The Macroeconomic Impact of Defense Expenditure on Economic Growth of Pakistan: An Econometric Approach

Transcription

1 Asian Social Science; Vol. 10, No. 4; 2014 ISSN E-ISSN Published by Canadian Cener of Science and Educaion The Macroeconomic Impac of Defense Expendiure on Economic Growh of Pakisan: An Economeric Approach Muhammad Haseeb 1, Nor' Aznin Abu Bakar 1, Muhammad Azam 1, Sallahuddin Hassan 1 & Nira Hariyaie Harani 2 1 School of Economics Finance and Banking, College of Business, Universii Uara Malaysia, Malaysia 2 School of Governmen, COLGIS, Universii Uara Malaysia, Malaysia Correspondence: Muhammad Haseeb, School of Economics Finance and Banking, College of Business, Universii Uara Malaysia (UUM), Sinok 06010, Kedah, Malaysia. Tel: scholar_economis@yahoo.co.uk Received: November 14, 2013 Acceped: December 29, 2013 Online Published: January 26, 2014 doi: /ass.v10n4p203 URL: hp://dx.doi.org/ /ass.v10n4p203 Absrac The broad objecive of he presen sudy is o examine wheher a long run relaionship beween defense expendiure and economic growh of Pakisan exis. For empirical invesigaion, an annual ime series daa over he period from , and ARDL was used. The empirical resuls suppor he exisence of long run negaive relaionship beween defense expendiure and economic growh. The resuls for long run negaive relaionship beween defense expendiure and economic growh was suggesed jus in case Pakisan MKH does no hold during he period under sudy. The findings furher suggesed ha he policy makers need o formulae appropriae policy o encourage and no o discourage he economic growh and developmen of Pakisan. Keywords: defense expendiure, economic growh, ARDL, Pakisan 1. Inroducion The relaionship beween defense expendiure and economic growh has araced considerable ineres which has been highly debaed among researchers. The miliary spending is a global issue and he purpose of increasing defense expendiure is mainly o cooperae wih local insecuriy and arm race. Moreover, developed counries have focus on he poin abou possible harmful effecs of unfeered miliary expendiure in developing counries. I was argued ha miliary expendiures may lead o problem of balance of paymen defici, decrease in economic growh, and as a resul imporan social and economic expendiure may crowd ou. In general, resuls of previous sudies were inconsisen and mix. Hassan e al. (2003) saed ha defense expendiure can affec posiively hrough an increase in securiy or expansion of aggregae demand and affec negaively hrough crowd ou invesmen. In case of developed counries, increase defense spending is negaively relaed wih economic growh, employmen and invesmen (Ram, 1995; Wilkins, 2004; Pradhan, 2010). In case of developing counries, he siuaion is unclear and complex. Wha is he effec of defense expendiure on developmen? There have been numerous aemped o answer his quesion since he seminal work of he Benoi (1978). Before he sudy of Benoi (1978) abou Growh and defense in developing counries, he issue of defense spending in developing counries was no highly debaable among he researchers. Hence, here is a common presumpion ha he defense expendiure is a burden on he economy and is negaively relaed o he economic growh. As a classical example, he pioneer sudy by Benoi (1978) eniled Bread vs. Guns can be considered. Benoi (1978) argued ha counries wih heavy defense burden show high growh rae and counries wih low defense burden show low growh rae. His argumen is based on a cross secional sudy of 44 developing counries. Therefore, he sudy simulaed he researchers o furher invesigae and find ou he relaionship beween miliary spending and economic growh. Pakisan needs o acquire and mainain a high GDP growh by spending more on developmen. The daa shows ha during , average GDP was esimaed a 5.06 which is very low as compare o oher Asian counries, such as Malaysia, Singapore, Thailand, Iran and India. The highes GDP growh (9.0 percen) was recorded in 2005, while he lowes GDP growh (1.7 percen) was recorded in 2009 (Economic Survey of Pakisan, 2012, 2013). Despie of facing high inflaion, exreme povery rae, more unemploymen, energy crises, deb burden and many oher major socio-economic issues, Pakisan spen huge amoun on defense as an effor o 203

