Capital Flow Volatility and Exchange Rates: The Case of India. Pami Dua and Partha Sen 1, 2

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1 Capal Flow Volaly and Exchange Raes: The Case of Inda Pam Dua and Parha Sen, 2 Absrac Ths paper examnes he relaonshp beween he real exchange rae, level of capal flows, volaly of he flows, fscal and moneary polcy ndcaors and he curren accoun surplus for he Indan economy for he perod 993Q2 o 2004Q. The esmaons ndcae ha he varables are conegraed and each granger causes he real exchange rae. The generalzed varance decomposons show ha deermnans of he real exchange rae, n descendng order of mporance nclude ne capal nflows and her volaly (only), governmen expendure, curren accoun surplus and he money supply. A prelmnary analyss suggess ha a smlar analyss can be performed for he foregn exchange reserves held by he RBI. Acknowledgemens: The auhors are graeful o he parcpans of he Asan Developmen Bank semnar on Macroeconomc Managemen and Governmen Fnances held a he NCAER n Sepember Research Asssance from Mansha Goel and Suman Kumar Ra are also graefully acknowledged. Deparmen of Economcs,Delh School of Economcs,Unversy of Delh, Delh 0007,E-mal: dua@econdse.org; parha@econdse.org 2 Ths repor was prepared by consulans for he Asan Developmen Bank. The vews expressed n hs repor are he vews of he auhors and do no necessarly reflec he vews or polces of he Asan Developmen Bank (ADB), or s Board of Governors, or he governmens hey represen. ADB does no guaranee he accuracy of he daa ncluded n hs paper and acceps no responsbly for any consequence of her use.

2 . Inroducon The 990s wnessed an upsurge n nernaonal capal flows he world over. Ths was a consequence of several facors such as fnancal lberalzaon and nnovaons, spread of nformaon echnology and prolferaon of nsuonal nvesors. A noeworhy feaure of he ncreased flows o developng counres was ha prvae (equy and deb) flows raher han offcal flows became a domnan source of fnancng large curren accoun mbalances. Furhermore, equy flows ganed mporance compared o deb flows. A he same me, capal flows o developng counres have been very volale n he recen pas. Ths s evden from recen epsodes of fnancal crses such as he Eas Asan crss of , followed by he urmol n global fxed ncome markes. More recenly, he collapse of Argenna s currency board peg n 200 and he revelaon of accounng rregulares and corporae falures n he U.S. n 2002 have affeced capal flows. Agans hs backdrop of an ncrease n magnude and varably of capal flows, hs sudy examnes he mpac of changes n he levels and volaly of capal flows on he Indan exchange raes, whle accounng for oher facors ha have a poenal nfluence on he real effecve exchange rae (REER). Unl 973, he Indan rupee followed a fxed exchange rae regme wheren he rupee was pegged o he pound serlng. Wh he breakdown of he Breon Woods sysem n he early 970s, Inda swched over o a sysem of managed exchange raes. Durng hs perod, he nomnal exchange rae was he operang varable o acheve he nermedae arge of a medum erm equlbrum pah of he real effecve exchange rae. REER fell 3 conssenly beween and from o In early 990s, Inda was faced wh a severe balance of paymen crss due o he sgnfcan rse n ol prces, he suspenson of remances from he Gulf regon and several oher exogenous developmens. Amongs he several measures aken o de over he crss, was a devaluaon of he rupee n July 99 o manan he compeveness of Indan expors. Ths naed he move owards greaer exchange rae flexbly. A lberalzed exchange rae managemen sysem was pu n place n March 992 along wh oher measures o lberalze rade, ndusry and foregn nvesmen. The unfcaon of he exchange rae of he Indan rupee made marke deermned. From hen on, he foregn exchange marke exhbed orderlness excep for a few epsodes of volaly durng whch he Reserve Bank of Inda (RBI) ook seps o resore sably. Moreover, wh he gradual openng of he curren and capal accoun ransacons and he growng nvesor confdence, here was an ncrease n he volume of capal nflows. There were surges n capal nflows n , and he frs half of Ths, along wh robus expor growh, began pushng he exchange rae upwards. Begnnng wh , REER rose connuously and sood a 74.4 n he fnancal year Durng he decade of 980s ne capal nflows o Inda were almos neglgble and became a quany o be reckoned wh only onwards. From a low of Rs. 699 crores n , ne capal nflows umped o Rs crores n From hen on, excep for a few aberraons (durng ne capal nflows fell o Rs. 069 crores due o he Eas Asan crss and n , hey agan dpped o Rs crores whch can be arbued o he global economc slowdown), capal nflows have been mushroomng. The ne capal nflows ncreased from an average of abou Rs. 200 crores durng he 980s o an average of over Rs. 2,000 crores durng he 990s. Whle n , ne capal nflows amouned o Rs crores, he fgure ncreased over fve mes o reach Rs crores n The composon of capal nflows also changed markedly. Inflows n he form of foregn drec nvesmen (FDI), porfolo nvesmen, exernal commercal borrowngs, non-resden deposs and socal depos schemes domnaed he capal accoun and he dependence on ad was nearly elmnaed. Ths s agan a reflecon of he growng confdence among nernaonal nvesors n Inda as ncreasngly lberalzed s polces. FDI o Inda whch sood a a low level 3 The defnon of REER used n hs paper s based on rade weghs. I s he weghed average of blaeral nomnal exchange raes of he home currency n erms of he foregn currences adused by domesc o foregn local-currency prces. Thus, a fall n REER mples deprecaon and an ncrease n he same mples apprecaon. The number of counres ncluded s 36.

