ies (Fig. 1).
The sma specializa ion s a egy depends on he h ee key elemen s desc ibed below.
I (1) he e is no much inno a ion and R&D ac i i y, i (2) he e a e no much compe i-
i e ad an ages in local economies, and i (3) spa ial de elopmen is no e ec i e and
economy is no deli e ing economic g ow h, wel a e, and happiness, he de elopmen
p ocess is no ully based on sma specializa ion s a egy. Ou empi ical analysis is
ocused di ec ly on he measu emen o compe i i e ad an age and spa ial de elopmen .
Inno a ion ac i i ies a e d i ing o ces o spa ial economic g ow h, bu in his a icle
we a e ocusing on ealized compe i i eness.
The elemen s o (1) c ea i e des uc ion and en ep eneu ial disco e y (see e.g. Ma-
li an a 2005) and (2) lexible se endipi y managemen can play egene a i e oles in
spa ial de elopmen (see e.g. Kakko e al. 2016; Ro h e al. 2017; Gheo ghiu e al.
2016). These aspec s do no elimina e he ole o s a egic planning in he con ex o
spa ial de elopmen .
Fig. 1. In e connec ions among inno a ion, compe i i e ad an age, and spa ial de elopmen
(Bo seko a e al. 2016).
31
Business, Managemen and Educa ion, 2017, 15(1): 28–41
In nex sec ions, we de ine ou empi ical analysis ools o he sma specializa ion
s a egy. Sma specializa ion o he EU egions does no happen in a acuum. Globali-
za ion, hype compe i ion, and apid echnological changes eshape he condi ions o
egions and local economies con inuously (see Fig. 2 abo e). Mindse s o local s ake-
holde s play an impo an ole in he o mula ion o sma specializa ion s a egies (see
Laha i, Pe ez-No d ed 2008; Vi kkala e al. 2014).
Based on Fig. 2 we can unde s and ha i is impo an ha he mindse s o s ake-
holde s (global mindse , i ual mindse , inno a ion mindse , and collabo a ion mindse )
co ela e wi h he eali ies o globaliza ion, hype compe i ion, and apid echnological
change. Ou empi ical app oach di ec ly suppo s egional and local eali y checks in
his espec .
3. Index amewo k o he s udy
All he ollowing indices a e based on Ka ppinen and Vähäsan anen (2015).
He indahl-Hi schman Index (HHI)
We apply he He indahl-Hi chman Index (HHI) o he Finnish sub- egion da a. Ou
da a includes 71 sub- egions and 24 indus ial sec o s. The He indahl-Hi schman index
(HHI) is a commonly accep ed measu e o ma ke concen a ion. We a e no analyzing
ma ke sha es bu he indus y sha es o sub- egions. The HHI o mula is he ollowing:
2
1=

=

∑
ni
ss
i
x
HHI x

(1)
whe e xi is he numbe o employed people in indus ial sec o (i) and x is o al numbe
o people employed in all indus ial sec o s in egion (s) and n is numbe o indus ial
sec o s (n). HHI-index is calcula ed as he sum o squa ed indus y sha es o each
sub- egion. In o he wo ds, i measu es he di e si ica ion o indus y s uc u e o a
Fig. 2. F amewo k showing ela ionships be ween compe i i e challenges, mindse s, and sma spe-
cializa ion challenges (modi ied, see Laha i, Pe ez-No d ed 2008: 313).
32
J. Kai o-oja e al. Sma specializa ion s a egy and i s ope a ionaliza ion in he egional policy: case Finland
sub- egion. HHI akes alues be ween [0,1]. The smalle he alue, he mo e di e si ied
egion, and ice e sa.
Balassa-Hoo e Index (BHI)
The key index in his s udy is he Balassa-Hoo e Index (BHI). The o mula o BHI is
he ollowing:
BHIsi =
si
i
s
x
X
x
X
(2)
whe e xsi is he numbe o employed people in egion s and in indus y i, (Xsi/Xi) is
co esponding sha e o all sub- egions. I BHIsi ≥ 1, he e is e ealed compa a i e
ad an age in ela ion o all egions. We use BHI wi h indus ial labo da a o S a is ics
Finland (2017).
