SCHUMPETER DISCUSSION PAPERS Inerdependence beween Foreign Exchange Markes and Sock Markes in Seleced European Counries Mevlud Islami SDP 2008-007 ISSN 1867-5352 by he auor
Inerdependence Beween Foreign Exchange Markes and Sock Markes in Seleced European Counries * Mevlud Islami Universiy of Wupperal/ European Insiue for Inernaional Economic Relaions (EIIW) e-mail: islami@wiwi.uni-wupperal.de Absrac In his analysis he inerdependence beween foreign exchange markes and sock markes for seleced accession and cohesion counries is discussed. This includes basic heoreical approaches. Monhly daa for he nominal sock marke indices and nominal exchange raes are used, where Ireland, Porugal, Spain, Greece, Poland, Czech Republic, Slovenia, and Hungary are included in he analysis. From he coinegraion analysis and VAR analysis boh long-erm links and shor-erm links for Poland are idenified. Conversely, for Slovenia, Hungary, Ireland, Spain, and Greece merely shorerm links resuled. Surprisingly, he direcion of causaion is unambiguously from he sock marke index o he exchange rae for all six counries considered. JEL classificaions: G15, F31, E44 Key words: Exchange Rae, Sock Markes, Coinegraion, VAR, European Inegraion * An earlier version of he paper was presened a he Jean-Monne workshop (DG2, Brussels, April 28, 2008) Financial Marke Inegraion, Srucural Change, Foreign Direc Invesmen and Economic Growh in he EU25 in he projec Conrac Agreemen No 2006 1623/001-00: Jean-Monne Projec. The auhor is solely responsible for he conens; his view does no represen he opinion of he Communiy. 1
I. Inroducion Since he 1970s he discussion abou he inerdependence beween foreign exchange markes and sock markes has been he subjec of many sudies. In he lae 1990s, i even experienced a furher inensificaion due o he financial and currency crisis in Asia, wih fas and massive adjusmens in boh foreign exchange markes and sock markes being observed. The more radiional perspecive was o assume ha he exchange rae could influence boh sock prices and sock marke indices. An increasing significance of capial movemens and is influence on exchange raes has already been aken ino accoun in various heoreical approaches, e.g. in he heory of uncovered ineres rae pariy. Dominance of capial movemens of financial ransacions relaive o rade is obvious in many counries, and as invesmen in socks is a key elemen of inernaional capial movemens i is crucial o consider he poenial inerdependence beween sock prices and he exchange rae. Sock marke capialisaion experienced a huge increase over he pas decade, paricularly in Easern European counries due o high porfolio capial inflows and in paricular due o high Foreign Direc Invesmens (FDI). The impac of sock markes on foreign exchange markes could be relaively srong in Easern European emerging counries as hese capial markes are relaively underdeveloped and srong capial inflows due o reduced capial flow barriers or favourable changes in expecaions could emporarily have a significan influence on nominal and real exchange rae movemens. If porfolio invesmens or Foreign Direc Invesmens concerns firms lised in sock markes, hen capial inflows will have an impac on sock markes. In like manner, capial inflows will have an indirec effec o he exen ha ineres raes fall and hence sock marke prices will rise (in line wih CAPM). An analysis of cohesion counries and accession counries offers an ineresing opporuniy o explore he links beween he wo markes in he conex of EU easern enlargemen. Furhermore, he EU financial marke is probably more inegraed han, for example, he Asian financial markes. The impac of he EU single marke in general and of financial marke inegraion in paricular implies a reducion of barriers o capial flows; hence sronger links beween he foreign exchange marke and he sock marke could resul. As regards comparable newly indusrialised Asian counries, significan resuls for such ype of linkages were found in many sudies (e.g. GRANGER e al., 2000; AMARE/MOHSIN, 2000; AJAYI e al., 1998). Agains his background i is 2
ineresing o analyze easern European EU counries whose capial markes are sill in a caching up process. Sronger links imply ha cenral banks mus also ake his aspec ino accoun when making decisions in erms of ineres rae and money supply, as hese decisions can have undesired impacs on he whole financial marke. The links beween he foreign exchange rae and sock marke prices are paricularly imporan in he conex of he growing openness of easern European counries and also because capial accumulaion and caching-up will be refleced in he dynamics of large and medium firms quoed on he sock marke. In he following analysis he focus is on EU cohesion counries and seleced possocialis ransiion economies. The resuls of he subsequen analysis show ha significan links exis for six counries (Ireland, Spain, Greece, Poland, Slovenia, and Hungary) in he shor-erm, where he sock marke index Granger-causes he exchange rae. Thus he main channel for he eigh counries considered is an impulse which runs from he sock marke o he foreign exchange marke. For Poland, addiional long-erm links exis wih he same direcion of causaion. The subsequen analysis is divided as follows: Afer he inroducion a selecive review of imporan lieraure is given in secion wo before heoreical foundaions and mehods employed are discussed in secions hree and four, respecively. In he fifh secion, empirical resuls are presened wih respec o he analysis of long-erm and shor-erm links beween foreign exchange markes and sock markes in seleced cohesion and accession counries. Finally, he paper ends wih a summary and some concluding remarks. II Previous Lieraure Mos of he analyses on he links beween foreign exchange markes and sock markes have focussed eiher on he US during he 1980s and 1990s, he mos developed capial marke, or on Souh Easern and Souh Asian counries (especially afer he Eas-Asian crisis in 1997). During his ime, boh foreign exchange markes and sock markes experienced huge volailiy. The firs sudy on he inerdependence beween foreign exchange markes and sock markes was carried ou by FRANCK/YOUNG (1972) who based heir sudy on a simple correlaion and regression analysis. They examined he repercussion of srong exchange rae volailiy of foreign currencies wih respec o he US dollar on sock 3
