Shi e aw, Admasu; Hailu, Degol
A icle
Job c ea ion and ade in manu ac u es: Indus y-le el
analysis ac oss coun ies
IZA Jou nal o Labo & De elopmen
P o ided in Coope a ion wi h:
IZA – Ins i u e o Labo Economics
Sugges ed Ci a ion: Shi e aw, Admasu; Hailu, Degol (2016) : Job c ea ion and ade in manu ac u es:
Indus y-le el analysis ac oss coun ies, IZA Jou nal o Labo & De elopmen , ISSN 2193-9020,
Sp inge , Heidelbe g, Vol. 5, Iss. 3, pp. 1-36,
h ps://doi.o g/10.1186/s40175-016-0052-z
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ORIGINAL ARTICLE Open Access
Job c ea ion and ade in manu ac u es:
indus y-le el analysis ac oss coun ies
Admasu Shi e aw
1*
and Degol Hailu
2
* Co espondence: ashi e aw@wm.
edu
1
The College o William and Ma y
Williamsbu g, Vi ginia, USA
Full lis o au ho in o ma ion is
a ailable a he end o he a icle
Abs ac
This pape examines indus y-le el esponses o manu ac u ing employmen in he
con ex o globaliza ion using a la ge sample o de eloped, de eloping, and
ansi ion economies. We ind ha de eloping coun ies need a ypically high a es o
alue-added g ow h (abou 10 %) o inc ease manu ac u ing employmen
app eciably (abou 4 %). The employmen bene i s o expo o ien a ion a e also
modes e en in “compa a i e ad an age”indus ies o de eloping coun ies.
Howe e , di e si ying he expo baske con ibu es signi ican ly o employmen
g ow h, pa icula ly in he medium- and high- echnology indus ies. Impo
compe i ion does no unde mine employmen g ow h in low- echnology indus ies
o de eloping coun ies while i displaces jobs in he same indus ies in O ganisa ion
o Economic Co-ope a ion and De elopmen (OECD) and ansi ion economies. Fo
de eloping coun ies, impo -induced job losses a e highe in he mo e capi al-
in ensi e medium- echnology indus ies. Jobs in high- echnology indus ies a e less
sensi i e o impo s wi h posi i e ela ionships obse ed in he OECD. In es men
also complemen s job c ea ion in low- echnology indus ies o de eloping coun ies
ha ha e ye o indus ialize.
JEL codes: J21, L60, O14, O25
Keywo ds: Labo demand, Employmen elas ici y, Manu ac u ing, Expo o ien a ion,
Impo compe i ion
1 In oduc ion
Economic de elopmen and po e y educ ion in de eloping coun ies depend c i ically
on access o gain ul job oppo uni ies. The Wo ld Bank’s2013Wo ld De elopmen Re-
po highligh ed he b oade socioeconomic signi icance o jobs ha anscend he p i a e
e u ns o employmen (Wo ld Bank 2012). Employmen in o mal sec o manu ac u ing,
he ocus o his pape , ecei es special a en ion om policymake s and esea che s
pa ly because i p o ides ela i ely s able and be e paying jobs. Such desi able a i-
bu es o jobs dese e emphasis as he bulk o employmen oppo uni ies in de eloping
coun ies a e c ea ed by small i ms in he un egis e ed sec o whe e ea nings a e ypic-
ally uns eady and job- ela ed bene i s a e nonexis en (Wo ld Bank 2012; Goldbe g and
Pa cnik 2003).
While a numbe o s udies unde sco e he c i ical ole o indus ial p og ess and di e -
si ica ion o economic g ow h (Hausmann e al. 2007; Jones and Olken 2005; Imbs and
Waczia g 2003), he labo ma ke implica ions o indus ializa ion and di e si ica ion a e
© 2016 Shi e aw and Hailu. Open Access This a icle is dis ibu ed unde he e ms o he C ea i e Commons A ibu ion 4.0
In e na ional License (h p://c ea i ecommons.o g/licenses/by/4.0/), which pe mi s un es ic ed use, dis ibu ion, and ep oduc ion in
any medium, p o ided you gi e app op ia e c edi o he o iginal au ho (s) and he sou ce, p o ide a link o he C ea i e Commons
license, and indica e i changes we e made.
Shi e aw and Hailu IZA Jou nal o Labo &
De elopmen (2016) 5:3
DOI 10.1186/s40175-016-0052-z
no en i ely clea pa ly because such p ocesses a e aking place in he con ex o inc eas-
ingly globalized economies. Unce ain y abou employmen p ospec s also a ises om e-
cen episodes o “job-less”economic g ow h expe ienced by bo h de eloped and
de eloping coun ies a leas in he sho o medium uns (Caballe o and Hammou 1997;
Kapsos 2005). In ac , many de eloping coun ies g apple wi h pe sis en ly high un-
employmen a es, especially in u ban a eas, in spi e o mo e open and g owing econ-
omies. O e coming cons ain s o economic g ow h and expo s he e o e does no seem
o gua an ee sa is ac o y labo ma ke ou comes. A ecen e iew o empi ical s udies
om semi-indus ialized de eloping coun ies by Goldbe g and Pa cnik (2007) shows ha
ade libe aliza ion has been accompanied by ising wage inequali y con a y o he ex-
pec a ion o mo e a o able ou comes o low-skilled wo ke s. E idence is s ill lacking on
he mo e p essing issue o unemploymen and global in eg a ion pa icula ly in de elop-
ing coun ies. The limi ed empi ical li e a u e coming mainly om de eloped coun ies
p o ides a mixed pic u e on he employmen e ec s o ade libe aliza ion as discussed
la e in his pape .
Labo economis s asse ha s ic labo ma ke egula ions a e among he main cul-
p i s o slow employmen g ow h (Bo e o e al. 2004; Hal iwange e al. 2008). The as-
sump ion is ha employe s espond o es ic i e hi ing and i ing egula ions wi h
lacklus e job c ea ion, in es ing ins ead on p oduc i i y enhancing ac i i ies (Caballe o
and Hammou 1997). Howe e , F eeman (2010) and Wo ld Bank (2012) epo only mod-
es , i any, impac s o labo ma ke egula ions in de eloping coun ies pa ly because o
weak en o cemen o egula ions.
1
Concu en wi h ade libe aliza ion, mos de eloping
coun ies ha e also been elaxing labo laws du ing he 1990s (Goldbe g and Pa cnik
2007) u he a enua ing he po en ial explana o y powe o labo ma ke ins i u ions.
O e he las decade o so, economis s began o explo e i m he e ogenei y in size,
p oduc i i y, and expo o ien a ion o be e unde s and he mechanisms h ough which
ade openness may a ec labo ma ke ou comes. Mo e ecen ade heo ies ex end he
Mel i z (2003) model wi h he e ogeneous i ms by in oducing labo ma ke impe ec ions
a ising no as such om hi ing and i ing egula ions bu om sea ch ic ions, e iciency
wages, o i m-speci ic wage ba gaining. Leading con ibu ions in his ega d include
Egge and K eickemeie (2009), Helpman e al. (2010), Felbe may e al. (2011a), and
Da is and Ha igan (2011). These new models highligh he condi ions unde which ade
openness could inc ease wage inequali y and he unemploymen a e. This ma ks a sig-
ni ican imp o emen o e compa a i e ad an age and in a-indus y ade models whose
implica ions o en do no ma ch obse ed labo ma ke ou comes.
While he abo emen ioned heo e ical con ibu ions inspi e he empi ical analysis in
his pape , some o hei es ic i e ea u es need o be add essed. Fo ins ance, po en ial
di e ences in he labo ma ke e ec s o ade o de eloped and de eloping coun ies a e
o en igno ed mainly because o he ocus on in a-indus y ade among coun ies wi h
simila economic s uc u es.
