65
4, XXI, 2018
Economics
DOI: 10.15240/ ul/001/2018-4-005
In oduc ion
The Medi e anean is one o he main
des ina ions o in e na ional ou ism in Spain.
Acco ding o he Spanish S a is ics Ins i u e (INE,
2016), mo e han hal o in e na ional ou is s
s aying a ho els chose he Medi e anean
coas al p o inces as a des ina ion in 2015.
Spain has abou 3,500 km o Medi e anean
coas line (INE, 2016). As shown in Fig. 1,
hese kilome e s a e dis ibu ed be ween he
peninsula coas (2,058 km) and he a chipelago
o he Balea ic Islands (1,428 Km).
Tou ism is an impo an economic sec o
on he Spanish Medi e anean coas s and i
has become one o he mos impo an sou ces
o employmen . Fo example, in Balea ic
Islands he ou ism sec o con ibu ed 44.8%
o he g oss domes ic p oduc (GDP) and
c ea ed 150,346 jobs (32.0% o o al), in 2014.
These da a a e signi i can ly highe han he
na ional a e age (11.1% o he GDP and 13%
o he employmen ). Acco ding o he Ho el
Occupancy Su ey (INE, 2016), in 2015 he
p o inces o he Medi e anean coas s accoun
o 47.15% o he o al s a employed in ho els
in Spain, and 47.36% o ho el beds o e ed.
Mo eo e , he numbe o isi o s is inc easing
e e y yea . In e na ional ou is s s aying a
ho els ha e g own by 26.3% om 2010 o 2015,
wi h a mean annual g ow h a e o nea ly 5%
du ing his pe iod (INE, 2016). In his con ex
o a consolida ed des ina ion wi h a g owing
ou ism demand, we conside i e y in e es ing
o gain a be e knowledge o he de e minan s
o i s demand.
A NONLINEAR DYNAMIC MODEL FOR
INTERNATIONAL TOURISM DEMAND ON
THE SPANISH MEDITERRANEAN COASTS
Isabel Albaladejo, Ma ibel González-Ma ínez
Fig. 1: The Spanish Medi e anean coas s
Sou ce: own
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66 2018, XXI, 4
Ekonomie
Since he 1990s, ou ism demand modelling
s udies ha e shi ed om s a ic eg ession
models o mo e sophis ica ed dynamic
speci i ca ions. Dynamic demand models can
accoun o habi pe sis ence and wo d-o -mou h
ecommenda ions om p e ious isi o s. The
mos common way o b ing a dynamic s uc u e
in o demand models is o include he lagged
demand in a linea ashion as an explana o y
a iable (Mo ley, 2009; Ga ín-Muñoz, 2006;
2007; 2009, among o he s). This p oposal
implies ha he e ec o p e ious ou is s on he
cu en ou ism demand is cons an (Albaladejo,
González-Ma ínez, & Ma ínez-Ga cía, 2016).
Howe e , se e al s udies (Mo ley, 1998; 2009;
Albaladejo, González-Ma ínez, & Ma ínez-
Ga cía, 2016) a i m ha a linea model is no
enough o accoun o he dynamics o ou ism
demand.
We a gue ha he cons an e ec assump ion
is no app op ia e o analyzing ou ism
demand. The in l uence o pas ou is s will be
la ge o smalle depending on he epu a ion
o a ac i eness o he ou ism des ina ion.
The a ac i eness o a des ina ion depends no
jus on i s na u al ea u es (wea he , beaches,
na u al a eas...) bu also on cha ac e is ics like
quali y o accommoda ions, quan i y o ou ism
se ices, di e si y o supply, and conges ion
o o e c owding, among o he s. The quali y
o ou ism se ices is one o he main ac o s
a ec ing he success o ou ism des ina ions
and many des ina ions a e adop ing a policy
o quali y se ice in o de o consolida e
hemsel es as an al e na i e op ion in he highly
compe i i e ma ke s o ou ism (Albaladejo,
González-Ma ínez, & Ma ínez-Ga cía, 2014).
Ano he impo an ac o is o e c owding
(San ana-Jiménez & He nández, 2011). Today,
he e is conce n abou he conges ion su e ed
by se e al adi ional des ina ions (Ba celona,
London, Pa is...). In a des ina ion like he
Spanish Medi e anean coas s, i is impo an
o know i hese a ibu es in l uence he e ec
o he pas ou is s on cu en demand and how.