prices of seleced US mulinaional firms included in he S&P 500 and Dow-Jones index. No significan resuls could be found. Afer he collapse of he Breon Woods Sysem and herefore he correspondingly more volaile exchange raes, research on his opic advanced in various ways e.g., he noeworhy sudy of AGGARWAL (1981). The inuiion for a link beween he exchange rae and he sock marke assumes ha a devaluaion or depreciaion of he currency makes expors more profiable and as mos major exporers are quoed on he sock marke, one will see a rise in sock marke prices. For he period beween January 1974 and December 1978, posiive long erm and shor erm links were found. These links, however, were sronger in he shor erm. SOENNEN/HENNIGAR (1988) used he real effecive exchange rae of he US dollar and sock prices. They found srong negaive links beween he changes of he US dollar and he changes of sock prices of US enerprises for he period 1980-1986. BAHMANI-OSKOOEE/SOHRABIAN (1992) applied he coinegraion concep and Granger causaliy ess in order o sudy any poenial links beween foreign exchange raes and sock prices. They were also he firs o research for a reverse relaion. They applied monhly daa for he period beween July 1973 and December 1988 for he S&P 500 index and he effecive exchange rae of he dollar, finding ha boh variables have an influence on each oher. However, hey were unable o find any long-erm links. Afer he Asian crisis, here were also various sudies abou he inerdependence beween foreign exchange and sock markes for Asian counries. Paricularly imporan sudies include ha of ABDALLA/MURINDE (1997), who considered in heir analysis Souh Korea, Pakisan, India and he Philippines by looking a he real effecive exchange raes of hese counries for he period from January 1985 o July 1994. Longerm links were esed using coinegraion concep and shor-erm links wih Granger causaliy ess. Only for India and he Philippines could long erm links be found. Using an error correcion model (ECM) for India and he Philippines implied for he former ha he exchange rae indeed influences he sock marke index; for he laer he reverse relaion resuled. For Souh Korea and Pakisan, posiive shor erm links have been found, where he exchange rae is causal in he Granger sense o he sock marke index. AMARE/MOHSIN (2000) included nine Asian counries (Hong Kong, Indonesia, Japan, Malaysia, he Philippines, Singapore, Souh Korea, Taiwan and Thailand) in heir sudy. They employed he coinegraion concep o examine poenial long-erm links beween he wo markes. Long-erm links could be confirmed only for he Philippines and Singapore. The inclusion of he addiional variable ineres rae led o 4
he resul ha for six of nine counries, long erm links could be confirmed. GRANGER e al. (2000) considered Hong Kong, Indonesia, Japan, Malaysia, he Philippines, Singapore, Souh Korea, Taiwan and Thailand by employing he coinegraion concep and Granger causaliy ess. In order o filer ou he shocks of he 1987 crash and he avian flu crisis in Asia, he ime series were divided ino hree pars. They herefore used daily daa of differen ime series lengh (alogeher from 3 January 1987 o 14 November 1997, i.e. 3,097 observaions). Excep for Japan, Singapore and Thailand significan links were found. These resuls effecively demonsrae ha bi-direcional links do exis. However, during he currency crisis i.e., in he shor-run i holds ha in mos cases sock prices have an influence on exchange raes. MUHAMMAD/RASHEED (2003) considered Bangladesh, India, Pakisan and Sri Lanka for he period from 1994 o 2000, also employing he coinegraion concep and Granger causaliy ess. For India and Pakisan hey could find neiher shor-erm nor long-erm links. However, for Bangladesh and Sri Lanka, bi-direcional (posiive) links could be confirmed. STAVÁREK (2004) examined he inerdependence beween he sock marke index and he real effecive exchange raes of four veeran EU members Germany, France, Ausria and he UK, four new EU members Poland, Slovakia, Czech Republic and Hungary as well as he USA for he periods 1970 o 1992 and 1993 o 2003; he employed he coinegraion concep, Vecor ECM (VECM) and he Granger causaliy es. For he veeran EU member counries and he US, boh longerm and shor-erm links were found, bu he direcion of causaliy is no uniform for all counries. Conversely, for he new members merely shor erm links resuled. III Theoreical Foundaion In he lieraure here are no many aemps o incorporae he sock marke and foreign exchange marke in a single model; he links beween he wo markes cerainly exis, bu hey are no as obvious and unambigous as, for example, he link beween he ineres rae and he exchange rae. JARCHOW (1999) incorporaes he sock marke in a modified Mundell-Fleming model based on he idea of represening he sock price in he sense of Tobin s q and a variable price level. The raio q consiss of exising real capial p A and newly produced real capial p. Hence, q can be inerpreed as he real sock price. 5