2
Simila ly, a ia ion in indus y-le el esponses o ade e-
o ms canno be in e ed di ec ly om he la es ade models gi en hei emphasis on
equilib ium unemploymen a e and wage inequali y. Howe e , he con o e sies su -
ounding ade libe aliza ion a ise p ima ily om di e gences in economic s uc u e and
pa e ns o specializa ion ac oss coun ies. The empi ical app oach in his pape he e o e
add esses such di e ences by using indus y-le el analysis o employmen o coun ies
wi h dissimila economic s uc u es. As compa ed o he la ge empi ical li e a u e on he
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 2 o 36
p oduc i i y and wage inequali y e ec s o globaliza ion, s udies ha add ess i s employ-
men e ec s a e a e and di e ema kably on a numbe o dimensions. These include di -
e ences in esponse a iables, le els o agg ega ion, measu es o ade openness, and da a
sou ces and quali y, which complica e meaning ul compa ison o he exis ing e idence
and he lessons o be d awn.
This pape con ibu es o his li e a u e by es ima ing a labo demand model o a la ge
sample o de eloping, ansi ion, and de eloped coun ies obse ed o e he pe iod 1990–
2009. The model examines indus y-le el esponses o manu ac u ing employmen o
changes in ma ke demand, ac o p ices, and ade openness as well as in es men and
expo baske di e si ica ion. We use ou -digi In e na ional S anda d Indus ial Classi i-
ca ion (ISIC) indus ies ha a e ma ched wi h ade lows om 72 coun ies. The analysis
allows model pa ame e s o a y ac oss egional labo ma ke s and indus y ca ego ies a
di e en le el o echnological ad ancemen . We also use coun y- and indus y-speci ic
ins umen al a iables o add ess endogenei y p oblems ha o en unde mine es ima ion
o labo demand models.
As a p e iew o ou esul s, we ind a nega i e wage elas ici y o labo demand ha
ends o decline in indus ies wi h ela i ely high labo sha e o ou pu . G ow h in de-
mand inc eases manu ac u ing employmen al hough he elas ici y is a less p opo ion-
a e such ha de eloping coun ies may need o achie e a ypically high a es o alue-
added g ow h (abou 10 %) o inc ease employmen by abou 4 %. While demand and
own-p ice elas ici ies o labo demand a e ema kably simila ac oss all coun ies and in-
dus ies, sys ema ic egional di e ences eme ge in he labo ma ke implica ions o ade
openness. The employmen esponse o ade openness also depends c ucially on he
echnological composi ion o indus ies. Expo o ien a ion has a bes modes employ-
men bene i s e en in “compa a i e-ad an age”indus ies o de eloping coun ies, while i
ends o slowdown job des uc ion in low- echnology indus ies o O ganisa ion o Eco-
nomic Co-ope a ion and De elopmen (OECD) coun ies. Howe e , we did no ind em-
ploymen educing e ec s o expo s as implied by ecen ade heo ies. Impo
pene a ion does no educe employmen g ow h in low- echnology indus ies o de elop-
ing coun ies while i leads o subs an ial job displacemen in he same indus ies in he
OECD. Fo de eloping coun ies, impo -induced job losses a e ela i ely high in he
mo e capi al-in ensi e medium- echnology indus ies. Di e si ica ion o he expo baske
boos s job c ea ion pa icula ly in skill-in ensi e indus ies o bo h de eloped and de el-
oping coun ies. Fo coun ies ha ha e ye o indus ialize and become accomplished ex-
po e s o manu ac u es, in es men has a s ong complemen a y e ec on employmen .
The es o he pape is o ganized as ollows: Sec ion 2 ou lines he heo e ical pe spec-
i es ha inspi e ou labo demand model and p o ides a e iew o exis ing empi ical e i-
dence. Sec ion 3 discusses he da ase s and desc ibes he dis ibu ion o key a iables as
well as he indus ial composi ion o employmen and ade. Es ima ion issues and ins u-
men s a e add essed in Sec ion 4 while Sec ion 5 discusses he esul s. Sec ion 6 p o ides
es ima es o an ex ended labo demand model while Sec ion 7 concludes he pape wi h
some policy implica ions.
2 Theo e ical amewo k
We d aw bo h on heo ies o labo demand and in e na ional ade o assess manu ac-
u ing employmen in he con ex o globaliza ion.
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 3 o 36
2.1 De i ed demand o labo
Following Hame mesh (1993), he own-p ice elas ici y o labo demand holding ou pu
cons an can be exp essed as:
ηLL ¼∂lnL
∂lnw¼−1−SL
½σð1Þ
whe e Lis labo and wis wage a e, σis he elas ici y o subs i u ion be ween labo and
o he inpu s, and S
L
is he e enue sha e o labo . Since wage shocks a ec p oduc p ices,
he esul ing adjus men in he scale o p oduc ion will also a ec labo demand. Hame -
mesh (1993) shows his e ec o depend on he p ice elas ici y o consume demand η.
The e o e, he o al own-p ice elas ici y o labo demand can be exp essed as:
ηLL ¼−1−SL
½σ−SLηð2Þ
Equa ion (2) shows a nega i e wage elas ici y o labo demand wi h wo componen s:
he “subs i u ion e ec ” ep esen ed by [1−S
L
]σand he “scale e ec ” ep esen ed by S
L
η
(Slaugh e 2001). In an indus y wi h low labo sha e, wage spikes a ec labo demand
p ima ily h ough he ac o subs i u ion e ec while he scale e ec domina es in indus-
ies wi h ela i ely high labo sha e.
Ou basic labo demand unc ion, ollowing Hame mesh’s log-linea speci ica ion can
hus be exp essed as:
ln Lj

¼δþβln Vj

þαln wj

þεj ð3Þ
whe e Ls ands o uni s o labo , Vis alue added, wis wage a e, jindexes indus y,
and indexes ime.
In assessing he e ec o ade openness on labo demand, Rod ik (1997) a gues ha
impo s no only push he p ice index down bu also aise he p ice elas ici y o demand
(η) as access o a wide a ie y o consume goods inc eases. The own-p ice elas ici y o
labo demand will hus inc ease in impo compe ing indus ies. He also unde sco es ha
be e access o impo ed in e media e inpu s and pa s may gi e domes ic i ms u he
lexibili y in o ganizing p oduc ion which implies an inc ease in σand hus highe wage
elas ici y o labo demand ollowing a educ ion in impo es ic ions. Slaugh e (2001)
p o ides u he de ails on hese mechanisms.
To be e unde s and he ne e ec in a gi en indus y wi h a known labo sha e, Eq. (2)
can be ea anged as: η
LL
=−σ−S
L
(η−σ). The e o e, in indus ies whe e η>σ, heown-
p ice elas ici y o labo demand inc eases wi h S
L
. Since he p ice elas ici y o p oduc de-
mand is equi alen o he elas ici y o subs i u ions be ween inal goods (Slaugh e 2001), an
inc ease in η
LL
wi h he labo sha e o ou pu implies ha consume s’elas ici y o subs i u-
ion be ween p oduc s is g ea e han i ms’elas ici y o subs i u ion be ween inpu s. T ade
libe aliza ion can in ensi y his by inc easing consume s’choices mo e han he inpu
choices o domes ic i ms. Howe e , i consume demand is ela i ely p ice inelas ic and
impo s p ima ily inc eases σ, hen he o al p ice elas ici y o labo demand will be lowe
o indus ies wi h ela i ely high labo sha e.
2.2 T ade heo ies and labo demand
Recen ade heo ies wi h he e ogeneous i ms highligh labo ma ke e ec s o ade
openness o he han h ough g ea e own-p ice elas ici y o labo demand. The basis o
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 4 o 36

his a gumen is he ecogni ion ha i ms pa icipa ing in expo ma ke s a e ypically
la ge and mo e e icien han i ms p oducing only o domes ic ma ke s (Be na d e al.
