American Inernaional Journal of Conemporary Research Vol. 2 No. 11; November 2012 Sock Marke and Real Ineres Rae of ASEAN Counries: Are hey Coinegraed? Suhal Kusairi; Nur Azura Sanusi Faculy of Managemen and Economics Universiy Malaysia Terengganu 21030 Kuala Terengganu, Terengganu D.I. Malaysia Abdul Ghafar Ismail Faculy of Economics and Managemen Universii Kebangsaan Malaysia Bangi, 43600 Selangor D.E. Malaysia Absrac The objecive of his research is o invesigae he new linkage paern of financial marke among he ASEAN counries. The research is eager o answer and explain he effec changes of ASEAN sock prices and real ineres rae from paricular ASEAN counry o ohers counries. Using monhly daa over sudy period 1991-2011 and apply he Coinegraion and Vecor Error Correcion Model (VECM), we found ha here were some he linkage of financial marke aciviies among counries in shor run and long run. Bu he level of inegraion occurs beween wo counries definiely depends on financial infrasrucure of each ASEAN counry members like he degree of financial liberalizaion. Implicaion of he resuls could be used o manage he governmen's moneary policy and applicable o invesmen decision maker for invesors ha ineresed in he region. Keywords: Financial Inegraion, Sock Price Index, Real Ineres Rae, ASEAN Counries. Inroducion The basic idea of globalizaion is o provide he economic infrasrucure among counries (regions) over he world in regard wih increase he mobiliy of economic and financial resources. We believe ha when he economy inegraed he flow and uilize of resources among counries will smoohly and usage alernaive of resource will be efficien. In he financial marke secor as example, some invesors have high liquidiy; hey need o diversify heir porfolio in regards o risk and reurn of inernaional invesmen and porfolio formaion. The successful invesors in invesmen and financing as well as governmen in managing economy and resources boh are depending on informaion ha hey have go. One of informaion ha could help hem is he degree of financial marke inegraion informaion. Currenly, financial inegraion especially on money and capial marke in various regions of he world is increasing significanly. Some facors ha lead o his inegraion is infrasrucure world economy, paricularly in he financial markes, which provided funds flow freely beween a counry due o reduced srucural obsacles as well as encouragemen for invesors o profi and manage risk in inernaional porfolio formaion. This developmen has been moivaed o academicians and praciioners o encourage hemselves in exploring and sudying economic and financial inegraions. Mos sudies in he issue focuses on money and capial markes o assess he financial inegraion wih differen variable o presen financial inegraion. Emmza and Losq (1985), Jorion and Schwarz (1986), Whealey (1988), Ernmza e al. (1992), Bekaer and Harvey (1994) using he sandard CAPM model o solve he issue bu he resul are mixed beween acceped and rejeced on inegraion hypohesis. In he same issue, Cho e al. (1986), Gulekin e al. (1989), Korajczyk and Vialle (1989) and Mioo (1992) ried o assess he inegraion bu using he differen model namely APT. They argued APT model more sable compare wih CAPM because i can capure some benchmarks, where CAPM based on he single benchmark. Unforunaely hey also found he mixed resul. 42
Cenre for Promoing Ideas, USA www.aijcrne.com Chen and Knez (1995) came ou wih he SDF model o es he financial inegraion hypohesis and heir resul was srongly rejecing he hypohesis. Similarly, Click and Plammer (2003) and Baharumshah e al (2005) esed he financial inegraion looked from money marke wih differen perspecive and he sudy ook accoun he long run relaionship beween wo counries. Boh resuls acceped he inegraion hypohesis. However, we argue ha he shor run relaionship is imporance due o pracical reason. Furhermore, he long run and shor run sudies is hardly rare in his issue. In his sudy we focus on financial marke inegraion in he ASEAN Counries (Malaysia, Indonesia, Singapore, Thailand and Philippine). Currenly his region represens 35% of capializaion capial marke in Asia region, and economic growh sable wih average 5% for las 10 year. Besides ha, he design of capial marke inegraion ASEAN counries and declared he esablishmen of he ASEAN economic communiy by 2015. The purposes of he research are 1) o sudy he inegraion of financial aciviies among ASEAN counries 2) To sudy he shor run and long run relaionships among ASEAN counries in financial aciviies. 3) To provide informaion in regards wih financial marke inegraion o suppor he decision makers like invesors as well as governmen of ASEAN counries. For his research, we analyze he financial inegraion of ASEAN Counries relaed o money and capial markes inegraion. The mehod used are he coinegraion dynamic using panel daa o capure he relaionship in shor run and long run financial indicaors among ASEAN counries. As we know he VECM was inroduced by Engle and Granger (1987). The advanage of VECM are 1) o know he shor run and long run effecs from paricular economic or financial shock, 2) To solve he ime series daa ha i s no saionary and spurious regression, (Kosov and Lingard; 2000). Even hough his model has a lo advanage bu i also go some limiaions. Gujarai (2003) saed ha VECM is more concern o forecasing from economeric model and needed some resricion like co inegraion condiion among variable. The sudy on inegraion is imporance due o give some implicaion in inernaional invesmen and moneary policy decision. Invesors and policy makers are ineresed o economy inegraion because when financial markes inegraed, invesors could easy o diversify he invesmen o ge he bes porfolio formaion in erm of expeced reurn and risk. The oher hand if financial marke inegraed here is possibiliy invesors will ge zero profi cause he movemen of price or value of he asse will similarly. Regards o moneary policy, economy inegraion would give signal for moneary policy maker o manage he economy especially in erm of fund flow managemen, ineres rae policy and money supply policy. Opposie wih ha, if financial marke is no inegraed would give advanage o invesmen diversificaion due o invesor would ge profi hrough arbirage mechanism. The res of his paper is organized as follows. Secion 2 will discuss he basic o exended heory in economy inegraion as well as financial marke inegraion. Secion 3 will discuss daa and mehodology ha will be employed o suppor he objecive of he research wih some consideraion regards wih weaknesses and leading of he paricular mehod. Secion 4 will discuss empirical finding hroughou descripive and inference saisical analysis. Finally secion 5 is conclusion for he finding and implicaion. 1. Lieraure Review Sudy he economy inegraion usually employs some basic concep. Firs, he law of one price sae ha any financial insrumen wih he same level of risks should be equally in price. Based on his idea, every counry should be focused on producion heir own advanages. In a goods marke conex, according o LoOP he idenical asse rade in differen counry and he same ime should coaed in he same price. An idea of he law of one price is he foundaion for PPP which sae he relaionship he exchange rae and price level in wo counries. Cassel (1918) PPP, he purchasing power of one uni of a currency should be he same in he wo counries due o spo exchange rae will equae he naional price level in he wo counries. Second, he erm srucure of ineres rae depics he shor run, medium and long run ineres rae. There are hree basic heories; liquidiy preference, marke segmenaion and unbiased expecaion ha underlying he erm srucure of ineres rae. Two key variables in erm srucure are inflaion and Treasury bill. Ineres rae pariy (IRP) sae ha expeced reurn of domesic financial asse should equae wih expeced reurn of foreign financial asse if here is no arbirage process and exchange currency marke in equilibrium. 43
