A Re-Examination of the Exchange Rate Disconnect Puzzle: Evidence from Firm Level Data 1

Transcription

1 A Re-Examinaion of he Exchange Rae Disconnec Puzzle: Evidence from Firm Level Daa 1 Rober Dekle Universiy of Souhern California Hyeok Jeong GRIPS Heajin Ryoo La Trobe Universiy June 2010 Absrac We reconcile he conflicing evidence beween he aggregae and firm level daa on he exchange rae elasiciy of expors. A simple correlaion beween exchange raes and expor quaniies using aggregae daa ha serves as he basis of some macroeconomic models resuls in insignifican esimaes of his elasiciy, while recen firm level evidence suggess significanly negaive values. Using firm level daa, we esimae a monopolisic compeiion model of exporing firms, and show ha he aggregae and firm level esimaes of his elasiciy agree wih each oher and are boh significanly negaive, as long as appropriae conrol variables are added o he esimaion equaion. JEL Classificaion: F41, F12, C23, C43 Keywords: Exchange rae disconnec puzzle, Consisen aggregaion, Firm level heerogeneiy, Exchange rae elasiciy of expor 1

2 1 Inroducion Over he las hree-decade experience of exchange rae floaing among indusrialized counries, here is ye o emerge a consensus regarding he impac of exchange rae flucuaions on expors. The empirical lieraure ha examined macroeconomic daa has generally found small or insignifican effecs of exchange rae flucuaions on he quaniy of expors. As an illusraion, Table 1 repors aggregae esimaes of he elasiciy of expors wih respec o exchange raes for each of he seven indusrialized G-7) counries of Canada, France, Germany, Ialy, Japan, U.K. and U.S., for he period of The las column pooled in Table 1 repors he esimae of he pooled sample including all seven counries wih counry dummies. We can see from he Table ha esimaes for his elasiciy are no significanly differen from zero for all he counries. 2 This lack of associaion beween exchange raes and expors a he aggregae level is an example of he so-called exchange rae disconnec puzzle. 3 Esimaes such as hose repored in Table 1 are imporan because hey have driven macroeconomic researchers o develop models o ry o explain his perceived lack of associaion beween exchange raes and expor volumes, usually relying on he local currency pricing assumpion, ha limis he response of expor prices o nominal exchange rae flucuaions. As an impressive example, Duare 2003) uses a calibraed general equilibrium model and shows ha by incorporaing local currency pricing LCP) and incomplee asse marke assumpions, a convenional general equilibrium model can accoun for he lack of correlaion beween expors and exchange raes. 4 In sharp conras o he resuls using aggregae daa, esimaes using firm level end o find a negaive relaionship beween appreciaing exchange raes and expor quaniies. Among oher sudies, Verhoogen 2008) finds ha following he 1994 peso devaluaion, Mexican firms increased heir expors. Fizgerald and Haller 2008), Dekle and Ryoo 2007), and Tybou and Robers 1997) find a negaive relaionship beween expors and an exchange rae appreciaion for Irish, Japanese and Columbian firms, respecively. Thus, i is imporan o deermine wha accouns for his discrepancy beween he resuls 2

3 using he aggregae and firm level daa, boh o build appropropriae macroeconomic models, and o conduc proper policy evaluaions on he impac of exchange rae changes on expor quaniies. In his paper, we ry o reconcile hese differen aggregae and firm level resuls. To moivae our esimaion equaion, we build a parial equilibrium model of monopolisic compeiion for exporing firms, and derive he relaionship beween expors and exchange raes as he exporing firm s supply equaion. The model is kep deliberaely simple, o resul in a linear relaionship beween expors and exchange raes a he firm level. Wihou lineariy, he expor equaion canno be aggregaed o he macroeconomic level in a sraighforward way. An explici model of he exporing firm is necessary o see exacly how he firm level produciviies will ener ino he aggregaed expor equaion. Heerogeneiy in his expor equaion arises, as produciviy differs among firms. We derive a macroeconomic relaionship beween expors and exchange raes by aggregaing his expor equaion across firms. We show ha in our example, he firm level produciviies ener in he aggregae expor equaion as a variance, and ha he omission of his variance can in principle cause he esimaes of he exchange rae elasiciy o be biased owards zero, by he usual omied variable argumens. We use panel daa of exporing firms of Japan o esimae he exchange rae elasiciy of expors a boh he firm and aggregae levels. 5 Esimaing he firm level expor equaion, we find ha he esimae of he exchange rae elasiciy of expors is negaive and significan, wih elasiciies ranging from o -0.77, wih he preferred esimae. Esimaing our aggregaed firm level expor equaion derived from our model, bu wihou including he firm level disribuional variable he variance of he firm level produciviies), we obain a saisically significan exchange rae elasiciy of aggregae expors of We hen perform an accouning exercise o idenify he facors responsible for our finding of a negaive aggregae exchange rae elasiciy here, and he finding of a small or zero elasiciy in he simple correlaions found in examples such as above. 6 We find ha simply by including he average values of he conrol variables arising from he model such as aggregae prices and produciviy, we can capure abou /-0.77) percen of he difference beween he 3

4 firm level esimae and he aggregae esimae of he exchange rae elasiciy. The remaining 15 percen is he pure aggregaion bias, arising from omiing he disribuional variable variance) of he firm level produciviies in he aggregae equaion. The idea ha price elasiciies are biased downwards in convenionally esimaed rade equaions, given he underlying aggregaion problem, was posulaed more han 50 years ago by Orcu 1950). To he bes of our knowledge, however, his is he firs paper o esimae and explicily compare he aggregae and firm level elasiciies of expors wih respec o exchange raes, where he macroeconomic expor equaion is obained by consisenly aggregaing he firm level expor equaions. Blundell and Soker 2005) carefully examine he general problems of aggregaion over heerogeneous individuals. Our paper provides a specific example of seeking he sources of and explicily quanifying he size of he aggregaion bias in he expor equaions. Furhermore, we idenify he preferences and echnologies from hese esimaes of he expor equaions. We find he imporance of decreasing reurns o scale echnology, and he high elasiciy of subsiuion among he consumpion goods in deermining he magniude of he exchange rae elasiciy of expors. This idenificaion of he deep parameers from he srucural esimaion of he expor equaion, o he bes of our knowledge, we do for he firs ime. There are also some recen papers ha have ried o reconcile he differen exchange rae responses of expors a he firm and aggregae levels. Berman, Marin, and Mayer 2009) focus on he produciviy heerogeneiy among firms. In heir model, in he spiri of Meliz 2003), only high produciviy firms will ener he expor marke, in response o an exchange rae depreciaion. The auhors show ha as an opimal response, hese high produciviy firms will raise heir prices ha is, increase heir markups insead of increasing heir expor quaniies. The auhors show ha his selecion effec of low quaniy response firms ino he overall expor marke can explain he weak impac of exchange rae movemens in aggregae daa. 7 Imbs and Mejean 2009) show ha he aggregaion of heerogeneous indusrial secors can resul in an aggregaion bias in he elasiciy of expors wih respec o exchange raes changes. In his paper, we focus on firms, raher han indusrial secors. 4

