Business Cycle Synchronization and Financial Integration in the Asia-Pacific Region

Transcription

1 Chaper 4 Business Cycle Synchronizaion and Financial Inegraion in he Asia-Pacific Region Vicor Ponines Flinders Business School, Flinders Universiy Friska Parulian Economic Research Insiue for ASEAN and Eas Asia (ERIA) March 2010 This chaper should be cied as Poniners, V. and F Parulian (2010), Business Cycle Synchronizaion and Financial Inegraion in he Asia-Pacific Region, in Findlay, C., F. Parulian and J. Corbe (ed.), Linkages beween Real and Financial Aspecs of Economic Inegraion in Eas Asia. ERIA Research Projec Repor , Jakara: ERIA. pp

2 Chaper 4 Business Cycle Synchronizaion and Financial Inegraion in he Asia Pacific Region Vicor Ponines Flinders Business School Flinders Universiy Friska Parulian Economic Research Insiue for ASEAN and Eas Asia (ERIA) Indonesia Absrac This paper explores he facors ha drive business cycle synchronizaion (BCS) in he Asia Pacific region. Three main facors ha figure prominenly in he lieraure, viz., rade inensiy, similariy of indusrial srucure and financial inegraion, are analyzed, wih emphasis on he impac of financial inegraion on BCS. We employ a dynamic panel GMM approach in our esimaion in order o conrol for biases associaed wih simulaneiy and unobserved counry-pair specific effecs. Our resuls agree wih heoreical predicions from he benchmark inernaional business cycle models greaer financial inegraion leads o divergen BCS. This srongly suggess ha conrolling for biases associaed wih simulaneiy and unobserved counry-pair heerogeneiy using a panel-based IV esimaor is crucial in unraveling he conrasing evidence found in he empirical lieraure. Once such biases are accouned for, he predicion by heory regarding he inverse relaionship beween financial inegraion and BCS becomes apparen. Keywords: financial inegraion, business cycle synchronizaion, Asia Pacific counries, dynamic panel GMM, inernaional business cycle models JEL Classificaions: C23, E32, E44, F36 94

3 Inroducion In he pas decade, he buzzword amongs policymakers, observers and academics has been globalizaion. Arising from he srong growh of rade, finance, ransporaion and communicaion, he impression has been ha he world has increasingly become borderless or o operae in sync as a single global marke. Fas forward o he pas year or so and, agains he backdrop of he global financial urmoil, a differen heme has emerged decoupling. The erm emanaes from he observaion ha despie weakening economic condiions in he US and a number of indusrial counries, economic condiions in emerging-marke counries have been surprisingly srong and resilien. This percepion challenges convenional wisdom ha when he US economy sneezes, he res of he world economy, especially emerging-marke counries, caches a cold. Iniially one could hink ha greaer rade and financial linkages would lead o igher business cycles insead of being divergen or asynchronous. A perfuncory inspecion of he daa would indeed sugges so (Lane and Milesi-Ferrei, 2004, 2007). However, heoreical predicions sugges ha rade and financial linkages can influence business cycle synchronizaion (henceforh BCS) eiher way. For example, sandard inernaional business cycle heories predic ha greaer financial inegraion should lead o a lower degree of BCS, whereas models of financial conagion, such as Allen and Gale (2000) show how inernaional financial inegraion can lead o financial panic and hus o synchronized business cycles. The quesion herefore is an empirical one, bu he curren empirical lieraure does no help as i fails o find a robus and sysemaic relaionship. Pure cross-secional sudies, for insance, find a significanly posiive relaionship beween financial inegraion and BCS, e.g. Imbs (2004, 2006). However, recen sudies using panel daa show a srong negaive effec, e.g. Cerqueira and Marins (2009) and Kalemli-Ozcan e al. (2009), and hus are in conformiy wih he basic ideas of sandard inernaional business cycle heories. This paper conribues o he empirical lieraure in a number of ways. Firs, we ake he pragmaic approach of using quaniy- and price-based indicaors of financial inegraion o ensure robusness in our resuls. This is imporan as he lack of mandaory reporing of acual bilaeral informaion on FDI and porfolio invesmen daa, which limis many 95

4 previous sudies (including ours), makes his a sensible and logical sraegy. 1 Second, in view of he daa limiaion jus menioned, we exploi he availabiliy for a number of years of survey-based daa on porfolio invesmen from he Coordinaed Porfolio Invesmen Survey (CPIS) gahered by he IMF. To he bes of our knowledge no sudy employs his daase o ascerain he direcion of he BCS finance link in a panel conex. Third, as we are using panel daa, we adop a panel-based GMM approach in our esimaion. We believe ha his echnique gives us wo imporan advanages compared o previous approaches, namely, conrolling for biases associaed wih simulaneiy, and unobserved counry-pair specific effecs. Finally, we examine he impac of rade and financial linkages on BCS across a broad cross-secion of Asian and Pacific counries. The evidence is mosly for OECD or indusrial counries, and lile empirical work has been done in his par of he world. Previous empirical works by Park and Shin (2009) and Shin and Sohn (2006) find eiher a negligible or an insignifican effec of financial inegraion on BCS. 2 Our resuls agree wih he benchmark sandard inernaional business cycle models. This srongly suggess ha conrolling for biases associaed wih simulaneiy, le alone unobserved counry-pair heerogeneiy, using a panel-based IV esimaor is crucial in unraveling he conrasing evidence found in he empirical lieraure. In a pure crosssecional insrumenal-variable regression any unobserved ime-invarian counry-pair specific effecs would be par of he error erm, leading o biased esimaes of he coefficiens, and as such previous sudies ha examine he direcion of he BCS finance link using pure cross-secional daa are affliced by his problem. Once biases associaed wih simulaneiy and unobserved counry-pair specific facors are accouned for, he heoreical predicion regarding he inverse relaionship beween financial linkages and BCS becomes apparen in he resuls. The res of he paper is srucured as follows. The nex secion reviews he lieraure on he relaionship beween financial inegraion and BCS. Secion 3 describes he daa and 1 Excepions o his limiaion are Kalemli-Ozcan e al. (2009), who use BIS proprieary daa on OECD counries, and Garcia-Herrero and Ruiz (2008), who use a novel daase on bilaeral flows beween Spain and a large number of counries aken from he Spanish Balance of Paymens. 2 An excepion is by Lee and Azali (2010), who look a a smaller sub-secion of counries han we examine in his paper and who emphasize OCA crieria. 96

