The Relationship between Savings and GDP in Iran: An ARDL Approach for the case of Iran

Transcription

1 Inernaonal journal of advanced scenfc and echncal research Issue 2 volume 6, December 2012 Avalable onlne on h:// ISSN The Relaonsh beween Savngs and GDP n Iran: An ARDL Aroach for he case of Iran Mohsen Mehrara Faculy of Economcs, Unversy of Tehran, Tehran, Iran Maysam Musa Faculy of Socal Scences, Unversy of Tehran Sma Nasbaras MSc n Economcs, Unversy of Tehran Absrac The objecve of hs aer s o examne he relaonsh beween savngs and economc growh n Iran for he erod , based on he auoregressve dsrbued lag (ARDL) aroach. The sudy fnds a conegrang relaonsh among real GDP, savngs, labor force, ol revenues and educaon. Comared o he oher varables, labor force and human caal (educaon) have he mos moran effec on economc growh arcularly n long-run. Moreover, n shor-run jus ol revenues and labor have sgnfcan effecs on economc growh. Esmang error correcon model revealed ha he seed of adjusmen o resore equlbrum s whch confrms ha here s a sable long-run relaonsh. Regardng weak mac of savng on economc growh, seems ha governmen and olcy makers should emloy olces ha would accelerae economc growh hrough hgher roducvy and rvleged human caal. JEL classfcaon: C12, C22, C52, E21, F43 Keywords: ARDL, Gross Domesc Savngs (GDS), Economc Growh, Iran Economy 1. Inroducon In he heores of economc growh, s ofen argued ha ncreased level of savngs can enhance economc growh hrough ncreased level of nvesmen. Accordng o heores of consumon, On he oher hand, Savngs can be affeced by many facors, ncludng economc growh. Hence, f economc growh rses, he level of savngs can be ncreased. Accordng o hese wo on of vews exressed n economc heores, nvesgang he relaonsh beween savngs and economc growh s an moran as well as conroversal ssue for economss and olcy makers. Some researchers have analyzed as cause and effec relaonsh. Anoher grou of economss beleve n caal fundamenalss' on of vew ha savngs cause growh. Page 39

2 Inernaonal journal of advanced scenfc and echncal research Issue 2 volume 6, December 2012 Avalable onlne on h:// ISSN There s a hrd grou of economcs who have confrmed Keynesan heory ha savngs deend uon he level of ouu. As a resul, because of he morance of savngs n economc growh and also he effecve role of economc growh n ncreasng savngs, s necessary o nvesgae he relaonsh beween he level of savngs and economc growh n Iran, and s resuls can be useful n desgnng olces. In hs aer we examne he shor- and long-run relaonshs beween savngs and economc growh for Iran over he erod , usng Auoregressve Dsrbued Lag (ARDL) aroach o conegraon and error correcon models (ECM). The res of he aer s organzed as follows. Secon 2 revews he leraure. Secon 3 descrbes daa and mehodology. Resuls are reored n Secon 4. Secon 5 concludes. 2. Revew of Leraure Andersson (1999) nvesgaed he causaly beween savng and growh n Sweden ( ), UK ( ), and USA ( ). Savng and GDP were esmaed n bvarae vecor auoregressve or vecor error-correcon models, and ess of Granger non-causaly were erformed whn he esmaed sysems. Accordng o he resuls, he auhor suggesed ha he causal chans lnkng savng and ouu was dfferen across counres. In he UK, here was a bdreconal causaly beween GDP and gross savng. In he Swedsh case, he emoral deendence s more undreconal from savng dynamcs o ouu growh. For he US here was no sascally sgnfcan long-run relaonsh beween he varables. The resuls also ndcaed ha he varables could be conneced n Granger-causal chans hrough dfferen channels, n long run and shor run chans, whch mgh dffer boh regardng drecon and sgn. In hs aer, Romm (2003) aled Johansen VECM esmaon echnque o nvesgae he drecons of relaonsh beween savngs and growh n Souh Afrca over he erod The resuls of hs sudy ndcaed no only a drec and an ndrec effec of rvae savng rae on growh bu also a osve effec of growh on he rvae savng rae. Romm mled ha he ndrec effec of rvae savng rae on growh s hrough he rvae nvesmen rae. He suggesed he exsence of a vruous cycle as growh enhances savng, whch n urn furher enhances growh. Nwachukwu and Egwakhde (2007) examned he deermnans of rvae savng n Ngera or he erod They comared he esmaon resuls of he Error-Correcon Model wh hose of hree convenonal models: Paral-Adjusmen, Growh Rae and Sac Models. The concluson was ha he ECM erformed much beer han he oher models. The esmaon resuls for he error-correcon model oned o he level of er caa ncome, erms of rade changes, ublc savng rae, exernal deb servce rao, and he nflaon rae as havng sascally osve nfluences on domesc savng. The real neres rae and growh rae of ncome had a negave mac on he savng rae. They also found a clear role for fscal olcy n ncreasng oal savng n he economy, wh he rvae secor consderng ublc savng as a comlemen for s own savng. Sajd and Sarfraz (2008) aled conegraon and vecor error correcon echnques o nvesgae causal relaonsh beween savngs and ouu n Paksan usng quarerly daa for he erod of 1973:1 o 2003:4. They dscovered a bdreconal long-run relaonsh beween savngs and ouu level, a undreconal long-run causaly from ublc savngs o ouu (GNP Page 40