2 mainain credibiliy. Researchers claim ha Pakisan spen more on non-developmenal projecs as compared o developmenal projecs. Governmen of Pakisan spen during on average a 0.75 percen on healh, 0.54 percen on educaion, 4.30 percen on developmen and 4.88 percen on defense (Economic Survey of Pakisan, 2012, 2013). Figure 1 shows he rend of defense, developmen and healh expendiure of Pakisan. Pakisan is one of hose counries who have spen major par of heir budge on defense since independence Healh Defense Expendiure Developmen Expendiure Figure1. Defense expendiure, developmen expendiure and healh expendiure (percenage of GDP) Source: Economic Survey of Pakisan (various issues) Anoher imporan poin ha can be raised from Figure 1 is he raio of developmen expendiure. Researchers claim ha highly declining in developmen expendiure over he las fifeen years is due o high spending on defense. As compare o healh, educaion and developmen expendiure, he percenage of defense expendiure shows relaively a high rend. During GDP growh on average a 5.06 percen, saving percen and inflaion 8.80 percen (Economic Survey of Pakisan, 2012, 2013) was measured. As shown in Figure 1, from defense expendiure was high as compared wih developmen expendiure and healh expendiure. Broadly speaking in he presence of low lieracy rae, high deficiency of medical faciliies and oher basic necessiies, Pakisan spen 4.88 percen (on average, ) on defense which is almos 10 imes higher han healh and educaion expendiure. In 2012, healh expendiure on per person per annum was RS 514 or USD 5.3, which was very low as a resul of percen inflaion. The res of he paper is srucured as: secion 2 deals wih he review of lieraure. Secion 3 presens heoreical underpinning, mehodology, model specificaion and daa sources. Secion 4 explains he empirical resuls and finally, secion 5 repors he conclusion and policy implicaion. 2. Review of Lieraure The relaionship beween defense expendiure and economic growh is a highly debaable issue among he researchers. Differen economeric models were applied wih he specificaion of differen empirical as well as heoreical perspecive, o examine he relaionship beween defense expendiure and economic growh. By using differen models and variables, researchers have found differen resuls on he basis of srong evidence and analysis. The lieraure on he effec of miliary expendiure on economic growh show posiive, negaive and insignifican resuls. As shown in he resuls above, for convince and beer undersanding, i will be discussed in hree separae secions. 2.1 Posiive Effecs of Defense Expendiure on Economic Growh Various previous sudies suggesed posiive relaionship beween miliary spending and economic growh. For example, Khan (2004) finds ou relaionship beween miliary spending and economic growh in case of Pakisan. This sudy used co-inegraion echniques and Vecor Error Correcion Model (VECM). By using annual ime series daa from , we discovered a long run posiive relaionship beween defense expendiure and economic growh aking a case sudy of Pakisan. In addiion, Cuaresma e al. (2004) examine he non-linear effec of defense spending on economic growh for USA from The paper empirically invesigaed he defense-growh nexus using annual ime series daa and applies economeric echnique of hreshold regression. The sudy found empirical evidences for USA, ha he miliary expendiures do have a level-effec on economic growh. Defense spending have a posiive exernaliy effec on economic growh, bu prevails for a 204

