G ijal a, Diego F.; U ibe-Te án, Ca los; Gache, I an
Wo king Pape
The con ac iona y e ec s o p o ec ionis ade policy in a
dolla ized economy
IDB Wo king Pape Se ies, No. IDB-WP-1480
P o ided in Coope a ion wi h:
In e -Ame ican De elopmen Bank (IDB), Washing on, DC
Sugges ed Ci a ion: G ijal a, Diego F.; U ibe-Te án, Ca los; Gache, I an (2024) : The con ac iona y
e ec s o p o ec ionis ade policy in a dolla ized economy, IDB Wo king Pape Se ies, No. IDB-
WP-1480, In e -Ame ican De elopmen Bank (IDB), Washing on, DC,
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The Con ac iona y E ec s o P o ec ionis
T ade Policy in a Dolla ized Economy
Diego F. G ijal a
Ca los U ibe-Te án
I an Gache
IDB WORKING PAPER SERIES Nº IDB-WP-1480
Janua y 2024
Depa men o Resea ch and Chie Economis
In e -Ame ican De elopmen Bank
Janua y 2024
The Con ac iona y E ec s o P o ec ionis T ade
Policy in a Dolla ized Economy
Diego F. G ijal a*
Ca los U ibe-Te án*
I an Gache **
* Uni e sidad San F ancisco de Qui o (USFQ)
** Wo ld Bank
Ca aloging-in-Publica ion da a p o ided by he
In e -Ame ican De elopmen Bank
Felipe He e a Lib a y
G ijal a, Diego F.
The con ac iona y e ec s o p o ec ionis ade policy in a dolla ized economy / Diego
F. G ijal a, Ca los U ibe-Te án, I an Gache .
p. cm. — (IDB Wo king Pape Se ies ; 1480)
Includes bibliog aphical e e ences.
1. Comme cial policy-Ecuado . 2. P o ec ionism-Ecuado . 3. Ta i -Ecuado . 4.
Dolla iza ion-Ecuado . I. Ca los U ibe-Te án. II. Gache , I án. III. In e -Ame ican
De elopmen Bank. Depa men o Resea ch and Chie Economis . IV. Ti le. V. Se ies.
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2024
Abs ac
This s udy analyzes he i m-le el impac s o empo a y sa egua d impo a i s
implemen ed in Ecuado om 2015 o 2017. Employing a di e ence-in-di e ences
me hodology, we explo e he policy’s e ec s on a unique da ase combining i m- and
p oduc -le el da a. We ocus on he di ec e ec s on impo ing i ms and indi ec e -
ec s h ough he alue chain. The analysis shows, ha while he sa egua ds signi i-
can ly educed impo s, hey also esul ed in sho - un nega i e scale e ec s on i ms.
These include educed sales, employmen , labo cos s, and ma e ial cos s, wi hou pos-
i i e impac s on local i ms in impo -compe ing indus ies. O e all, ou indings sug-
ges a con ac iona y e ec o p o ec ionis policies, pa icula ly in a dolla ized econ-
omy, highligh ing he complex implica ions o ade measu es on i m pe o mance
and economic sec o s.
JEL classi ica ions: F13, F14, F16, O24, O54
Keywo ds: T ade policy, P o ec ionism, Inpu -ou pu linkages, Eme ging ma ke s, La in
Ame ica
Acknowledgmen s: We hank Pablo As udillo and Se icio de Ren as In e nas (SRI)
o p o iding comp ehensi e yea ly ansac ion-le el da a o all egis e ed i ms in
Ecuado . We a e also g a e ul o he La in Ame ica and he Ca ibbean Resea ch Ne -
wo k o he In e -Ame ican De elopmen Bank G oup o hei inancial suppo o he
p ojec “The Poli ical Economy o T ade Policy in La in Ame ica and he Ca ibbean.”
Thanks o Paul E. Ca illo, Kaspe V ojlik, P iya anjan Jha, and an anonymous e iewe
a he In e -Ame ican De elopmen Bank o help ul commen s on an ea lie e sion
o his pape . We also app ecia e discussions wi h pa icipan s a he USFQ B ownbag
semina , he LACEA-LAMES annual mee ing, and he IEA Annual Cong ess. A special
men ion o Sa a B bo ich o he excellen wo k in c ea ing he inal da ase . The opin-
ions in his pape a e ou s and do no ep esen hose o ou ins i u ions. Replica ion
iles a e a ailable om he au ho s upon eques .
1. In oduc ion
T ade a i s h oughou he wo ld ha e emained s able o declined in ecen decades,
ye he use o empo a y ade ba ie s (TTBs)—an idumping measu es, coun e ailing
du ies, and sa egua ds—has ballooned (Bown,2011;G üble and Rei e ,2021). Se e al
a icles ha e analyzed he i m-le el e ec s o ecen cases o coun ies using TTBs, bu ha e
ocused mainly on an idumping (see e.g. Jabbou e al.,2019;Konings and Vandenbussche,
2013;Vandenbussche and Zana di,2010), which ends o a ec a ela i ely small numbe
o i ms. In con as , we look a he i m-le el e ec s o empo a y sa egua ds ha a ec ed
abou 80% o he uni e se o impo ing i ms in Ecuado , a dolla ized eme ging economy.
Following a decade-long oil boom, a he end o 2014, Ecuado ’s oil p ice ell o less
han hal o i s 2011-2013 le els, educing go e nmen e enue and h ea ening a la ge
ade de ici . The Ecuado ian go e nmen esponded by implemen ing a b oad se o em-
po a y sa egua d impo a i s o limi impo s. The sa egua ds came in o e ec on Ma ch
11, 2015 and a ec ed app oxima ely one- hi d o all impo s, including in e media e inpu s
(capi al and aw ma e ials) and inal goods (consump ion).
The Ecuado ian implemen a ion o sa egua ds p o ides an ideal case s udy because i
used a i s (as opposed o non- a i ba ie s), and because o i s b oad-based, empo a y
na u e. Since i a ec ed a ound one- hi d o impo s (close o 3,000 HTS 10-digi subhead-
ings), he policy gene a ed he e ogeneous exposu e ac oss i ms and indus ies. Also,
since he sa egua ds co e ed inal and in e media e goods, hey had an e ec on i ms’
ac i i y bo h as p oduce s and as consume s o goods and se ices. Finally, he policy was
la gely unexpec ed, as i s a ed a mos i e mon hs a e he ini ial decline in oil p ices.
The implemen a ion o he Ecuado ian sa egua ds also allows us o nea ly isola e hei
e ec , wi hou se e al o he usual con ounding ac o s. Fi s , because he policy was im-
plemen ed unila e ally unde he p o ision o A icle XVIII o he WTO, he e was no ecip-
oca ion by Ecuado ’s ading pa ne s. Second, he sa egua ds we e ini ially designed o
las o 15 mon hs, and he e o e i ms conside ed hem empo a y.1Thi d, since Ecuado
is a dolla ized economy, he e we e no e ec s on he nominal exchange a e and he Cen al
Bank did no espond.
We analyze he in luence o sa egua d impo a i s on he pe o mance o Ecuado ian
i ms by aking ad an age o hei a ying exposu e o he policy. Gi en ha i ms and in-
dus ies ha e unique impo p o iles, hey we e a ec ed di e en ly by he in oduc ion o
sa egua ds. This di e si y allows us o e alua e he causal impac o he policy by apply-
ing a di e ence-in-di e ence app oach. Al hough impo su cha ges we e implemen ed
1The sa egua ds we e ex ended in Ap il 2016 ollowing a s ong ea hquake ha a ec ed he Ecuado ian
Coas . They we e ully phased ou in June 2017.