2003; Be na d and Jensen 1999). Fo malizing hese obse a ions, he Meli z (2003) ade
model shows ha he selec ion o expo e s om he uppe end o he i m size and p od-
uc i i y dis ibu ions in ensi ies he ealloca ion o jobs owa d mo e p oduc i e i ms.
Such job chu ning, howe e , lea es equilib ium wages and unemploymen in ac because
o he assump ion o pe ec ly compe i i e labo ma ke s in he Meli z (2003) model. The
inno a ion o ecen ade heo ies is hus o in oduce labo ma ke impe ec ion in
Meli z- ype models o assess ade- ela ed wage inequali y and unemploymen .
Helpman e al. (2010) p opose a ade model wi h he e ogeneous i ms and sea ch ic-
ions. Fi ms in his model sc een wo ke s o hei abili ies and la ge i ms ha e economies
o scale in sc eening allowing hem o hi e wo ke s wi h abo e a e age abili ies. Opening
ade inc eases p o i s o la ge i ms en e ing expo ma ke s and aises hei incen i e o
sc een wo ke s e e mo e s ic ly. Since wo ke s wi h supe io abili ies a e di icul o e-
place, wages in expo i ms will be highe on a e age as compa ed o wages in non-
expo ing i ms who sc een less, hence inc easing wage inequali y a e ade libe aliza ion.
S ic e sc eening o wo ke s in he Helpman e al. (2010) model also educes he hi ing a e
among expo i ms, which can inc ease he equilib ium unemploymen a e i he acancy-
o-unemploymen a io is low.
Felbe may e al. (2011a) p opose a simila model wi h sea ch ic ions whe e ade e-
duces he unemploymen a e as long as i leads o a e age p oduc i i y g ow h. These au-
ho s a gue ha he alue o a new job o an employe inc eases wi h a e age i m
p oduc i i y (hence inc easing he job c ea ion a e), bu p oduc i i y g ow h equi es a e-
duc ion in a iable ade cos s o an inc ease in he numbe o ading pa ne s.
3
A ade model by Egge and K eckmei e (2009) elies on wo ke s’p e e ence o a “ ai ”
wage, which is ied o i m pe o mance. T ade openness unde his assump ion leads o
wage inequali y as wages ise signi ican ly in highly p oduc i e i ms ha en e in o expo
ma ke s. Non-expo i ms ace s i compe i ion om impo ed inal goods while expe i-
encing p essu e o keep up wi h high wages in expo i ms. Unemploymen in he Egge
and K eckmei e (2009) model inc eases because he combined e ec educes p o i ma -
gins o non-expo i ms o cing hem o ei he cu jobs o exi he ma ke . Da is and
Ha inga (2011) add an e iciency wage a gumen o a Meli z- ype model whe e la ge
i ms pay highe han he ma ke -clea ing wage o elici e o om hei wo ke s as i is
pa icula ly ha de o moni o e o in la ge i ms. While Da is and Ha inga (2011) p e-
dic a ise in unemploymen a e ollowing ade openness, i is expec ed o be mode a e
as compa ed o he olume o job ealloca ion ac oss i ms.
O e all, he abo emen ioned ade models wi h impe ec labo ma ke s sugges ha
ee ade could ha e undesi able consequences in e ms o inequali y and/o unemploy-
men despi e clea wel a e bene i s. These p edic ions a e qui e di e en om bo h he
adi ional Hecksche -Ohlin-Samuelson model and he in a-indus y ade models, and
hey seem o be mo e consis en wi h ac ual da a and public opinion on ade. In he
compa a i e ad an age ade models, o ins ance, ade openness would lead o in e -
indus y ealloca ion o labo ( om impo compe ing indus ies o expo o ien ed ones)
and educes unemploymen in a labo -abundan coun y. In he in a-indus y ade
models, coun ies wi h simila endowmen s can gain om ade wi hou job ealloca ion
ac oss i ms, as hey assume no i m he e ogenei y.
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 5 o 36
The p eceding discussion sugges s ha a labo demand model needs o accoun o ex-
po o ien a ion and impo compe i ion. An inc ease in he e enue sha e o expo i ms
could educe employmen g ow h as in he Helpman e al. (2010) and Da is and Ha inga
(2011) models, o i may lead o employmen g ow h as in Felbe may e al. (2011a). Since
he isk o i m exi declines wi h i m size and p oduc i i y (Be na d and Jensen 1999),
one would also expec jobs in expo e i ms o be ela i ely mo e s able. I is he e o e
possible ha as an indus y ge s inc easingly expo o ien ed, employmen becomes mo e
secu e while job c ea ion a es may slowdown. Al hough ade heo ies wi h he e oge-
neous i ms ypically assume i m p oduc i i y o be a andom d aw om a Pa e o dis i-
bu ion, in p ac ice, expo e i ms would engage in long- e m p oduc i i y enhancing
ac i i ies such as inno a ion, aining o wo ke s, and in es men in he la es machine y
and equipmen —in e en ions ha a e mo e equen among la ge i ms (Re enga 1997).
The esul ing p oduc i i y gains, including hose om lea ning- h ough-expo ing, may
allow expo e s o inc ease ou pu wi h limi ed job c ea ion. The e ec on ne employ-
men hus becomes an empi ical ques ion.
Impo compe i ion, apa om educing wo ke s’ba gaining powe (Rod ik 1997), may
lead o job des uc ion as in Egge and K eckmeie (2009). Howe e , he employmen e -
ec a guably a ies ac oss indus ies wi hin a coun y depending on sou ces o compe i-
i eness. I access o in e media e inpu s is a majo cons ain o domes ic i ms,
educing impo es ic ions may inc ease a e age p oduc i i y. Compe i i e p essu e
could also lead o p oduc i i y g ow h by educing ei he x-ine iciency o i m/wo ke
en s (Re enga 1992). P oduc i i y g ow h may hus allow domes ic i ms o compe e e -
ec i ely wi h impo s and a oid apid job des uc ion. Simila o he e ec s o expo s on
labo demand, he ac ual employmen esponse o impo compe i ion is ul ima ely an
empi ical ques ion.
The labo demand model wi h expo o ien a ion and impo pene a ion a he in-
dus y le el can be exp essed as:
ln Lj

¼δþβln Vj

þαln wj

þϕX
Y

j
þφM
MþY

j
þεj ð4Þ
whe e Xs ands o expo s, Yis ou pu , and Mis impo s.
A de ailed discussion o es ima ion issues will be picked up in Sec ion 4, while we now
u n o a e iew o ela ed empi ical s udies.
2.3 Exis ing empi ical e idence
The mul iplici y o new ade models wi h di e en assump ions and labo ma ke impli-
ca ions sugges s ha he unemploymen e ec s o ade need o be assessed empi ically.
The empi ical li e a u e unsu p isingly shows mixed esul s. Fo a sample o indus ialized
coun ies in he OECD, Felbe may e al. (2011b) ind ha ade openness, measu ed as
he ade sha e o GDP, educes he long- un unemploymen a e signi ican ly. Using a
la ge sample o de eloped and de eloping coun ies, Du e al. (2009) also ind ha ade
libe aliza ion educes he na ional unemploymen a e in he long un al hough un-
employmen may inc ease in he sho un. While hese pape s assess na ional unemploy-
men a es, hey say e y li le abou indus y-speci ic e ec s, which can be impo an
gi en he ac oss-coun y di e ences in indus y s uc u e.
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 6 o 36
S udies ha examine indus y-le el employmen and ade o en use da a om a single
coun y and p o ide in e es ing esul s. Ea lie s udies by G eenaway e al. (1999) o he
UK, Re enga (1992) and Sachs e al. (1994) o he USA, and Re enga (1997) o Mexico all
ind employmen educing e ec s o ade openness.