American Inernaional Journal of Conemporary Research Vol. 2 No. 11; November 2012 Third, he CAPM inroduced by Markowiz (1952), and coninued by Sharpe (1964) and Linner (1965). I explains he relaionship beween risky asse and heir expeced reurn o deermine he asse s price. The heory sae ha an invesor should ake accoun wo risk in invesmen decision: risk free rae and asses premium. In line wih he price, he higher risk will ake higher expeced reurn han he price will couned he lower price, vice versa. In an inernaional finance conac, if PPP is hold, a financial asse wih he same risk characerisic should be saed wih he same price. Ross (1976) exended he asse pricing heory by CAPM wih inroducing he APT (arbirage pricing heory). If CAPM priced he asse based on asse risk premium ha generaed from he bes one porfolio asse in he marke han we call a single index, APT exended his idea wih priced an asse wih muliple index. Usually he muliple indexes are generaed from macroeconomic variables or facors. Fourh, he opion pricing model, Black and Scholes (1973) inroduced he financial modeling, how o price he derivaive financial asses like opion. Now he model we call as Black Scholes equaion. The basic idea of he heory is o hedge he paricular asse by buying and selling he underlying asse in jus he righ way and definiely o eliminae risk. Meron (1973) coninued his work o derive he opion pricing model from basic idea Black Schole equaion. Meanwhile associaed wih he measuremen echniques used o see and es he process and he level of inegraion of an economy i is no simple, complex and very spacious. Some auhors sugges several mehods according o he objecives hey wan o find in heir research. Naranjo and Proopapadakis (1997), Baele e al (2007), hey used he asse pricing model. Barram e al (2004) Kim e al (2005), Chambe and Gibson (2008), Yong Fu e al (2011) hey used GARCH and is variance. Ohers researchers used VECM and co inegraion model Baharumshah e al (2007), Raj and Dhal (2008), Phuan e al (2009) and, Bernholz and Kugler (2011). In USA financial marke here are some researchers concern on he financial inegraion issue. Naranjo and Proopapadakis (1997), hey used muly facor asse pricing model (APT) o asses he financial inegraion a fixed and ime varying model and sample hree major capial marke (NYSE, NASDAQ and AMEX). They creaed he conradicive issue in previous inegraion resul, heir argumen is he previous sudy didn apply he benchmark o compare he level of inegraion, he resul of jus saed a saisic significancy of he model. They found is rejec he inegraion of NYSE, NASDAQ and AMEX boh fixed and ime varying a inerval confidence sandard. Similarly, Ayuso and Robero (2001) analysed wheher here has been an increase in he degree of financial marke inegraion during he nineies. Bu hey analysed by using he sochasic discoun facor o mesure he marke inegraion and arbirage. They look a he financial marke inegraion hrough he composi index, he evidence found suggess ha during he nineies here has been an increase of he degree of marke inegraion beween sock markes. Conversely, Alexakis e al (1997), examined he financial marke inegraion look a from real ineres rae of EMS and non EMS. Using he sandar model of IRP he found ha real ineres rae inegraed wihin amoung nice EMS counries and non EMS counry ha paricipae in he long run. The presence of he EMS along wih he associaed lower exchange rae volailiy, has srenghened he real ineres rae pariy as compared o he non- EMS case. Remain in Euro financial marke, Kleimeier and Harald Sander (2000), heir sudy was moivaed by recen regulaory changes in EU in erm of EMS. Using he he same sandar heory of UIP, he sudy invesigaed he degree of inegraion in reail lending in six core European Union (EU) counries using co-inegraion approach and he corresponding error correcion model (ECM) mehodology. In he pre-break period hey could deec inegraion o a limied level, he evidence for inegraion weakened in he pos-1992 period. This could however reflec a convergence process, paricularly wih respec o spreads. As European lending raes are no ye fully inegraed, he sill segmened financial markes pose a challenge for a unied moneary policy. Fuhermore, Barram e al (2004) used a ime-varying copula model o invesigae he impac of he inroducion of he Euro on he dependence beween seveneen European sock markes. The model is implemened wih a GJR-GARCH- model for he marginal disribuions and he Gaussian copula for he join disribuion, which allows capuring ime-varying, non-linear relaionships. The resuls showed ha wihin he euro area, marke dependence increased afer he inroducion of he common currency only for large equiy markes and ransacion coss remain imporan barriers o invesmen in and hus inegraion of smaller markes. 44
Cenre for Promoing Ideas, USA www.aijcrne.com Coninued by Kim e al (2005) examined he influence of he european Moneary Union (EMU) on he dynamic process of sock marke inegraion over he period 1989 2003 using a bivariae EGARCH framework wih imevarying condiional correlaions. Their found ha here has been a clear regime shif in European sock marke inegraion wih he inroducion of he EMU. Linear sysems regression analysis showed ha he increase in boh regional and global sock marke inegraion over his period was significanly driven in par, by macroeconomic convergence associaed wih he inroducion of he EMU and financial developmen levels. Ouside of boh European and American regions, Phylakis and Ravazzolo (2002) examined he economic and financial inegraion simulaneously a he regional and global level for group of Pacific Basin counries by analyzing he covariance excess reurn on naional sock marke. They found evidence ha economic inegraion spurred financial inegraion. Ineresing evidence was economic and financial inegraion were no need free foreign exchange marke infrasrucure. Their resul also explained he ransmission shock beween PBC s wih wo block economy, Japan and USA. There are some issues in regards wih effec of financial inegraion owards macroeconomic volailiy and home bias. Using panel daa regression models Neaime (2005) examined empirically he impac of regional and inernaional financial inegraion on macroeconomic volailiy in he developing economies of he MENA