Sha ku, Gen iana; Kumi, E is
A icle
Does insu ance ma ke impac he economic g ow h?
E idence om Albania
The Eu opean Jou nal o Compa a i e Economics (EJCE)
P o ided in Coope a ion wi h:
Uni e si y Ca lo Ca aneo (LIUC), Cas ellanza
Sugges ed Ci a ion: Sha ku, Gen iana; Kumi, E is (2021) : Does insu ance ma ke impac he
economic g ow h? E idence om Albania, The Eu opean Jou nal o Compa a i e Economics (EJCE),
ISSN 1824-2979, Uni e si y Ca lo Ca aneo (LIUC), Cas ellanza, Vol. 18, Iss. 2, pp. 267-289,
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The Eu opean Jou nal o Compa a i e Economics
Vol. 18, no. 2, pp. 267-289
ISSN 1824-2979
h p://dx.doi.o g/10.25428/1824-2979/001
Fi s published online: 27/08/2021
Does insu ance ma ke impac he economic g ow h?
E idence om Albania
Gen iana Sha ku*, E is Kumi**
Abs ac
Insu ance plays a signi ican ole in he economy de elopmen all o e he wo ld, being an impo an
sou ce o capi al accumula ion and in es men . This pape s udies he long un dynamic ela ions be ween
economic g ow h and he insu ance ma ke in Albania. Using seconda y qua e ly da a om 2005 o 2018,
we ha e aken in o conside a ion h ee main indica o s o he insu ance ma ke : (i) li e and non-li e
insu ance olume; (ii) li e and non-li e insu ance densi y and (iii) li e and non-li e insu ance pene a ion
index. The da a analysis is ca ied h ough Johansen’s ec o e o -co ec ion model. The indings o he
s udy e ealed no long un ela ion be ween economic g ow h and insu ance ma ke , when he employed
indica o s a e he p emium olume and he pene a ion index. On he o he hand, when he insu ance
ma ke is measu ed by he densi y index, we ound a long un nega i e ela ion be ween g ow h and li e
insu ance ac i i y and a long un posi i e ela ionship be ween g ow h and non-li e insu ance ac i i y.
JEL classi ica ion: G22, F43
Keywo ds: Insu ance ma ke , Economic g ow h, Albania
1. In oduc ion
Albania is a coun y ha has expe ienced a long ansi ion, a e he beginning o
he e o ms in 1990. Insu ance ma ke has no been a p io i y o he economic e o ms
in he i s decade. Acco ding o he s a is ics o he Insu ance Commission (Albanian
Financial Supe iso y Au ho i y a he p esen ), he p emium pe capi a in 1999 was
only USD 4.2, while in 2018 i has been inc eased mo e han en old. The insu ance
ma ke in Albania is signi ican ly de eloped in he second decade o ansi ion pe iod.
The numbe o insu ance companies has been inc eased, he o eign capi al en e ed, he
legisla ion was signi ican ly imp o ed e c. The insu ance ma ke in Albania has always
been domina ed by non-li e insu ance p oduc s. In 2019, he li e insu ance ac i i y
sha ed abou 7% o o al insu ance ac i i y. The s uc u e o he insu ance ma ke in
Albania has been changed om he s a e monopoly (un il 1999) o oligopoly (up o
2002) and hen o monopolis ic compe i ion (du ing he las decade) acco ding o
* Uni e si y o Ti ana, Facul y o Economics, Albania, gen ianasha ku@ eu .edu.al
** Me opoli an Uni e si y, Ti ana, Albania, ekumi@um .edu.al
Acknowledgemen : We would like o exp ess ou g a i ude o he EJCE Edi o s, M . Ma eo Migheli and
M . Gio anni Ramello, o hei a ailabili y since he submission o he manusc ip . Also, we would like
o hank he anonymous e iewe s o sha ing hei opinions and helping us imp o ing he pape .
EJCE, ol. 18, no. 2 (2021)
A ailable online a h ps://ejce.liuc.i
268
Sha ku & Shehu (2016). Howe e , he compe i ion deg ee a ies wi hin he classes and
ac i i ies o he insu ance ma ke . Among li e and non-li e insu ance, he li e insu ance
ac i i y is mo e concen a ed han he non-li e insu ance ma ke , due o he small
numbe o insu ance companies ope a ing in he li e insu ance ma ke .