5 The paper is organized as follows. Secion 2 inroduces a sandard monopolisic compeiion model of exporing firms. Secion 3 discusses sources of bias in he aggregae expor equaions. Secion 4 esimaes he model. The elasiciy parameers including he exchange rae elasiciy) of he expor equaions are esimaed a boh he firm and aggregae levels. The preferences and echnology parameers of he model are also idenified from his esimaion. Secion 5 concludes. 2 Model 2.1 Monopolisic compeiion We consider a New Open Economy ype of monopolisic compeiion model, pioneered by Obsfeld and Rogoff 1996), for exporing firms. There are firms indexed by i [0, 1], each of which produces a single differeniaed final good indexed also by i) a each discree dae. The firms are locaed eiher in a domesic counry or in a foreign counry. The final goods ranging from [0, n] are produced by domesic firms and he res are produced abroad. A represenaive consumer ges uiliy from he following CES composie consumpion Y such ha 1 Y = 0 ) θ y θ 1 θ 1 θ i di, where y i denoes he consumpion of good i a dae. The parameer θ governs he elasiciy of subsiuion among he differeniaed goods, which we assume 1) θ > 1. In his monopolisic compeiion framework, he domesic price level P is given by 1 n ) 1 θ 1 P = p 1 θ p f 1 θ i i di + di, e 0 where p i denoes he price of good i ranging from 0 o n) in he domesic currency, p f i he price of good i ranging from n o 1) in he foreign currency, and e he foreign currency price of he domesic currency. We assume he law of one price n p f i = e p i. 5

6 This simplifies he domesic price level such ha [ 1 P = 0 ] 1 p 1 θ 1 θ i di. Similarly, he price level in he foreign counry P f is P f = [ 1 0 ) ] 1 1 θ p f 1 θ i di. The domesic consumer chooses his final goods consumpion bundle y i ) i [0,1] from uiliy maximizaion: 1 max y i ) i [0,1] 0 ) θ y θ 1 θ 1 θ i di subjec o 1 0 p i y i di Z, where Z denoes he nominal value of he oal expendiures of he domesic consumer. 8 This gives he domesic demand for final good i as y i = pi P ) θ Z P = pi P ) θ Y. ) Similarly, foreign demand for good i is y f i = p f θ i P Y f f. Then, he world demand for good i, yi w = y i + y f i, is given by y w i = pi P ) θ Y + p f i P f ) θ Y f = = pi P p f i P f ) θ Y w ) θ Y w, where Y w = Y + Y f denoes world aggregae consumpion, and hence he world s real income. The inverse demand funcions for he good i is: 2) 3) p i = P y w i p f i = P f Y w y w i Y w ) 1 θ, ) 1 θ. 6

7 2.2 Supply funcion of exporing firms The firm i a dae uses labor l i, capial k i and impored raw maerials m i o produce he differeniaed good q i according o he following generalized Cobb-Douglas form of echnology q i = A i li α ) α ) β ) γ ki mi, β γ where A i denoes he firm level oal facor produciviy erm. Define ρ = 1 α + β + γ). This parameer ρ measures he degree of reurns o scale: ρ > 0 for decreasing reurns o scale, ρ = 0 for consan reurns o scale, and ρ < 0 for increasing reurns o scale. Noe ha his reurns o scale parameer relaes o he firm level echnology, no o he aggregae echnology. We assume ha markes for hese inermediae inpus are perfecly compeiive. Le w, r and w f denoe he prices of labor l i, capial k i and impored raw maerials m i, respecively. Then, he cos funcion he minimized cos for he given inpu prices w, r and w f and oupu level q i ) dual o he producion funcion above is ) ) 4) C w, r, wf e, q i = w l i + wf e m i w, r, wf, q i e w, r, wf e, q i + r k i ) = α + β + γ) w ) α+β+γ r ) α β α+β+γ w, r, wf e, q i ) ) w f γ α+β+γ ) 1 qi α+β+γ, e A i where l i, k i and m i denoe he condiional facor demand funcions. A well-defined cos funcion is required o be non-negaive, homogeneous of degree one, monoone increasing, concave in inpu prices, and concave in oupu. 9 These properies of he cos funcion imply ha he parameer space should saisfy 5) α 0, β 0, γ 0 and ρ 0. The oal revenues of he monopolisic firm i facing he inverse demand funcions in equa- 7

8 ions 2) and 3) is 6) ) P f R, Y w, yi w e = p i y i + pf i e y f i = P f e Y w ) 1 θ y w i ) 1 1 θ. Given he cos funcion in 4), he revenue funcion in 6) and he marke clearing condiion q i = yi, w he oal supply of good i is deermined o maximize profis: ) ) P f yi w = arg max R yi w = 1 1 θ ) P f e, Y w, yi w e C 1 w, r, wf e, y w i Y w ) 1 θ Ai ) α+β+γ w ) α+β+γ r ) α β α+β+γ ) w f γ α+β+γ e ν, where [ ρ ν = α + β + γ + 1 ] 1. θ 2.3 Exchange rae elasiciy of expors Le s i be he expor share in he oal supply of good i. Then, we have he following ideniy for expors and hence he log expor equaion such ha 7) ln y f i = ν ln 1 1 ) θ νγ y f i = s iy w i, ν α + β) α + β + γ ln e α + β + γ ln wf + ν ln P f να α + β + γ ln w + ν θ ln Y w + νβ α + β + γ ln r ν α + β + γ ln A i + ln s i. Here, we assume ha he expor share s i is exogenously deermined. However, in general, he expor share may depend on he exporing firm s produciviy level. Unforunaely, in he daa, we do no direcly observe he fixed coss as well as oher poenial facors ha link expor shares and produciviy. In our empirical work, his may induce correlaion beween he idiosyncraic error erm, and he expor shares. Thus, in our empirical work, we insrumen he expor share, alhough we do no explicily endogenize hese shares. 8