The porfolio balance approach is a model which, besides he foreign exchange marke, also incorporaes he money marke and he marke of domesic and foreign securiies (BRANSON, 1977). Marke paricipans possess a wealh sock wih given socks of nominal money, domesic bonds and foreign bonds for which invesors choose he preferred porfolio srucure, namely based on (expeced) reurns of he alernaive asses. The demand for domesic money, foreign securiies or domesic securiies depend boh on domesic ineres rae i and he yield on foreign bonds (i f which is he foreign ineres rae plus he expeced devaluaion rae. The asse markes included in his model are represened by he equaions M É w B É w 2 1 Ç f (W, i, i ) ( Å) ( Ä) ( Ä) Ç f (W, i, i ) ( Å) ( Å) ( Ä) e Ç F É w Ç f (W, i, i ), 3 ( Å) ( Ä) ( Å) where W = M + B + ef Toal wealh W is he sum of money M, domesic bonds B, and foreign bonds ef (F is he sock of foreign bonds denominaed in foreign currency in he counry considered; e is he exchange rae in price noaion). The signs given below he equaions indicae he influence of he corresponding variables on he demand of M, B and ef, respecively. In an e-i-space, he equilibrium loci for foreign bonds (FF) and domesic bonds (BB) are boh negaively sloped. The slope of he MM curve porraying equilibrium in he money marke is posiive. The securiies considered in his model represen bonds wih very shor mauriies. In a modified version of he porfolio balance approach, WELFENS (2007) includes he sock marke insead of he domesic bonds marke (for furher Branson-ype models, where beside he sock marke also he oil marke is incorporaed as an addiional asse marke, see WELFENS (2008)). In his model, he supply side of he sock marke is given as he produc of he real sock marke index P /P and capial sock K. The demand for socks (also for foreign bonds and money) depends on marginal uiliy of money, capial produciviy, expeced growh rae of he sock marke price, and he sum of foreign bonds ineres rae and expeced depreciaion rae of he exchange rae. In an e-p space, he KK curve and FF curve are boh posiively sloped and he MM curve is negaively sloped. These approaches emphasize socks while flows are considered by REITZ e al. (2007). This flow-approach considers he aggregaion of end-user order flows, which conain 6
differen informaion from differen ypes of cusomers wih respec o he expeced fundamenal value of he exchange rae. (A financial cusomer is much more engaged in exchange rae research han a commercial cusomer, as he laer only inends o hedge is money amouns resuling from expors or impors.) In paricular, shor-erm deviaions of he exchange rae from is fundamenal value should be explained wih his approach as radiional models do no offer saisfacory resuls. ADLER/DUMAS (1984) capure he link beween enerprise reurn and is exposure vis-à-vis relaive exchange rae change in a single facor model which is given by he equaion r i É a i Å b d Å Ñ i i The slope coefficien b i expresses he exchange rae exposure of enerprise i (i = 1,..., n), a i denoes he consan and e i he error erm (where E(e i ) = 0 and Var(e i ) = s 2 ). The variable d represens exchange rae reurn and r i he reurn of enerprise i. BODNAR/WONG (2003) proposed an augmened marke model (a wo-facor model) which subdivides he risk exposure of enerprises ino wo componens (facors): he overall marke exposure i.e., he risk an enerprise is exposed o he oal sock marke and exchange rae exposure. The modified equaion ri É a i Å bid Å Öirm Å Ñi (2) can be esimaed as usual by OLS. ß i now represens he sock marke risk, i.e. he bea-facor known from he sandard Capial Asse Pricing Model (CAPM), wih r m expressing he sock marke reurn and b i represening he exchange rae exposure (see also ENTORF/JAMIN, 2007). The facor models presened above presume ha he variable exchange rae is he explanaory variable, and he variable sock price (a enerprise level) is he explained variable. Making some reflecions abou he linkage beween he wo variables lead o he realizaion ha boh variables can acually have an impac on each oher a he macro level, as BAHMANI-OSKOOEE/SOHRABIAN (1992) for example have emphasized. Two possible channels will be explained hrough which links beween he wo markes can resul. The exchange rae has an impac on sock prices paricularly on expor-oriened enerprises. An increase of he exchange rae, i.e. a depreciaion of he domesic currency, favours expors, herefore sock prices of enerprises should increase. Moreover, FROOT/STEIN (1991) emphasized paricularly ha foreign direc invesmens (FDI`s) are also influenced by real exchange rae as real devaluaion of (1) 7
domesic currency simulaes ne inflows he laer in urn will affec rade balance in he medium erm. The Froo-Sein model emphasizes he role of imperfec capial markes. The influence of he sock (marke) price on exchange rae can be aken ino accoun hrough including ransacions in he sock marke in he money demand funcion. Referring o he 1920s onse of he Grea Depression in he Unied Saes, FIELD (1984) emphasizes he imporance of considering he significan impac of sock rading s value on he demand o hold cash balances. He assers ha he fac of having no recognized sock rading as a relevan argumen in he demand for money (an expansion of he money supply could be misjudged as expansionary while i migh be neural or even resricive, namely if rising urnover figures in asse markes fully absorb he addiional liquidiy) led indirecly o he Grea Depression, as he naure of moneary policy was misjudged i was less expensive han he FED hough. Hence, he incorporaes he sock marke in his augmened money demand funcion namely, he ransacion volume of sock markes muliplied by he sock price. In a modern version of he Field argumen, one may argue wih respec o FDI ha he demand for domesic money increases if foreign invesors