2. METHODOLOGICAL BASE

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1 Uluslararası Sosyal Araşırmalar Dergisi The Journal of Inernaional Social Research Cil: 10 Sayı: 49 Volume: 10 Issue: 49 Nisan 2017 April Issn: A NEW LOOK AT THE RELATIONSHIP BETWEEN AVIATION DEMAND AND ECONOMIC GROWTH: STRUCTURAL MODEL ESTIMATION FOR THE CASE OF TURKEY Nisa SEÇİLMİŞ * Leven KORAP ** Absrac This sudy aims o consider he relaionship beween aviaion demand and economic growh in an empirical way. For his purpose, he Turkish daa are used in ligh of he advances in ime series esimaion echniques. The resuls reveal ha coinegraion beween he variables canno be rejeced. Aviaion demand is found like a luxury good and economic growh end o ac as a consrain on demand condiions. Furher, a posiive real income shock in a srucural vecor error correcion framework leads nearly one-o-one significan response in aviaion demand. The forecas error variance decomposiion findings give suppor o hese resuls. Keywords: Economic Growh, Aviaion Demand, SVEC, Impulse-Response Funcion, Granger Causaliy, Variance Decomposiion, VAR. 1. INTRODUCTION An imporan aspec of economic growh is he increasing demand for services. The ransporaion secor, in his sense, fulfills one of he needs mosly required by economic agens. Such a endency also validaes for Turkey as a developing counry. The main rends in he aviaion secor indicae a huge volume of ransacions mainly due o he high qualiy, securiy and fasness of hese services. Especially, for he pos period, his is an explici sylized fac winessed by he Turkish economy. For insance, he number of aircrafs increased by %233, sea capaciy rose by % 264, cargo capaciy pushed up by %502, and he number of flying desinaions reached o 341 (Direcoae General of Civil Aviaion, 2016: 25). Figure 1 give some oher daa realizaions ha highligh his issue of ineres in recen years. Figure 1: Air Passenger Traffic in Turkey ( ) The figure above gives furher evidence wih respec o he fas developmen in his secor. I is easy o noice ha here has been an ever-increasing rend in oal air passenger raffic. As he sub-deerminans, boh he domesic and he inernaional flighs have a similar paern acing ogeher. Thus, his preliminary search provides us an insigh dealing wih he course of aviaion demand in Turkey. In he relaed lieraure, we see ha here exis a limied number of sudies ha examine he linkages beween aviaion and economic growh. Marazzo (2010) ess he relaionship beween aviaion demand and gross domesic produc (GDP) for Brazil. Using he daa from 1966 o 2006 in a vecor auoregressive (VAR) framework, a long-run equilibrium is found beween he wo variables and a uni-direcional causaliy running from GDP o aviaion demand is observed in a posiive manner. Thus, economic growh seems o reain valuable informaion o forecas air ranspor demand. Impulse-response funcions suppor hese findings in he sense ha aviaion demand reacs posiively o he change in GDP. Zhang and Zhu (2011) examine he relaion beween air ransporaion and GDP for he case of Chine beween The * Yrd. Doç. Dr., Gazianep Üniversiesi, Havacılık ve Uzay Bilimleri Fakülesi, nsecilmis@ganep.edu.r ** Yrd. Doç. Dr., Kasamonu Üniversesi, İkisadi ve İdari Bilimler Fakülesi, lkorap@kasamonu.edu.r

2 resuls obained from he ime series echniques and causaliy analyses indicae ha economic growh subsanially promoe he civil aviaion growh in he long-run. However, he developmen of civil aviaion has a caalyic role on economic growh. Likewise, Sun and Li (2011) carry ou an empirical analysis beween air ranspor indusry and economic growh in China for he period. There seems o be a srong correlaion beween hese indicaors, and economic growh has a significan role in improving he developmen of air ranspor indusry. Air passenger conribues more o economic growh han air cargo, bu a srucural change happens afer civil aviaion reform in 2002 ha leads air cargo o have a more prominen role on economic growh. Chi and Baek (2013) examine he shor- and long-run effecs of economic growh and some marke shocks on air passenger and freigh services for he case of US economy. The so-called marke shocks are represened by 9/11 erroris aacks, Iraq war, SARS epidemic and 2008 financial crisis. For he period in an auoregressive disribued lag (ARDL) framework of coinegraion, he sudy finds ha air passenger and freigh services end o increase wih economic growh in he long-run. Bu, in a shor-run perspecive, only air passenger service is responsive o economic growh. Mehmood