4
Mo e ecen ly, Au o e al. (2013) ind
ha impo compe i ion om China has a signi ican nega i e e ec on local labo ma ke s
in he USA. Dau h e al. (2014) ind ha impo s om China and Eas Eu ope ha e a mild
ad e se employmen e ec on employmen while he ne employmen e ec o ade expos-
u e is posi i e because o s ong Ge man expo s o hese coun ies. Hasan e al. (2007) in-
es iga e he e ec s o India’s 1991 ade e o m on indus y-le el labo demand. They ind
signi ican pos - e o m inc eases in he own-p ice elas ici y o labo demand, which end o
be highe o Indian s a es wi h lexible labo ma ke s. Howe e , he coe icien s on indica-
o s o ade policy shi s a e by and la ge insigni ican . Also, using indus y- and s a e-le el
da a om India, Hasan e al. (2012) ind ha ade p o ec ion inc eases unemploymen in
s a es wi h lexible labo ma ke s pa icula ly in u ban a eas wi h expo -o ien ed indus ies.
The e idence om La in Ame ican coun ies is no as encou aging. Acco ding o
A anasio e al. (2004), ade libe aliza ion in Colombia du ing he la e 1980s and ea ly
1990s signi ican ly inc eased wage inequali y and he likelihood o in o mal sec o em-
ploymen whe e wages and bene i s a e minimal. The a gumen is ha o mal sec o i ms
exposed o inc eased impo compe i ion cu pe manen employmen posi ions and ou -
sou ce some ac i i ies o low-wage wo ke s in he in o mal sec o . In B azil, Menezes-
Filho and Muendle (2011) ind la ge ansi ions o wo ke s ou o he labo o ce and in o
unemploymen ollowing ade libe aliza ion. The au ho s a gue ha ealloca ion o labo
o expo e s and compa a i e-ad an age sec o s is no enough o accommoda e impo -
induced job displacemen s om he o mal sec o . Bo h A anasio e al. (2004) and
Menezes-Filho and Muendle (2011) use household su eys o ma ch wo ke s wi h hei
indus ial a ilia ion, and i will be in e es ing o examine he e idence based on ac ual
indus y-le el da a as we do la e in his pape . The e is now a la ge li e a u e on he
p oduc i i y e ec s o ade libe aliza ion in de eloping coun ies.
5
S udies on A ican coun ies a e a he sca ce and ocus on Sou h A ica. Using
indus y-le el da a, Jenkins (2008) shows ha bo h impo s and expo s ha e nega i e e -
ec s on labo demand in Sou h A ican manu ac u ing while Johnson and Sub amanian
(2001) show ha a i educ ions inc ease p oduc i i y g ow h. Fi m-le el e idence by
Söde bom and Teal (2000) show ha expo e i ms in A ica a e la ge , mo e p oduc i e,
and capi al in ensi e on a e age han i ms supplying only o domes ic ma ke s.
The empi ical e idence on unemploymen e ec s o ade libe aliza ion is hus qui e
mixed al hough he weigh o e idence leans sligh ly owa d he unemploymen inc easing
e ec . Such mixed esul s a e unsu p ising gi en he wide a ia ion ac oss s udies in
e ms o dependen a iables, indica o s o ade openness, model speci ica ion, es ima-
ion me hods, and ime ho izon. Some s udies use na ional unemploymen a es while
o he use s a e- and indus y-le el da a. T ade measu es also include indices o ade ol-
ume as well as ac ual ade policy changes. How much o he dispa i y in he exis ing em-
pi ical e idence e lec s di e ences in da a and me hodologies is qui e unknown. One o
he con ibu ions o his pape is hus o p o ide a consis en se o empi ical e idence on
he employmen - ade ela ionship using he same da a sou ces, le el o disagg ega ion,
model speci ica ion, and es ima ion me hod o a la ge sample o de eloping, ansi ion,
and de eloped coun ies o e a compa able ime ho izon. The analysis also akes in o
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 7 o 36
accoun po en ial di e ences in he employmen esponse o ade openness based on he
echnological ad ancemen o manu ac u ing indus ies. This app oach allows a be e
compa ison o pe o mances ac oss coun ies while add essing di e ences in indus y
s uc u e and deg ee o ade in eg a ion.
3 Da a and desc ip i e s a is ics
3.1 Da a
The pape combines wo da ase s on manu ac u ing indus ies. The i s one is UNIDO’s
Indus ial S a is ics da abase (INDSTAT4) ha p o ides disagg ega ed da a on indus ial
ac i i ies a he ou -digi ISIC le el. INDSTAT4 epo s, among o he a iables, he num-
be o wo ke s (L) and cu en US dolla alues o o al ou pu (Y), alue added (V), he
wage bill (W), and in es men (I) in an indus y. The o he da a sou ce is he Uni ed
Na ions Commodi y T ade da abase (COMTRADE), which p o ides highly disagg ega ed
da a on expo s (X) and impo s (M) a he le el o six-digi Ha monized Sys em ade
classi ica ion codes (HS codes). The ade da a is es ic ed o manu ac u ing indus ies.
The wo da ase s a e combined a he ou -digi ISIC le el using a conco dance p o ided
by he UN s a is ics di ision.
The esponse a iable o in e es , ln(L
ij
), is he loga i hm o o al numbe o wo ke s in
coun y iand indus y ja ime . The wage a e (w)inanindus y ep esen s hea e age
wage pe wo ke ob ained by di iding he o al wage bill by he o al numbe o wo ke s.
Pa ial labo p oduc i i y ( ) is calcula ed as alue added pe wo ke in a ou -digi ISIC
indus y. Cons an p ice alues o ou pu , alue added, and wages a e calcula ed using
p oduce p ice indices (PPI) o wo-digi ISIC indus ies om INDSTAT2 da abase. This
da abase p o ides indus y-le el indices o olume o ou pu om which we we e able o
eco e he unde lying p oduce p ice index. Fo indus ies wi h missing alues o PPI, we
use he manu ac u ing sec o PPI.
The expo sha e o ou pu (X/Y) and impo pene a ion a es [M/(M+Y)] a e calcu-
la ed by using ade da a om COMTRADE and o al ou pu om INDSTAT4. The
numbe o expo i ems (HS) e e s o he numbe o six-digi p oduc s in a ou -digi
ISIC indus y o which a coun y has nonze o expo s. The numbe o compe ing coun-
ies (CX) is he numbe o expo ing coun ies a ound he wo ld; o each HS code, a
coun y is an ac i e expo e .
We ha e da a on he abo emen ioned a iables o 72 coun ies: eigh om Sub-
Saha an A ica (SSA), 11 om Asia and he Paci ic (ASIA), en om La in Ame ican and
he Ca ibbean (LAC), eigh om Middle Eas and No h A ica (MENA), 16 om Cen al
and Eas Eu ope (CEE), and 19 om he OECD. The sample pe iod ex ends om 1990 o
2009 wi h unbalanced panel a he indus y le el. See Appendix C o he lis o coun ies.
3.2 G ow h a es
Table 1 p o ides summa y s a is ics on manu ac u ing ou pu and employmen by egion.
Real manu ac u ing alue added g ew a abou 3 % pe annum du ing 1990–2008
6
o he
en i e sample wi h g ow h a es in de eloping coun ies exceeding ha o OECD
coun ies.
A abou 3 % pe annum, SSA and MENA a e he only egions wi h ela i ely s ong
employmen g ow h du ing he sample pe iod. To pu g ow h a es in pe spec i e, i
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 8 o 36
cha ac e is ics ha a e indus y speci ic and ime in a ian . This es ima o will also ad-
d ess he in luence o coun y ixed e ec s. The ime ixed e ec s will cap u e a ia ions
o e ime in in e es a es and o he mac oeconomic shocks ha a e common o all in-
dus ies. Since sample coun ies a e a di e en s ages o indus ializa ion and success in
one indus y could ha e spillo e e ec s on ela ed indus ies, i is un ealis ic o assume
independence o ε
ij
ac oss indus ies wi hin a coun y. Robus s anda d e o s will hus
be used h oughou he analysis.