Region’s Rela i e Specializa ion Index (RRSI)
We use RRSI as a measu e o compa a i e specializa ion o sub- egions. RRSI can be
calcula ed in he ollowing way:
( )
( ) ( ) ( )
22 2
12
11 1= − + − +…+ −
i i in
s
RRSI BHI BHI BHI
  
   
(3)
The highe he RRS index is he mo e specialized he s uc u e o manu ac u ing in-
dus y is in he egion. I he s uc u e o a egion is homogenous, he RRSI ob ains alue
ze o. I he RRSI ≠ 0, he indus ial s uc u e o a egion di e s om he coun y’s a e -
age. The highe he RRSI alue, he mo e a egion is di e en om he whole coun y.
4. Empi ical demons a ions: case Finland
In his sec ion, we p esen some empi ical esul s based on sma specializa ion ools
p esen ed abo e. We ocus on key esul s in he case o Finland. Fi s , we igu e ou he
HHI index o sub- egions in Finland (Fig. 3). This indica o is impo an o esilience
analysis. Small HHI alue means s onge esilience po en ial and highe index numbe s
mean weake esilience. The HHI is an indica o o indus ial di e si y.
F om he Figu e 3, we can obse e ha in 2014 he se en mos di e si ied sub-
egions in Finland we e Kuopio, Tu ku, Lah i, Helsinki, Tampe e, Hämeenlinna and
Po i. Excep in Helsinki and Tampe e, hey all ha e been g ow h-led sub- egions in
he ecen ecession. The GDP a e o g ow h in Finland was 2.07% in 2011–2014.
Co esponding igu es o he sub- egions a e: 4.94% in Tu ku, 4.19% in Hämeenlinna,
3.81% in Jy äskylä, 3.80% in Kuopio, 3.63% in Po i, and 2.27% in Lah i. The a es
o GDP g ow h in Helsinki (1.97%) and in Tampe e (1.86%) we e sligh ly less han
he a e age (S a is ics Finland 2017). Since he la e 2000s Oulu egion has been one
o he g ow h cen e s in Finland due o Nokia and he apid g ow h o he ICT-sec o .
Du ing 2011–2014, i s a e o g ow h (0.53%) de ia ed 70% om he coun y a e age.

33
Business, Managemen and Educa ion, 2017, 15(1): 28–41
The HHI-index ells ha he egion is he leas di e si ied among he g oup o la ge
sub- egions.
On he he hand, Salo sub- egion was hi by he wo s nega i e a e o g ow h,
–9.04% in 2011–2014. O he sub- egions wi h nega i e a es o g ow h we e Po oo
(–7.05%), Lo iisa (–5.46%), Ålands Skä gå d (–5.25%), E elä-Pi kanmaa (–4.64%), Sy-
dös e bo en (–0.86%), Raahe (–0.68%), Kou ola (–0.66%), and Äänekoski (–0.26%).
F om he Figu e 3 we can obse e ha excep in Kou ola and Salo, hese sub- egions
ha e ela i ely la ge alues o he HHI, i.e. hei indus ial s uc u es a e less di e si-
ied han in a e age.
0,867
0.000 0.050 0.1000.150 0.2000.250 0.300 0.3500.400 0.4500.500
Kuopio
Tu ku
Lah
Helsinki
Tampe e
Hämeelinna
Po i
Jakobs ad
Joensuu
Lounais-Pi kanmaa
Ko ka-Hamina
Keski-Ka jala
Mikkeli
Kokkola
Suupohja
Lappeen an a
Ylä-Sa o
Ma iehamns s ad
Luo eis-Pi kanmaa
Riihimäki
Jy äskylä
Pohjois-Sa akun a
Raasepo i
Yli ieska
Kajaani
Kou ola
Pielisen Ka jala
Jou sa
Rauma
Ro aniemi
Pohjois-Lappi
Ky önmaa
Pieksämäki
Salo
Vakka-Suomi
Sa onlinna
I ä-Lappi
Seinäjoki
E elä-Pi kanmaa
Ylä-Pi kanmaa
Po oo
Fo ssa
Saa ijä i-Vii asaa i
To niojokilaakso
Oulu
Äänekoski
Kehys-Kainuu
Sisä-Sa o
Haapa esi-Siikala a
Va kaus
Jä iseu u
Kausnen
Kuusiokunna
Vaasa
Tun u i-Lappi
Lo iisa
Ni ala-Haapajä i
Sydös e boen
Keu uu
Jämsä
Koillis-Sa o
Kemi-To nio
Loimaa
Oulunkaa i
Ålands landsbygd
Ima a
Koillismaa
Åboland-Tu unmaa
Raahe
Ålands skä gå d
Fig. 3. He indahl-Hi schman Index o sub- egions (LAU1) based on he analysis o 24 indus ial
sec o s in Finland, 2014.