In his pape , he in e na ional ou ism
demand in he Spanish Medi e anean coas s
is analyzed using annual da a o he pe iod
2005 o 2015. A dynamic ou ism model is
p oposed which allows he e ec o p e ious
ou is s o a y wi h he cha ac e is ics o he
des ina ion. Ou model is an ex ension o he
s anda d dynamic equa ion o ou ism demand
o include in e ac ion e ec s be ween p e ious
ou is s and wo ea u es: quali y o ou ism
se ices and ou ism conges ion. The aim o
he wo k is o s udy how bo h a ibu es a ec
he ela ionship be ween p e ious ou is s
and cu en ou ism demand on he Spanish
Medi e anean coas s. Empi ical i ndings on
quali y and conges ion play an impo an ole in
policy decisions.
A sys em GMM dynamic panel da a
analysis (Blundell & Bond, 1998) is ca ied
ou o es ima e he model. The da a a e
disagg ega ed bo h by p o ince o des ina ion
( he 11 Spanish p o inces ha make up
he Medi e anean a ea) and by coun y o
o igin. Since he main ou is ma ke is he
Eu opean Union (EU), we conside Eu opean
ou is s om he ollowing coun ies: Belgium,
F ance, Ge many, Holland, I aly, Po ugal and
Uni ed Kingdom. In 2015, mo e han 86% o
Eu opean Union ou is s came om one o
hese coun ies (INE, 2016). The esul s show
e idence o a s ong pe sis ence in ou ism
demand. P e ious ou is s ha e an impo an
posi i e and non-cons an e ec . I is posi i ely
in l uenced by he quali y o he ou ism se ices
and nega i ely by ou ism conges ion.
Ou analysis p o ides e idence ha
he p e ious ou is s e ec depends on he
a ac ion o epu a ion o he des ina ion. This
esul suppo s a nonlinea dynamic ou ism
demand model. In addi ion, o he bes o he
au ho s´ knowledge, his is he i s ecen s udy
o conside he Spanish Medi e anean coas s
as a whole. Mos p e ious s udies ha e ied o
explain he demand in di e en Medi e anean
coun ies (Ga & Falzon, 2014; Papa heodo ou,
1999). O he s udies on Spain analyze he majo
ou is cen e s o he Medi e anean, especially
he Balea ic Islands (Ga ín-Muñoz & Mon e o-
Ma ín, 2007; Rosselló, Aguiló, & Rie a, 2005;
Aguiló, Rie a, & Roselló, 2005).
The pape is o ganized as ollows. The
ollowing sec ion discusses he ole o he
p e ious ou is s on ou ism demand. I
summa izes he empi ical li e a u e o he
panel da a case, and ou dynamic model is
p oposed. Sec ion 2 p esen s he da a and
some desc ip i e s a is ic o he a iables
conside ed in he s udy. I also p o ides he
empi ical model and desc ibes he econome ic
me hod used o es ima ion. Sec ion 3 con ains
he esul s and hei in e p e a ion. Finally, he
las sec ion d aws some conclusions.
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67
4, XXI, 2018
Economics
1. The Impac o P e ious Tou is s
1.1. Li e a u e Re iew
The e is a widesp ead ag eemen ha ou ism
demand is likely o be a ec ed by p e ious
ou is s, ei he because o hei in l uence on
o he po en ial isi o s, o because hey epea
des ina ions (Mo ley, 2009; Ga ín-Muñoz, 2006;
2007; 2009, among o he s). P e ious ou ism
l ows inc ease in o ma ion abou a des ina ion,
he eby educing unce ain y o po en ial isi o s
(wo d-o -mou h ecommenda ions). Besides,
since he e is less unce ain y associa ed wi h
a des ina ion wi h which you a e al eady amilia ,
habi s migh induce ou is s no o a y hei
des ina ion o e ime (habi pe sis ence).
Rega ding ou ism demand modelling,
dynamic econome ic models allow us o ake
in o accoun he causal ela ionship be ween
p e ious isi o s’ l ows and he cu en demand.
Mos common dynamic speci i ca ions include
he p e ious ou is s as an explana o y
a iable in he model. Focusing on he panel
da a analysis, he e is an impo an numbe o
s udies ha ha e es ima ed a lagged dependen
a iable model. As examples, we ha e he
wo k by Maloney and Mon es Rojas (2005)
o ou is demand a Ca ibbean des ina ions;
Naudé and Saayman (2005) o ou is demand
in 43 A ican s a es; Ga ín-Muñoz (2006; 2007;
2009) o ou ism demand a di e en Spanish
des ina ions; Ga ín-Muñoz and Mon e o-Ma ín
(2007) o ou ism demand in he Balea ic
Islands (Spain); Massidda and E zo (2012)
o domes ic ou ism in I aly; and Rod íguez,
Ma ínez-Roge and Pawlowska (2012) o
academic ou ism demand in Galicia (Spain).
