DEMAND PULL AND SUPPLY PUSH

Transcription

1 DEMAND PULL AND SUPPLY PUSH IN PORTUGUESE CABLE TELEVISION NETWORKS: A VAR APPROACH JOÃO LEITÃO * Universidade da Beira Inerior (UBI) Dearameno de Gesão e Economia (DGE) Covilhã, Porugal Absrac In his aer a Vecor Auoregressive Model is alied o he mos reresenaive Poruguese cable elevision oeraors, in order o obain a dynamic analysis of he ineraciviy esablished beween he suly and he demand of nework services, hrough he sraegy of verical inegraion of services. The resuls reveal he exisence of wo driving forces in he Poruguese main cable neworks, on he one hand, he suly ush which conribues o he enhancemen of he basic cable demand, and on he oher hand, he demand ull which inensifies he inroducion of new verically inegraed services. In he wo case sudies, i is also deeced ha verical inegraion of services has a negaive imac on he rice of he basic cable elevision service. Key Words: Cable Television, Vecor Auoregressive Model, Coinegraion. JEL: C32, C5, L96. * Mailing address: Universidade da Beira Inerior, Pólo das Ciências Sociais e Humanas, Dearameno de Gesão e Economia, Covilhã, Porugal. jleiao@fenix.ubi.. The auhor is graeful o Carlos Osório (UBI - Porugal), José R. Pires Manso (UBI - Porugal), José Ricardo B. Nogueira (UFPE Brazil), José Luis Miralles Marcelo (UNEX - Sain), and José Luis Miralles Quirós (UNEX - Sain) for helful commens on revious versions of his aer. A secial deb of graiude is due o Carlos Osório and José Luis Miralles Marcelo for he osiive incenives and consrucive commens on he iniial draf. The usual cavea alies.

2 DEMAND PULL AND SUPPLY PUSH IN PORTUGUESE CABLE TELEVISION NETWORKS: A VAR APPROACH. INTRODUCTION Wih he emerging of he oen nework aradigm, i is execed ha he sraegies of he cable elevision oeraors will be guided by he dynamics of he ineraciviy beween he suly and he demand of nework services, romoed by he verical inegraion of services, which embraces he inegraion of differen and comlemenary funcions, on he same disribuion nework. In his aer an economeric sudy of he main Poruguese cable elevision neworks is resened, in order o beer undersand he ineraciviy of he suly and he demand of nework services, obained hrough he imlemenaion of he verical inegraion of services sraegy. To his effec, wo cases are confroned (he incumben one: TV Cabo; and he enran one: Cabovisão), in order o analyse he relaions beween he eneraion rae of he cable elevision service, he demand for he basic service, he rice, and he verical inegraion of services. The same model is used for idenifying he facors ha conribue o he reinforcemen of he ineraciviy logic beween he suly and he demand of nework services, boh in a bigger dimension nework (he incumben one), and in a smaller dimension nework (he enran one). In addiion o his, an analysis of he imac of he sraegy of verical inegraion of services on he ricing of he basic cable elevision service is made. In he firs secion, a brief lieraure review abou some emirical sudies of Cable Television in he USA is made, and a summary review of he lieraure relaing o he economeric insrumen used in boh case sudies, he Vecor Auoregressive (VAR) model; is also made. In he second secion, he mehodology, he objecives, he hyoheses in his sudy, and he secificaions of he seleced model, are resened. In he hird secion, he economeric sudy is develoed, following an emirical sraegy which conemlaes he develomen of hree sequenial hases, namely, he deerminaion of he inegraion order of he variables, he definiion and he esimaion of he VAR model, and he resenaion of he main resuls of he dynamic analysis. Finally, he conclusions are resened, aking ino consideraion a comaraive analysis beween he resuls obained for he incumben, and for he enran. 2

3 2. LITERATURE REVIEW 2.. EMPIRICAL STUDIES The roblemaic regarding he esimaion of he eneraion rae of he basic cable elevision service was develoed in he ioneer sudies of Comanor and Michel (97), Park (972), and Pacey (985), alied o he main cable elevision oeraors in he USA. These sudies oined ou ha he rice influences, significanly, he basic demand, and ha he number and he qualiy of he channels offered also influences, osiively, he demand level. These findings formed he basis of he carrying ou of sudies concerning he relaion beween he demand and he rice, as well as of he imac of he regulaory disosiions on he rice of his kind of service. In his conex, he sudy of Mayo and Osuka (99) mus be noed, concerning he US Cable Television Indusry, where he relaions beween demand, rice, and regulaory racice, are analysed, before he deregulaion 2. The auhors of ha sudy concluded ha he ricing of he basic cable elevision service deends on oeraor marke ower, demand condiions (including he comlemenariies beween he basic and he remium service) and on associaed regulaory disosiions. The resuls also revealed he exisence of some variabiliy in he effecs on he alernaive ways of regulaing he rice of he basic service, which led o he conclusion ha his rice was influenced no only by he marginal cos, and he demand condiions of he remium services, bu also by he comlemenariies beween he basic and he remium services. In order o accomlish he rice ca esablished by he regulaory agency, he oeraors resonded wih a reducion of he variey of he elevision channels or wih an increase in he rice of he remium services which were ied o he basic service (Mayo and Osuka, 99). Waerman and Weiss (997) oined ou he imlicaions of he siuaion of verical inegraion by he four main US cable oeraors on erformance, on rice, and on romoion sraegies. This effec resecs he radiional Demand Law, which saes ha: for an increase in he rice corresonds a decrease in he demanded quaniy. 2 In he USA, he subscriion rices were deregulaed in The Cable Ac of 984; hey were re-regulaed in he Cable Ac of 992, and hey became again deregulaed wih he adoion of he Telecommunicaions Ac of