region over he period 1980 2002. Empirical resuls indicaed ha financial openness is associaed wih an increase in consumpion volailiy, conrary o he noions of improved inernaional risk-sharing opporuniies hrough financial inegraion. Baele e al (2007) invesigaed, wha is a financial inegraion eroded he equiy home bias? They se up and compare he observed foreign asse holdings of 25 markes wih opimal porfolio weighs obained from five benchmark models. The Inernaional CAPM opimal weighs equaled he relaive world marke capializaion shares. Alernaive models ha allowed for various degrees of misrus in he I-CAPM and involve reurns daa in compuing opimal weighs indicae a subsanially lower ye posiive home bias. For many counries, home bias decreased sharply a he end of he 1990s, a developmen which hey link o ime-varying globalizaion and regional inegraion. We can synhesis from he above wo researhers ha he financial inegraion need friendly fund flow mobilizaion policy o suppor he sound fiscal and moneary policies. Opposie wih oher researchers, Claessens and Schmukler (2007) look a from he firm perspecive and heir paricipiion o suppor financial Inegraion. They analyzed firms from various counries raising capial, rading equiy, and/or cross-lising in major financial markes. Using a large sample of 39,517 firms from 111 counries covering he period 1989-2000, hey found ha, alhough inegraion increases subsanially over his period, only relaively few counries and firms acively paricipae. Neverheless, a srucural reforms, he developmen of he domesic financial secor is concern facor, since of he high degree of financial inegraion is significanly affeced owards lower macroeconomic volailiy. Besides ha he number of financial firms and volume of rading involed and has a imporance rule o increase he inernaional financial inegraion. Chambe and Gibson (2008) proposed he mulivariae GARCH(1,1)-M reurn generaing model due o he previous sudy on financial inegraion is no allowing for parial marke inegraion as well as for he pricing of sysemaic emerging marke risk. They found ha emerging markes sill remain o a large exen segmened and ha financial inegraion has decreased during he financial crises of he 1990s. They found ha counries wih an undiversified rade srucure have more inegraed financial markes. Finally, heir resuls suggesed ha counries less open o rade are more segmened. In he ASEAN region, Baharumshah e al (2007) examined he dynamic linkage of real ineres rae among ASEAN counries using he VECM and co-inegraion esing. They found ha real ineres rae among ASEAN counries inegraed in he long run and here was a dynamic causaliy in he shor run. I implied ha here was iner dependen in moneary policy among ASEAN counries. Beside ha hey also found ha real ineres rae pariy hold beween ASEAN counries and Japan, nor beween ASEAN and US. Furhermore, Phuan e al (2009) almos using he same mehod, argued his inegraion is resul from financial liberalizaion policy of ASEAN counries. However long run esablished differen sages depend on when he liberalizaion adoped. Ineresingly of he resuls, he counry adoped liberaion a he firs sage unaffeced by ohers. Even i will have greaer influen on oher financial markes. 45
American Inernaional Journal of Conemporary Research Vol. 2 No. 11; November 2012 I-W. Yu e al, (2010) broadly sae ha financial inegraion has srong implicaions for financial sabiliy. In fac, financial inegraion among economies helps o improve heir capaciy o absorb shocks and increase he developmen. Thus inensified financial linkages in a world of increasing capial mobiliy may also saions he risk of cross-border financial conagion. The equiy marke inegraion process flucuaed depend on inensiy of economic aciviy. Neverheless, he process will coninue and he degrees of inegraion beween developed and emerging equiy markes are differen. The divergence may be characerized o he characerisic in he poliical, economic and insiuional aspecs across jurisdicions. The laes invesigaion on he issues, Bernholz and Kugler (2011) invesigaed he financial inegraion in he early modern period in Spain using hreshold error correcion. They argued ha he silver and gold currencies offered arbirage opporuniies beween he marke for silver and gold as well as foreign exchange. However, ransacion cos, which may have been raher subsanial in he pas, hindered arbirage and led o a band of arbirage inaciviy for he exchange rae around is par value. They found ha here was lile deviaion beween wo marke places in he early modern and larger deviaion in Medina del Compo. Furhermore, Yong Fu e al (2011) analyzed volailiy ransmission and asymmeric linkages beween he sock and foreign exchange markes. In conras wih he exising lieraure by using indusrial level daa and applied he rivariae Baba, Kraf and Kroner-generalized auoregressive condiional heeroscedasiciy (BEKK-GARCH) model. Boh resuls of hese research gave he same view ha modern financial marke has a small deviaion due o he ransacion coss are small, he barriers on he marke was decreasing, he faser he flow of asses and liquidiy high. Finally ha news shock in of a financial marke affec for volailiy of oher marke bu asymmeric effecs. 2. Mehodology and daa 2.1 Research Model In his secion, he ime series esimaions are uilized o measure he long run inegraion beween reurn and ineres rae for each counry. Therefore in order o deermine he financial marke inegraion in he ASEAN Counries, he OLS regression equaions can be shown hrough esimaion model as follows: R i = β j + β j R* i + β j I* i + e I i = β j + β j R* i + β j I* i + u (1a) (1b) Which R refer o reurn of counry i a ime, R* is reurn of oher counry, I is ineres rae of counry i a ime, I* is ineres rae of oher counry, e is an error erm for reurn equaion and u is an error erm for ineres rae equaion. 2.2 Uni Roo Tes Normally, uni roo es is used o deermine saionariy and his es can be explained using following equaion: 46 Y 1 (2) Y where, μ is error variable and fulfil all Ordinary Leas Square (OLS) assumpion ha is zero min, consan variances (σ 2 ) and non auo-coleraed. This ype of error normally is known as whie noise error erm. Then, OLS is run on equaion (2) above. If value ρ=1, we can say ha sochasic variable Y has nonsaionary problem. To solve his problem, differeniaion on he variable mus be done unil i become saionary. involved in his es is H 0 : ρ = 1 (nonsaionary) and H 1 : ρ 1 (saionary). According o his hypohesis, saisic value used is known as τ. While criical value is he same wih wha being prepared by Fuller (1976). I is also known as MacKinnon criical value. If saisical τ value is bigger han MacKinnon criical value, H 0 will be rejeced. This means ha he ime series is saionary. Oherwise, if saisical τ value is smaller han MacKinnon criical value, hen H 0 will no be subsraced. This means ha ime series is non-saionary and firs order differeniaion should be done. In order o deermine inegraed degree for each ime series, we applied wo ses of uni roo ess o he daa; he Augmened Dickey-Fuller es and he semi nonparameric Phillips-Perron es.