Mo e ecen ly, Capacci, Sco cu and Vici (2015)
includes wo lags o he dependen a iable o
analyze he impac o he Blue Flag on o eign
ou is s on he I alian coas s; and Pop awe
(2015) uses a panel da a se o o e 100
coun ies o es he hypo hesis ha co up ion
has a nega i e e ec on ou ism. Since all
hese s udies include he p e ious ou is s in
a linea ashion, he e ec o his a iable on he
cu en ou ism demand is assumed cons an
o e ime and o he c oss-sec ion. Thus, i
is independen o a iables like he quali y o
ou ism se ices and ou ism conges ion, which
may a ec he des ina ion’s epu a ion.
Mo ley (1998; 2009) and Albaladejo,
González-Ma ínez and Ma ínez-Ga cía (2016)
ha e ques ioned his way o inco po a ing
dynamics in o he model. Mo ley (2009)
a gues ha he simple inclusion o he lagged
dependen a iable allows epea isi s o be
inco po a ed in o a model, bu no wo d-o -
mou h ecommenda ions. He shows ha his
in o ma ion l ow has gene ally been neglec ed
in he li e a u e. Using he di usion model
(Bass, 1969; Mahajan, Mulle , & Bass, 1990),
Mo ley (1998; 2009) inco po a e ele an
ou ism in o ma ion l ows in a adi ional ou ism
demand model. The esul is a nonlinea model
ha includes quad a ic unc ions o p e ious
ou is s as e ms. Mo ley (1998), Rosselló,
Aguiló and Rie a (2005), Aguiló, Rie a and
Roselló (2005) and Hsu and Wang (2008) ha e
es ima ed he model wi h ime se ies da a and
i nd e idence o suppo his model.
Albaladejo, González-Ma ínez and
Ma ínez-Ga cía (2016) a gue ha he cons an
e ec o he p e ious ou is s esul ing om
he usual dynamic econome ic model is no in
acco dance wi h he Tou ism A ea Li e Cycle
(TALC) heo y o Bu le (1980), one o he mos
accep ed heo ies in ou ism li e a u e. Taking
in o accoun bo h his heo y and he adi ional
ou ism demand model, Albaladejo, González-
Ma ínez and Ma ínez-Ga cía (2016) p opose
a new dynamic speci i ca ion ha includes
a quad a ic unc ion o p e ious demand.
They es he model using panel da a om
Spanish egions du ing he pe iod 2000-2013.
Thei empi ical esul s show a posi i e and
dec easing e ec o he p e ious ou is s.
Bo h app oaches (di usion model and TALC
model) sugges ha usual cons an elas ici y
demand models a e likely misspeci i ed.
The e o e, a nonlinea dynamic speci i ca ion
is p e e ed. We ag ee wi h his gene al
conclusion, bu we add a new a gumen no
p esen in he p e ious li e a u e. A linea model
does no allow one o link he e ec o pas
ou is s o epu a ion o a ac i eness o he
ou ism des ina ion, assuming a cons an e ec .
Howe e , he in l uence o p e ious ou is s
may be a ec ed by changes in he epu a ion
o he ou ism des ina ion. In es men in he
ou ism indus y can imp o e he des ina ion’s
epu a ion (Albaladejo & Ma ínez-Ga cía,
2016), implying a mo e posi i e e ec o
p e ious ou is s on he cu en demand. The
quali y o ou ism se ices o a des ina ion and
i s ou is o e c owding a e wo cha ac e is ics
wi h a high impac on i s isi o s (Vajčne o á,
Žia an, Ryglo á, & And áško, 2014; Bee li &
Ma in, 2004).
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68 2018, XXI, 4
Ekonomie
1.2 A Nonlinea Dynamic Demand
Model
In his pape , we p opose a nonlinea dynamic
model whe e cu en ou ism demand can be
in l uenced by p e ious ou is s. Ou model allows
us o s udy how he numbe o p e ious ou is s
in e ac s wi h wo impo an ea u es o he ou is
des ina ion: ou ism se ices quali y, and ou ism
conges ion. Fo his pu pose, we add o he
s anda d dynamic ou ism model wo in e ac ion
e ms. The model can be exp essed as
01121 1
   
TTTQ
 

31 1

TO X

,
(1)
whe e subsc ip s and -1 deno e he ime
pe iod. The dependen a iable is T, he numbe
o ou is s, Q is he se ices quali y, O is he
des ina ion´s o e c owding, and X′=(x¹,x²,...,xK)
is he ec o o he emaining k explana o y
a iables (p ice, income, e c.), which can also
include lagged explana o y a iables and
dummy a iables. Thus, T –1∙Q –1 cap u es
he in e ac ion be ween p e ious ou is s and
quali y o ou ism se ices, and T –1∙O –1 he
in e ac ion be ween he p e ious ou is s and
he o e c owding o he des ina ion.
