How Can he Effec s o he In oduc ion
o a New Ai line on a Na ional Ai line
Ne wo k be Measu ed?
A Time Se ies App oach o he Ryanai Case in Spain
Jose
´I. Cas illo-Manzano, Lou des Lo
´pez-Valpues a,
and Diego J. Ped egal
Add ess o co espondence: Jose
´I. Cas illo-Manzano, Facul ad de Ciencias Econo
´micas y Emp es-
a iales, Uni e si y o Se ille, A da. Ramo
´n y Cajal, 1, 41018 Se ille, Spain ([email p o ec ed]).
Lou des Lo
´pez-Valpues a is a Facul ad de Ciencias Econo
´micas y Emp esa iales, Uni e si y o
Se ille (Spain) ([email p o ec ed]). Diego J. Ped egal is a Ingenium Resea ch G oup and IMACI,
Uni e si y o Cas illa-La Mancha (Spain) ([email p o ec ed]).
The au ho s would like o exp ess hei g a i ude o he Fundacio
´n Cen o de Es udios Andaluces
o he financial esou ces ha i p o ided o his s udy. The au ho s a e also g a e ul o S e en
A. Mo ison, he anonymous e iewe , and Ge ma
`Bel o hei e y help ul commen s.
Abs ac
This pape quan ifies he Ryanai Effec on he Spanish ai line ne wo k. I p oposes new me hodology
based on an ad anced ime se ies app oach ha allows bo h he di ec and indi ec effec s o he
inco po a ion o a new ai line o be measu ed and ha can be easily ex apola ed o o he ai po
sys ems. The findings show he mean indi ec effec on o he ai lines, in absolu e alue, is 8.6 pe
cen o he o al ai po affic, peaking a a maximum o almos 29 pe cen . Also, su p isingly,
he e is ound o be a nega i e indi ec effec a only ou o he en ai po s analysed.
Da e o eceip o final manusc ip : June 2011
263
Jou nal o T anspo Economics and Policy, Volume 46, Pa 2, May 2012, pp. 263–279
1.0 In oduc ion
The e is a weal h o li e a u e illus a ing he in e na ional de elopmen o he low-cos
model and i s expansion in o diffe en geog aphical a eas (see F ancis e al., 2006, o an
o e iew o his de elopmen ). To be specific, in Eu ope, he ea ly mid-1980s’ libe alisa-
ion be ween I eland and he UK c ea ed he condi ions ha allowed he fi s low-cos
ai line o appea in Eu ope, Ryanai (see F ancis e al., 2006, o he easons ha
a ou ed he c ea ion o Low Cos Ca ie s (LCCs) in hese wo coun ies). This ai line
has de eloped in o he main low-cos Eu opean ai line and he mos success ul LCC in
he wo ld in e ms o p ofi abili y (Oli ei a, 2008).
Ryanai ollowed in he oo s eps o he Sou hwes Ai lines company (see Guillen
and Lall, 2004, on he main diffe ences be ween Ryanai and Sou hwes ), al hough ime
has shown ha Ryanai has emained mo e ai h ul o he ea u es o he o iginal low-
cos model han i s p ecu so , Sou hwes (Alamda i and Fagan, 2005). I has also
c ea ed a model ha can be easily eplica ed (Guillen and Lall, 2004).
One o he salien ea u es o he Ryanai managemen model o ou analysis is he
use o unde u ilised seconda y ai po s, o en a om main ci y ai po s, and egional
ai po s. This is wha diffe en ia es he ai line om o he majo LCCs like easyJe o
Sou hwes (Dob uszkes, 2006; F ancis e al., 2006; G aham, 2009). Ryanai usually
a oids using p ima y ai po s, excep when a seconda y ai po is no a ailable in he
egion (G aham, 2009), as he la e a e less expensi e in e ms o landing cha ges; hey
a e less conges ed han he majo hub ai po s; sho e u na ounds a e possible and,
he e o e, mo e jou neys pe day pe plane can be achie ed (Ba e , 2004).