3 of Rs. 837 crores durng , pcked up sgnfcanly hereafer and durng , sood a Rs. 2,463 crores; an average annual ncrease of over 00%. FII nflows o Inda sared only n (Rs.,445 crores) and snce hen have been on he rse. They oaled Rs. 5,998 crores durng Thus, over a span of en years, FII nflows ncreased by over four mes. Toal foregn nvesmen (FII+FDI) n Inda over he perod o accouned for over 55% of he oal ne capal nflows. Fgure 4 gves he relaonshp beween nomnal ne capal nflows agans REER for he perod o and clearly shows he rends dscussed above. I s evden from he fgure ha capal flows o Inda were near zero unl he begnnng of 990s and began o ncrease sgnfcanly only hereafer as he counry, wh s newly naed lberalzaon, ncreasngly provded aracve avenues o nves. A he same me, REER, whch fell beween and , also began o apprecae as a resul of ncreasng capal nflows and expor growh. The correlaon beween ne capal nflows and REER s as hgh as for he perod o In hs paper, robus economerc echnques are appled o Indan daa o examne he relaonshp beween capal flows, REER and foregn exchange reserves of he RBI for he perod 993Q2 o 2004Q. An earler sudy by Chakrabory (2003) dscusses he relaonshp beween capal flows and REER for Inda beween 993Q2 and 200Q. The sudy uses an unresrced VAR framework and he varables ncluded are, ne capal nflows (aggregae of FDI, porfolo nvesmen and exernal commercal borrowng), and rae of growh of domesc cred and rae of nflaon as proxes for moneary and fscal polces, respecvely. The paper concludes ha REER deprecaed n response o one sandard devaon nnovaon o foregn capal nflows. Ths concluson, ha s conrary o economc nuon, mgh be a resul of he weak economerc mehodology used n he paper. 5 Ths paper s dvded no he followng secons. Secon 2 descrbes he heorecal model. Secon 3 repors he economerc mehodology. The emprcal esmaes are repored n Secon 4. Secon 5 concludes he paper. Daa defnons and sources are repored n he appendx. 2. Theorecal Model To focus on he ssue of capal flows, we need a model of mperfec asse subsuably beween domesc and foregn asses. We absrac from he role of capal markes and nvesmen oo many hngs have changed n he ndusral srucure of he Indan economy o perm ncorporaon n a small macro model. So defne (as n Branson e.al. (977)) W M + B + ( F / E) P () where W s real wealh, M he nomnal money supply, B he supply of (all shor) governmen bonds, F s he ne foregn asses of he prvae secor, E s he nomnal exchange rae (here, he foregn currency prce of domesc currency an apprecaon of he rupee s a rse n E 6 ) and P s he prce level. We could have deflaed by a prce ndex, whch ncludes he foregn good prce also bu hs s probably no crucal o he emprcal sory. There are hree asses and by he balance shee consran, f wo of hese are n equlbrum, hen so s he hrd one. 4 Fgure measures Ne Capal Inflows by ne foregn nvesmen defned as he sum of ne foregn nvesmen n Inda (Drec + Porfolo) and ne foregn nvesmen abroad. 5 Marcelo and Hugo (2000) examne he long-run response of he real exchange rae o capal flows for Mexco. They conclude ha a once and for all un ncrease n he rao of quarerly capal nflow o quarerly annualzed GDP would, ceers parbus, lead o a long-run real apprecaon of he peso of abou 2 percen. Ths conforms o economc heory. 6 Tha s how he daa s repored n Inda.

4 M P o = L(, * E, Y, W) (2) E where L s he real demand for money, (*) s he domesc (foregn) nomnal neres rae, Y s he oupu level. A do over a varable s s me dervave. Smlarly, here s a marke-clearng condon for he domesc bond marke. B = J ( ) (3) P Here, L, L 2 < 0, L 3 > 0; 0 L 4 J > 0, J 2 < 0, J 3 < 0, 0 J 4 Fnally, here s an IS curve * * P Y = A( Y, Π, G) + TB( Y, Y, ) (4) EP where A s domesc absorpon, Y (Y*) s he domesc (foregn) oupu, Π s he expeced (and acual) rae of nflaon, G governmen expendure, TB he rade balance and P*/P s he relave prce of foregn goods. There are wo dynamc equaons a Phllps Curve and a foregn asse accumulaon equaon. 0 y E = H ( Y Y ) E Π (5) F o F = TB( ) + * (6) EP EP EP The sysem () o (6) can be solved for 3 dynamc varables, F and P * P* A sem-reduced form for would look lke he followng: EP M + B. P EP P * M P B P * * ( F,,, G, G,...,,,..., µ µ ) ψ (7) = + +, + where he forcng varables are *, G and µ (he growh rae of money). The above s rue for a freely floang exchange rae model. Where nervenon akes place EP/P* becomes only deermned wh he nervenon varable. In he Indan conex wh he Reserve bank of Inda nervenng connuously o manan a consan effecve exchange rae, we can nver equaon (7) o ge he level of foregn exchange as he endogenous varable C EP M B * * F = Φ( ; F,,, G, G+,...,, +,...,, µ +,...) P * P P µ (8) Equaon (8) can be hough of as a sem-reduced form for EP/P* wh he Cenral Bank s reacon funcon nsered n. Or equvalenly, s he Exchange marke Pressure Model wh he varable of neres (for us) beng he cenral Bank s sock of foregn exchange reserves. Hgher real balances are assocaed wh a real deprecaon, and herefore s negavely assocaed wh he holdng of foregn exchange (nsofar as he Cenral Bank sells foregn exchange o preven hs). Smlarly, for he counry s sock of foregn asses, we should expec a posve relaonshp. In he esmaed equaon we should expec capal nflows and governmen expendure o be posvely assocaed wh he foregn exchange reserves. Fnally n keepng

5 wh he exchange marke pressure leraure an acquson of foregn exchange akes place when he real value of he currency s hgh. 3. Economerc Mehodology Based on he model n he prevous secon, we evaluae n a VAR framework, he relaonshp beween real effecve exchange rae, ne capal nflows and her volaly, fscal polcy ndcaor, moneary polcy ndcaor, and real curren accoun surplus. The secon below descrbes he economerc mehodology employed. Tess for nonsaonary are frs dscussed, followed by a descrpon of conegraon and granger causaly, generalzed mpulse response and decomposon analyss. Fnally, we analyze generalzed mpulse response analyss n a conegraed VAR model. Nonsaonary The classcal regresson model requres ha he dependen and ndependen varables n a regresson be saonary n order o avod he problem of wha Granger and Newbold (974) called spurous regresson. Nonsaonary or he presence of a un roo can be esed usng he augmened Dckey-Fuller (ADF) es (979, 98), he Phllps Perron (PP) es (988) and he KPSS es proposed by Kwakowsk e al. (992). To es f a sequence y conans a un roo, hree dfferen regresson equaons are consdered n ADF es: y y y = = = p + γ y + θ + β y + ε = 2 p + γ y + β y + ε = 2 p + β y + ε = 2 α (8) α (9) y γ (0) The frs equaon ncludes boh a drf erm and a deermnsc rend; he second excludes he deermnsc rend; and he hrd does no conan an nercep or a rend erm. In all hree equaons, he parameer of neres s γ. If γ=0, he y sequence has a un roo. The esmaed -sasc s compared wh he approprae crcal value n he Dckey-Fuller ables o deermne f he null hypohess s vald. The crcal values are denoed by τ τ, τ µ, and τ for equaons (8), (9), and (0) respecvely. We follow Doldado, Jenknson and Sosvlla-Rvero s (990) sequenal procedure for he ADF es when he form of he daa-generang process s unknown. Such a procedure s necessary snce ncludng he nercep and rend erm reduces he degrees of freedom and he power of he es mplyng ha we may conclude ha a un roo s presen when, n fac, hs s no rue. Furher, addonal regressors ncrease he absolue value of he crcal value makng harder o reec he null hypohess. On he oher hand, nappropraely omng he deermnsc erms can cause he power of he es o go o zero (Campbell and Perron, 99). The sequenal procedure nvolves esng he mos general model frs (equaon 8). Snce he power of he es s low, f we reec he null hypohess, we sop a hs sage and conclude ha here s no un roo. If we do no reec he null hypohess, we proceed o deermne f he rend erm s sgnfcan under he null of a un roo. If he rend s sgnfcan, we rees for he presence of a un roo usng he sandardzed normal dsrbuon. If he null of a un roo s no reeced, we conclude ha he seres conans a un roo. Oherwse, does no. If he rend s no sgnfcan, we esmae equaon (9) and es for he presence of a un roo. If he null of a un roo s reeced, we conclude ha here s no un roo and sop a hs pon. If he null s no reeced, we es for he sgnfcance of he drf erm n he presence of a un roo. If he drf erm s sgnfcan, we es for a un roo usng he sandardzed normal dsrbuon. If he drf s no sgnfcan, we esmae equaon (0) and es for a un roo. We also conduc he Phllps-Perron (988) es for a un roo manly because he Dckey- Fuller ess requre ha he error erm be serally uncorrelaed and homogeneous whle he Phllps-Perron es s vald even f he dsurbances are serally correlaed and heerogeneous.