Cenre for Promoing Ideas, USA www.aijcrne.com The Augmened Dickey Fuller Tes (ADF) which was inroduced by Said and Dickey (1984) can be shown by he following equaions: Y Y Y L Y 0 1 1 i i (3a) i 1 L 0 1Y 1 2T i Y i (3b) i 1 Whereas, Y is firs differeniaion for ime series Y which is (Y - Y -1 ). β 0 is inercep, ν and ε are errors erm. T is ime flow rend and i refer o lag period from 1 o L. To ensure ha he error erm for each of he above equaion is only whie noise; opimum lag lengh period should be fixed. Opimum lag lengh can be fixed using Akaike Informaion Crieria (AIC) proposed by Akaike (1997). The formula for AIC is as follows: 2 AIC exp 2S / N (4) where, σ 2 is variance for residual sum of square. S is number of variables in he righ hand side of he equaion including inercep and N is sample size. hypohesis ha involved o es equaions (3a) and (3b) is Y series ha include non-saionary uni facor ha is H 0 : Y = 1 and alernaive hypohesis is Y series ha does no includes saionary facor uni, ha is H 1 : Y 1. hypohesis will be rejeced if β 1 is negaive and significan. Accepance or rejecion of H 0 is based on au saisical value as previously menioned in curren sudy. Criical value for his es is used from Fuller (1976). Second, he Philip-Perron Tes (PP) can also confirm inegraion degree for each ime series. Inroduced by Philips and Perron (1988), PP es involves he following equaions: Y u1 1Y 1 (5a) Y u1 1Y 1 2 (5b) where, Y is Y series firs differeniaion and is ime rend. In equaion (5a), o be saionary he au saisical value (τ αμ ) mus be negaive and significan and differs from zero. For Y o be saionary in equaion (5b), au saisic (τ ατ ) mus be negaive and significan and differ from zero. For his PP es, criical value is obained from MacKinnon (1991). 2.3 Co inegraion Tess Afer he saionary es, he nex sep is o deermine coinegraion or long run inegraion beween variables involved sock reurn and ineres rae for each counry. Coinegraion es was inroduced by Johansen and Juselis (1990) o sudy long run relaion beween variables. Gonzalo (1994) viewed his Johansen mehod as he bes. Based on Nur Azura e al. (2009), he resul from Johansen es is obained wih respec of special characerisic of ime series for daa involved. This mehod also gives esimaion for all coinegraion vecors ha exis in a ime series sysem and suiable saisic es. Beside, Johansen mehod also enables a hypohesis es o be done on coefficien in coinegraion vecor. The equaion drawn will be as follows: Y Y 1 p p 1 i 1 Y i i BX Where, A i I, i A j, Y is a k-vecor of non-saionary I(1) variables, X is a d-vecor of i 1 p j i 1 deerminisic variables, and is vecor of whie noises wih zero mean and finie variance. The number of coinegraing vecors is represened by he rank of he coefficien marix Π. Johansen s mehod is o esimae he Π marix in an unresriced form, hen es wheher one can rejec he resricions implied by he reduced rank of Π. The likelihood raio (LR) es for he hypohesis ha here are a mos r coinegraion vecors is called he race es saisic. I is o be noed ha he variables under consideraion should have idenical orders, and in paricular are inegraed of order one (Engle and Granger, 1987). Tesing for coinegraion of he ype CI(d,b) for b<d are no of primary ineres, since for b<d he coinegraing vecor is no saionary and does no have a sraighforward economic inerpreaion (Charemza and Deadman, 1997). 47 (6)
American Inernaional Journal of Conemporary Research Vol. 2 No. 11; November 2012 2.4 Descripion of Daa Time series monhly daa were colleced for a period of December 1991 o November 2011 from Thomson Daa Sream. The variables for he raw daa are Composie Indexes, CPI and ineres rae (inerbank ineres rae). From he raw daa hen we defined he real ineres rae and sock reurn. The frequency of ime series is in monhly. All ime series daa covered ASEAN Counries ha consiss of Malaysia, Singapore, Indonesia, Thailand and Philippine. 3. Resuls 3.1 OLS Regression The basic equaions for his sudy are he sock reurn and real ineres rae equaions. Each equaion will deermine he inegraion beween sock reurn/real ineres rae of counry i wih he sock reurn/real ineres rae and real ineres rae/sock reurn for oher counries. Referring o he regression model formaion in equaion (1a) and (1b), Table 1 shows he OLS regression resul. Table 1: OLS Regression Resul for Equaion (1a) RI RM RP RS RT RI 0.146** (2.267) 0.225* (3.784) 0.166* (3.761) 0.278* (4.091) RM 0.149** (2.250) 0.237* (3.990) 0.001*** (0.016) 0.207* (2.984) RP 0.268* (3.901) 0.268* (3.958) 0.082** (1.675) 0.402* (5.676) RS 0.358* (3.862) 0.003*** (0.033) 0.145** (1.655) 0.175** (1.732) RT 0.239* (4.016) 0.172* (2.875) 0.306* (5.738) 0.069*** (1.628) II 0.013*** (0.315) -0.043*** (-0.937) 0.008*** (0.236) 0.069*** (1.304) IM 0.052*** (0.229) 0.042*** (0.168) -0.026*** (-0.142) -0.455** (-1.808) IP -0.093*** (-0.875) 0.213** (2.050) -0.055*** (-0.776) 0.151*** (1.413) IS -0.593*** (-1.590) -0.064*** (-0.171) 0.081*** (0.240) -0.649** (-1.664) IT 0.078*** (0.611) -0.241** (-2.175) 0.085*** (0.750) 0.040*** (0.460) Consan 2.110** (2.024) -0.654*** (-0.696) -0.090*** (-0.113) 0.177*** (0.244) 0.290*** (0.268) R 2 0.474 0.369 0.509 0.234 0.520 F 26.035 16.902 29.924 8.821 31.273 D.W 2.164 2.406 2.263 1.890 2.217 *,**,*** denoes 1%, 5% and 10% significan level. Table 1 shows he OLS regression resul for 5 models which he sock reurn of Indonesia as he endogenous variable (Model 1), sock reurn for Malaysia as endogenous variable (Model 2), sock reurn for Philippines as endogenous variable (Model 3), sock reurn of Singapore as endogenous variable (Model 4) and sock reurn of Thailand as endogenous variable (Model 5). From he R 2 and Durbin Wason value, he resul shows ha he variables are in non-saionary sae. 48