2
be ween 2015 and 2017, we es ima e hei immedia e (2015), sho - un (2016 and 2017),
and medium- un (2018-2021) e ec s, all ela i e o a 2014 baseline.
Using i m-le el a ia ion in exposu e, we assess hei di ec impac on impo s and
es ima e he elas ici y o impo s wi h espec o a i s (di ec exposu e). Subsequen ly,
we examine how hese p o ec i e measu es ha e a ec ed a ious pe o mance indica o s
o impo ing i ms, including o al ac o p oduc i i y (TFP), sales and he likelihood o
i m exi . We also look a he channels h ough which sa egua ds migh ha e a ec ed hese
pe o mance measu es, speci ically employmen , labo cos s and ma e ial cos s.
Likewise, using indus y a ia ion a he ISIC 4-digi le el, we e alua e he sa egua ds’
impac on he same pe o mance indica o s o impo ing-expo ing, local impo -compe ing,
and local non-impo -compe ing i ms. We es ima e he e ec s o indus y-le el p o ec ion
gene a ed by he sa egua ds (ou pu exposu e) and, using ISIC 4-digi o al equi emen s
inpu -ou pu ables, we also es ima e he impac o sa egua ds on downs eam indus ies
h ough hei alue chain exposu e (inpu exposu e).
Figu e 1p o ides a simple o e iew o he me hodology conside ing he impo dy-
namics. I shows he mon hly pe cen age a ia ion o he impo s alue wi h espec o
he a e age o Janua y 2014–Feb ua y 2015, sepa a ed by whe he he HTS subheadings
we e a ec ed by he sa egua ds. The igu e also shows he pe cen age a ia ion o o al im-
po s. Be o e he implemen a ion o he sa egua ds, each g oup o impo s beha ed e y
simila ly, bu his was no he case du ing and a e he implemen a ion o he sa egua ds:
impo s o a ec ed p oduc s ell signi ican ly mo e ela i e o he Janua y 2014–Feb ua y
2015 a e age.
Ou esul s poin o a clea sho - and medium- e m ade-o be ween educing a
ade de ici by inc easing he cos o impo s and he i m-le el cos s o using sa egua ds
o achie e his goal. In 2017, he las yea he policy was in place, an addi ional 1% o
di ec exposu e led o a i m-le el dec ease o 2.6% in he a e o impo g ow h. Impo s
elas ici y eached -0.15 in his yea , a ela i ely low alue consis en wi h he empo a y
na u e o he sa egua ds.
This educ ion in impo s among exposed impo ing i ms was associa ed wi h la ge
nega i e pe o mance esul s. The mechanism is a educ ion in he i ms’ scale (Head and
Ries,1999): In 2017, an addi ional di ec exposu e o 1% was associa ed wi h a educ ion o
0.86% in sales g ow h, 0.40% in employmen g ow h, and 0.99% in ma e ial cos s g ow h.
These e ec s pe sis ed un il 2021, beyond he implemen a ion o he policy.
Along wi h hese esul s, we ind ha exposu e o he sa egua ds was associa ed wi h
a highe p obabili y o i ms exi ing he ma ke . By 2021, a 1% inc ease in exposu e esul ed
in a 1.37% highe p obabili y o exi .
3
S a o sa egua ds
End o sa egua ds
-80 -60 -40 -20 0 20 40
Pe cen age a ia ion
2012m1
2013m1
2014m1
2015m1
2016m1
2017m1
2018m1
2019m1
2020m1
2021m1
2022m1
Non-a ec ed A ec ed All impo s
Figu e 1: Impo E olu ion o A ec ed and Non-a ec ed HTS 10-digi Subheadings
This igu e displays he impo dynamics o a ec ed and non-a ec ed HTS 10-digi subheadings
be o e (2012-2014), du ing (2015-2017), and a e (2018-2021) he pe iod o implemen a ion o he
sa egua d impo a i s in Ecuado . I p esen s pe cen age changes compa ed o he a e age impo
le els be ween Janua y 2014 and Feb ua y 2015. Da a o o al impo s come om he Cen al Bank
o Ecuado ’s Comme ce da ase . Mon hly high- equency a ia ion is smoo hed ou using a h ee-
pe iod mo ing a e age.
We also analyze he e ec s o sa egua d impo a i s on o he ypes o i ms using
indus y-le el a ia ion in ou pu and inpu exposu e (Co den,1966,1971). Impo ing-
expo ing i ms and local impo -compe ing i ms we e no a ec ed. The la e esul is
impo an because i shows ha he i ms ha could ha e bene i ed om impo p o ec ion
did no ob ain any ad an age.
Local i ms ope a ing in non-impo -compe ing indus ies we e nega i ely a ec ed
by he policy h ough hei alue chain exposu e. These i ms expe ienced a empo a y
decline in p oduc i i y g ow h be ween 2016 and 2018. In he las yea , a 1% inc ease
in inpu exposu e led o a 0.71% dec ease in he g ow h a e o TFP. An addi ional 1% in
inpu exposu e was also associa ed wi h a pe sis en decline in he g ow h a e o sales and
ma e ial cos s, eaching 6.67% and 7.61% in 2021, espec i ely. The g ow h o labo cos s
among hese i ms also dec eased be ween 2018 and 2020. In he las yea , a 1% inc ease
in inpu exposu e implied a educ ion o 13.63% in he g ow h a e o labo cos s.
4
Finally, we show ha he sa egua ds did no ha e an e ec on he sha e o new i ms by
indus y. Toge he wi h an inc eased p obabili y o exi among impo ing i ms, his esul
p o ides e idence o a ne nega i e e ec o sa egua d impo a i s on i m c ea ion.
The pape con ibu es o he ecen li e a u e ha inds ha p o ec ionis ade policy
has con ac iona y e ec s e en in he case o a ixed exchange a e (Ba a ie i e al.,2021).
We p o ide empi ical mic oeconomic e idence o hese nega i e e ec s in he con ex o
a dolla ized eme ging economy, which displays some elemen s o a ixed exchange a e,
excep o he expansiona y policy needed om he Cen al Bank o sus ain he ixed ex-
change a e. To he bes o ou knowledge, his is he i s pape o p o ide a sys ema ic
e alua ion o a b oad-based sho - e m p o ec ionis policy in a dolla ized economy.
Mo e gene ally, ou pape con ibu es o he li e a u e ha analyzes he e ec s o ade
policy on i ms’ pe o mance. Howe e , in con as o he common ocus o he li e a u e
on he long- un consequences o pe manen a i educ ions, we ocus on he sho - and
medium- un e ec s o a ype o empo a y ade ba ie s (TTBs), sa egua d impo a i s.
This is impo an because he e ec s o inc easing a i s a e no symme ic wi h hose o
alling a i s (Fu ce i e al.,2021). The analysis p o ides e idence on a policy ool ha is
inc easingly used by de eloping coun ies acing balance o paymen s p oblems, bu ha
has been scan ly analyzed.2
The pape also con ibu es o he li e a u e ha looks a he e ec s o ade policy
h ough alue chains. Speci ically, we p o ide empi ical e idence on he sho - and medium-
un e ec s o sa egua ds h ough e ical p oduc ion linkages. Finally, i also con ibu es
o he s ill-scan li e a u e on ade policy e ec s a he i m le el in La in Ame ica in gen-
e al, and Ecuado in pa icula .
Rela ion o he Li e a u e
This pape is ela ed o he li e a u e ha discusses he e ec s o ade policy unde
di e en exchange a e egimes (Au ay e al.,2022;Ba a ie i e al.,2021), ocusing on he
con ex o dolla iza ion.