Ryanai plays he dominan ole in many o hese seconda y o egional ai po s and
in some, such as Cha le oi and Gi ona (Ba bo , 2006), almos exe cises a monopoly.
This powe influences i s p ice s a egy, as Ryanai seems o se lowe a es when fligh s
depa om o a i e a domina ed ai po s (Ba bo , 2006; Malighe i e al., 2009). This
is, in u n, influenced by he ac ha ope a ing a ai po s o his ype allows Ryanai
always o be in a posi ion o nego ia e ai po ees (F o
¨idh, 2008; Oli ei a, 2008). In his
way Ryanai has shown ha seconda y ai po s a e no only able o cha ge less (see
Cas illo-Manzano, 2010) bu also offe subsidies o a ac ai lines (Papa heodo ou and
Lei, 2006), o en wi h he aid o local o egional public au ho i ies (see Cas illo-
Manzano and Lo
´pez-Valpues a, 2010).
Seconda y ai po manage s whe e LCCs a e ound should be awa e ha hey a e
acing high ola ili y in hei affic, due bo h o he g ea e likelihood o bank up cy o
me ging o hese kinds o ai lines and o hei dependence on he aid and subsidies ha
hey apply o . The e is e en highe ola ili y when he ai po has a dominan single
LCC (Guillen and Lall, 2004; Ba bo , 2006; Bel, 2009), as is he case o Ryanai a many
o he seconda y ai po s whe e i ope a es.
In his con ex , he objec i e o his a icle is an analysis o wha has been dubbed,
acco ding o Guillen and Lall (2004), he Ryanai Effec on he Spanish ai line ne wo k.
Following Vowles (2001) and Pi field (2008) on he Sou hwes Effec , he Ryanai Effec
would be he effec on a e age ai a es, affic olumes, and ma ke sha es expe ienced in
he ma ke s in o which Ryanai en e s. The p io academic li e a u e has s udied he
impac o he a i al o a new LCC a he ai po s which accep hem, mainly analysing
he effec ha his a i al has on ai a es and he spillo e effec s on nea by ai po s
Jou nal o T anspo Economics and Policy Volume 46, Pa 2
264
(Mo ison, 2001; Vowles, 2001; Da aban and Fou nie , 2008). Wi h espec o he effec s
on affic, mos o he s udies (Donzelli, 2010; G aham and Dennis, 2010) analyse he
impac o he a i al o an LCC by compu ing he o e all g ow h in passenge numbe s
wi hou analysing any possible colla e al effec s on he affic o o he companies.
This pape seeks o quan i y he o e all effec on comme cial affic by esponding o
he ollowing ques ion: gi en he e iden inc ease ha he a i al o Ryanai means o an
ai po ’s affic which has been highligh ed in he li e a u e (Ba e , 2004; F ancis e al.,
2004; Yo k A ia ion, 2007; Bel, 2009), how much o his g ow h can be di ec ly a ibu ed
o Ryanai ’s own affic, and wha p opo ion can be a ibu ed o he eac ion o he
o he ai lines a he ai po o he a i al o said low-cos ai line? Fo he o he companies,
he a i al o his low-cos company can ha e ei he a compe i i e o a ca alys effec —
ha is, be a s imulus ha inc eases hei olume o affic — o i can ha e no effec
wha soe e , o i can lead o a educ ion in hei affic due o he subs i u ion effec .