Despi e hese sa egua ds, he panel ixed e ec s model is unlikely o add ess all he
endogenei y p oblems sa is ac o ily. Job losses in speci ic manu ac u ing indus ies may
igge selec i e ade p o ec ion measu es ha educe impo s, while inc eased emale
labo o ce pa icipa ion and/o mig a ion may uel expo compe i i eness. The e o e, we
use ins umen al a iables o accoun o p oblems o e e se causa ion and ime a ying
un-obse ables and ob ain exogenous a ia ion in impo pene a ion a e and expo
o ien a ion as well as eal wages and eal alue added.
The ins umen s we cons uc a e coun y and indus y speci ic and a y o e ime. One
o ou ins umen s o impo pene a ion a e is a weigh ed a e age exchange a e index o
majo impo supplie coun ies o a pa icula indus y o a gi en coun y. Since he US
Dolla is he cu ency o choice o mos in e na ional ansac ion, we use US Dolla ex-
change a es o impo pa ne coun ies. Exchange a e indices om he IMF Financial S a-
is ics da abase a e weigh ed by he sou ce coun y’s sha e in o al impo s o a coun y in a
gi en indus y using ade lows om he COMTRADE da abase. We also cons uc an
a e age implici GDP de la o o impo supplie coun ies weigh ed in a simila ashion as
an addi ional ins umen o impo pene a ion a e. The assump ion is ha exchange a es
and p ice indices o key impo supplie coun ies a e exogenous o economic condi ions in
a speci ic indus y o he impo ing coun y while a ec ing impo cos s.
The ins umen s o impo pene a ion a e can be exp essed as:
EXIij ¼X
k
Mijk
X
k
Mijk
0
B
B
@
1
C
C
A
EXUS
k ð6Þ
PPIij ¼X
k
Mijk
X
k
Mijk
0
B
B
@
1
C
C
A
PPIk ð7Þ
whe e EXI
ij
is a weigh ed a e age exchange a e index o impo supplie coun ies, M
ijk
ep esen s impo by coun y i om supplie coun y kin indus y ja ime ,andEX
US
k is
US Dolla exchange a es o impo supplie coun ies. PPI
k
ep esen s implici GDP de-
la o s o sou ce coun ies as a p oxy o hei p oduce p ice indices while PPI
ij
is a
weigh ed a e age indus y-speci ic index o impo sou ce coun ies.
In cons uc ing he ins umen s o impo pene a ion, we allow he composi ion o pa -
ne coun ies o a y ac oss indus ies and o e ime, which oge he wi h he annual da a
on exchange a es and GDP de la o s p o ide us wi h indus y-speci ic ins umen s o each
samplecoun y.Weusea2.5%impo sha easacu o poin ode e mine hese o im-
po pa ne coun ies. The selec ed sou ce coun ies accoun on a e age o 89 % o
indus y-le el impo s in ou sample. As muchasda aallow,we ake h eeda apoin seach
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 15 o 36

o he 1990s and 2000s o allow changes in he composi ion o impo sou ce coun ies. In
a ew cases, da a limi a ions es ic us o only wo se s o pa ne coun ies, i.e., one se o
he 1990s and ano he se o he 2000s.
Ou ins umen s o impo compe i ion di e om ha o Au o e al. (2013) whe e
hey used impo s by o he de eloped coun y om China o ins umen US impo s
om China. Dau h e al. (2014) ollow a simila app oach o Ge many. Unlike hese
au ho s, we examine he employmen impac o impo in ensi y in gene al a he han
ocusing on compe i ion om eme ging economies—China in he case o he US and
China and Eas Eu ope in he case o Ge many. Ou app oach measu es he changes in
impo supplie coun ies di ec ly a he han he indi ec app oach which elies on he
beha io o impo ing coun ies a a simila le el o de elopmen .
To ins umen he expo -ou pu a io, we cons uc indus y-speci ic weigh ed a e age
eal exchange a e index o expo ing coun ies. We use he o icial US dolla exchange a e
index adjus ed o indus y-speci ic p ice indices. The p oduce p ice indices o majo ex-
po des ina ion coun ies a e weigh ed by hei espec i e expo sha es om a gi en in-
dus y using ade lows om COMTRADE. The o icial exchange a e is assumed o be
exogenous o i ms in a ou -digi ISIC indus y and so also a e p oduce p ices in he ex-
po des ina ion coun ies. In addi ion o his, we also use a weigh ed GDP index o expo
des ina ion coun ies o cap u e demand shocks in pa ne coun ies using he expo sha es
as weigh s. To be included in he calcula ion o he eal exchange a e index and he GDP
index, a des ina ion coun y should accoun o a leas 2.5 % o an indus y’sexpo s om
a sample coun y. The selec ed des ina ion coun ies accoun on a e age o 90 % o
indus y-le el expo s om ou sample.
The ins umen s o expo -ou pu a io can be exp essed as:
REXIUS
ij ¼EXUS
i
PPIij
X
k0
Xijk0
X
k0
Xijk0
0
@1
APPIk0
0
B
B
B
B
B
B
@
1
C
C
C
C
C
C
A
ð8Þ
GDPIij ¼X
k0
Xijk0
X
k0
Xijk0
0
B
B
@
1
C
C
A
GDPIk0 ð9Þ
whe e REXIUS
ij is weigh ed a e age eal exchange a e index o expo des ina ion
coun ies, X
ijk '
is o al expo om indus y jo coun y i o des ina ion coun y k′a
ime ,EX
US
i is he o icial exchange a e o expo ing coun y i, PPI
ij
is indus y-le el
p oduce p ice index ( om INDSTAT2) o expo ing coun y, and PPI
k'
is implici
GDP de la o o an expo des ina ion coun y. GDPI
k'
is he GDP index o an expo
des ina ion coun y while GDPI
ij
is he agg ega e GDP index o expo des ina ion
coun ies applicable o indus y jo an expo ing coun y.
12
Assuming ha wo ke s in a ou -digi indus y will conside he a e age wage in he e-
spec i e wo-digi indus y as an al e na i e wage, we use he la e o ins umen eal
wage a es a he ou -digi le el. The ac ha we a e using eal wages al eady akes in o
accoun he wo-digi p oduce p ice index in ha indus y. Real alue added o each
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 16 o 36
ou -digi indus y is ins umen ed by he eal GDP o he same coun y o cap u e de-
mand shocks om he en i e domes ic economy.
Following he discussion in Sec ion 3, he labo demand model will be es ima ed sepa -
a ely o he six egions. By c ea ing sub-samples o coun ies wi h compa able geo-
g aphic, his o ical, and ins i u ional backg ounds, we hope o u he mi iga e he e ec s
o ime a ying coun y-le el he e ogenei y ha ou model does no con ol o . These in-
clude di e ences in echnological capabili ies, human capi al, and ins i u ional quali ies
ha could a ec he employmen esponse o exogenous shocks in ou co a ia es. The
as egional di e ence in indus ial s uc u e and dynamics shown ea lie in Sec ion 3
seem o suppo his s a egy a he han imposing he same coe icien o all de eloped
and de eloping coun ies.
Wi hin each egion, he employmen model will also be es ima ed o he en i e manu-
ac u ing sec o as well as o high-, medium-, and low- echnology indus ies. The idea is
o allow o he e ogeneous employmen esponses o exogenous shock in ou co a ia es
ac oss g oups o indus ies which may a ise om unobse ed echnological and ma ke
cha ac e is ics. The obse ed s uc u al di e ences in Sec ion 3 suppo his classi ica ion
o indus ies, which hope ully enhances he s a is ical p ecision and policy ele ance o
he econome ic analysis.