4 The main resuls revealed ha verically inegraed oeraors offered a smaller diversiy of elevision channels, in erms of he basic service. These kinds of oeraors also favoured he remium elevision channels, in which hey had ariciaed. In his sense, hey have included frequenly he referred channels in he offering of remium cable channels, and also have imlemened more aggressive romoional camaigns, which were comlemened by he racice of discoun rices for he remium channels ha were verically inegraed by he cable oeraor (Waerman and Weiss, 997). Chiy (200) found ha he cable oeraors verically inegraed wih remium elevision channels 3 offered, on average, one less remium service, and one or wo fewer basic services han he remaining oeraors. These oeraors sell he remium ackages more successfully, bu hey offer services wih smaller diversiy, a higher rices. They simulae he demand for remium services, hrough he suly of smaller and cheaer basic ackages. The oeraors inegraed wih he basic channels 4 sell he basic ackages more successfully, and in sie of heir endency for excluding cerain cable elevision services from heir disribuion neworks, hey simulae he demand hrough he suly of some basic ackages wih a bigger diversiy, using a smaller dulicaion of rograms and a greaer number of remium services. Furhermore, Chiy (200) considers ha he sign of he effec of he verical inegraion on rice is no clear, due o he fac ha he oeraors selec so much of he rice based uon he qualiy level of he final service offered o he consumers. On he one hand, he basic inegraion has a osiive effec on he basic rice, bu a negaive effec on he average rice of he remium services. On he oher hand, he remium inegraion has a negaive effec on he basic rice bu, even so, has a osiive effec on he average rice of he remium services. 3 Tha is, he remium oeraors. 4 Tha is, he basic oeraors. 4

5 2.2. VECTOR AUTOREGRESSIVE MODEL The VAR model 5 is esecially alied o he analysis of ime series and i has been used in an exensive way by several economiss, for analysing daa, forecasing and making saisical inference. In he vision of Sims (980), he VAR model ermis he deerminaion of he exisence of inerrelaions beween he se of endogenous variables included in he sysem. The main advanage of using his kind of model derives from he caaciy o analyze he dynamic resonse of he endogenous variables of he sysem, hrough he use of he analysis of Variance Decomosiion, and he Imulse-Resonse Funcions. The Variance Decomosiion of he forecas error, in erms of he comonens associaed wih he differen disurbances, rovides he idenificaion of he sources of he flucuaion of variables. The Imulse-Resonse Funcions inended as dynamic muliliers reveal he variaion of he endogenous variables, which is rovoked by a uniary imulse in random disurbances of he sysem (Ballabriga, 99; Wason, 994). In he ambi of he analysis of he long and shor erm economic relaions, several ioneer works should be menioned which discuss he coinegraion conce, namely, Granger (983), Granger and Weiss (983), and Engle and Granger (987). The consrucion of coinegraed models involves wo fundamenal ses, namely, he deerminaion of he coinegraion degree (ha is, he number of uni roos in he model), and he esimaion of he unknown arameers (Lükeohl, 999). 3. METHODOLOGY 3.. OBJECTIVES The Poruguese Cable Television Secor is an aroriae uni of analysis for making a conras beween he sraegies of he oeraors: incumben, versus enran; aking ino consideraion he coexisence of inegraed oeraors, and non inegraed oeraors, in erms of he hysical aciviies, and he simulaneous racice of verical inegraion of services. 5 For revisions abou he main develomens of he VAR Model, see Holz-Eakin, Newey and Rosen (988), Lükeohl (99, 2004), Banerjee, Dolado, Galbraih and Hendry (993), Hamilon, (994), Canova (995), Hendry (995), Johansen (995), Haanaka (996), Favero (2000), and Canova and Ciccarelli (2003). 5

6 In he scenario of verical inegraion of services erformed by each oeraor, which use ackage ie-in sales of differen nework services, for examle, elevision, Inerne, fixed elehone and oher comlemenary services which are echnologically-relaed. In his sense, we resen a dynamic analysis 6 of he imac on he sraegy of ricing for he basic service arising from he imlemenaion of he verical inegraion sraegy of services, boh for a verically-inegraed oeraor, and for an oeraor which is no verically- -inegraed. In a broad sense, he ineres of his sudy is, fundamenally, based on he fac ha he Cable Television Secor has a significan weigh in he Poruguese Services Communicaions Srucure, and he need for analyse he differen sraegies imlemened by he main cable elevision oeraors, in erms of he organizaion of aciviies, he insalled nework, and ricing. In a more secific sense, we will be analysing he dynamic relaion beween he eneraion rae of he cable elevision service and he basic demand, as well as he relaion beween he basic demand and he verical inegraion of services. Furhermore, we aim o undersand he effec due o he imlemenaion of he sraegy of verical inegraion of services on he rice of he basic service HYPOTHESES Taking ino consideraion he fac ha here is a mixure of elevision services offered in he Poruguese Cable Television Secor, Inerne and fixed elehone hrough bidirecional neworks, which may generae nework exernaliies, and incororaing he visions of Kaz and Shairo (985), Hayashi (992), Economides and Himmelberg (995) and Economides (996), in relaion o he roblem concerning he realized execaions, given he referred nework exernaliies, i ineress o idenify and clarify he exisence of dynamic and ineracive forces beween he suly and he demand, as was roosed, in heoreical erms, by Geroski (2003), as well as he resulan imlicaions, in erms of he verical inegraion of services and ricing sraegies, on he ar of he cable elevision oeraors. In he resen sudy, he following hyoheses are considered: - Hyohesis : The eneraion rae of cable elevision services resens a osiive relaion wih he rice of he basic service. 6 This analysis is obained hrough he alicaion of a VAR Model, which allows erforming an inerreaive analysis of he exernal shocks o he sysem. 6

7 - Hyohesis 2: The verical inegraion of services has a negaive effec on he rice of he basic service. - Hyohesis 3: The eneraion rae of cable elevision services has a osiive relaion wih basic demand. - Hyohesis 4: The basic demand inensifies he verical inegraion of services. - Hyohesis 5: The basic demand has a negaive relaion wih rice, in he bigger dimension nework. - Hyohesis 6: The basic demand has a osiive relaion wih rice, in he smaller dimension nework. 4. THE ECONOMETRIC STUDY In his iem, an economeric sudy 7 is develoed for he wo main cable elevision oeraors in Porugal, TV Cabo (since he s T: 995, unil he 3 rd T:2003) 8 and Cabovisão (from 4 h T: 996, unil 3 rd T:2003), using he same seleced VAR model. 4.. INTEGRATION ORDER OF THE VARIABLES An imoran subjec for using he VAR model is he analysis and evaluaion of he ime series used in he sudy, since he VAR model resuoses ha his series is saionary. Firs, we will evaluae if he ime series are inegraed or no, and, hen, if so, we will deermine he inegraion order of he variables, in order o find he bes way for making i saionary. 7 The daa was colleced from Auoridade Nacional de Comunicações (ANACOM). 8 For examle, he eriod beween he firs Trimeser of 995 and he hird Trimeser of 2003, is reresened by: s T: 995, ill he 3 rd T:2003). 7