3 Inernaonal journal of advanced scenfc and echncal research Issue 2 volume 6, December 2012 Avalable onlne on h:// ISSN and GDP), and a undreconal from rvae savngs o gross naonal roduc (GNP). They also found ha he seed of adjusmen n case of savngs s sronger han ha of level of ouu. Ther resuls also ndcaed ha here s a muual shor-run relaonsh beween GDP and domesc savngs, and a undreconal shor-run causaly from GNP o naonal and domesc savngs, and a undreconal relaonsh from GDP o ublc savngs. In her sudy, Agrawal and Sahoo (2009) nvesgaed he long-run deermnans of oal and rvae savngs and he drecon of causaly beween savngs and growh n Bangladesh over The evdence ndcaed ha oal savngs rae s deermned by GDP growh rae, deendency rao, neres raes and bank densy. I s also revealed ha rvae savngs rae s affeced by he ublc savngs rae. In addon, usng he Granger Causaly ess, he resuls suggesed a b-dreconal causaly beween savngs and growh. Agrawal and Sahoo also aled he Forecas Error Varance Decomoson (FEVD) analyss usng he VAR framework. The causaly resuls obaned usng he Granger causaly ess and he esmaed savngs funcons are confrmed usng FEVD analyss. Abu (2010) emloyed Granger causaly and conegraon echnques o analyze he assocaon relaonsh beween savng and economc growh n Ngera durng he erod Accordng o he resuls, he concluded ha he varables (economc growh and savng) are conegraed, and ha a long-run equlbrum exss beween hem. He also suggesed ha causaly runs from economc growh o savng. So he Solow s hyohess ha savng recedes economc growh s rejeced, and he Keynesan heory ha s economc growh ha leads o hgher savng s acceed n Abu's sudy. Shahbaz and Al Khan (2010) nvesgaed he relaonsh beween economc growh and domesc savngs n Paksan for he erod of In dong so, Conegraon echnques and ARDL Bounds Tesng were emloyed o examne for long run assocaon, whle Innovave Accounng Technques and Toda and Yamamoo (1995) were aled for causal relaonsh. Ng-Perron de-rended es was used for order of negraon of runnng acors. The resuls revealed ha here was a long run relaonsh beween economc growh and domesc savngs and her assocaon was robus a leas n long san of me. Causal resuls hrough Innovave Accounng echnque assered ha here was one-way causaly runnng from economc growh o domesc savngs. Bu he causaly from he oose sde was weak. The resuls aaned by Toda and Yamamoo s echnque also confrmed ha economc growh causes domesc savngs n Paksan. Budhedeo (2012) aemed o emrcally examne he growh-savng relaonsh n Inda for deermnng he causal lnkages beween he wo usng annual daa for over sxy years of he lanned economc era. In hs sudy, Budhedeo examned he causal relaonsh beween growh rae of savng and economc growh rae usng he un roo es and Wald s F sasc for Granger causaly esng. The emrcal resuls revealed ha here s absence of any causal relaonsh beween savng growh raes and economc growh raes n eher drecon for Inda and hence he wo varables are ndeenden of each oher. 3. Daa and Mehodology To allow for causaly and dynamcs and gven ha no all of our me-seres may be saonary o he same order (some are I(0) whle ohers are I(1)), he conegraon echnque suggesed by Pesaran e al. (2001), he auoregressve dsrbued lag model (ARDL) rocedure wll be used. The aroach can be mlemened regardless of wheher he varables are Page 41