I is also ela ed o he la ge se o s udies ha looks a he e ec s o ade policy
on i ms’ pe o mance, pa icula ly p oduc i i y. Caliendo and Pa o (2022) and Gold-
be g and Pa cnik (2016) e iew he li e a u e on he e ec s o ade policy in gene al and
De Loecke and Goldbe g (2014); Ha ison and Rod íguez-Cla e (2010) and Meli z and
2Acco ding o WTO S a s (a ailable a h ps://s a s.w o.o g/) since 1996 43 coun ies ha e had sa egua ds
in o ce a some poin . In any gi en yea , a ound 10 coun ies had a leas one measu e in o ce, and in 2015—
he peak yea and he yea ha we analyze o Ecuado —17 coun ies had a o al o 43 sa egua d measu es
in o ce. Since 2001 Ecuado had a o al o 9 yea s wi h sa egua d measu es in o ce.
5
Va iable Impo e Impo e -
expo e
Local, impo
compe ing
Local,
non-impo
compe ing
Impo s 2.38M
(8.12M)
2.32M
(8.92M)
101.14K
(782.80K)
73.08K
(777.88K)
Expo s 61.77K
(1.07M)
11.51M
(29.93M)
78.87K
(1.55M)
20.01K
(739.70K)
TFP 4.63 (12.03) 24.72
(44.56)
12.91
(20.46)
1.63
(4.38)
Sales 8.13M (41.37M) 19.46M
(60.50M)
2.68M
(9.44M)
3.90M (24.33M)
Wages 757.60K
(2.93M)
2.09M
(4.65M)
429.88K
(1.38M)
265.91K
(1.38M)
Employmen 63
(295)
263 (626) 50
(142)
30
(191)
Ma e ials 5.00M (28.25M) 11.94M
(28.57M)
1.48M
(5.68M)
3.05M (19.30M)
Table 2: Desc ip i e S a is ics o Full Sample Pe iod (2012-2021) by Fi m’s T ade S a us
This able p esen s he mean and s anda d de ia ion o impo s, sales, TFP, wages, employmen , and cos o
ma e ials by i m’s ade s a us o he en i e panel o i ms used o he es ima ion. S anda d de ia ions a e
p esen ed in pa en heses. Mis millions, Kis housands.
empo a y wo k o consul ing ac i i ies di ec ly ela ed o he p oduc ion p ocess. Labo
cos s also include cos s ela ed o egula ions such as manda o y social secu i y con ibu-
ions made by he employe on behal o he employee, and he paymen o he 15% sha e
o p o i s ha he i m is equi ed o pay o employees on an annual basis. Employmen
only conside s wo ke s hi ed unde o mal con ac s.
Impo e -expo e i ms a e much la ge han he es o he i ms in he economy in
e ms o sales, numbe o wo ke s, o pu chase o ma e ials. They a e also he mos p o-
duc i e, ollowed by local i ms in impo -compe ing indus ies (see Table 2). This esul
highligh s he ele ance o o eign compe i ion. Impo e -expo e i ms ace compe i ion
in in e na ional ma ke s, while local i ms in impo -compe ing indus ies ace compe i ion
om impo ed goods.
3. Fi ms’ Exposu e o T ade Policy
T ade policy a ec s economic ac i i y h ough di e en channels. The e o e, i ms’
exposu e o ade policy is highly he e ogeneous. To see why, we p opose a b oad classi-
ica ion o i ms acco ding o hei engagemen wi h in e na ional ma ke s: i ms ha a e
12
impo e s, hose ha a e impo e -expo e s, local i ms ha sell hei p oduc s in impo -
compe ing ma ke s, and local i ms ha sell hei p oduc s in non-impo -compe ing ma -
ke s.
In ou classi ica ion, i ms a e designa ed as impo e s i hey main ain an impo s-
o-sales a io o a leas 0.05 o h ee consecu i e yea s.5We posi ha hese i ms use
hei impo ed goods ei he o di ec sales o inal consume s o o sell as in e media e
goods o o he i ms. Consequen ly, sa egua d impo a i s ha e an immedia e impac on
hese i ms’ business ope a ions. We classi y hese i ms as di ec ly exposed, indica ing ha
sa egua d impo a i s signi ican ly in luence hei ou pu .
Fi ms a e classi ied as impo e -expo e i hey main ain impo - and expo - o-sales
a ios o no less han 0.05 o e a span o h ee yea s. We pos ula e ha hese i ms di ec ly
impo ma e ials as inpu s o hei p oduc ion, pu chase addi ional inpu s locally, and
subsequen ly dis ibu e hei p oduc s domes ically and in e na ionally.
These i ms can be a ec ed h ough wo channels. Fi s , hey a e di ec ly exposed ia
he ou pu pu chased in e na ionally o use in hei manu ac u ing p ocesses. Second,
hey ace an indi ec exposu e due o hei dependence on locally sou ced inpu s om o he
domes ic i ms, which may hemsel es be di ec ly a ec ed by he policy. This a ec s he
i m h ough he exposu e o i s alue chain o he sa egua d impo a i s, some hing ha
we call inpu exposu e.
I should be no ed ha , o bo h g oups o i ms (impo e s and impo e -expo e s),
p o ec ionis ade policies a e expec ed o exe ad e se e ec s, p ima ily h ough in-
c eased p oduc ion cos s ( e e o Konings and Vandenbussche,2013, o an analysis on
expo e s).
Assessing he impac o p o ec ionis ade policies on local i ms p esen s a complex
challenge. Fo i ms ope a ing in ma ke s ha compe e wi h impo s, sa egua d impo
a i s can lead o wo po en ial indi ec e ec s. The i s is ou pu p o ec ion, s emming
om a i s imposed on compe ing o eign goods. This e ec is indi ec because, while he
i m i sel is no subjec o a i s, he ma ke o i s p oduc s is in luenced by he policy.
Consequen ly, ade p o ec ion measu es a e likely o con e a compe i i e ad an age on
hese i ms ela i e o o eign supplie s.
This g oup o i ms could also expe ience an inc ease in p oduc ion cos s i hey ely
on inpu s om impo -dependen i ms a ec ed by sa egua d impo a i s. In such sce-
na ios, a decline in i m pe o mance is an icipa ed due o hei inpu exposu e. This concep
aligns wi h he no ion o e ec i e p o ec ion, as de eloped by Co den (1966,1971), which
5The a ionale o using a h ee-yea pe iod o de ine i ms’ ade s a us is associa ed wi h he es ablish-
men o ou baseline sample o he p e-policy pe iod in he empi ical analysis.
13
highligh s he dual impac o p o ec ionis ade policies. Ami i and Konings (2007), in
hei empi ical analysis o he Indonesian con ex , in oduced he e ms ou pu exposu e
and inpu exposu e o desc ibe hese dis inc bu in e ela ed e ec s.
Fi ms ope a ing in ma ke s ha do no di ec ly compe e wi h impo s a e no imme-
dia ely subjec o he di ec e ec s o p o ec ionis policies. Indi ec ly, howe e , hese i ms
can be a ec ed h ough hei supply chains. Speci ically, hey may ace subs an ial in-
c eases in p oduc ion cos s due o hei supplie s’ suscep ibili y o p o ec ionis measu es
(inpu exposu e). Consequen ly, we an icipa e obse ing de imen al impac s o such poli-
cies on hese i ms’ pe o mance, p ima ily d i en by he inc eased ope a ional cos s asso-
cia ed wi h hei inpu p ocu emen .