6 The es sascs for he Phllps-Perron es are modfcaons of he -sascs employed for he Dckey-Fuller ess bu he crcal values are precsely hose used for he Dckey-Fuller ess. In boh he ADF and he PP es, he un roo s he null hypohess. A problem wh classcal hypohess esng s ha ensures ha he null hypohess s no reeced unless here s srong evdence agans. Therefore hese ess end o have low power, ha s, hese ess wll ofen ndcae ha a seres conans a un roo. Kwakowsk e al. (992) herefore sugges ha based on classcal mehods may be useful o perform ess of he null hypohess of saonary n addon o ess of he null hypohess of a un roo. Tess based on saonary as he null can hen be used for confrmaory analyss, ha s, o confrm conclusons abou un roos. Of course, f ess wh saonary as he null as well as ess wh un roo as he null boh fal o reec he respecve nulls or boh reec he respecve nulls, here s no confrmaon of saonary or nonsaonary. KPSS Tes wh he Null Hypohess of Dfference Saonary To es for dfference saonary (DS), KPSS assume ha he seres y wh T observaons (=,2,,T) can be decomposed no he sum of a deermnsc rend, random walk and saonary error y = δ + r + ε where r s a random walk r = r - + µ and µ s ndependenly and dencally dsrbued wh mean zero and varance σ 2 µ. The nal value r 0 s fxed and serves he role of an nercep. The saonary hypohess s σ 2 µ=0. If we se δ = 0, hen under he null hypohess y s saonary around a level (r 0 ). Le he resduals from he regresson of y on an nercep be e, =,2,,T. The paral sum process of he resduals s defned as: S = e = The long run varance of he paral error process s defned by KPSS as 2 2 σ = lmt E( S ) T T A conssen esmaor of σ 2, s 2 (l), can be consruced from he resduals e as S 2 ( l) = T T = e 2 + 2T l s = w( s, l) T e e = s + where w(s,l) s an oponal lag wndow ha corresponds o he selecon of a specral wndow. KPSS employ he Barle wndow, w(s,l) = s/(l+) as n Newey and Wes (987), whch ensures he non-negavy of s 2 (l). The lag operaor l correcs for resdual seral correlaon. If he resdual seres are ndependenly and dencally dsrbued, a choce of l = 0 s approprae. The es sasc for he DS null hypohess s η µ = T 2 T = S 2 / s 2 ( l ) s KPSS repor he crcal values of η µ (p. 66) for he upper al es. Thus, hree ess, ADF, PP and KPSS ess are used o es for he presence of a un roo. The KPSS es, wh he null of saonary, helps o resolve conflcs beween he ADF and PP ess. If wo of hese hree ess ndcae nonsaonary for any seres, we conclude ha he seres has a un roo. If he varables are nonsaonary, we es for he possbly of a conegrang relaonshp usng he Johansen and Juselus (990) mehodology. If he varables are ndeed conegraed, we can consruc a vecor error-correcon model ha capures boh he shor-run and long-run dynamcs. Conegraon and Granger Causaly

7 The possbly of a conegrang relaonshp beween he varables s esed usng he Johansen and Juselus (990, 92) mehodology. If he varables are ndeed conegraed, we can consruc a vecor error-correcon model ha capures boh he shor-run and long-run dynamcs. Consder he p-dmensonal vecor auoregressve model wh Gaussan errors: y y s an = A y A p y p + A 0 + ε where m vecor of I() only deermned varables. The Johansen es assumes ha he varables n y are I(). For esng he hypohess of conegraon he model s reformulaed n he vecor error-correcon form where, Π = I p y = Πy + Γ y + A0 = m p = A, Γ = p = + A, + ε =,..., p. Here he rank of Π s equal o he number of ndependen conegrang vecors. If he vecor y s I(0), Π wll be a full rank m m marx. If he elemens of vecor y are I() and conegraed wh rank (Π) = r, hen Π = α β, where α and β are m r full column rank marces and here are r < m lnear combnaons of y. The model can easly be exended o nclude a vecor of exogenous I() varables. Under conegraon, he VECM can be represened as y p = αβ ' y + Γ y + A + ε 0 = where α s he marx of adusmen coeffcens. If here are non-zero conegrang vecors, hen some of he elemens of α mus also be non zero o keep he elemens of y from dvergng from equlbrum. Johansen and Juselus (990, 92) sugges he LR es based on he maxmum egenvalue (λ max ) and race (λ race ) sascs o deermne he number of he conegrang vecors. Snce λ max es has a sharper alernave hypohess as compared o λ race es, s used o selec he number of conegrang vecors. If he presence of conegraon s esablshed, he concep of Granger causaly can also be esed n he VECM framework. For example, f wo varables are conegraed,.e. hey have a common sochasc rend, hen causaly n he Granger (emporal) sense mus exs n a leas one drecon (Granger, 986; 988). Thus n a wo varable vecor error correcon model, we say ha he frs varable does no Granger cause he second f he lags of he frs varable and he error correcon erm are only no sgnfcanly dfferen from zero. Ths s esed by a on F or Wald χ 2 es. Generalzed Impulse Response Analyss Dynamc relaonshps among varables n VAR models can be analyzed usng nnovaon accounng mehods ha nclude mpulse response funcons and varance decomposons. An mpulse response funcon measures he me profle of he effec of shocks a a gven pon n me on he fuure values of varables of a dynamcal sysem. A maor lmaon of he convenonal mehod advocaed by Sms (980, 8) s ha he mpulse response analyss s sensve o he orderng of varables n he VAR (see Lukepohl, 99). In hs approach, he underlyng shocks o he VAR model are orhogonalzed usng he Cholesky decomposon of he varance-covarance marx of he errors, Σ =E(ε ) = PP, where P s a lower rangular marx. Thus a new sequence of errors s creaed wh he errors beng orhogonal o each oher, and conemporaneously uncorrelaed wh un sandard errors. Therefore he effec of a shock o any one of hese orhogonalzed errors s unambguous because s no correlaed wh he oher orhogonalzed errors. Generalzed mpulse responses overcome he problem of dependence of he orhogonalzed mpulse responses on he orderng of he varables n he VAR. Koop e. al (996) orgnally proposed he generalzed mpulse response funcons (GIRF) for non-lnear dynamcal sysems bu hs was