Cenre for Promoing Ideas, USA www.aijcrne.com Table 2: OLS Regression Resuls for Equaion (1b) II IM IP IS IT RI 0.015 (0.964) -0.033 (-0.822) -0.017 (-1.515) 0.008 (0.252) RM 0.015 (0.173) 0.083** (2.091) -0.002 (-0.141) -0.067** (-2.000) RP -0.122 (-1.335) 0.002 (0.111) 0.005 (0.392) 0.015 (0.449) RS 0.008 (0.069) -0.007 (-0.296) -0.066 (-1.132) 0.001 (0.019) RT 0.068 (0.863) -0.018 (-1.221) 0.061*** (1.711) -0.013 (-1.250) II 0.099* (9.704) 0.027 (0.896) -0.020** (-2.311) -0.037 (-1.450) IM 2.918* (9.641) -0.108 (-0.645) 0.084*** (1.793) 1.012* (8.400) IP 0.137 (0.972) -0.017 (-0.681) 0.079* (4.464) 0.258* (5.037) IS -1.084** (-2.187) 0.166*** (1.814) 1.022* (4.542) 0.747* (4.000) IT -0.243* (-1.425) 0.229 (8.367) 0.386* (5.109) 0.085* (3.914) Consan -0.065* (-0.047) 1.621 (6.972) 5.751* (10.873) 0.275 (1.510) -2.087* (-4.022) R 2 0.341 0.560 0.323 0.353 0.534 F 14.923* 36.732* 13.801* 15.754* 33.057* D.W 0.248 0.363 1.310 1.155 0.729 *,**,*** denoes 1%, 5% and 10% significan level. Table 2 shows he OLS regression resul for 5 models which he real ineres rae of Indonesia as he endogenous variable (Model 6), real ineres rae for Malaysia as endogenous variable (Model 7), real ineres rae for Philippines as endogenous variable (Model 8), real ineres rae for Singapore as endogenous variable (Model 9) and real ineres rae of Thailand as endogenous variable (Model 10). From he R 2 and Durbin Wason value, he resul shows ha he variables are in non-saionary sae. This is normal and ofen occurred in ime series daa. Therefore, o solve his problem, saionary es should be carried ou o idenify he saionariy of he daa. In model predicion ha uses ime series daa, uni roo es needs o be done o each variable o idenify nonsaionary problem. Saionariy for each variable should be deermined o avoid spurious regression problem and he variables saionariy is deermined using Augmened Dickey Fuller (ADF) es inroduced by Said and Dickey (1984) and Philip-Perron (PP) es inroduced by Philips and Perron (1988). 3.2 Uni Roo Tes Appendix 1 and 2 summarize he oucome of he ADF and PP ess on all variables in his sudy. The null hypohesis esed is ha he variable under invesigaion has a uni roo agains he alernaive ha i does no. In each case, he lag-lengh is chosen using he Akaike Informaion Crierion (AIC). In he firs half of Table 3 and Table 4, he null hypohesis ha each sock reurn variable has a uni roo can be rejeced by boh ADF and PP ess. While in he second half of Table 3 and Table 4, he real ineres rae variables for each counry are saionary a I(0), boh ADF and PP ess rejec he null hypohesis. Since he daa appear o be saionary by applying he ADF and PP ess in level form, no furher ess are performed. We, herefore, mainain he null hypohesis ha each variable is saionary a level. 3.3 Coinegraion Tes The resuls of Johansen VAR coinegraion procedure are repored in Appendix 3 for sock reurn of Indonesia, Appendix 4 for sock reurn of Malaysia, Appendix 5 for sock reurn of Philippines, Appendix 6 for sock reurn of Singapore, Appendix 7 for sock reurn of Thailand, Appendix 8 for real ineres rae of Indonesia, Appendix 9 for real ineres rae of Malaysia, Appendix 10 for real ineres rae of Philippines, Appendix 11 for real ineres rae of Singapore and Appendix 12 for real ineres rae of Thailand. 49
American Inernaional Journal of Conemporary Research Vol. 2 No. 11; November 2012 The resuls of esing for he number of coinegraing vecors are repored in Appendix 3-14, which presens boh he maximum-eigenvalue Max eigen and he race saisics Trace. The mulivariae coinegraion finding shows, boh maximum-eigenvalue and race es saisics exiss a leas 8 coinegraing vecors a 5% significance level. Appendix 3 o Appendix 7 shows ha exiss long run relaionship beween sock reurn of each counry (namely; Indonesia, Malaysia, Philippines, Singapore and Thailand) wih sock reurn and real real ineres rae of oher counries. While for he real ineres rae equaions, Appendix 8 o appendix 12 shows ha he null hypohesis of no coinegraion can be rejeced and a leas 8 variables are coinegraed. This clearly shows ha, here is long-run relaionship beween he variables in his sudy and he relaionship may be appearing in he shor-run. In he long run, he sock reurns of each counry are inegraed wih he sock reurn and real ineres rae of oher counry wihin he ASEAN region. While for he real ineres rae equaions, in he long run, he real ineres rae of each counry are inegraed wih he real ineres rae and sock reurn of oher counry wihin he ASEAN region. Based on he coinegraion resuls, he nex sep is o es he shor-run inegraion beween variables in he sock reurn and real ineres rae equaions. Table 3 shows he ECT coefficiens for each equaion ha provides evidence of an error correcion mechanism are negaive excep for sock reurn of Malaysia. Based on Table 3, he RI resul shows ha he sock reurn of Indonesia is depend on he sock reurn of Malaysia. Posiive inegraion is repored for boh variables. While for RM, he variabiliy of RM are depends on he signal from RI, RP and IP. RI and RP can influence RM posiively, bu for IP he relaionship is significanly negaive a 1% significance level. In he RT equaion, he significan variables ha affec he sock reurn of Thailand are RI and II. While for he real ineres rae equaions, only he sock reurn of Thailand can influence he real ineres rae of Indonesia. For Malaysia, he real ineres rae equaion resul shows ha RP and RT are significan a 5% and 1% significance level respecively. An increase in RP and RT will decrease he real ineres rae of Malaysia. In he IP, he significan variables ha affec IP are RI and IT. In he IS equaion resul shows ha he relaionship beween RI and IS are posiive, while he relaionship beween IP and IS is negaive wih 1% significance level for boh variables. For he IT equaion resuls, only sock reurn of Indonesia can influence he real ineres rae of Thailand posiively. Table 3: VECM Resuls Dependen variable RI RM RP RS RT II IM IP IS IT RI RM RP RS RT II IM IP IS IT Lag Lengh = 1 AIC = 49.0580 0.2345*** 0.1215-0.0608-0.0965 0.0042-0.0409 0.0038 0.0028 ECT (e1,- 1) value - 8.6666*** AIC =51.8271 0.1656*** 0.1738*** 0.0272 0.1672-0.0141-0.0740*** -0.0126-0.0073 2.3746*** AIC =48.6505 0.0522-0.0615-0.0078-0.0464-0.0314-0.0003-0.0021 0.0146-4.1321*** AIC =51.210-0.2198 0.1146 0.0974 0.2009 0.0460-0.0102 0.0158-0.0021-1.9006 AIC = 50.0070-0.3329*** -0.0503-0.1241 0.0154 0.0775* -8.83E-05 0.0309 0.0004-0.5683 AIC =47.3190 0.5168*** 0.3394 0.0704 0.6574*** -0.0085-0.0115-0.0099 0.0431 0.1838 AIC = 47.2027-1.4890-1.7371** 0.0841-3.1343*** 0.5886 0.2542-0.0030 0.0548-0.0425 AIC = 47.2053 0.4391*** 0.0810-0.0297 0.2447 0.0692 0.0095 0.0100 0.0756*** -2.2966 AIC =47.9190-1.7651*** -0.0604 0.1892-0.4737 0.1762-0.0058-0.6521*** 0.1818-2.4019* AIC = 46.977 0.7350*** 0.2673 0.1090 0.0679 0.0786 0.0242-0.0314 0.0064 0.8416 As explained by Rosilawai, Abu Hassan Shaari & Ismadi (2007) a posiive ECT indicaes ha he endogenous variables are adjused in he long run bu heir values are oo high o be in equilibrium. 50