Many academics and p ac i ione s in Albania ha e explo ed he ac o s ha
in luence he economic de elopmen in Albania, such as o eign di ec in es men ,
emi ances, banking sec o , mone a y policy, iscal policy e c. Bu e y ew o hem
ha e included he insu ance ac i i y as a po en ial a iable o economic de elopmen .
The la e de elopmen o he insu ance sec o in Albania, may be one o he easons ha
i is no conside ed in hei s udies. Howe e , he in e na ional li e a u e sugges s ha a
ela ionship be ween economic de elopmen and insu ance ac i i y may exis e en in
de eloping coun ies like Albania.
The aim o his a icle is o explo e he ela ionship be ween insu ance ac i i y and
economic g ow h, conside ing bo h he segmen s: li e and non-li e insu ance and
economic de elopmen . The li e a u e e iew ega ding his ela ionship is summa ized
in he i s sec ion o he a icle. The second sec ion p esen s he me hodology and he
da a base used in he s udy and he hi d sec ion discusses he indings. The inal sec ion
con ains some conclusions ega ding he insu ance ma ke in Albania.
2. Li e a u e Re iew
The ela ionship be ween economic g ow h and insu ance indus y is subjec o
many au ho s, s udying he da a in di e en coun ies and in di e en economic
de elopmen pe iods. In his s udy, we classi y he au ho s and hei indings acco ding
he o he economic de elopmen o he coun ies aken in conside a ion, s a ing wi h
Wa d & Zub uegg (2000), who in oduced a s udy ha ep esen s a g ea con ibu ion
o examine he dynamic ela ionship be ween economic g ow h and inc ease in he
insu ance indus y o nine OECD coun ies. They used a unique se o annual da a o
eal GDP and o al eal p emiums, om 1961 o 1996, o each coun y. The G ange
causali y es sugges s ha in some OECD coun ies, he insu ance indus y causes
economic g ow h, bu in o he coun ies he e e se e ec . Only o he UK and USA
he au ho s e ealed an insigni ican ela ionship. Kugle & O ogi (2005) s udied he
UK da a o he pe iod 1966-2003. The models hey used o in es iga e he long- un
Gen iana Sha ku, E is Kumi, Does insu ance ma ke impac he economic g ow h? E idence om Albania
A ailable online a h ps://ejce.liuc.i
269
ela ionship be ween insu ance ma ke and economic g ow h, we e based on
disagg ega ed da a. They used Johansen’s coin eg a ion es and G ange causali y, and
hei empi ical analysis e ealed a posi i e long- un ela ionship be ween GDP and he
size o he insu ance sec o , which is cha ac e ized as bidi ec ional. I is impo an o
men ion Kugle & O ogi (2005) ealized ha Wa d & Zub uegg (2000) concluded
insigni ican esul s, because hey used agg ega e da a (li e and non-li e p emiums).
Di e en ly om p e ious au ho s, Adams e al. (2009), examined he dynamic
ela ion be ween comme cial bank ac i i y, insu ance and economic g ow h only in one
coun y, in Sweden o he pe iod 1830 o 1998, using ime-se ies da a and pe o ming
es s o G ange causali y. The s udy concluded ha insu ance has G ange -caused
economic g ow h and bank lending. Fu he mo e, he insu ance sec o has a posi i e
e ec on economic g ow h only in he high economic de elopmen pe iods.
La e on, Ege & Bahadi (2011) explo ed he ole o insu ance in changing
economic g ow h using da a o wen y-nine coun ies om 1999 o 2008 (Aus alia,
Aus ia, Belgium, Canada, Czech Republic, Denma k, Finland, F ance, Ge many,
G eece, Hunga y, Iceland, I eland, I alia, Japan, Tu key, Sou h Ko ea, Luxembu g,
Mexico, Holland, No way, Poland, Po ugal, Slo akia, Spain, Sweden, Swi ze land,
England and USA). The panel da a analysis e ealed a posi i e ela ionship be ween
insu ance and economic g ow h.
Chang e al. (2014) applied boo s apping G ange causali y model o e a pe iod
o 1979–2006, o 10 OECD o examine he ela ionship be ween insu ance and
economic g ow h. Thei indings we e no uni o m o all he coun ies included in he
s udy. While P adhan a al. (2017) explo ed he causal ela ionship be ween insu ance
ma ke pene a ion and economic g ow h pe capi a in 19 Eu ozone coun ies o he
pe iod 1980–2014. Employing G ange causali y, he esul s we e mos ly non-uni o m
ac oss he Eu ozone coun ies du ing his selec ed pe iod.