8 furher developed by Pesaran and Shn (998) for lnear mulvarae models. An added advanage of he GIRF s ha snce no orhogonaly assumpon s mposed, s possble o examne he nal mpac of responses of each varable o shocks o any of he oher varables. The generalzed mpulse response analyss can be descrbed n he followng way 7. Consder a VAR (p) model: x p = Σ Φ x = + ε, =,2,, T. () where x = (x, x 2,, x m ) s an m vecor of only deermned dependen varables and {Φ, =,2,,p} are m m coeffcen marces. If x s covarance-saonary, he above model can be wren as an nfne MA represenaon: x = Σ A ε, =,2,,,T. (2) = 0 where m m coeffcen marces A can be obaned usng he followng recursve relaons: A = Φ A + Φ 2 A Φ p A p, =,2,.. (3) wh A 0 = I m and A = O for < 0. Consder he effec of a hypohecal m vecor of shocks of sze δ = (δ,,δ m ) hng he economy a me compared wh a base-lne profle a me +n, gven he economy s hsory. The generalzed mpulse response funcon of x a horzon n, s gven by: GI x ( n, δ, Ω ) = E( x + n ε = δ, Ω ) E( x + n Ω ) (4) where he hsory of he process up o perod - s known and denoed by he non-decreasng nformaon se Ω. Here he approprae choce of hypoheszed vecor of shocks, δ, s cenral o he properes of he mpulse response funcon. By usng Sms (980) Cholesky decomposon of Σ (=E(ε )) = PP, he m vecor of he orhogonalzed mpulse response funcon of a un shock o he h equaon on x +n s gven by: o ψ = An Pe, n = 0,,2,.., (5) where e s an m vecor wh uny as s h elemen and zero elsewhere. However, Pesaran and Shn (998) sugges o shock only one elemen (say h elemen), nsead of shockng all elemens of ε, and negrae ou he effecs of oher shocks usng an assumed or hsorcally observed dsrbuon of errors. Thus, now he generalzed mpulse response equaon can be wren as GI x ( n, δ, Ω ) = E( x + n ε = δ, Ω ) E( x+ n Ω ) (6) If he errors are correlaed a shock o one error wll be assocaed wh changes n he oher errors. Assumng ha ε has a mulvarae normal dsrbuon,.e., ε N(0, Σ), we have E( ε ε = δ ) = ( σ, σ 2, Λ, σ m ) σ δ = Σe σ δ (7) Ths gves he predced shock n each error gven a shock o ε, based on he ypcal correlaon observed hsorcally beween he errors. Ths s dfferen from he case where he dsurbances are orhogonal and he shock only changes he h error as follows: E( ε ε = δ ) = δ e (8) δ = σ n equaon (7),.e. measurng he shock by one sandard By seng devaon, he generalzed mpulse response funcon ha measures he effec of a one sandard error shock o he h equaon a me on expeced values of x a me + n s gven by g = 2 ψ ( n) σ A Σe, n = 0,, 2,.. (9) n 7 For a dealed dscusson and proofs, see Pesaran and Pesaran (997) and Pesaran and Shn (998).

9 These mpulse responses can be unquely esmaed and ake full accoun of he hsorcal paerns of correlaons observed amongs he dfferen shocks. Unlke he orhogonalzed mpulse responses, hese are nvaran o he orderng of he varables n he VAR. Generalzed Varance Decomposon Analyss The forecas error varance decomposons provde a breakdown of he varance of he n- sep ahead forecas errors of varable whch s accouned for by he nnovaons n varable n he VAR. As n he case of he orhogonalzed mpulse response funcons, he orhogonalzed forecas error varance decomposons are also no nvaran o he orderng of he varables n he VAR. Thus, we use he generalzed varance decomposon whch consders he proporon of he N-sep ahead forecas errors of x whch s explaned by condonng on he nonorhogonalzed shocks, ε, ε +,, ε +N, bu explcly allows for he conemporaneous correlaon beween hese shocks and he shocks o he oher equaons n he sysem. Thus, whle he orhogonalzed varance decomposon (Lukepohl, 99) s gven by, n 2 ( e Al Pe ) 0 l= 0 θ ( n) = n ( e A A e ), =, 2,, m. (20) l= 0 he generalzed varance decomposon s gven by, Whle by consrucon = n σ l= 0 = n l= 0 l l 2 ( e Al e ) g θ ( n), =, 2,, m (2) ( e A A e ) m m l l 0 θ ( n) =, due o he non-zero covarance beween he nonorhogonalzed shocks, g θ ( n). = Pearsan and Shn (998) have shown ha he orhogonalzed and he generalzed mpulse responses as well as forecas error varance decomposons concde f Σ s dagonal and for a non-dagonal error varance marx hey concde only n he case of shocks o he frs equaon n he VAR. Thus o selec beween he orhogonalzed and generalzed analyss, we frs es f Σ s dagonal or no. The null hypohess s: H 0 : σ = 0, for all. where σ sands for he conemporaneous covarance beween he shocks n he endogenous varables. The Lkelhood-rao es sasc s gven by LR (H 0 H ) = 2 (LL U LL R ) (22) where LL U and LL R are he maxmzed values of he log-lkelhood funcon under H (he unresrced model) and under H 0 (he resrced model), respecvely. LL U s he sysem loglkelhood and LL R s compued as he sum of he log-lkelhood values from he ndvdual equaons. The LR es sasc follows a χ 2 dsrbuon wh degrees of freedom equal o he number of endogenous varables. Generalzed Impulse Response Analyss n a Conegraed VAR Model The generalzed mpulse response analyss can be exended o a conegraed VAR model. Consder he followng Vecor Error Correcon Model (VECM) descrbed by Pesaran and Shn (998): x = Πx p + Σ Γ x + ε, =,2,,T. (23) =