Cenre for Promoing Ideas, USA www.aijcrne.com Therefore, for he case of RM as he endogenous variable, he posiive ECT indicaes ha RM diver from he long run equilibrium seady sae. While for RI, RP, RS, IP, and IS shows ha he variables are convergence o he long run equilibrium and explain he shor-run inegraion beween variables in he RI, RP, RS, IP and IS equaions. 4. Conclusion This sudy empirically proves ha here is a long run and shor run relaionship/inegraion wihin he ASEAN region in he movemen of sock reurn and real ineres rae. Therefore, in he shor run, he invesors behaviour is based on he signal of sock reurn and real ineres rae of oher counries wihin he ASEAN region. While in he long run, he governmen policy should ake ino accoun he marke inegraion for economic planning, especially in financial marke. The sudy on inegraion is imporance due o he implicaion o he inernaional invesmen and moneary policy decision. Invesors and policy makers are ineresed o economy inegraion because when financial markes inegraed, invesors could easy o diversify he invesmen o ge he bes porfolio formaion in erm of expeced sock reurn and risk. The oher hand if financial marke inegraed here is possibiliy invesors will ge zero profi cause he movemen of price or value of he asse will similarly. Regards o moneary policy, economy inegraion would give signal for moneary policy maker o manage he economy especially in erm of fund flow managemen, real ineres rae policy and money supply policy. Opposie wih ha, if financial marke is no inegraed would give advanage o invesmen diversificaion due o invesor would ge profi hrough arbirage mechanism. References Ayuso, J. and Blanco, R. (2001). Has financial marke inegraion increased during he nineies? Journal of Inernaional Financial Markes, Insiuions and Money. 11. p265 287. Alexakis, P., Apergis., N and Xanhakis., E (1997). Inegraion of Inernaional Capial Markes; Fuher Evidence from EMS and Non EMS Membership. Journal of Inernaional Financial Markes, Insiuions, and Money. 7. P277-287. Baele L, Pungulescu, C., and Ter Hors, Jenke. (2007). Model Uncerainy, Financial Marke Inegraion and he Home Bias Puzzle. Journal of Inernaional Money and Finance. 26 p 606-630. Baharumshah, AZ, Tze., C., Roy, HKW (2007). Dynamic Financial Linkages of Japan and ASEAN Economies: Evidence Based on Real Pariy. IJMS (1), 23-48. Bernholz, P. and Kugler, P. (2011). Financial marke inegraion in he early modern period in Spain: Resuls from a hreshold error correcion model. Economics Leers. 110. P 93 96. Barram, SM. and Taylor, SJ. and Wang, YH. (2004). The Euro and European Financial Marke Inegraion. Lancaser Universiy, Managemen School, Deparmen of Accouning and Finance, Lancaser LA1 4YX, Unied Kingdom. Chambe A. and Gibson, R (2008). Financial inegraion, economic insabiliy and rade srucure in emerging markes. Journal of Inernaional Money and Finance. 27. p 654 675. Claessens S and Schmukler, SL. (2007). Inernaional financial inegraion hrough equiy markes: Which firms from which counries go global? Journal of Inernaional Money and Finance. 26. p788-813. Francis, B. B, Hasan, I and Sun, X.(2008). Financial marke inegraion and he value of global diversificaion: Evidence for US acquirers in cross-border mergers and acquisiions. Journal of Banking & Finance 32 p1522 1540 Kim, SJ., Moshirian, F., and Wu, E. (2006). Evoluion of inernaional sock and bond marke inegraion: Influence of he European Moneary Union. Journal of Banking & Finance 30 p 1507 1534 Kim, SJ., Moshirian, F., and Wu, E. (2005) Dynamic sock marke inegraion driven by he European Moneary Union: An empirical analysis. Journal of Banking & Finance. 29. p 2475 2502 Neaime, S. (2005). Financial Marke Inegraion and Macroeconomic Volailiy in he MENA Region: An Empirical Invesigaion. Review of Middle Eas Economics and Finance. Volume 3, Number 3. Naranjo, A., and Proopapadakis., A. (1997). Financial Marke Inegraion Tess: An Invesagaion Using US Equiy Markes. Journal of Inernaional Financial Markes, Insiuions, and Money. 7. p93-135. Nur Azura S., Nanhakumar L. and Mohd Fikri M. (2009). Causaliy beween Fiscal Adjusmen and Dynamic Economics Performance: The Case of Malaysia. In he proceedings of UMT 8 h Inernaional Annual Symposium on Susainabiliy Science and Managemen, 3-4 May, 222-229. Phuan, SM and Lim, KP. (2009). Financial Liberalizaion and Sock Markes Inegraion for Asean-5 Counries. Inernaional Business Research. 2. No. 1. Phylakis, K and Ravazzolo, F. (2002). Measuring financial and economic inegraion wih equiy prices in emerging markes. Journal of Inernaional Money and Finance. 21. p879 903. 51
American Inernaional Journal of Conemporary Research Vol. 2 No. 11; November 2012 Rosilawai A., Abu Hassan Shaari M. N. and Ismadi I. (2007). The Dynamic Causal Beween Financial Developmen And Economic Growh : Empirical Wvidence From Malaysia Based On Vecor Error Correcion Modeling Approach. Labuan Bullein of Inernaional Business & Finance. 5. p23-39. Vo XV. (2009). Inernaional financial inegraion in Asian bond markes. Research in Inernaional Business and Finance. 23 p 90 106. Yu., IP-W., Fung KP., Tam, SC (2010). Assessing Financial Marke Inegraion in Asia Equiy Markes. Journal of Banking and Finance. 34. P 2879-2885. Appendix 1: ADF Uni Roo Tes Resul Variable Augmened Dicker Fuller I(0) I(1) Sock reurn of Indonesia Wihou Inercep -13.02507* -12.22734* Inercep -13.34767* -12.20042* Trend and Inercep -13.32763* -12.17362* Sock reurn of Malaysia Wihou Inercep -9.236011* -13.34659* Inercep -9.343961* -13.31686* Trend and Inercep -9.325275* -13.28727* Sock reurn of Phillipine Wihou Inercep -14.16192* -10.58955* Inercep -14.29130* -10.56737* Trend and Inercep -14.25963* -10.55001* Sock reurn of Singapore Wihou Inercep -13.24158* -15.77519* Inercep -13.23855* -15.74064* Trend and Inercep -13.24218* -15.70491* Sock reurn of Thailand Wihou Inercep -15.00291* -11.36804* Inercep -15.02848* -11.34235* Trend and Inercep -15.00139* -11.31742* Real ineres rae of Indonesia Wihou Inercep -1.774247*** -16.87284* Inercep -2.490429-16.83805* Trend and Inercep -2.489102-16.81968* Real ineres rae of Malaysia Wihou Inercep -1.202011-17.46312* Inercep -2.777402*** -17.43290* Trend and Inercep -3.045124-17.43112* Real ineres rae of Phillipine Wihou Inercep -1.577410-15.21504* Inercep -2.645449*** -15.20436* Trend and Inercep -11.97670* -15.16639* Real ineres rae of Singapore Wihou Inercep -1.931480*** -12.96940* Inercep -2.528044-12.96049* Trend and Inercep -4.514849** -12.93229* Real ineres rae of Thailand Wihou Inercep -2.069790** -21.27862* Inercep -2.619881*** -21.24233* Trend and Inercep -2.906308-21.20881* 52 *,**,*** denoes 1%, 5% and 10% significan level *,**,*** denoes 1%, 5% and 10% significan level.