Despi e he low le el o de elopmen , he e a e a lo o au ho s ha ha e s udied
he ela ionship be ween economic g ow h and he insu ance ma ke in de eloping
coun ies. Ve ma & Bala (2013) based on he O dina y Leas Squa e eg ession model,
examined he ela ionship be ween he li e insu ance and economic g ow h in India o
he ime pe iod 1990 o 2011. The indings o he s udy concluded ha li e insu ance
EJCE, ol. 18, no. 2 (2021)
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signi ican ly in luences he economic g ow h o India. These indings a e in line wi h
Ghosh (2013) and Din e al. (2017) o India and Chau e al. (2013) o Malasyia.
Olayungbo & Akinlo (2016) and Alhassan, A.L. (2016) s udied he ela ionship
be ween insu ance and economic g ow h in A ican coun ies ( i e ou o eigh
coun ies we e he same in bo h s udies). Olayungbo & Akinlo (2016) ocused hei
esea ch in eigh A ican coun ies o he pe iod o 1970–2013. The s udy showed
posi i e ela ionships o Egyp , while sho - un nega i e and long- un posi i e e ec s
we e ound o Kenya, Mau i ius, and Sou h A ica. On he con a y, nega i e e ec s
we e ound o Alge ia, Nige ia, Tunisia, and Zimbabwe. On he o he hand, Alhassan
(2016), e ealed a long- un ela ionship be ween insu ance ma ke ac i i ies and
economic g ow h o Kenya, Mau i ius, Mo occo, Nige ia and Sou h A ica. Omoke
(2011) s udied he impac o he insu ance ma ke in Nige ia on economic g ow h o a
pe iod be ween 1970 and 2008. Con a y o he indings o Olayungbo & Akinlo (2016)
and Alhassan (2016), he insu ance sec o did no e eal any posi i e and signi ican
impac on economic g ow h in Nige ia wi hin he pe iod o s udy. Akinlo & Apanisile
(2014), s udied he ela ionship be ween insu ance and economic g ow h in sub-Saha an
A ica o e he pe iod 1986-2011. The au ho s ound ha insu ance has a posi i e and
signi ican impac on economic g ow h in sub-Saha an A ica.
The e ec o he insu ance sec o in he economic de elopmen o Tu key has
been examined by Yildi im (2015). He employed he G ange Causali y Tes and VAR
Model using imes e da a be ween 2006-2014 yea s. He ound a posi i e ela ionship
be ween he economic de elopmen and insu ance sec o .
C is ea e al. (2014) aimed o es ablish he co ela ion be ween insu ance and
economic g ow h in Romania, o he pe iod 1997-2012, based on s a is ical me hods
conce ning he analysis be ween he GDP and insu ance indica o , aking in o
conside a ion insu ance pene a ion and insu ance densi y. As a conclusion, hey ound
ou he li e insu ance is a ec ing mo e signi ican ly he GDP pe capi a, compa ed wi h
he non-li e insu ance. The impac o insu ance ma ke in economic g ow h in he ex-
Yugosla ia egion is es ed by Njegomi & S ojić (2010). They used he coun y-specific
ixed e ec s models o panel da a o he pe iod 2004-2008. The analysis e ealed a
posi i e e ec o insu ance on economic g ow h. Kjose ski (2011) s udied he
ela ionship o insu ance and economic g ow h o Macedonia, o he pe iod 1995–

Gen iana Sha ku, E is Kumi, Does insu ance ma ke impac he economic g ow h? E idence om Albania
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2010, using he mul iple eg ession models. Wi h he scope o sol e he model i was
used he echnique o leas squa es, ollowed by analysis o a iabili y in o de o
iden i y he e ec s o each a iable. He used h ee di e en insu ance a iables - li e
insu ance, non-li e insu ance and o al insu ance pene a ion, and he concluded ha he
o al insu ance indus y and non-li e insu ance ha e a posi i e and signi ican e ec on
economic g ow h o Macedonia. Li e insu ance a ec s he economic g ow h o
Macedonia signi ican ly, bu in a nega i e way.