In his model, he ma ginal e ec o T -1
on T is a ec ed by wo cha ac e is ics o he
des ina ion. I is measu ed by he exp ession:
12131
1


 

TQO
T
 
, (2)
This e ec measu es he impac o he
p e ious ou is s on he cu en demand. I is
no cons an . Bo h p e ious le els o quali y and
o e c owding a he des ina ion can modi y his
e ec . I , as expec ed, β1 and β2 a e posi i e and
β3 is nega i e, i is a ma ginal e ec inc easing
wi h Q -1 and dec easing wi h O -1 (No e ha
he mos common dynamic speci i ca ion se s
β2 = β3 = 0, omi ing in e ac ion e ec s. In he
esul ing linea model, he ma ginal e ec is
cons an .). No e ha , i T is measu ed wi h
loga i hms, as is usual in empi ical ou ism
demand s udies, Equa ion (2) means ha he
elas ici y o ou ism demand wi h espec o
lagged demand is no cons an bu dependen
on quali y and conges ion.
The g ea e he se ices quali y
pe cei ed by he ou is and/o he smalle
he massi i ca ion in he ou is des ina ion,
he be e he epu a ion ha his des ina ion
will ha e. A be e epu a ion implies a highe
impac o he p e ious ou is s on he cu en
demand. In con as , i he inc eases in he
isi o s o a des ina ion a e no accompanied by
an adequa e in es men in quali y and quan i y
o he ou ism se ices, ou is s’ opinion abou
he des ina ion will be wo s , and hei posi i e
e ec on he u u e demand will be lowe . Tha
is, a des ina ion can cushion he downwa d
dynamics o his e ec by in es ing in ou ism.
2. Da a and Me hodology
2.1 Da a and Va iables
The Medi e anean coas s a e he main
des ina ion o in e na ional ou ism in Spain.
Acco ding o he INE (2016), in 2015, abou
25.7 million in e na ional ou is s s ayed a
ho els in he Medi e anean p o inces. They
ep esen 55% o he in e na ional ou is s
a i ing in Spain and s aying in ho els (The
in e na ional ou is s who chose ho els and
simila es ablishmen s as accommoda ion
in Spain ep esen ed 67% o o al a i als in
2015 (INE, 2016)). The e olu ion o hese
ou is s om 2005 o 2015 is p esen ed in Fig.
2. Tou ism ose sha ply om 2005 o 2006, bu
s agna ion is obse ed in 2007 and 2008, and
a sha p d op occu s in 2009, as esul o he
i nancial c isis and he economic ecession.
Since 2010, he numbe o ou is s seems o be
expe iencing a new g ow h phase.
To explain he in e na ional ou ism demand
o he Spanish Medi e anean coas s, we
es ima e he model p oposed in Sec ion 1.2
using annual da a disagg ega ed by p o ince
o des ina ion and coun y o o igin. We
use a balanced panel da a se consis ing o
he 11 p o inces ha make up he Spanish
Medi e anean coas s and he 7 Eu opean
coun ies which a e he main o igin ma ke s o
he pe iod 2005-2015. Panel da a ha e some
ad an ages o e c oss sec ional o ime se ies
da a. One is ha hey enable us o con ol o
unobse able c oss sec ional he e ogenei y,
which is common in p o incial da a. Time se ies
and c oss sec ion s udies no con olling o his
he e ogenei y un he isk o ob aining biased
esul s. Mo eo e , panel da a usually gi e
a la ge numbe o da a poin s, so inc easing he
deg ees o eedom, educing he collinea i y
among explana o y a iables and imp o ing
he e i ciency o econome ic es ima es (Hsiao,
2003; Bal agi, 2008).
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69
4, XXI, 2018
Economics
Ou model includes economic demand
a iables, such as income and p ices,
a dummy a iable o con olling he e ec s o
he economic c isis, and a nonlinea e m o
cap u e he e ec o p e ious ou is s. This e m
means he e ec o he p e ious ou is s can be
no cons an , bu can depend on he quali y o
he ou ism se ices and he ou is conges ion
a he des ina ions (Equa ion 2).
