Tho becke, Willem
A icle
In es iga ing how exchange a es impac Japan's
machine y expo s since 1990
Economies
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Sugges ed Ci a ion: Tho becke, Willem (2024) : In es iga ing how exchange a es impac Japan's
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Ci a ion: Tho becke, Willem. 2024.
In es iga ing How Exchange Ra es
Impac Japan’s Machine y Expo s
since 1990. Economies 12: 133.
h ps://doi.o g/10.3390/
economies12060133
Academic Edi o s: Robe Czudaj and
Ral Fendel
Recei ed: 1 Feb ua y 2024
Re ised: 9 May 2024
Accep ed: 24 May 2024
Published: 28 May 2024
Copy igh : © 2024 by he au ho .
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economies
A icle
In es iga ing How Exchange Ra es Impac Japan’s Machine y
Expo s since 1990
Willem Tho becke
Resea ch Ins i u e o Economy, T ade and Indus y, Tokyo 100-8901, Japan; [email p o ec ed]
Abs ac : Japan expo s sophis ica ed capi al goods. Since he Global Financial C isis (GFC), Japanese
companies ha e o sho ed he p oduc ion o lowe -end goods and pa s and componen s o Asian
coun ies. Because o his, se e al esea che s a gued ha a weake yen no longe s imula es machine y
expo s much because an inc ease in Japanese expo s inc eases pa s and componen s impo s om
o e seas Asian subsidia ies. This pape inds ha , a e he GFC, a weake yen no longe inc eases
Japanese machine y expo s o Asia bu con inues o s imula e expo s ou side o Asia. Thus, he
weake yen since 2020 does no help Asian i ms o impo i al Japanese capi al goods bu does
inc ease he p o i abili y o Japanese manu ac u e s and hei expo s o non-Asian coun ies.
Keywo ds: Japan; capi al goods; expo olumes
JEL Classi ica ion: F14; G10
1. In oduc ion
Japan has a compa a i e ad an age in p oducing machine y and capi al goods. I
manu ac u es exca a o s, machine ools, u bines, obo s, machine y o manu ac u e semi-
conduc o s and ex iles, and o he capi al goods. Japan has adi ionally played an impo -
an ole in expo ing hese goods o downs eam Asian coun ies. Kwan (2004) no ed ha ,
i Asian i ms a e unable o ob ain capi al goods om Japan, hey a e equen ly unable o
ob ain hem a all.
Japan’s machine y expo s a e sophis ica ed. Hidalgo and Hausmann (2009) de el-
oped a me hod o measu e he sophis ica ion o p oduc s. They obse ed ha complex
goods equi e ad anced capabili ies. These p oduc s a e mo e likely o be made by coun-
ies wi h di e se expo baske s. They de ined an economy’s complexi y based on i s
abili y o expo a ied and ad anced p oduc s. They de ined a p oduc ’s sophis ica ion
based on i s non-ubiqui y. I e a ing be ween measu es o an economy’s complexi y and
a p oduc ’s ubiqui y, hey calcula ed p oduc complexi y indices (PCIs) o mo e han
1200 p oduc s. Highe PCI alues indica e mo e ad anced p oduc s.
These PCIs can be used o gauge he complexi y o Japan’s machine y expo s in
compa ison o he o he h ee leading machine y expo e s, he U.S., China, and Ge many.
Taking a weigh ed a e age o Japan’s op en machine y expo s in 2021, he a e age
machine y PCI in 2021 equaled 1.53. The alues o he U.S., China, and Ge many we e,
espec i ely, 1.27, 1.02, and 1.10. Thus, Japan’s machine y expo s a e ad anced ela i e o
compa able coun ies. Japan’s o al expo baske has also been a ed as he mos complex
in he wo ld e e y yea be ween 2000 and 2021.
A e hese sophis ica ed expo s sensi i e o exchange a es? This ques ion is ele an
as he Japanese eal e ec i e exchange a e in 2024 is close o i s lowes le el in 50 yea s.
Abiad e al. (2018) a gued ha mo e complex goods a e ha de o p oduce and, hus, ha e
ewe subs i u es. Because o his, hey no ed ha he p ice elas ici y o demand should
be lowe o mo e complex p oduc s and, hus, ha expo s o hese goods should be less
sensi i e o exchange a es.