Few esea che s ha e s udied he ela ion be ween he insu ance ma ke and
economic de elopmen in Albania. Madani and Bazini (2017) ha e s udied how he
Albanian insu ance ma ke is in luenced by he economic g ow h and o he ac o s such
as in la ion, educa ion o popula ion, popula ion g ow h, go e nmen policies, p i a e
in es men , e c. Using insu ance pene a ion indica o s om 1999 o 2013, hey ound
ha economic g ow h nega i ely a ec s he endency o Albanian ci izens on he
eques o p oduc s o he li e insu ance indus y. Kalaja a al. (2017) ha e examined he
impac o he insu ance ma ke on economic de elopmen in Albania. Using insu ance
densi y indica o s, o he pe iod 2006-2015, he au ho s ha e ound e idence o a
posi i e e ec o he de elopmen o he li e and non-li e insu ance ma ke s on
economic g ow h and ha economic g ow h is nega i ely a ec ed by sa ings and he
in la ion a e. On he o he hand, Zyka & My a aj (2014) in hei s udy, ound an
insigni ican ole o he insu ance ma ke in Albanian economy.
The composi ion o he insu ance ma ke in luences he impac ha each
insu ance segmen may ha e in economic de elopmen . The insu ance ac i i y ha is
he la ges pa o he ma ke may signi ican ly d i e he esul . A ena (2008), e i ying i
he e is a causal ela ionship be ween insu ance ma ke ac i i y and economic g ow h
o 55 coun ies, du ing he pe iod 1976 – 2004, concluded ha bo h li e and non-li e
insu ance ha e posi i e and signi ican causal e ec s on economic g ow h. Fo li e
insu ance, high-income coun ies d i e he esul s, and o non-li e insu ance, bo h
high-income and de eloping coun ies d i e he esul . Haiss & Sümegi (2008), in o de
o s udy he ela ionship be ween insu ance and economic g ow h, applied a panel da a
analysis o e he pe iod 1992-2005, o 29 coun ies o OECD. They ound ou ha Fo
he New EU Membe S a es om Cen al and Eas e n Eu ope, he economic g ow h is
impac ed mo e om liabili y insu ance, compa ed wi h he o he coun ies ha li e
EJCE, ol. 18, no. 2 (2021)
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insu ance played a mo e impo an ole. I is explained by he ac ha he mo o hi d
pa y liabili y cons i u es he la ges pa o he o al insu ance ma ke in Cen al and
Eas e n Eu ope coun ies.
The ela ion o he insu ance ma ke , especially he li e insu ance one, wi h
economic de elopmen depends on he de elopmen and he cha ac e is ics o he
inancial sys em o a speci ic coun y. Oued aogo e al. (2016), es ed he ela ion
be ween he de elopmen o he li e insu ance sec o and economic g ow h, o a
sample o 86 de eloping coun ies o e he pe iod 1996-2011. He concluded ha he
ma ginal posi i e impac o he de elopmen o li e insu ance dec eases wi h he le els
o deposi in e es a e, bank c edi and s ock ma ke alue aded, while he e ec is
g ea e in coun ies wi h high-quali y ins i u ions. Webb a al. (2002) used a c oss sec ion
analysis o s udy he posi i e e ec o he bank and insu ance sec o on economic
g ow h, in 55 de eloping and de eloped coun ies. He disco e ed ha he e ec o
bank and insu ance ma ke s oge he is s onge han when measu ed independen ly
om each o he . Din a al. (2017) ha e es ed he ela ionship be ween insu ance and
economic g ow h o six (de eloped, eme ging and de eloping) coun ies o e he
pe iod o 1980 o 2015. The au ho s concluded a significan and posi i e ela ionship
be ween non-li e insu ance and economic g ow h in he sho - un o he all he
coun ies aken in conside a ion, while he ela ionship be ween li e insu ance and
economic g ow h is no uni o m among he coun ies conside ed in he s udy.
I is di icul o come o a conclusion ega ding he indings o he s udies which
explo e he ela ionship be ween insu ance ma ke and economic g ow h. Se e al
au ho s ha e applied di e en s a is ical es s and models as well as di e en indica o s
o measu ing economic g ow h and he insu ance ma ke . This may be one o he
easons ha he esea ch esul s a e non-uni o m e en among coun ies a he same
le el o de elopmen .
3. Me hodology and da a selec ion
The ocus o his s udy is o examine he long un dynamic ela ions be ween
economic g ow h and he insu ance ma ke in Albania, using Johansen’s ec o e o -
co ec ion model. Al hough he Engle & G ange (1987) p ocedu e can be
implemen ed, i is less e icien when using h ee o mo e a iables. In es ing h ee o
Gen iana Sha ku, E is Kumi, Does insu ance ma ke impac he economic g ow h? E idence om Albania
A ailable online a h ps://ejce.liuc.i
273
mo e a iables, mo e han one coin eg a ion ec o may be expec ed, and as Ende s
(2014) explains, he me hod has no sys ema ic p ocedu e o he es ima ion o mul iple
coin eg a ing ec o s.