9 From he log expor equaion 7) above, he elasiciy of expors wih respec o he exchange rae is given by: 8) ν α + β) ɛ = α + β + γ θ α + β) = 1 + ρθ 1). Firs, he exchange rae elasiciy of expors is negaive for all parameer values saisfying he resricions in equaions 1) and 5). Our model suggess ha expors should decrease, as he exchange rae increases i.e., as he domesic currency appreciaes relaive o he foreign currency). The magniude of he elasiciy, however, depends on he preferences θ) and echnology α, β and ρ) parameers. The larger he share of non-impored inpus he higher he α + β), or he larger he elasiciy of subsiuion among differeniaed goods he higher he θ), he larger he decrease in expors o he increase in exchange raes. The larger he degree of decreasing reurns o scale he higher he ρ), he smaller he decrease in expors o he appreciaion. In he exreme case of consan reurns o scale ρ = 0) and no use of impored raw maerials γ = 0 and hence α + β = 1), he elasiciy is compleely deermined by he elasiciy of subsiuion parameer θ, which has no upper bound, so ha expor quaniies can be exremely sensiive o he movemen of exchange raes. In he oher exreme case, where he exporing firm relies enirely on impored inpus α + β = 0), expor quaniies would no change a all o he movemen of exchange raes, regardless of he elasiciy of subsiuion and reurns o scale parameers. Idenificaion of hese preferences and echnology parameers would allow us o have a deeper undersanding on he exchange rae elasiciy of expors. In sum, our model of monopolisic compeiion implies: firs, ha he relaionship beween expors and exchange raes is log-linear, conrolling for facor prices, he foreign price level, world real income, he firm level produciviy and he expor shares; and second, ha he elasiciy of expors wih respec o he exchange rae is negaive, he magniude of which, depends on he preferences and echnology parameers. 9

10 3 Expor equaions 3.1 The firm level expor equaion The exchange rae elasiciy of expors ɛ can be inferred by esimaing he firm level log expor equaion 7). Noe ha he model imposes wo resricions on he coeffi ciens in he log expor funcion in 7). The sum of he coeffi ciens of ln w and ln r is equal o he coeffi cien of ln e, and he sum of he coeffi ciens of ln w, ln r and ln w f is equal o he negaive of he coeffi cien of ln P f. Wih hese resricions, he log expor funcion can be re-wrien such ha ln y f i = ν ln 1 1 ) ) ) ν α + β) θ α + β + γ ln w νβ e w f α + β + γ ln r 9) w ) P f +ν ln + ν w f θ ln Y w ν + α + β + γ ln A i + ln s i. To be specific, suppose ha firm level oal facor produciviy A i can be expressed as: 10) ln A i = κ + τ ln Φ + δ ln z i + ũ i, where Φ denoes aggregae oal facor produciviy TFP), z i he observable aribues of firm level produciviy, and ũ i he unobservable idiosyncraic produciviy erm. We allow he firm s expor share s i o depend on he firm s unobserved idiosyncraic produciviy erm. Thus we insrumen s i by he average expor share wihin he indusry in which he firm belongs, excluding is own share denoed by s i ). Tha is, we use he following insrumenal variables relaionship: 11) ln s i = a 0 + a 1 ln s i + v i, where ln s i is orhogonal o ũ i as well as o v i. Subsiuing he produciviy equaion in 10) and he expor share equaion in 11) ino he log expor equaion in 9), we ge he following log-linear expor equaion: 12) ln y f i = ϕ 0 + ϕ 1 ln ê + ϕ 2 ln r + ϕ 3 ln P f + ϕ 4 ln Y w + ϕ 5 ln Φ + ϕ 6 ln z i + ϕ 7 ln s i + u i, where he relaionships beween he coeffi ciens in his expor equaion and he deep parameers are ϕ 0 = ν ln 1 1 ) ν κ + θ α + β + γ + a 0, 10

11 ν α + β) 13) ϕ 1 = α + β + γ, νβ 14) ϕ 2 = α + β + γ, 15) ϕ 3 = ν, 16) ϕ 4 = ν θ, ϕ 5 = ϕ 6 = ν τ α + β + γ, ν δ α + β + γ, ϕ 7 = a 1, and he normalized variables are defined such ha ê = e w, r w f = r f, P w = P f, and u w f i = 3.2 The aggregae expor equaion ν α + β + γ ũi + v i. Consider a similar log-linear relaion beween expors and exchange raes defined on aggregae variables, such ha 17) ln y f = φ 0 + φ 1 ln e + φ 2 Ψ + Ω, where y f is aggregae average expors, e he nominal exchange rae, Ψ he vecor of conrol variables, and Ω he aggregae error erm. Would he exchange rae elasiciy of expors φ 1 esimaed from his aggregae expor equaion 17) be consisen wih he esimae for ϕ 1 in he firm level expor equaion 12)? Noe ha he level of expors is wrien as: 18) y f i = êϕ 1 r ϕ 2 ) ϕ3 P f Y w ) ϕ 4 Φ ϕ 5 z ϕ 6 i sϕ 7 i exp ϕ 0 + u i ). Taking he cross-secional average E i on boh sides of equaion 18), 19) y f E i {y f i } = exp ϕ 0 ) ê ϕ 1 r ϕ 2 ) ϕ3 P f Y w ) ϕ 4 Φ ϕ 5 E i {z ϕ 6 i sϕ 7 i } E i {exp u i )}, 11

12 because of he orhogonaliy of he error erm u i from z i and s i. Taking he naural logarihms on boh sides of equaion 19), 20) ln y f = ϕ 0 + ϕ 1 ln ê + ϕ 2 ln r + ϕ 3 ln P f + ϕ 4 ln Y w + ϕ 5 ln Φ + ln E i {z ϕ 6 i sϕ 7 i } + ln E i {exp u i )} = ϕ 0 + ϕ 1 ln ê + ϕ 2 ln r + ϕ 3 ln P f + ϕ 4 ln Y w + ϕ 5 ln Φ + ϕ 6 ln z + ϕ 7 ln s { ) ϕ6 ) ϕ7 } zi si + ln E i + ln E i {exp u i )} z s = ϕ 0 + ϕ 1 ln ê + ΘΛ + B + U, where 21) 22) 23) ΘΛ = ϕ 1 ln w w f ) B = ln E i { zi z U = ln E i {exp u i )}. + ϕ 2 ln r + ϕ 3 ln P f ) ϕ6 ) ϕ7 } si s + ϕ 4 ln Y w + ϕ 5 ln Φ + ϕ 6 ln z + ϕ 7 ln s This gives us aggregaed expors consisen wih firm level expors in 12). The ΘΛ erm includes he variables ha reflec he informaion se underlying he firm s decisions, such as relaive facor prices, he general price level, he real income of consumers, he firm s own produciviy and he expor share. The B erm arises because of aggregaion, which reflecs he disribuion of he heerogeneous characerisics of firms, e.g., firm level produciviy and expor shares. Wih only aggregaed or macroeconomic daa, we canno conrol for B, whose calculaion requires firm level daa. The U erm is an aggregae ime-series error erm ha is consisen wih he firm level relaion. Since he error erm u i is orhogonal o all he regressors in he firm level equaion 12) over all i s and s, U is orhogonal o he aggregae variables in he aggregae equaion 20) over ime. 3.3 Sources of bias in ypical aggregae expor equaions Omiing variables in he firm s informaion se A comparison of he ypically esimaed macroeconomic relaion beween expors and exchange raes in 17), wih he consisenly aggregaed relaion in equaion 20) suggess ha here are 12