Economies 2024,12, 133. h ps://doi.o g/10.3390/economies12060133 h ps://www.mdpi.com/jou nal/economies
Economies 2024,12, 133 2 o 11
Baek (2013) employed an au o eg essi e dis ibu ed lag (ARDL) model and qua e ly
da a o e he 1991–2010 pe iod o in es iga e Japan’s machine y and anspo equipmen
and o he expo s o Sou h Ko ea. The ARDL coe icien indica es ha eal exchange a es
do no impac Japan’s expo s o Ko ea in he long un. He explained his inding by no ing
ha , since Ko ea elies on machine y om Japan, demand does no espond o exchange-
a e-d i en p ice changes. Wal e e al. (2012) used an ARDL model and qua e ly da a
o e he 1989 o 2011 pe iod o in es iga e Japan’s expo s o machine y and anspo a ion
and o he goods o he U.S. They also ound ha eal exchange a es do no impac Japan’s
machine y and anspo a ion expo s o he U.S.
Sa o e al. (2013) examined how indus y-speci ic eal exchange a es a ec Japanese
expo s o h ee elec ical machine y indus ies (o ice machine y, elec ical appa a uses,
and communica ion equipmen ) and o anspo a ion equipmen . They employed a
mon hly ec o au o eg ession (VAR) o e he 2001–2013 pe iod and Japan’s expo s o he
wo ld. They epo ed impulse- esponse unc ions indica ing ha a posi i e exchange a e
shock (yen app ecia ion) p oduced long-las ing declines in expo s o each ca ego y.
Chinn (2013) in es iga ed Japan’s expo s o he wo ld o e he 1990 o 2012 pe iod.
His heo e ical amewo k was he impe ec subs i u es model, whe e expo s a e a unc-
ion o he eal exchange a e and g oss domes ic p oduc in he impo ing coun ies. He
used qua e ly da a and Johansen maximum likelihood echniques. He epo ed ha
exchange a e elas ici ies we e co ec ly signed and a ied be ween 0.4 and 0.7.
Tang (2014) examined ade be ween Japan, China, Hong Kong, Indonesia, Malaysia,
he Philippines, Singapo e, Sou h Ko ea, Taiwan, and Thailand o e he 1980–2009 pe iod.
His heo e ical amewo k was also he impe ec subs i u es model. He used annual
da a and panel dynamic o dina y leas squa es es ima ion (DOLS). Fo equipmen goods
expo s, he ound ha he exchange a e coe icien was inco ec ly signed.
Tho becke (2015) in es iga ed Japanese capi al and equipmen goods expo s o
15 coun ies o e he 1982–2009 pe iod. He also used he impe ec subs i u es model,
annual da a, and panel DOLS es ima ion. Using se e al speci ica ions, he ound ha a
10 pe cen eal app ecia ion o he yen dec eases expo s by abou 5 pe cen .
The pe iod a e 1982 was e en ul o he Japanese economy. Be ween 1981 and 1984,
Japan ag eed o a olun a y expo es ain limi ing he numbe o ca s i expo ed o
he U.S. In 1985, o educe he U.S. ade de ici , Japan, F ance, Wes Ge many, and he
U.K. ag eed in he Plaza Acco d o le hei cu encies app ecia e agains he U.S. dolla .
F om he ime he acco d was signed in Sep embe 1985 un il he middle o 1995, he yen
app ecia ed om 240 o he U.S. dolla o below 88 o he dolla .
Japanese expo e s los p ice compe i i eness. To cu cos s, hey eloca ed labo -
in ensi e asks o ac o ies in he Associa ion o Sou heas Asian Na ions (ASEAN) and
China. The inal goods we e hen expo ed a ound he wo ld. Japanese inal goods expo s
ell om 20% o wo ld inal goods expo s in 1985 o 10% in 1995. Japanese ou wa d o eign
di ec in es men (FDI) inc eased om 0.5% o Japanese GDP in 1985 o mo e han 2.5% by
he end o he decade. U a a and Kawai (1999) epo ed ha Asia was a dominan ecipien
o Japanese FDI in he la e 1980s and 1990s. Japanese expo s o in e media e and capi al
goods (ICG) o China and ASEAN inc eased om 28% o Japanese ICG expo s in 1985 o
40% in 1995. China and ASEAN’s expo s o inal goods inc eased om 3% o wo ld inal
goods expo s in 1985 o abo e 10% in 1995.1
Bayoumi and Lipwo h (1998) p o ided o mal e idence on he de e minan s o
Japanese FDI o e he 1983–1995 pe iod. In addi ion o examining he impac o he
eal exchange a e, hey also in es iga ed whe he he mo i e o FDI was o use o eign
subsidia ies o complemen Japanese p oduc ion o whe he i was o supply he hos
coun y ma ke . In he i s case, FDI o a coun y should be ela ed o capi al o ma ion
in Japan since p oduc ion in he wo loca ions a e complemen s. In he second case, FDI
o a coun y should be ela ed o capi al o ma ion in he hos coun y since domes ic and
o eign i ms in he hos coun y bo h espond o hos coun y ma ke condi ions. The
au ho s epo ed ha an app ecia ion o he yen inc eased FDI lows and ha FDI lows
Economies 2024,12, 133 3 o 11
we e closely ela ed o capi al o ma ion in Japan bu no in he hos coun y. These indings
imply ha he mo i e o Japanese FDI was e ical in eg a ion, whe e subsidia ies in o he
coun ies became pa o he p oduc ion p ocess.