inves in domesic enerprises and raise he nominal amoun of sock marke ransacions. On he one hand, sock price increases, on he oher hand he ineres rae increases as a consequence of increased money demand. Therefore capial inflows are addiionally favoured, and domesic currency will appreciae under flexible exchange rae. In case of fixed exchange rae, sock marke prices should consequenly have no influence on exchange raes bu may have an impac on foreign exchange reserves of he cenral bank, which is commied o preserving he curren value of he exchange rae. If domesic currency appreciaes, he cenral bank is obliged o perform foreign exchange inervenions. Obviously he exchange rae can have a srong impac on he sock price a he micro level. However, a he macro level he impac could be weaker or even non-exisen, as a sock marke index acually measures he performance of a diversified porfolio. In oher words, enerprises weighed by heir capial sock of several indusries are incorporaed in a sock marke index. The exchange rae should have a greaer impac on a sock marke index when more expor-oriened enerprises are represened in he sock marke index. Hence, he composiion of a sock marke index is a crucial hin when i comes o he quesion as o wheher he exchange rae does indeed have a significan impac on he sock marke index. 8
A he macro level, capial (in)flows (e.g., due o invesmens in securiies) can have a srong impac on he exchange rae as well. Invesmens in securiies can be made eiher in bonds or in shares. Hence exchange raes are no only affeced hrough foreign invesmens on domesic bonds bu also hrough foreign invesmens on lised domesic enerprises. As he equiy markes in emerging counries are relaively underdeveloped he effec of sock markes can be much higher han in highly developed capial markes. Moreover, emerging markes are quie ineresing for invesors, as high reurns can ofen be obained even hough he risk is higher. According o he Capial Asse Pricing Model (CAPM), however, he invesor is willing o bear a higher risk if he or she expecs an enerprise reurn which is a leas as high as is corresponding bea (SHARPE e al., 1995). Hence, he securiy marke line (SML) can be used o assess shares and is hus quie a useful insrumen in making decisions on invesmens. Anoher reason for invesmens in hese counries is ha emerging markes do no srongly correlae wih highly developed sock markes. Hence, porfolios can furher be diversified. IV Daa and Mehods Employed 1 Daa and Counries In he subsequen analysis, four accession counries (Poland, Czech Republic, Slovenia, and Hungary) and four cohesion counries (Ireland, Porugal, Spain, and Greece) are included in he analysis. Monhly (average) daa (from Eurosa.; Index, 1995=100) of nominal sock marke indices and nominal bilaeral exchange raes (denominaed as domesic currency per US dollar uni (for which ime series daa had o firs be ransformed) will be used. The ime series applied o he accession counries are considered unil June 2008, bu he iniial values of he ime series vary for boh counry groups due o a lack of daa (iniial values depend on he counries included in he analysis, i.e. iniial values correspond o he iniial values available a he daa source menioned above). The inroducion of he Euro poses an addiionally srong resricion for he applied daa of he cohesion counries concerning he daa lengh. For his reason, cohesion counries are considered unil December 1998 (Greece unil December 2000). The iniial values of he cohesion counries are given as follows: Greece: 09-1988; Ireland:12-1986; Porugal: 12-1992; Spain: 01-1987, and hose of he accession 9
counries: Poland: 04-1991; Slovenia: 01-1994; Czech Republic: 04-1994; Hungary: 01-1991. 2 Mehods Employed For he furher analysis, i is imporan o examine wheher he ime series applied fulfil he propery of saionariy. An appropriae uni roo es mus be carried ou, as his propery decides wheher long-erm or shor-erm links beween variables can be examined. The Augmened Dickey Fuller (ADF) es is a quie powerful es, and i will herefore be employed in his analysis. This es is based on he following regression: áy É ây Å Ü à áy Å u, (3) Ä1 m jé1 j Ä j where Ä represen he difference operaor. The null hypohesis, y conains a uni roo (i.e. Å = 0), will be rejeced if he -value is less han he criical ADF value. Since auocorrelaion of Äy is aken ino accoun, he u mus now fulfil he propery of whienoise, oherwise he lag-lengh mus be opimized unil i does. The equaion can adequaely be esimaed by OLS. The links beween disinc variables can be explored eiher in he shor-erm or in he long-erm. The laer can be carried ou by using he coinegraion concep. The precondiion for he employmen of his approach is ha all considered ime series mus be nonsaionary and inegraed of he same order. Coinegraion means ha ime series have a leas one common sochasic rend excep for some emporarily deviaions. According o ENGLE/GRANGER (1987), coinegraion is defined as follows: Le Y be a vecor of k variables which are all inegraed of order d. The componens of Y are hen coinegraed of order (d, c) in case of he exisence of a leas one linear combinaion z of hese variables. The variable z is hen inegraed of order d-c (d Ç c > 0), i.e. ÉÑY = z ~ I(d-c) (4) In oher words, if he variables are inegraed of order 1 Ö for economic variables his is ofen he case Ö hen he residuals (resuling from he regression equaions) mus be of minor order, i.e. I(0) (ENGLE/GRANGER, 1987). The vecor É is denoed as coinegraing vecor. The number of linear independen coinegraing vecors represens he coinegraion rank r. In case of r = k he sysem consiss of k saionary variables Ö i.e., he coinegraion concep canno be employed. If 10