34
J. Kai o-oja e al. Sma specializa ion s a egy and i s ope a ionaliza ion in he egional policy: case Finland
Nex , we p esen Balassa-Hoo e Index o indus ial p oduc ion (24 manu ac u ing
sec o s) in eigh u ban egions (Fig. 4). Wi h he excep ion o Oulu, hese egions ha e
mo e di e si ied indus ial s uc u e han in a e age (see Fig. 3).
In Figu e 4, i he BHI alues o indus ies exceed eigh hen compa a i e ad an age
is e ealed. 13 such manu ac u ing indus ies can be ound. As we can see, he BHI
alues a e no e enly dis ibu ed among he egions. We can in e p e o mean ha when
he alue o BHI > 8, he indus ies as agg ega e e eal compa a i e ad an age, bu no
necessa ily in a speci ic egion. To ge his in o ma ion, we need o inspec Figu e 5,
whe e cases o BHI > 1 a e exposed.
Few obse a ions can be made.
Fi s , no indus y exsi s as a sou ce o e ealed compa a i e ad an age in all eigh e-
gions. Second, h ee indus ial sec o s (“Machine y and equipmen epai , main enance
and ins alla ion”, “Manu ac u ing o u ni u e”, and “Manu ac u ing o chemicals and
chemical p oduc s”) gi e impe us o e ealed compa a i e ad an age in i e egions.
This esul can be in e p e ed in e ms o sma specializa ion. One one hand, hese i e
Fig. 4. Balassa-Hoo e Index (BHI) o indus ial p oduc ion (24 manu ac u ing sec o s) in some u -
ban sub- egions in Finland, 2014.
0246810 12 14 16 18 20
10 Manu ac u ing o ood p oduc s
11 Manu ac ing o be e ages
12 Manu ac o ing o o obacco p oduc s
13 Manu ac u ing o exles
14 Manu ac o ing o clo hes
15 Lea he and lea he p oduc s manu ac u ing
16 Manu ac u ing o wood and co k p oduc s (excep …
17 Manu ac u ing o pape and pape p oduc s
18 P inng and ep oducon o eco ded media
19 Manu ac u ing o coke and e ined pe oleum…
20 Manu ac u ing o chemicals and chemical p oduc s
21 Manu ac u ing o basic pha maceucal p oduc s and…
22 Rubbe and plasc p oduc s
23 Manu ac u ing o o he non-me allic mine al p oduc s
24 Me al p ocessing
25 Fab ica ed me al p oduc s (excl. machine y and…
26 Compu e , elec onic and opcal p oduc s
27 Manu ac u ing o elec ical equipmen
28 Manu ac u ing o o he machine y and equipmen
29 Manu ac u ing o mo o ehicles, aile s and semi-…
30 Manu ac u ing o o he anspo equipmen
31 Manu ac u ing o u ni u e
32 O he p oducon
33 Machine y and equipmen epai , main enance and…
Helsinki Tampe e Tu kuOulu Jy äskyläKuopio Po i Ro aniemi
35
Business, Managemen and Educa ion, 2017, 15(1): 28–41
egions ha e been success ul in compe i ion as compa ed o he whole coun y. On he
o he hand, hese i e egions ha e an oppo uni y o exploi in e - egional syne gies.
Tha is, Helsinki, Tu ku, Oulu, Kuopio and Po i could y o seek s a egic alliances o
coope a e in ac i i ies whe e syne gies can be ound; in manu ac u ing o chemicals
and chemical p oduc s, o example. Figu es 7–9 desc ibe co esponding in e egional
syne gy po en ials o all 70 LAU1 egions, and some manu ac u ing indus ies.
Thi d, as we combine he esul s o Figu e 3 and 5, i can be ound ha less di e si-
ied sub- egions Oulu and Ro aniemi ( ela i ely high HHI alues) ha e less e ealed
compa a i e ad an age in indus ies. Fu he , he e a e some domina ing indus ies in
hei egional economy: “Compu e , elec onic and op ical p oduc s” in Oulu (BHI =
5.2), “Manu ac u ing o mo o ehicles, aile s and semi- aile s” (BHI = 13.7), and
unspeci ied “O he p oduc ion” in Ro aniemi (BHI = 10.5). Co espondingly, in Hel-
sinki sub- egion he e a e nine manu ac u ing indus ies, which belong o e ealed
compa a i e ad an age sec o s, and he ange o he BHI alue is om 1.1 o 2.5. This
kind o in o ma ion is highly aluable o sma specializa ion discussions in Finland.