Cenre for Promoing Ideas, USA www.aijcrne.com Appendix 2: PP Uni Roo Tes Resul Variables Phillips Perron (PP) I (0) I (1) Sock reurn of Indonesia Wihou inercep -12.94857* -86.97636* Inercep -13.34767* -86.69500* Trend and inercep -13.32763* -86.78776* Sock reurn of Malaysia Wihou inercep -13.70878* -143.1244* Inercep -13.78462* -142.6975* Trend and inercep -13.75797* -143.7077* Sock reurn of Phillipine Wihou inercep -14.18194* -116.8137* Inercep -14.29728* -116.5945* Trend and inercep -14.26586* -120.9887* Sock reurn of Singapore Wihou inercep -13.38635* -50.82601* Inercep -13.38204* -50.68148* Trend and inercep -13.37366* -50.52308* Sock reurn of Thailand Wihou inercep -15.00240* -113.9356* Inercep -15.02848* -113.8571* Trend and inercep -15.00139* -114.7914* Real ineres rae of Indonesia Wihou inercep -1.646456*** -16.92888* Inercep -2.390312-16.89315* Trend and inercep -2.385462-16.87762* Real ineres rae of Malaysia Wihou inercep -1.077140-17.46896* Inercep -2.633841*** -17.43875* Trend and inercep -2.883489-17.43112* Real ineres rae of Phillipine Wihou inercep -5.518003* -59.10417* Inercep -7.374961* -59.64063* Trend and inercep -12.07879* -58.87119* Real ineres rae of Singapore Wihou inercep -3.752385* -63.46640* Inercep -7.252445* -85.25212* Trend and inercep -9.399398* -84.54337* Real ineres rae of Thailand Wihou inercep -2.209761** -21.48382* Inercep -3.007351** -21.44967* Trend and inercep -3.532026** -21.41173* 53
American Inernaional Journal of Conemporary Research Vol. 2 No. 11; November 2012 Appendix 3: Johansen and Juselius Coinegraion Resul for Sock reurn of Indonesia λ Max-eigen r=0 0.498169 164.0991 58.43354 r 1 0.473690 152.7637 52.36261 r 2 0.412044 126.4024 46.23142 r 3 0.352389 103.4025 40.07757 r 4 0.284717 79.74845 33.87687 r 5 0.226154 61.01915 27.58434 r 6 0.159070 41.23289 21.13162 r 7 0.073668 18.21229 14.26460 r 8 0.016994 4.079342 3.841466 λ race r=0 0.498169 750.9598 197.3709 r 1 0.473690 586.8607 159.5297 r 2 0.412044 434.0970 125.6154 r 3 0.352389 307.6946 95.75366 r 4 0.284717 204.2921 69.81889 r 5 0.226154 124.5437 47.85613 r 6 0.159070 63.52452 29.79707 r 7 0.073668 22.29164 15.49471 r 8 0.016994 4.079342 3.841466 Appendix 4: Johansen and Juselius Coinegraion Resul for Sock reurn of Malaysia λ Max-eigen r=0 0.495504 162.8384 58.43354 r 1 0.478184 154.8050 52.36261 r 2 0.406515 124.1750 46.23142 r 3 0.330643 95.54203 40.07757 r 4 0.283310 79.28057 33.87687 r 5 0.219290 58.91736 27.58434 r 6 0.166325 43.29500 21.13162 r 7 0.066412 16.35526 14.26460 r 8 0.048947 11.94410 3.841466 λ race r=0 0.495504 747.1526 197.3709 r 1 0.478184 584.3143 159.5297 r 2 0.406515 429.5093 125.6154 r 3 0.330643 305.3343 95.75366 r 4 0.283310 209.7923 69.81889 r 5 0.219290 130.5117 47.85613 r 6 0.166325 71.59436 29.79707 r 7 0.066412 28.29936 15.49471 r 8 0.048947 11.94410 3.841466 54
Cenre for Promoing Ideas, USA www.aijcrne.com Appendix 5: Johansen and Juselius Coinegraion Resul for Sock reurn of Philippines λ Max-eigen r=0 0.493860 162.0643 58.43354 r 1 0.471111 151.6006 52.36261 r 2 0.408136 124.8258 46.23142 r 3 0.309405 88.10808 40.07757 r 4 0.265635 73.48242 33.87687 r 5 0.188662 49.75871 27.58434 r 6 0.107121 26.96641 21.13162 r 7 0.078359 19.42057 14.26460 r 8 0.046206 11.25911 3.841466 λ race r=0 0.493860 707.4859 197.3709 r 1 0.471111 545.4217 159.5297 r 2 0.408136 393.8211 125.6154 r 3 0.309405 268.9953 95.75366 r 4 0.265635 180.8872 69.81889 r 5 0.188662 107.4048 47.85613 r 6 0.107121 57.64609 29.79707 r 7 0.078359 30.67968 15.49471 r 8 0.046206 11.25911 3.841466 Appendix 6: Johansen and Juselius Coinegraion Resul for Sock reurn of Singapore λ Max-eigen r=0 0.500185 165.0571 58.43354 r 1 0.479087 155.2170 52.36261 r 2 0.415859 127.9518 46.23142 r 3 0.331114 95.70962 40.07757 r 4 0.250214 68.53626 33.87687 r 5 0.212421 56.83246 27.58434 r 6 0.087763 21.86166 21.13162 r 7 0.073330 18.12551 14.26460 r 8 0.050081 12.22809 3.841466 λ race r=0 0.500185 721.5195 197.3709 r 1 0.479087 556.4624 159.5297 r 2 0.415859 401.2454 125.6154 r 3 0.331114 273.2936 95.75366 r 4 0.250214 177.5840 69.81889 r 5 0.212421 109.0477 47.85613 r 6 0.087763 52.21526 29.79707 r 7 0.073330 30.35360 15.49471 r 8 0.050081 12.22809 3.841466 55