8 To deermine he inegraion order of he variables, we will consider he ess roosed by Dickey and Fuller (979), which will esablish he secificaions of a model including an endogenous lagged variable, exressed by he following: Y ρ ε (.) Y Therefore, he following null hyohesis is esed: H ρ ρ, ρ (2.) 0 : 0 0 < This es can be made, using he saisic, or he following saisic: ˆ ρ ρ 0 S ˆ ρ N(0,) (3.) where ρˆ is he esimae of he ordinary leas square, for he arameer ρ ; and esimae of he sandard deviaion of ρˆ. S ρˆ is he According o Dickey and Fuller (979), o es he null hyohesis (of exisence of a uni roo), agains he alernaive hyohesis, hree differen models should be aken ino consideraion, namely: Y Y ρ ε (wihou consan, and wihou endency) (4.) Y Y µ ρ ε (wih consan, and wihou endency) (5.) Y Y µ β ρ ε (wih consan, and wih endency) (6.) In racice, he ess roosed by Dickey and Fuller (979) consis of he esimaion of he hree equaions reviously resened (4., 5., and 6.), hrough he use of he mehod of he Ordinary Leas Square (OLS), and of he realizaion of he foremenioned es of saisical significance ( H : ρ ). In an alernaive way, we may esimae he following equaions: Y 0 Y γ ε (7.) Y µ γ ε (8.) Y Y Y µ β γ ε (9.) where γ ρ ; in his case, he es of he null hyohesis H : ρ, is equivalen o he 0 es of he hyohesis H : γ 0. The alernaive hyohesis is exressed by H : γ 0. 0 < 8

9 An alernaive o he foremenioned DF ess is he use of he Augmened Dickey- -Fuller Tes (ADF), including a minimum number of lags in he deenden variable, in order o eliminae he ossible observance of error auocorrelaion. Marques (998) advocaes ha, during he firs hase of he ADF ess, we should follow he same logic as he simle DF ess, whereas, in he second hase, we should carry ou he ess of he null hyoheses. So, we consider he resuls obained hrough he esimaion of he hree following models: Y Y Y γ Y δ Y ε j j (0.) j δ j Y j ε (.) j µ γy µ β γy δ Y ε j j (2.) j In he DF ( γ ) ess and he ADF ( ) γ ess, he null hyohesis H : γ ρ 0, is 0 esed, agains he alernaive hyohesis H : γ 0. The non-rejecion of H 0, when γˆ is non < significan, leads o he conclusion ha he ime series is no saionary (ha is, inegraed), or ha i resens a uni roo. In order o secify he model which rovides he bes adjusmen, we make use of wo differen informaion crieria, ha is, he Akaike Informaion Crieria (AIC), and he Schwarz Bayesian Crieria (SBC), in order o selec he model which minimizes he values obained for he foremenioned crieria. For deecing error auocorrelaion, he LM es is used, and we also calculae he robabiliy of he Q saisic, originally, roosed by Ljung and Box (979), aking ino consideraion he correlograms generaed from he esimaion rocess. Nex, he resuls of he DF ess and he ADF ess alied o he variables of he case of TV Cabo are resened. 9

10 Table 2. The DF Tess and he ADF Tess, wih consan and wih endency, a a 5% significance level TV Cabo (b variable) Variable Noes: Observedδ DF Tess and ADF Tess Lags Criicalδ AIC SBC PQ(2) LM Tes b -2, ,5484-5,95-4,9848 0,50 [] The b variable is he rice of he basic cable elevision service. [2] The ime series ha is used here corresonds o he naural logarihm of he variable in sudy. [3] The number of lags included in he models, is he one which rovides he eliminaion of he error auocorrelaion. [4] The criical value was colleced from MacKinnon (996). LM0,777 LM40,4454 Since he observedδ, in module, is smaller han he corresonden criical value, in module, oo, so he H 0 is no rejeced, a a 5% significance level ( α ). From his, we can conclude ha he ime series ( b ) is inegraed, or ha i has a uni roo. Noes: Table 3. The DF Tess and he ADF Tess, wih consan and wihou endency, a a 5% significance level TV Cabo (en and bd variables) Variables DF Tess and ADF Tess Observed δ Lags Criical δ AIC SBC PQ(2) LM Tes en -2, ,9604-2,7764-2,545 0,504 bd -2,775-2,9540,4985,6346 0,848 LM0,526 LM40,0989 LM0,3304 LM40,4665 [] The en variable is he eneraion rae of he cable elevision service; and he bd is he variaion of he number of subscribers of he cable elevision service. [2], [3], and [4] are alied in a similar way. As he observedδ, in module, is smaller han he criical values, in module, so he H 0 is no rejeced, a a 5% significance level, from his we can conclude ha he ime series ( en ) and ( ) bd are also inegraed, or ha hey have a uni roo. The endogenous variables ha are going o be included in he VAR model, for he incumben oeraor, such as, he eneraion rae (en), he variaion of he demand for cable elevision (bd), and he rice of he basic service (b), are no saionary, or inegraed. The variables, in firs differences, are saionary, so he hree ime series, in sudy, are inegraed of order, or I(). In he case sudy of Cabovisão, he resuls obained from he rocess of deerminaion of he inegraion order of he variables, are ranscribed in he ables resened below. 0

11 Table 4. The DF Tess and he ADF Tess, wih consan and wih endency, a a 5% significance level Cabovisão (b variable) Variable DF Tess and ADF Tess Observed δ Lags Criical δ AIC SBC PQ(2) LM Tes b -2, ,5875-4,694-4,4754 0,2 LM0,2858 LM40,6529 In his case, he observedδ, in module, is smaller han he criical value, in module, so he H 0 is no rejeced, a a 5% significance level. From his, we can derive ha he ime series (b) is inegraed, or ha i has a uni roo. Table 5. The DF Tess and he ADF Tess, wih consan and wihou endency, a a 5% significance level Cabovisão (en and bd variables) DF Tess and ADF Tess Variables Observed δ Lags AIC SBC PQ(2) LM Tes Criical δ LM0,7856 en -0, ,9862-2,036 -,8366 0,35 LM40,8722 bd -2, ,9762 2,7557 2,857 0,837 LM0,7674 LM40,7288 Since he δ observed, in module, are smaller han he criical values, in module, so he H 0 is no rejeced, a a 5% significance level. From his, in he enran case, we can also derive ha he ime series (en, and bd), are inegraed, or ha hey have a uni roo. Therefore, he variables ha are going o be included in he VAR model alicable o he enran are no saionary, or inegraed. The variables, in firs differences, are also saionary. This find confirms ha he original series are I().

