Iranian Economic Review, Vol.5, No.26, Spring 200 Economic Facors in Deermining he Peneraion Coefficien of Mobile Phone in Iran Mansour Khalili Araghi Ghahreman Abdoli Absrac n his paper we have sudied he adopion rae of mobile phone Iin Iran via he new echnology diffusion models approach. The resul show ha is diffusion paern has a S shaped curve which is consisen wih logisic model. Effecive facors in diffusion paern are: populaion, GDP, digializaion of he elecommunicaion sysem, governmen expendiures on he elecommunicaion secor, price of mobile phone and he inflaion rae. We have also found ha he logisic model has a baer explanaory power han he ime series models. Keywords: Mobile Phone, Diffusion, ARMA model, Logisic model. Professor; Faculy of Economics, Universiy of Tehran. Assisan Professor; Faculy of Economics, Universiy of Tehran.
42/ Economic Facors In Deermining he Peneraion Coefficien - Inroducion From he lae 980's he use of he services of mobile- phone has had a rapid growh in Iran; wih wo consequences: ) fas increase in procuring he capabiliies like elecommunicaion indusries and is infrasrucures, 2) remarkable reducions in he price of he se and service of he mobile phone. Usually heories concerning he diffusion of a new echnology has one common poin; and ha is peneraion and diffusion of new echnology in he sociey in ime has a S shaped curve. Tha means a he ouse of he inroducion of a new echnology is peneraion is slow, hen i become slow. The ime process of diffusion of a new echnology iself is affeced by diffusion of informaion. Tha is a he ouse here are a few number of people who accep he new echnology and know is advanages, hey hen will convey hese advanages o he ohers persuading hem o use he new echnology. In he laer sage because here are more people who have used he new echnology, diffusion of informaion will be a a wider dimension and finally a limied number of people will remain o accep using his new echnology. The pioneer in economic sudies in he area of diffusion of new echnology was Grilichez (957). Afer him here were qui a number research in his area, in order o see he review of he lieraure one can see Geroski (2000), Frank (2004), Meade and Islam (2006) The firs inercounries sudy of he peneraion rae of mobile phone belongs o De Kimpe a al, (998). They have divided he effecive facors on he peneraion rae of mobile phone ino exogenous and endogenous facors, which is a developed model of Bass's model. Gruber and Verboven (200) have shown ha he peneraion of mobile in he sociey has a S shaped curve in which economical, echnical, culural and social facors were imporan. Frank (2004) has uilized he logisic model o sudy he paern of mobile phone. According o his sudy he effecive facors in he peneraion coefficien of mobile phone in Finland were digializaion of he elecommunicaion sysem, populaion, GDP, and land- phone. Lee, M. & Cha,, (2007) have sudied he effec of mobile- phone for he S. Korea. They have also done some forecasing in ha regard. According o heir findings he logisic models predic he peneraion coefficien beer han ime service model and he explanaory facors which were used in Frank's model are also effecive in Korea.
Khalili Araghi, M. & Gh. Abdoli. /43 In Iran he demand for mobile phone has been acceleraed in recan years. The number of subscribed has been increased from 0.5 million in 995 o 6.7 million in 2006. In his paper we have suelied he rend of peneraion of mobile phone and he effecive facors for is peneraion. The S Shaped models have been compared wih ime service model in heir forecasing power. 2- The Models a) Comperz (825) has inroduced he diffusion paern of new echnology wih he following equaion: α e = K e β () If we use equaion () for mobile, we will have as he number of subscribed mobile phone in ime, which K, α and β are parameers. In he above equaion [ o, K] ; when moves from - o + goes from o o K. α and β will deermine he posiion of he S shaped curve. b) Grilichez (957) has also inroduced he following equaion for a S shaped curve, which also has been used by Frank (2004) for sudying he diffusion paern of mobile phone. y y ( ) = = (2) ( a+ b ) b + e + k e Equaion (2) is he logisic equaion of he diffusion of new echnology. () is he number of subscribed mobile phone in ime, and y which is a funcion of populaion is he opimal number of he recipiens of mobile phone; b is he speed of diffusion of mobile phone in he sociey. c) Along wih logisic models, he auoregressive moving average models ARMA (p, q) have also been used for forecasing of diffusion of new echnology. In hese models P is he rank of auo regression and q is he moving average erm. Auo regression model AR(p) is = μ + γ y + γ 2 y 2 +... + γ p y p + ε And moving average MA(q) is wrien as