4. Iden i ica ion S a egy
Based on he p e ious discussion, ou empi ical s a egy exploi s i ms’ he e ogeneous
exposu e o sa egua d impo a i s and he di e en channels h ough which ade pol-
icy can a ec economic ac i i y. In his sec ion, we discuss he design o he measu es
o exposu e and hei dis ibu ions ac oss i ms and yea s, ollowed by he de ails o ou
iden i ica ion s a egy.
4.1. Measu es o Exposu e
In Sec ion 3, we delinea ed h ee measu es o exposu e o cap u e he impac s o he
sa egua d impo a i s. Fo cla i y, conside = 0 as he immedia e p e-policy pe iod.
The policy is implemen ed in pe iod = 1 and pe sis s du ing = [1,˜
T], whe e ˜
T > 1.
We obse e i m ac i i ies o a o al o T > ˜
Tpe iods. Deno e τi, as he sa egua d impo
a i le ied on good iin pe iod . Acco ding o he policy amewo k, i is e iden ha
τi, = 0 ∀ia = 0,τi, ≥0 o = [1,˜
T], and hen i e e s o τi, = 0 ∀ia > ˜
T.
Ex ending he wo k o p e ious s udies (Co den,1966,1971;Ami i and Konings,2007)
ha e alua ed ou pu and inpu exposu e a he indus y le el, we in oduce a measu e
o di ec exposu e a he i m le el. This measu e se es as a ea men indica o de ined
only o impo e s and impo e -expo e s. Le Mi,j,0be he alue o impo s o p oduc i
by i m jimmedia ely p eceding he implemen a ion o he policy. The cumula i e di ec
exposu e o i m jup o pe iod is exp essed as:
ed
j, =1
Mj,0
X
s=1
Ij,0
X
i=1
τi,sMi,j,0,(1)
14
whe e Ij,0 ep esen s he o al numbe o impo ed a ie ies by i m jin he p e-policy
pe iod, and Mj,0is he o al alue o impo s by i m jin he same pe iod.
This exposu e me ic e lec s he po en ial e ec i e a e ha a i m would ace unde
he cu en sa egua d impo a i egime τi, , conside ing i s impo s uc u e p io o he
change in policy. Assuming no an icipa ion e ec s, di ec exposu e is deemed exogenous.
The ange o alues o ed
j, spans om ze o o he highes a i a e es ablished in he policy.
Inco po a ing he amewo k o Ami i and Konings (2007), ou analysis also includes
measu es o ou pu and inpu exposu e, calcula ed a he indus y le el. Ou pu exposu e
cap u es he le el o p o ec ion ha an indus y ecei es agains in e na ional p oduc s
ha di ec ly compe e wi h i s ou pu . Following (Co den,1966,1971), ou pu exposu e
cons i u es he ini ial aspec o wha is e med e ec i e p o ec ion.
Le Mi,k,0 ep esen he o al alue o impo s o p oduc iby indus y k. The accumu-
la ed ou pu exposu e o indus y kup o pe iod is o mula ed as:
eo
k, =1
Mk,0
X
s=1
Ik,0
X
i=1
τi,sMi,k,0,(2)
whe e Ik,0deno es he spec um o p oduc s wi hin indus y kbe o e he s a o he policy.
The concep o e ec i e p o ec ion ex ends o a second laye , e lec ing he po en ial ise
in p oduc ion cos s o i ms ha sou ce inpu s om hose a ec ed by he policy. The inpu
exposu e o indus y kis de ined as he weigh ed a e age o ou pu exposu e endu ed by
i s supplie indus ies. Fo mally:
ex
k, =X
m
ωk,m,0·eo
k, ,whe e ωk,m,0=yk,m,0
yk,0
.(3)
He e, ωk,m,0, he weigh in he equa ion, e lec s he p opo ion o p oduc s ha in-
dus y kp ocu es om indus y m(yk,m,0) in ela ion o i s o al acquisi ions (yk,0) in he
p e-policy pe iod. These weigh s a e se be o e he policy’s implemen a ion o a oid en-
dogenei y and ensu e he alidi y o he ea men a iable.
To ge a sense o he s uc u e o he measu es o exposu e, Figu e 3p esen s he cumu-
la i e annual dis ibu ions o i ms and indus ies co esponding o di ec , ou pu , and in-
pu exposu es. Each dis ibu ion is condi ional on he ele an g oup o i ms. Di ec expo-
su e is condi ional on impo e s; ou pu exposu e is condi ional on impo e -expo e s and
local i ms in impo -compe ing indus ies; and inpu exposu e is condi ional on impo e -
expo e s and local i ms in impo - and non-impo -compe ing indus ies. The dis ibu-
ion o di ec exposu e is a he i m le el, while he dis ibu ions o ou pu and inpu
exposu es a e a he indus y le el (ISIC 4-digi s).
15
0 .2 .4 .6 .8 1
Cumula i e dis ibu ion
0 .1 .2 .3 .4 .5
Fi m-le el di ec exposu e
2015 2017 2019 2021
(a) Di ec
0 .2 .4 .6 .8 1
Cumula i e dis ibu ion
0 .1 .2 .3 .4 .5
Indus y-le el ou pu exposu e
2015 2017 2019 2021
(b) Ou pu
0 .2 .4 .6 .8 1
Cumula i e dis ibu ion
0 .05 .1 .15 .2 .25
Indus y-le el inpu exposu e
2015 2017 2019 2021
(c) Inpu
Figu e 3: Dis ibu ion o Measu es o Exposu e This igu e shows he dis ibu ions o he h ee
measu es o exposu e: di ec , ou pu , and inpu . Each dis ibu ion is condi ional on he ele an g oup o
i ms. Di ec exposu e is condi ional on impo e s and impo e -expo e s; ou pu exposu e is condi ional
on impo e -expo e s and local i ms in impo -compe ing indus ies; and inpu exposu e is condi ional
on impo e -expo e s and local i ms in impo - and non-impo -compe ing indus ies. The dis ibu ion o
di ec exposu e is a he i m le el, while he dis ibu ions o ou pu and inpu exposu es a e a he indus y
le el (ISIC 4-digi s).
A subs an ial p opo ion o i ms and indus ies a e no exposed o he sa egua d im-
po a i s. App oxima ely 20% o i ms ha e ze o di ec exposu e, while a ound 17% o
indus ies show no ou pu exposu e.
Inpu exposu e, howe e , p esen s a di e en pa e n. Due o he in e -indus ial link-
ages wi hin alue chains, almos all indus ies expe ience some le el o exposu e o sa e-
gua d impo a i s. Despi e his, he magni ude o inpu exposu e is gene ally lowe com-
pa ed o di ec and ou pu exposu es. While di ec and ou pu exposu es can each up o
45% (aligned wi h he policy’s maximum a i a e) in he ini ial yea o implemen a ion,
inpu exposu e seldom exceeds abou 20%.
The dynamic na u e o he policy and he cumula i e design o he exposu e indices
mean ha he exposu e dis ibu ions e ol e o e ime. Since impo s a e kep cons an a
baseline le els, exposu e o he policy g adually diminishes due o he phasing-ou o sa e-
gua d impo a i s. This end is e iden in he e olu ion o ou h ee exposu e measu es
o e ime.
By 2017, he o e all educ ion in exposu e is modes , ye some s ochas ic dominance is
obse able in Figu e 3. By 2019, e en hough he policy is no longe ac i e, he accumula ed
na u e o ou measu es s ill allows us o ack he exposu e o i ms and indus ies. As
expec ed, a ma ked dec ease in exposu e le els is appa en , becoming mo e p onounced
by 2021, which ma ks he las yea o ou analysis.