As desc ibed p e iously, he fi s effec , he compe i i e o ca alys effec , would be
a ibu able o Ryanai ha ing become a leading company in he Eu opean a ia ion
sec o . In some coun ies, like Spain, i is e en he leading ai line in passenge affic. I
should he e o e be an icipa ed ha when a leading company b eaks in o new ma ke s/
ai po s, i could aise he compe i i eness o he o he companies/ai lines ope a ing
he e and, especially, poin he way (pull o knock-on effec ) o o he s ha we e no
ope a ing in his ma ke (gene ally, a egional o p e iously unde u ilised seconda y
ai po ) o ollow hem. Wi h espec o inc eased compe i i eness, his has been docu-
men ed by Sou hwes . To be specific, acco ding o Vowles (2001), he en y o Sou hwes
can in some cases lead o o he ca ie s lowe ing hei a es o emain compe i i e, which
s imula es mo e affic. Gillen and Lall (2004) also s a e ha a es all p io o he a i al
o Sou hwes a a new des ina ion and his gene a es emendous demand which also
benefi s o he ca ie s. Wi h ega d o he possible pull effec , acco ding o Yo k
A ia ion (2007), Ryanai ac ed as a ca alys o u he g ow h a Eindho en ai po by
p o ing ha low- a e se ices we e sus ainable, hus a ac ing new ai lines. Gene ally,
his compe i i e effec , in any o i s o ms, could also be suppo ed by he inc ease in he
appeal o he ai po om he pe spec i e o ans e s on he back o Ryanai ’s new
des ina ions.
Wi h ega d o he abo e-desc ibed subs i u ion effec , his can in u n be one o wo
ypes: Fi s , he a i al o Ryanai wi h connec ions o he main Eu opean ci ies, like
London and Pa is, can ha e an effec on he connec ions ha al eady exis be ween he
Spanish ai po s and des ina ions such as hese which had p e iously been in he hands
o he ne wo k ca ie s (NCs). Second, he in oduc ion o new poin - o-poin des ina-
ions, especially in he case o egional ai po s, will educe he numbe o fligh s o hubs
like Mad id and Ba celona, which we e p e iously an obliga o y s opo e poin when
a elling o he new des ina ions. This possible nega i e poin , namely he all in NCs
affic, has been condemned by Spanish a el agency associa ions p o es ing abou non-
e u nable subsidies and o he economic aid being g an ed o Ryanai and o he LCCs
by he public au ho i ies (see Cas illo-Manzano and Lo
´pez-Valpues a, 2010). Acco ding
o hese associa ions, hese subs i u ion effec s a e especially de imen al o con e ence
ou ism (see Cas illo-Manzano e al., 2011).
Bo h he o al di ec and indi ec effec s o Ryanai need o be measu ed om he
poin o iew o anspo policy o local and egional public adminis a ions o assess
How Can he Effec s o he In oduc ion o a New Ai line be Measu ed? Cas illo-Manzano e al.
265
he inc easingly equen and highe economic compensa ion ha he company demands
o ope a e in egional ai po s bo h in Spain (see Cas illo-Manzano e al., 2011) and in
he es o Eu ope.
Me hodologically, his s udy uses an econome ic model o es ima e he ne quan i a-
i e impac o he a i al o his ai line on he main affic a Spanish ai po s in line
wi h o he s udies (Pi field, 2007, 2008).
The majo ad an age o he p oposed me hodological app oach is ha i can be
easily ex apola ed o o he ai po sys ems o measu e he effec s ha he a i al o any
new ai line, be i an LCC o an NC, would ha e on he o he ai lines a he a ious
ai po s.
The a icle is o ganised as ollows. Sec ion 2 lays ou he da a and p esen s he
me hodological app oach. Sec ion 3 p esen s he empi ical esul s, while Sec ion 4
includes he discussion o hese findings and, finally, Sec ion 5 p esen s he conclusions
o he s udy.
2.0 Da a and Me hods
The Spanish ai po s analysed in his s udy we e chosen o ha ing achie ed Ryanai
affic figu es o o e 400,000 passenge s in 2008. Fou o he en ai po s in he sample
we e in he lis o he op fi y busies ai po s in Eu ope in 2008, specifically Mad id-
Ba ajas ( ou h), Palma de Majo ca ( hi een h), Ma
´laga ( hi y-second), and Alican e
( o y-fi s ). When we add he case o Ba celona (nin h), whe e Ryanai s a ed ope a ing
in he au umn o 2010, o hese ai po s, i can be seen ha , unlike in o he coun ies,
Ryania ope a es a he majo hubs in Spain, no only a seconda y o egional ai po s.