44/ Economic Facors In Deermining he Peneraion Coefficien = μ + ε θ ε... θ ε The general model of ARMA (p,q) is he combinaion of (3) & (4): q q (4) = μ + γ y +... + γ y + ε θ ε... θ ε p p q q (5) One can find p and q by auocorrelaion funcion (ACF) and parial auocorrelaion funcion (PACF). In his aricle we have uilized he Frank's model which can be explained as follows: According o equaion (2) we had: y = ( a+ b ) + e (6) Where is he poenial recipiens of mobile phones; b, he relaive growh rae of diffusion which varies in ime. Can be defined as = γ PO P (7) In (7), y is he oal poenial recipiens of mobile phone and γ is he peneraion coefficien in he sociey. Frank has defined b as he following relaion: b = β a + β g GDP + β d DIG + βttel (8) In which GDP, DIG and TEL are gross domesic produc, digializaion of elecommunicaion sysem and he number of land phones, respecively. In our sudy we have modified (8) o (9) b = β α + β GDP+ β DIG+ β TEL+ β INF+ β PS + β GOV+( q) ε (9) g d T f p go INF is inflaion rae; PS price of mobile phone and GOV is he governmen expendiures a elecommunicaion secion. The firs derivaive of (6) will give us he speed of diffusion of mobile phone, or he number new mobile phone a ime. The second derivaive shows he change in he number of new mobile phones a ime. From equaion (6) we have:
Khalili Araghi, M. & Gh. Abdoli. /45 ( a+ b ) = = + e ( a+ b ) + e Using equaion (0) we ge: b ( ) = b = 2b One can subsiue (7) and (9) in o (6) and use NLS esimaion mehod. 3- Variables and Daa Digializaion of he elecommunicaion sysem of Iran sared in 989, afer ha, he peneraion rae of land phone and mobile phone increased dramaically. This variable has been enered ino equaion (9) as a dummy variable which has he value of zero for he years 986-988 and one for he years afer, Daa of land phone and mobile phone and heir prices were colleced from Iran Telecommunicaion Company (ITC). Oher daa were colleced from he Iran Saisic Cenre and he Cenral Bank of Iran. Saionariy of he daa were checked wih he Augmened Dicki Fuller es. The resuls are presened in able (). Table : Tes of Saionariy of he Daa Variable ADF Saisic 0% criical level γ -3.2-2.98 Pop -3.05-3.39 GDP -3.74-2.8 Tel -4.5-3.55 P s -3.07-2.92 Inf -5.0-3.38 Gov -4.46-3.48 All he variables are saionary a α= 0%
46/ Economic Facors In Deermining he Peneraion Coefficien 4- Esimaion of he Models 4-- Logisic Model In able (2) we have presened he resuls by using he Frank's logisic model. According o he able, β T is negaive, bu no significaion. Negaive β T means mobile phone is a subsiue for land phone and posiive β T means ha hey are complemen o each oher. The esimaion for γ is 45% which gives he maximum peneraion rae of he firs operaor which has been he subjec of his sudy. The coefficien of GDP is posiive, ha is as income improves diffusion of mobile phone increases. The coefficien of DIG is consisen wih he heory; improvemen and peneraion of digializaion in he elecommunicaion sysem makes he expansion of mobile phone more possible. The price of mobile phone has had a negaive effeced on is diffusion. As he governmen expendiures on he elecommunicaion goes up, so does he diffusion of mobile phone. Finally inflaion has had a negaive effec. Table 2: The Resuls of he Esimaion of Logisic Model wih NLS Mehod Coefficien Esimae a -20.2-2.56 β a.98 3.482 β y 0.967 4.829 β d 0.873 3.02 β T -0.0073-0.00026 γ 0.45 3.0097 β inf -0.86-3.23 β p -0.92-2.95 β go 0.78 3.028 R 2 2 =0.72 R = 0.65 D.w =.82 N= 20 F= 7.28 4-2- ARMA Model By using ACF and PACF he rank of AR was found o be P= 2; and he rank of MA, q=.