The dependen a iable is he numbe o
in e na ional ou is s (T) who choose ho els and
simila es ablishmen s as accommoda ion (We
a e awa e ha using only he da a o ou is s
s aying a ho els is a limi a ion. Howe e , in
his pape we ha e chosen o be syn he ic
and o p esen only ho el demand da a. In any
case, in Spain ho el demand da a a e qui e
signi i can because hey ep esen a ound
70% o he in e na ional demand egis e ed in
Spain h oughou he pe iod (INE, 2016)). Da a
a e aken om he Ho el Occupancy Su ey
(INE, 2016). Two adi ional economic ac o s
a e included among he explana o y a iables:
o igin income and p ice. To measu e o igin
income, we use he eal pe capi a GDP o each
o igin coun y (GDP). This a iable was aken
om OCDE (2016). The p ice a iable included
in ou model e l ec s he cos o li ing o ou is s
a he di e en des ina ions ela i e o he cos
o li ing in he coun y o o igin (IP):
/
/

des ina ion
des ina ion o igin
o igin Spain o igin
CPI
IP CPI EX
(3)
whe e CPIdes ina ion and CPIo igin a e he
consume p ice indices (CPIs) o each o he
11 des ina ions conside ed and each o igin
coun y, espec i ely; EXSpain/o igin is he nominal
e ec i e exchange a e o Spain s each
coun y (The nominal exchange a e be ween
Spain and Eu ozone coun ies is equal o 1.
The e o e, we only need o mul iply he CPI o
he o igin coun y by he nominal exchange a e
in he case o he Uni ed Kingdom). Da a on
exchange a es and CPIs o each coun y we e
collec ed om Eu os a (2016). Da a on CPI o
he 11 Spanish p o inces we e collec ed om
he INE (2016).
Addi ionally, based on Fig. 2, we conside
a dummy a iable o cap u e he in l uence on
ou ism o he i nancial and economic c isis.
Fig. 2: In e na ional ou is s lodged a ho els in Spanish Medi e anean p o inces
Sou ce: own om he da a p o ided by he INE (2016)
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70 2018, XXI, 4
Ekonomie
This a iable, D2009, akes he alue 1 om
2009 onwa d and 0 in o he yea s.
To build he in e ac ions included in he
nonlinea e m o ou model, a measu e o
quali y o ou ism se ices (Q) and a measu e
o ou is conges ion (O) ha e o be de i ned.
Measu ing bo h ea u es is no an easy ask.
The e is no uni e sal de i ni ion o ei he o
hese a ibu es in ou ism.
Wi h ega d o quali y, we ocus on he supply
o ou ism se ices, speci i cally on he quali y o
ou ism accommoda ions. Nicolau and Selle s
(2010), and he e e ences he ein, highligh
ha quali y o accommoda ions is s a egic o
inc easing ou ism compe i i eness. We ha e
ollowed his idea in ou pape . The pe cen age
o luxu y ho els is u ilized as a p oxy o quali y
o ou ism accommoda ions. We use he o i cial
classi i ca ion sys em in Spain om 1 o 5 golden
s a s and om 1 o 3 sil e s a s o de i ne he
ca ego y o ho els. Conside ing as luxu y ho els
he ou and i e golden s a s ho els, he quali y
o ou ism se ices is de i ned as
100
ou and i e golden s a s ho els
o al numbe o ho els
Q (4)
Da a on ho els we e collec ed om he
INE (2016). The a io (4) has also been used
as quali y measu e in he pape o Albaladejo,
González-Ma ínez and Ma ínez-Ga cía
(2014).
Conges ion o o e c owding o a des ina ion
inc eases when he numbe o isi o s is
excessi e in ela ion o he space o capaci y o
he des ina ion o accommoda e hose ou is s,
especially du ing peak pe iods. In o de o
ob ain an idea abou he conges ion in each
p o ince, we conside he ela ionship be ween
i s ou ism demand and i s ou ism supply,
speci i cally we use he a io be ween he o al
numbe o ou is s lodged a ho els and he
o al numbe o ho el beds as p oxy o ou is
conges ion a each des ina ion p o ince
domes ic and in e na ional ou is s
o al numbe o beds
O
(5)
Da a on ho el beds and ou is s we e
collec ed om he INE (2016). The a io (5)
can be conside ed as a measu e o he densi y
o ou is s lodged a ho els. I epo s on he
ela ionship be ween ou ism demand and
ou ism supply in each p o ince. The g ea e
he numbe o ho el beds in a des ina ion, he
highe he chance o accommoda ing isi o s
sui ably.
A ele an ad an age o using bo h measu es
(Q and O) is ha hei homogeneous cha ac e
allows compa isons among se e al p o inces.