e al. (2013) search for ineracions beween aviaion demand and economic growh for India by means of causaliy analyses, graphic mehods and variance decomposiion esimaes. Resuls from he period reveal a coinegraion relaionship beween aviaion demand and economic growh, and i is found ha economic growh reacs srongly o he shocks in aviaion demand. Hu e al. (2015) invesigae he domesic air passenger raffic and real economic growh in China by using heerogeneous panel models. For he period, hey find a unidirecional shor-run causaliy from air passenger raffic o real economic growh, bu a reverse causaliy canno be observed. Coinegraion beween hese indicaors canno be rejeced. There are also regional sudies on his subjec such as Baker e al. (2015). They examine he relaion beween regional air ransporaion and economic growh by using 88 airpors daa in Ausralia and find a srong muual relaion beween hese indicaors. Our paper aims o implemen his ask in ligh of conemporaneous ime series esimaion echniques. The ouline of he paper can be summarized as follows. The nex secion deals wih some mehodological issues used for esimaion purposes. Secion 3 inroduces he daa and quesions he validiy of saionary relaionships beween he variables. Based on hese findings, some causaliy analyses are carried ou in secion 4. Secion 5 is devoed o he dynamic naure of he model and repors briefly he srucural vecor error correcion (SVEC) innovaion accouning esimaes. Secion 6 summarizes he resuls and concludes he paper. 2. METHODOLOGICAL BASE The sudy ries o uilize he sysem approach of Johansen (1995) wih he maximum likelihood esimaion o see he rank condiion of he model. In his procedure, i is searched for a long-run coefficien marix of a reduced rank r > k, and k r marices and β wih rank r are examined such ha Π = β. y β is a ( 0) Here, I process where y is endogenous variable vecor in a VAR model, β coinegraing vecor(s), and adjusmen parameer(s) wih respec o a disurbance in he saionary equilibrium relaionship. The coinegraing vecors are esimaed by using wo likelihood es saisics known as maximum eigenvalue for he null hypohesis of r versus he alernaive of r + 1 and race for he null hypohesis of r agains he alernaive of n coinegraing relaions, for r = 0,1,, n 1 where n is he number of endogenous variables. This approach enables he researcher o examine wheher here exis a single or more coinegraed vecor in he long-run variable space and yields informaion abou he model based exogeneiy properies of he variables wih increased asympoic properies. Having considered he coinegraion relaionship, a SVEC model is employed o reveal he dynamic srucure of he daa. To fulfill such a purpose, he ineracions beween he variables are designed in line wih he SVEC impulse response funcions. This ask requires idenificaion of he economic relaionships as shocks raced in srucural impulse responses and is carried ou by resricing he esimaed covariance marix in he VAR process. Some resricions need o be imposed on he C (1) marix of long-run effecs of shocks and he non-singular B marix of conemporaneous effecs of shocks. The reduced form disurbances and srucural innovaions u are associaed wih each oher such ha u = B wih he marix of longrun effecs of he u residuals. 1 p 1 ( ) ( ( I ) ) 1 m i= 1 i ' ' ' ' C (1) = β Ψ β = β Γ β (1) ' Where and β are orhogonal complemens of and β, respecively: = = 0 and Ψ is he mean lag marix of he VAR represenaion. If coinegraion rank r = 0 ' ββ, his model specificaion is

3 reduced o 1 C (1) = Ψ, whereas if Π marix is of full rank when r = n, where n is he number of endogenous variables, all elemens in y endogenous variable vecor would be saionary in heir levels and hus C (1) is a null marix. Wha is imporan here is he idenificaion of he srucural model o discern he effecs of shocks from each oher ha requires o esimae srucural innovaions. The relaionship beween he ' variances of reduced form residuals and he srucural innovaions yields ha B B = Ω, which imposes n( n + 1) / 2 independen resricions on B. The orhogonaliy assumpion for he srucural shocks requires n( n 1) / 2 addiional zero resricions o he off-diagonal elemens for exac idenificaion. 