American Inernaional Journal of Conemporary Research Vol. 2 No. 11; November 2012 Appendix 7: Johansen and Juselius Coinegraion Resul for Sock reurn of Thailand λ Max-eigen r=0 0.497789 163.9187 58.43354 r 1 0.477033 154.2804 52.36261 r 2 0.421196 130.1365 46.23142 r 3 0.326479 94.06631 40.07757 r 4 0.275382 76.66242 33.87687 r 5 0.222301 59.83687 27.58434 r 6 0.082453 20.48024 21.13162 r 7 0.061396 15.08000 14.26460 r 8 0.032998 7.986108 3.841466 λ race r=0 0.497789 722.4475 197.3709 r 1 0.477033 558.5288 159.5297 r 2 0.421196 404.2484 125.6154 r 3 0.326479 274.1119 95.75366 r 4 0.275382 180.0456 69.81889 r 5 0.222301 103.3832 47.85613 r 6 0.082453 43.54635 29.79707 r 7 0.061396 23.06611 15.49471 r 8 0.032998 7.986108 3.841466 Table 8: Johansen and Juselius Coinegraion Resul for Real ineres rae of Indonesia λ Max-eigen r=0 0.478926 155.1433 58.43354 r 1 0.413064 126.8159 52.36261 r 2 0.343275 100.0766 46.23142 r 3 0.292632 82.39664 40.07757 r 4 0.234753 63.67841 33.87687 r 5 0.198122 52.55016 27.58434 r 6 0.082374 20.45973 21.13162 r 7 0.075749 18.74760 14.26460 r 8 0.043124 10.49144 3.841466 λ race r=0 0.478926 630.3597 197.3709 r 1 0.413064 475.2164 159.5297 r 2 0.343275 348.4005 125.6154 r 3 0.292632 248.3240 95.75366 r 4 0.234753 165.9273 69.81889 r 5 0.198122 102.2489 47.85613 r 6 0.082374 49.69877 29.79707 r 7 0.075749 29.23904 15.49471 r 8 0.043124 10.49144 3.841466 56
Cenre for Promoing Ideas, USA www.aijcrne.com Appendix 9: Johansen and Juselius Coinegraion Resul for Real ineres rae of Malaysia λ Max-eigen r=0 0.488490 159.5523 58.43354 r 1 0.421863 130.4107 52.36261 r 2 0.372495 110.9090 46.23142 r 3 0.291970 82.17396 40.07757 r 4 0.227709 61.49789 33.87687 r 5 0.187817 49.51116 27.58434 r 6 0.080993 20.10180 21.13162 r 7 0.073738 18.23043 14.26460 r 8 0.046795 11.40627 3.841466 λ race r=0 0.488490 643.7935 197.3709 r 1 0.421863 484.2412 159.5297 r 2 0.372495 353.8305 125.6154 r 3 0.291970 242.9215 95.75366 r 4 0.227709 160.7475 69.81889 r 5 0.187817 99.24965 47.85613 r 6 0.080993 49.73849 29.79707 r 7 0.073738 29.63670 15.49471 r 8 0.046795 11.40627 3.841466 Appendix 10: hansen and Juselius Coinegraion Resul for Real ineres rae of Philippines λ Max-eigen r=0 0.491738 161.0684 58.43354 r 1 0.465614 149.1396 52.36261 r 2 0.348183 101.8620 46.23142 r 3 0.292804 82.45461 40.07757 r 4 0.230832 62.46211 33.87687 r 5 0.189084 49.88251 27.58434 r 6 0.079023 19.59212 21.13162 r 7 0.071038 17.53768 14.26460 r 8 0.045526 11.08949 3.841466 λ race r=0 0.491738 655.0885 197.3709 r 1 0.465614 494.0201 159.5297 r 2 0.348183 344.8805 125.6154 r 3 0.292804 243.0185 95.75366 r 4 0.230832 160.5639 69.81889 r 5 0.189084 98.10181 47.85613 r 6 0.079023 48.21929 29.79707 r 7 0.071038 28.62717 15.49471 r 8 0.045526 11.08949 3.841466 57
American Inernaional Journal of Conemporary Research Vol. 2 No. 11; November 2012 Appendix 11: Johansen and Juselius Coinegraion Resul for Real ineres rae of Singapore λ Max-eigen r=0 0.481763 156.4429 58.43354 r 1 0.456414 145.0770 52.36261 r 2 0.409300 125.2942 46.23142 r 3 0.321325 92.25174 40.07757 r 4 0.258136 71.06421 33.87687 r 5 0.188805 49.80064 27.58434 r 6 0.078570 19.47511 21.13162 r 7 0.072477 17.90649 14.26460 r 8 0.045920 11.18793 3.841466 λ race r=0 0.481763 688.5003 197.3709 r 1 0.456414 532.0574 159.5297 r 2 0.409300 386.9804 125.6154 r 3 0.321325 261.6861 95.75366 r 4 0.258136 169.4344 69.81889 r 5 0.188805 98.37017 47.85613 r 6 0.078570 48.56954 29.79707 r 7 0.072477 29.09443 15.49471 r 8 0.045920 11.18793 3.841466 Appendix 12: Johansen and Juselius Coinegraion Resul for Real ineres rae of Thailand λ Max-eigen r=0 0.487283 158.9916 58.43354 r 1 0.446627 140.8301 52.36261 r 2 0.340479 99.06551 46.23142 r 3 0.285493 80.00681 40.07757 r 4 0.228506 61.74360 33.87687 r 5 0.189148 49.90146 27.58434 r 6 0.081178 20.14965 21.13162 r 7 0.072974 18.03411 14.26460 r 8 0.044209 10.76133 3.841466 λ race r=0 0.487283 639.4841 197.3709 r 1 0.446627 480.4925 159.5297 r 2 0.340479 339.6625 125.6154 r 3 0.285493 240.5970 95.75366 r 4 0.228506 160.5901 69.81889 r 5 0.189148 98.84654 47.85613 r 6 0.081178 48.94508 29.79707 r 7 0.072974 28.79544 15.49471 r 8 0.044209 10.76133 3.841466 58