13 wo caegories of omied variable bias in he aggregae expor equaion in 17). Firs, if he se of conrol variables Ψ in he macroeconomic relaion 17) omis one or more of he conrol variables in Λ basically he variables in he exporing firms informaion se) in he consisen aggregae relaion in 20) and if here exiss some degree of covariance over ime beween he omied variables and he exchange rae, he aggregae exchange rae elasiciy of expors φ 1 in 17) will be biased. For example, suppose he relaive facor price r = r w he raio of he renal raes of capial o wage raes) is omied, as in a ypical macroeconomic expor equaion. Le φ 1 be he OLS esimae for he exchange rae elasiciy of expors from he ypical macroeconomic expor equaion. Then, we have ] E [ φ1 = ϕ 1 + Covln e, ln r ) ϕ V ar ln e ) 2 V ar ln r ) = ϕ 1 + Corrln e, ln r ) V ar ln e ) ϕ 2. Thus, he larger he ime-series correlaion beween he omied variable and he exchange rae, he larger he omied variable bias. The larger he variance of he omied variable over ime, he larger is he bias. However, he larger he variance of he exchange rae iself, he smaller is he omied variable bias. Tha is, he omied variable bias for he exchange rae elasiciy of expors ends o be smaller for an economy where he exchange rae is more volaile. This may explain why we find srong correlaions beween exchange rae depreciaions and expor expansions in developing counries as documened by Tornell and Wesermann 2002), where exchange raes are more volaile and facor prices are more regulaed, and hence he smaller heabove kind of omied variable bias for he exchange rae elasiciy of expors. The direcion as well as he size of he bias depend on he covariance as well as he coeffi cien on he omied variable iself. In his example, according o our model ϕ 2 = νβ α+β+γ < 0) and also according o our esimae, he coeffi cien ϕ 2 on he renal-o-wage raio is negaive. The daa suggess Covln e, ln r ) is also negaive. Therefore, he bias from omiing he renalo-wage raio is posiive. Tha is, omiing he renal-o-wage raio will bias he aggregae elasiciy of expors wih respec o exchange raes, φ 1, owards zero, and hence can be a source of he observed exchange rae disconnec. 13

14 3.3.2 Aggregaion bias { ) ϕ6 ) ϕ7 } z The omission of he erm B = ln E i s i i z s in he macroeconomic expor equaion creaes a furher source of omied variable bias. This bias resuls from he aggregaion of heerogeneous firms, which depends on he disribuion of he relaive produciviy z i z, and he expor shares s i s normalized o he means). Le ζ be he vecor of parameers of he join disribuion of he produciviy and expor share erms a dae. If he movemen of B is no independen from he movemen of he mean values of z and s via some parameers in ζ, he coeffi ciens on ln z and ln s in he ypical macroeconomic expor equaions will be biased downwards. This is he usual aggregaion bias in he aggregaion lieraure as discussed in Blundell and Soker 2005). Lewbel 1992) shows ha he necessary and suffi cien condiion o avoid his aggregaion bias in log-linear models is ha he disribuion is mean-scaled, i.e., he disribuion of hose mean-scaled variables is independen from he mean values of z and s. When he mean-scaled propery in Lewbel 1992) is saisfied for he join disribuions of produciviy, and he expor shares, he coeffi ciens on labor produciviy and he expor shares hemselves can be consisenly esimaed from he aggregae expor equaion 17). However, even when he mean-scaled propery is saisfied, omiing he disribuion erm B can generae anoher ype of aggregaion bias for he exchange rae elasiciy of expors in 17), if B covaries wih he exchange rae over ime. Suppose, for example, ha he join disribuion of z i z and s i s is lognormal. Then, he ζ are ime-varying variances of z i z and s i s he movemens in any of hese variances or covariances are correlaed wih exchange raes over ime, he exchange rae elasiciy of expors esimaed from 17) will be biased. This ype of aggregaion bias canno be avoided by ypical aggregae expor equaions. By comparing he firm-level esimae of he exchange rae elasiciy of expors which is free from his aggregaion bias) wih he esimaes from he aggregae expor equaion, which includes he same relevan prices and produciviy variables bu missing he B erm, we can quanify he magniude of his aggregaion bias for he exchange rae elasiciy of expors. If 14

15 4 Esimaion 4.1 Daa We use annual firm level daa during he years beween 1982 and 1997, obained from he Japan Developmen Bank Corporae daabase. Our sample firms are in he manufacuring secor. This is a daabase of large firms lised on he various sock exchanges of Japan. An imporan characerisic is ha here is virually no exi or enry ino our sample of exporers from 1982 o In our sample, here are 352 exporing firms in each year, covering over 90 percen of oal Japanese manufacuring expor sales value. These firms belong o 52 four-digi level indusry groups, which we accoun for when we include indusry level variables in he esimaion. Expors and oal sales are from he Japan Developmen Bank daabase. Expor quaniies are defined as expor values divided by he indusry specific Japanese expor price indices he base year of 1995, foreign currency bases) from he Bank of Japan Economic and Financial daabase. The aggregae Japanese expor price index from he Inernaional Financial Saisics from he IMF is used as a proxy for he foreign price. Firm level expor shares are defined as expors divided by he sum of domesic sales and expors. Noe ha we use differen price indices for domesic sales and expor sales, o ge real values, in order o calculae he real quaniy share of expors. Aggregae expor shares are defined as he average of he firm level expor shares. The exchange rae is measured by he reciprocal of he composie of he rade-weighed nominal raes of he Japanese Yen, o he foreign currencies of he op 15 rading parner counries of Japan. The annual nominal exchange raes are from he Inernaional Financial Saisics from IMF, and he rade weighs are compued from he Japan Saisical Yearbook. For world real income, we ake Japan s op 15 rading parners real GDP s obained from he PWT version 6.1), and sum hem, by weighing by he rade weighs wih Japan. As a proxy for he prices of impored raw maerials used by Japanese exporing firms, we ake he average spo crude oil marke price index from he Inernaional Financial Saisics. 15