5 he measures used for each of he variables. Secion 4 describes he esimaion sraegy. Secion 5 presens he empirical resuls. Secion 6 offers some policy implicaions emanaing from he resuls, and Secion 7 concludes. 2. Lieraure Background Financial inegraion has been argued o affec business cycle synchronizaion bu as o wheher i should lead o igher or synchronized business cycles is unclear. Sandard inernaional macro heories predic ha greaer financial inegraion should lead o a lower degree of business cycle synchronizaion. As shown by Backus e al. (1992) and Baxer and Crucini (1995), in a wo-counry general equilibrium model wih complee financial markes, a counry hi by a posiive produciviy shock receives capial from he oher counry, resuling in a negaive oupu correlaion beween he wo. Similarly, Backus e al. (1994) documen ha complee markes resul in negaively correlaed GDP because an economy hi by a posiive echnology shock will arac capial flows away from he no-shock economy. Heahcoe and Perri (2001, 2003, 2004) also find resuls ha are in line wih he above menioned sudies hrough a model in which inernaional financial marke inegraion occurs endogenously in response o less-correlaed shocks. They argue ha increasing globalizaion in financial markes is he key for less inernaional co-movemen. A combinaion of less-correlaed shocks coupled wih he resuling deepening of inernaional asse markes can accoun for he less-correlaed inernaional real business cycle. Likewise, inernaional specializaion heories along he lines of Obsfeld (1994) yield a similar predicion. However, surprisingly, he empirical evidence is sill mixed as o he relaionship beween financial inegraion and business cycle correlaion. In a pure cross-secional conex, sudies find a significanly posiive relaionship beween financial inegraion and BCS. Using a sysem of simulaneous equaions, Imbs (2004) finds evidence ha economic regions wih srong financial links are significanly more synchronized. Employing he same approach bu using he 2001 Coordinaed Porfolio Invesmen Survey (CPIS) gahered by he IMF, Imbs (2006) finds similar resuls. Kose e al. (2003) using a cross-counry sample of 76 counries 21 indusrial and 55 developing 97

6 find evidence ha financially open developing economies have synchronized cycles wih he core rich G7 counries over he period Davis (2009) also finds a posiive relaionship beween inernaional credi and BCS over a cross-counry sample of 58 counries from 1991 o Jansen and Sokman (2004) invesigae he relaionship beween FDI and BCS over he period using daa from Canada, France, Germany, he Neherlands, he UK and he US, and find ha he rapid expansion of FDI can be relaed o he phenomenon of more synchronized business cycles. Finally, Kose e al. (2008a) and Kose e al. (2008b) find he same resuls wih a dynamic laen facor model. A noable excepion ha documens a negaive relaionship beween financial inegraion and BCS in a pure-cross secion conex is by Garcia-Herrero and Ruiz (2008). Using acual bilaeral financial flows from Spain hese auhors esimae a sysem of simulaneous equaions and find ha greaer financial inegraion leads o divergen BCS. Bordo and Heibling (2003) also find a long-run increase in cycle synchronizaion, bu conclude ha lile of i can be ascribed o a proxy of financial inegraion using he removal of capial conrol. Alhough one can reconcile hese sudies ha find a posiive relaionship beween financial inegraion and BCS based on models of financial conagion, such as Allen and Gale (2000), which show how inernaional financial inegraion can lead o financial panic and hus o synchronized business cycles, hese sudies conflic wih he benchmark inernaional business cycle models discussed above. Opposed o cross-counry sudies ha consisenly find a posiive effec of financial inegraion on BCS, some recen sudies using panel daa show a robus negaive effec, and hus are in conformiy wih he basic ideas of sandard heories. For insance, using panel hree-sage leas squares esimaion for 15 OECD counries from 1984 o 2003, Xing and Abbo (2007) find ha economic regions wih srong financial links are significanly less synchronized. Using GMM mehods for 20 OECD counries from 1970 o 2002 Cerqueira and Marins (2009) also find a negaive and significan effec of financial inegraion on BCS. Using daa for eigh Asian counries ASEAN5 (Indonesia, Malaysia, he Philippines, Singapore and Thailand), plus hree addiional members of Eas Asia (China, Japan and Korea) Lee and Azali (2009) also find a 98

7 similar significanly negaive effec. Finally, Kalemli-Ozcan e al. (2009), using a rich panel daa srucure on banks inernaional bilaeral exposure over he pas hree decades across 20 developed counries, show ha once counry-pair and ime-fixed effecs are conrolled for, a higher degree of cross-border financial inegraion leads o less synchronized, more divergen business cycles. A noable excepion ha documens a posiive relaionship beween financial linkages and BCS using panel daa is by Schiavo (2008). Using a sysem of simulaneous equaions for 190 developed counry pairs over he period , he sudy shows ha financial inegraion is associaed wih less-divergen business cycles. Inklaar e al. (2007), using a sample of 21 OECD counries over he period , find ha he financial inegraion measures suggesed by Imbs (2004) are no robusly relaed o BCS. 3. Daa and Measuremen In order o examine empirically he effec of financial linkages as well as he effec of wo oher channels rade linkages and similariy in indusrial srucure on BCS, we esimae he following equaion: ij, 0 1ij, 1 1T ij, 2Sij, 3Fij, ij,, (1) where i,j represens counry pair i and j; ij, denoes he business cycle correlaion or synchronizaion (BCS) beween counries i and j; ij, -1 is he lagged BCS beween counries i and j; T ij, is a measure of bilaeral rade inensiy; S ij, is an index of he similariy of he indusrial srucure beween counries i and j; and F ij, is a measure of financial inegraion beween counries i and j. In Equaion 1 we assume ha ij, conains he following wo effecs: (i) he unobserved ime-invarian counry-pair specific effec, η ij,, and (ii) a sochasic error erm ε ij,, varying across ime and crosssecion. We adop a panel approach over he period To acquire a meaningful measure of business cycle correlaion as well as o purge any possible cyclical effecs on 99