5 Es ima ion esul s
13
Table 4 p esen s es ima es o he labo demand model o g oups o de eloping, ansi-
ion, and de eloped coun ies. As would be expec ed, we ind a nega i e and s a is ically
signi ican own-p ice elas ici y o labo demand ac oss all egions. In de eloping coun-
ies, he coe icien on eal wage anges om 0.44 in MENA o 0.54 in SSA wi h an a e -
age o 0.48. In e es ingly, Table 4 shows posi i e and s a is ically signi ican coe icien s on
he in e ac ion e m be ween eal wages and he labo sha e o ou pu o all egions. This
sugges s ha he elas ici y o employmen wi h espec o eal wages declines as he labo
sha e o ou pu inc eases. A a e age alues o labo sha e, which is abou 42 % in de el-
oping coun ies, he esul s indica e abou 5 % educ ion in he own-p ice elas ici y o
labo demand. This is consis en wi h he neoclassical ac o demand heo y whe e he
a e o ac o subs i u ion declines as i ms use mo e o one inpu keeping ou pu con-
s an . The sign o he in e ac ion e m also sugges s ha he elas ici y o subs i u ion o
inpu s o manu ac u ing i ms is g ea e han consume s’elas ici y o subs i u ion be-
ween inal p oduc s, al hough in heo y he la e has no uppe bound (Slaugh e 2001).
Fo mal compa ison o coe icien s in Appendix A: Table 10 in he Appendix shows ha
he coe icien on wage in OECD coun ies is signi ican ly la ge han coe icien s in each
de eloping egion. Among de eloping coun ies, s a is ically signi ican di e ences exis
mainly on he in e ac ion e m be ween labo sha e and log wages.
14
Demand o manu ac u ed goods has he expec ed posi i e and s a is ically signi ican
e ec on labo demand. Ac oss he de eloping wo ld, he a e age demand elas ici y o
employmen is abou 0.43, i.e., a 1 % g ow h in eal alue added leads o a 0.43 % inc ease
in employmen . While coe icien s on alue added in Table 4 show s a is ically insigni i-
can di e ences among de eloping egions, Appendix A: Table 10 shows ha hey a e sig-
ni ican ly lowe han ha o OECD coun ies. Gi en he ac ual con ac ion o
manu ac u ing employmen in he OECD, he posi i e demand elas ici y indica es he
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 17 o 36
ealloca ion o jobs om he declining LT indus ies owa d be e pe o ming MT and
HT indus ies.
The coe icien s on eal alue added in Table 4 sugges ha he employmen bene i s o
indus ializa ion in de eloping coun ies a e a he mode a e han wha policymake s
may ha e wished o . A de eloping coun y needs o main ain abou 10 % g ow h in eal
alue added o achie e a 4.3 % annual g ow h in manu ac u ing employmen . Howe e ,
pe o mance indica o s in Tables 1 and 2 sugges ha such spec acula a es o alue-
added g ow h a e a he in equen . In coun ies whe e popula ion and labo o ce con-
inue o g ow a 2–3 % pe annum, inc easing he employmen sha e o manu ac u ing
may equi e e en highe a es o indus ial expansion.
While demand and wage elas ici ies o labo demand a e ema kably simila ac oss de-
eloping egions in e ms o coe icien size and signi icance, Table 4 shows s iking di e -
ences in he employmen esponse o pa icipa ion in in e na ional ade (see also
Appendix A: Table 10). LAC and MENA a e he only de eloping egions whe e impo
pene a ion signi ican ly dampens domes ic labo demand. This is no su p ising in he
case o LAC gi en i s high impo pene a ion a e ela i e o o he de eloping egions.
This inding is also consis en wi h exis ing coun y-le el s udies in La in Ame ica as dis-
cussed ea lie (Re enga 1997; A anasio e al. 2004; Menezes-Filho and Muendle , 2011).
Impo pene a ion causes no ad e se employmen e ec s in ASIA, while i signi ican ly
inc eases employmen g ow h in SSA. The la e is likely he esul o be e access o
impo ed in e media e inpu s mo e han o se ing he nega i e employmen e ec s o
compe i ion om impo ed inal p oduc s. While impo compe i ion has s a is ically sig-
ni ican job des uc ion e ec s in CEE and OECD coun ies, he employmen e ec in he
OECD is a he ma ginal as compa ed o CEE.
La ge egional di e ences also eme ge in he employmen e ec s o expo o ien a ion.
O he hings being equal, g ow h in manu ac u ed expo s inc eases labo demand signi i-
can ly in LAC and ASIA. Posi i e albei weake employmen e ec s o expo s a e also
Table 4 Es ima ed labo demand model by egion: IV-panel ixed e ec s
SSA MENA LAC ASIA DVPG CEE OECD
Ln (V) 0.3597*** 0.3724*** 0.3935*** 0.4614*** 0.4337*** 0.2770*** 0.6402***
(0.0336) (0.0206) (0.0227) (0.0149) (0.0096) (0.0109) (0.0082)
M/(M+Y) 0.2437** −0.3097*** −0.3961*** 0.0214 0.0679 −0.3188*** −0.0600**
(0.0967) (0.0922) (0.0836) (0.0987) (0.0443) (0.0688) (0.0251)
X/Y −0.0382 −0.0045 0.0355*** 0.0212*** 0.0268*** 0.0172* 0.0141***
(0.0305) (0.0358) (0.0082) (0.0079) (0.0061) (0.0096) (0.0037)
Ln (w)−0.5421*** −0.4406*** −0.4635*** −0.4785*** −0.4804*** −0.3649*** −0.6440***
(0.0214) (0.0136) (0.0172) (0.0117) (0.0071) (0.0092) (0.0062)
Ln (w)*s 0.0743*** 0.0337*** 0.1215*** 0.0823*** 0.0577*** 0.0020*** 0.0674***
(0.0068) (0.0029) (0.0065) (0.0045) (0.0021) (0.0002) (0.0016)
Cons an 5.3675*** 4.7048*** 4.7174*** 4.0743*** 4.2927*** 5.8563*** 2.0429***
(0.4848) (0.3097) (0.3828) (0.2517) (0.1581) (0.1741) (0.1382)
Obse a ions 1367 3619 2789 5235 13010 7950 16258
Numbe o indus ies 162 397 449 448 1456 1068 1501
No e: All a iables a e lagged by one pe iod. Vis eal alue added, w is eal wage, sis he sha e o labo in ou pu , X/Y is
he expo sha e o ou pu , and M/(M + Y) is impo pene a ion a e. Robus s anda d e o s indica ed in pa en heses.*,
**, and *** ep esen s a is ical signi icance a 10, 5, and 1 %, espec i ely. DVPG e e s o de eloping coun ies
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 18 o 36
obse ed in CEE and OECD coun ies. Owing pa ly o hei limi ed pa icipa ion in ex-
po ma ke s, employmen in SSA and MENA does no a y wi h he expo -ou pu a io
o an indus y. O e all, he e idence does no suppo he nega i e ela ionship be ween
employmen and expo g ow h p edic ed by some o he new ade heo ies wi h he e o-
geneous i ms. Bu ou indings a e mo e consis en wi h Felbe may e al. (2011a) whe e
expo o ien a ion inc eases job c ea ion. None heless, he coe icien s on he expo a io
a e ypically small e en o egions whe e hey a e s a is ically signi ican and di e ences
ac oss egions a e la gely insigni ican as shown in Appendix A: Table 10. Such unimp es-
si e employmen bene i s sugges ha he size and p oduc i i y ad an ages o expo ing
i ms may ha e allowed hem o inc ease expo s wi h limi ed adjus men o labo .
The esul s in Table 4 e lec a e age employmen esponses ac oss all manu ac u ing
indus ies igno ing po en ial he e ogenei y ac oss g oups o indus ies. By es ima ing he
labo demand models o echnology-based g oups o indus ies, we allow employmen
esponses o a y wi hin each egion. Table 5 examines employmen in low- echnology in-
dus ies while Tables 6 and 7 epo he esul s o medium- and high- echnology indus-
ies, espec i ely. Because o limi ed numbe o obse a ions o he SSA sample, Table 6
combines he MT and HT indus ies in A ica.