We i s pe o m he augmen ed Dickey – Fulle (ADF) o es o s a iona i y and
uni oo s o a iables in bo h le el and i s di e ence ollowed by Phillips-Pe on es
o check o majo al e a ions. In o de o es o coin eg a ion and es ima e he
VECM, all a iables mus be in eg a ed o o de one I(1), hence being s a iona y a i s
di e ence. A e es ing o s a iona i y, we pe o m a es o de e mine he lag leng h
s uc u e, elying on mul iple c i e ia mainly including Akaike In o ma ion C i e ion
(AIC), Schwa z In o ma ion C i e ion (SC) and Hannan-Quinn In o ma ion C i e ion
(HQ).
The e o e, we pe o m he Johansen (1988) coin eg a ion es o de e mine he
exis ence o one o mo e coin eg a ion ec o s, since all he hypo heses in conside a ion
consis o h ee a iables. The coin eg a ion es will he e o e de e mine he ank o
λ=αβ’. Ha ing de e mined he o de o coin eg a ion, we es ima e a VECM and
examine he coin eg a ing ec o and he speed o adjus men s o he pa ame e s.
Assuming he e a e mul iple coin eg a ing ec o s, we will selec one coin eg a ing
ec o , o he eigen ec o based on he la ges eigen alue. I is impo an o no e ha i
he e a e mo e han one coin eg a ion ela ionships in a h ee- a iable sys em, he e
exis one coin eg a ing ec o o each subse (Ende s, 2014). A las , we in e p e he
ele an coin eg a ing ec o and he speed o adjus men coe icien .
The a iables included in his s udy a e G ow h, LLI, LNI, LID, NID, LIPI, and
NIPI. The G ow h a iable e ie ed om he INSTAT (Na ional Ins i u e o S a is ics
o Albania) na ional accoun s ime se ies, while li e and non-li e insu ance olumes we e
accessed a AFSA (Albanian Financial Supe iso y Au ho i y). As he scope o he
a icle is o s udy he long un ela ionship be ween he insu ance ma ke and economic
g ow h, we use ake in o conside a ion h ee main indica o o he insu ance ma ke :
(i) li e and non-li e insu ance olume;
(ii) li e and non-li e insu ance densi y; and
(iii) li e and non-li e insu ance pene a ion index.
The li e and non-li e insu ance olumes a e ans o med o gene a e he a iables
o in e es . Table 1 p o ides he lis o a iables and hei de ini ions.
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Table 1:De ini ions o a iables
Va iable Name
De ini ion o a iables
G ow h
Economic g ow h (in pe cen age)
LLI
Na u al loga i hm o olume o li e insu ance p emium
LNI
Na u al loga i hm o olume non-li e insu ance p emium
LIDR
Li e insu ance densi y a e – li e insu ance p emium olume pe
capi a (in Eu o pe capi a)
NIDR
Non-li e insu ance densi y a e – non-li e insu ance p emium olume
pe capi a (in Eu o pe capi a)
LIPR
Li e insu ance pene a ion a e – li e insu ance p emium olume o
GDP a io (in pe cen age)
NIPR
Non-li e insu ance pene a ion a e – non-li e insu ance p emium
olume o GDP a io (in pe cen age)
The olumes a e a i s con e ed in o na u al loga i hms, o gene a e LLI and
LNI. The li e and non-li e insu ance densi y is hen calcula ed as he olume pe capi a
(LID and NID) whe eas he li e and non-li e insu ance pene a ion a e is calcula ed as
he a io o he p emium olume o he g oss domes ic p oduc (also e ie ed om
INSTAT) a a gi en ime (LIPR and NIPR). Table 2 p o ides he summa y s a is ics o
he a iables in hei inal o m.