8 he variables, he 28 years have been spli ino subperiods of four years each. 3 Our sraegy of invesigaion assumes ha counries in he Asia Pacific region inegrae wihin he region as well as wih wo major economic blocs he Unied Saes and he EU-14. The EU bloc includes Ausria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Ialy, he Neherlands, Porugal, Spain, Sweden and he UK. The Asian Pacific bloc comprises China, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, he Philippines, Singapore, Taiwan, Thailand, Ausralia and New Zealand. The business cycle correlaions refer o he Pearson correlaion of cyclical componen of annual real GDP expressed in US dollars beween counries i and j over he relevan subperiods. The cyclical componens of GDP are compued in wo ways afer aking he naural logarihms of real GDP: (i) using he Hodrick Presco (HP) filer, and (ii) he Baxer King (BK) band-pass filer. 4 Two differen measures of bilaeral rade inensiy will be considered. The firs is a sandard measure used in many recen sudies, for insance, Clark and van Wincoop (2001), Frankel and Rose (1997, 1998) and Imbs (2004) among ohers, and is calculaed as: T 1 i, j 1 T X ij, Y i, M Y ij, j, (2) where X ij, denoes oal merchandise expors from counry i o j in year, M ij, denoes impors o i from j, and Y i denoes nominal GDP in counry i. An alernaive measure, proposed by Clark and van Wincoop (2001) based on he model in Deardoff (1998), and employed by Imbs (2004, 2006) among ohers, can be consruced as: T 2 i, j T ( X ij, M ij Y Y i,, j, ) Y W (3) W where Y is world GDP. T 2 differs from T 1 in ha i is independen of counry size and depends only on rade barriers. In he empirics, we ake he naural logarihm of boh , , , , , and We do no broach he lieraure on he appropriae measure of synchronizaions of business cycles, noing only ha mos sudies employ simple bilaeral correlaion coefficiens in order o measure he srengh and direcion of he associaion beween he cyclical componens of he annual real GDP of wo counries. 100

9 measures of bilaeral rade inensiy. We inerpre ha he higher he values of T 1 and T 2 he greaer he rade inensiy beween counries i and j. In erms of Equaion (1), he sign of β 1 can be posiive or negaive as heory predics ha closer bilaeral rade could resul in synchronized (posiive) or asynchronous (negaive) business cycles. There are no sandard measures of similariy in indusrial srucures (Imbs, 2004). We use wo measures of similariy in indusrial srucures for comparabiliy wih exising research. The firs, a measure akin o a Herfindahl index of concenraion, is employed in Clark and van Wincoop (2001), Imbs (2004, 2006) and Krugman (1991), among ohers, and is measured as: 1 1 Si, j S ni S nj, (4) T N n where S ni and S nj denoe he GDP shares for indusry n in counries i and j, respecively. If wo counries had idenical indusrial srucures, ha is, he indusry shares in GDP were he same for counries i and j, hen he index would be 0. On he oher hand, when wo counries have compleely disjoined or differen indusrial srucures, he index reaches a maximum value of 2. Therefore, lower values of S 1 imply more similariy in indusrial srucure beween counries i and j. Our second measure of similariy of indusrial srucure, suggesed by Shea (1996) and used by Imbs (2001, 2003) and Baxer and Kouparisas (2005) is he correlaion of indusry shares: S 2 i, j 1 T N n N n S S 2 ni ni S nj N n S 2 nj (5) If S ni = S nj, ha is, GDP shares of each indusry are he same in counries i and j, S 2 is equal o 1. In oher words, lower values of S 2 imply less similariy in indusrial srucure beween counries i and j. We also ake he naural logarihms of boh measures of similariy of indusrial srucure in our empirics. Theory clearly predics ha similar producion paerns beween counries should lead o synchronized business cycles, and 101

10 as such he sign of β 2 changes depending on he measure used for similariy of indusrial srucure in Equaion (1). Tha is, S 1 implies β 2 < 0, while S 2 implies β 2 > 0. Bilaeral financial inegraion can be difficul o measure effecively. On his basis, our measures of financial inegraion encompass quaniy- and price-based measures o ensure robusness. We firs discuss our quaniy-based measures of financial inegraion and hen urn o our price-based measures. Our quaniy-based measure of financial inegraion is consruced in hree ways. The firs measure uses he recenly updaed daase of Lane and Milesi-Ferrei (2007) and, following Cerqueira and Marins (2009), is calculaed as he average of he sum of socks of asses and liabiliies of foreign direc invesmen (FDI) and porfolio invesmen beween counries i and j scaled by nominal GDP: 5 F 1 ij, 1 T Ai, Li Yi,, A j, Y L j, j,, (6) where Ai, and Li, are oal asses and liabiliies of counry i, a ime. We can inerpre F 1 as a measure of he exen of openness beween pairs of counries o global financial markes, and as such we hink of higher values of F 1 when pairs of counries are more financially inegraed wih world financial markes. An alernaive measure of financial openness, which builds on he IMF s Annual Repor on Exchange Arrangemens and Exchange Resricions (AREAER) and is hus based on informaion on conrols on financial flows, is he index-based measure recenly pu ogeher by Chinn and Io (2008). To consruc a bilaeral measure, he average of he sum of he indices beween counries i and j is calculaed as: 2 1 F ij, ( ITOi, ITO j, ), (7) T where ITO i, and ITO j, denoe he Chinn Io indices for counries i and j, respecively. Likewise, F 2 akes higher values when pairs of counries have officially lower resricions on financial flows. 5 Also using he Lane and Milesi-Ferrei daase, Imbs (2004) consrucs his own alernaive measure of bilaeral financial inegraion by using he difference beween he socks of asses and liabiliies (ne foreign asse) beween counries i and j. 102

