Relationship between education and GDP growth: a mutivariate causality analysis for Bangladesh. Abstract

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1 Relaioship bewee educaio ad GDP growh: a muivariae causaliy aalysis for Bagladesh Tariq Saiful Islam Deparme of Ecoomics, Rajshahi Uiversiy Md Abdul Wadud Deparme of Ecoomics, Rajshahi Uiversiy Qamarullah Bi Tariq Islam Deparme of Ecoomics, Rajshahi Uiversiy Absrac This paper uses he mulivariae causaliy aalysis o examie relaioship bewee educaio ad growh i Bagladesh usig aual ime series daa from 976 o 003. Rece research works have preferred mulivariae o he bivariae approach as he former is hough o be more geeral ha he laer. Besides growh ad educaio whose relaioship we examied, wo oher variables icluded i our aalysis are capial ad labour. The empirical resuls show evidece of bidirecioal causaliy bewee educaio ad growh i Bagladesh. Ciaio: Islam, Tariq Saiful, Md Abdul Wadud, ad Qamarullah Bi Tariq Islam, (007) "Relaioship bewee educaio ad GDP growh: a muivariae causaliy aalysis for Bagladesh." Ecoomics Bullei, Vol. 3, No. 35 pp. -7 Submied: February 6, 007. Acceped: Augus 0, 007. URL: hp://ecoomicsbullei.vaderbil.edu/007/volume3/eb-07c3000a.pdf

2 Relaioship bewee educaio ad GDP growh: a muivariae causaliy aalysis for Bagladesh Tariq Saiful Islam, Md Abdul Wadud * ad Qamarullah Bi Tariq Islam Deparme of Ecoomics, Rajshahi Uiversiy Rajshahi 605, Bagladesh Absrac: This paper uses he mulivariae causaliy aalysis o examie relaioship bewee educaio ad growh i Bagladesh usig aual ime series daa from 976 o 003. Rece research works have preferred mulivariae o he bivariae approach as he former is hough o be more geeral ha he laer. Besides growh ad educaio whose relaioship we examied, wo oher variables icluded i our aalysis are capial ad labour. The empirical resuls show evidece of bidirecioal causaliy bewee educaio ad growh i Bagladesh. JEL Classificaio: C3 ime series models Keywords: Grager causaliy; GDP; Educaio; Bagladesh. Iroducio Deiso (967) was oe of he firs o lay imporace o ivesig i educaio, which was hough o have impac o growh ad developme. Ivesme i educaio ca ehace growh ad developme by ecouragig aciviies ha ca help cach up wih foreig echological progress (Berhelemy ad Varoudakis, 996). Rece empirical sudies of educaio ad growh, paricularly hose usig causaliy aalysis, have geeraed diverse resuls. Behabib ad Spiegel (994) foud ha improved level of educaio posiively affeced growh i Chiese Taipei while Berhelemy e al. (996) came ou wih a differe resul. Fracis ad Iyare (006) foud evidece of bidirecioal causaliy for Jamaica ad evidece of causaio ruig from icome o educaio for Barbados, ad Triidad ad Tobago. So, i ca be said ha empirical resuls o causaliy bewee educaio ad growh have bee mixed ad more resuls, based o improved mehodology, ca help clear he issue. Mos causaliy sudies used he bivariae approach. A rece developme has bee he use of he mulivariae approach ha is expeced o shed a more accurae ligh o he issue. I hese sudies, variables oher ha hose whose causaliy is sudied are icluded. Foremos amog hese are capial ad labour, which are hough o provide logisic suppors o he variables whose causaliy is esed. Also, ay subsiuio bewee capial ad labour, which is very likely, ca affec he relaioship bewee educaio ad GDP. Hece, iclusio of capial ad labour, as see i equaios (3) ad (4) below, which augmes hese causaliy equaios is very perie. To our kowledge, i sudies of relaioship bewee educaio ad GDP, here has bee o applicaio of he mulivariae approach, which icluded capial ad labour. Hece, our paper, which adops he mulivariae causaliy aalysis ca be regarded as more geeral ha he previous bivariae sudies. * Correspodig auhor. wadud68@yahoo.com