Table 2: Desc ip i e s a is ics o a iables
Va iable Name
Mean
S d De
Min
Max
G ow h
5.944
3.911
-1.811
13.521
LLI
14.097
0.517
12.370
14.782
LNI
16.513
0.418
15.659
17.288
LIDR
5.552
2.423
0.015
11.195
NIDR
0.506
0.204
0.901
0.078
LIPR
0.061
0.018
0.094
0.374
NIPR
0.674
0.189
1.117
2.094
We ocus on he pe iod o ime om he i s qua e o 2005 up un il he second
qua e o 2018. Conside ing he na u e o he s udy and he na u e o he insu ance
ma ke in Albania, we included qua e ly da a, as annual da a would mean ha ing ew
obse a ions a ailable o an e icien es ima ion. As desc ibed in he sec ion II, he
ma ke insu ance in Albania has been ob iously de eloped only a e 2005, due o he
imp o emen o insu ance legal amewo k, ma ke libe aliza ion and eo ganiza ion o
he insu ance ma ke s uc u es.
Gen iana Sha ku, E is Kumi, Does insu ance ma ke impac he economic g ow h? E idence om Albania
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281
somehow la ge, hus we ake in conside a ion he ci cums ance in which he use o
many lags is accompanied wi h he p oblems o losing many obse a ions.
Table 9: P e-es ima ion lag o de selec ion s a is ics
Lag
LR
FPE
AIC
SC
HQ
4
32.275
0.042
5.308
6.844*
5.886*
7
17.459*
0.041*
5.083*
7.681
6.060
Figu e 3 displays he end o LIDR and NIDR se ies. LIDR shows a clea and
con inuous upwa d end ac oss all he sequence, while NIDR show a mino upwa d
end a he s a , which con inues o g ow app oxima ely a e he middle o he se ies
up o he end. Consequen ly, his sugges s he inclusion o he de e minis ic end in
u he es ima ions.
Figu e 3: T end o a iables
T end o LIDR
T end o NIDR
Table 10 ep esen s he esul s o he Johansen es s o G ow h, LIDR and
NIDR. Acco ding o he ace s a is ic, a 5% le el o signi icance (almos a 1% le el o
signi icance), no mo e han wo coin eg a ing ec o s exis . Acco ding o he Maximum
– Eigen S a is ic, a 5% le el o signi icance no mo e han one coin eg a ing ec o s
exis be ween he selec ed a iables. In any case, as p e iously s a ed, when he e is
mo e han one coin eg a ing ec o , he i s eigen ec o which is based on he la ges
eigen alue is ega ded as he mos use ul o u he analysis.

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Table 10: Johansen coin eg a ion es
Hypo hesized
No. o CE(s)
Eigen alue
T ace
S a is ic
p- alue
Max-Eigen
S a is ic
p- alue
None
0.555
68.136
0.000*
37.244
0.001*
A mos 1
0.334
30.891
0.011*
18.706
0.062
A mos 2
0.233
12.185
0.057
12.185
0.057
A e concluding he p esence o coin eg a ion be ween a iables, we ollow he
analysis by es ima ing he VECM including one coin eg a ion equa ion. Annex 1
ep esen s he es ima es o he VECM. Rega ding he i s equa ion o he sys em and
conside ing he e o co ec ion e m ECT -1=1.000G ow h -1 +25.893 LIDR -1 - 1.232
NIDR -1 + 0.022 T end - 13.065, he esul s show ha he p e ious yea de ia ion o
economic g ow h om he long un equilib ium is co ec ed in he cu en pe iod a a
speed o 62.3%. The magni ude o he speed o adjus men mechanism o he long- un
equilib ium is ela i ely high, which implies ha he p ocess is highly expec ed o
con e ge in he long- un. The speed o adjus men is 14.6% o he second equa ion,
and only 0.9% o he hi d equa ion. Fu he mo e, he speed o adjus men coe icien
is signi ican a 5% le el only o he i s and he hi d equa ion.
Focusing on he i s equa ion, he coin eg a ing ec o is gi en by β’1= (1.000,
25.893, -1.232, 0.022, -13.065), which gi es he ollowing coin eg a ing ela ionship:
G ow h = -25.893 LIDR + 1.232 NIDR -0.022 T end +13.065
The coin eg a ion equa ion sugges ha he e exis in he long- un a nega i e
ela ion be ween g ow h and li e insu ance densi y, while on con a y a posi i e ela ion
wi h non-li e insu ance. As he non-li e insu ance ac i i y domina es he insu ance
ma ke in Albania (i consis ed abou 93 pe cen o agg ega e insu ance ma ke in 2017),
i is expec ed a posi i e ela ionship be ween economic g ow h and non-li e insu ance.