3. TESTING FOR COINTEGRATION The sample period for model consrucion is chosen as wih annual frequency of he daa. The aviaion demand is represened by he variable P A X which includes he knowledge of passengers carried in air ranspor. The oher variable G D P is used for economic growh, and for his purpose, he GDP daa wih consan 2005 US$s are considered. Boh daa are in heir naural logarihms and aken from he elecronic daa delivery sysem of he World Developmen Indicaors published by World Bank (hp://daa.worldbank.org/). Due o he crisis-prone naure of he Turkish economy wihin he sample, some dummies are creaed for he slump periods of he economy. These dummies ener he model in an unresriced way no o have a long-run effec ha is endogenous o he sysem. 1, [1994] 1, [1999] 1, [2001] 1, [2009] d94 =, d99 =, d01 =, d09 = 0, oherwise 0, oherwise 0, oherwise 0, oherwise Then, some uni roo ess are employed. The resuls from preliminary Augmened Dickey-Fuller / ADF (1981) uni roo es and Perron (1997) uni roo es wih single endogenously deermined break dae in Table 1 give no evidence of saionariy in he level form. Boh ess assume he null hypohesis of a uni roo for he esimaion process. Following he recommendaion of Ng and Perron (2001), he choice of opimum lag in uni roo analyses was decided on he basis of minimizing a modified version of he Schwarz informaion crierion. Table 1: Uni Roo Tess ADF (1981) es P A X G DP Inercep inercep&rend inercep inercep&rend level differenced % CV Perron (1997) es Model A Model B Model C (break in inercep) (break in rend) (break in inercep & rend) P A X G DP % CV For he lag lengh of unresriced VAR model, various model selecion informaion crierions are examined. Wih he maximum lag selecion 4, he sequenial modified LR saisics and minimized Schwarz (SC) and Hannan-Quinn (HQ) informaion saisics sugges o use lag order 1, while Akaike informaion crierion (AIC) and final predicion error (FPE) saisics minimize wih lag order 2. In his paper, we choose o follow SC crierion o consruc he dynamics of he model. Given hese bases for he VAR model, he coinegraion relaionship is esimaed. For his purpose, a firs, he daa rend and es ype specificaions are examined. We obain no coinegraed relaionship when a linear or quadraic daa rend is assumed. Thus, he model is esimaed wih inercep and no rend resriced as he es ype in he long-run variable space. The rank es resuls wih 5% CVs and he coinegraion saisics are given in Table 2. CVs are aken from Oserwald-Lenum (1992) and use p-values from MacKinnon e al. (1999). From he able, he exisence of a mos one coinegraing relaionship canno be rejeced by boh rank saisics. The adjusmen coefficiens indicae real income has a weakly exogenous characerisic as a forcing variable, so he normalizaion is carried ou upon he variable P A X o give he esimaed equaion economic meaning. The long-run relaionship beween he variables is repored in Eq. 1 wih asympoic saisisics beneah he coefficiens

4 Table 2: Coinegraion Resuls (p-values in parenheses) Daa rend and es ype: No deerminisic rend & resriced consan H 0 Eigenvalue Trace es 0.05 CV Max-eigen es 0.05 CV r = (0.00) (0.00) (0.00) r (0.07) 8.73 (0.07) 9.16 (0.07) Unresriced coinegraing coefficiens P A X G DP C Unresriced adjusmen coefficiens D( P A X ) D( G DP ) Coinegraing equaion (sandard error in parenheses) P A X G DP C (0.58) (22.10) Adjusmen coeficiens (sandard error in parenheses) D( P A X ) (0.02) D( G DP ) (0.02) β y = P A X * G D P (2) ( ) ( ) There exiss a posiive relaionship beween aviaion demand and real income, and a 1% increase in real income leads nearly o a 2.7% increase in air passenger carried in ransporaion secor. This means ha aviaion demand is considered by economic agens like a luxury good. Addiionally, 6% of he adjusmen in aviaion demand disequilibrium condiions o long-run equilibrium is realized wihin one period. 4. THE SHORT- AND LONG-RUN CAUSALITY In his secion, he possible long-run causaliy relaionships are esed beween aviaion demand and real income. I is obvious ha coinegraion necessarily implies causaliy in a leas one direcion. For his purpose, briefly o sae, long-run causaliy capured by he significance of error correcing erm in he Johansen procedure has been examined such ha: n n n PAX = φ + γ GDP + η PAX + λ ECT + i i= 1 1i i i= 1 1i i i= 1 1i 1 1 n n n GDP = φ + γ PAX + η GDP + λ ECT + i i= 1 2i i i= 1 2i i i= 1 2i 1 2 For he dynamic srucure of causaliy es, i is assumed ha η = 1 for he order of auoregressive model similar o he coinegraion analysis. ECTs sand for he error correcion erm aken from he longrun coinegraing space. Error correcion mechanism included in he auoregressive models gives some addiional knowledge of causal relaions beween he variables which allow o disinguish shor- and longrun causaliy from each oher. The W ald or F ess