Impact of Debt on Primary Deficit and GSDP Gap in Odisha: Empirical Evidences

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1 S.R. No /2015/CEFT Impac of Deb on Primary Defici and GSDP Gap in Odisha: Empirical Evidences 1. Inroducion The excessive pressure of public expendiure over is revenue receip is financed hrough borrowing and his accumulaion of borrowing leads o boh financial and real burden on he people. I is because ha he presen borrowing is financed hrough fuure ax hence is called financial burden o he people. Furher, i is also observed ha he increasing level of axable income may cause adverse effecs on he willingness o work and save. This ype of effec is called he real burden of he public deb. Alhough here is revenue surplus of Rs crore in he FY (Finance Accoun, Gov. of Odisha), he Sae's revenue posiion sared deerioraing incurring revenue deficis coninuously. This widening level of revenue defici combined wih high level of fiscal defici forced he Gov. of Odisha o go for inernal deb. 2. Objecives The objecives of his sudy is o examine 2.1 The solvency aspec deb of Odisha by capuring he primary defici 2.2 The impac of deb on GSDP gap. GSDP gap is he difference beween poenial GSDP and acual GSDP. 3. Seleced Lieraures The lieraure in he conex of public deb has been carried ou in he case of India by auhors such as Venkaaraman (1968), Singh (1999), Rangarajan and Srivasav (2005), Kanan and Singh (2007), and Bal and Rah (2014) shows public deb has negaively affecs he economic growh 1 P a g e

2 in he long run. So far, no sudy on his aspec is made on Odisha. This moivae us o makes an aemp o examine he impac of deb specific o Odisha by aking Bohn (1998) framework. 4. Analyical Framework and Daa Sources Bohn (1998) framework suggess ha he primary surplus generaed on accoun of public deb is a sufficien condiion for solvency. This sudy has exended he Bohn framework by including GSDP gap. The poenial GSDP is calculaed hrough Hodrick-Presco (HP) filer. Since here is iner-relaionship among deb (DB), primary defici (PD) and GSDP gap (OG), Srucural VAR (SVAR) is used for our analysis. Our model is as follows: DB 1 PD 0 OG 0 b DB PD 1 0 b b DB OG PD og 1 DB PD OG (1) Where, DB PD and OG are he srucural impacs of public deb, primary defici and GSDP gap respecively. The 3 3 coefficien marix shows he srucural impacs of he resriced variables. All he daa are aken in real erms. The mehodology is explained in he annex. 5. Resuls & Analysis The firs sep is o know he saionary or non-saionary propery of he variables o avoid he spurious regression in ime series. Hence, ADF and PP es are conduced and he resuls show ha all he series are saionary a firs order difference. In he subsequen sep, he opimum lag selecion crieria are implemened hrough VAR model by following AIC, SC and HQ crieria. These crieria suggesed ha lag 2 is he opimum and VAR follows he sabiliy condiion. I indicaes ha here are no roos of he polynomial ouside of he uni circle and hence can be concluded ha VAR saisfy he sabiliy condiion in he model. In he nex sep, his sudy illusraed he dynamic relaion among hese variables in a srucural VAR wih long run resricion framework, and he resuls are presened in Table 1. 2 P a g e

3 Table 1: Srucural VAR Parameer Esimaes Parameer Coefficien Sd. Error P-Value 1.71 *** DB b PD DB b OG *** PD b OG Noe: *** indicaes significan a 1 percen level; DB = public deb; PD = primary defici; OG = GSDP gap. 5.1 The resuls from Table 1 show ha he impac of public deb on primary defici is significan and posiive. I indicaes ha higher public deb leads o higher primary defici. 1% rise of deb raio leads o 1.71% rise in he primary defici raio. This implies ha here were insolvency issues during he period of FY o FY The resuls from Table 1 also indicaes ha he impac of public deb on GSDP gap is negaive and saisical significan. This implies ha deb has a posiive impac on GSDP by reducing he gap beween poenial and acual GSDP. More specifically, 1% rise in deb raio reduces he GSDP gap by 2.79 %. 5.3 No conclusive resuls are found relaing o he impac of primary defici on GSDP gap. 5.4 In he nex sep, his sudy capures long erm relaionship among hese variables hrough impulse response funcion (figure 1 and 2). The fuure 10 year ime period is aken ino accoun o examine he relaionship..3 Fig. 1: Response of Primary Defici due o Shock of Deb P a g e

4 Fig.2: Response of GSDP gap due o Shock of Deb The figure 1 shows he response of primary defici raio on accoun of change in one sandard deviaion in deb raio. I will be negaive for coming five years bu i will have posiive effec (i will be primary surplus) in he nex 6 o 10 years The response of GSDP gap (figure 2) o one sandard deviaion change in deb raio indicaes he gap would come down in he beginning of he period and i will have a neuralized effec in subsequen years. 6. Policy Implicaions This sudy suggess an incremenal rise in deb raio for reducing he GSDP gap and improving he primary defici raio. The decline in GSDP gap will be achieved hrough higher economic growh and, generae more revenue for he Sae, which in urn, will improve he primary defici. 4 P a g e

5 References Bal, D. P. and Rah, B. N. (2014), Public Deb and Econoic Growh in India: a Reassessmen, Economic Analysis and Policy, Vol. 44, pp Bohn, H. (1998), The Behaviour of U.S. Public Deb and Deficis, The Quarerly Journal of Economics, Vol. 113(3), pp Kannan R, Singh, B. (2007), Deb-defici dynamics in India and macroeconomic effecs: a srucural approach, Munich Personal Repec Arch Available on he web: hp://mpra.ub.uni-muenchen.de/16480/. Mendoza, E.G. and Osry, J.D. (2008), Inernaional Evidence On Fiscal Solvency: Is Fiscal Policy Responsible?, Journal of Moneary Economics, Vol. 55(6), pp Rangarajan, C., Srivasav, D. K. (2005), Fiscal Deficis and Governmen Deb: Implicaions for Growh and Sabilizaion. Economic Poliical Weekly, Vol. 40, pp Singh, C. (1999), Domesic Deb and Economic Growh in India. Economic Poliical Weekly, Vol. 34, pp Venkaaraman,K. (1968), Saes Finances in India, George Allen and Unwin, London. 5 P a g e

6 Annex Mehodology The sudy use srucural vecor auo regression (SVAR) model by puing long run resricion because reduced VAR model does no allow us o esimae he impac of public deb on primary defici as well as GSDP gap. So, he VAR model is in presen conex appears as follows: y k x u (2) j1 j j Where, y = [DB, PD, OG,] /, η is a vecor associaed wih consan erm, and βj is a marix of VAR parameers for lag j, x-j is he 3 3 marix of he variables and u is whie noise disurbance erm. In he case of reduced VAR model he impac of one variable consequenly affec o all oher variables and hence i s difficul o assess he impac of a paricular variable on oher variable. Therefore he sudy akes SVAR model o show he impac of public deb (DB) on primary defici (PD) and GSDP gap (OG) by aking annual daa from FY o FY (in real erms). The main purpose of SVAR esimaion is o obain non-recursive orhogolizaion of he error erms for impulse response analysis. To idenify he long-run srucural impac, we chose he idenificaion of Blanchard and Quah (1989) long-run consrains 1. 1 This kind of resricion is applied only in he case of inegraed variable. 6 P a g e

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