12 THE VAR MODEL Afer deermining he inegraion order of he variables, which reveal ha he oaliy of he variables is inegraed of order, we roceed o resen he VAR model ha is going o be esed. The VAR model is consiued by a sysem wih four equaions, including four endogenous variables, shown in he following way: k k k k u vis b bd en en Ω θ σ β α k k k k u vis b bd en bd Ω θ σ β α k k k k u vis b bd en b Ω θ σ β α k k k k u vis b bd en vis Ω θ σ β α (3.) where: en is he eneraion rae of he Cable Television Service or nework densiy, calculaed by he quoien beween he number of subscribers and he number of cabled households; bd is he variaion of he number of subscribers of he basic cable elevision service; b is he rice of he basic cable elevision service; vis is he dummy variable concerning he verical inegraion of services (equal o 0, if does no exis vis, and equal o, oherwise);,,k is he number of lags, aking k as he oimal number of lags ( max ); and is he corresonding rimeser Oimal Number of Lags Now, we roceed o he selecion of he oimal number of lags ( max ), considering he resuls of five differen informaion crierias, namely, he Likelihood Raio (LR), he Final Predicion Error (FPE), he Akaike Informaion Crieria (AIC), he Schwarz Bayesian Crieria (SBC), and he Hannan and Quinn Crieria (HQ). Firsly, we resen he resuls concerning o he case of TV Cabo.

13 Table 6. Selecion of he Oimal Number of Lags TV Cabo Lags LogL LR FPE AIC SBC HQ NA 7.25E * 6.75E-09* * * * E Legend: NA No Available; * I idenifies he oimal number of lags seleced by each informaion crieria. In order o deermine he exisence (or no) of error auocorrelaion, we resen he resuls of he LM ess, and he robabiliies of he Q saisic (PQ(2)) 9, and he robabiliies of he corresonding adjused value (PQ(2) Ad.). Table 7. Deecion of Error Auocorrelaion in he TV Cabo VAR Model Lags AIC SBC PQ(2) PQ(2) Ad. Tese LM -5,9975* -4,3649* 0,9994 0,8772 LM 0,2598 LM4 0, ,6593-3,2775 0,9986 0,8494 LM 0,0864 LM4 0,3000 Legend: * I idenifies he number of lags which rovides he minimizaion of he values of he informaion crierias: AIC and SBC. By he resuls of he ess for deecing an hyoheic error auocorrelaion, simulaing VAR models, wih and 2 lags, resecively, we found ha he VAR model should be esimaed, using jus lag, since his oion rovides he minimizaion of he values of he informaion crierias: AIC and SBC; guaraneeing also he inexisence of error auocorrelaion. In wha concerns o he case of Cabovisão, he resuls obained from he rocess for selecing he oimal number of lags ( max ) are ranscribed in he Table 8. resened below. Table 8. Selecion of he Oimal Number of Lags Cabovisão Lags LogL LR FPE AIC SBC HQ NA 7.52E E * * 2.35E-07* * * Legend: Nd No Available; * I idenifies he oimal number of lags seleced by each informaion crieria. 9 In he resen case, we have a reduced number of observaions; herefore, i is no convenien o use a big number of lags. For his reason, we consider only he robabiliy of 2 coefficiens of auocorrelaion o be equal o zero (Marques, 998). 3

14 In order o deermine he occurrence (or no) of error auocorrelaion, he resuls of he LM ess are resened, as well as he robabiliies associaed o he Q saisic (PQ(2)) and o he corresonding adjused value (PQ(2) Ad.). Table 9. Deecion of Error Auocorrelaion in he Cabovisão VAR Model Lags AIC SBC PQ(2) PQ(2) Ad. Tese LM -2,624* -,2575* 0,9994 0,6270 LM 0,6307 LM4 0, ,5077 -,0274 0,5430 0,000 LM 0,2532 LM4 0,839 Legend: * I idenifies he number of lags which rovides he minimizaion of he values of he informaion crierias: AIC and SBC. Lükeohl (999) saes ha he AIC overesimaes he order, in an asymoic way, wih osiive robabiliy, whereas he SBC rovides he esimaion of he order, in a consisen way, if he VAR rocess for generaing informaion has a finie order. Therefore, we roceed wih he esimaion of a VAR model, wih one lag, aking ino consideraion, on he one hand, he resul of he SBC, and on he oher hand, he reduced number of observaions (only, 28 rimesers), and he use of four variables in he esimaion rocess. Besides, by carrying ou several ess, i was verified ha his model rovides he minimum values for he AIC and he SBC, wihou occurrence of error auocorrelaion Coinegraion Tess Based on he coinegraion conce develoed by Engle and Granger (987), if from a VAR model here resuls a unique coinegraing vecor, hen his reveals he exisence of a long erm economic relaion beween he variables, in sudy, which is exressed, in mahemaical erms, by a sysem consiued by I() variables (no saionary), which roduce a linear combinaion ha is saionary, or I(0). In he mehodology roosed by Johansen (988, 99), and Johansen and Juselius (990), i is esablished he ossibiliy of exisence of more han one coinegraing vecor, hrough he deerminaion of he larges ossible number of coinegraing vecors, in funcion of he oaliy of he endogenous variables included in he sysem. For his urose, i can be aken as a reference, a VAR model wih an order equal o, including a Y vecor wih an 4