16
4.2. Empi ical Speci ica ions
Ou speci ica ions a e based on he linea di e ence-in-di e ence models p e iously
used by Machin e al. (2003); D aca e al. (2011) and Ha asz osi and Lindne (2019) in he
labo ma ke li e a u e.6We use di e en speci ica ions o each ype o i m in line wi h
he exposu e ha hey ace.
To de e mine he e ec s o sa egua d impo a i s on impo e s, we use ou measu e
o di ec exposu e ed
j, as a ea men a iable, whe e jdeno es i ms and deno es yea s.
Ou eg ession can be w i en as
zj, −zj,0=α +β ed
j, +γ Xj,0+εj, ,(4)
whe e he le -hand-side is he log- a ia ion in ou come z,α a e ime-speci ic ixed e ec s,
and γ measu es he e ec s o i m-speci ic cha ac e is ics. Ou pa ame e o in e es is β ,
which quan i ies he e ec o di ec exposu e o he impo sa egua ds on each speci ic
ou come.
We a e echnically compu ing a weigh ed a e age o he a e age ea men e ec (ATE).
Howe e , as poin ed ou by Callaway e al. (2021), he e a e se e al ca ea s ha mus be
aken in o accoun when using he wo-way ixed-e ec s es ima o o summa ize he e ec
o a con inuous ea men a iable. One majo conce n is he possibili y o bias a ising
e en i he classical pa allel ends assump ion is sa is ied. Howe e , in ou se ing, we a e
con iden ha we can in oke he s ong pa allel ends assump ion es ablished by Call-
away e al. (2021) due o he way we cons uc ed ou measu es o exposu e. Speci ically,
any bias esul ing om some uni s ecei ing a dose di e en om he one speci ied in he
o iginal ea men design should no be p oblema ic. Consequen ly, we in e p e β (and
he ele an coe icien s in he subsequen models) as a weigh ed a e age o he ATE e ec s
ac oss expec ed a i s.
I he i m-le el impac o he policy is p o ound enough, i will a ec impo ing i ms’
decisions on he ex ensi e ma gin o hei ac i i ies, i.e., some i ms may shu down hei
ope a ions due o he inc eased p oduc ion cos s. To e alua e his e ec , we use a modi ied
e sion o (4), whe e he ou come a iable is a bina y a iable, dj, , ha akes he alue o
1 i a i m shu s down in pe iod while i was open in pe iod 0. Ma hema ically,
dj, = Φ(θ +ξ ed
j, +ν Xj,0+ϵj, ),(5)
6Handley e al. (2020) use a simila s a egy o es ima e he e ec o impo a i s on expo s in he Uni ed
S a es h ough he lens o alue chain linkages.
17
whe e Φ(·) ep esen s he cumula i e dis ibu ion unc ion o he No mal dis ibu ion.
He e, ξ cap u es he impac o he sa egua d impo a i s on i ms’ exposu e, which may
esul in hem shu ing down.
As we discussed in Sec ion 3, iden i ying he e ec on he es o i ms in he economy
is mo e complex. In he case o impo e -expo e i ms, hey su e di ec exposu e o he
policy because o hei impo ing ac i i y, bu hey also ace inpu exposu e, because hey
migh s ill buy inpu s om i ms in indus ies ha we e a ec ed by he policy. The model
we es ima e o measu e hese e ec s can be w i en as:
zj,k, −zj,k,0=α +β ed
j, +θ ex
k, +γ Xj,0+εj,k, ,(6)
whe e θ measu es he e ec o inpu exposu e, which is measu ed a he indus y le el.
The exposu e o local i ms in impo -compe ing indus ies occu s h ough wo chan-
nels. Fi s , hese i ms ha e local sales ha migh be compe ing wi h impo s. Thus, he
i s channel is he p o ec ion igge ed by ou pu exposu e. The second channel is, again,
h ough he exposu e o hese i ms’ supplie chain, which is cap u ed by inpu exposu e.
The model o his g oup becomes he ollowing:
zj,k, −zj,k,0=α +β eo
k, +θ ex
k, +γ Xj,0+εj,k, ,(7)
whe e bo h measu es o exposu e a e measu ed a he indus y le el.
Finally, local i ms in non-impo compe ing indus ies a e mainly a ec ed by he ex-
posu e aced by hei supply chain. The model in his case simpli ies o:
zj,k, −zj,k,0=α +θ ex
k, +γ Xj,0+εj,k, ,(8)
whe e, again, exposu e is measu ed a he indus y le el.
Because o he di e en ia ed e ec s ha he policy design can ha e on i ms and in-
dus ies depending on hei impo s uc u e, we include a wide se o i m and indus y
cha ac e is ics se a baseline (2014) as con ols o all ou speci ica ions. In pa icula ,
we include indus y-le el ixed e ec s, dummy a iables ha iden i y i ms’ size acco d-
ing o hei sales, He indahl indexes o sales and impo s (compu ed a he ISIC 3-digi
le el), and i ms’ capi al s ock. Addi ionally, we conside he deg ee o impo pene a ion
a he indus y le el (ISIC 3-digi s), p o ince-le el ixed e ec s (de ined acco ding o he
i ms’ iscal iden i ica ion numbe ), a dummy ha iden i ies big co po a ions, and one ha
iden i ies i ms ha belong o business g oups. The las wo dummy a iables a e key o
18
con olling o a ia ion in he policy ha could be explained by he deg ee o lobbying
powe ha la ge i ms migh ha e in he design o he policy (Bomba dini,2008).
5. Resul s
We p esen he esul s o ou analysis in h ee sec ions. Fi s , we examine he impac o
sa egua d impo a i s on impo e s. We s a wi h an assessmen o he di ec e ec s on
impo s, hen explo e he implica ions on i m pe o mance, and conclude wi h an analysis
o he po en ial channels o in luence. Addi ionally, his sec ion inco po a es a placebo
es o assess he obus ness o ou iden i ica ion s a egy. We u he expand ou baseline
analysis by ex ending he s udy pe iod o e alua e he long- e m e ec s induced by he
policy.
Subsequen ly, we u n ou a en ion o non-impo ing i ms. Mi o ing ou app oach
wi h impo e s, we s udy he pe o mance e ec s on non-impo ing i ms and del e in o
he unde lying mechanisms d i ing hese esul s. We conclude he esul s sec ion by ex-
amining how sa egua d impo a i s may ha e in luenced he eme gence o new i ms in
indus ies wi h highe exposu e le els.
5.1. E ec s on Impo e s
In his sec ion, we ocus on he e ec o sa egua d impo a i s on impo e s. We see
hese esul s as he main e ec s o he policy because impo ing i ms a e he ones acing
he sa egua ds di ec ly. In his case, he ea men a iable co esponds o he measu e o
di ec exposu e de ined in equa ion (1).
5.1.1. E ec s on Impo s
The p ima y objec i e o he sa egua d impo a i s is o p o ec he balance o pay-
men s by educing impo s. We es ima e equa ion (4) using i m-le el o al impo s as he
ou come a iable. The esul s can be ound in Panel A o Table 3, which shows he e ec o
he sa egua ds on cumula i e o al impo s o he h ee yea s ha he policy was in place.
Sa egua d impo a i s we e highly e ec i e in limi ing impo s h oughou hei im-
plemen a ion. To guide he in e p e a ion, ecall om Figu e 1 ha he pe iod o sa egua d
implemen a ion was cha ac e ized by a gene al decline in impo s, wi h a deepe con ac-
ion on a ec ed p oduc s. Ou esul s show ha his e ec ound a he p oduc -le el
il e s i s way up o he i m le el: an addi ional 1% inc ease in i m-le el di ec exposu e
is associa ed wi h a 1.4% educ ion in he g ow h a e o impo s du ing 2015.