10 where Π = I m p p Σ Φ Γ = Σ = = +, Φ for =,2,,p-, and Λ s an m g marx of unknown coeffcens. If x s frs-dfference saonary, x can be wren as he nfne movng average represenaon, x = Σ C ε, =,2,,T. (24) = 0 The generalzed mpulse response funcon of x +n wh respec o a shock n he h equaon s gven by: where n =0 g x n = 2, ( ) σ ψ B Σe, n = 0,,2, (25) n B n = Σ C s he cumulave effec marx wh B 0 = C 0 = I m. Smlarly, he orhogonalzed mpulse response funcon of x wh respec o a varablespecfc shock n he h equaon are gven by o ψ x, ( n ) = Bn Pe, n = 0,,2, (26) Once agan he wo mpulse response funcons as well as he forecas error varance decomposons concde f eher he error varance-covarance marx s dagonal or for a nondagonal error varance-covarance marx, f we shock he frs equaon n he VAR. 3. Emprcal Resuls The varables used n he paper are he real effecve exchange rae, ne capal nflows and her volaly, fscal polcy ndcaor, moneary polcy ndcaor, and real curren accoun surplus. The REER ndex s he weghed average (36-counry) of he blaeral nomnal exchange raes of he home currency n erms of foregn currences adused by domesc o foregn relave local-currency prces. The exchange rae of a currency s expressed as he number of uns of Specal Drawng Rghs (SDRs) ha equal one un of he currency (SDRs per currency). A fall n he exchange rae of he rupee agans SDRs herefore represens a deprecaon of he rupee relave o he SDR. Smlarly, a rse n he exchange rae represens an apprecaon of he rupee. The sum of foregn nsuonal nvesmen and foregn drec nvesmen has been aken as he proxy for ne capal nflows. To compue real ne capal flows, nomnal capal flows are deflaed by consumer prce ndex. The volaly of real ne capal nflows has been calculaed by usng he 3-perod movng m 2 / 2 sandard devaon: V = [( / m) ( Z + Z + 2) ], where m = 3 and Z denoes ne capal = nflows. Governmen expendure and hgh-powered money are he fscal and moneary polcy ndcaors respecvely. All he varables are n real erms compued by deflang he nomnal varables by consumer prce ndex. We examne he relaonshp beween rade based REER, ne capal nflows and her volaly n he presence of fscal and moneary polcy ndcaors and real curren accoun surplus. As dscussed n he nroducon, ne capal nflows were neglgble unl he begnnng of 990s and pcked up only hereafer. Snce hen hey have been on he rse, excep for some aberraons. REER has also exhbed an upward rend snce REER and ne capal nflows (Fgures A, B, 2 and 3) generally moved n he same drecon and he correlaon coeffcen beween REER and ne capal nflows s for he perod 993Q2 o 2004Q (Table ). FDI rose sgnfcanly n he early 990s whle FII flows sared only n 993. Boh have been on he rse ever snce. Fgure 4 plos REER and he volaly of capal nflows. I s clear ha boh varables generally moved n andem whch s refleced by he correlaon coeffcen of Now we urn o he emprcal esmaes ha are based on quarerly daa from 993Q2 o 2004Q. We frs es for nonsaonary of all he varables. The resuls of he hree un roo ess are summarzed n Tables 2A & 2B ha show ha all he varables can be reaed as

11 nonsaonary. Tesng for saonary of dfferences of each varable confrms ha all he varables are negraed of order one. We use Johansen s FIML echnque o es for conegraon beween REER, real ne capal nflows (sum of FII and FDI) and her volaly, real money supply, real governmen expendure, and real curren accoun surplus 8. Afer asceranng ha he varables are negraed of he same order, we selec he order of he VAR usng he lkelhood rao es ha suggess an opmal lag lengh of 3. The nex sep s he selecon of he deermnsc erms n VAR. Snce mos macroeconomc daa exhb a lnear rend (and no quadrac rend) whch can be capured by an nercep, we selec an nercep n VAR bu no rend. The maxmum egenvalue es sasc selecs one conegrang vecor (Table 3A). We fnd ha all of he varables n he conegrang vecor have he expeced sgns, as suggesed by he heorecal model. The conegrang vecor suggess ha whle REER s posvely relaed o real ne capal nflows and her volaly, real governmen expendure, and real curren accoun surplus, s negavely relaed o money supply. The sgns are herefore economcally plausble. The conegrang equaon 9 s as follows: MODEL : REER = 0.6*cap f&fd *vol 0.0*m *g *ca (.05) (.00) (.5) (.00) (0.06) where REER s he rade based REER (36-counry), cap f&fd s real ne capal nflows defned as sum of real ne FII and FDI, cap oal s real ne capal nflows defned as aggregae real ne capal nflows, vol s he 3-perod movng sandard devaon of cap f&fd, m s real M0, g s real governmen expendure, and ca s real curren accoun surplus. In he above conegrang vecor, real ne capal nflows, her volaly and real governmen expendure are sgnfcan a 5% level of sgnfcance, curren accoun surplus a 0% and real money supply a 5% (Table 4A). Insead of usng he aggregae of FII and FDI as he measure of ne capal nflows, f we use he oal capal nflows as hey appear n he Balance of Paymen accouns, we ge he followng conegrang equaon: MODEL 2: REER = 0.7*cap oal *vol 0.009*m *g *ca (.00) (.00) (.) (.08) (0.07) In he above conegrang vecor, real ne capal nflows, volaly of aggregae FII and FDI are sgnfcan a 5% level of sgnfcance, real governmen expendure and real curren accoun surplus a 0% level of sgnfcance, and real money supply a 5% (Table 4B). Usng he vecor error correcon model, we es wheher he varables ndvdually Granger cause REER n boh he equaons. For hs, we es for he on sgnfcance of he lagged varables of each varable along wh he error correcon erm. The resuls repored n Table 5A and Table 5B ndcae ha he null hypohess of no Granger causaly s srongly reeced n all he cases n boh models. An nvesgaon of he dynamc neracon of varous shocks n he pos sample perod s examned usng he varance decomposon and he mpulse response funcons. Insead of he orhogonalzed mpulse responses, we use he generalzed mpulse responses and varance decomposons. The advanage of usng he generalzed mpulse responses s ha he orhogonalzed mpulse responses and varance decomposons depend on he orderng of he varables. If he shocks o he respecve equaons n VAR are conemporaneously correlaed, he orhogonalzed and generalzed mpulse responses may be que dfferen. On he oher hand, f 8 Alernave measures of all he varables were also red. For nsance, o capure capal nflows foregn exchange reserves were employed. Volaly was measured by he hree-perod and four-perod movng average coeffcen of varaon. Alernave moneary polcy measures ncluded M3, M and domesc cred. Fscal polcy measures ncluded a measure of fscal sance as descrbed by Josh and Lle (998) as well as fscal defc. Varous measures of neres rae dfferenal we have red hree-monh and one-year dfferenal beween he Treasury Bll rae and LIBOR, dfference beween commercal paper rae and hree-monh LIBOR, hree-monh LIBOR and one-year LIBOR. The varables seleced and repored n model and model 2 gave he mos sasfacory resuls. 9 p-values of he zero-resrcon es for each varable are gven n parenheses.