11 Finally, one of his paper s conribuions is o use in a panel conex he Coordinaed Porfolio Invesmen Survey (CPIS) gahered by he IMF ha provides direc observaions on bilaeral asse holdings from 2001 unil A he ouse, however, one should also recognize ha he daa have heir own limiaions. Problems of underreporing (Lane and Milesi-Ferrei, 2004), non-inclusion of foreign direc invesmen (FDI), and he absence of some counries in he collecion in view of he non-mandaory naure of he reporing, are some of he concerns ha plague hese daase (Imbs, 2006). 7 Noneheless, given our awareness of he problems inheren in he daase, which is borne ou of he lack of daa sources based on mandaory reporing of bilaeral informaion on FDI and porfolio invesmen, our hird quaniy-based measure of financial inegraion is compued, as in Garcia-Herrero and Ruiz (2008): F 3 ij, I Y ij, i, I Y ji, j,, (8) where I ij, represens financial flows from counry i o counry j a ime. Similar o F 1 and F 2, F 3 akes higher values when pairs of counries are more financially inegraed. In order o measure financial inegraion hrough a price-based indicaor, we follow Schiavo (2008) in defining financial inegraion as he Euclidean disance beween he spread among long- and shor-erm ineres raes as well as he spread among long-erm bank lending raes, respecively: F LS 2 2 ij, ( loiri loir j ) ( siri sir j ) (9) F LL 2 2 ij, ( loiri loir j ) ( bliri blir j ), (10) where loir i, sir i, blir i are he long- and shor-erm and bank lending raes in counry i. The underlying argumen behind boh measures is ha i uilizes he noion ha ineres rae equalizaion can be expressed in he form of disance from he law of one price saring from long- and shor-erm ineres raes (F LS ) or from long-erm bank lending raes (F LL ). The appeal of boh measures is ha hese raes span orhogonal markes 6 Imbs (2006) uses he 2001 CPIS survey daa, which effecively makes i a pure cross-secional sudy. 7 For insance, wo of he 13 Asia Pacific counries ha are examined in his paper, namely, China and Taiwan, are boh absen from he collecion. 103

12 and herefore give a muli-faceed or complee picure of closer financial inegraion raher han focusing only on a single rae, which may produce a disored picure (Schiavo, 2008). Being a measure of disance from he law of one price, higher values of F LS and F LL imply less financial inegraion beween counries i and j. As discussed in Secion 2 above, sandard inernaional business cycles heories show ha greaer financial inegraion leads o divergen business cycles and as such he sign of β 3 changes, depending also on he measure used for financial inegraion in Equaion (1). Tha is, F 1, F 2 and F 3 all imply β 3 < 0, while F LS and F LL boh imply β 3 > Some Sylized Trends As a preliminary sep, his secion presens a graphical evoluion of our measures of BCS as well as he measures of financial inegraion ha we employ laer in our analysis. We begin by examining he sylized rends in our BCS measures over he period considered in our analysis. Figure 1 presens he business cycle synchronizaion beween he Asia Pacific economies and he EU-14. The figure has wo graphs, one for each of derending echniques used he Hodrick Presco (HP) filer and he Baxer King (BK) band-pass filer. Each graph conains ime-series plos of he average BCS for all possible pairs of Asian and EU-14 counries a a poin in ime. The average BCS level varies over ime beween 0.5 o 0.5, bu here are no obvious rends. To be sure, he Asian financial crisis of made he business cycle asynchronous beween hese wo regions as well as during he mid-2000s. However, by he end of he period of ineres, here is a divergence in oucome on wheher Asian business cycles became more (HP filer) or less (BK filer) correlaed wih he EU-14 counries. 8 Obviously, in relaion o cross-counry empirical sudies ha find a posiive relaionship beween financial inegraion and BCS, he sign of β 3 is he reverse of he above. Tha is, β 3 > 0 for F 1, F 2 and F 3, and β 3 < 0 for he case of F LS and F LL. 104

13 Figure 1. Asia EU Business Cycle Correlaion across Time.4 HP Filered BK Filered Noe: The correlaion is esimaed wih a four-year rolling window. Source: Auhors calculaions. 105

14 Figure 2. Asia US Business Cycle Correlaion across Time.6 HP Filered BK Filered Noe: The correlaion is esimaed wih a four-year rolling window. Source: Auhors calculaions. 106

15 Figure 2 is an analogue ha considers he BCS of he Asia Pacific economies o he Unied Saes. In he afermah of he seep decline in BCS levels around he ime of he Asian financial crisis, BCS levels ypically hovered around 0.4 or so in he 2000s. However, as porrayed in he figure, here is a endency beween business cycles across he Asia Pacific counries and he Unied Saes in 2007 o be less correlaed. Finally, Figure 3 is an analogue ha considers he inra-asia Pacific counries BCS levels over ime. The single mos sriking observaion of Figure 3 is he marked conras in average BCS levels in his figure as compared, in paricular, wih he average BCS levels presened in Figure 2. This suggess a shrinking relaionship beween he business cycles of he Asia Pacific counries and wih major counries ouside of i, mos especially he Unied Saes, whereas, a he inra-regional level, decoupling does no seem o be a phenomenon over ime. Obviously, he above analysis has is limiaions, and hus should be aken as indicaive only on wheher business cycles in he Asia Pacific economies are moving asynchronously or are decoupled over ime wih he wo major economic blocs considered in he analysis. For one, he analysis is uncondiional no oher facors have been aken ino accoun as possibly affecing BCS. This will be he focus of our aenion in he subsequen secions, bu before ha we ake a brief look a he rends of our financial inegraion measures over ime. 107