2.2 Me hodology and Model
Speci i ca ion
Following he model p oposed in Sec ion 2 and
conside ing he a iables de i ned abo e, he
econome ic model is ep esen ed as
,1,12,1,1
   
ij ij ij ij i
TTTQ
 
3,1 ,1 4 , 5 ,
 
ij i j ij
TO GDP IP

6,
2009
ij
D

(6)
whe e he subsc ip i deno es he des ina ion
p o ince (Alican e, Alme ia, Balea ic Islands,
Ba celona, Cas ellon, Gi ona, G anada, Malaga,
Mu cia, Ta agona and Valencia); j deno es he
o igin coun y (Belgium, F ance, Ge many,
Holland, I aly, Po ugal and Uni ed Kingdom),
and indica es he ime pe iod ( = 2005-2015).
ηij is he unobse ed p o incial-speci i c a iable
(o i xed e ec s) ha a ies ac oss p o inces
and o igin coun ies, bu is in a iable o e ime,
and εij, is a dis u bance e m. A key assump ion
h oughou his pape is ha he dis u bance εij,
is unco ela ed ac oss p o inces, bu p o incial
he e oscedas ici y and se ial co ela ion a e
allowed o . All a iables a e exp essed in
na u al loga i hms so ha he coe i cien s may
be in e p e ed as elas ici ies.
As discussed in Sec ion 1.2, he e ec o
he p e ious ou is (Tij, -1) depends on β1, β2,
β3, and he p e ious quali y and conges ion
o he des ina ion (see Equa ion 2). Since
a log-log model is used, his e ec ep esen s
he elas ici y o cu en ou ism demand wi h
espec o p e ious demand. A posi i e sign
is expec ed o β1, hus a posi i e β2 would
imply ha his elas ici y inc eases wi h he
p e ious le el o quali y o he ou ism supply,
gi en a le el o ou is conges ion. Likewise,
a nega i e β3 would imply ha he elas ici y
dec eases wi h he p e ious ou is conges ion,
gi en a le el o quali y. I β2 and β3 a e ze o,
he elas ici y is cons an ac oss he des ina ions
and h ough ime. As usual in demand models,
we expec a posi i e sign o β4 and a nega i e
sign o β5 and β6.
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Economics
A gene alized me hod o momen s (GMM)
panel da a es ima ion (A ellano & Bond, 1991;
A ellano & Bo e , 1995; Blundell & Bond,
1998) was applied o conduc ou empi ical
analysis. O dina y Leas Squa es (OLS) is no
app op ia e o es ima e dynamic panel models
wi h he lagged dependen a iable among he
eg esso s. The lagged dependen a iable is
co ela ed wi h he unobse able p o incial
e ec (ηi), which gi es ise o “dynamic panel
bias” (Nickell, 1981). The wi hin g oups and
andom e ec s es ima o s do no elimina e he
“dynamic panel bias” and a e also biased and
inconsis en . To sol e his p oblem, A ellano and
Bond (1991) sugges i s di e encing he model
o emo e he unobse ed i xed e ec s (ηi). As
he di e enced lagged dependen a iable is
s ill po en ially endogenous, i is ins umen ed
wi h lagged le els o he endogenous a iable
o sol e he p oblem o au oco ela ion. I he
εij, a e no se ially co ela ed, we can use
lags 2 and upwa ds o he endogenous a iable
as ins umen s. Blundell and Bond (1998)
ex ended his es ima o by building a sys em
o equa ions o med by he equa ion in i s
di e ences and he equa ion in le els. The
ex ended GMM es ima o , called sys em GMM,
uses lagged i s -di e ences as ins umen s
o equa ion in le els, in addi ion o he usual
lagged le els as ins umen s o equa ion in
i s -di e ences.
In his pape , we apply he sys em GMM
(Blundell & Bond, 1998) p ocedu e o es ima e
he model (6). We use he one-s ep obus o
he e oscedas ici y es ima o and he wo-s ep
es ima o o compa ison (One-s ep GMM
es ima o is based on he assump ion ha
he εij, a e i.i.d. In his pape , we use one-s ep
obus es ima o s, whe e he esul ing s anda d
e o s a e consis en wi h panel-speci i c
au oco ela ion and he e oscedas ici y).
Al hough he wo-s ep es ima o is heo e ically
p e e ed, i is app op ia e o conside he one-
s ep esul s when making in e ences, since he
asymp o ic s anda d e o s o one-s ep GMM
es ima o s a e i ually unbiased (A ellano &
Bond, 1991).