Yoshi omi (2007) desc ibed he ade ha accompanies his e ical FDI as e ical
in a-indus y ade (VIIT). VIIT di e s om ade in inal goods modeled in adi ional
ade heo y (e.g., weal hy economies expo ing capi al goods and de eloping economies
expo ing appa el). VIIT also di e s om ho izon al in a-indus y ade be ween wo
weal hy na ions (e.g., ade in wo di e en ypes o au omobiles). Unde VIIT, i ms
slice he alue chain ac oss de eloped, eme ging, and de eloping coun ies based on
he compa a i e ad an age. Each egion’s compa a i e ad an age is de e mined by i s
endowmen o capi al and skilled and unskilled labo and by i s physical and ins i u ional
in as uc u e. Fo ins ance, a Japanese company migh eloca e lowe -skilled asks o
lowe -wage loca ions and pe o m complex asks a highe -wage loca ions.
Tho becke (2008) in es iga ed how an app ecia ion o he yen ela i e o he U.S. dolla
impac ed Japanese o al expo s o he U.S. and Japanese expo s o in e media e goods o
Eas Asia o e he 1982–2003 pe iod. The esul s indica ed ha a 10% app ecia ion o he
yen/dolla eal exchange a e educed Japanese expo s o he U.S. by 4% and inc eased
Japanese in e media e goods expo s o Eas Asia by 8%. These indings imply ha Japan
educed expo s di ec ly o he U.S. in esponse o yen app ecia ions bu also p o ided mo e
pa s and componen s o downs eam ac o ies in Asia. These ac o ies hen expo ed he
inal goods o he U.S., Japan, and o he coun ies. Thus, he yen app ecia ion u he ed he
di ision o labo in Asia, wi h Japan p oducing and expo ing echnology-in ensi e pa s
and componen s o downs eam Asian coun ies whe e he inal goods we e assembled
and e-expo ed.
Sasaki e al. (2022) obse ed ha , when he yen app ecia ed du ing he 2008–2009
Global Financial C isis (GFC), Japanese mul ina ional co po a ions (MNCs) con inued o
eloca e manu ac u ing o e seas. This helped o o se he loss o p ice compe i i eness
om he app ecia ing yen, Then, as he yen began dep ecia ing in 2012, Japanese i ms did
no esho e p oduc ion bu con inued o p oduce ab oad.
Shimizu and Sa o (2015) no ed ha Japanese i ms esponded o he s ong yen du ing
he GFC by expanding he p oduc ion o low-end p oduc s ab oad and p oducing high-end
p oduc s domes ically. They employed Kalman il e me hods o in es iga e he exchange
a e pass- h ough o majo machine y indus ies. Using mon hly da a om 1980 o 2014,
hey ound ha , when he yen was s ong be ween 2009 and 2012, he deg ee o pass-
h ough inc eased. They also epo ed ha , as he yen weakened a e 2012, i ms chose
o p ice o ma ke a he han o pass- h ough dep ecia ions in o o eign p ices. Keeping
o eign cu ency p ices s able a he han le ing hem all as he yen dep ecia ed educed
he s imula i e impac o he dep ecia ion on expo olumes.
Shimizu and Sa o (2015) also examined he ela ionship be ween he yen eal e ec i e
exchange a e, indus ial p oduc ion in Japan and i s ading pa ne s, and he Japanese
ade balance. Using an ARDL model and mon hly da a, hey ound e idence o a J-cu e
e ec o e he 1985–1998 pe iod bu no o e he 1999–2014 pe iod. They no ed ha , o
se e al decades, Japanese i ms had been inc easing o e seas p oduc ion. Thei p oduc ion
ne wo ks we e cen e ed in Asian coun ies. As he yen app ecia ed du ing he GFC, hese
i ms accele a ed he di ision o labo by eloca ing mo e p oduc ion o Asia. Because o
his, Sa o and Shimizu no ed ha a weake yen no longe s imula es machine y expo s as
much because an inc ease in expo s inc eases he impo s o pa s and componen s om
o e seas subsidia ies in Asia.