applied o he join significance of he sum of he lags of each explanaory variable and he ess of he lagged error correcion erms highligh us for he knowledge of Granger exogeneiy or endogeneiy of each dependen variable in a saisical sense. If he dependen variables can be driven by he error erm yielded in he saionary coinegraing vecor, his implies he exisence of a long-run causal relaionship. Such a finding would mean ha he variable considered has no been found weakly exogenous wih respec o he saionary coinegraing variable space. This can be done by esing H : 0 0 λ i = hrough he ess of he lagged error correcing erms. If he nonsignificance of he error correcion is acceped, his means ha he dependen variable responds only o shor-erm shocks o he sochasic environmen. In his sense, he rejecion of he non-significance of he differenced explanaory variables will be referred o as shor-erm causaliy. This can be done by esing he null hypohesis of he non-significance of γi or η i in a saisical sense. Finally, we es joinly he nonsignificance of all he explanaory variables including boh he differenced variables and he lagged error correcing erm for he absence of Granger causaliy, called as srong exogeneiy of he dependen variable. The resuls are given in Table 3. (3)

5 Table 3: Granger Causaliy Analysis F ype Wald Tess in a VEC Form (Probs. in parenheses) _Dep. Var. Shor run dynamics H0: here is no causal relaion (source of causaion is independen variables) P A X G D P EC T P A X (0.05) 3.86 (0.02) G D P 0.76 (0.59) (0.33) Join ess of boh shor run dynamics and ECT Dep. Var. H0: here is no causal relaion (source of causaion is independen variables) P A X G D P and EC T 3.00 (0.04) G D P P A X and EC T 1.12 (0.42) Our findings imply ha here exiss a unidirecional causaliy beween changes in aviaion demand and real income growh, and real income growh is a Granger-cause of he changes in aviaion demand. However, we canno rejec he he null hypohesis of no Granger causaliy from real income growh o aviaion demand. The inclusion of coinegraing knowledge derived from error correcing erm makes no difference in our resuls. Thus, i is possible o infer ha changes in economic growh end o ac as a consrain on aviaion demand. 5. SVEC ANALYSIS Given he long-run naure of he model, in his sub-secion, only he shor-run srucure of a dynamic form is esed o idenify he sysem wih conemporaneous resricions. For his purpose, i is benefied from he exogeneiy properies of he coinegraion model. Due o he weakly exogenous characerisic of he real income variable, no conemporaneous impac of he variable P A X is allowed on he variable G DP. This resricion leads o exac idenificaion of he srucural VAR in a coinegraing framework. Boosrap sandard errors are given in parenheses. Table 4: SVEC Model Shor Run Idenificaion Esimaed B marix / Srucural VAR is jus idenified (SEs in parenheses) Maximum likelihood mehod using Amisano and Giannini (1997) scoring algorihm. Conemporaneous zero resricions o he off-diagonal elemens [ n ( n 1 ) / 2 = 1 ] PAX GDP P A X (0.5656) (0.4297) G DP (0.6304) I is seen ha an immediae ( P A X ) shock is resuled significanly in a posiive response upon iself (of a value ). Likewise, he variable G D P reacs posiively o own G D P shock in a significan way (of a value ). Wha is more imporan a his poin is he dynamic ineracion beween boh variables. A posiive 1% real income shock leads nearly one-o-one significan response (of a value ) in variable P A X. Le us now relae hese saisics o he graphs obained from he impulse response of he srucural shocks using 95% Hall percenile confidence inervals and 2000 boosrap replicaions wihin a horizon of 5 year. The verical axis in Figure 2 below gives he magniude of he impulse response shocks, while he horizonal axis is he ime period forecased in annual basis. For he diagram (a), he confidence inervals have he same sign ha recalls saisical significance nearly 2 years following he shock, while in diagram (b) his emerges nearly 2½ years laer han he occurance of he relaed shock. These resuls clearly are in andem wih he coinegraion findings obained in he earlier secions. Finally, he SVEC forecas error variance decomposiions are presened in Table