16 For indusry specific domesic inpu prices, we ake indusry specific domesic wages from he Japan Saisical Yearbook. Indusry specific labor produciviy is defined indusry oupu per worker a he four digi level. For he ineres rae, we ake he one year LIBOR London Iner-Bank Offered Rae). 4.2 Firm level esimaion Using he above exporing firm daa as well as he aggregae daa, we esimae he firm level expor equaion in 12) ln y f i = ϕ 0 + ϕ 1 ln ê + ϕ 2 ln r + ϕ 3 ln P f + ϕ 4 ln Y w + ϕ 5 ln Φ + ϕ 6 ln z i + ϕ 7 ln s i + u i. Table 2 repors he esimaes of he coeffi ciens in his expor equaion. Noe ha he sample sizes decline from he oal of 5616=352*16), as no all of he explanaory variables are available for all firms. Depending on he assumpions regarding he unobserved heerogeneiy in he error erm u i, we esimae he equaion using ordinary leas squares OLS), fixed effec FE), and random effec RE) esimaors. For all hree cases, he signs of he esimaed coeffi ciens agree wih he predicions of our model. Tha is, he coeffi ciens on he exchange rae ê, and he ineres rae r are negaive, while he coeffi ciens on he foreign price level P f, world real income Y w, aggregae TFP Φ, indusry-specific labor produciviy z i, and he firm-specific insrumened) expor share s i all in log erms) are all posiive. In paricular, in conras o he insignifican aggregae elasiciies of expors wih respec o exchange raes in Table 1, he firm level esimaes for ϕ 1 he exchange rae elasiciy of expors) are significanly negaive for all hree cases: 0.41 for OLS, 0.77 for FE, and 0.75 for RE. 10 The esimaes are very close beween he fixed effec esimaor and he random effec esimaor, no only for he exchange rae elasiciy, bu also for all oher coeffi ciens. According o he Hausman specificaion es, he fixed effec model agains he random effec model is no rejeced. The Hausman es saisic is 6.27 wih he p-value of 0.51.) Thus, we ake he fixed-effec specificaion as our benchmark and our benchmark elasiciy of expor wih respec o exchange rae is To check he robusness of our resuls, we documen he OLS resuls 16

17 as well. By varying he subse of omied variables from he full se of conrol variables, we can evaluae which variables are more responsible for he omied variable bias han ohers. Table 3 shows he OLS esimaion resuls for various specificaions, by omiing differen subses of variables in he model. The firs column repors he resul wih all he variables in he model included; he exchange rae elasiciy is significanly negaive a Omiing all variables oher han he exchange rae column 2), he exchange rae elasiciy becomes significanly posiive a 0.42, suggesing ha even a he firm level, he omission of relevan conrol variables can resul in he opposie sign, in he relaionship beween exchange raes and expors. In column 3, he specificaion includes only four variables i.e., ineres rae, foreign price level, indusry produciviy and he firm expor share, oher han he exchange rae), which urn ou o be significan for boh he OLS and he FE esimaes. We hen omi world real income and domesic TFP. In his specificaion, we find ha he exchange rae elasiciy urns smaller and insignifican. Thus, omiing boh world real income and domesic TFP seems o resul in serious bias in esimaing he exchange rae elasiciy. Columns 4 o 9 experimen, omiing a variable in he model one by one, from he ineres rae o he firm expor share. Here omiing any single variable in he model, excep for omiing only world income, or only TFP biases he exchange rae elasiciy owards zero and insignifican. Omiing only he domesic TFP raises he exchange rae elasiciy. Omiing only he world income virually has no effec. The sensiiviy analysis repored in columns 10 o 17 in Table 3 is done by omiing a group of relaed variables, raher han omiing each single variable. Column 10 includes only he quaniy variables Y w, Φ, z i and s i ). Column 11 includes only he price variables r and P f ). Column 12 includes only he firm s supply-side variables r, Φ, z i and s i ). Column 13 includes only he demand-side variables Y w and P f ). Column 14 drops only he produciviy relaed variables, while column 15 includes only he produciviy relaed variables Φ, z i and s i ). Column 16 includes only he aggregae variables r, P f, Y w and Φ ). Column 17 includes only he indusry or firm specific variables z i and s i ). In none of he specificaions is he 17

18 exchange rae elasiciy significanly negaive. Table 4 repeas he same exercise for he fixed effec esimaor, our benchmark case. As a reminder, he FE esimae of he exchange rae elasiciy was higher a -0.77, han he OLS esimae a However, despie he differences in he magniudes of he esimaes and heir significance levels, we ge similar resuls for he FE as hose for he OLS. Omiing any subgroups of he variables in our model involves sizeable biases. Only when eiher world income or TFP is omied is he bias negligible. The only difference beween he FE esimaor and he OLS esimaor is ha he bias from omiing he wo insignifican variables world income and domesic TFP) in he full model is relaively small wih he esimae a -0.68) for he FE esimaor, compared o he OLS esimaor. There are wo oher noiceable observaions from he sensiiviy analysis for he FE esimaor. The bias in he exchange rae elasiciy is he highes when indusry level produciviy column 8) and he firm s expor share variables are omied column 9). Thus, omiing he wo firm level produciviy variables seem o generae he mos serious omied variable biases. This, of course, does no mean ha conrolling for aggregae variables is unimporan. Column 17 confirms ha excluding he aggregae variables also generaes biases in our firm level regressions. However, even afer correcly conrolling for he aggregae variables, omiing eiher or boh of he firm level produciviy variables can generae subsanial omied variable biases, as shown in columns 8, 9 and Aggregae esimaion Suppose i is possible o esimae he consisenly aggregaed expor equaion 20) ln y f = ϕ 0 + ϕ 1 ln ê + ϕ 2 ln r + ϕ 3 ln P f + ϕ 4 ln Y w + ϕ 5 ln Φ + ϕ 6 ln z + ϕ 7 ln s + B + U. Since i is consisenly aggregaed from he firm level equaion 12), we should be able o obain he same esimaes for all he coeffi ciens from ϕ 0 o ϕ 7, as we did from he firm level esimaion { ) ϕ6 ) ϕ7 } z of 12). However, he aggregaion effec erm B = ln E i s i i z s is no feasible o include in ypical macroeconomic expor equaions for wo reasons. Firs, we can hardly know 18