3 higher level of defense spending a lower levels of his expendiure and a negaive exernaliy. The sudy was also suggesed wih a cross counry analysis o find a non-linear effec of he defense spending on economic growh. The main argumen of hese researchers demand is affeced based on he Keynesian Muliplayer effecs. An exogenous increase in miliary spending is caused by an increase in demand, if and only if demand increases uilizaion, hus growh, employmen and purchasing power also increases. As a resul, povery decrease, saving increase, invesmen increase and finally, economic growh increase. Rashid and Arif (2012) invesigaed he casual relaionship using uni roo es and panel co-inegraion in 14 developing counries from he period The resul suggesed ha miliary expendiure is an exogenous variable and i may affec economic aciviies in hese counries. One of he mos imporan argumens of hose researchers who find posiive relaionship beween defense expendiure and economic growh is he engagemen of miliary ino Research and Developmen (R&D). In a sudy, Anwar e al. (2012) used granger causaliy and Johansen co-inegraion ess on ime series daa from he period for Pakisan. The resuls were winessed for long run posiive relaionship beween defense expendiure and economic growh. 2.2 Negaive Effecs of Defense Expendiure on Economic Growh Mos researchers argued ha if low income counry have high defense burden, i mus be financed by borrowing, issuing of new noes, and cuing down on oher public expendiures. This siuaion causes he inflaion which decreases savings, invesmen and furher affecs he economic growh. Dunne e al. (2002) sudied he panel of 11 small indusrialized economies by using co-inegraion echniques followed by VECM, and an annual ime series daa from 1951 o The sudy found ha miliary expendiure have posiive impac on exernal deb, bu in real sense, miliary expendiure have negaive impac on he economic growh because mos developing counries which already face exernal deb impor arms by loan. Therefore, heir exernal deb increases more which furher affec he GDP growh. However, Smaldone (2006) suggesed in his sudy of Africa ha he relaionship beween defense expendiure and economic growh will be heerogeneous, complex and elusive, bu hink ha variaion can be explained by inervening variables. Heerogeneous means effec may be negaive, posiive or insignifican. I depends on he geopoliical, geographical and geo economic condiions of any counry, bu in he case of Africa, negaive effec end o be deeper and wider because Africa faces legiimacy problem, securiy crises and economic budgeary consrains. Furhermore, Dunne (2012) conribue o he debae on he economic effecs of miliary spending using a large cross-counry panel daa-se for As well as providing a relaively up o dae analysis, sub-groups are creaed ha allow he analysis o focus on groups of counries a differen income levels and Sub-Saharan Africa (SSA), an area which has seen a large number of damaging conflics. Esimaing he empirical growh model gives resuls ha show variaion across he sub-groups, wih he general picure of significan negaive shor-run effec and insignifican long-run effec of miliary burden on per capia GDP growh, no consisen across he differen income groups. In addiion, breaking down he SSA group ino hose involved in conflic and hose ha are no, provides some furher inriguing findings ha sugges he value of furher work on he impac of conflic on growh. Shahbaz e al. (2011) discovered a long run negaive relaionship beween defense spending and economic growh in for Pakisan. In anoher sudy, Shahbaz and Shabbir (2012) sudy he relaionship beween miliary expendiure and economic growh in case if Pakisan. They conclude ha here is long run negaive relaionship beween hese wo variables during he period In addiion, hese poins refer ha; he defense expendiure is an opporuniy cos, and he governmen budge consrains required ha an increase in miliary expendiure will be financed by he cuing down of oher public expendiures. 