r = 0, a long-erm relaionship does no exis due o a lack of a leas one saionary linear combinaion for hese variables Ö i.e., coinegraion exiss only in he case of 0 < r < k (ENDERS, 1995; KIRCHGÜSSNER/WOLTERS, 2007). Boh long-erm and shor-erm links can also be explored simulaneously in case of he exisence of a coinegraing relaionship beween he considered variables. In his case, an Error Correcion Model (ECM) can be employed. In a wo-variable case, a very simple wo-sep procedure could be carried ou. The firs sep would be o regress each variable on he oher if he propery of nonsaionariy for boh variables is given, i.e.: y 0 0 y É a Å b x Å z (5) x 1 1 x É a Å b y Å z (6) In he second sep, he ransformaion ino an ECM follows. According o he Granger represenaion heorem, an exising coinegraion relaionship always conains an equivalen ECM (and he reverse), and his can be expressed wih he following equaions: áy É ä y 0 Ä ä (y Ä a y ÉÄ Ä1 ÄÄ Ç0 y É z -1 nx b0x 1) Å Üa xjáx ÄÄÄÅ jé1 Ä j ny Å Ü a áy jé1 yj Äj Å u y (7) áx É ä x 0 Å ä (y Ä a x ÉÄ Ä1 ÄÄ Ç1 É z x Ä 1 n x b1x 1) Å Ü bxjáx ÄÄÄÅ jé1 Ä j ny Å Ü b áy The parameers á y and á x give informaion abou long-erm links (speed of adjusmen oward he long-erm equilibrium) beween he variables y and x. If a leas one of hese parameers is significanly differen from zero, a long-erm link hen exiss beween he considered variables. The parameers a xj, a yj, b xj and b yj represen shor-erm links. Furhermore, if he parameer á y (á x ), and a leas one a xj (b yj ) is significanly differen from zero Ö b yj (a xj ) is no significanly differen from zero Ö he variable x (y ) is said o Granger cause y (x ). The advanage of his approach is ha he informaion los hrough differeniaing he daa in level can be aken ino accoun in differenced daa. A problem arises in his conex wih esing he propery of saionariy of he residuals, as he common uni roo ess are hough o be employed for realised bu no generaed ime series. The criical values of he ADF es are herefore no valid, and oher criical values mus be considered (MACKINNON, 1991). Furhermore, in case of more variables, wo problems can emerge. On he one hand, muliple coinegraion relaions jé1 yj Ä j Å u x (8) 11
can exis, and on he oher hand, he endogenous variable canno be fixed a priori. If a coinegraing relaion for he considered n variables exiss, each variable should be exchangeable as an endogenous and exogenous variable and also be significanly differen from zero. Ofen, however, exacly his anomalous feaure emerges. Therefore a more powerful es is needed. The Johansen approach, based on a VAR, can overcome hese problems. The saring-poin is he following VAR wihou a deerminisic rend (JOHANSEN, 1988): Y É A 1 Y Ä 1 Å A 2YÄ2 Å... Å A pyäp Å U (9) The variables are I(1), and hey may be coinegraed. Subracion of boh sides wih Y -1 and rearrangemen of (9) leads o he Vecor Error Correcion Model (VECM) wih áy É ÄãY * * * Ä 1 Å A1áYÄ1 Å A2áYÄ2 Å... Å A pä1áy ÄpÅ1 Å U, (10) p A j jé1 * j ã É I Ä Ü and A É Ä Ü A, j É 1, 2,..., p Ä1 p i ié jå1 The marix I denoes he ideniy marix and à conains he long-erm links beween he included variables. Tess for coinegraion can be carried ou hrough examining he rank of he marix à (i.e., esing wheher he eigenvalues â i are significan differen from zero). The number of significan eigenvalues is equivalen o he rank of he marix à (LäTKEPOHL/KRÜTZIG, 2004). The idea is he same as in he case of he ADF es. The difference is ha uni roo is esed in a muli-equaion case. Considering he eigenvalues, wo ess can be generaed: Ä Tr (r) É Ü ln(1 Ä åã k iérå1 i ) (race-es) wih he hypohesis H 0 : he number of posiive eigenvalues is a mos r vs. H 1 : here are more han r (r < k) posiive eigenvalues. Ä å r, r Å1) É ÄT ln(1 Ä åã ) (â max -es) max ( rå1 However, he hypoheses of he â max -es are consruced as follows: H 0 : he number of posiive eigenvalues is exacly r vs. H 1 : here are exacly r + 1 posiive eigenvalues. The sequences of ess sar wih r = 0 and end when he null hypohesis canno be rejeced any more. The coinegraion rank is hen equivalen o he value a which he null hypohesis could no be rejeced (BROOKS, 2003). The null hypohesis will be rejeced if he value of he es saisic is larger hen he criical value. 12
If he aemp of deecion of any long-erm links beween variables fails, an alernaive would be o ascerain wheher a leas shor-erm links can be found. Shor-erm links can be explored by employing VAR models for variables, which has been induced o saionariy. In a VAR model, he dependence of a variable o iself is considered up o he lag p and o oher variables as well (SIMS, 1980). A VAR wihou deerminisic rend is given in (9), where in his case Ö shor-erm links are explored Ö all variables mus be saionary. These models can easily be esimaed by OLS. The correc specificaion of he model can be checked wih he usual insrumens, i.e. checking wheher he residuals fulfil he propery of whie-noise or may be serially auocorrelaed (e.g., using he Q saisics for each single equaion). Finally, he inerdependencies should adequaely be specified. The VAR process is no able o specify which variable is exogenous and which one is endogenous. Hence, Granger-causaliy ess will be employed. A variable, say x, is said o Granger-cause he oher variable, say y, if he inclusion of x improves he forecas of y and vice versa. If boh variables Granger cause each oher, a feedback relaionship is given. Considering í x ê ë y è p í à ç É Üê é ié1ë à 11,i 21,i à à 12,i 22, i í x ç è ê éë y Äi Äi è ç Å u é hen in a bivariae VAR x Granger causes y if å 21,i ç 0 for a leas one i (i = 1, 2,..., p) and å 12,i = 0 ( ì i É 1,..., p ) and y Granger causes x if å 12,i ç 0 for a leas one i (i = 1,.., p) and å 21,i = 0 ( ì i É 1,..., p ). In his es he significance of lags of he considered variables is examined by using F- ess in order o ascerain wheher he whole parameers of he lags are insignifican or a leas one parameer is significanly differen from zero. Therefore variables mus fulfil he propery of saionariy. (11) V Empirical Resuls 1 Uni Roo Tes The firs sep in he analysis consiss of esing ime series o deermine wheher hey fulfil he propery of non-saionariy as i is a requiremen for he employmen of he coinegraion concep. Therefore, he ADF es will be employed in level and in firs 13