12 shocks are no conemporaneously correlaed, hen he wo ypes of mpulse responses may no be ha dfferen and also orhogonalzed mpulse responses may no be sensve o a re-orderng of he varables. Thus, before proceedng furher, we es he hypohess ha he off-dagonal elemens n he covarance marx equal zero. The LR es sasc s for model and for model 2 whereas he 95% crcal value of he χ 2 dsrbuon wh 5 degree of freedom s Therefore, he null hypohess ha Σ s dagonal s reeced for boh models. Hence, we use he generalzed mpulse framework. Generalzed Varance Decomposons and Impulse Response Analyss Varance decomposons gve he proporon of he h-perods-ahead forecas error varance of a varable ha can be arbued o anoher varable. These, herefore, measure he proporon of he forecas error varance of REER ha can be explaned by shocks gven o s deermnans. Resuls n Table 6A and 6B provde varance decomposons for a 24-quarer me horzon. For model, a he end of he 24-quarer forecas horzon, around 68% of he forecas error varance of REER s explaned by s own nnovaons. Real ne capal nflows and her volaly ogeher explan abou 27% of he oal varaon afer 24 quarers 0. As for model 2, we fnd ha for he same forecas horzon, around 73% of he forecas error varance of REER s explaned by s own nnovaons, capal nflows explan around 55% and her volaly explans nearly % of he oal varaon n REER. Thus, he relaonshp beween capal flows and REER s more promnen n model 2. In boh models, deermnans of REER n descendng order of mporance nclude ne capal nflows and her volaly (only), governmen expendure, curren accoun surplus, and money supply. Noe ha he forecas error varance decomposons only gve us he proporon of he forecas error varance of REER ha s explaned by s deermnans. They do no ndcae he drecon (posve or negave) or he naure (emporary or permanen) of he varaon. Thus, he mpulse response analyss s used o analyze he dynamc relaonshp among varables. Impulse responses for model are shown n fgures 5A.-5A.5 and hose for model 2 are shown n fgures 5B.-5B.5. In boh he models, he drecons of changes observed n he mpulse responses conform o he sgns obaned earler n he conegrang vecor. The mmedae and permanen effec on REER of a one sandard devaon shock o ne capal nflows s posve. The ne mpac of a one sandard devaon shock o he volaly s posve n he shor run as well as n he long run. A one sandard devaon shock o real money supply has a long run negave mpac on REER, hough s posve n some of he nal perods. The mmedae and permanen effec of a one sandard devaon shock o governmen expendure s posve. A one sandard devaon shock o he curren accoun surplus has a negave effec nally bu he permanen effec s posve. I s noeworhy ha all shocks have a permanen effec on he REER, whch s wha we expec, gven ha s nonsaonary. Thus, boh models gve smlar resuls. Now we urn o he resuls o capure he nervenon by he Reserve bank of Inda. For hs we look no he relaonshp beween real foregn exchange acqusons, rade based REER (36-counres), ne capal nflows, fscal polcy ndcaor, moneary polcy ndcaor, and real curren accoun surplus. All hree un roo ess (ADF, PP and KPSS Table 2A and 2B) conclude ha real foregn exchange acquson s nonsaonary. Therefore we use Johansen s FIML echnque o es for conegraon beween foregn reserve acqusons, REER, real ne capal nflows (sum of FII and FDI), real money supply, real governmen expendure, and real curren accoun surplus. We selec he order of he VAR usng he lkelhood rao es ha suggess an opmal lag lengh of 3. The maxmum egenvalue es sasc selecs one conegrang relaon beween he varables (Table 7). We fnd ha all of he varables have he expeced sgns, as suggesed by he heorecal model. The conegrang vecor suggess ha whle real foregn exchange acqusons s posvely relaed o REER, real ne capal nflows, real governmen expendure, and real curren accoun surplus, s negavely relaed o money supply. The sgns are herefore economcally plausble. The conegrang equaon s as follows: 0 Noe ha he generalzed forecas error varance decomposons add o more han 00 percen. The magnude of he sum depends on he srengh of he covarances beween he dfferen errors. Real foregn exchange acqusons are denoed by forexacq. p-values of he zero-resrcon es for each varable are gven n parenheses.