I he p oduc ion o pa s and componen s has been eloca ed o Asian coun ies, hen
he yen exchange a e would ha e less o an impac on Japanese expo s o hese coun ies.
A dep ecia ion o he yen agains he cu ency o an Asian coun y p o iding pa s and
componen s o Japan would inc ease he yen cos s o hese impo ed inpu s. This inc ease
in cos s would mi iga e he inc ease in p ice compe i i eness a ising om he impac o
a weake yen on Japanese alue-added expo ed back o his coun y. Thus, i Japan has
Economies 2024,12, 133 4 o 11
o sho ed mo e p oduc ion o Asian coun ies a e he GFC, a yen dep ecia ion agains an
Asian coun y’s cu ency would ha e less o a s imula i e e ec on expo s o ha coun y
a e 2009.
This pape in es iga es whe he he in luence o exchange a es on Japan’s machine y
expo s has declined since he GFC. I also in es iga es whe he he exchange a e ma e ed
less o expo s o Asian coun ies a e he 2008–2009 GFC. To do his, i ex ends he model
o Tho becke (2015) o include he 2010–2020 pe iod. The esul s indica e ha , o he lion’s
sha e o machine y expo s, exchange a es no longe ma e o Japan’s expo s o Asian
coun ies bu do ma e o Japan’s expo s o non-Asian coun ies. The weak yen a e he
COVID-19 pandemic hus will no help companies in Asian coun ies pu chase i al capi al
goods om Japan bu will bene i companies in o he egions.
The nex sec ion discusses he da a and me hodology. Sec ion 3p esen s he esul s.
Sec ion 4concludes.
2. Da a and Me hodology
To es ima e expo elas ici ies, Tho becke’s (2015) model is ex ended using ecen da a.
Employing he impe ec subs i u es model, he examined Japanese machine y expo s o
15 coun ies o e he 1982–2009 pe iod. This pape also uses he impe ec subs i u es
model o guide he empi ical speci ica ion, ollowing Chinn (2013), Tang (2014), and many
o he esea che s. The impe ec subs i u es model posi s ha expo s depend on he eal
exchange a e be ween he expo ing and impo ing coun ies and on GDP in he impo ing
coun ies. The same 15 coun ies ha Tho becke used a e employed he e and he sample
pe iod is ex ended o 2020.2
Following Chinn (2004) and o he esea che s, he model is ea ed as a semi- educed
o m. Exchange a es a e ola ile and o en ha e a li e o hei own (see, e.g., Obs eld
and Rogo 2000). Thus, Chinn and o he s gi e a s uc u al in e p e a ion o he es ima ed
exchange a e elas ici ies. This pape ollows hem.
Annual da a on Japanese machine y and equipmen expo s a e measu ed in U.S.
dolla s and ob ained om he CEPII-CHELEM da abase. These a e de la ed using he U.S.
Bu eau o Labo S a is ics de la o o Japanese expo s. The esul s a e almos iden ical
when Japanese expo s a e de la ed using he Bank o Japan’s expo p ice index o
machine y expo s con e ed o U.S. dolla s using he yen/dolla exchange a e. Da a on
bila e al eal exchange a es be ween Japan and he impo ing coun ies and on eal GDP
in he impo ing coun ies a e also ob ained om he CEPII-CHELEM da abase.
The CEPII-CHELEM da abase also disagg ega es machine y and equipmen expo s
in o 12 ca ego ies. These a e ae onau ics, ag icul u al equipmen , comme cial ehicles,
compu e equipmen , cons uc ion equipmen , elec ical appa a uses, elec ical equipmen ,
machine ools, p ecision ins umen s, ships, specialized machines, and elecommunica ions
equipmen . Exchange a e elas ici ies a e also es ima ed o each o hese subca ego ies.
Tho becke (2015) es ima ed he ela ionship be ween machine y and equipmen ex-
po s, eal exchange a es, and GDP using panel DOLS. This echnique is app op ia e when
he a iables ha e uni oo s and when he e is a coin eg a ing ela ionship be ween he
a iables. Table 1p esen s he esul s om a se ies o panel uni oo es s o hese a iables.
The esul s do no pe mi ejec ion o he null hypo hesis o a uni oo o eal GDP. The
esul s do, howe e , pe mi ejec ion o he main ained hypo hesis o a uni oo o eal
exchange a es and o mos ca ego ies o machine y and equipmen expo s. The model,
hus, canno be es ima ed by panel DOLS. I is es ima ed ins ead wi h ixed e ec es ima ion
wi h eal GDP included in i s di e ence o m and wi h he o he a iables included in
le els. Bo h pe iod and c oss-sec ional ixed e ec s a e also included in he es ima ion.