This is due bo h o Spanish ai po cha ges being low and o he ac ha he e a e no
g ea diffe ences be ween hese cha ges a he a ious ai po s, wha e e hei size.1
The o al effec o Ryanai ’s a i al on he abo e-men ioned ai po s o Decembe
2008 will be spli in o a di ec effec and an indi ec effec :
1 The di ec effec is he effec ha he li e a u e has adi ionally measu ed — ha is, he
pe cen age ep esen ed by Ryanai affic ou o he o al affic a he ai po (see
equa ion (1)). TRi; ¼Ryanai affic a ai po idu ing mon h and TTi; ¼ o al
affic a ai po iin mon h (see Figu e 1). Finally, lis he mon h ha Ryanai
began o ope a e a ai po iand Nis he numbe o obse a ions:
DEi¼P
N
¼l
TRi;
P
N
¼l
TTi;
100:ð1Þ
1
Fo example, he ai po cha ge o domes ic and Eu opean Union fligh s a Ba celona ai po ’s spec acula new
e minal was €6.12 pe onne (10–100 onne ai c a ), while a Ba celona’s seconda y and mos dis an ai po s,
Reus and Gi ona, he cha ge s ood a €5.55 — ha is, only 10 pe cen less. Ne e heless, new cha ges ha e come
in o o ce in 2011 wi h g ea e disc imina ion acco ding o ai po size.
Jou nal o T anspo Economics and Policy Volume 46, Pa 2
266
2 The indi ec effec , o en igno ed by p e ious s udies, will comp ise wo en ies, which
will be agg ega ed o hei es ima ion. These en ies a e he compe i i e o ca alys
effec on o he ai lines, wi h a posi i e sign, and he subs i u ion effec on o he ai lines
— NCs in he main — wi h a nega i e sign. The subs i u ion effec can be caused bo h
by Ryanai offe ing connec ions which had p e iously been offe ed by o he ai lines
and also by he company’s new des ina ions, which educe affic o na ional hubs
like Mad id and Ba celona. The da a used o measu e he indi ec effec s o Ryanai
on ai po ican be di ided in o h ee g oups:
(A) The endogenous a iables will be he mon hly ai affic, wi hou conside ing
Ryanai affic, a he en Spanish ai po s included in he s udy; his is esidual
affic. The a ailable ime se ies spans om Janua y 1996 o Decembe 2008
a e aken om AENA yea books (sou ce: www.aena.es).
(B) The exogenous a iables, sepa a ed in o wo g oups, a e as ollows:
(B.1) Dummy exogenous a iables: a wide ange o a iables a e included in
models o es ima e a numbe o in e en ion a iables and ou lie effec s
seen in he da a. The mos impo an , wi h hei defini ions, a e as
ollows:
Figu e 1
Millions o Ai Passenge s (Pe Mon h) a he Ten Spanish Ai po s Conside ed
1996 1998 2000 2002 2004 2006 2008
0
0.05
0.1
0.15
0.2
Millions
0
2
4
6
Millions
0
0.2
0.4
0.6
Millions
Mad id
Palma de Majo ca
Málaga
Alican e
Gi ona
Valencia
Se ille
Mu cia
Reus
San ande
How Can he Effec s o he In oduc ion o a New Ai line be Measu ed? Cas illo-Manzano e al.
267

(B.1.1) Eas e : Ai affic a ound his holiday pe iod is especially in ense
in Spain. Indeed, i is conside ed o be high season o ou is s,
among o he easons due o he nume ous celeb a ions o he
passion o Ch is . Acco dingly, he mo eable eas o Eas e
a iable is defined by assigning diffe en weigh s o he days in
ques ion depending on he expec ed affic densi y a Spanish
ai po s ( hese weigh s ha e o add up o one). Maximum weigh s
a e assigned o Wednesday, Thu sday, Eas e Sunday, and
Monday. Weigh s o ze o a e assigned o he es o he days.