2.3 Insignifican Effecs of Defense Expendiure on Economic Growh Dunne and Uye (2009) sudied he impac of defense spending on economic growh for 103 counries, which was almos 39 percen of he whole world and he resuls were divided ino hree differen caegories. They sudied 63 cross counries in which 19 percen shows a posiive impac, 38 percen displays a negaive impac and 43 percen shows an insignifican resuls. So, he mos dominaed par shows an insignifican resul. Therefore, he sudy of he res 40 counries which refers o single or small group of counries found ha 20 percen counries show posiive, 37 percen show negaive and 45 percen show an insignifican impacs, hus in conclusion of all 103 counries, 20 percen show posiive, 37 percen show negaive and 44 percen show an insignifican resuls. Meanwhile, Habibullah e al. (2008) used ADF uni roo es for saionary, ARDL es for co-inegraion o find ou relaionship beween defense expendiure and economic growh in Asian counries from he period In case of Pakisan hey found defense spending and GDP are inegraed wih uni roo es and ARDL es shows he long run relaionship beween he wo variables. In addiion, Tahir and Sajid (1999) invesigaed he relaionship beween defense spending and economic growh in LDCs and Pakisan by using ganger causaliy es from he period 1996 o 1997.They suggesed a feedback relaionship in he case of 205

4 Pakisan, India and Iran. Meanwhile, Khan (2012) found ha miliarizaion in Pakisan is in-efficien and crowds ou privae secor aciviies. Furhermore, his sudy suggesed ha here is no evidence o suppor he claim ha miliary is more adminisraive, compeen and less corrup. Therefore, his presen sudy inends o conribue o he exising lieraure in four differen ways. Firsly, he sudy uses ARDL echnique which does no impose a priori resricion of exogenous variable, and of single co-inegraion relaion inheried in Granger causaliy approach used in earlier sudies (Noe 1). Secondly, he sudy incorporaes a whole secion o analyze hisorical changes and he possible deermining facors of defense spending in Pakisan. The sudy also akes ino accoun developmen expendiure no only o undersand underlying long-run relaion, if any, wih he defense expendiure, bu also is dynamics wih GDP growh. Thirdly, sudy uses he mos recen annual ime series daa and fourhly, i uses a more differen conrol variable as compared o oher sudies on Pakisan. 3. Theoreical Underpinning Miliary Keynesianism which focuses on defense spending as a componen of aggregae demand and on spillover effec of hese spending also explains he economic effec of defense expendiure. Increased aggregae demand due o high defense spending will add o he economy s oupu and generae employmen. Benoi (1978) suggess ha his Keynesian effecive demand can enhance he produciviy by lowering he resource cos, reducing unemploymen, and increasing profi. Thus, his will lif he invesmen rae which resul in growh wih a muliplier effec. 3.1 Mehodology To verify he relaionship beween defense expendiure and growh, he following regression model is used: GDP 0 1DF 2DV 3INF 4SAV (1) Where GDP = Gross Domesic Produc, DF = Defense Expendiure, DV = Developmen Expendiure INF = inflaion, SAV = saving and = error erm. Moreover, Time series mehod has been used in he empirical analysis. The sandard procedure of he ime series mehod involves he implemenaion of uni roo es and he esimaion of long run relaionship. Firs: Uni roo es is used o confirm wheher a variable is saionary, I (0) or non-saionary, I (1). There are wo main mehods for esing he saionary of each variable; Augmened Dickey-Fuller Tes (ADF) and Phillips Person Tes (PP). In his sudy, ADF mehod has been employed because his mehod is considered more useful as compared o DF and PP es. DF es may creae problem of auocorrelaion. Therefore, o ackle auocorrelaion problem, Dickey and Fuller (1981) developed anoher es called ADF es. Second: in second sep sudy analyze co-inegraion; here are differen mehods of analyzing long run relaionship among he variables. Over he pas decade, considerable aenion has been paid in empirical economics o es for he exisence of long-run relaionship, which uses co-inegraion echniques majorly. The mos reliable es o explore he long run relaionship is Auo Regressive Disribued Lag (ARDL) model popularize by Pesaran e al. (1999).This ineviably involves a cerain degree of pre-esing, hus inroducing a furher degree of uncerainy ino he analysis of long-run relaions. Bu hird esing procedure suiable for boh order I (0) or I (1). In order o es for he long run relaionship beween miliary