Economies 2024,12, 133 5 o 11
Table 1. Panel Uni Roo Tes s.
Uni Roo Tes
Real
GDP
Real Exchange
Ra e
Machine y
Expo s
Tes
S a is ic
Tes
S a is ic
Tes
S a is ic p-Value Tes
S a is ic p-Value
Le in, Lin, and Chu * 3.84 0.999 −5.31 0.000 −5.04 0.000
B ei ung -s a 6.83 1.000 −4.59 0.000 −0.744 0.228
Im, Pesa an, and Shin W-s a 5.23 1.000 −4.61 0.000 −3.61 0.000
Augmen ed Dickey–Fulle Fishe Chi-squa e 14.24 0.993 69.74 0.000 59.30 0.001
Phillips–Pe on Fishe Chi-squa e 15.48 0.987 48.28 0.019 46.25 0.029
Uni Roo Tes
Elec ical
Appa a uses
Specialized
Machine y
P ecision
Ins umen s
Tes
S a is ic p- alue Tes
S a is ic p- alue Tes
S a is ic p- alue
Le in, Lin, and Chu * −4.15 0.000 −7.01 0.000 −1.48 0.068
B ei ung -s a 1.56 0.940 −4.91 0.000 1.55 0.939
Im, Pesa an, and Shin W-s a −2.62 0.004 −4.77 0.000 −0.485 0.314
Augmen ed Dickey–Fulle Fishe Chi-squa e 54.13 0.004 70.50 0.000 38.03 0.149
Phillips–Pe on Fishe Chi-squa e 61.75 0.001 69.61 0.000 41.96 0.072
Uni Roo Tes
Cons uc ion
Equipmen
Compu e
Equipmen Ships
Tes
S a is ic p- alue Tes
S a is ic p- alue Tes
S a is ic p- alue
Le in, Lin, and Chu * −3.18 0.001 −3.05 0.001 −10.99 0.000
B ei ung -s a −2.89 0.002 −0.744 1.000 −6.19 0.000
Im, Pesa an, and Shin W-s a −2.38 0.009 −1.74 0.041 −9.30 0.000
Augmen ed Dickey–Fulle Fishe Chi-squa e 45.22 0.037 44.25 0.045 136.06 0.000
Phillips–Pe on Fishe Chi-squa e 39.09 0.124 289.47 0.000 135.84 0.000
Uni Roo Tes
Machine
Tools
Elec ical
Equipmen
Comme cial
Vehicles
Tes
S a is ic p- alue Tes
S a is ic p- alue Tes
S a is ic p- alue
Le in, Lin, and Chu * −6.04 0.000 −2.60 0.005 −4.59 0.000
B ei ung -s a −2.00 0.023 −2.52 0.006 −3.49 0.000
Im, Pesa an, and Shin W-s a −4.34 0.000 −3.54 0.000 −4.79 0.000
Augmen ed Dickey–Fulle Fishe Chi-squa e 71.13 0.000 64.34 0.000 74.49 0.000
Phillips–Pe on Fishe Chi-squa e 58.45 0.014 57.96 0.002 66.64 0.000
Uni Roo Tes
Telecommunica ions
Equipmen Ae onau ics Ag icul u al
Equipmen
Tes
S a is ic p- alue Tes
S a is ic p- alue Tes
S a is ic p- alue
Le in, Lin, and Chu * 0.14 0.557 −4.09 0.000 −0.80 0.212
B ei ung -s a 2.21 0.986 −0.96 0.162 −0.53 0.299
Im, Pesa an, and Shin W-s a 1.18 0.880 −5.97 0.000 −1.10 0.136
Augmen ed Dickey–Fulle Fishe Chi-squa e 25.87 0.682 97.10 0.000 45.06 0.038
Phillips–Pe on Fishe Chi-squa e 26.73 0.638 104.35 0.000 35.20 0.236
No es: The able p esen s es s a is ics o panel uni oo es s o he null hypo hesis o a uni oo . The es s a e
discussed in Le in e al. (2002), B ei ung (2000), Im e al. (2003), Maddala and Wu (1999), and Choi (2001). In each
case, lag leng hs a e selec ed based on he Schwa z In o ma ion C i e ion. A end e m is included in he es
equa ions. p- alue ep esen s he p obabili y alue o he es o he main ained hypo hesis o a uni oo .
Economies 2024,12, 133 6 o 11
3. Resul s
Table 2examines whe he exchange a e changes impac expo olumes. The able
p esen s he esul s o es ima ing exchange a e elas ici ies o all machine y expo s and o
he 12 subca ego ies. Column (2) lis s he sha e o each subcomponen in o al machine y
expo s in 2020. Column (3) p esen s he esul s o he en i e 1990–2020 sample pe iod.