19 ) z he ime-varying join disribuions of i z, s i s a priori. Second and relaed, B iself involves he parameers ϕ 6 and ϕ 7 ha need o be esimaed. Thus, unless we are willing o assume z parameric forms of he ime-varying join disribuions of i z, s i s ), we canno even calculae B o correc for he aggregaion bias. We can, however, quanify he size of his aggregaion bias by comparing he esimaes of he following aggregae expor equaion which omis B ) 24) ln y f = ψ 0 + ψ 1 ln ê + ψ 2 ln r + ψ 3 ln P f + ψ 4 ln Y w + ψ 5 ln Φ + ψ 6 ln z + ψ 7 ln s + U wih he firm level esimaes ha are no subjec o he aggregaion bias. This is done in Table 5. We consruc he aggregae daa from our firm level daa so ha hey are consisenly aggregaed from he firm level daa. We firs esimae he aggregae expor equaion 24), and compare he esimaes wih he OLS firm level esimaes. We also esimae i using differenced daa, and compare wih he fixed-effecs esimaor. The aggregae OLS esimaes are more or less similar o he OLS firm level esimaes for all he coeffi ciens. Tha is, if he idiosyncraic error erm u i is indeed i.i.d., he aggregaion bias seems o be small for all coeffi ciens, including he exchange rae elasiciy. However, if he u i includes unobservable fixed effecs, he aggregaion bias seems o be { ) ϕ6 ) ϕ7 } z subsanial. Firs of all, omiing he erm B = ln E i s i i z s underesimaes he elasiciy of he indusry produciviy z a 0.47, compared o 0.68 in he firm level esimae); and overesimaes he elasiciy of he firm expor share s a 0.93 compared o 0.60 in he firm level esimae). I underesimaes he ineres rae elasiciy a compared o in he firm level esimae) while overesimaes he TFP elasiciy a 0.33 compared o 0.19 in he firm level esimae). The foreign price elasiciy remains virually he same a 0.73 compared o 0.74 in he firm level esimae). The world income elasiciy incorrecly) urns negaive a , alhough i is insignifican. Finally, he aggregae esimaion underesimaes he exchange rae elasiciy our key parameer) a compared o in he firm level esimae). 19

20 4.4 Idenificaion of he deep parameers Recall ha he exchange rae elasiciy in equaion 8) is: θ α + β) ɛ = 1 + ρθ 1), which shows ha he responsiveness of expors o exchange raes depends on he deep parameers of preferences and echnology. We can uncover he deep parameers θ, α, β, γ, ρ) from he elasiciy parameers ϕ 1 o ϕ 4 in he expor equaion, using he parameer mappings in equaions 13) o 16). From he deep parameers, we can uncover he preferences and he echnology of Japanese exporing firms and deermine he effecs of he preference and echnological parameers on he exchange rae elasiciy of expors. The elasiciy of subsiuion parameer θ of he uiliy funcion is idenified by θ = ϕ 3 ϕ 4. Given his θ, α + β + γ is idenified from equaion 15) such ha: 25) ϕ 3 = ν [ ρ = α + β + γ + 1 ] 1 θ [ 1 α + β + γ) = + 1 ] 1. α + β + γ θ Then, from equaion 13), we idenify α + β such ha 26) ν α + β) ϕ 1 = α + β + γ = ϕ 3 α + β) α + β + γ, given he α + β + γ from equaion 25). γ is idenified from he difference beween he α + β + γ from equaion 25), and he α + β from equaion 26). Then, using he equaions 13) and 14), β is idenified by 27) β = ϕ 2 ϕ 1 α + β), given he α + β from equaion 26). Finally, α is idenified from he difference beween he α + β in equaion 26), and he β in equaion 27). 20

21 In sum, he preferences and echnology parameers are idenified such ha 28) 29) 30) 31) θ = h θ ϕ s ) = ϕ 3 ϕ 4, α = h α ϕ s ) = ϕ 2 ϕ ϕ 3 ϕ 4, β = h β ϕ s ) = ϕ ϕ 3 ϕ 4, γ = h γ ϕ s ) = ϕ 1 + ϕ ϕ 3 ϕ 4, where ϕ s ϕ 1, ϕ 2, ϕ 3, ϕ 4 ). The implied reurns o scale parameer ρ is 32) ρ = h ρ ϕ s ) = 1 ϕ ϕ 3 ϕ 4. Table 6 repors he uncovered preferences and echnology parameers for each se of esimaes from he firm level OLS esimaion, he firm level fixed effec esimaion, he aggregae levels esimaion, and he aggregae firs-differenced esimaion. Sandard errors of hese deep parameers are compued using dela mehods. 11 There are some noiceable feaures of he deep parameers ha are robus o he specificaions of he error erms. Firs, Japanese exporing firms are facing srong decreasing reurns o scale. The esimaed ρ varies beween 0.52 and 0.65, which are significanly differen from zero i.e., consan reurns o scale echnology). Furhermore, he sandard errors of he ρ parameer are small for all specificaions, and hence ρ seems o be fairly precisely esimaed. Noe ha he higher he ρ, he smaller he exchange rae elasiciy. Tha is, he exchange rae elasiciy is likely o be overesimaed when he ypical consan reurns o scale Cobb-Douglas producion funcion for firm level echnology is used in deriving he expor equaion. Second, he elasiciy of subsiuion parameer in demand θ is much larger han uniy, varying from 4 o 10, excep for he case of firs-differenced aggregae esimaion. 12 When ρ < 1, as he elasiciy of subsiuion parameer θ becomes larger, he larger he decrease in expors o he appreciaion of exchange rae. Obviously, in he exreme case of Leonief preferences of θ = 0, expors do no respond a all o he movemen of exchange rae. Our large esimaes for θ implies ha he observed significan elasiciy of expors wih respec o exchange rae is indeed relaed o he high subsiuabiliy among he differeniaed consumpion goods