expendiure and economic growh in his sudy, ARDL esing approach has been employed. This mehod is recenly used by Hirnissa e al. (2009). In fac, he procedure allows for differen long-run relaionships and shor-run dynamics and his is imporan for he esimaion of he equilibrium condiions. Thus, ARDL has various advanages. Firs, his echnique is able o examine he presence of shor run as well as long run relaionship beween dependen and independen variable. Second, i akes a sufficien numbers of lags o capure he daa generaing process in a general o specific modeling framework. Third, i provides robus resul in a small sample size. Since he sample size of his sudy is based on 35 observaions, hence his provides more moivaion o adop his model. Third: In hird sep, sudies apply bound esing procedure which involves hree sages. The firs sage is o esablish he exisence of a long run relaionship. This is based on Esimaing Error Correcion (ECM) models by aking GDP as an independen variable and hus he following unresriced ECM model is consruced. 206

5 Y 0 yy Y 1 xx Y i Y 1 i Y 1 i 1 i 0 (2) The second sep is o compue he F-es for esing he exisence of a long run relaionship. The H 0 for no co-inegraion amongs he variables in Equaion (2) is: H 0: δ 1 = δ 2 = δ 3 = δ 4 = δ 5 Agains he alernaive hypohesis ha no all of hese coefficiens are equal o zero: H 1 : δ 1 δ 2 δ 3 δ 4 δ 5 0 Pesaran (1999) provided wo ses of criical values of bound; one se assuming ha all he repressors are I (1), and anoher se assuming ha hey all are I (0). The H 0 of co-inegraion is rejeced if he calculaed F-es falls above he upper bound. If he compued F-es falls below he lower bound, hen he H 0 of co-inegraion canno be rejeced. Finally, he resul is inconclusive if i falls in beween he lower and upper bound. In such an inconclusive case, he order of inegraion, I (d) for he explanaory variables mus be known before any conclusion can be drawn (Pesaran, 1999). The hird sep is o compare he compued F-values in he second sep wih all upper and lower 90, 95 or 99 percen criical values bounds. Fourh: In sep four, sudies apply long run relaionship es. Considered GDP and DV are wo variables a mixure of I (0) and I (1). To esimae he ARDL bounds esing approach, firs do check if here is long run relaion beween hese variables by applying join significan on β 1 and β 2 in he Equaion (3) YGDP K i j GDP i j GDP j 1GDP 1 2DE 1 i 1 j 0 (3) Here k and i are calculaed from AIC and SIC mehod. Compare he F-Saisic value wih he criical values provided by Pesaran (1999). If he calculaed F-saisic is greaer han he upper bound criical value a provided independen variables and he specificaion of he long run relaion, i means here is long run relaion beween hese variables. If he calculaed F-saisic is lower han he lower bound, hen here is no co-inegraion. If F-saisics value is in beween lower and upper bound, hen he resuls are inconclusive. Therefore, if here is co-inegraion, hen long run relaion and shor run relaion using Equaion [4] and [5] are: GDP K i 1 GDP j i j 0 DE j j (4) GDP K i j GDP i jde j 1 i 1 j 0 (5) Here 0 > π > -1 and are saisically significan, oherwise his equilibrium will no have convergence. Fifh: In sep five, sudies apply CUSUM es which is used o check if here is an issue of recursive residuals in his model. 3.2 Daa This sudy is based on ime series secondary daa ranging from he period from 1975 o The daa have been aken from Handbook of Saisics on Pakisan Economy, a documen published by he Sae Bank of Pakisan wih he help of Federal Bureau of Saisic (FBS) and Federal Bureau of Revenue (FBR), and also he Economic Survey of Pakisan ( various issues) respecively. 4. Empirical Resuls 4.1 Descripive Saisics Resuls show ha in he period of maximum GDP 9.00 percen, defense expendiure 7.22 percen, 207