Rega ding he long- un nega i e ela ion be ween g ow h and non-li e insu ance, i is in
line wi h he indings o Kjosje ski (2011) o Macedonia. This esul may be explained
by he ac ha he inancial sys em in Albania is a bank-based sys em, and he sa ing
cul u e p e ails o e he insu ance cul u e o he Albanians. On he o he hand, when
conside ing he sho - un coe icien s, LID has a posi i e e ec on g ow h, while NID
has a nega i e e ec on g ow h. Howe e , mos o he LID sho - un coe icien s,
Gen iana Sha ku, E is Kumi, Does insu ance ma ke impac he economic g ow h? E idence om Albania
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283
excep he i s lag and su p isingly he las lag, a e no signi ican , and all o he NID
sho - un coe icien s a e no signi ican .
To check he s abili y o he model we un a pos es ima ion es , pa icula ly
con olling o no mali y, au oco ela ion and he e oscedas ici y. The LM es o se ial
co ela ion could no ejec he null hypo hesis o no se ial co ela ion a 7 lags and a
5% le el o signi icance (Annex 2), he e o e we conclude he model su e s no
au oco ela ion p oblem. We u he pe o m he Ja que-Be a es o no mali y (Annex
3). A 5% le el o signi icance, we canno ejec he null hypo hesis, hence we conclude
ha he esiduals a e no mally dis ibu ed. A las , we pe o m he he e oscedas ici y es
(Annex 4), which shows ha a 5% le el o signi icance we ail o ejec he null
hypo hesis o cons an a iance, so he model is homoscedas ic. Conside ing he pos
es ima ion es s, we conclude ha he model’s indings a e obus .
5. Conclusions
Insu ance ma ke ac i i y may con ibu e o economic g ow h, playing bo h oles,
as a inancial in e media y and a p o ide o isk ans e and indemni ica ion, allowing
di e en isks o be managed mo e e icien ly.
In his s udy, we ha e been ocused on Albanian insu ance ma ke o explo e he
long ela ionship be ween g ow h and he insu ance ma ke . Insu ance is measu ed
using h ee di e en indexes such as g oss w i en p emiums, pene a ion and densi y
a es.
The empi ical indings o ou s udy e ealed ha he e is no long un ela ion
be ween economic g ow h and insu ance ma ke when he second one is measu ed by
he g oss w i en p emium olume and he pene a ion a e. On he o he hand, when
he insu ance ma ke is measu ed by he densi y a e, he model con i med ha he e
exis s a long- un nega i e ela ion be ween economic g ow h and li e insu ance densi y,
and a posi i e ela ion be ween economic g ow h and non-li e insu ance.
The indings a e in line wi h a pa o he s udies ci ed in li e a u e e iew, which
e ealed ha he li e insu ance ma ke has a posi i e impac in high income coun ies,
bu no in de eloping ones and ha he economic de elopmen is mo e a ec ed by he
insu ance ac i i y which domina es he ma ke . As he insu ance ma ke is p e ailed by
he non-li e insu ance ma ke , i is expec ed ha he las one d i es he posi i e esul .
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Due o he low le el o insu ance cul u e and he unde de elopmen o li e-insu ance
companies in espec o o he inancial in e media ies such as banks and in es men
unds, he Albanian ci izens ha e no in e es in di ec ing hei sa ings and in es men s
owa ds he insu ance companies. They s ill di ec hei sa ings owa ds adi ional
al e na i es, like bank deposi s.
The abo e indings may be o a high impo ance o he go e nmen and he
policymake s, because he Albanian inancial legisla ion should aim o s imula e he
insu ance ma ke , especially he li e insu ance ac i i y, wi h he same a en ion as he
banking sec o .
Fu he mo e, he indings o his s udy would help he expe s o add ess some
impo an aspec s ha could be conside ed in ope a ing in he ield o insu ance ma ke ,
and he go e nmen o adop some public measu es o consolida e and s eng hen he
insu ance ma ke in Albania. The indings o his s udy may be used in he u u e o
analyse he ela ionship be ween economic de elopmen and he insu ance ma ke in
he con ex o a egional a ea.