differences. For he sake of clariy, he presenaion of he resuls will be divided ino wo groups, he group of cohesion counries, and he group of accession counries. The ADF es criical values depend on seleced lag lengh; for his reason, he opimal lag lengh mus be deermined somehow. In a univariae auoregressive process, he number of lag p is chosen, for example, by he Akaike Informaion Crierion (AIC) or Schwarz Bayesian Crierion (SBC). Furhermore, he lag lengh is augmened if significan serial auocorrelaion for he residuals is indicaed (esed by Q saisics). In his analysis, boh he mulivariae AIC (MAIC) and he mulivariae SBC (MSBC) are employed. The variable SP expresses he nominal sock marke index and EXR he nominal exchange rae. DSP and DEXR express he differenced variables of SP and EXR, respecively. Cohesion Counries The resuls show ha excep for he exchange rae in case of Ireland, boh sock marke indices and exchange raes are nonsaionary for all considered ime series. Hence, he requiremen of employing he coinegraion concep is no fulfilled for Ireland. A VAR in firs differences mus herefore be employed. Counry Variable -Sa. Tes criical values Ireland SP 0.7125 1% -3.4768 DSP -3.1375 5% -2.8818 EXR -3.2895 10% -2.5777 DEXR -5.9077 Porugal SP -0.9946 1% -3.5285 DSP -4.7437 5% -2.9042 EXR -2.3184 10% -2.5896 DEXR -6.0621 Spain SP 0.4635 1% -3.4775 DSP -6.2969 5% -2.8821 EXR -0.6409 10% -2.5778 DEXR -8.3412 Greece SP -1.3650 1% -3.4775 DSP -3.8481 5% -2.8821 EXR 0.5620 10% -2.5778 DEXR -8.5979 Null Hypohesis: has a uni roo Tab. 1a: Resuls of ADF es. 14
Accession Counries Obviously all ime series are I(1) according o he ADF es, i.e. saionariy will be induced afer firs differences. All accession counries included in he analysis can herefore be aken ino accoun for esing long-erm links beween he wo variables. Counry Variable -Sa. Tes criical values Poland SP -0.3558 1% -3.4627 DSP -11.7245 5% -2.8757 EXR -2.0019 10% -2.5744 DEXR -10.1764 Slovenia SP 1.9228 1% -3.4731 DSP -8.7503 5% -2.8802 EXR -1.3872 10% -2.5768 DEXR -8.4053 Czech Rep. SP -0.0969 1% -3.4699 DSP -9.5093 5% -2.8788 EXR -0.1042 10% -2.5761 DEXR -9.4750 Hungary SP -1.1418 1% -3.4632 DSP -3.0379 5% -2.8759 EXR -1.7570 10% -2.5745 DEXR -11.4651 Null Hypohesis: has a uni roo Tab. 1b: Resuls of ADF es. 2 Long Term Links In he second par of he analysis, he coinegraion concep is employed. In a wovariable case he Engle-Granger wo-sep approach could be employed. Obviously, he Johansen approach is a more sophisicaed approach and a he same ime i is more pleasan in implemenaion even in a wo-variable case. The ransformaion ino a Vecor Error Correcion Model (VECM) leads o a quasi VAR anyway. As he resuls of he Johansen approach depend on seleced lag order of he VAR, he opimal lag has o be deermined by an appropriae informaion crierion. In his analysis, he mulivariae AIC will be employed. Neverheless, he lag lengh may need o be augmened if serial correlaion does no disappear. Tab. 2a and 2b show ha excep for Poland, sock marke indices and exchange raes are no coinegraed for any of he counries, as he criical values are no exceeded by he 15
es saisic values; in oher words, here are no long erm links for seven of he eigh counries under consideraion. Counry Ireland Lags None A mos 1 Porugal Lags 5 None A mos 1 Spain Lags 6 None A mos 1 Saisic Saisic 13.2342 0.2063 Saisic 11.4983 1.6909 Criical Value Prob.** Criical Value Prob.** 15.4947 0.1065 3.8415 0.6497 Criical Value Prob.** 15.4947 0.1826 3.8415 0.1935 Greece Lags 2 None A mos 1 Saisic 7.0238 0.0011 **MacKinnon-Haugh-Michelis (1999) p-values Tab. 2a: Resuls of he Coinegraion es (cohesion counries) Criical Value Prob.** 15.4947 0.5749 3.8415 0.9735 Counry Poland Lags 4 None A mos 1 Czech Rep. Lags 2 None A mos Slovenia Lags 2 None A mos Saisic 17.8659 0.0570 Saisic 5.3659 0.8128 Saisic 6.7315 0.0435 Criical Value Prob.** 15.4947 0.0216 3.8415 0.8112 Criical Value Prob.** 15.4947 0.7688 3.8415 0.3673 Criical Value Prob.** 15.4947 0.6091 3.8415 0.8347 Hungary Lags 3 None A mos 1 Saisic 6.9283 0.1633 **MacKinnon-Haugh-Michelis (1999) p-values Tab. 2b: Resuls of he Coinegraion es (accession counries) Criical Value Prob.** 15.4947 0.5860 3.8415 0.6861 3 Shor erm links In he nex sep shor erm links are explored. An appropriae approach for his purpose is a bivariae VAR(p). A VAR process presumes ha all variables depend on each oher, i.e. here is no exogenous variable given. A suiable propery of his approach is ha, on 16