15 order n, which conains he oaliy of he variables (inegraed of order, ha is, I()) exressed by he following: Y Φ µ Y ε (5.) i i i where Y is he vecor of inegraed variables of order, of he ye (nx); Φ i is he marix of he arameers (nxn); µ is he vecor of he deerminisic erms; and ε is he vecor of he whie noise residuals (nx). The error correcion model is exressed in he following way: Y i µ Γ Y ε (6.) i ΠY i where Γ is he marix of shor erm relaions; and Π is he marix of long erm relaions. The rank of Π (ha is, r) corresonds o he number of linearly indeenden vecors, ha is, he number of coinegraing vecors, obained from he endogenous variables included in he Y vecor. In his conex, we can consider hree ossible scenarios: a) If r ( Π) 0, hen here are no saionary combinaions. In his case, we should esimae a VAR model wih he variables exressed in firs differences. b) If r ( Π ) n, hen he Y vecor is saionary. In his case, we should esimae a VAR model wih he variables exressed in level. c) If r ( Π ) r < n, hen here are r coinegraing vecors which corresond o he number of equilibrium relaions, in he long erm. Based on he rincile of he maximum likelihood, for making significan conras beween he number of Eigenvalues of he Π marix, we are going o consider he following saisics (Johansen and Juselius, 990): i) The Trace Saisic ( λ Trace ) (7.) This saisic rovides he conras beween he null hyohesis ( H 0 ), ha is, he number of coinegraing vecors is smaller or equal o r, and he alernaive hyohesis ( H ), ha is, he number of coinegraing vecors is bigger han r, ha is, H 0 : r r0, agains H : r > r 0. 5

16 ii) The Max-Eigenvalue Saisic ( λ Max ) (8.) These saisics rovide he conras beween he ( H 0 ), ha is, he number of coinegraing vecors is equal o r, and he( H ), ha is, he number of coinegraing vecors is equal o r, ha is, H : r r agains : 0 0 H r r0. In he case of TV Cabo, he resuls of he coinegraion ess roosed by Johansen and Juselius (990) are ranscribed in he Table (0.) resened below. Noes: Table 0. Coinegraion Tess TV Cabo Hyohesis Hyohesis Criical Values EV H 0 H λ Max H 0 H λ Trace λ Max λ Trace r0 r r0 r> * r r r r> * r2 r r 2 r> r3 r r 3 r> [] The ime series ha are used, corresond o he naural logarihms of he variables en, bd, b, and he dummy regarding he vis. [2] The firs column corresonds o he Eigenvalues (EV). [3] The criical values of he saisics of he Trace Saisic and of he Max-Eigenvalue Saisic, a a significance level of 5%, were colleced from Oserwald-Lenum (992). * I denoes he rejecion of he iniial hyohesis, a a significance level of 5%. By observing he hird line of he Table (0.), we see ha he values obained for Max- -Eigenvalue Saisic and for he Trace Saisic are smaller han he criical values. Therefore, he ( H 0 ) relaing o he exisence of wo coinegraing vecors canno be rejeced, agains he ( H ) concerning o he exisence of a leas hree coinegraing vecors, a a confidence level of 95%. The inegraed variables of order have similar behaviours in he long erm, and heir reresenaion is according o he wo coinegraing vecors which will be incororaed in he VAR model, as error correcion erms. In wha concerns he case of Cabovisão, he resuls of he coinegraion ess are seen in he Table (.) resened below. Table. Coinegraion Tess Cabovisão Hyohesis Hyohesis V. Críicos EV H 0 H λ Max H 0 H λ Trace λ Max λ Trace r0 r r0 r> * r r r r> r2 r r 2 r> r3 r r 3 r> Noes: [], [2], and [3] are alied in he same way. * I denoes he rejecion of he iniial hyohesis, a a significance level of 5%. 6

17 From he analysis of he second line of Table (.), we noe ha he observed values for he Max-Eigenvalue Saisic and for he Trace Saisic are smaller han he criical values. Thus, he null hyohesis, which saes he exisence of a unique co-inegraing vecor, canno be rejeced, wih a confidence level of 95%. According o he resuls reviously resened, he variables I() included in he sysem resen a similar behaviour in he long erm, and he corresonding reresenaion is in conformiy wih he only one coinegraing vecor, which will be included laer in he VAR model wih an error correcion erm (ECT) THE DYNAMIC ANALYSIS In he resen iem, an inerreaive analysis is made of he oaliy of he endogenous variables included in he model, which ermis us o make a dynamic simulaion of he effecs originaed by he shocks in he differen random disurbances of he sysem, and o show he imorance of each shock by he orion of he variance of he forecas error exlained by each endogenous variable Granger Causaliy The causaliy relaions, defined in he erms originally roosed by Granger (969), reresen he caaciy of a variable (X) included in he sysem, o assis he forecas of anoher variable (Y), equally included in he sysem. According o Sims (980,.29), «a es for block-exogeneiy has secial ineres, in he conex of a VAR model, because i examines how i will accoun for he observed cyclical variabiliy of he economy». In he resen case, he conras of he significance of each causaliy relaion is made, observing he values of he saisics, a wo significance levels, 5% and 0%, resecively, whereas in he deecion of he significance of he ECT, he saisic is used. In he case of TV Cabo, he use of he exogeneiy ess yielded he resuls resened in Table (2.), where he values corresonding o he eneraion rae of cable elevision service (en), he variaion of he number of subscribers o he basic cable elevision service (bd), and rices of he basic cable elevision service (b) were, reviously, logarihmized. 7

18 Table 2. The Granger Causaliies Conrass TV Cabo LOGPEN LOGBD LOGBP VIS Block ECT ECT2 LOGPEN LOGBD LOGBP * * VIS * * * Noes: [] For a beer undersanding of Table (2.), consider he variable or he block, exressed in each column, as being he indeenden variable (ha is, he origin of he causaliy), and he variable resened in line, as being he deenden variable (ha is, he desiny of he causaliy). 2 [2] The causaliy conrass are made hrough he alicaion of he χ saisic, wih one degree of freedom, whereas he significance conrass alied o he coefficiens of he error correcion erms (ECT, and ECT2), are made hrough he use of he saisic. * Significance level: 5%. The coefficien is significan, since he absolue value of he saisic is bigger han he criical value. Analysing he Granger Causaliy Conrass alied o he case of TV Cabo, we can observe ha he variaion of he basic demand (bd) causes, in a Granger sense, he rice of he basic service (b), a a significance level of 5%. Considering he rice of he basic service (b) as he deenden variable, he block of variables consiued by he remaining variables included in he sysem, namely, he eneraion rae (en), he variaion of he basic demand (bd), and he verical inegraion of services (vis), causes, in a Granger sense, he rice of he basic service, a a significance level of 5%. Wih regard o unidirecional causaliy, defined in he sense bd b (ha is, demand rice), we see confirmaion of he fac ha he dynamics of he demand of he nework services affec he ricing sraegy imlemened by he incumben, making use of ackage ie-in sales of verically-inegraed services, which allows a greaer valorisaion of hese services, on he ar of he subscribers. sense In erms of unidirecional causaliies, he observance of a causaliy defined in he bd vis mus be sressed (ha is, demand verical inegraion of services), which is jusifiable by he effec of he demand ull. This effec is roduced by he conribuion of he basic demand for inensifying he verical inegraion of services, exressing he ineraciviy beween he demand of his kind of nework services and he verically-inegraed suly, on he ar of he incumben. There is also deeced a unidirecional causaliy which is defined in he sense en vis (ha is, eneraion rae verical inegraion of services), which is jusified by he sraegic choice of he incumben, reinforcing he nework densiy, which recedes he inroducion of new verically-inegraed services. 8