19
Changes in ou come be ween and 2014
2015 2016 2017
Panel A: Change in i m-le el impo s
Expec ed a i −1.429 ∗∗∗ −3.010 ∗∗∗ −2.649 ∗∗∗
(0.257) (0.553) (0.571)
Mean ∆z−0.081 −0.307 −0.144
Obse a ions 2891 2826 2795
Panel B: Impo s elas ici y
Expec ed a i −0.088 ∗∗∗ −0.188 ∗∗∗ −0.147 ∗∗∗
(0.021) (0.045) (0.036)
Obse a ions 2891 2826 2795
Table 3: E ec s o Sa egua ds on Impo s and Impo s Elas ici y This able shows, in Panel A,
he ela ionship be ween i m-le el ou pu exposu e o sa egua ds and he change in impo s. In Panel B, he
able p esen s he es ima e o impo s elas ici y o changes in sa egua d impo a i s. The es ima es in panel
A co espond o equa ion (4). To ob ain he es ima es o impo s elas ici y, we es ima e (4) sepa a ely o
he change in impo s and he change in paid sa egua ds. Then, we use he seemingly un ela ed eg ession
amewo k o es ima e he non-linea combina ion o he β coe icien s o bo h eg essions. In all cases,
s anda d e o s a e clus e ed a he indus y le el (ISIC 3-digi s). The es ima ions o each yea include
con ols o economic sec o (ISIC 1-digi ), i m size (CAN classi ica ion), whe he o no he i m belongs o
a business g oup (iden i ied by SRI), He indahl indexes o sales and impo s, he loga i hm o he i m-le el
capi al s ock, p o ince-le el ixed e ec s, and he i m-le el sha e o impo s and expo s o he Eu opean
Union. The a ia ion in he ou come a iable is winso ized a he bo om and op 0.5%.
To ge a be e sense o he magni ude o he e ec , no e ha he a e age i m-le el
impo con ac ion be ween 2014 and 2015 was 8%. The e o e, a 1% addi ional exposu e o
sa egua d impo a i s implies a u he educ ion o 0.1 pe cen age poin s in his g ow h
a e. This e ec mo e han doubles du ing he second yea o implemen a ion and pe sis s
du ing he hi d yea , when a 1% addi ional exposu e is associa ed wi h a 2.6% dec ease
in impo s g ow h. All hese esul s a e signi ican a he 1% le el.
Recall ha ou esul s p o ide in o ma ion on he cumula i e changes be ween he
baseline yea (2014) and each o he yea s epo ed. The la ge e ec in 2016 is consis en
wi h an addi ional ull yea o sa egua d impo a i s, while he lowe coe icien in 2017
is consis en wi h he ac ha i ms we e only pa ially exposed o sa egua ds in 2017, as
hey we e phased ou by June o ha yea .
Nex , we es ima e equa ion (4) o e ec i e paid a i s and impo s as ou comes in a
se o seemingly un ela ed eg essions, ollowing Ha asz osi and Lindne (2019). The a-
io be ween he β coe icien s o impo s and e ec i ely paid a i s ep esen s he impo
elas ici y wi h espec o ad alo em sa egua d impo a i s. We calcula e wo ypes o
elas ici y: impac elas ici y, which cap u es i ms’ esponses o he policy du ing i s i s
20
yea o implemen a ion, and sho - e m elas ici y, which accumula es he e ec s o 2016
and 2017. These pa ame e s a e ele an o policy design since hey enable he pa ame-
e iza ion o models capable o es ima ing ade policy e ec s ex an e. We p esen hese
es ima ions in Panel B o Table 3.
The elas ici y o impo s wi h espec o he sa egua d a e is −0.088 on impac . This
elas ici y eaches i s lowes poin in 2016 (−0.188) and hen inc eases o −0.147 in 2017. The
elas ici y on impac ep esen s 47% o he s onges esponse o impo s o he inc ease in
a i s.
Ou indings e eal a ange o elas ici ies ha is lowe han ecen es ima es in he li e -
a u e. Speci ically, Boehm e al. (2023) epo an impac elas ici y o −0.26 and a sho - un
elas ici y o −0.76. A key ac o d i ing hese disc epancies is likely he dis inc policy de-
signs conside ed in each analysis. Ou s is based on he escala ion in a i a es induced by
sa egua d impo a i s, which due o policy es ic ions mus be empo a y. Acco dingly,
we expec i ms’ esponse o be smalle , as hey expec he su cha ges o be sho -li ed. In
con as , Boehm e al. (2023) u ilize exogenous a ia ion esul ing om changes in mos
a o ed na ion a i s, which end o in luence ade o e mo e p olonged ime pe iods.
5.1.2. E ec s on Pe o mance
In his sec ion, we discuss he e ec s o sa egua d impo a i s on he pe o mance o
impo ing i ms. To gauge his impac , we ack annual changes in o al ac o p oduc i -
i y (TFP), sales, and he numbe o i ms du ing he policy implemen a ion pe iod (2015
o 2017), using 2014 as a e e ence poin . The esul s a e summa ized in Table 4, o e -
ing a comp ehensi e iew o how impo su cha ges in luenced he ope a ional me ics o
impo ing i ms du ing he speci ied ime ame.
Con a y o p e ious esea ch (e.g. Ami i and Konings,2007;De Loecke e al.,2016;
Topalo a and Khandelwal,2011), we ind ha inc eased ade p o ec ion is no associa ed
wi h a educ ion in he p oduc i i y g ow h o di ec ly exposed i ms. Al hough he coe i-
cien s a e consis en ly nega i e, he obse ed dec ease in p oduc i i y is ne e s a is ically
signi ican (Panel A).
Rega ding sales, ou da a e eal a clea ela ionship be ween g ea e di ec exposu e
and educed sales g ow h. Speci ically, a 1% ise in di ec exposu e is associa ed wi h a
0.27% dec ease in sales g ow h in he i s yea o policy implemen a ion. This nega i e
end becomes mo e p onounced o e he nex wo yea s, wi h sales g ow h declining by
0.55% in 2016 and 0.86% in 2017. These indings a e s a is ically signi ican a he 1% le el
(Panel B). The la ge decline in sales is he i s sign o he nega i e scale e ec associa ed
wi h inc eased ade p o ec ion (Head and Ries,1999).
21
These ou comes a e consis en wi h p o ec ionis ade policies being gene ally con-
ac iona y o di ec ly a ec ed i ms. Fo impo ing i ms, which ely hea ily on impo s
o hei ope a ions, impo su cha ges di ec ly impac hei cos s uc u e, leading o he
obse ed scale educ ion in line wi h Head and Ries (1999).
Al hough he esul s o 2020-2021 a e consis en wi h hose o p e ious yea s, i is im-
po an o no e ha hese yea s a e a ec ed by he impac o he Co id-19 pandemic. S ill,
he e is no a p io i eason o expec ha i ms ha we e mo e exposed o he sa egua ds
based on hei 2014 impo s uc u e we e also mo e a ec ed by he pandemic, p o iding
suppo o ou analysis.
5.2. E ec s on O he Fi ms
In his sec ion, we es ima e he impac o he sa egua d impo a i s on he es o
i ms, i.e., hose ha also expo in addi ion o impo ing and hose ha do no ade wi h
he es o he wo ld. We ca ego ize hese i ms in o h ee g oups based on hei in e na-
ional ade in ol emen : impo e -expo e s, local i ms in impo -compe ing indus ies,
and local i ms in non-impo -compe ing indus ies. We assess he e ec s on i e a i-
ables: To al ac o p oduc i i y (TFP), sales, employmen , labo cos s, and ma e ial cos s.