Simila sma specializa ion analysis can be applied o all Eu opean sub egions and
u ban cen es.
Fig. 5. Re ealed compa a i e ad an age (BHI > 1) in indus ial sec o s o some key Finnish u ban
sub- egions 2014 (BHI alues inside columns)
1.1
2.5
1.1
1.7
1.6
1.9
2.4
1.7
1.3
3.4
2.2
1.2
1.3
1.2
1.7
1.4
1.5
1.2
1.5
1.7
2.9
1.6
6.1
1.2
1.5
3.9
1.2
1.3
1.9
1.1
2.1
1.1
1.3
1.6
1.1
1.1
1.4
5.2
1.3
1.1
3,7
1.8
2.9
1.8
2.0
1.2
1.1
1.5
2.0
1.4
1.2
1.2
2.0
1.0
4.5
1.2
2.4
1.7
1.1
1,1
13.7
1.2
10.5
0.02.0 4.06.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0
10 Manu ac u ing o ood p oduc s
11 Manu ac ing o be e ages
13 Manu ac u ing o exles
14 Manu ac u ing o clo hes
15 Lea he and lea he p oduc s manu ac u ing
16 Manu ac u ing o wood and co k p oduc s (excep …
17 Manu ac u ing o pape and pape p oduc s
18 P inng and ep oducon o eco ded media
19 Manu ac u ing o coke and e ined pe oleum…
20 Manu ac u ing o chemicals and chemical p oduc s
21 Manu ac u ing o basic pha maceucal p oduc s and…
22 Rubbe and plasc p oduc s
23 Manu ac u ing o o he non-me allic mine al p oduc s
24 Me al p ocessing
25 Fab ica ed me al p oduc s (excl. machine y and…
26 Compu e , elec onic and opcal p oduc s
27 Manu ac u ing o elec ical equipmen
28 Manu ac u ing o o he machine y and equipmen
29 Manu ac u ing o mo o ehicles, aile s and semi-…
30 Manu ac u ing o o he anspo equipmen
31 Manu ac u ing o u ni u e
32 O he p oducon
33 Machine y and equipmen epai , main enance and…
Helsinki Tampe eTu kuJy äskyläOulu Kuopio Po i Ro aniemi
36
J. Kai o-oja e al. Sma specializa ion s a egy and i s ope a ionaliza ion in he egional policy: case Finland
In Figu es 6a and 6b, we igu e ou he key indings o he Region’s Rela i e Spe-
ciliza ion Index (RRSI) o Finnish sub- egions. The highe he RRS index he mo e
specialized he s uc u e o manu ac u ing indus y is in a egion as compa ed o he
whole coun y (see Equa ion 3).
The BHI index can be used o indus y speci ic analyses. Ins ead, he RRS index can
be used o measu e he specializa ion in ensi y o he whole egional economy. The RSS
index can also be used o measu e he agg ega e de ia ion o specializa ion om coun-
y’s a a e age. RSS index analyses can e eal use ul in o ma ion o egional sma
specializa ion s a egies. The HHI analysis e lec s he isk po en ial ha is embedded in
egion’s economic s uc u e, i i con on s he exogenous economic shocks. Ins ead, he
RRSI analysis e lec s egions’ isk o exogenous (na ional o sup ana ional) indus ial
o egional policy. The e o e, sma specializa ion policy should be egion speci ic. All
Finnish egions a e co e ed in he RRSI analysis in Figu es 6a and 6b.
Fig. 6a. RRS Index, 35 sub- egions in Finland, he index numbe e e s o he mos
specialized sub- egion, ankings 1–35, 2014.
0,05,0 10,015,020,025,030,0 35,040,0 45,050,0
Åboland-Tu unmaa
Koillis-Sa on
Po oo
Yli ieska
Kausnen
Sydös e boen
Ro aniemi
Raahe
Jämsä
Vakka-Suomi
Ky önmaa
Kajaani
Kemi-To nio
Lounais-Pi kanmaa
Mikkeli
Tun u i-Lappi
Ima a
Ålands landsbygd
Ålands skä gå d
Koillismaa
To niolaakso
Oulunkaa i
Ylä-Sa o
I ä-Lappi
Lo iisa
Pohjois-Lappi
Suupohja
Pohjois-Sa akun a
Ma iehamn
Luo eis-Pi kanmaa
Kehys-Kainuu
Kuusiokunna
Kokkola
Tu ku
Ylä-Pi kanmaa
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
...225,7