6 Figure 2: SVEC Impulse Response Funcions (a) Response of P A X o G DP (b) Response of G DP o P A X The resuls indicae ha he larger he sample period in he esimaion process he higher he proporion of forecas error of aviaion demand explained by real income. Indeed, for a forecas horizon of 20 years, he forecas error of he variable P A X accouned by real income is explained more by he variable G DP (of a value 0.54). However, proporions of forecas error in he variable G DP is explained o a much larger exen by iself. The SVEC forecas error variance decomposiion findings suppor he exogeneiy characerisic of he real income variable and he endogeneiy characerisic of he aviaion demand wih respec o he real income for he empirical model considered in his paper. Table 5: SVEC Forecas Error Variance Decomposiions Proporions of forecas error in P A X accouned for by Forecas horizon P A X G DP Proporions of forecas error in G DP accouned for by Forecas horizon P A X G DP CONCLUDING REMARKS Since he 1980s, airline indusry has grown dramaically in worldwide. Wih is various exensions, such as airlines, airpors, ground handling services, aircraf manufacurers, he air ranspor secor has an imporan place in naional economies. Aviaion demand form he basis for invesmen decisions and allow he roaion of he wheel of he aviaion indusry. There are limied numbers of sudies searching for he relaionship beween passenger demand and real income especially for emerging marke economies. This paper aims o conribue o his srand of lieraure by conducing an empirical model for he case of he Turkish economy. Our resuls reveal ha coinegraion beween aviaion demand and real income canno be rejeced and ha real income is found weakly exogenous wihin he esimaion process. For he sample period, aviaion demand seems o be considered like a luxury good by economic agens. Then, some causaliy analyses are performed by also using he saionary knowledge aken from he coinegraing vecor. A unidirecional causaliy is found in he sense ha real income growh is a Granger-cause of he changes in aviaion demand. This means ha economic growh is able o ac as a consrain on aviaion demand. Finally, he innovaion accouning mehods used for he dynamic naure of he model esimae ha a posiive real income shock leads nearly o one-o-one significan response in aviaion demand. The forecas error variance decomposiion findings give suppor o all hese esimaion resuls. REFERENCES AMISANO, G. and GIANNINI, C. (1997). Topics in Srucural VAR Economerics, 2 nd ed., Berlin: Springer-Verlag. BAKER, D., MERKER, R. and KAMRUZZAMAN, M. (2015). Regional aviaion and economic growh: coinegraion and causaliy analysis in Ausralia, Journal of Transpor Geography, 43, pp CHI, J. and BAEK, J. (2013). Dynamic relaionship beween air ranspor demand and economic growh in he Unied Saes: a new look, Transpor Policy, 29, pp DICKEY, D.A. and FULLER, W.A. (1981) Likelihood raio saisics for auoregressive ime series wih a uni roo, Economerica, 49, pp Direcoae General of Civil Aviaion (DGCA) (2014). Aciviy Repor 2016, Turkey

7 HU, Y., XIAO, J., DENG, Y., XIAO, Y. and SHOUYANG, W. (2015). Domesic air passenger raffic and economic growh in China: evidence from heerogeneous panel models, Journal of Air Transpor Managemen, 42, pp hp://daa.worldbank.org/, access daa: JOHANSEN, S. (1995) Likelihood-based inference in coinegraed vecor auoregressive models, Oxford: Oxford Universiy Press. MACKINNON, J.G., HAUG, A.A. and MICHELIS, L. (1999). Numerical disribuion funcions of likelihood raio ess for coinegraion, Journal of Applied Economerics, 14, pp MARAZZO, M., SCHERRE, R. and FERNANDES, E. (2010). Air ranspor demand and economic growh in Brazil: a ime series analysis, Transporaion Research Par E, 46, pp MEHMOOD, B., SHAHID, A. and YOUNAS, I. (2013). Inerdepencies beween aviaion demand and economic growh in India, Economic Affairs, 58(4), pp NG, S. and PERRON, P. (2001). Lag lengh selecion and he consrucion of uni roo ess wih good size and power, Economerica, 69(6), pp OSTERWALD-LENUM, M. (1992). A noe wih quaniles of he asympoic disribuion of he maximum likelihood coinegraion rank es saisics, Oxford Bullein of Economics and Saisics, 54, pp PERRON, P. (1997) Furher evidence on breaking funcions in macroeconomic variables, Journal of Economerics, 80, pp SUN, S. and LI, Y. (2011). An empirical analysis on influence of air ranspor developmen o Chinese economic growh. Paper Presened a he Inernaional Conference on E-Business and E-Governmen ICEE, China: Shanghai, 6-8 May 2011, pp ZHANG, H.-Y. and ZHU, M.-G. (2011). An empirical research on he relaion beween he air ransporaion and economic growh. Paper Presened a he Inernaional Conference on Managemen Science & Engineering 18 h Annual Conference Proceedings, Rome: Ialy, Sepember 2011, pp