A c ucial assump ion o he alidi y o GMM
is ha he ins umen s a e exogenous. We
conduc wo diagnos ic es s: Hansen (1982)
J- es s o he o e iden i ying es ic ions o
he GMM es ima o s, and he A ellano and
Bond (1991) es o au oco ela ion in he
dis u bance e m, εij, (The Hansen s a is ics is
a chi-squa ed es o de e mine i he esiduals
a e co ela ed wi h he ins umen a iables.
I nonsphe ici y is suspec ed in he e o s, he
Hansen o e iden i i ca ion es is heo e ically
supe io o he Sa gan (1958) es ).
3. Resul s
We show wo di e en GMM es ima es: one-
s ep and wo-s ep e sions o he sys em
GMM (GMM-SYS). In bo h es ima es he
lagged dependen a iable and he wo lagged
in e ac ion e ms a e ea ed as endogenous.
Since he usual o mulas o coe i cien
s anda d e o s in wo-s ep GMM end o be
downwa d biased when he ins umen coun is
high, we use he Windmeije (2005) s anda d
e o s co ec ion.
The empi ical esul s om he es ima ion o
he model a e shown in Tab. 1. The es ima ed
coe i cien o he lagged dependen a iable
is signi i can and posi i e, and he es ima ed
coe i cien s o he in e ac ion e ms a e bo h
signi i can and ha e opposing signs. As
expec ed, he e ec o he lagged dependen
a iable depends posi i ely on he pe cen age
o luxu y ho els, and nega i ely on he a io
be ween ou is s and ho el beds. Thus, he e
is a non-cons an e ec o he p e ious numbe
o ou is s o e cu en ou is s. Addi ionally,
he esul s e eal a gene ally sa is ac o y
pe o mance o he econome ic models. The
au oco ela ion es s (A ellano & Bond, 1991)
do no de ec any se ial co ela ion p oblem
in he esiduals. As expec ed, he esiduals in
di e ences a e au oco ela ed o o de 1, while
he e is no au oco ela ion o second o de . In
addi ion, he Hansen (1982) J- es does no
ejec he null o join alidi y o he ins umen s.
Bo h es ima es (one-s ep and wo-s ep)
yield simila esul s. All a iables a e s a is ically
signi i can . Es ima ed β1 (0.9626, 0.9674) and
β2 (0.0149, 0.0147) a e posi i e, and es ima ed
β3 (-0.0159, -0.0182) is nega i e. Thus, he
elas ici y o ou ism demand wi h espec o he
lagged demand is posi i e, inc easing wi h he
pe cen age o luxu y ho els, and dec easing
wi h he a io be ween ou is s and ho el beds
a he des ina ion. This means ha quali y o
ou ism se ices and ou is conges ion a e
ele an o explaining in e na ional ou ism
demand in he Medi e anean coas s. The
implica ion o his esul is ha , in o de o
a ac mo e ou is s, he supplie s o ou ism
p oduc s should imp o e hei se ice quali y
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72 2018, XXI, 4
Ekonomie
and adap ho el capaci y. The es ima ed income
elas ici y (0.0301, 0.0294) is posi i e, showing
ha he a i al o Eu opean ou is s o Spanish
Medi e anean coas s depend posi i ely on
he weal h o i s o igin coun y. As expec ed,
nega i e p ice elas ici y is es ima ed wi h alues
o -0.1752 and -0.2148, sugges ing ha ou is
a i als a e also sensi i e o p ice changes.
Finally, he dummy a iable ep esen ing he
impac o he global c isis has he expec ed
nega i e sign (-0.0989 and -0.0971).
One o he mos impo an de e minan s
o he in e na ional ou ism on he Spanish
Medi e anean coas s seems o be he lagged
dependen a iable, which con ols bo h he
e ec o he wo d-o -mou h ecommenda ions
and he e ec o habi pe sis ence. Since
β2 and β3 a e signi i can , he e ec o his
a iable is non-cons an , bu a ies ac oss he
des ina ions and o e ime. In any gi en yea ,
i a ies be ween he di e en Medi e anean
p o inces depending on i s pe cen age o
luxu y ho els and he ela ionship be ween i s
ou ism demand ( ou is s) and ou ism supply
(ho el beds). Mo eo e , gi en a pa icula
des ina ion, i inc eases wi h he quali y o
se ices o e ed by ho els, and dec eases when
he inc ease in he ou is s is no accompanied
by a p opo ional inc ease in he numbe o
ho el beds. In o de o show hese esul s,
he elas ici y o ou ism demand wi h espec
o he p e ious ou is s has been calcula ed
in each o he p o inces using he es ima ed
coe i cien s om he second column o Tab. 1.