Table 5 indica es ha o mos coun ies, he elas ici y o employmen wi h espec o
alue added is la ge in LT indus ies (by abou en pe cen age poin s) ela i e o he manu-
ac u ing sec o a e ages epo ed in Table 4 ( ha o LAC and CEE a e close o he a e -
age). This is no he case o MT indus ies in Table 6, whe e he coe icien s on alue
added a e ypically lowe han he espec i e egional a e age in Table 4 o all egions.
These esul s a e consis en wi h he desc ip i e s a is ics ha LT indus ies a e ypically
labo -in ensi e while MT indus ies end o be capi al-in ensi e. The employmen in ensi y
o alue-added g ow h in HT indus ies (Table 7) is o en be e han MT indus ies bu less
han LT indus ies. LAC and CEE a e excep ions whe e demand elas ici ies o employmen
in HT indus ies a e s onge ela i e o LT indus ies. As discussed ea lie , HT indus ies
a e he only indus ies in CEE and OECD coun ies ha exhibi ed employmen g ow h.
Table 5 Es ima ed labo demand model o low- echnology indus ies by egion: IV-panel ixed
e ec s
SSA MENA LAC Asia DVPG CEE OECD
Ln (V) 0.4403*** 0.5452*** 0.3779*** 0.6026*** 0.5489*** 0.2782*** 0.7516***
(0.0480) (0.0345) (0.0408) (0.0241) (0.0159) (0.0168) (0.0141)
M/(M+Y)−0.0290 −0.5260*** −0.0830 0.1866 −0.0586 −0.6591*** −0.2830***
(0.1435) (0.1187) (0.1897) (0.1470) (0.0660) (0.1084) (0.0442)
X/Y −0.0193 0.1211*** −0.0163 0.0401** 0.0346** 0.0128 0.1343***
(0.0299) (0.0425) (0.0452) (0.0157) (0.0135) (0.0176) (0.0096)
Ln (w)−0.4931*** −0.5793*** −0.4370*** −0.6230*** −0.5629*** −0.3172*** −0.7399***
(0.0342) (0.0275) (0.0288) (0.0215) (0.0134) (0.0157) (0.0111)
Ln (w)*s 0.1110*** 0.0775*** 0.1401*** 0.1784*** 0.1284*** 0.0013*** 0.0507***
(0.0138) (0.0100) (0.0124) (0.0090) (0.0054) (0.0002) (0.0021)
Cons an 3.8088*** 2.9508*** 4.8977*** 2.3120*** 2.7883*** 5.6677*** 0.9704***
(0.6850) (0.4734) (0.7177) (0.3922) (0.2464) (0.2737) (0.2545)
Obse a ions 671 1143 944 1610 4368 2683 4692
Numbe o indus ies 80 127 145 139 491 347 435
No e: See no es unde Table 4
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 19 o 36
Al hough impo pene a ion a es in LT indus ies a e highe han o he indus ies, his
does no seem o induce signi ican educ ion in labo demand in de eloping coun ies
(Table 5). The only excep ion is he esou ce ich MENA egion whe e he coe icien on
impo pene a ion is la ge, nega i e, and s a is ically signi ican . As de eloping coun ies
ha e become he main sou ces o LT expo s (accoun ing o abou wo hi ds o o al LT
expo s o coun ies in ou sample), he absence o a s ong ad e se employmen e ec
o impo s in his sec o could be he esul o ade among de eloping coun ies. Fo de-
eloped and ansi ion economies, howe e , LT impo s cause signi ican displacemen o
low-skill jobs. This indica es he ela i e compe i i eness o de eloping coun ies in LT
Table 6 Es ima ed labo demand model o medium- echnology indus ies by egion: IV-panel
ixed e ec s
SSA MENA LAC Asia DVPG CEE OECD
Ln (V) 0.3261*** 0.3141*** 0.3973*** 0.2838*** 0.3607*** 0.4240*** 0.5806***
(0.0511) (0.0365) (0.0444) (0.0292) (0.0176) (0.0215) (0.0166)
M/(M+Y) 0.3232** −0.5156** −0.5473*** −0.4580** 0.1886** −0.2788** −0.2495***
(0.1323) (0.2418) (0.1523) (0.1977) (0.0757) (0.1288) (0.0626)
X/Y −0.0092 −0.0226 0.0353 0.0351*** 0.0233** 0.0144 0.0761***
(0.1455) (0.0766) (0.0773) (0.0113) (0.0117) (0.0109) (0.0232)
Ln(w) −0.5740*** −0.3979*** −0.4930*** −0.3936*** −0.4630*** −0.4886*** −0.5816***
(0.0302) (0.0214) (0.0311) (0.0213) (0.0117) (0.0180) (0.0119)
Ln (w)*s 0.0646*** 0.0345*** 0.1546*** 0.0732*** 0.0548*** 0.0519*** 0.0809***
(0.0081) (0.0051) (0.0130) (0.0092) (0.0035) (0.0031) (0.0034)
Cons an 5.9938*** 5.4613*** 4.9503*** 6.9532*** 5.4960*** 4.3036*** 2.5997***
(0.7348) (0.5998) (0.7560) (0.5174) (0.3044) (0.3289) (0.2906)
Obse a ions 696 1380 893 1600 4437 2539 5366
Numbe o indus ies 82 149 143 137 491 346 497
No e: See no es unde Table 4
Table 7 Es ima ed labo demand model o high- echnology indus ies by egion: IV-panel ixed
e ec s
MENA LAC ASIA DVPG CEE OECD
Ln (V) 0.3715*** 0.4394*** 0.3771*** 0.4335*** 0.4098*** 0.6365***
(0.0506) (0.0361) (0.0315) (0.0209) (0.0243) (0.0144)
M/(M+Y)−0.1984 −0.4408** 0.1953 −0.0517 −0.1176 0.1222**
(0.1926) (0.1821) (0.1734) (0.1059) (0.1241) (0.0505)
X/Y −0.1101 0.0480*** −0.0059 0.0294*** 0.0160 −0.0020
(0.0974) (0.0078) (0.0148) (0.0089) (0.0318) (0.0043)
Ln(w) −0.5269*** −0.5007*** −0.4396*** −0.5072*** −0.5031*** −0.6869***
(0.0302) (0.0323) (0.0195) (0.0138) (0.0182) (0.0111)
Ln (w)*s 0.0953*** 0.0831*** 0.0457*** 0.0717*** 0.0232*** 0.0953***
(0.0110) (0.0095) (0.0069) (0.0049) (0.0017) (0.0036)
Cons an 5.0214*** 4.1416*** 5.4001*** 4.4400*** 4.4876*** 2.3626***
(0.7198) (0.5628) (0.5494) (0.3390) (0.3540) (0.2277)
Obse a ions 983 870 1821 3797 2449 5527
Numbe o indus ies 107 144 155 424 337 506
No e: See no es unde Table 4
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 20 o 36

indus ies and ou indings suppo he iew ha ade wi h de eloping coun ies educe
jobs in high-income coun ies (Au o e al. 2013).
As shown in Table 6, jobs in medium- echnology indus ies a e pa icula ly suscep ible
o impo compe i ion ac oss all egions excep SSA. Unlike he LT indus ies, he
employmen - educing e ec s o impo compe i ion in MT indus ies a e a bi s onge
o de eloping coun ies as compa ed o CEE and OECD coun ies. Un il e y ecen ly,
mo e han 50 % o wo ld expo s o MT p oduc s a e supplied by OECD coun ies show-
ing hei compe i i e ad an age. MT indus ies in A ica seem o bene i s om inc eased
impo pene a ion, which could be explained by be e access o in e media e inpu s. Jobs
in high- echnology indus ies a e by a he leas sensi i e o impo compe i ion ela i e
o LT and MT indus ies. The only excep ion is La in Ame ica whe e s a is ically signi i-
can employmen con ac ion occu s as a esul o impo pene a ion. On he lip side,
he wo egions ha domina e wo ld expo s in HT indus ies, i.e., OECD and ASIA, ha e
posi i e employmen elas ici ies wi h espec o impo pene a ion, al hough he coe i-
cien o ASIA is no s a is ically signi ican . This sugges s ha g ea e ade openness in
high- echnology indus ies could be bene icial o mos coun ies.