The exchange a e ma e s o Japanese machine y expo s. A 10% yen app ecia ion
educes expo s by 7.6%. Fo he indi idual subca ego ies, 9 o he 12 ca ego ies exhibi
s a is ically signi ican expo declines in esponse o yen app ecia ions. Only he exchange
a e coe icien on ship expo s is inco ec ly signed. Table A1 in he Appendix Ap esen s
he co esponding GDP elas ici ies.
Table 2. Panel o dina y leas squa es es ima es o exchange a e elas ici ies o Japan’s machine y
expo s o 15 coun ies (wi h s anda d e o s in pa en heses).
Expo Ca ego y
Sha e o
Machine y
Expo s in 2020
Sample Pe iod
1990–2020 1990–2000 2000–2010 2010–2020
(1) (2) (3) (4) (5) (6)
Machine y (All) 1.00 −0.764 *** −0.577 *** −0.601 *** −0.274
(0.115) (0.176) (0.120) (0.171)
Elec ical appa a uses 0.227 −0.660 *** −0.665 *** −0.215 0.354
(0.146) (0.191) (0.174) (0.279)
Specialized machines 0.206 −0.455 ** −0.745 *** −0.283 0.387
(0.207) (0.214) (0.213) (0.460)
P ecision ins umen s 0.142 −1.427 *** −0.930 *** −1.268 *** −1.057 ***
(0.170) (0.155) (0.217) (0.396)
Cons uc ion equipmen 0.075 −1.400 *** −1.204 *** −1.929 *** −0.465
(0.139) (0.363) (0.339) (0.432)
Compu e equipmen 0.059 −1.871 *** 0.361 −1.541 *** 0.441
(0.173) (0.336) (0.258) (0.535)
Ships 0.052 0.955 ** −1.220 1.120 1.878
(0.400) (1.045) (0.790) (1.567)
Machine ools 0.052 −0.965 *** −0.689 *** −0.836 *** 1.717 *
(0.180) (0.257) (0.232) (0.906)
Elec ical equipmen 0.050 −0.429 *** 0.070 −0.531 ** −0.958 **
(0.148) (0.413) (0.219) (0.440)
Comme cial ehicles 0.049 −0.904 *** −2.286 *** −0.966 ** 0.522
(0.251) (0.608) (0.396) (0.756)
Telecommunica ions equipmen 0.045 −0.329 0.896 0.698 −1.921 ***
(0.311) (0.807) (0.574) (0.422)
Ae onau ics 0.032 −0.205 −0.900 0.162 −2.026 ***
(0.341) (0.644) (0.597) (0.739)
Ag icul u al equipmen 0.010 −1.01 *** −1.261 *** −0.377 −1.170 **
(0.191) (0.473) (0.292) (0.564)
No es: The able p esen s es ima es o exchange a e elas ici ies om a panel o dina y leas squa es model o
Japan’s expo s o 15 coun ies. Expo s a e measu ed in U.S. dolla s and de la ed using p ice de la o s o
Japanese expo s ob ained om he U.S. Bu eau o Labo S a is ics. The explana o y a iables include he bila e al
CPI-de la ed eal exchange a e be ween Japan and each o he impo ing coun ies and he i s di e ence o
eal GDP in he impo ing coun ies. The 15 impo ing coun ies a e Aus alia, Canada, China, F ance, Ge many,
Hong Kong, Indonesia, Malaysia, he Ne he lands, Singapo e, Sou h Ko ea, Taiwan, Thailand, he U.K., and
he U.S. Coun y and yea ixed e ec s a e included in he es ima ion. Whi e s anda d e o s a e epo ed in
pa en heses. *** (**) [*] deno es signi icance a he 1% (5%) [10%] le el.
Economies 2024,12, 133 7 o 11
The esul s o he 1990–2000 subsample in column (4) and he 2000–2010 subsample
in column (5) also indica e ha app ecia ions educe expo s. Fo o al machine y expo s,
a 10% app ecia ion educes expo s by abou 6% in bo h subsample pe iods. Many o he
indi idual subca ego ies also exhibi dec eases in expo s in esponse o app ecia ions.
The esul s o he 2010–2020 subsample in column (6) no longe p esen s ong
e idence ha app ecia ions educe machine y expo s. The exchange a e coe icien o
o al machine y expo s is small and no s a is ically signi ican . Fo mos o he la ge
subca ego ies, exchange a e dep ecia ions no longe inc ease expo s.