16 Figure 3. Asia Asia Business Cycle Correlaion across Time HP Filered BK Filered Noe: The correlaion is esimaed wih a four-year rolling window. Source: Auhors calculaions. 108

17 Figure 4. Financial Inegraion over Time (Quaniy-Based) 12 Financial Inegraion ASIA and ASIA ASIA and EU ASIAand USA 4.0 Financial Inegraion ASIA and ASIA ASIA and EU ASIA and USA.016 Financial Inegraion ASIA and ASIA ASIA and EU ASIA and USA Noe: The correlaion is esimaed wih a four-year rolling window. Source: Auhors calculaions. 109

18 Figure 5. Financial Inegraion over Time (Price-Based) Financial Inegraion - FLS Financial Inegraion - FLL ASIA and ASIA ASIA and EU ASIA and USA ASIA and ASIA ASIA and EU ASIA and USA Noe: The correlaion is esimaed wih a four-year rolling window. Source: Auhors calculaions. 110

19 Figures 4 and 5 give a graphical depicion of he evoluion over ime of our quaniybased and price-based measures of bilaeral financial inegraion, respecively. Figure 4 has hree graphs, one for each of our bilaeral financial inegraion measures (F 1, F 2 and F 3 ). Each graph conains ime-series plos of he cross-counry-pair average of he relevan financial inegraion measure. 9 Figure 4 clearly shows ha, according o our firs measure of financial inegraion, Asia s inegraion wih world financial markes has increased considerably over he pas hree decades. Indeed, a more deailed inspecion of his paricular plo of F 1 indicaes ha he dramaic rise occurred around he middle of he 1990s. Whereas here is a clear and persisen upward rend in F 1, here is a reversal in Asia s openness o financial flows someime in he mid-1990s according o our second bilaeral measure (F 2 ). From his poin unil he end of he period considered, our second measure seems o flucuae around an approximaely consan mean, which inuiively suggess ha Asia has no made much furher progress in reducing formal resricions on financial flows in recen years. Wih regards o our las quaniy measure of bilaeral financial inegraion (F 3 ), in consisency wih Kim and Lee (2008), is evoluion porrays Asia s increasing hough limied inra-regional financial inegraion as i falls behind ha of is inegraion wih he US. Finally, Figure 5 presens a graphical depicion of our price-based measures of financial inegraion. Clearly, wih he excepion of he period around he ime of he Asian crises, cross-counry dispersion or disance from he law of one price is declining over ime, bu remains sizable, and is, likewise, suggesive of Asia s greaer inegraion wih he EU-14 and he US han wihin he region. Supplemenary resuls o he above discussions are provided by he uncondiional correlaions of he respecive bilaeral variables in Table While mos of our quaniy-based indicaors of financial inegraion end o show a very weak (almos zero) negaive relaionship wih our wo BCS measures, his sands in conras o he uncondiional correlaion resuls beween mos of our price-based indicaors and our 9 Noice ha he ime-scale axis for he graph conaining he F 3 measure is no in synch wih he oher wo measures. Recall from our previous discussion ha he F 3 measure is consruced using he CPIS daa which are only available for 1997 and hen from 2001 o The uncondiional correlaions for he smaller sample period of when using he CPIS daa in consrucing he hird quaniy-based indicaor of financial inegraion, i.e. F 3, is presened separaely in Table A1 in he Appendix. 111

20 wo BCS measures a weak posiive relaionship. Furhermore, he low correlaion (< 0.5) among our measures of he explanaory variables in Equaion (1) suggess ha mulicollineariy is no an issue here. 11 Table 1. Correlaion Marix of he Variables HP BK T1 T2 S1 S2 F1 F2 FLS FLL HP BK T T S S F F FLS FLL Noe: All variables are in logarihmic form wih he excepions of HP, BK, F 2, F LS and F LL. Source: Auhors calculaions. 4. Mehodology 4.1. Dynamic Panel GMM Technique 12 In a pure cross-secional regression any unobserved ime-invarian counry-pair specific effecs would be par of he error erm, leading o biased esimae of he coefficiens. Previous sudies of he direcion of he BCS finance link using pure cross-secional daa are affliced by his problem. A panel conex, however, allows us o conrol for hese unobserved ime-invarian counry-pair specific effecs and, as a resul, he problem of biased coefficien esimaes are eiher reduced or eliminaed. This is imporan as here is growing evidence in he lieraure ha culural biases and differences, for insance, have a subsanial impac on a variey of financial flows porfolio and direc invesmen (Ekinci e al., 2008; Guiso e al., 2009) as well as on foreign bank lending (Giannei and Yafeh, 2008; Mian, 2006). In addiion, he GMM esimaor does no require any paricular disribuions of he error erm. This veers away from he 11 I should be noed a his poin ha he high correlaion beween T 1 and T 2, S 1 and S 2 and F 1 and F 2 in Table 2 does no pose any mulicollineariy problems in he esimaion of Equaion (1) as wo respecive measures of, for insance, rade inensiy, are enered separaely as explanaory variables in Equaion (1). 12 The discussion ha follows draws in par on Calderon and Chong (2001), Chong and Gradsein (2007) and Levine e al. (2000). 112