4 Inernaonal journal of advanced scenfc and echncal research Issue 2 volume 6, December 2012 Avalable onlne on h:// ISSN negraed of order (1) or (0) and can be aled o small fne samles. Based on emrcal leraure, heores of economc growh, and dagnosc ess, he long run relaonsh beween economc growh and savngs can be secfed as: ln RGDP 1 ln GDS 2 ln L 3 ln OILREV 4SER u 0 (1) Where RGDP s GDP a consan rce, GDS s gross domesc savngs, L s labor force, OILREV s real ol revenues, SER s he secondary enrolmen rao and roxes for he qualy of human caal. s an saonary error erm. All varables exce SER are exressed n naural logarhm (ln sands for logarhm). The man sources of varables are from he Cenral Bank of Iran (CBI) and Sascal Cener of Iran (SCI). The me erod of he sudy s over he years 1970 o To examne long run relaon among he seres we mlemen ARDL bounds esng aroach o conegraon develoed by Pesaran e al., (2001). The bounds esng aroach has several advanages: ales rresecve of he order of negraon for ndeenden varables, I(0) or I(1); s beer sued o small samles; and a dynamc error correcon model (ECM) can be derved from he ARDL model hrough a smle lnear rearamerzaon. The verson of error correcon model of ARDL aroach s gven by: ln RGDP 0 ln OILREV ln L 3 1 ln OILREV ln RGDP 1 ln SER 1 5 SER 0 ln GDS ln RGDP ln GDS (2) 2 ln L Where,,, and refer o shor run and 1 o 5 o long run arameers. The null hyohess of no conegraon s H 0 : δ 1 = δ 2 = δ 3 = δ 4 = δ 5 = 0 agans he alernave hyohess H 1 : δ 1 δ 2 δ 3 δ 4 δ 5 0. The rejecon of he null based on he F-sasc suggess conegrang relaonsh. The crcal bounds have been abulaed by Pesaran e al. (2001). The uer crcal bound (UCB) s based on he assumon ha all seres are I(1). The lower bounds (LCB) ales f he seres are I(0). If UCB s lower han he calculaed F-sasc, he null of conegraon s susaned. If he F-sasc s less han he LCB hen here s no conegraon. The decson abou conegraon wll be nconclusve f he F-sasc les beween UCB and LCB. In such suaon, we wll have o rely on he lagged error correcon erm o nvesgae long run relaonsh. The orders of he lags n he secfcaon (2 are seleced by he Schwarz Bayesan creron (SBC). For annual daa, Pesaran and Shn (1999) recommended choosng a maxmum of 2 lags. From hs, he lag lengh ha mnmzes SBC s seleced. If a long run relaonsh exss, he ARDL reresenaon of equaon (1) s formulaed as follows: ln RGDP 1 1 SER ln RGDP 1 (3) 1 0 ln GDS ln L ln OILREV 1 Page 42

5 Inernaonal journal of advanced scenfc and echncal research Issue 2 volume 6, December 2012 Avalable onlne on h:// ISSN k The ARDL mehod esmae ( 1),number of regressons n order o oban he omal lags for each varable, where +1 s he maxmum number of lags o be used and k s he number of varables n he equaon (Shresha and Chowdhury, 2005). The model s seleced based on he Schwarz-Bayesan Creron (SBC) ha use he smalles ossble lag lengh and s herefore descrbed as he arsmonous model. The ARDL secfcaon of shor run dynamcs s nvesgaed usng ECM verson of ARDL model of he followng form: ln RGDP 0 SER ECM ln RGDP ln GDS 2 (4) 0 ln L 2 0 ln OILREV The lagged resdual erm (ECM) n equaon 4 shows he dsequlbrum n long renrelaonsh (u n equaon 1). The goodness of f for ARDL model s checked hrough sably ess such as cumulave sum of recursve resduals (CUSUM) and cumulave sum of squares of recursve resduals (CUSUMSQ). 4. Emrcal Resuls Pesaran e al. (2001) crcal values are based on he assumon ha he varables are negraed of order I(0) or I(1). Un roo ess nsure ha none of he seres s negraed of I(2) or hgher. Boh he augmened Dckey Fuller (ADF) (1979) and Phlls Perron (PP) (1988) unroo ess have been emloyed for ha urose and he resuls are summarzed n Tables 1. Tes for saonary shows ha all varables are negraed of order 1 and hus saonary n dfference. 2 Table 1: Un Roo Tes ADF es sasc (wh rend and nerce) PP es sasc (wh rend and nerce) Varables Level Frs Dfference Level Frs Dfference ln RGDP ** ** ln GDS ** ** ln L ** ** ln OILREV *** *** SER *** *** Noes: ** and *** denoesgnfcancy a 5% 1% levels resecvely.the omal lag srucure s deermned by SBC Page 43