The ac ha exchange a es do no impac specialized machine y expo s a e 2000
is consis en wi h Baek’s (2013) obse a ion ha downs eam coun ies such as Sou h
Ko ea depend on machine y expo s om Japan. Japan expo s obo s, semiconduc o
manu ac u ing machines, and o he ad anced machine y. As discussed in he in oduc ion,
acco ding o Hidalgo and Hausmann’s measu e, Japan has he mos sophis ica ed expo
baske , and specialized machine y expo s a e especially ad anced. Abiad e al. (2018)
no ed ha he e a e ew subs i u es o complex goods, and, hus, ha hei exchange a e
elas ici ies should be small.
Comme cial ehicle expo s also ceased o espond o exchange a e changes a e
2010. Nguyen and Sa o (2019) ound ha Japanese anspo a ion equipmen expo e s
esponded o yen dep ecia ions du ing he dep ecia ion ha began in 2012 by p icing o
ma ke . This mean ha , a he han lowe ing p ices in he impo ing coun y’s cu ency,
hey chose o keep o eign p ices close o cons an . Thus, hey chose no o inc ease expo
olumes as he yen dep ecia ed, bu a he o inc ease p o i ma gins.
Telecommunica ions equipmen was e y sensi i e o exchange a es o e he 2010–2020
pe iod. Be o e he GFC, Japan was a leading p oduce o cellphones. Howe e , as Sa o e al.
(2013) discussed, he sha p app ecia ion o he yen ha s a ed wi h he GFC combined
wi h he sha p dep ecia ion o he Ko ean won caused Japan’s communica ion equipmen
expo s o plumme and Ko ean communica ions expo s o soa . Tho becke (2023) epo ed
ha , by 2012, Samsung o Ko ea had become he la ges phone manu ac u e by sales. I
con inued o hold his posi ion up o 2022.
Table 3p esen s exchange a e elas ici ies sepa a ely o Asian and non-Asian coun ies.
Focusing on he 2010–2020 pe iod, column (8) epo s elas ici ies o Asian coun ies
and column (9) o non-Asian coun ies. Column (8) o Asian coun ies con inues o
indica e ha exchange a e dep ecia ions do no s imula e expo s o mos ca ego ies. The
coe icien o o al machine y expo s is small and s a is ically insigni ican . Coe icien s o
6 o he 12 subca ego ies a e posi i e (inco ec ly signed), wi h he coe icien on elec ical
appa a uses being posi i e and ha ing a p obabili y alue o 0.055 and he coe icien on
machine ools being posi i e and ha ing a p obabili y alue o 0.035.
Column (9) o non-Asian coun ies, on he o he hand, indica es ha dep ecia ions
s imula e machine y expo s. Fo o al machine y expo s, a 10% dep ecia ion inc eases
expo s o non-Asian coun ies by almos 6%. The e is also a s a is ically signi ican ela ion-
ship be ween exchange a e dep ecia ions and ising expo s o 5 o he 12 subca ego ies.
The esul s in columns (8) and (9) a e consis en wi h Shimizu and Sa o’s (2015) hypo h-
esis ha he eloca ion o p oduc ion o Asian coun ies has weakened he link be ween
exchange a e dep ecia ions and Japanese machine y expo s o Asia.
Ano he ac o d i ing he esul s in Table 3is he su ge in FDI ha Shimizu and
Sa o (2015) epo ed as Japanese MNCs in ensi ied he slicing up o he alue chain o
Asian coun ies a e he GFC. Bayoumi and Lipwo h (1998) ound ha a yen app ecia ion
inc eases Japanese FDI. They also no ed ha inc eases in Japanese FDI o a coun y a e
accompanied by inc eases in Japanese capi al goods expo s as pa o he ini ial in es men .
Thus, an app ecia ion o he yen can be associa ed wi h an inc ease in capi al goods
expo s associa ed wi h he Japanese in es men . Expo s o Asia o ca ego ies ha a e
clea ly no ela ed o equipping ac o ies in Asia (e.g., ae onau ics, ag icul u al equipmen ,
and elecommunica ions equipmen ) esponded as expec ed o exchange a e changes
o e he 2010–2020 pe iod. Sec o s ha may be ela ed o cons uc ing and equipping
Economies 2024,12, 133 8 o 11
ac o ies in downs eam Asian coun ies (e.g., specialized machine y, compu e equipmen ,
cons uc ion equipmen , and machine ools) no longe espond as expec ed o exchange
a e changes.
Table 3. Panel O dina y Leas Squa es Es ima es o Exchange Ra e Elas ici ies o Japan’s Machine y
Expo s o Asian and Non-Asian Coun ies (wi h S anda d E o s in Pa en heses).