6 developmen expendiure 8.43 percen, inflaion percen and savings percen were recorded. Meanwhile, minimum GDP 1.70 percen, defense expendiure 2.3 percen, developmen expendiure 0.87 percen inflaion 3.10 and savings 9.66 percen were also recorded. Table 1. Descripive saisic of he variables Variable Mean Median Maximum Minimum S.D GDP DE DEV INF SAV Uni Roo Tes ADF ess are repored in Table 2; wih series in level are run wih consan and rend, while series in firs difference also run wih consan and rend. All he es of uni roo of hese variables -saisics corresponding o he parameer ρ = 0, he calculaed values are compared wih abulaed- values. The saisics shows ha all he variables are saionary. A level GDP, INF and SAV are saionary I (0) a 5% significance while DE and DV are non-saionary bu becomes saionary I(1) in firs difference a 5% significance value. Table 2. Resuls of ADF uni roo es Variable Level Firs Difference Inercep Inercep and rend Inercep Inercep and rend Decision GDP -4.49* I(0) DE ** I(1) DV ** I(1) INF -3.00* I(0) SAV -3.44* I(0) Noe: * Saionary a level and 5% criical value (-2.95) ** Saionary a firs difference and 5% criical value (-2.95) 4.3 Opimal ARDL Model Afer performing uni roo es, ARDL model was run o choose an opimal model of economic growh. The opimal model is chosen based on he lowes values of AIC and SBC. Afer running a couple of enaive ARDL models, he ARDL (2, 3, 0, 4, 4) model has been chosen because i has he lowes AIC ( ) and SBC ( ) values. The esimaion resuls of he opimal ARDL model are shown in Table 3. Table 3. Opimal ARDL (2, 3, 0, 4, 4) esimaion resuls Regressor Coefficien Sandard Error T-Raio Probabiliy GDP(-1) GDP(-2) DV DV(-1) DV(-2) DV(-3) DE INF INF(-1) INF(-2)

7 Regressor Coefficien Sandard Error T-Raio Probabiliy INF(-3) INF(-4) SAV SAV(-1) SAV(-2) SAV(-3) SAV(-4) C T R-Squared R-Bar-Squared S.E. of Regression F-sa. F(18, 13) Mean of Dependen S.D. of Dependen Residual Sum of Squares Equaion Log-likelihood Akaike Info. Crierion DW-saisic Schwarz Bayesian Crierion ARDL Bound Tes Resuls The F-es has a non-sandard disribuion which depends upon wheher variables included in he ARDL model are I (0) or I (1), and he number of regressors. Pesaran (1999) provides wo ses of criical value bound; one se assuming ha all regressors are I (1) and he oher are all I (0). Table 4 shows he upper and lower 90, 95 and 99 percen criical value bound. Table 4. Criical value bound K** 90% 95% 99% 4 I(0) I(1) I(0) I(1) I(0) I(1) Criical values* *The criical value bounds are from Table F, resriced inercep and no rend in Pesaran, 1999; **No. of regressors. The null hypohesis of no coinegraion is rejeced if he calculaed F-es falls above he upper bound. If he compued F-es falls below he lower bound, hen he null hypohesis of no co-inegraion canno be rejeced. Finally, he resul is inconclusive if i falls in beween he lower and upper bound. The calculaed F-ess are repored in Table 3. I shows ha all F-values are higher han upper bound criical values a he 10 percen significance level. Thus, he null hypohesis of no co-inegraion is rejeced. Therefore, i means all variables are co-inegraed o each oher. Table 5. F-ess for coinegraion Tes F-saisic Lag selecion F(GDP/DE, DV, INF, SAV) , 3, 0, 4, 4 F(DE/GDP, DV, INF, SAV) , 2, 0, 1, 2 F(DV/GDP, DE, INF, SAV) , 0, 0, 1, 0 F(INF/GDP, DE, DV, SAV) , 1, 0, 1, 2 F(SAV/GDP, DE, DV, INF) , 0, 0, 0, 0 209

8 4.5 Diagnosic Tes The robusness of he model has been confirmed by diagnosic ess for serial correlaion, funcion form, normaliy, heerscedasiciy and srucural sabiliy for he model. As shown in he Table 6, i generally passes all he diagnosic ess. These ess show ha here is no evidence of auocorrelaion in he disurbance of error erm. The ARCH es suggess he errors are homoscedasiciy. The model passes he Jarque-Bera normaliy es suggesing ha he errors are normally disribued. However, in he absence of model misspecificaion hypohesis, i fails a 5 percen level in he model. Pesaran e al. (1999) also face a similar problem. They argued ha i may be linked o he presence of some non-linear effecs or asymmeric in he adjusmen of he regress, and ha heir linear specificaion is incapable of aking i ino accoun. Hence, one possibiliy would be o swich o a non-linear model. Table 6. Diagnosic es ARDL (2, 3, 0, 4, 4) Tes H 0 Saisic p-value Decision SC HE There is no serial