3 I is worhwhile o meio wo higs. Mos of he earlier sudies ivolved developed ecoomies, while our sudy is o a developig ecoomy ha has see cosiderable ad seady icrease i he expediure o educaio. I is ecessary o see wheher our resuls agree wih, or differ from, hose obaied for he developed couries. Also, he resuls of our sudy ca be compared wih he esimaes ha will be obaied for oher developig ecoomies by researchers i fuure. The secod poi relaes o some impora aspecs of coiegraio ad causaliy sudy. This refers o he use of vecor auoregressive (VAR) ad vecor error correcio model (VECM). The VAR model esseially suggess a shor ru relaioship bewee he variables. This shorcomig ca be avoided if VECM, which ca geerae log-ru relaio, is used. So, our resuls refer o he log-ru.. Variable defiiios, daa sources ad graphical represeaio I his sudy, we use aual ime series daa of real GDP, expediure o educaio, capial, ad labour of Bagladesh for he period 976 o 003. Here, expediures o educaio referred o aual expediures ad are o a measure of he level of huma capial. These were obaied from various issues of he Saisical Yearbook of Bagladesh, which is a publicaio of he Bagladesh Bureau of Saisics. Idexes were prepared by us. These daa i a idexed form wih base year 976 are show i Figure. I ca be see ha from 976 o 984 he level of all four variables remaied almos he same. Afer 984, excep labour which grew very slowly, oher variables picked up. GDP icreased more ha labour. Growh i educaioal expediure was very cosiderable. The highes level of growh is see i case of capial Figure : Idex of real GDP (GDP), capial (K), labour (L), educaio (ED) from 976 o 003 (976 = 00) Idex of GDP, K, L ad ED GDP K L ED Years

4 3. Empirical Sudy Our empirical sudy cosiss of he ui roo ess, he coiegraio es ad, fially, he Grager causaliy ess. These are give below. 3.. Ui roo ess The augmeed Dickey-Fuller es is used o es for he exisece of ui roos ad deermie he order of iegraio of he variables. The ess are doe boh wih ad wihou a ime red. Akaike mehod is used o choose he opimal lag legh, which is foud o be for all variables. I ca be see i Table ha presece of a ui roo, which idicaes osaioariy, cao be rejeced for levels of he variables a he 5% sigificace level. I was also foud ha i could o be rejeced for he firs differece. However, he osaioariy problem vaished afer secod differece. Table : Augmeed Dickey-Fuller Ui Roo Tes Variable Lags Wih a ime red Wihou a ime red Tes saisics Criical values Tes saisics Criical values GDP K L ED GDP K L ED Noe: GDP deoes real GDP; K, capial; L, labour; E, eergy;, secod differece operaor. Criical values (5%) are from MacKio (99). Firs differece values are o repored, as saioariy could o be achieved he. 3.. Coiegraio ess The maximum likelihood esimaio mehod of Johase ad Juselius (990) is used o es for coiegraio. Gozalo (994) provided Moe Carlo evidece ha Johase-Juselius mehod performed beer ha ohers accordig o differe crieria. We firs cosider a VAR model give by Z = δ + Π Z Π k Z k + ε, =,,,T () The correspodig VECM ca be wrie as: Z = δ + Γ + Z Γk Z k + + ΩV ε () where V is he lagged level EC erm, 3

5 [ GDP K L E D] Z =, Γ i = + Π Π i, i =,...,k, Π = Π... Π k, deoes he firs differece operaor, δ is he iercep erm ad ε is whie oise. A examiaio of he Π marix eables us o deec exisece of coiegraig relaios amog he Z variables. The mos ieresig case is 0< rak (Π)= r < p. This implies ha here are r coiegraig relaios amog he eleme of Z, ad here are p r marices α ad β such ha Π = α β. Here α is a marix of error correcio parameer ad β is ierpreed as a marix of coiegraig vecors, wih he propery ha β Z is saioary, eve hough Z iself is osaioary. The resuls of he coiegraio ess are repored i Table. The opimum lag legh is foud o be oe, which is obaied by usig Akaike Iformaio Crierio. Criical values are ake from Oserwald-Leum (99). Boh eigevalue ad race ess are coduced, which geerae same resul. Table : Coiegraio Tes Maximum eigevalue es Wihou a red Wih a red Variables Coiegraio rak Tes saisics Criical values Tes saisics Criical values GDP K L ED r = r Trace es GDP K L ED r = r I Table, i ca be see from he maximum eigevalue es for wih ad wihou red ha esimaed es saisics is less ha he criical value for r = 0. This meas ha he hypohesis of o coiegraio is rejeced. To fid he umber of coiegraig vecors we see ha for r, he esimaed es saisics is less ha he criical value, which meas ha here is oly oe coiegraig vecor. The coiegraig vecor is as follows: [ LGDP LED LK LL] =[ ] Similar resuls are oiced for he race es wih ad wihou a red Grager causaliy ess By he Grager Represeaio Theorem (Grager, 988) ad by focusig o educaio expediure ad GDP, Eq. () ca be rewrie as 4