In addi ion, o impo e -expo e s, we examine he impac on expo s.
Impo e -expo e s could be in luenced by impo su cha ges in wo ways: di ec ex-
posu e due o hei impo s and indi ec exposu e h ough local supply chains. Howe e ,
we ind no signi ican impac on his g oup h ough ei he channel (see Figu e 7in he
Appendix). The absence o no able e ec s on impo e -expo e s migh be a ibu ed o
hei la ge size and in e na ional ma ke p esence, po en ially allowing hem o abso b
he addi ional cos s induced by he policy. Howe e , i is impo an o no e ha he num-
be o obse a ions wi hin his g oup o i ms is a he limi ed, ep esen ing jus 7% o ou
sample i ms (Table 1). This small p opo ion and ou come a iabili y could impac he
p ecision o he es ima ion.
Fo local i ms in impo -compe ing indus ies, we apply he concep o e ec i e p o-
ec ion. While hese i ms migh bene i om ade p o ec ion, hey could also ace highe
inpu cos s due o alue chain exposu e. We obse e no signi ican e ec s o he sa egua d
a i s on hese i ms, and ou es ima es show minimal a ia ion. This inding is impo an
because, as Jabbou e al. (2019) sugges , he g oup o i ms mos likely o bene i om
sho - e m p o ec ionism comp ises impo -compe ing i ms. The ac ha we do no ind
signi ican e ec s s ongly suppo s he idea ha he bene i s o p o ec ionism a e minimal
o non-exis en . The esul s a e de ailed in Figu e 8in he Appendix.
28
-3 -2 -1 0 1 2 3
E ec
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Poin es ima e 95% CI
(a) To al ac o p oduc i i y
-12 -10 -8 -6 -4 -2 0
E ec
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Poin es ima e 95% CI
(b) Sales
-12 -10 -8 -6 -4 -2 0 2
E ec
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Poin es ima e 95% CI
(c) Employmen
-20 -15 -10 -5 0 5
E ec
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Poin es ima e 95% CI
(d) Labo cos s
-14 -12 -10 -8 -6 -4 -2 0
E ec
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
Poin es ima e 95% CI
(e) Ma e ials
Figu e 5: Dynamic E ec s o Sa egua ds on Local Fi ms in Non-impo -compe ing In-
dus ies This igu e shows he dynamic ela ionship be ween indus y-le el inpu exposu e o sa egua ds
and he change in he ou comes o local i ms ha ope a e in non-impo -compe ing indus ies. The ou -
comes include i m-le el TFP (Panel a), sales (Panel b), employmen (Panel c), labo cos s (Panel d) and
ma e ial cos s (Panel e). In all cases, s anda d e o s a e clus e ed a he indus y le el (ISIC 3-digi s) and
all he con ol a iables om Table 3a e included. The es ima ions o each yea include con ols o eco-
nomic sec o (ISIC 1-digi ), i m size (CAN classi ica ion), whe he o no he i m belongs o a business
g oup (iden i ied by SRI), He indahl indexes o sales and impo s, he loga i hm o he i m-le el capi al
s ock, p o ince-le el ixed e ec s, and he i m-le el sha e o impo s and expo s o he Eu opean Union.
The a ia ions in he ou come a iables a e winso ized a he bo om and op 0.5%.
Las ly, we analyze he impac on local i ms in non-impo -compe ing indus ies. Mos
o hese i ms (93%) belong o wholesale & e ail indus ies. They do no impo di ec ly
bu likely pu chase impo ed goods om local impo e s o local esale wi hou o eign
compe i ion. The e o e, hese i ms do no ace ei he di ec o ou pu exposu e, bu hey
may be a ec ed h ough hei alue chain. The esul s a e shown in Figu e 5.
Sa egua d impo a i s consis en ly ha m economic ac i i y among non-impo -compe ing
i ms. F om he second yea o he policy, o al ac o p oduc i i y (TFP) begins o de-
c ease. By 2016, a 1% inc ease in inpu exposu e leads o a 0.45% d op in TFP g ow h,
signi ican a he 5% le el. This nega i e end con inues h ough 2017 (-0.48%) and 2018
(-0.71%), e en a yea a e he policy ended, in ensi ying o -0.95% in 2019, al hough wi h
less signi icance due o a iabili y among i ms.
29
Sales a e e en mo e ad e sely a ec ed. Al hough no signi ican in 2015 and 2016,
by 2017, a 1% inc ease in inpu exposu e causes a 2.49% dec ease in sales g ow h. This
nega i e impac on sales pe sis s and wo sens, eaching a 6.67% dec ease by 2021.
We ind no signi ican e ec s on o mal employmen , wi h he excep ions o 2015 and
2021. In he i s yea o policy implemen a ion, a 1% inc ease in inpu exposu e co e-
sponded o a 1.14% dec ease in o mal employmen g ow h. Al hough his nega i e e ec
pe sis ed in subsequen yea s, i was no s a is ically signi ican .
Rega ding labo cos s, no signi ican e ec was de ec ed du ing he pe iod o ac i e
sa egua d impo a i s. Howe e , a no able change occu ed be ween 2018 and 2021, wi h
labo cos s dec easing signi ican ly, especially in 2020, he yea o he pandemic, whe e
hey ell by 13.63% in esponse o a 1% inc ease in inpu exposu e.
Ma e ial cos s also dec ease om 2016 onwa d. A 1% inc ease in inpu exposu e e-
sul s in a 2.50% educ ion in he g ow h o ma e ial cos in 2016, alling o -8.07% by 2020.
These e ec s a e signi ican a he 1% le el om 2016 o 2021.
These indings e lec he b oade impac o sa egua d impo a i s on he p oduc-
ion scale o local non-impo -compe ing i ms. Ou esul s also suppo exis ing li e a u e
on p o ec ionism’s nega i e impac on p oduc i i y, especially h ough inpu exposu e in
downs eam indus ies.
Fu he mo e, ou analysis e eals ha alue chain impac s a e mo e subs an ial han
di ec indus y p o ec ion. This is in line wi h p e ious indings ha inpu a i s ha e
mo e p onounced e ec s han ou pu a i s. O e all, ou esul s show a gene al nega-
i e scale e ec , wi h sales, labo , and ma e ial cos s declining ac oss a ious i m g oups,
pa icula ly no iceable h ough inpu exposu e among local non-impo -compe ing i ms.
Con a y o some s udies, we ind no nega i e impac on expo e s’ sales o o he pe o -
mance me ics.
The null e ec on impo e -expo e s and he nega i e impac on local i ms align wi h
he con ex o he a i implemen a ion, which was a esponse o alling oil p ices and
he esul ing agg ega e demand shock. Local i ms aced educed demand, wi h exposed
i ms hi ha de , whe eas expo e s we e less a ec ed.
Con a y o expec a ions, we ind no posi i e impac on local impo -compe ing i ms,
hough hey a e be e han non-impo -compe ing i ms by no expe iencing nega i e
impac s om alue chain exposu e in labo o ma e ial cos s.
30
5.3. New Fi ms
We conclude his sec ion showing esul s on he e ec o sa egua d impo a i s on
i m en y. Since we canno see i ms ha we e willing bu did no en e he ma ke , we
ocus on he change in he sha e o new i ms in each indus y.
Fi s , we de ine new i ms as hose open be ween 2015 and 2021 bu no p esen in 2014.
Unlike p e ious sec ions, ou benchma k is composed o all i ms open in 2014 as opposed
o only hose included in he balanced panel. We hen calcula e hei sha e a each poin
in ime as a pe cen age o all ac i e i ms in hei indus y and ade s a us ca ego y.