correlaion in he residual There is no auoregressive condiional heerscedasiciy. x 2 = Fail o rejec H 0 x 2 = Fail o rejec H 0 NO Normal disribuion JB = Fail o rejec H 0 FF Absence of model misspecificaion x 2 = Fail o rejec H Resuls of Long Run Relaionship The primary focus of his sudy is on he long run effecs of defense expendiure on economic growh. Thus, i is axiomaic ask o es for he co-inegraion of variables. Co-inegraion of a se of ime series implies ha long run saionary relaionship exised among he componen of non-saionary series. The co-inegraion echnique pioneered by (Hendry, 1986; Granger, 1986; Engle & Granger, 1987) provides an axiomaic foundaion of he mehodology. Thus, he empirical resuls for his model repored in Table 7, obained he depending GDP(Y) as he depending variable. Table 7. The esimaed long-run coefficiens resuls ARDL(2, 3, 0, 4, 4) Regressor Coefficien -Raio C DF * DV INF SAV ** Noe: *Negaively significan wih respec -value (-1.96); ** Posiively significan wih respec o -value (+1.96). The resuls of able 7 above indicae ha wo variables ou of four are significan. I means Pakisan defense expendiure is negaively relaed wih GDP growh, bu saving is posiively relaed wih GDP growh. In addiion, his resuls show ha for 1 percen increase in defense expendiure, here is a decrease in he GDP by 0.57 percen, and a one percen increase in saving, leads o an increase in he GDP by 0.73 percen. The resuls are similar o he finding of Looney (1995), Tahir & Sajid (1999) and Habibullah e al. (2008) ha defense spending negaively impac o he economic growh, bu also canno be used as macroeconomic 210

9 sabilizer. Thus, he finding of Khan (2004) and Aslam (2007) illusraed ha defense spending do no negaively impac o he economic growh. Those resuls are proof ha here is long run relaionship beween defense expendiure and economic growh, and Pakisan defense spending, negaively impac o he economic growh. In addiion, i is also proof ha he naional saving has a posiive impac on economic growh and he oher wo variables developmen expendiure and inflaion does no have a considerable impac eiher negaive or posiive on economic growh. 4.7 Sabiliy Tes The cumulaive sum (CUSUM) and he cumulaive sum of squares (CUSUMSQ) graphical are presened in Figure 2. This figure indicaes he absence of any insabiliy of he coefficiens because he plos of hese saisic remains wihin he criical bound of he 5 percen significan level. Hence, hese saisics confirm he sabiliy of long-run coefficien of he GDP funcion in he model Plo of Cumulaive Sum of Recursive Residuals The sraigh lines represen criical bounds a 5% significance level Figure 2(a). Plo of cumulaive sum of recursive residual 1.5 Plo of Cumulaive Sum of Squares of Recursive Residuals The sraigh lines represen criical bounds a 5% significance level Figure 2(b). Plo of cumulaive sum of recursive residual Therefore, he resul of his sudy is obained hrough he empirical invesigaion of he model. Mainly, empirical invesigaion is based on ARDL model bu some preliminary ess are also done o fulfill he assumpions of ARDL. Before applying ARDL, find ou he order of inegraion wheher he variables are saionary or no and furhermore, find ou he variables saionary a level I (0) or a firs difference I (1). Variables are achieved saionary, bu GDP, INF and SAV are saionary in level a five percen significan level and DE, DV are non-saionary a level and become saionary afer firs difference a five percen significan level. These resuls were obained by uilizing ADF uni roo es. In addiion, he resuls of co-inegraion (F-es) were shown ha all F-values are greaer han upper bound value a 10 percen significan level, and his signifies ha here is co-inegraion among all variable and he null hypohesis of no co-inegraion is rejeced. The exisence of co-inegraion opens up for furher invesigaion because if a ha poin here is no co-inegraion, hen his model canno be furher invesigaed. For furher invesigaion o achieve he ulimae goal which is o find ou he long run relaionship a his sage, we need o apply same es o confirm he heeroscedasiciy, srucural 211