Khalili Araghi, M. & Gh. Abdoli. /47 = μ + γ + γ 2 2 + ε θ ε (3) The resuls of he esimaion of equaion (3) are presened in able (3): Table 3: The Resuls of he Esimaion of E q. (2) Variable Coefficien SE γ.4597 0.3805 6.24 γ 2-0.5462 0.28376 -.42 μ 82656. 284.3 4.06 θ 0.6478 0.5473.45 R 2 =0.62 2 R = 0.58 D.w = 2.0 As can be seen from able (3) he variables in ARMA (2, ) are significan and we can say he auocorrelaion moving average model along wih Frank's logisic model are good predicors. 4-3- Comparison of Logisic and ARMA Models In figure () we have drawn he ARMA and logisic models. The cumulaive number of mobile phones are on he verical axis. The logisic model has a S shape and he ARMA model oscillaes. According o he lieraure he diffusion of new echnology has a S shaped curve, which in our case he logisic model is a beer fi. 8000000 6000000 4000000 2000000 0000000 8000000 6000000 4000000 2000000 0 986 988 990 992 994 996 998 2000 2002 2004 2006 Logisic Acual ARMA ear Fig : Comparison of Logisic, ARMA wih Acual DATA
48/ Economic Facors In Deermining he Peneraion Coefficien In able (4) he perdiion power of hese wo models wih he residual sum of square (RSS) and mean square of errors (MSE) crieria are shown. According o able 4 he logisic model can predic diffusion of mobile phone in Iran beer han ARMA model. Table 4: Compassion of Logisic and ARMA Models in Terms RSS and MSE Crieria Logisic Model ARMA Model RSS 6.42 E +09 5.43E + MSE.86 E + 07.89 E+ 07 5- Summary and Conclusion The lieraures on he diffusion of new echnology models have shown ha he paern of diffusion hrough ime has a S shaped curve. By using hese models i can be shown ha a each poin in ime how much is he peneraion coefficien, and consequenly wha should be he proper policy. We have considered mobile phone as a new echnology o Iranian sociey and have seen ha is paern of diffusion has had a S shaped curve. According o our finding GDP, digializaion of he elecommunicaion sysem, populaion, governmen expendiures on elecommunicaion secor have had posiive effecs on he diffusion of mobile phone in Iran, while is price and inflaion have had a negaive effec. Comparing logisic model wih ime series model shows ha he logisic model explains he role of effecive facor in he peneraion of mobile phone and also will give us a beer predicaion han he ime service model. References - Bass,F.M.(969) "A new produc growh model for consumer durables", Managemen Science, 5, 25-227. 2- Daa,A. and Agarwal,S.(2004) "Telecommunicaion and economic growh: a panel daa approach", Applied Economics, 36,649-654. 3- Dekimpe,M.G., Parker,P.M. and Sarvary,M.(998) Saged esimaion of inernaional diffusion models- an applicaion o gelobal celluar elephone adopion", Technological Forecasing and Social Change, 57,05-32.
Khalili Araghi, M. & Gh. Abdoli. /49 4- Frank,L.D.(2004) "An analysis of he effec of economic siuaion on modeling and forecasing he diffusion of wireless communicaions in Finland", Technological Forecasing and Social hange, 7,39-403. 5- Griliches,Z.(957) "Hybrid Corn: an exploraion in he economics of echnical change", Economeria, 25,507-522. 6- Gruber,H.(2007) "Compeiion and innovaion: he diffusion of mobile elecommunicaions in cenral and easern Europe", Informaion Economics and policy 3,9-34. 7- Gruber,H. and Verboven,F.(200) "The diffusion of mobile elecommunicaions services in he European Union", European Economic Review, 45,577-880. 8- Kim,. Lee and Koh,J.D.(2005) "Effecs of consumer preferences on he convergence of mobile elecommunicaion devices", Applied Economics, 37,87-826. 9- Lee,M. and Cho,.(2007) "The diffusion of mobile elecommunicaions services in Korea", Applied Economics leers,477-48. 0- Boelho,A., Cosa Liglia.(2004) "The diffusion of cellular phones in Porugal", Telecommunicaions policy 28,27-437.