Expo
Ca ego y
Sample Pe iod:
1990–2020 1990–2000 2000–2010 2010–2020
Expo s o:
Asian
Coun ies
Non-
Asian
Coun ies
Asian
Coun ies
Non-
Asian
Coun ies
Asian
Coun ies
Non-
Asian
Coun ies
Asian
Coun ies
Non-
Asian
Coun ies
(1) (2) (3) (4) (5) (6) (7) (8) (9)
Machine y
(All)
−0.953 *** −0.295 *** −0.350 −0.860 *** −0.792 *** −0.410 *** −0.201 −0.583 ***
(0.117) (0.097) (0.022) (0.177) (0.144) (0.134) (0.171) (0.187)
Elec ical
appa a uses
−0.887 *** −0.095 −0.388 −0.101 *** −0.527 *** 0.098 0.515* −0.329
(0.149) (0.117) (0.244) (0.211) (0.201) (0.190) (0.266) (0.263)
Specialized
machines
−0.633 *** −0.009 −0.630 ** −0.889 *** 0.402 −0.164 0.478 0.085
(0.204) (0.208) (0.293) (0.290) (0.360) (0.269) (0.502) (0.355)
P ecision
ins umen s
−1.627 *** −0.930 *** −0.750 *** −1.154 *** −1.534 *** −1.000 *** −1.113 *** −0.770 **
(0.167) (0.103) (0.190) (0.203) (0.258) (0.196) (0.422) (0.370)
Cons uc ion
equipmen
−1.166 *** −1.971 *** −1.526 *** −0.803 ** −2.160 *** −1.699 *** −0.158 −1.774 ***
(0.141) (0.159) (0.508) (0.372) (0.371) (0.339) (0.437) (0.420)
Compu e
Equipmen
−2.273 *** −0.822 *** 0.798 −0.188 −1.619 *** −1.463 *** 0.343 0.764
(0.186) (0.179) (0.405) (0.344) (0.310) (0.269) (0.593) (0.459)
Ships 0.338 2.495 *** −1.702 −0.613 −0.010 2.252 ** 1.589 3.123
(0.440) (0.538) (1.214) (1.425) (0.726) 1.100 (1.528) (2.395)
Machine
Tools
−1.059 *** −0.733 *** −0.477 −0.954 *** −1.049 *** −0.622 *** 2.050 ** 0.726
(0.186) (0.222) (0.377) (0.262) (0.262) (0.265) (0.961) (0.827)
Elec ical
equipmen
−0.392 ** −0.527 *** 0.496 −0.461 −0.745 *** −0.348 −0.822 * −1.316 **
0.159 (0.194) (0.479) (0.417) (0.238) (0.238) (0.450) (0.506)
Comme cial
Vehicles
−1.087 *** −0.450* −2.256 *** −2.323 *** −1.374 *** −0.557 0.943 −1.266
(0.285) (0.262) (0.777) (0.684) (0.430) (0.414) (0.756) (0.992)
Telecomm-
unica ions
equipmen
−0.442 −0.047 1.808 * −0.241 1.083 0.313 −2.132 *** −1.024 **
(0.314) (0.338) (0.992) (0.684) (0.609) (0.577) (0.443) (0.394)
Ae onau ics −0.437 0.373 −0.763 −1.070 0.320 0.004 −2.196 *** −1.301
(0.358) (0.403) (0.801) (0.852) (0.800) (0.393) (0.732) (0.971)
Ag icul u al
equipmen
−0.965 *** −1.128 *** −1.633 ** −0.798 * −0.827 * 0.075 −1.117 * −1.395 **
(0.223) (0.209) (0.642) (0.472) (0.432) (0.302) (0.595) (0.597)
No es: The able p esen s es ima es o exchange a e elas ici ies om a panel o dina y leas squa es model o
Japan’s expo s o 15 coun ies. Expo s a e measu ed in U.S. dolla s and de la ed using p ice de la o s o
Japanese expo s ob ained om he U.S. Bu eau o Labo S a is ics. The explana o y a iables include he bila e al
CPI-de la ed eal exchange a e be ween Japan and each o he impo ing coun ies and he i s di e ence o eal
GDP in he impo ing coun ies. Asian coun ies include China, Hong Kong, Indonesia, Malaysia, Singapo e,
Sou h Ko ea, Taiwan, and Thailand. Non-Asian coun ies include Aus alia, Canada, F ance, Ge many, he
Ne he lands, he U.K., and he U.S. Coun y and yea ixed e ec s a e included in he es ima ion. Whi e s anda d
e o s a e epo ed in pa en heses. *** (**) [*] deno es signi icance a he 1% (5%) [10%] le el.