13 MODEL : forexacq = 3.98*REER *cap 0.05*m *g +.47*ca (.02) (.00) (.00) (.00) (.00) All he varables n he above conegrang vecor are sgnfcan a he 5% level (Table 8) and have he correc sgns.e., n accordance wh our heorecal presumpon. 5. Conclusons Ths paper fnds ha he real effecve exchange rae s conegraed wh he level of capal flows, volaly of he flows, hgh-powered money, curren accoun surplus and governmen expendure. Ths relaonshp s sascally sgnfcan and each of he above deermnans Granger causes he real effecve exchange rae. The generalzed varance decomposons show ha deermnans of he real exchange rae, n descendng order of mporance nclude ne capal nflows and her volaly (only), governmen expendure, curren accoun surplus and he money supply. The drecon of he generalzed mpulse responses conform o he sgns obaned n he conegrang vecor. Shocks o each of he deermnans have a long run mpac on he real effecve exchange rae ha s conssen wh economc heory. Turnng o he foregn exchange reserves of he RBI, we have red o sugges ha we can use a sem-reduced form (ha ncludes he RBI s unknown reacon funcon) o ge a conegregang vecor. Ths lne of enqury s fruful and needs o be examned n deal. References Branson, Wllam H., Hannu Halunen and Paul R. Masson (977), Exchange Raes n he Shor Run. The Dollar- Deuschemark Rae, European Economc Revew, Vol. 0, pp Campbell, J. Y. and P. Perron (99), Pfalls and Opporunes: Wha Macroeconomss Should Know Abou Un Roos, NBER Macroeconomc Annual, Unversy of Chcago Press, Illnos. Chakrabory Indran (2003), Lberalzaon of Capal Inflows and he Real Exchange Rae n Inda: A VAR Analyss, IMF Workng Paper, No. 35. Dabos Marcelo and Juan-Ramon V. Hugo (2000), Real Exchange Rae Response o Capal Flows n Mexco: An Emprcal Analyss, IMF Workng paper, No. 08. Dckey, D. A. and W. A. Fuller (979), Dsrbuon of he Esmaors for Auoregressve Tme Seres wh a Un Roo, Journal of he Amercan Sascal Assocaon, 74, pp ( 98), Lkelhood Rao Sascs for Auoregressve Tme Seres wh a Un Roo, Economerca, 49, pp Dolado, J., T. Jenknson, and S. Sosvlla-Rvero (990), Conegaron and Un Roos, Journal of Economc Surveys, 4, pp Granger, C. W. J. (986), Developmens n he Sudy of Conegraed Varables, Oxford Bullen of Economcs and Sascs, 48, pp Granger, C. W. J. (988), "Some Recen Developmens n he Concep of Causaly", Journal of Economercs, 39, Johansen, S. and K. Juselus (990), Maxmum Lkelhood Esmaon and Inference on Conegraon wh Applcaons o he Demand for Money, Oxford Bullen of Economcs and Sascs, 52, pp (992), Tesng Srucural Hypohess n a Mulvarae Conegraon Analyss of PPP and he UIP for UK, Journal of Economercs, 53, pp Josh, Vay and I.M.D. Lle (998), Inda: Macroeconomcs and Polcal Economy, , Oxford Unversy Press, pp Kohl Renu (2003), Capal Flows and Domesc Fnancal Secor n Inda, Economc and Polcal Weekly, pp Koop, G., M. H. Pesaran, and S. M. Poer (996), Impulse Response Analyss n Nonlnear Mulvarae Models, Journal of Economercs, 74, pp Kwakowsk, Dens, Peer C.B. Phllps, Peer Schmd, and Yongcheol Shn (992), Tesng he Null Hypohess of Saonary agans he Alernave of a Un Roo, Journal of Economercs, 54, Lukepohl, H. (99), Inroducon o Mulple Tme Seres Analyss, Sprnger-Verlag, New York. Pesaran, M. H. and B. Pesaran (997), Workng wh Mcrof 4.0: An Ineracve Economerc Sofware Package (DOS and Wndows versons), Oxford unversy Press, Oxford. Pesaran, M. H. and Y. Shn (998), Generalzed Impulse Response Analyss n Lnear Mulvarae Models, Economc Leers, 58,, pp Phllps, P. and P. Perron (988), Tesng for a Un Roo n Tme Seres Regresson, Bomerca, 75, pp Repor on Currency and Fnance ( ): Reserve Bank of Inda Publcaon. Sms, C. (980), Macroeconomcs and Realy, Economerca, 48, pp. -48 (98), An Auoregressve Index Model for he US , Large Scale Economerc Models, ed. J. B. Ramsey, Norh-Holland, The Neherlands.

14 Vrman A. (2002), Inda s BOP Crses and Exernal Reforms: Myhs and Paradoxes ICRIER Publc Polcy Workshop Paper. Table : Correlaon Coeffcens (993Q2 2004Q) Real Varables REER Cap f&fd cap oal vol m g ca REER forexacq VARIABLE/ TESTS ADF Tes REER PP Tes REER ADF Tes cap f&fd PP Tes cap f&fd ADF Tes cap oal PP Tes cap oal ADF Tes vol PP Tes vol ADF Tes m PP Tes m ADF Tes g PP Tes g ADF Tes ca PP Tes ca Null: γ=0 n Eq. (3) τ τ Table 2A: Un Roo Tess (993Q2-2004Q) Null: γ=0, α=0 n Eq. (3) φ Null: γ=0 n Eq.(2) τ µ Null: γ=0, α=0 n Eq. (2) φ Null: γ=0 Eq. () τ RESULTS (UNIT ROOT PRESENT) Yes Yes Yes Yes Yes No Yes Yes Yes Yes Yes No Yes Yes ADF Tes Forexacq PP Tes Forexacq Yes Yes Crcal Values 0% 5% % Table 2B: KPSS Level Saonary Tes Varables/Lags l=0 l= l=2 l=3 l=4 l=5 l=6 l=7 l=8 Concluson (Un Roo Presen)

15 REER Yes cap f&fd No cap oal Yes vol No m Yes g Yes ca Yes forexacq Yes Noe: l s he lag runcaon parameer. Asympoc crcal values for η µ : Crcal level: Crcal value(η µ ): H 0 : H : Sascs Table 3A: Tess for Conegraon: λ max Tess Crcal values 95% 90% RESULTS No. of C. V. MODEL : REER = f(cap f&fd, vol, m, g, ca) r = 0 r = Reec Null Hypohess r r = Do no reec Null Hypohess Noe: r s he order of conegraon. C. V. denoes he conegrang vecor. H 0 : H : Sascs Table 3B: Tess for Conegraon: λ max Tess Crcal values 95% 90% RESULTS No. of C. V. MODEL 2 : REER = f(cap oal, vol, m, g, ca) r = 0 r = Reec Null Hypohess r r = Do no reec Null Hypohess Noe: r s he order of conegraon. C. V. denoes he conegrang vecor. Table 4A: Zero-Resrcon Tes Null Hypohess χ2 (calculaed) Concluson cap f&fd = (.05) Reec null hypohess vol = (.00) Reec null hypohess m = (.5) Reec null hypohess g = (.00) Reec null hypohess ca = (.06) Reec null hypohess Noe : p value n parenhess

16 Table 4B: Zero-Resrcon Tes Null Hypohess χ2 (calculaed) Concluson cap oal = (.00) Reec null hypohess vol = (.00) Reec null hypohess m = (.) Reec null hypohess g = 0 3.3(.08) Reec null hypohess ca = (.07) Reec null hypohess Noe : p value n parenhess Table 5A: Granger Causaly Tess Null Hypohess Number of Lags χ2 (calculaed) Concluson MODEL : REER = f(cap f&fd, vol, g, ca) REER s no Granger caused by cap f&fd (.04) Reec null hypohess* REER s no Granger caused by vol (.4) Reec null hypohess*** REER s no Granger caused by m (.0) Reec null hypohess* REER s no Granger caused by g (.07) Reec null hypohess** REER s no Granger caused by ca (.06) Reec null hypohess** Noe: p value n parenhess. *,**,*** a 5%, 0% and 5% level of sgnfcance respecvely Table 5B: Granger Causaly Tess Null Hypohess Number of Lags χ2 (calculaed) Concluson MODEL 2 : REER = f(cap oal, vol, g, ca) REER s no Granger caused by cap oal 2 7.6(.06) Reec null hypohess** REER s no Granger caused by vol 2 0.5(.02) Reec null hypohess* REER s no Granger caused by m 2.33(.0) Reec null hypohess* REER s no Granger caused by g (.04) Reec null hypohess* REER s no Granger caused by ca 2 8.3(.04) Reec null hypohess* Noe: p value n parenhess. *,** a 5% and 0% level of sgnfcance. Table 6A: Generalzed Forecas Error Varance Decomposon for REER Horzon REER cap f&fd vol m g ca