21 complicaed inference inroduced by using a Pearson correlaion coefficien (bounded a 1 and 1) o measure BCS as he error erm is unlikely going o be normally disribued. In order o esimae our model (Equaion 1) consisenly and efficienly, we use a generalized mehod of momens (GMM) esimaor for dynamic panel daa models ha was inroduced by Holz-Eakin e al. (1990) and Arellano and Bond (1991), and furher developed in a series of papers including Arellano and Bover (1995) and Blundell and Bond (1998). This esimaor encompasses a regression equaion in boh differences and levels, each one wih is specific se of insrumenal variables. Consider he following regression equaion for BCS: y ij, yij, 1 X ij, ij ij,, (11) where y is he business cycle correlaion measure, X represens he se of explanaory variables apar from he lagged business cycle correlaion measure, η is an unobserved, ime-invarian counry-pair specific effec, ε is he error erm, and he subscrips i, j and represen counry pairs and ime period, respecively. We eliminae counry-pair specific effecs (η ij ) by aking firs differences of Equaion (11): y ij, yij, 1 ( ij, 1 ij, 2 ij, ij, 1 ij, ij, 1 y y ) ( X X ) ( ) (12) The use of own suiable lagged levels of y ij, as insrumens is required o deal wih he problem ha by differencing he lagged dependen variable (y ij, 1 y ij, 2 ) is correlaed wih he error erm, ε ij, ε ij, 1. The same sraegy is applied o form insrumens for oher explanaory variables ha are allowed o be endogenous in he sense ha hey can be affeced by curren and pas realizaions of business cycle correlaions. This feaure enables us o avoid simulaneiy bias due o he endogeneiy of our financial linkages variables. Sricly speaking, under he assumpion ha (i) he explanaory variables, X, are weakly exogenous (no correlaion wih fuure realizaions of he error erm), and (ii) he error erm, ε, is no serially correlaed, he dynamic panel GMM esimaor explois he following momen condiions: E [ y ij, s ij, ij, 1 ( )] 0 for s 2; = 3,,T (13) 113

22 E [ X ij, s ij, ij, 1 ( )] 0 for s 2; = 3,,T. (14) The resuling GMM esimaor based on hese condiions is known as he difference- GMM esimaor. There is, however, an issue wih he difference-gmm esimaor. If lagged dependen variables and explanaory variables are persisen over ime, he lagged levels likely represen weak insrumens for he firs-differenced variables. This causes finie sample bias and low accuracy, which leads o he need o complemen he regression in firs differences wih a regression in levels. The insrumens for he regression in firs differences are he same as above. The insrumens for he regression in levels, in urn, are he lagged differences of he same corresponding variables, under he assumpion ha alhough here may be correlaion beween he levels of he righhand side variables and he counry-pair specific effec in Equaion (11), none exiss beween he differences of hese variables and he counry-pair specific effec. The addiional momen condiions for he regression in levels are: E E [ y ij, s yij, s1 ij ij, ) ( )] 0 for s = 1 (15) [ X ij, s X ij, s1 ij ij, ) ( )] 0 for s = 1. (16) The consisency of he GMM esimaor depends on wheher lagged values of he explanaory variables are valid insrumens in he regression. To address his issue, we consider wo specificaion ess: he firs is he Hansen es of over-idenifying resricions, which ess he overall validiy of he insrumens. Failure o rejec he null hypohesis suppors he model. The second es examines he hypohesis ha he error erm is no serially correlaed. We es wheher he differenced error erm, ha is, he residual of he regression in differences, is second-order serially correlaed. 13 If he es fails o rejec he null hypohesis of absence second-order serial correlaion, we conclude ha he original error erm is serially uncorrelaed and use he corresponding momen condiions. 13 Second-order serial correlaion of he differenced residual indicaes ha he original error erm is serially correlaed and follows a moving-average process a leas of order one. 114

23 5. Esimaion Resuls Table 2 presens he dynamic panel GMM esimaion resuls using business cycle correlaion or synchronizaion as he dependen variable. The able has six columns. The firs column refers o he explanaory variables used in he esimaion of a paricular specificaion of he dynamic panel GMM. The second o fourh columns conain he coefficien esimaes of he explanaory variables, ha is, measures of rade, similariy of indusrial srucure, and financial, respecively, along wih he p-values in square brackes; esimaes ha are significanly differen from zero a he 0.10, 0.05 and 0.01 are marked by one, wo and hree aserisks, respecively. The las wo columns conain he specificaion ess resuls. The able also conains wo panels. The upper panel conains he resuls using he Hodrick Presco filer; he lower panel conains he esimaes using he Baxer King band-pass filer. Each panel has four ses of resuls, and each se is delineaed based on he measure of financial inegraion (F) used as he explanaory variable in he GMM esimaion. In urn, each se conains four rows of resuls ha perain o all possible permuaions of F wih he oher explanaory variables T (bilaeral rade) and similariy of indusrial srucure (S). We begin by examining he specificaion es resuls. The Hansen es of overidenifying resricions in all cases does no rejec he null hypohesis ha he insrumens are no correlaed wih he error process. In addiion, ess of serial correlaion fail o rejec he null ha he error erm, expressed in firs differences, is no second-order serially correlaed in all cases. This suppors using lags of he explanaory variables as insrumens In addiion, apar from using inernal insrumens, i.e. lags of he explanaory variables, we also included he pair-wise sum of he recenly updaed exchange rae regime classificaion of Reinhar e al.(2010), he pair-wise sum of GDP per capia, and he absolue value of differences in GDP per capia as exernal insrumens in he GMM esimaions. 115