6 GDP γ yi ED i + δ yi GDP i + = α + β ECT + λ K yi i yi L i ε y + θ + (3) ED γ ei ED i + δ ei GDP i + = α + β ECT + λ K ei i ei L i ε e + θ + Boh he capial ad labor equaios are omied because we are o sudyig causaliy bewee hese variables. However, hese variables appear o he righ had side of he GDP ad ED equaios (eqs. 3 ad 4). Thus, he variables capial ad labour augme he causaliy equaios which, i he case of bivariae aalysis, would o have bee here. As we foud he series o be coiegraed, here mus be eiher uidirecioal or bidirecioal Grager causaliy. Resuls are give i Table 3. (4) Table 3: Grager causaliy ess Depede variable ECT -saisic F-saisic. GDP -.06 ** ED ** Noe: ** idicaes sigificace a he % level. Usig a F-es, we fid bidirecioal log ru causaliy bewee educaio ad GDP because we cao rejec he ull hypoheses ha he coefficies o he ECTs are zero i boh he GDP equaio ad he educaio equaio. The coefficies o he ECTs i he GDP equaio ad i he educaio equaio are sigifica a he % level. We did a exercise usig cumulaive oals of expediures ad obaied he same resul, ha of bidirecioal causaliy bewee educaio ad GDP. Sice he four variables ha we cosidered sigificaly rose from 984, we redid he aalysis for he sub-sample afer 984. I ook hree differeces, which is raher uusual, o aai saioariy ad eve he coiegraio of he releva variables could o be achieved. Hece i ca be cocluded ha o log-ru relaioship bewee educaio ad growh could be esablished if our aalysis is cofied o he period The resul could be due o he shorer period ( ) we cosidered ad he larger umber of differeces, which reduced he degrees of freedom, we had o ake. 5

7 4. Coclusios I his paper, we examied he causal relaioship bewee educaio ad icome (GDP) growh for Bagladesh over he period usig a mulivariae approach. The relaioship bewee icome ad educaio ca ake hree forms. Icome ca cause educaio o grow, hese ca help each oher o grow or educaio ca cause icome o grow. I appears ha Bagladesh is i he secod sage where icome ad educaio are helpig each oher o grow. Our resuls show ha here is bidirecioal causaliy ruig from GDP o educaio ad vice versa. This resul coradics may earlier sudies which foud uidirecioal causaliy ruig eiher from educaio o growh or growh o educaio, bu i is cosise wih he prevailig siuaio i Bagladesh where GDP growh ad educaioal expediure are workig i adem. There are several aspecs of his paper ha may be of ieres o he researchers workig i his area. Applicaio of he mulivariae causaliy aalysis usig he VECM framework makes he resuls of his paper more geeral. I he area of research sudyig causaliy bewee educaio ad growh, especially i he developig ecoomy, hese resuls ca provide a bechmark of compariso for fuure research work. Refereces Behabib, J. ad M.M. Spiegel, (994), The role of huma capial i ecoomic developme evidece from aggregae cross-coury daa, Joural of Moeary Ecoomics, 34 (), Ocober. Berhelemy, G.C. ad A. Varoudakis, (996), Policies for ecoomic ake-off, Policy Brief o, OECD, Paris. Deiso, E. (967), Why growh raes differ?, The Brookigs isiuio, Washigo, D.C. Fracis, B. ad S. Iyare (006), Educaio ad developme i he Caribbea: a coiegraio ad causaliy approach, Ecoomics Bullei, 5 (), -3. Gozalo, J., (994), Five aleraive mehods of esimaig log-ru equilibrium relaioships. J. Ecoomerics 60, Grager, C.W.J., (988), Some rece developmes i a cocep of causaliy. J. Ecoomerics 39, 99-. Johase, S., Juselius, K., (990), Maximum likelihood esimaio ad iferece o coiegraio wih applicaios o he demad for moey. Oxford Bull. Eco. Sa. 5, MacKio, J., (99), Criical values for coiegraio ess. I: Egle, R.F., Grager, C.W.J. (Eds.), Log-ru Ecoomic Relaioships: Readigs i Coiegraio. Oxford Uiversiy Press, New York, pp Oserwald-Leum, M., (99), Pracioers corer a oe wih quariles of he asympoic disribuio of he maximum likelihood coiegraio rak es saisics. Oxford Bullei of Ecoomics ad Saisics, 54,