19 Concerning o he join-causaliy revealed by he remaining variables relaive o he sraegy of verical-inegraion of services, we observe ha he mixed acion of he demand, of he rice of he basic service, and of he increase of he nework densiy, as a mechanism for reinforcing he marke ower does recede he imlemenaion of he sraegy of verical inegraion of services, on he ar of he incumben. As concerns he block of he remaining variables, he exisence of a relaion of indeendence was verified among he variables. This siuaion can be jusified by he reduced number of observaions ha is used in he resen sudy. In he case of Cabovisão, he alicaion of he blocks-exogeneiy ess rovided he resuls ha are resened in Table (3.), where he values of he oal of he variables were, reviously, logarihmized. Table 3. The Granger Causaliies Conrass Cabovisão LOGPEN LOGBD LOGBP VIS Block ECT LOGPEN * ** LOGBD LOGBP VIS Noes: [] For a beer undersanding of Table (3.), consider he variable or he block, exressed in each column, as being he indeenden variable (ha is, he origin of he causaliy), and he variable resened in line, as being he deenden variable (ha is, he desiny of he causaliy). 2 [2] The causaliy conrass are made hrough he alicaion of he χ saisic, wih one degree of freedom, whereas he significance conrass alied o he coefficiens of he error correcion erm (ECT), are made hrough he use of he saisic. * Significance level: 5%. ** Significance level: 0%. The coefficien is significan, since he absolue value of he saisic is bigger han he criical value. Using he analysis of he causaliy conrass, we found a unidirecional causaliy defined, in he sense, b en (ha is, rice eneraion rae). From here, we conclude ha he rice of he basic service causes, in a Granger sense, he eneraion rae (which measures he nework densiy), a a significance level of 5%. Considering he nework densiy as he deenden variable, we observed ha he block of he remaining variables included in he sysem causes, in a Granger sense, he eneraion rae (nework densiy), a a significance level of 0%. For he remaining blocks of variables we found he exisence of relaions of indeendence. 9

20 Variance Decomosiion of Cholesky Nex, in he case of TV Cabo, he resuls of he variance decomosiion of Cholesky, for 4, 8, 2, and 24 Trimesers, are resened, aking ino consideraion he ercenage weighs, for each ossible causaliy relaion 0. Table 4. Percenage Weighs of he Causaliy Relaions TV Cabo Hyoheses Causaliy Relaions 4 Trimesers Percenage Weighs 8 2 Trimesers Trimesers 24 Trimesers LOGBD LOGPEN 0,2 0,76,03,30 LOGBP LOGPEN 3,86 5,20 5,66 6,04 VIS LOGPEN 0,8 0,40 0,50 0,60 H3 LOGPEN LOGBD 34,56 27,35 23,42 7,94 LOGBP LOGBD,70 3,03 4,54 7,38 VIS LOGBD 3,20 6,62 9,56 4,62 H LOGPEN LOGBP 7,49 22,26 3,89 52,27 H5 LOGBD LOGBP 4,4 4,25 2,3 7,87 H2 VIS LOGBP,60,84 2,03 2,49 LOGPEN VIS 9,36 20,4 26,7 33,39 H4 LOGBD VIS 34,87 45,70 47,92 49,25 LOGBP VIS 0,57 5,72 3,70,88 Considering he analysis based on he variance decomosiion of Cholesky, roosed by Sims (980), we conclude ha only he rice has a direc and significan imac on he eneraion rae (ha is, he nework densiy). For a forecas horizon wih 8 rimesers, he direc imac over he nework densiy (logen), was calculaed a 0,76%, by acion of he basic demand (logbd); a 5,20%, hrough he rice (logb), and a 0,40%, across he verical inegraion of services (vis). Thus, he rice resens a causaliy relaion relaive o he nework densiy. The same does no haen wih he wo oher variables. The nework densiy and he verical inegraion of services have a direc and significan imac on he basic demand, whereas he rice of he basic service does no resen a significan imac on he behaviour of he basic demand. 0 For a grahic reresenaion abou he Variance Decomosiion of Cholesky (24 Trimesers) TV Cabo, lease see he Grah, of he Annex. We only consider as direc and significan imacs over he variance of he forecas error, values bigger han 5%, for a forecas horizon wih 8 Trimesers (Goux, 996,.67). 20