10 sabiliy, serial correlaion and normaliy in he daa. Resuls of his sudy show ha all variables passes es hrough he diagnosic es. Resuls of long-run coefficien show ha ou of five variables (GDP, DE, DV, INF, and SAV); wo variables DE and GDP are saisically significan and have long run relaionship. I explains ha defense expendiure negaively impac on economic growh, whereas saving posiively impac on economic growh. Therefore, one (1) percen increases in defense expendiure cause 0.57 percen decrease in economic growh and one percen increase in saving cause 0.73 percen increases in economic growh. Finally, he resul of cumulaive sum of recursive residual (CUSUM) es shows ha here is no problem of recursive residual, which means ha he daa is sable. 5. Conclusion and Policy Implicaion The main objecive of his paper is o examine wheher here is long run relaionship beween defense expendiure and economic growh. To accomplish his, sudy used annual ime series daa from1980 o The ARDL approach is used for esimaion purpose. The resuls indicae he presence of long run relaionship; hus variables are saionary, co-inegraed and model is significan. Moreover, Pakisan defense expendiure is negaive and saving is posiively relaed wih GDP growh. Furhermore, here is no significan long run relaionship beween defense expendiure, developmen expendiure and inflaion. Thus, his evidence rejecs he common percepion ha he increase in defense expendiure causes a decrease in developmen expendiure. The resuls of he presen sudy sugges ha he popular percepion ha defense expendiure hurs economic growh seem o hold over he esimaion period, bu MKH does no hold in case of Pakisan. Furhermore, he resuls of his sudy suppor he argumens ha defense expendiure is an opporuniy cos. No doub defense is a vial elemen of naional securiy; however, policy makers should consider for economic, social, energy and oher elemens of naional securiy. References Anwar, M. A., Rafique, Z., & Joiya, S. A. (2012). Defense spending-economic growh nexus: A case sudy of Pakisan. Pakisan Economic and Social Review, 50(2), Benoi, E. (1978). Growh & Defense Spending in Developing Counries. Economic Developmen and Culural Change, 26, hp://dx.doi.org/ / Cuaresma, J., Crespo, D., & Gerhard, F. (2004). A non-linear defense growh nexus? Evidence from he US economy. Defense and Peace economics, 15(1), hp://dx.doi.org/ / Dickey, D. A., & Fuller, W. A. (1979). Disribuion of he Esimaors for Auoregressive Time Series wih a Uni Roo. Journal of he American Saisical Associaion, 74, Dickey, D. A., & Fuller, W. A. (1981). Likelihood Raio Saisics for Auoregressive Time Series wih a Uni Roo. Economerica, 49, hp://dx.doi.org/ / Dunne, J. P. (2012). Miliary spending, growh, developmen and conflic. Defense and Peace Economics, 23(6), hp://dx.doi.org/ / Dunne, J. P., & Uye. (2009). Miliary spending and developmen. Chaper in Tan, Andrew (forhcoming 2009) The Global Arms Trade. Europa/Rouledge (London). Rerieved from hp:// Dunne, J. P., Nikolaiduo, E., & Smih, R. (2002). Miliary spending, invesmen and economic growh in small indusrializing economies. The Souh African Journal of Economics, 70(5), Engle, R. F., & Granger, C. W. J. (1987). Co-inegraion and error correcion: Represenaion esimaion and esing. Economarica, 55(2), hp://dx.doi.org/ / Governmen of Pakisan. (2013). Economic Survey of Pakisan ( ), Economic Advisor s Wing, Finance Division, Islamabad-Pakisan. Habibullah, M. S., Law, S. H., & Dayang, A. M. (2008, December). Defense spending and economic growh in Asian economies: A panel error-correcion approach: Munich Personal RePEc Archive. MPRA Paper, Hassan, M. K., Waheeduzzaman, M., & Rahman, A. (2003). Defense Expendiure and Economic Growh in he SAARC counries. The Journal of Poliical, Social and Economic Sudies, 28(3), Hendry, D. F., Pagam, A. R., & Sargan, J. D. (1986). In S. Johansen (Ed.), Dynamic specificaion. Likelihood-based inference in co-inegraed vecor auoregressive models, Oxford: Oxford Universiy Press. 212

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