17 Table 6B: Generalzed Forecas Error Varance Decomposon for REER Horzon REER cap oal vol m g ca Noe: Enres n each row are he percenages of he varances of he forecas error n REER ha can be arbued o each of he varables ndcaed n he column headngs. The decomposons are repored for one-, four-, sx-, welve-, and weny four-quarer horzons. The exen o whch he generalzed error varance decomposons add up o more or less han 00 percen depends on he srengh of he covarances beween he dfferen errors. H 0 : H : Sascs Table 7: Tess for Conegraon: λ max Tess Crcal values 95% 90% RESULTS No. of C. V. MODEL : forexacq = f(reer, cap, m, g, ca) r = 0 r = Reec Null Hypohess r r = Reec Null Hypohess Noe: r s he order of conegraon. C. V. denoes he conegrang vecor. Table 8: Zero-Resrcon Tes Null Hypohess χ2 (calculaed) Concluson REER= (.02) Reec null hypohess cap = (.00) Reec null hypohess m = (.00) Reec null hypohess g = (.00) Reec null hypohess ca = (.00) Reec null hypohess Noe : p value n parenhess Fgure A: REER vs. Ne Capal Inflows (Nomnal)

18 Noe: Pror o 990, dsaggregaed daa on FII and FDI are no avalable. Therefore we have measured Ne Real Capal Inflows as foregn nvesmen n Inda (FDI+FII) and abroad. Fgure B: REER vs. Ne Capal Inflows (Real) Fgure 2: REER vs. Ne Capal Inflows (FII+FDI) (Real)

19 Fgure 3: REER vs. Toal Capal Inflow (Real) Noe: Toal ne capal nflows are aken as hey appear n he Balance of Paymen accouns. Fgure 4: REER vs. Volaly

20 Generalzed Impulse Responses of REER o One Sandard Error Shocks o oher Varables: Fgure 5A.: Shock o Real Ne Capal Inflows (cap f&fd ) Fgure 5A.2: Shock o Volaly of Real Ne Capal Inflows (vol)

21 Fgure 5A.3: Shock o Real Money Supply (m) Fgure 5A.4: Shock o Real Governmen Expendure (g) Fgure 5A.5: Shock o Real Curren Accoun Surplus (ca) Fgure 5B.: Shock o Real Ne Capal Inflows (cap oal )

22 Fgure 5B.2: Shock o Volaly of Real Ne Capal Inflows (vol) Fgure 5B.3: Shock o Real Money Supply (m) Fgure 5B.4: Shock o Real Governmen Expendure (g)

23 Fgure 5B.5: Shock o Real Curren Accoun Surplus (ca) Varables used n he models repored: Real Effecve Exchange Rae (REER) Daa Defnons and Sources Varable Defnon Source The REER ndex s he weghed average of he blaeral nomnal exchange raes of he home currency n erms of foregn currences adused by domesc o foregn relave localcurrency prces. The exchange rae of a currency s expressed as he number of uns of Specal Drawng Rghs (SDRs) ha equal one un of he currency (SDRs per currency). The number of counres used s 36. Real Ne Capal Inflows (cap) Money Supply (m) Curren Accoun Surplus (ca) Governmen Expendure (g) Two measures:.sum of real Foregn Insuonal Invesmen and real Foregn Drec Invesmen (cap f&fd ) 2. Sum of FII, FDI, Loans, Bankng Capal, Rupee Deb Servce and Oher Capal (cap oal ) Real M0 Aggregae Creds o Curren Accoun mnus Aggregae Debs o Curren Accoun. Toal Revenue Expendure + Toal Capal Expendure Handbook of Sascs on Indan Economy and RBI Bullen Handbook of Sascs on Indan Economy and RBI Bullen Handbook of Sascs on Indan Economy and RBI Bullen Handbook of Sascs on Indan Economy and RBI Bullen Monhly Absrac of Sascs and

24 Volaly n Real Ne Capal Inflows (vol) Three perod movng average sandard devaon of sum of real FDI and real FII: m 2 / 2 V = [( / m) ( Z + Z + 2) ] where m=3 and Z = s cap. Calculaed Foregn Exchange Acqusons (forexacq) Change n he foregn exchange reserves over he las quarer. Calculaed Varables n oher models red bu no repored: Varable Defnon Source Three measures:. Commercal Paper Rae 3 monhs LIBOR 2. 3-monh T-Bll rae 3 monhs LIBOR 3. -year T-Bll neres rae year LIBOR Two measures of foregn neres rae: Handbook of Sascs on Indan Ineres Dfferenal. 3 monhs LIBOR Economy, RBI Bullen and 2. year LIBOR Real Domesc Cred Fscal Defc Exchange Rae Money Supply Fscal Sance Ousandng Bank Cred o he commercal secor Real Gross Fscal Defc Real Effecve Exchange Rae (Expor based) Two measures:. Real M 2. Real M3 Dfference beween acual fscal defc (X) and cyclcally neural fscal defc (CNFD) where CNFD = g GDP* - GDP*, g = expendure o nomnal GDP rao ( n a gven base perod) = revenue o nomnal GDP rao ( n a gven base perod) GDP* = rend value of GDP Tme varyng hree-quarer or four-quarer coeffcen of varaon of real ne capal nflows (boh measures). Ths s calculaed as follows: Handbook of Sascs on Indan Economy and RBI Bullen Handbook of Sascs on Indan Economy and Conroller General of Accouns Handbook of Sascs on Indan Economy and RBI Bullen Handbook of Sascs on Indan Economy and RBI Bullen Calculaed on he bass of formula n Josh, Vay and I.M.D. Lle (998), Inda: Macroeconomcs and Polcal Economy,964-99, Chaper 9, Oxford Unversy Press. Volaly of Capal Inflows Calculaed where m = eher 3 or 4 and Z s real ne capal nflows.