Gen iana Sha ku, E is Kumi, Does insu ance ma ke impac he economic g ow h? E idence om Albania
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285
Appendix
Annex 1: VECM es ima es
Va iables
(1)
∆G ow h
(2)
∆LID
(3)
∆NID
ECT -1
-0.623**
(0.172)
-0.009
(0.007)
-0.146**
(0.052)
∆G ow h -1
0.357
(0.195)
0.012
(0.008)
0.190*
(0.059)
∆G ow h -2
-0.022
(0.200)
0.016
(0.008)
0.139*
(0.060)
∆G ow h -3
0.430*
(0.185)
0.010
(0.008)
0.235**
(0.056)
∆G ow h -4
-0.124
(0.195)
0.016
(0.008)
0.049
(0.059)
∆G ow h -5
-0.001
(0.168)
0.007
(0.007)
0.153**
(0.051)
∆G ow h -6
0.310
(0.172)
0.007
(0.007)
0.041
(0.052)
∆LID -1
18.665**
(6.114)
-0.359
(0.254)
-1.776
(1.843)
∆LID -2
0.629
(6.653)
-0.283
(0.276)
-3.208
(2.006)
∆LID -3
12.889
(6.706)
-0.576
(0.278)
0.191
(2.022)
∆LID -4
10.750
(6.558)
0.124
(0.272)
-0.612
(1.977)
∆LID -5
7.487
(6.474)
-0.188
(0.269)
1.771
(1.952)
∆LID -6
15.327**
(5.391)
-0.079
(0.224)
1.144
(1.625)
∆NID -1
-1.008
(0.651)
-0.028
(0.027)
-0.772**
(0.196)
∆NID -2
-0.179
(0.690)
-0.042
(0.029)
-0.707**
(0.208)
∆NID -3
-0.940
(0.779)
-0.050
(0.032)
-0.842**
(0.235)
∆NID -4
-0.984
(0.704)
-0.040
(0.029)
-0.148
(0.212)
∆NID -5
-0.881
(0.591)
-0.031
(0.025)
-0.360
(0.178)
∆NID -6
-0.928
(0.540)
-0.022
(0.022)
-0.471**
(0.163)
C
-0.020
(0.669)
0.069**
(0.028)
0.774**
(0.202)
Obse a ions
47
47
47
R-squa ed
0.747
0.742
0.788
** p<0.01, * p<0.05,
S anda d e o s a e shown in pa en hesis
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Annex 2: VECLM Tes
VEC Residual Se ial Co ela ion LM Tes s
Null Hypo hesis: no se ial co ela ion a lag o de h
Sample: 2005Q12018Q2
Included obse a ions: 47
Lags
LM-S a
P ob
1
10.46747
0.3140
2
6.285575
0.7110
3
8.478594
0.4867
4
10.11757
0.3411
5
9.923588
0.3567
6
6.705728
0.6677
7
7.158196
0.6207
P obs om chi-squa e wi h 9 d .
Annex 3: No mali y Tes
VEC Residual No mali y Tes s
O hogonaliza ion: Cholesky (Lu kepohl)
Null Hypo hesis: esiduals a e mul i a ia e no mal
Sample: 2005Q12018Q2
Included obse a ions: 47
Componen
Skewness
Chi-sq
d
P ob.
1
-0.695319
3.787166
1
0.0516
2
0.319298
0.798616
1
0.3715
3
0.238627
0.446051
1
0.5042
Join
5.031832
3
0.1695
Componen
Ku osis
Chi-sq
d
P ob.
1
3.769842
1.160620
1
0.2813
2
3.342544
0.229784
1
0.6317
3
3.349819
0.239647
1
0.6245
Join
1.630051
3
0.6526
Componen
Ja que-Be a
d
P ob.
1
4.947786
2
0.0843
2
1.028400
2
0.5980
3
0.685698
2
0.7097
Join
6.661884
6
0.3533

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Annex 4: He e oscedas ici y es
VEC Residual He e oskedas ici y Tes s: No C oss Te ms (only le els and squa es)
Da e: 01/06/19 Time: 17:00
Sample: 2005Q12018Q2
Included obse a ions: 47
Join es :
Chi-sq
d
P ob.
238.9187
228
0.2965
Indi idual componen s:
Dependen
R-squa ed
F(38,8)
P ob.
Chi-sq(38)
P ob.
es1* es1
0.789794
0.790998
0.7093
37.12032
0.5100
es2* es2
0.820049
0.959381
0.5774
38.54229
0.4450
es3* es3
0.812650
0.913178
0.6122
38.19453
0.4606
es2* es1
0.810599
0.901011
0.6215
38.09815
0.4650
es3* es1
0.826011
0.999475
0.5484
38.82254
0.4325
es3* es2
0.892311
1.744412
0.2069
41.93859
0.3040
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