one hand, he own endogenous srucure of a variable is considered; on he oher hand, inerdependence o he oher variables is also aken ino accoun up o he lag p. Cohesion Counries The resuls show ha for Ireland significan links beween he nominal sock marke index and he nominal exchange rae can be confirmed unil he second lag. Obviously he direcion of causaion is from sock marke index (DSP) o exchange rae (DEXR). For Spain and Greece, significan links can be confirmed, while for Greece a feedback relaionship seems o exis. Conversely, he sock marke index and he exchange rae for Porugal do no depend on each oher. An explanaion for his could be he small number of observaions included in he analysis (73 observaions). I would be desirable o have a ime series lengh of a leas en years as monhly daa are used. The daa lengh may be one explanaion for he lack of significance inerdependence beween he exchange rae and sock marke index in Porugal. From he VAR analysis, we can conclude ha for he cohesion counries, hree of he four counries considered are inerrelaed where he foreign exchange marke seems o be influenced by he sock marke. For Greece, a bi-direcional link seems o exis. In order o ensure wheher DSP or DEXR can be regarded as he exogenous variable especially for Greece, as a lack of clariy remains Granger causaliy ess mus be employed. 17
Ireland DEXR DSP Consan 0.2193 [0.8697] 1.0268 [1.6816] DEXR(-1) 0.3236 [3.2927] 0.1406 [0.5909] DEXR(-2) -0.2511 [-2.4509] 0.4228 [1.7043] DEXR(-3) 0.1986 [1.8360] -0.0828 [-0.3160] DEXR(-4) -0.1523 [-1.3820] 0.1051 [0.3939] DEXR(-5) 0.0342 [0.3072] 0.3031 [1.1229] DEXR(-6) -0.0391 [-0.3579] 0.0161 [0.0608] DEXR(-7) -0.0736 [-0.6814] 0.3772 [1.4422] DEXR(-8) 0.0445 [0.4273] -0.2713 [-1.0757] DEXR(-9) 0.1295 [1.3706] 0.2492 [1.0890] DSP(-1) 0.0855 [2.2058] 0.4807 [5.1217] DSP(-2) -0.0965 [-2.2197] -0.4156 [-3.9469] DSP(-3) 0.0564 [1.2503] 0.2214 [2.0259] DSP(-4) -0.0186 [-0.4000] -0.0570 [-0.5063] DSP(-5) 0.0340 [0.6911] -0.0699 [-0.5871] DSP(-6) -0.0620 [-1.1911] -0.3022 [-2.3978] DSP(-7) 0.0336 [0.6217] 0.0537 [0.4106] DSP(-8) -0.0895 [-1.6853] -0.1961 [-1.5254] DSP(-9) -0.0888 [-1.6853] 0.3906 [3.1613] R-squared 0.2853 0.3726 Adj. R-squared 0.1744 0.2752 -saisics in [ ] Tab. 3a.1: Resuls of VAR esimaion for Ireland 18
Porugal DEXR DSP Consan 0.1192 [0.4104] 1.6797 [1.1943] DEXR(-1) 0.2747 [2.1891] 0.0735 [0.1210] DSP(-1) 0.0161 [0.6321] 0.3726 [3.0263] R-squared 0.1003 0.1431 Adj. R-squared 0.0738 0.1179 Tab. 3a.2: Resuls of VAR esimaion for Porugal Spain DEXR DSP Consan 0.4704 [2.6694] 1.3903 [1.8770] DEXR(-1) 0.3303 [3.9449] 0.0323 [0.0918] DEXR(-2) -0.0359 [-0.4242] -0.1302 [-0.3662] DSP(-1) 0.0079 [0.4172] 0.4760 [5.9731] DSP(-2) -0.0527 [-2.6164] -0.3928 [-4.6434] R-squared 0.1556 0.2423 Adj. R-squared 0.1308 0.2200 Tab. 3a.3: Resuls of VAR esimaion for Spain 19
Greece DEXR DSP Consan 0.3719 [1.3522] 4.6308 [2.0124] DEXR(-1) 0.3125 [3.0411] -0.6183 [-0.7192] DEXR(-2) -0.146005 [-1.3449] -0.1392 [-0.1532] DEXR(-3) 0.1019 [0.9593] 0.6011 [0.6761] DEXR(-4) -0.2281 [-2.1588] -0.8151 [-0.9220] DEXR(-5) 0.0284 [0.2794] 0.2385 [0.2805] DEXR(-6) 0.0130 [0.1281] -2.4684 [-2.8991] DEXR(-7) -0.1111 [-1.0113] 0.0960 [0.1045] DEXR(-8) 0.1650 [1.4721] -0.3674 [-0.3917] DEXR(-9) -0.6719 [-1.7562] -0.2897 [-0.3091] DEXR(-10) 0.1269 [1.1226] 0.5066 [0.5357] DEXR(-11) -0.1869 [-1.6666] -0.6081 [-0.6481] DEXR(-12) 0.1246 [1.1849] -0.8881 [-1.0091] DSP(-1) 0.0030 [0.2575] 0.3343 [3.4354] DSP(-2) -0.0042 [-0.3546] 0.0460 [0.4629] DSP(-3) 0.0119 [0.9971] -0.0093 [-0.0931] DSP(-4) -0.0166 [-1.3265] 0.2274 [2.1688] DSP(-5) -0.0186 [-1.4020] -0.3381 [-3.0454] DSP(-6) 0.0166 [1.2173] -0.0310 [-0.2713] DSP(-7) -0.0010 [-0.0770] 0.1905 [1.6784] DSP(-8) 0.0241 [1.8345] 0.0316 [0.2871] DSP(-9) -0.0281 [-2.1219] 0.0861 [0.7760] DSP(-10) 0.0119 [0.8544] -0.0538 [-0.4613] DSP(-11) 0.0274 [1.9270] -0.3269 [-2.7499] DSP(-12) 0.0404 [2.8277] 0.1915 [1.6028] R-squared 0.4025 0.3399 Adj. R-squared 0.2721 0.1959 Tab. 3a.4: Resuls of VAR esimaion for Greece 20
Granger causaliy ess show ha he hypohesis édsp does no Granger cause DEXRè can be rejeced for hree of four counries, i.e. Ireland (can be rejeced a 5.7% significance level), Spain, and Greece. The reverse direcion canno be confirmed for any of he cohesion counries. The seleced lag lengh is equivalen o he lag lengh of he VAR model as i is inended o ascerain wheher he inerdependen links confirmed wih he VAR approach can be specified wih respec o he direcion of causaion. Counry Ireland Lags: 2 Null Hypohesis: F-Saisic Probabiliy DSP does no Granger Cause DEXR 2.9305 0.0567 DEXR does no Granger Cause DSP 1.1458 0.3210 Porugal Lags: 1 DSP does no Granger Cause DEXR DEXR does no Granger Cause DSP 0.3995 0.0147 0.5295 0.9040 Spain Lags: 2 DSP does no Granger Cause DEXR DEXR does no Granger Cause DSP 3.5551 0.0674 0.0313 0.9348 Greece Lags: 12 DSP does no Granger Cause DEXR DEXR does no Granger Cause DSP 3.2995 1.2089 Tab. 3a.5: Resuls of Granger causaliy ess for he cohesion counries 0.0004 0.2860 Accession Counries The resuls of he VAR model for he accession counries are similar o hose of he cohesion counries. Absolue changes of exchange raes and sock marke indices show significan inerdependence for Hungary and Slovenia. For he Czech Republic, exchange rae and sock marke indices seem o be independen. For Poland, a VECM is employed as long-erm links could be confirmed. From he VECM, shor-erm links become obvious. As in he equaion of DEXR, boh he adjusmen parameer and he parameer of DSP in -2 are significan. I can hus be concluded ha he sock marke index Granger causes he exchange rae (i.e. SPêEXR). In case of he oher counries, Granger causaliy ess confirm ha here is a significan link beween sock marke and foreign exchange marke for Slovenia, where SPêEXR. 21