22 Third, he relaive size of he labor share α and he capial share β varies depending on he specificaions. Noe, however, ha he relaive share beween domesic labor and capial does no affec he exchange rae elasiciy. Only he sum α + β maers relaive o he impored inpu share γ. Here in our esimaes, no only he sum, bu also each of he domesic inpu share parameers α and β, are larger han he impored raw maerial share parameer γ. In fac, he esimaes for γ iself are very small. 14 Thus, he observed magniude of he exchange rae elasiciy does no seem o be relaed o he share of impored inpus. 5 Conclusion This paper provides an example of how heory combined wih an appropriae use of microeconomic daa can be helpful in solving macroeconomic empirical puzzles. We have resolved he conflicing evidence beween he firm and aggregae level daa, regarding he so-called exchange rae disconnec puzzle. The idea ha price elasiciies are biased downwards in he convenionally esimaed aggregae rade equaions, given he underlying aggregaion problem, was posulaed more han 50 years ago by Orcu 1950). However, here does no seem o exiss an aemp o quanify and seek he sources of he bias. We ried o perform his quaniaive evaluaion. We build a monopolisic compeiion model of exporing firms, o derive an expor equaion a he firm level, which can be consisenly aggregaed up o he macroeconomic level. We use our framework o reconcile he conflicing evidence in he exising lieraure regarding he exchange rae elasiciies a he firm and macroeconomic levels. We show ha he esimaes for all elasiciy parameers are similar beween he firm and consisenly) aggregaed levels once all he variables relevan o he firm s expor supply decision are aken ino accoun. In paricular, we found a significanly negaive elasiciy of expors wih respec o exchange raes in boh firm and aggregae level expor equaions. I urns ou ha he omission of only some par of he key variables in he informaion se of exporing firms can lead o he puzzling observaion of he lack of associaion beween he movemens in expor quaniies and exchange raes, i.e., he exchange rae disconnec puzzle. 22

23 Specifically, we found ha omiing he average values of he firm level produciviy may yield a subsanial bias for he esimaes of he elasiciy of expors. We also found ha a pure aggregaion bias, i.e., omiing he disribuional characerisics of firm level heerogeneiies which is ineviable in he macroeconomic expor equaions wihou using firm level daa) exiss, bu i is smaller han he firs kind of bias due o he omission of he average values of he variables hemselves. We also idenified he deep parameers of preferences and echnology, and found subsanial decreasing reurns o scale echnology among he Japanese exporing firms and a fairly high elasiciy of subsiuion among he differeniaed goods in consumer preferences. Boh parameers urn ou o be imporan in deermining he magniude of he exchange rae elasiciy of expors. References [1] Berman, N., P. Marin, and T. Mayer, "How Do Differen Exporers Reac o Exchange Rae Changes? Theory, Empirics, and Aggregae Implicaions," manuscrip 2009), Universiy of Paris. [2] Blackorby, C., D. Primon, R. Russell, Dualiy, Separabiliy, and Funcional Srucure: heory and Economic Applicaion, 1978), Amserdam, Norh-Holland. [3] Blundell, R. and T. Soker, Heerogeneiy and Aggregaion, Journal of Economic Lieraure ), [4] Dekle, R., Exchange Rae Exposure and Foreign Marke Compeiion: Evidence from Japanese Firms, Journal of Business ), [5] Dekle, R. and H. Ryoo, Exchange Rae Flucuaions, Financing Consrains, Hedging, and Expors: Evidence from Firm Level Daa, Journal of Inernaional Financial Markes Insiuions and Money, 2007). [6] Duare, M., "Why Don Macroeconomic Quaniiies Respond o Exchange Rae Variabiliy?" Journal of Moneary Economics, pp , May. [7] Fizgerald, D. and S. Haller, "Exchange Raes and Producer Prices: Evidence from Microeconomic Daa," manuscrip 2009), Sanford. [8] Grossman, G., E. Helpman, Innovaion and Growh in he Global Economy, Cambridge: MIT Press 1991). [9] Imbs, J. and H. Mejean, "Elasiciy Opimism," manuscrip, 2009), HEC Lausanne. 23

24 [10] Inernaional Moneary Fund, Inernaional Financial Saisics, various years. [11] Japan Saisical Research and Training Insiue in Minisry of Inernal Affairs and Communicaions, Japan Saisical Yearbook, various years. [12] Lewbel, A., Aggregaion wih Log-Linear Models, Review of Economic Sudies ), [13] Meliz, M., The Impac of Trade on Inra-Indusry Reallocaions and Aggregae Indusry Produciviy, Economerica ), [14] Obsfeld, M. and K. Rogoff, Foundaions of Inernaional Macroeconomics, The MIT Press 1996), Cambridge. [15] Orcu, G. H., Measuremen of Price Elasiciies in Inernaional Trade, Review of Economics and Saisics ), [16] Tornell, A. and F. Wesermann, Boom-Bus Cycles in Middle Income Counries: The Facs, IMF Saff Papers 2002). [17] Tybou, J. and M. Robers, "The Decision o Expor in Columbia: An Empirical Model of Enry wih Sunk Coss," American Economic Review ). [18] Verhoogen, E., "Trade, Qualiy Upgrading, and Wage Inequaliy in he Mexican Manufacuring Secor," Quarerly Journal of Economics ). 24

25 Noes 1 We hank he paricipans in he 2005 Norh American Economeric Sociey Winer Meeings; he 2005 NBER Japan Projec Meeings; and he Fall 2006 Japan Economic Seminar; especially he discussans, Menzie Chinn, Maurice Obsfeld, and Jim Harrigan for helpful commens. We hank he Developmen Bank of Japan for access o he JDB daa. Corresponding hyeok.jeong@vanderbil.edu 2 For a sensiiviy check, we run simple auoregressive disribued lag models of log expors on log exchange raes. In he levels specificaion, he coeffi ciens on he exchange rae he conemporaneous and lagged combined) are eiher insignifican or, posiive if significan e.g., he Unied Saes). In he firs-differenced specificaion, he coeffi ciens on he exchange rae are insignifican, excep for Ialy. 3 Noe ha his exchange rae disconnec puzzle is differen from he well-known J-curve effec in he inernaional finance and rade lieraure. The exchange rae disconnec puzzle is abou he lack of associaion beween he movemens of exchange raes and gross expor quaniies while he J-curve effec is abou he sluggish and J-shaped adjusmen of rade balance i.e., ne expor sales) o he improvemen in erms of rade. 4 In her model, a posiive moneary shock depreciaes he nominal exchange rae on impac, bu because of LCP, he relaive prices of home and foreign goods are unchanged. The expendiure swiching effec is eliminaed; only a small wealh effec from he increase in money supplies) remains. However, since local consumers have a bias owards local goods, he wealh effec on revenues is quaniaively small. Therefore, exchange rae changes have lile apparen effec on consumer demands, and he volailiy of home consumpion and he volailiies of oher real variables) is separaed from he volailiy of he nominal exchange rae. 5 Our sample includes only firms lised on he sock exchanges of Japan, which includes mainly large firms. In Japan, i is well known ha large firms comprise he bulk of expors. Our sample of lised firms comprise over 90 percen of oal Japanese expors. In fac, remarkably, he 10 larges Japanese firms comprise over 40 percen of all expors. 6 Ineresingly, i urns ou ha he omission of only some par of he key variables in he informaion se of exporing firms can lead o he puzzling observaion of he lack of associaion beween he movemens in expor quaniies and exchange raes. Specifically, we found ha omiing he average values of firm level produciviy may yield subsanial bias for he esimaes of he elasiciy of expors. We also found ha a pure aggregaion bias he omission of he disribuional characerisics of firm level heerogeneiies exiss, bu is somewha smaller han he firs kind of bias ha is due of he omission of he average values of he variables. 7 While our model is also consisen wih he enry and exi of firms from he expor marke, o show our main resul ha esimaes using aggregae daa may suffer from aggregaion bias, we do no have o explicily model and esimae he enry and exi decisions of firms. Thus, in our analysis, we focus on changes in inrafirm expors, ha is, we neglec he change in aggregae expors caused by he enry and exi of firms from he expor marke. In any even, he enry and exi of firms ino he expor marke accouns for only a very small percenage of he change in oal expors from Japan Fukao and Kwon, 2006). 8 Noe ha he original budge consrain is n 0 p iy i di+ 1 n p f ) i e y i di Z, which is simplified o 1 0 p iy i di Z due o he law of one price. Furhermore, he law of one price also implies ha P f p i P = e P equivalenly = pf i. This makes he demand funcion of domesic goods and ha of foreign goods symmeric, given he P f 25