24 Table 2. Dynamic Panel GMM esimaions of Business Cycle Synchronizaions (Crisis Years Included) Variables Trade (T ij, ) Specializaion (S ij, ) Finance (F ij, ) Hansen es (p value) AB es for AR(2) (p-value) Hodrick Presco Derended T 1, S 1, F [0.00]*** [0.04]** [0.01]** T 2, S 1, F [0.01]** [0.01]** [0.00]*** T 1, S 2, F [0.00]*** 1.27 [0.03]** [0.00]*** T 2, S 2, F [0.01]** 1.85 [0.03]** [0.00]*** T 1, S 1, F [0.00]*** [0.00]*** [0.00]*** T 2, S 1, F [0.05]** [0.12] [0.03]** T 1, S 2, F [0.00]*** [0.00]*** [0.00]*** T 2, S 2, F [0.02]** 2.68 [0.00]*** [0.00]*** T 1, S 1, F LS [0.01]** [0.02]** [0.05]* T 2, S 1, F LS [0.01]** [0.42] [0.04]** T 1, S 2, F LS [0.00]** [0.04]** [0.05]* T 2, S 2, F LS [0.02]** [0.07]* [0.03]** T 1, S 1, F LL [0.04]** [0.02]** [0.07]* T 2, S 1, F LL [0.04]** [0.02]** [0.00]*** T 1, S 2, F LL [0.01]** [0.04]** [0.07]* T 2, S 2, F LL [0.02]** [0.27] [0.02]** Baxer King Derended T 1, S 1, F [0.01]** [0.00]*** [0.00]*** T 2, S 1, F [0.00]*** [0.00]*** [0.00]*** T 1, S 2, F [0.01]** [0.00]*** [0.00]*** T 2, S 2, F [0.00]*** [0.00]*** [0.00]*** T 1, S 1, F [0.98] [0.30] [0.01]** T 2, S 1, F [0.02]** [0.28] [0.00]*** T 1, S 2, F [0.51] [0.21] [0.01]** T 2, S 2, F [0.02]** [0.25] [0.00]*** T 1, S 1, F LS [0.09]* [0.72] [0.00]*** T 2, S 1, F LS [0.02]** [0.00]*** [0.00]*** T 1, S 2, F LS [0.02]** [0.72] [0.01]** T 2, S 2, F LS [0.01]** [0.00]*** [0.01]** T 1, S 1, F LL [0.22] [0.53] [0.02]** T 2, S 1, F LL [0.01]** [0.00]*** [0.00]*** T 1, S 2, F LL [0.08]* [0.95] [0.02]** T 2, S 2, F LL [0.01]** [0.00]*** [0.01]** Noes: Numbers in square brackes are p-values. Significance levels: *10%, **5%, ***1%. The GMM esimaions include lags of he dependen variable as well as ime-dummies. The esimaes of he impac of bilaeral rade inensiy on BCS are srongly posiive (more rade beween wo counries induces higher BCS). Of he 32 coefficiens (= 2 116

25 derending echnique 2 measures of bilaeral rade linkages 2 measures of similariy of indusrial srucure 4 measures of financial inegraion, 15 wo are significan a he 10% level, 21 are significanly so a he 5% level, and six a he 1% level. Of hese saisically significan coefficiens, hese coefficiens range from 0.04 (using T 2 as one of he regressors in he GMM esimaion) o (using T 1 as one of he regressors), and his means ha an increase by our relevan measure of bilaeral rade inensiy by one sandard deviaion implies ha BCS saring from is mean would increase from (= 1.547*0.016) o (= 0.04*6.35). On average, his represens moving he correlaion of oupu by abou 22% of one sandard deviaion, quie an economically significan effec. Concerning similariy of indusrial srucure, mos esimaed coefficiens are significan, alhough once we conrol for endogeneiy some of he esimaed coefficiens have incorrec signs (we should expec ha S 1 < 0, S 2 > 0; more similar counries have higher BCS). Of he 32 coefficiens, 28 have correc signs; of hese 28 coefficiens, one is significan a he 10% level, seven are significan a he 5% level, and 11 a he 1% level. Finally, we found in our esimaion resuls ha he higher is he financial linkages beween counries (higher F 1 and F 2, lower F LS and F LL ) he less synchronizaion of business cycles. This finding is srikingly consisen across all esimaed coefficiens, all of which are saisically significan a convenional significance levels. These esimaed coefficiens range from o (boh using F 2 as one of he regressors), and from o (boh using F LL as regressor). 16 This means ha an increase by one sandard deviaion by our relevan measure of financial linkages implies ha BCS saring from is mean would be reduced from o (using F 2 as one of he regressors), while BCS increases from o (using F LL as regressor). In urn, his represens moving he correlaion of oupu from 20% o 60% of one sandard deviaion, again quie an economically significan effec. 15 Noe ha here are five measures of financial inegraion used in his paper. The resuls using he fifh measure are presened in a separae able. 16 We recognize ha we are dealing wih quaniy- and price-based indicaors of financial inegraion, and as such we separae he economic inerpreaion of he size coefficiens based on his disincion. 117

26 Table 3 is an analogue o Table 2, bu excludes he crisis years of from he GMM esimaion. Alhough some of he esimaed coefficiens los heir saisical significance, he general feaures and sory of he resuls are sill srikingly similar o is Table 2 analogue. Table 4 is also an analogue o Table 2 ha considers our final indicaor of financial inegraion (which is also our hird quaniy-based indicaor of financial inegraion) using he 2001 o 2007 CPIS daa. 17 Though wo as well as four of he eigh esimaed coefficiens of he indicaors for financial and bilaeral rade linkages, respecively, are saisically indisinguishable from zero, his addiional sensiiviy es does no undermine he iniial findings: boh specificaion ess are fulfilled; a slighly weaker alhough consisen resul indicaes ha more rade beween wo counries induces higher BCS; here are some indicaions ha more similar counries have higher BCS; and; finally, increased financial linkages beween counries leads o divergen BCS. 17 In order o creae he measure of BCS, i.e. he correlaion beween cyclical oupu in counries i and j, we follow Rose (2009) by using 20 quarerly observaions (five years) preceding hrough ime τ. 118