Second, we adjus ou es ima ion app oach. The ou come a iable is he sha e o new
i ms by indus y a he ISIC 4-digi le el. We conside only ou pu and inpu exposu e,
since di ec exposu e is de ined a he i m le el. O he con ols a e indus y a e ages se
a he 2014 baseline.
Thi d, due o limi ed da a on impo e -expo e s, which causes p oblems wi h he
compu a ion o s anda d e o s (boo s apped, wi h 1,000 epe i ions), we include impo e -
expo e s in he same ca ego y as impo ing i ms. This esul s in h ee ade s a us ca e-
go ies ins ead o ou . Wi h hese adjus men s, he esul s o ou es ima ions a e p esen ed
in Figu e 6.
P o ec i e impo a i s can ha e a ying e ec s on he sha e o new i ms, depend-
ing on hei pa icipa ion in in e na ional ade. Fo impo e -expo e s, ou pu exposu e
can ac as a ba ie o en y, imposing highe a i s du ing sa egua d pe iods. In con as ,
ou pu exposu e migh o e a p o ec i e ad an age o new i ms in impo -compe ing
indus ies. Inpu exposu e, howe e , likely poses an en y ba ie o all i ms due o in-
c eased inpu cos s.
Ou es ima es o impo e -expo e s (Panels a and c in Figu e 6) indica e no signi i-
can impac o sa egua d a i s on he sha e o new i ms. Ou pu exposu e shows negli-
gible, non-signi ican , nega i e e ec s, while inpu exposu e’s e ec is i ually ze o.
Fo local i ms in impo -compe ing indus ies (Panels b and d, Figu e 6), he ex-
pec ed ends a e obse ed, al hough none o he es ima es is s a is ically signi ican . Ou -
pu exposu e, o e ing p o ec ion, yields posi i e e ec s, whe eas he aised p oduc ion
cos s om inpu exposu e lead o nega i e poin es ima es. Local i ms in non-impo -
compe ing indus ies see la ge (in absolu e alue) ye non-signi ican changes due o in-
pu cos inc eases om alue chain exposu e.
In summa y, sa egua d impo a i s do no signi ican ly a ec he sha e o new i ms
in mo e exposed indus ies, nei he as ba ie s no as p o ec i e measu es. Coupled wi h
ou indings o a posi i e exi p obabili y among impo e s (Figu e 4d), we obse e a ne
nega i e e ec o he policy on i m-le el decisions a he ex ensi e ma gin.
31
Panel A: Ou pu Exposu e
-.01 -.008-.006 -.004 -.002 0 .002 .004
E ec
2014
2015
2016
2017
2018
2019
2020
2021
Poin es ima e 95% CI
(a) Impo e -expo e s
-.004-.002 0 .002 .004 .006 .008 .01
E ec
2014
2015
2016
2017
2018
2019
2020
2021
Poin es ima e 95% CI
(b) Local, impo compe ing
Panel B: Inpu Exposu e
-.03 -.02 -.01 0 .01 .02 .03
E ec
2014
2015
2016
2017
2018
2019
2020
2021
Poin es ima e 95% CI
(c) Impo e -expo e s
-.025-.02-.015-.01 -.005 0 .005 .01 .015
E ec
2014
2015
2016
2017
2018
2019
2020
2021
Poin es ima e 95% CI
(d) Local, impo compe ing
-.25 -.2 -.15 -.1 -.05 0 .05 .1 .15
E ec
2014
2015
2016
2017
2018
2019
2020
2021
Poin es ima e 95% CI
(e) Local, non-impo comp.
Figu e 6: E ec s o Sa egua d Impo Ta i s on he Indus y Sha e o New Fi ms This ig-
u e shows he dynamic ela ionship be ween indus y-le el ou pu and inpu exposu e o sa egua ds and he
change in he sha e o new i ms in each indus y by ade s a us. The g oup o impo e -expo e s includes
impo ing and impo ing-expo ing i ms due o he small numbe o obse a ions in he second g oup. In
all cases, s anda d e o s a e boo s apped (1,000 epe i ions) and all p e ious con ols a e included a he
indus y le el (ISIC 4 digi s). The es ima ions o each yea include con ols o economic sec o (ISIC 1-
digi ), i m size (CAN classi ica ion), whe he o no he i m belongs o a business g oup (iden i ied by
SRI), He indahl indexes o sales and impo s, he loga i hm o he i m-le el capi al s ock, p o ince-le el
ixed e ec s, and he i m-le el sha e o impo s and expo s o he Eu opean Union, all agg ega ed a he
indus y le el. The a ia ions in he ou come a iables a e winso ized a he bo om and op 0.5%.
6. Conclusion
In his pape , we analyzed he i m-le el e ec s o sa egua d impo a i s imple-
men ed by he Ecuado ian Go e nmen in esponse o a balance o paymen s c isis spa ked
by a sha p d op in oil p ices a he end o 2014. The policy is pa icula ly ins uc i e due o
i s use o a i s a he han non- a i ba ie s, i s empo a y and la gely un o eseen na u e,
and i s impac on a wide ange o goods, bo h inal and in e media e.
We employed a quan i a i e app oach, aking ad an age o he he e ogeneous p e-
policy exposu e o i ms and indus ies. We analyzed di ec exposu e o impo ing i ms,
and ou pu and inpu exposu e a he indus y le el, in line wi h he li e a u e on e ec i e
p o ec ion. Using his amewo k, we conduc ed a di e ence-in-di e ence analysis a bo h
i m and indus y le els.
32
Fo impo ing i ms di ec ly a ec ed by he sa egua d a i s, we s udied he e ec s on
impo s and calcula ed he a i elas ici y o impo s, a c ucial me ic o policy e alua ion.
Ou indings indica e ha despi e lowe sho - e m elas ici ies compa ed o o he s udies,
he a i s signi ican ly cu bed impo s.
We also assessed he impac o he policy on pe o mance me ics such as p oduc-
i i y (TFP), sales, and exi p obabili y o a ec ed i ms. The esul s showed signi ican ,
pe sis en , nega i e impac s on sales and an inc easing likelihood o i m exi pos -policy,
hough no immedia e e ec s we e obse ed du ing he policy pe iod.
Analyzing he unde lying mechanisms, we obse ed signi ican , sus ained nega i e
impac s on employmen and ma e ial cos s g ow h a es, wi h no no able e ec s on labo
cos s, possibly due o he speci ici ies o he Ecuado ian labo ma ke .
We ex ended ou analysis o o he i m ca ego ies, including impo e -expo e s, local
i ms in impo -compe ing, and non-impo -compe ing indus ies. The mos ad e sely
a ec ed i ms we e he local non-impo -compe ing i ms, expe iencing nega i e, las ing
e ec s on p oduc i i y, sales, labo , and ma e ial cos s. Fo o he i ms, he policy did no
ha e signi ican e ec s on hese pa ame e s.
Ou esea ch o e s c ucial insigh s o policymake s. Speci ically, i sheds ligh on
how ade policy impac s p oduc ion scale. We ound ha p o ec i e ade measu es o -
en esul in a signi ican dec ease in p oduc ion scale and a co esponding d op in inpu
demand. These measu es end o ha e a ecessiona y e ec , e en in economies wi hou
ac i e exchange a e policy. This highligh s he need o de eloping coun ies o ocus on
enhancing compe i i eness. Policies aimed a acili a ing access o in e na ional ma ke s
and encou aging g ow h by exposing local businesses o o eign compe i ion a e essen ial.
33
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