21 For a forecas horizon of 8 rimesers, he direc imac on he demand (logbd) was calculaed a 27,35%, by acion of he nework densiy (logen), a 6,62%, across he verical inegraion of services (vis), and a 3,03%, hrough he rice of he basic service (logb). Alhough he nework densiy has he mos significan imac on he basic demand; i resens a decreasing effec, along he forecas horizon. This fac confirms he imorance of he suly ush as a mechanism for exanding he subscribers mass, and for aaining he ineraciviy beween he suly and he demand of nework services. The verical inegraion of services resens a ersisen and growing effec on he basic demand, which reinforces he logic of he oeraor in offering, more and more, new verically-inegraed services, in order o exand he number of subscribers o he basic demand, which works as an obligaory anchor for he subscriion o oher comlemenary and inegraed services. For a forecas horizon of 8 rimesers, we found ha he direc imac on he rice of he basic service (logb), was calculaed a 22,26%, by acion of he nework densiy (logen), a 4,25%, across he basic demand (logbd), and a,84%, hrough he verical inegraion of services (vis). Consequenly, he resuls obained by he analysis of he variance decomosiion confirm he reviously deeced unidirecional causaliies of he nework densiy, and of he demand, relaive o he verical inegraion of services. For a forecas horizon of 8 rimesers, he direc imac on he verical inegraion of services (vis) was calculaed a 20,4%, across he nework densiy (logen), a 45,70%, by acion of he basic demand (logbd), and a 5,72% hrough he rice (logb). From his, we conclude ha he basic demand resens a srong causaliy relaive o he sraegy of verical inegraion of services, imlemened by he incumben, which signals he imorance of he demand ull in he diffusion of new verically inegraed services. In he case of Cabovisão, he resuls of he variance decomosiion, for 4, 8, 2, and 24 Trimesers, are ranscribed in he Table For a grahic reresenaion of he Variance Decomosiion of Cholesky (24 Trimesers) Cabovisão, lease see he Grah 2, of he Annex 2. 2

22 Table 5. Percenage Weighs of he Causaliy Relaions Cabovisão Percenage Weighs (in %) Hyoheses Causaliy Relaions 4 Trimesers 8 Trimesers 3 2 Trimesers 24 Trimesers LOGBD LOGPEN 4,87 6,20 6,56 6,93 LOGBP LOGPEN 7,09 20,77 23,57 26,6 VIS LOGPEN 0,25 0,23 0,2 0,9 H3 LOGPEN LOGBD 7,20 5,36 4,76 4,2 LOGBP LOGBD 3,37 2,56 2,35 2, VIS LOGBD 0,20 0,29 0,32 0,34 H LOGPEN LOGBP 34,97 50,2 55,70 62,29 H6 LOGBD LOGBP 2,4 2,97 3,22 3,50 H2 VIS LOGBP 0,6 0,32 0,35 0,39 LOGPEN VIS 2,22 22,80 23,25 23,70 H4 LOGBD VIS 0,7 9,0 8,5 8,00 LOGBP VIS 5,23 6,62 6,93 7,25 The analysis of he causaliy relaions revealed ha he variaion of he basic demand, and he rice have a direc and ersisen effec on he eneraion rae (or, nework densiy). For 8 rimesers, he direc imac on he nework densiy (logen) was calculaed a 6,20%, by acion of he basic demand (logbd), a 20,77%, hrough he rice (logb), and a jus 0,23%, across he verical inegraion of services (vis). Taking ino consideraion he revious finding relaed o he exisence of a unidirecional causaliy relaion beween he rice and he nework densiy, we observe ha he rice has he mos significan and ersisen imac on he nework densiy, while he effec due o he variaion of he basic demand jus increases 2,06 ercenage oins, in he forecas eriod beween he 4 h and he 24 h rimesers. In wha concerns he analysis of he causaliy relaions beween he variables of he second block, we mus sress ha he nework densiy only has a significan imac on he basic demand. The rice and he verical inegraion of services do no resen a direc and significan imac on he basic demand. 3 As i was, reviously, considered in he incumben case, we also consider as direc and significan imacs on he variance of he forecas error, values bigger han 5%, for a forecas horizon wih 8 Trimesers (Goux, 996,.67). 22

23 For 8 rimesers, we observe ha he nework densiy (logen), resens he mos significan imac, reaching 5,36%, being followed by he rice (logb) a 2,56%, and in he las lace, he verical inegraion of services (vis), which only conribues 0,29% of he exlained variance of he forecas error of he basic demand (logbd). In erms of he direc imacs on he rice of he basic service (logb), we mus sress ha he nework densiy (logen) is he one which resens a more significan and ersisen effec, since afer 8 rimesers, i conribues for 50,2% of he exlained variance of he forecas error of he rice. All he variables show a significan imac on he verical inegraion of services. This siuaion is confirmed by he conribuions obained for he exlanaion of he variance of he forecas error of he verical inegraion of services (vis), where a forecas horizon wih 8 rimesers, which were calculaed a 22,80%, hrough he nework densiy (logen), a 9,0%, by he acion of he basic demand (logbd), and a 6,62%, across he rice (logb) Imulse-Resonse Funcions In he case of TV Cabo 4, he values of he Imulse-Resonse Funcions, rovide he inerreaions ha are resened here. Firsly, he resonse of he rice relaive o he imulses in he eneraion rae is relaively insignifican, showing a negaive imac afer he shock ha lass unil he 4 h rimeser. Alhough he resonse of he rice relaive o he imulses in he eneraion rae is negaive in he firs four rimesers, he sign of he causaliy weigh is osiive 5. This is in conras o he resul obained hrough he variance decomosiion, which has revealed he exisence of a significan imac of he eneraion rae on he rice of he basic service. From here, he deducion of a osiive relaion beween he eneraion rae and he rice can be made, ha is, for an increase in he nework densiy; here is a corresonding increase in he rice of he basic service. Secondly, he resonse of he rice relaive o he innovaions which occurred in he verical inegraion of services is null, in he resen eriod, becoming negaive, in he second eriod. Laer on, i is osiive, assuming negaive values saring from he 6 h rimeser. 4 For more deails, lease consul he Table 6, of he Annex. 5 According o Goux (996), he signal of he causaliy weigh is obained hrough he sum of he values of he coefficiens of he imulse-resonse funcions, which are obained for a forecas horizon of 0 rimesers. 23