27 Table 3. Dynamic Panel GMM esimaions of Business Cycle Synchronizaions (Crisis Years Excluded) Variables Trade (T ij, ) Specializaion (S ij, ) Finance (F ij, ) Hansen AB es for AR(2) es (p-value) (p-value) Hodrick Presco Derended T 1, S 1, F [0.00]*** [0.76] [0.01]** T 2, S 1, F [0.01]** [0.01]** 0.573[0.00]*** T 1, S 2, F [0.00]*** [0.03]** [0.00]*** T 2, S 2, F [0.01]** [0.02]** [0.00]*** T 1, S 1, F [0.00]*** [0.19] [0.00]*** T 2, S 1, F [0.02]** [0.39] [0.51] T 1, S 2, F [0.00]*** [0.10] [0.00]*** T 2, S 2, F [0.06]** [0.00]*** [0.00]*** T 1, S 1, F LS [0.01]** [0.73] [0.05]** T 2, S 1, F LS [0.03]** [0.00]*** [0.89] T 1, S 2, F LS [0.00]*** [0.66] [0.04]** T 2, S 2, F LS [0.86] [0.00]*** [0.10] T 1, S 1, F LL [0.03]** [0.45] [0.06]* T 2, S 1, F LL [0.03]** [0.10] [0.89] T 1, S 2, F LL [0.01]** [0.38] [0.04]** T 2, S 2, F LL [0.09]* [0.02]*** [0.24] Baxer King Derended T 1, S 1, F [0.01]** [0.06]* [0.00]*** T 2, S 1, F [0.00]*** [0.04]** [0.00]*** T 1, S 2, F [0.01]** [0.09]* [0.00]*** T 2, S 2, F [0.00]*** [0.05]* [0.00]*** T 1, S 1, F [0.85] [0.08]* [0.00]*** T 2, S 1, F [0.01]** [0.01]** [0.00]*** T 1, S 2, F [0.40] [0.04]** [0.00]*** T 2, S 2, F [0.01]** [0.01]** [0.00]*** T 1, S 1, F LS [0.09]* [0.17] [0.01]** T 2, S 1, F LS [0.99] [0.05]* [0.00]*** T 1, S 2, F LS [0.02]** [0.17] [0.00]*** T 2, S 2, F LS [0.86] [0.12] [0.02]** T 1, S 1, F LL [0.37] [0.17] [0.03]** T 2, S 1, F LL [0.67] [0.08]* [0.00]*** T 1, S 2, F LL [0.10] [0.37] [0.04]** T 2, S 2, F LL [0.96] [0.07]* [0.01]** Noes Numbers in square brackes are p-values. Significance levels: *10%, **5%, ***1%. The GMM esimaions include lags of he dependen variable as well as ime-dummies. 119

28 Table 4. Dynamic Panel GMM esimaions of Business Cycle Synchronizaions (Using CPIS Daa) Variables Trade (T ij, ) Specializaion (S ij, ) Finance (F ij, ) Hansen AB es for AR(2) es (p-value) (p-value) Hodrick Presco Derended T 1, S 1, F [0.04]** [0.17] [0.09]* T 2, S 1, F [0.05]* [0.29] [0.27] T 1, S 2, F [0.81] [0.09]* [0.05]** T 2, S 2, F [0.09]* [0.73] [0.66] Baxer King Derended T 1, S 1, F [0.03]** [0.01]*** [0.03]** T 2, S 1, F [0.52] [0.02]** [0.09]* T 1, S 2, F [0.30] [0.94] [0.05]* T 2, S 2, F [0.93] [0.62] [0.04]** Noes: Numbers in square brackes are p-values. Significance levels: *10%, **5%, ***1%. The GMM esimaions include lags of he dependen variable as well as ime-dummies. Source: Auhors calculaions. 6. Policy Implicaions The implicaions of he above resuls for Asian policy making are imporan and far reaching. Given ha Asia s inegraion wihin iself and wih counries ouside he region has advanced seadily in recen years, he finding of an inverse relaionship beween bilaeral financial linkages and BCS migh indicae ha financial inegraion makes i easier for hese counries o ransfer financial asses, which should help Asian counries diversify hemselves agains counry-specific risks, and hus enable heir decoupling (Flood e al, 2009; Garcia-Herrero and Ruiz, 2008). This is consisen wih he basic argumen underlying he heory of inernaional risk sharing, as furher financial inegraion offers beer opporuniies for risk diversificaion. In view of he benefis of increasing financial inegraion by affording beer risk sharing opporuniies, he imporance in acualiy of developing and srenghening capial markes hrough which agens can diversify heir porfolio via cross-border ownership of asses is essenial and canno be over-emphasized. Moving forward, reforms aimed a improving he capabiliy of agens o adjus he size of heir asse porfolio (savings rae), e.g. pension-fund schemes, in response o shocks as well as o 120

29 being more recepive of cross-border M&As can furher enhance risk-sharing opporuniies beween counries (Kalemli-Ozcan e al., 2004). On he oher hand, i is alleged ha he downside of greaer financial inegraion is ha i can pose risks o financial sabiliy. This claim akes on ever-increasing racion and prominence in discussions, especially in ligh of he recen painful experience wih he global financial crisis, which ends o demonsrae he role ha financial linkages play in he ransmission of shocks beween economies. However, despie concerns in policy circles, i appears ha he jury is sill ou on wheher greaer financial inegraion increases he likelihood of crises. For insance, in a recen sudy Fech e al. (2008) show ha he availabiliy of beer risk-sharing mechanisms end o offse he risk of spillover or ransmission of shocks, and hus financial inegraion leads o an improvemen in welfare as specializaion benefis are magnified and realized. 18 Furhermore, a few sudies argue ha greaer inegraion poses no risk o financial sabiliy on is own, bu when oo-rapid a liberalizaion of financial markes inerac, for insance, wih cerain disorions in he economy such as weak and lax supervisory regulaions as well as problems of credibiliy and enforcemens of conracs, hese disorions ge magnified and financial insabiliy problems arise (Fech e al., 2008). 19 Noneheless, as financial inegraion deepens and inernaional capial flows become more inense he enduring and considerable challenge for policy makers is o be able o couner balance he benefis and alleged risk of greaer financial inegraion. This radeoff will vary across economies as i will be a funcion of he level of financial marke developmen of individual counries in he region. Thus, he appropriae policy approach o enable counries o reap he benefis of he opporuniies ha come wih furher financial inegraion, e.g. inernaional risk sharing, and a he same ime conain he alleged inheren risk of greaer financial inegraion, will likely differ across counries in he region (BIS, 2009). 18 See also Bonfiglioli and Mendicino (2004) and Glick e al. (2006). For conrasing evidence, see for insance, Demirguc-Kun and Deragiache (2001) and Harmann e al. (2005). 19 See, for insance, Ishii and Habermeier (2002). 121