Fig. 3 shows hese es ima ed elas ici ies o he
yea s 2006 and 2015 (Since elas ici y depends
on cha ac e is ics o he ou is des ina ion, o
each p o ince he elas ici y o p e ious ou is s
is he same o ou is s a i ing om di e en
o igin coun ies). The es ima es o bo h yea s
show a e y simila anking. G anada is he
p o ince wi h he lowes es ima ed e ec o
p e ious ou is s, while he Balea ic Islands
ha e he highes es ima ed e ec e e y yea . In
his p o ince, he in l uence o p e ious ou is
is e y simila o bo h yea s showing ha i s
a ac i eness as a ou is des ina ion has
emained s able o he las en yea s. The same
happens in Malaga, which is he hi d p o ince
wi h g ea es elas ici y a e he Balea ic Islands
and Alme ia. The es o he p o inces show
a la ge inc ease in he es ima ed elas ici y
du ing he pe iod o analysis. This esul
indica es ha imp o emen s ca ied ou in
he Medi e anean coas s ho els ha e been
app op ia e o sa is ying he g owing ou ism
demand ha his a ea is expe iencing.
Dependen a iable: Tij, GMM-SYS
Explana o y a iables one-s ep wo-s ep
Tij, -1 0.9626*** 0.9674***
Tij, -1⋅Qi, -1 0.0149*** 0.0147***
Tij, -1⋅Oi, -1 -0.0159** -0.0182**
GDPj 0.0301*** 0.0294**
IPij, -0.1752** -0.2148**
D2009 -0.0989*** -0.0971***
Hansen es (p- alue) 0.076 0.076
AR(1) (p- alue) 0.000 0.000
AR(2) (p- alue) 0.208 0.222
Numbe o obse a ions 770 770
Numbe o g oups 77 77
Sou ce: own using he x abond2 command in STATA10 (Roodman, 2009)
No e: *, **, *** deno e signi i can a he 10%, 5% and 1% le el espec i ely.
Tab. 1: Es ima ion esul s o in e na ional ou ism demand model, 2005-2015
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73
4, XXI, 2018
Economics
Fig. 4 shows he sca e plo and eg ession
line be ween es ima ed elas ici y o he
lagged dependen a iable and pe cen age o
luxu y ho els in 2015, and Fig. 5 be ween he
es ima ed elas ici y and ou is s-ho el beds
a io. Bo h i gu es g aphically illus a e why
he e ec o p e ious ou is s is g ea e o less
in each p o ince. As expec ed, Fig. 4 shows
a posi i e ela ionship and Fig. 5 a nega i e
one. On a e age, he highe he pe cen age o
luxu y ho els he g ea e he posi i e e ec o he
p e ious ou is s on he cu en demand (see
Fig. 4). The Balea ic Islands a e an example.
Howe e , he e a e p o inces mo ing away
om his a e age beha io . Alme ia has a high
es ima ed elas ici y in ela ion o i s pe cen age
o luxu y ho els. On he o he hand, Ba celona
has a low es ima ed elas ici y in ela ion o i s
ho el quali y, p obably due o ou is conges ion.
Fig. 5 indica es ha he lowe he ou is
conges ion, he mo e bene i cial he in l uence o
p e ious ou is s on he cu en demand. This
is he eason why Alme ia has a high elas ici y.
I is he p o ince wi h he lowes ou is s-ho el
beds a io. Balea ic Islands and Ba celona
mo ing away om his a e age beha io
showing a la ge elas ici y, because hey a e
he p o inces ha o e he highes ho el quali y.
In con as , Cas ellon, due o i s low pe cen age
o luxu y ho els, has a lowe es ima ed elas ici y
han ha co esponding o i s le el o ou is
conges ion. Finally, looking a Fig. 4 and 5, i
is easy o unde s and why he Balea ic Islands
and G anada a e he p o inces wi h g ea es
and lowes elas ici y, espec i ely. The Balea ic
Islands ha e he highes quali y ho els, as well
as he second lowes a io be ween ou is s
and ho el beds. In con as , G anada (along
wi h Cas ellon) has he lowes pe cen age o
high-quali y ho els, and he g ea es ou is
conges ion (along wi h Ba celona).
To sum up, esul s om he GMM es ima es
imply ha p e ious ou is s ha e played an
ac i e ole in he g ow h o ou ism in he
Spanish Medi e anean coas s. The signi i can
posi i e e ec o he p e ious ou is s e eals
Fig. 3: Es ima ed elas ici y o ou ism demand wi h espec o p e ious ou is s
Sou ce: own
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