(B.1.2) Business: Mon hly ime se ies ha a e o als o daily ac i i ies
can be influenced by each calenda mon h’s weekday and
weekend composi ion. This a iable is in oduced o ake in o
accoun he diffe ences among mon hs ega ding he p opo -
ion o weekdays wi h espec o weekends. I is cons uc ed as
he numbe o business o ading days wi h espec o weekend
days and holidays in each indi idual mon h — ha is, he
numbe o business o ading days minus he numbe o
Sa u days and Sundays mul iplied by 5/2. Ex a holidays in
each mon h a e sub ac ed om he business days.
(B.1.3) Leap: Add esses he leap yea effec . The alue is 1 when
Feb ua y con ains 29 days, and 0 o he wise.
(B.1.4) 9/11: The nega i e effec on ai affic ha esul ed om he
9/11 e o is a acks which, as ound in ea lie s udies (Inglada
and Rey, 2004), also had a significan effec on he Spanish
ai po sys em. The du a ion o hese effec s in numbe o
mon hs has been de e mined empi ically by es ima ing succes-
si ely models in which his effec ha e inc easing du a ions om
one o six yea s and choosing he model wi h he bes fi .
(B.1.5) The e a e o he ou lie s, o en ela ed o bad wea he condi-
ions, co e s ikes by ai - affic con olle s, o e en he
opening o new ai e minals like Te minal T4 a Mad id-
Ba ajas ai po (LST4). These ha e all been de ec ed by s a is-
ical ools. The p ocedu e o sea ch o such ou lie s consis s o
selec ing he esiduals ou side ou imes s anda d de ia ion
and including hem as po en ial candida es in he models unde
diffe en specifica ions (see he me hodological sec ion below).
The ou lie s a e included in final models wi h he specifica ion
ha p o ides he bes fi when hey a e s a is ically significan .
(B.2) Economic ac i i y: The li e a u e a gues ha economic ac i i y is closely
linked o ai affic as a esul o which i is gene ally included as an
indica o when modelling ai affic (see Inglada and Rey, 2004). In his
a icle, economic ac i i y is ep esen ed using a Spanish Minis y o he
Economy and T easu y syn he ic economic ac i i y index (sou ce:
h p://se iciosweb.meh.es/apps/dgpe/de aul .aspx).
(C) The Ryanai indi ec effec : This effec has been spli in o wo e ms o es ing:
(i) one cons an o he pe iods when Ryanai was ope a ing a each ai po ,
Jou nal o T anspo Economics and Policy Volume 46, Pa 2
268
measu ing he shock i p oduces (called ‘Ryan Shock’ a e wa ds); and (ii) mean
co ec ed Ryanai affic, measu ing how he dynamics o Ryanai affic affec
he o e all dynamics a a gi en ai po and any possible lags o his a iable
(‘Ryan Dynamic’). The e we e ou cases (Gi ona, Reus, Mu cia, and San ande )
whe e he p e ious p ocedu e had o be efined in o de o find app op ia e
models. Ryanai has a dominan posi ion a hese ou ai po s ha would explain
he s uc u al changes ha ha e been de ec ed a e Ryanai commenced ope a-
ions, esul ing in he need o special ea men in hese cases (see de ails below).
The ime se ies models employed in he analysis a e in he class o disc e e ime linea
T ans e Func ion models (see Cas illo-Manzano e al., 2010, o an analysis o he
ad an ages o his me hodology on anspo a ion esea ch s udies). The gene al o mu-
la ion may be exp essed as in equa ion (2):
yi; ¼X
h
j¼1
oni;jBðÞ
dmi;jBðÞ
ui;j; þNiBðÞei; ;ð2Þ
whe e yi; a e he ai passenge o al da a o he i h ai po excluding he Ryanai
passenge s; ui;j; a e he inpu s on which he ou pu da a depend (mos o hem de e -
minis ic, wi h he sole excep ions o he economic cycle and pa o he Ryanai indi ec
effec , see he lis abo e); ei; is a ze o mean and cons an a iance Gaussian whi e noise;
oni;jðBÞ¼ðoi;0þoi;1Bþþoni;jBni;jÞðj¼1;...;hÞa e polynomials in he backshi
ope a o ( ha is, Bky ¼y k) ha may ha e leading ze o coefficien s when a pu e
ime delay is necessa y; and dmi;jðBÞ¼ð1þdi;1Bþþdmi;jBmi;jÞðj¼1;...;hÞa e
s a iona y o s able polynomials.