6 Inernaonal journal of advanced scenfc and echncal research Issue 2 volume 6, December 2012 Avalable onlne on h:// ISSN To nvesgae he resence of long-run relaonshs among he varables, esng of he bound under Pesaran, e al. (2001) rocedure s used. The resuls of he bound es are gven n Table 2. The crcal values used n hs aer are exraced from Narayan (2004). The calculaed F-sascs s 6.19 whle uer crcal bound a sgnfcance level 1% s Ths mles ha here s long run relaonsh among GDP, GDS, ol revenues, labor force and educaon over he erod of n Iran. Table 2: Bounds Tes Resuls F-sascs Lag Sgnfcance Level Bound Crcal values I(0) I(1) % % % The nex sage of he rocedure would be o esmae he coeffcens of he long-run relaons and he assocaed error correcon model (ECM) usng he ARDL aroach. The omal lags on varables were seleced by he Schwarz Bayesan Creron (SBC) and urned ou o be he ARDL (1, 0, 1, 1, 1). The long-run esmaed coeffcens are shown n he Table 3. As can be seen, all he coeffcens are sgnfcan. One ercen rse n GDS s execed o ncrease GDP er caa by jus 0.22 ercen. Alhough GDS aears wh he execed osve sgn and sgnfcan, bu he coeffcen s small n sze. The labor force and he qualy of human caal have been he man ngredens for economc growh. The varable of ol revenues has also he execed osve sgn. Table 3. Esmaed long run coeffcens based on ARDL aroach Regressor Coeffcen -value consan ln GDS ln L ln OILREV SER The resuls of error correcon model, reored n Table 4. The shor-run coeffcens are less han he long-run ones. The resuls sugges ha he shor-run mac of savngs and human caal on he economc growh are small and nsgnfcan. The coeffcens for he oher exlanaory varables have he execed sgn and are sgnfcance. Moreover, he coeffcen of he ECM s negave and srongly sgnfcan a 1% level. Ths corroboraes he exsence of a Page 44

7 Inernaonal journal of advanced scenfc and echncal research Issue 2 volume 6, December 2012 Avalable onlne on h:// ISSN sable long-run relaonsh and ons o a long-run conegraon relaonsh among varables. The ECM reresens he seed of adjusmen o resore equlbrum n he dynamc model followng a dsurbance. The coeffcen of he ECM s around -0.68, mlyng ha a devaon from he long-run equlbrum s correced by 68% afer each year. The dagnosc ess e.g., Lagrange Muller (LM) for seral correlaon, ARCH effecs, normaly of resdual erms, whe heeroskedascy and Ramsy RESET for funconal form reored n Table 5 sugges ha he shor-run model asses all dagnosc ess. We fnd no evdence of seral correlaon, auoregressve condonal heeroskedascy and whe heeroskedascy. The resdual erms are normally dsrbued and he funconal form of he model aears well secfed. Table4. Error correcon reresenaon for he seleced ARDL model Regressor Coeffcen -value ln GDS ln L ln OILREV SER ECM Seral Correlaon LM = 0.72 (0.69) ARCH Tes = 0.21 (0.89) Normaly Tes = 1.31(0.51) Heeroscedscy Tes = 0.91 (0.60) Ramsey RESET Tes = 1.46 (0.42) Noes: The robably values for he dagnosc ess are gven n arenhess The los of he cumulave sum of recursve resduals (CUSUM) and cumulave sum of squares of recursve resduals (CUSUMSQ) sably ess as shown resecvely n fgures 1 and 2 ndcae ha all he coeffcens of esmaed model are sable over he sudy erod as hey fall whn he crcal bounds CUSUM 5% Sgnfcance Page 45