Poland Coinegraing Eq.: EXR(-1) 1 SP(-1) 0.7030 [3.7432] Consan -296.6521 Error Correcion: DEXR DSP CoinEq. -0.0071 [-4.1854] 0.0063 [0.5642] DEXR(-1) 0.3088 [4.1702] 0.7094 [1.4679] DEXR(-2) -0.2456 [-3.1263] 0.4111 [0.8019] DEXR(-3) 0.0350 [0.4557] -0.0909 [-0.1814] DEXR(-4) -0.1133 [-1.5644] 0.7011 [1.4831] DSP(-1) 0.0041 [0.3559] 0.1721 [2.2964] DSP(-2) 0.0303 [2.6010] 0.1052 [1.3830] DSP(-3) 0.0115 [0.9069] -0.0407 [-0.4930] DSP(-4) 0.0079-0.0257 [0.6378] C 0.0719 [0.3153] R-squared 0.2333 0.0683 Adj. R-squared 0.1968 0.0240 -saisics in [ ] [-0.3192] 1.8182 [1.2214] Tab. 3b.1: Resuls of VECM esimaion for Poland For Hungary a significan impac of sock marke on he foreign exchange marke can only be confirmed a 10% (exacly a 7%) significance level. The reason for he weaker links beween he wo markes in comparison o he cohesion counries may be based upon he fac ha financial markes (especially sock markes) in Easern Europe are sill underdeveloped as confirmed in he analysis of KÖKE/SCHRÖDER (2003). Moreover, HOLTEMÖLLER (2005) confirmed ha many accession counries iner alia he accession counries considered in his analysis exhibi a very low moneary inegraion. As a measuremen of moneary inegraion, he ineres rae spreads of he counries considered vis-à-vis he Euro ineres rae and counry specific risk premium volailiy were used. An imporan reason in his conex could also be he fac ha he currencies of hese counries excep for Poland do no floa freely bu wihin currency bands (managed floaing). For his reason, rue links may become blurred. 22
Slovenia DEXR DSP Consan 0.3320 [1.1182] 1.8974 [2.5173] DEXR(-1) 0.3320 [4.7664] -0.0654 [-0.3436] DSP(-1) -0.0700 [-2.2303] 0.3042 [3.8168] R-squared 0.1575 0.0890 Adj. R-squared 0.1464 0.0770 Tab. 3b.2: Resuls of VAR esimaion for Slovenia Czech Rep. DEXR DSP Consan -0.2183 [-0.9565] 0.7170 [0.9616] DEXR(-1) 0.2890 [3.8422] 0.0390 [0.1588] DSP(-1) 0.0064 [0.2875] 0.3153 [4.3665] R-squared 0.0836 0.1050 Adj. R-squared 0.0724 0.0940 Tab. 3b.3: Resuls of VAR esimaion for Czech Rep. Hungary DEXR DSP Consan 0.1650 [0.6080] 5.6226 [1.6571] DEXR(-1) 0.2726 [3.7638] 1.6353 [1.8062] DEXR(-2) -0.0832 [-1.1378] -0.3223 [-0.3526] DSP(-1) 0.0030 [0.5008] 0.1823 [2.4706] DSP(-2) 0.0126 [2.1595] -0.0547 [-0.7472] R-squared 0.0921 0.0393 Adj. R-squared 0.0738 0.0201 Tab. 3b.3: Resuls of VAR esimaion for Hungary. Counry Czech Rep. Lags: 1 Null Hypohesis: F-Saisic Probabiliy DSP does no Granger Cause DEXR 0.0827 0.7740 DEXR does no Granger Cause DSP 0.0253 0.8740 Slovenia Lags: 1 DSP does no Granger Cause DEXR DEXR does no Granger Cause DSP 4.9744 0.1181 0.0272 0.7316 Hungary Lags: 2 DSP does no Granger Cause DEXR DEXR does no Granger Cause DSP 2.7010 1.6446 Tab. 3b.4: Resuls of Granger causaliy ess for he accession counries 0.0696 0.1957 23
Neverheless, he resuls of boh counry groups are quie surprising in comparison wih previous research on his aspec. Moreover, he resuls are no in consensus wih par of radiional heory as exchange rae is assumed o influence sock price. I is also asonishing ha he resuls do no show bi-direcional links bu an unambigous direcion of causaion from sock marke o foreign exchange marke. The arising quesion is now how o explain his resul. The unusual and a priori unexpeced resuls of unidirecional causaliy link from SP o EXR could be explained wih high capial inflows (i.e., porfolio invesmens and FDI) in hese counries during heir caching up process. For invesors, i is quie aracive o inves in hese counries as high marginal produc of capial can be expeced. Anoher explanaion could be based upon capial marke liberalizaion. I cerainly faciliaes cross border invesmens, and his can lead o an increasing movemen of capial across counries. Hence, financial marke inegraion could be one reason wih respec o faciliaion of cross border invesmens. Under hese circumsances, a unidirecional causaion from sock marke o foreign exchange marke is possible. Indeed, hese counries experienced much FDI during his ime, bu no simulaneously. (Hungary and he Czech Republic, for insance, araced high FDI inflows relaive o GDP in early 1990s, bu Poland laer.) This could also be a reason for he differen resuls wihin he accession counries. If here are srong porfolio adjusmens, he exchange rae could also be affeced. Furhermore, capial marke liberalizaion could induce increasing speculaions on sock markes and foreign exchange markes, which also may have an impac on he inerdependence beween hese wo markes. The resuls suppor he assumpions made in he Dornbusch model, for example, ha shor-erm deviaions from he long-erm equilibrium are mainly caused by he fac ha financial marke prices are flexible and prices of goods are sicky in he shor-erm (DORNBUSCH, 1976). VI Concluding Remarks In his analysis, four cohesion counries (Ireland, Porugal, Spain, Greece) and four accession counries (Poland, Czech Rep., Slovenia, Hungary) have been considered in order o examine any poenial links beween nominal sock marke index and nominal exchange rae. For his purpose, monhly daa were used, where he cohesion counries were aken ino accoun unil he inroducion of he Euro. The coinegraion concep 24
was employed for esing on long-erm links and he VAR approach for shor-erm links. Finally, Granger causaliy ess were employed for deerminaion of he exogenous and endogenous variable. The resuls show ha for five counries, significan links exis beween he sock marke index and foreign exchange rae, where for Poland boh longerm and shor-erm links exis. An unambigous resul wih respec o he direcion of causaion, from sock marke index o he foreign exchange marke is a surprise. I could be parly explained by high incipien capial inflows. Comparable analyses for emerging Asian counries showed differen resuls. The resuls of he analysis presened could largely be explained by high capial inflows hrough FDI inflows and porfolio invesmens in hese counries. Increased financial marke inegraion in Europe could be anoher reason, as i implies free rade and free movemen of capial wih higher capial inflows anicipaed, markes will reac. This fac could have srenghened he laen links beween he wo markes. 25
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