I is impo an o include a specific commen on he Ryanai inpu a iables in o-
duced in equa ion (2). B oadly speaking, he inpu a iables linked o he Ryanai
indi ec effec a e: (i) ‘Ryan Shock’: one s ep a iables wi h ze os be o e Ryanai
commenced ope a ion, and ones a e he company had commenced ope a ion; and (ii)
‘Ryan Dynamic’: Ryanai affic minus i s mean le el du ing he pe iod o ope a ion.
Howe e , al hough his would be he gene al way ha he ai po s a e ea ed, he e a e
ou ai po s ha beha e in a special way gi en he dominan ole played by Ryanai in
hei affic. These a e he a o emen ioned cases o Gi ona, Reus, Mu cia, and
San ande . As such, he s anda d me hod used o handling he Ryanai indi ec effec
by di iding i in o ‘Ryan Shock’ and ‘Ryan Dynamic’, as in he cases shown in Table 1,
was inadequa e o hese ou ai po s. By way o example, Figu e 2 shows he special
case o Gi ona and compa es a iable yi; ( ha is, he o al numbe o passenge s
excluding Ryanai ) wi h Ryanai affic a Gi ona ai po (whe e Ryanai commenced
ope a ions in Decembe 2002).
I is clea ha he o al effec o Ryanai is eno mous in his case, since, o pu i in
simple e ms, Ryanai affic is g ea e han all he o he fligh s oge he and is on he
inc ease. The impo ance o Ryanai a Gi ona e en affec s he dynamics o he affic
he e as, a e Ryanai s a ed o ope a e in Gi ona, he endency ha was seen was o
numbe s o non-Ryanai passenge s o dec ease du ing summe (peaks), while hey
ended o inc ease du ing win e ( oughs). This sugges s ha Ryanai fligh s ha e
diffe en and opposing effec s in win e and in summe (al hough i will be shown below
How Can he Effec s o he In oduc ion o a New Ai line be Measu ed? Cas illo-Manzano e al.
269
Table 1
Es ima ion Resul s o Uni a ia e Models wi h In e en ion Va iables
Mad id-Ba ajas Alican e Valencia Ma
´laga Palma de Majo ca Se ille
Eas e
Business
Leap
9/11
Cycle
0.032
0.021
0.056
(20)
1.845
0.035
0.003
0.044
0.044
(13)
1.732
0.071
(20)
1.966B
0.052
0.007
0.035
0.052
(19)
1.168
0.088
0.005
0.077
(14)
2.109B
0.118
(28)
2.523B
4
Ryan Shock
Ryan Dynamic 0.158
0.119 0.0350.079
0.0360.048–0.061B
0.014B
3
0.085–0.087B 0.077B
AO97JUN
AO97DEC
AO98APR
AO98JUN
AO99NOV
AO99DEC
AO00MAR
LS03JAN
AO03MAY
LST4
LS08NOV
0.062
0.048
0.058
0.044
0.044
0.041
0.092
0.165 0.063
0.037
0.065
0.135
0.061
0.172
MA1
MA2
MA12
MA24
0.202
0.474
0.666
0.392
0.240
0.312
0.294
0.559 0.568 0.152
0.192
0.463
s20.468 0.797 2.282 0.787 1.855 1.897
Q(12)
Q(24)
Be a-Ja que
4.432
15.062
5.805
(0.054)
19.142
27.949
0.428
(0.807)
3.775
9.094
1.277
(0.528)
12.281
28.466
0.3077
(0.857)
19.577
33.701
0.0042
(0.997)
10.935
22.001
0.332
(0.847)
No e: Significan a 10 pe cen , 5 pe cen , and 1 pe cen le els, espec i ely. s2s ands o he inno a ions a iance; Q(12) a e he Ljung–Box Q
s a is ics o 12, espec i ely; Be a-Ja que is a no mali y es (P- alues in b acke s); His a a iance a io homoscedas ici y es (P- alues in b acke s). The
numbe o mon hs ha he 9/11 effec las ed is gi en in b acke s a e he coefficien o he a iable.