24 The negaive relaion beween he verical inegraion of services and he rice of he basic service confirms he saisical inference of he analysis of he variance decomosiion, which oined ou he exisence of a non-significan imac of he verical inegraion of services on he rice. In he case of TV Cabo, he sraegy of verical inegraion of services assumes secial imorance in maximizing he rofis obained by his oeraor, which is verically inegraed in he Gruo PT, since his siuaion faciliaes he suly of addiional services wih increased value for he subscribers, obaining a reducion in he roducion coss hrough he roery of comlemenary monoolies 6 conjugaed wih a solid brand image of he Moher- -Comany, which ermis he reinforcemen of he marke ower of he incumben. Thirdly, he resonse of he basic demand relaive o he imulses in he eneraion rae is osiive and significan, only reaching a negaive value saring from he 6 h rimeser. This resul confirms he main resuls of he analysis of he variance decomosiion. On he one hand, his osiive relaion reveals he imorance of he suly ush romoed by he incumben, hrough he exansion of he number of cabled households which rovides he uilizaion of he ineraciviy beween he suly and he demand of nework services, considering ha he suly ushes he addiional subscriion of verically inegraed nework services, hrough he same cable disribuion nework. On he oher hand, his confirms he caaciy ha he monoolis has o influence he consumers' execaions, forcing he referred consumers o subscribe o he services offered hrough he bigger dimension nework. Fourhly, he resonse of he verical inegraion of services relaive o he imulses in he basic demand is osiive and significan, assuming a sable value saring from he 5 h rimeser. This confirms he resul obained hrough he analysis of he variance decomosiion, which has, reviously, indicaed he exisence of a direc and significan imac of he basic demand on he verical inegraion of services. The imorance of he effec of demand ull on he imlemenaion of he sraegy of verical inegraion of services imlemened by he incumben, referred by Geroski (2003), is also raified. This effec is exressed by he fac ha he basic demand ulls he inroducion of new verically inegraed services. 6 This siuaion reflecs he dominan osiion exercised by he hisoric oeraor: Porugal Telecom (PT); in he differen Telecommunicaions Subsecors in Porugal, and he simulaneous roery of he naional fixed elehone nework, and he cable nework. 24

25 Fifhly, he resonse of he rice in relaion o he imulses in he basic demand is negaive and no very significan. This resul is in conras wih he inference obained hrough he analysis of he variance decomosiion, which has revealed he exisence of a significan imac of he demand on rices of he basic service. In he case of Cabovisão, he values of he imulse-resonse funcions revealed ha he resonse of he rice in relaion o he imulses in he eneraion rae, assumes a osiive value, which becomes sable from he 4 h quarer onwards. This finding confirms he inference obained hrough he variance decomosiion. Thus, a osiive relaion beween he eneraion rae and he rice of he basic service is observed, ha is, for every increase in he nework densiy of he enran, here is a corresonding increase in he rice of he basic service. Furhermore, he resonse of he rice relaive o he imulses in he verical inegraion of services is null, in he resen momen, and i is osiive, in he second eriod, saring laer o be negaive, bu insignifican, from he 3 h eriod; and assuming a sable value, from he h rimeser. This resul confirms he saisical inference of he analysis of he variance decomosiion, which confirms he exisence of a non-significan effec of he verical inegraion of services on he rice of he basic service. As concerning he resonse of he basic demand relaive o he imulses in he eneraion rae, his is osiive and significan, being sable from he 3 h rimeser onwards. The resul obained hrough he analysis of he variance decomosiion confirms ha he eneraion rae has a significan effec on he basic demand. This effec can be exlained by he fac ha he enran has available a smaller dimension nework. This siuaion rovides he inernalizaion of he osiive nework exernaliies observed in he iniial hases of he disribuion nework (ha is, he release and he exansion hases). The resonse of he verical inegraion of services relaive o he imulses in he basic demand is osiive and significan, assuming a sable value, from he 0 h rimeser onwards. This resul is confirmed by he analysis of he variance decomosiion, which oined ou he exisence of a direc and significan imac of he basic demand on he verical inegraion of services, neverheless he weigh of he causaliy o be smaller han he one deeced in he incumben case. 25

26 The resonse of he rice of he basic service relaive o he imulses in he demand is osiive and non-significan, assuming a sable value, from he 0 h rimeser onwards. This resul is confirmed by he inference obained hrough he analysis of he variance decomosiion, which oined ou he exisence of a non significan imac of he demand on he rice. According o he resul obained hrough he analysis of he variance decomosiion, his imac is no very significan, and in comaraive erms, i is also smaller han he one ha was observed in he incumben case. In he enran case, he discovery ha he rice of he basic service has a osiive relaion wih he demand, can be jusified by he reduced number of subscribers and by he inernalizaion of he srong nework exernaliies ha are observed in he iniial hases of he disribuion nework. This comaraive resul can be jusified, on he one hand, by he reduced mass of subscribers owned by he enran, which aenuaes he effec of he demand as a caalyic mechanism for he verical inegraion of services and, on he oher hand, by he observance of a smaller rhyhm of diffusion of new verically inegraed services, aking ino consideraion he ossible occurrence of differen forms of ineraciviy beween he suly and he demand of services which are ransaced hrough he cable elevision neworks. 26

27 5. CONCLUSIONS From he develomen of he economeric sudy alied o he main Poruguese Cable Television Neworks, we conclude ha he economic variables, in our sudy, are inegraed of order one, and herefore, no saionary. The variables are also coinegraed, denoing he exisence of long erm economic relaions. In he incumben case, in wha concerns he resuls of he causaliy conrass, hree main findings deserve a secial menion. Firs, he demand causes in a Granger sense, he rice of he basic service, which reveals he negaive imac of he demand on he rice. Second, he nework densiy causes in a Granger sense, he verical inegraion of services. This raifies he revious imorance of he exansion of he nework, in erms of he number of cabled households, which works as a form of suly ush. Third, he demand causes in a Granger sense, he verical inegraion of services. This raifies he argumens resened by Geroski (2003), which show he imorance of he demand ull for deermining he seed of reacion, in erms of he diffusion of new verically inegraed services, on he ar of he incumben. In he enran case, he rice of he basic service causes in a Granger sense he eneraion rae. This allows verifying he imorance of he rice as a signalling mechanism of he qualiy of he offered services, and as a financing elemen of he exansion of he horizonal nework dimension. The differences observed in he causaliy conrass reveal he advanage of being he firs, obained by he incumben, which is "forced" o inensify he verical inegraion of services, whereas he enran imlemens a sraegy which gives a secial imorance o he hysical exansion of he nework. In wha concerns o he hyoheses, in sudy, we have o enhance he exisence of a osiive relaion beween he eneraion rae and he rice of he basic service (see he Hyohesis ). This finding is in conras wih he resuls obained in he sudies alied o he cable elevision indusry in he USA, accomlished by Comanor and Michel (97), Park (972), and Pacey (985), which oined ou he exisence of a negaive relaion beween he eneraion rae and he rice of he basic service. In he wo Poruguese case sudies, he resuls revealed he imorance of increasing he nework densiy (during he iniial hases: release, and exansion), in deermining he increases in he rice of he basic service. 27