8 Inernaonal journal of advanced scenfc and echncal research Issue 2 volume 6, December 2012 Avalable onlne on h:// ISSN CUSUM of Squares 5% Sgnfcance 5. Concluson Ths aer has nvesgaed he deermnans of economc growh wh an emhass on he effecs of savngs n Iran usng annual daa for he erod alyng auoregressve dsrbued lag (ARDL) aroach. Accordng o he resuls, we found a conegraon relaonsh among real GDP, savngs, labor force, ol revenues and educaon. Esmang error correcon model revealed ha he seed of adjusmen o resore equlbrum s whch confrms ha here s a sable long-run relaonsh. Comared o he oher varables, labor force and human caal have he mos moran effec on economc growh n long-run. In shor-run, however, he varables of savng growh and educaon do no have sgnfcan effecs on economc growh, exlanng jus a small ar of economc growh. Bu he labor force and ol revenues aear o lay a more moran role n shor-run growh. Therefore, does no seem ha savngs would conrbue o economc growh arculary n shor-run. Wh regard o he moran mac of labor force and human caal on economc growh, ranng sklled labor and rofessonals n varous secors of he economy and ncreasng labor roducvy can be an essenal se n order o smulae hgher long-run growh. In hs regard, s necessary o develo some arorae olces. The resuls show ha ol revenue has a more moran role n economc growh han savngs. To acheve susanable growh n he fuure, gven he hgh deendence of Iran economy on ol revenues, mus ake olcy measures ha subsanally enlarge and dversfy her economc base. Acknowledgemens The auhors would lke o acknowledge he fnancal suor of unversy of Tehran for hs research under he gran number /1/18. Page 46

9 Inernaonal journal of advanced scenfc and echncal research Issue 2 volume 6, December 2012 Avalable onlne on h:// ISSN References 1. Abu, N Savng-Economc Growh Nexus n Ngera, : Granger Causaly and Conegraon Analyses, Revew of Economc and Busness Sudes 3 (1), Agrawal, S., & Sahoo, P., Savngs and Growh n Bangladesh, The Journal of Develong Areas 42 (2), Andersson, B., On he Causaly Beween Savng and Growh: Long- and Shor Run Dynamcs and Counry Heerogeney, Workng Paer Seres 1999:18, Usala Unversy, Dearmen of Economcs. 4. Budhedeo, Sh. H., Savng and Economc Growh n Inda: A Granger Causaly Analyss, Asan Journal of Research n Busness Economcs and Managemen 2 (9). 5. Dckey, D.A., & Fuller, W.A., Dsrbuon of he Esmaors for Auoregressve Tme Seres wh a Un Roo, Journal of he Amercan Sascal Assocaon 74, Narayan, P., & Syab, S. A., An Emrcal Invesgaon of The Deermnans of Oman s Naonal Savngs, Economcs Bullen 3 (51), Nwachukwu, T. E., & Egwakhde, F. O., An Error-Correcon Model of he Deermnans of Prvae Savng n Ngera, Afrcan Economc Socey (AES) Conference, Cae Town, Souh Afrca, July Pesaran, M. H., & Pesaran B., Workng wh Mcrof 4.0: Ineracve Economerc Analayss New York: Oxford Unversy Press. 9. Pesaran, M.H., Shn, Y., & Smh, R.J., Bounds Tesng Aroaches o The Analyss of Level Relaonshs, Journal of Aled Economercs 16, Phlls, P.C.B., & Perron, P., Tesng for a Un Roo n Tme Seres Regresson, Bomerca 75, Sajd, G. M., & Sarfraz, M., Savngs and Economc Growh n Paksan: An Issue of Causaly, Paksan Economc and Socal Revew 46 (1), Romm, A. T., The Relaonsh beween Savngs and Growh n Souh Afrca: An Emrcal Sudy, The Challenge of Growh and Povery: The Souh Afrcan Economy Snce Democracy, Unversy of he Wwaersrand. 13. Shahbaz, M., & Al Khan, R. E., Old Wne n New Boles: Savng Growh Nexus: Innovave Accounng Technque n Paksan, Theorecal and Aled Economcs 7(548), Tang, T., Jaanese Aggregae Imor Demand Funcon: Reassessmen from Bound Tesng Aroach, Jaan and he World Economy 15 (4), Page 47