26 prices of p i and p f i. 9 See Blackorby, Primon, and Russell 1978) for a general discussion on he dual mapping beween he cos funcion, and echnology and he properies of he cos funcion. 10 The differences beween he FE and OLS esimaes for oher coeffi ciens are as follows. The magniude of he exchange rae elasiciy is larger for he FE esimae han for he OLS esimae. The same is rue for he ineres rae elasiciy, and he OLS esimae of he ineres rae elasiciy is insignifican, while is FE esimae is significan. The world income elasiciy is small and insignifican for boh he OLS and FE esimaes. For he TFP elasiciy, he OLS esimae is much larger han he FE esimae, bu boh are insignifican. The esimaes of he indusry produciviy elasiciy are significan boh for he OLS and FE, bu he OLS esimae is smaller han he FE esimae. The esimaes of he firm expor share elasiciies are significan boh for he OLS and FE, bu he OLS esimae is larger han he FE esimae. 11 Le s denoe he variance-covariance marix V ϕ s ) for he esimaor ϕ s = ϕ 1, ϕ 2, ϕ 3, ϕ 4 ) such ha σ 2 1 σ 12 σ 13 σ 14 V ϕ s ) = σ 12 σ 2 2 σ 23 σ 24 σ 13 σ 23 σ 2 3 σ 34. σ 14 σ 24 σ 34 σ 2 4 The gradiens of he parameer mappings h θ o h ρ in equaions 28) o 32) are given by [ h θ ϕ s ) 1 = 0, 0,, ϕ ] 3 ϕ 4 ϕ 2, 4 [ ] h α ϕ s ) 1 1 ϕ =,, 1 ϕ ϕ 3 ϕ ϕ 3 ϕ ϕ 3 ϕ 4 ) 2, ϕ 2 ϕ ϕ 3 ϕ 4 ) 2, [ ] h β ϕ s ) 1 ϕ = 0,, ϕ 3 ϕ ϕ 3 ϕ 4 ) 2, ϕ ϕ 3 ϕ 4 ) 2, h γ ϕ s ) = h ρ ϕ s ) = [ 1, 0, 1 + ϕ 3 ϕ 4 [ 0, 0, 1 ϕ 1 ϕ ϕ 3 ϕ 4 ) 2, ϕ 1 + ϕ ϕ 3 ϕ 4 ) 2 ] ϕ ϕ 3 ϕ 4 ) 2, ϕ ϕ 3 ϕ 4 ) 2 Then, he sandard error for each deep parameer x for x = θ, α, β, γ and ρ) is compued such ha σ x = [ h x ϕ s ) V ϕ s ) h x ϕ s ) ] 1 2, where h x ϕ s ) is he gradien of he funcion h x evaluaed a he esimae of ϕ s. The variance and covariance marix for each of he four esimaors of firm level OLS esimaion, firm level FE esimaion, aggregae level esimaion, and aggregae differenced esimaion is available upon reques. 12 This is because he elasiciy of he world income is esimaed incorrecly) o be negaive alhough insignifican. 26. ],

27 13 However, his parameer seems o be less precisely esimaed compared wih he reurns o scale parameer, paricularly for he high OLS esimae a The lower FE esimae for θ a 3.89 seems o be relaively precise. In fac, he FE esimaes are more precise han hose of oher specificaions for all deep parameers excep for γ. 14 The FE esimae for γ is slighly negaive bu wih a high sandard error. 27

28 Table 1 Disconnec puzzle wih Macroeconomic Daa Using log level daa 1) Canada France Germany Ialy UK US Japan Pooled 3) Exchange Rae 2) 0.23) 1.01) 0.77) 0.90)* 0.13) 0.29) 0.38) 0.20) Consan 0.002)** 0.01) 0.01) 0.02) 0.002)* 0.01) 0.01) 0.00)** R-squared Using log level daa 1) Canada France Germany Ialy UK US Japan Pooled 3) Exchange Rae 2) 0.22) 0.86) 0.61) 0.68) 0.12) 0.26)* 0.29) 0.16) Lagged Exchange Rae Lagged Expor Consan ) 0.04)*** 0.32)*** 0.86) 0.06)*** -0.94) 0.64) 0.07)*** 0.71)*** 0.68) 0.08)** 0.98)*** 0.13) 0.05)*** 0.27)*** 0.26)** 0.05)*** 0.31)*** 0.29) 0.07) 0.32)*** 0.16)** 0.03)*** 0.18)*** R-squared Using log differenced daa Canada France Germany Ialy UK US Japan Pooled 3) Exchange Rae 2) 0.20) 1.04) 0.75) 0.79)*** 0.12) 0.29) 0.37) 0.19) Lagged Exchange Rae Lagged Expor Consan )** 0.08)*** 0.002)*** 1.18) 0.08)*** 0.01) 0.68)* 0.06)*** 0.01) 0.75) 0.06)*** 0.01) 0.12) 0.06)*** 0.002)*** 0.25) 0.05)*** 0.00) 0.39) 0.07)*** 0.01) 0.18) 0.04)*** 0.002)*** R-squared Noe: Monhly IFS daa for he period from 1982 o 1997 are used. Heeroskedasiciy robus sandard errors are in parenhesis. * significan a 10%; ** a 5%; *** a 1%. 1. Linear rends are included. 2. Nominal effecive exchange raes. 3. Using G-7 counries wih he counry dummy.