Jou nal o T anspo Economics and Policy Volume 46, Pa 2
270
ha he summe effec is in ac insignifican , since i would seem ha he summe
declines had s a ed be o e Ryanai commenced ope a ions a he ai po — see Table 2).
Fo his eason, win e and summe a e es ima ed as sepa a e effec s in he model (see
new a iables Sum## and Win## in Table 2, whe e ‘##’ s ands o he las wo digi s o
he yea ).
T affic a Reus ai po was seen o ollow a simila beha iou , pe haps due o he
ac ha be o e Ryanai a i ed a hese ai po s, bo h we e only used du ing he
summe season (mainly as ope a ing bases o cha e fligh s o he Ca alonian coas ).
Simila ly, he egional ai po s in Mu cia and San ande also ha e o add ess
Ryanai ’s dominan posi ion, as a esul o which he Ryanai indi ec effec has had o
be adap ed o he s uc u al changes p oduced by he company a e i s a i al. Specifi-
cally, he Ryanai indi ec effec a bo h o hese ai po s was di ided in o se e al
empi ically iden ified s eps (see Table 2, ou h column, hi d ow). Specifically, o
Mu cia ai po h ee diffe en s eps we e ound (Feb ua y 2005 o Feb ua y 2007,
Ma ch 2007 o Oc obe 2007, and No embe 2007 onwa ds), while a San ande ai po ,
only wo s eps we e needed (Ma ch 2005 o Feb ua y 2007 and Ma ch 2007 onwa ds).
To summa ise, he Ryanai indi ec effec (Hi; ) would be he addi ion o he T ans e
Func ion e ms in (2) ha ha e links wi h he Ryanai a iables. In mos cases i will be
jus wo e ms, he shock and he dynamic effec s (‘Ryan Shock’ and ‘Ryan Dynamic’ as
defined abo e and shown in Table 1), ha is:
Hi; ¼X
n
j2Ryanai
oni;jBðÞ
dmi;jBðÞ
ui;j; :ð3Þ
The gene al ep esen a ion o he noise model NiBðÞei; in (2) is an ARIMA pi;di;qi
ðÞ
Pi;Di;Qi
ðÞ
12 o mula ion shown in equa ion (4):
NiBðÞei; ¼1
1BðÞ
di1B12
ðÞ
Di
#qiBðÞ
piBðÞ
QiB12

PiB12
ðÞ
ei; :ð4Þ
Figu e 2
Million Passenge s (Pe Mon h) a Gi ona Ai po
1996 1998 2000 2002 2004 2006 2008
0
0.1
0.2
0.3
0.4
0.5
Million passenge s
Passenge s a Gi ona ai po
Ryanai
y
i,
How Can he Effec s o he In oduc ion o a New Ai line be Measu ed? Cas illo-Manzano e al.
271
cha e fligh s o he Ca alonian coas (83.7 pe cen o fligh s a Gi ona and 92.2 pe
cen a Reus we e cha e fligh s in 2002, be o e he a i al o Ryanai a Gi ona in
Decembe o ha same yea ).
The la ge nega i e indi ec effec a Reus o almos 29 pe cen mus be highligh ed.
This is a clea example o he incompa ibili y o he Ryanai model wi h o he ai lines
which, he e o e, inc eases he dependence o he ecei ing ai po on said company.
This esul is especially ele an i i is aken in o accoun ha Ryanai has commenced
ope a ions a Ba celona, which aises se ious ques ions abou he u u e o affic a
Gi ona and Reus.6
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