No all de eloping coun ies bene i om expo -o ien ed low- echnology manu ac u -
ing. Table 5 shows ha only MENA and ASIA ha e s a is ically signi ican employmen
bene i s om LT expo s. In e es ingly, he coe icien on expo -ou pu a io is posi i e
and signi ican o LT indus ies o he OECD sugges ing ha expo o ien a ion helps
slowdown he a e o job des uc ion in his sec o . This is consis en wi h he declining
employmen sha e and inc easing expo a io o his sec o in he OECD (Fig. 2). Expo
o ien a ion in MT indus ies has employmen bene i s only in ASIA and OECD egions
sugges ing hese a e he dominan expo e s in his indus y.
High- echnology expo s a e no impo an sou ces o employmen gain wi h he excep-
ion o LAC whe e he coe icien is posi i e and signi ican . The size o he coe icien on
expo a io is qui e low e en when s a is ically signi ican ea i ming he limi ed con i-
bu ion o expo -o ien ed manu ac u ing o job c ea ion. Once again, he ac ha ex-
po e s a e ela i ely la ge and p oduc i e seems o allow hem o inc ease expo s wi h
limi ed job c ea ion. Equally impo an is he obse a ion ha expo o ien a ion is no
endange ing exis ing jobs as some o he la es ade heo ies p edic ed.
Summing up, low- echnology indus ies s ill seem o ha e signi ican employmen po-
en ials o de eloping coun ies. A shi owa d MT manu ac u ing may inc ease p od-
uc i i y and alue-added g ow h in de eloping coun ies, as shown ea lie in Fig. 2, bu
such a ansi ion is less likely o gene a e mo e employmen because o he capi al-
in ensi e na u e o he sec o and i s limi ed expo o ien a ion. F om an employmen
pe spec i e, a s uc u al change ha a o s HT o e MT indus ies may se e de eloping
coun ies be e as hei human capi al and pe capi a income con inue o ise. This is
pa ly because he ou pu sha e o HT indus ies in o al manu ac u ing is s ill e y low in
de eloping coun ies and employmen in his sec o is a less suscep ible o impo com-
pe i ion. The la e is pe haps an indica ion o he ole o in e media e inpu s as well as
g owing FDI lows in his sec o om OECD o de eloping coun ies.
6 Ex ended model
In his sec ion, we ex end he labo demand model by conside ing addi ional dimensions
o expo ac i i ies. Coun ies and indus ies wi h compa able expo -ou pu a ios may
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 21 o 36
di e in he ange o expo i ems, i.e., he ex ensi e ma gin. Hausmann e al. (2007) a gue
ha he disco e y o new expo i ems is bound o be sub-op imal because o sunk cos s
ha a e p i a e and he public-good na u e o success ul new expo p oduc s. The au-
ho s also show di e si ica ion as an impo an p edic o o bo h he le el and u u e
g ow h a e o pe capi a income. In a ela ed li e a u e, Be na d e al. (2010) and
Goldbe g e al. (2010) ind ha mul ip oduc i ms a e signi ican ly la ge , mo e p oduc -
i e, and mo e expo o ien ed han single p oduc i ms. Whe he di e si ica ion a ec s
employmen oppo uni ies, holding expo - a io cons an , is hus wo h explo ing.
Ou conjec u e is ha he employmen bene i s o adding a new expo i em may de-
pend on he cu en di e si y o he expo baske . Fo a de eloped coun y wi h a b oad
ange o manu ac u ed expo i ems, adding one mo e p oduc may no ha e a no iceable
employmen e ec as compa ed o a de eloping coun y wi h only a ew expo i ems. We
a emp o explo e his ela ionship by including in he labo demand model he o al
numbe o six-digi expo i ems (HS codes) wi hin a ou -digi ISIC indus y and com-
pa e he ou come o de eloped and de eloping coun ies.
Once a new expo i em is in oduced, subsequen employmen g ow h will be d i en
by he in ensi e ma gin, which in u n depends pa ly on he compe i i eness o he global
ma ke in ha pa icula indus y. P oduc s wi h ela i ely low disco e y cos s a e likely
o be expo ed by i ms om mul iple coun ies. Wi h ewe buye s and many supplie s,
impo e s may exe cise ma ke powe and use he h ea o swi ching supplie coun ies/
i ms o dic a e he e ms o exchange in hei ad an age. The esul ing unce ain y o de-
mand and con ac e ms may educe expo e s’incen i e and abili y o c ea e and e ain
jobs. To cap u e his e ec , he ex ended labo demand model includes a measu e o he
numbe o ac i e expo e coun ies (CX) o each ou -digi indus y.
Finally, cons ain s o job c ea ion may a ise om inadequa e in es men s in machin-
e y and equipmen . Since Eq. (5) al eady con ols o alue added, he ocus he e is on
he ole o in es men on labo p oduc i i y o domes ic i ms acing compe i i e p es-
su e. One example is he educ ion in main enance cos and down ime by eplacing
old machines by new ones. The p oduc i i y e ec could also be associa ed wi h he in-
c ease in he scale o p oduc ion as in es men in ensi ies. We expec such comple-
men a y employmen e ec s o be impo an o coun ies a ea ly s ages o
indus ializa ion. Fo o he s, high in es men a es may dampen labo demand as p o-
duc ion becomes mo e capi al-in ensi e. The ex ended model includes he in es men
a e as one o he explana o y a iables, and i is calcula ed as he pe cen age o manu-
ac u ed ou pu dedica ed o in es men pu poses. The ex ended model is exp essed
as ollows:
ln LðÞ
ij ¼δþβln VðÞ
ij; −1þαln wðÞ
ij; −1þϕX
Y
0
@1
Aij; −1
þφM
MþY
0
@1
Aij; −1
þ
ψln wðÞ
ij; −1sij; −1þγln HSðÞ
ij; −1þπln CXðÞ
ij; −1þij þu þεij
ð10Þ
The esul s om he ex ended model a e p esen ed in Table 8. Because o he subs an-
ial educ ion in he numbe o obse a ions due o missing alues o he new a iables,
he ex ended model is i s es ima ed o he en i e manu ac u ing sec o wi hou del ing
in o echnology-based indus y ca ego ies. The coe icien s on p e iously discussed co a -
ia es emain simila o hose in Table 4 wi h mino di e ences in magni ude and a ew
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 22 o 36
losses o p ecision due o sample size educ ion. The e o e, he emaining discussion o-
cuses on he new a iables in he ex ended model.
A key obse a ion is he posi i e and s a is ically signi ican coe icien on he numbe
o expo i ems (HS) o de eloping coun ies. This is pa icula ly ue in SSA and LAC
coun ies and o a ce ain ex en in MENA oo. This sugges s ha a e con olling o
expo -ou pu a io, adding new expo i ems has signi ican employmen bene i s o
coun ies ha ha e ye o become accomplished expo e s o manu ac u es. No such em-
ploymen bene i s accompany expo di e si ica ion in ASIA and OECD coun ies, which
cu en ly domina e wo ld expo s o manu ac u es. The ma ginal employmen bene i s
om p oduc adding seem o decline wi h he scale o expo ac i i ies. This appea s o
esona e wi h he indings o Imbs and Waczia g (2003) ha as coun ies de elop, hei
economies become inc easingly less (mo e) concen a ed (di e si ied) un il a h eshold
le el o pe capi a income is eached, beyond which specializa ion kicks in.
Pa icipa ing in expo ma ke s in which he e a e a la ge numbe o compe i o s does
no ha e any no iceable employmen e ec s. None heless, he e is some e idence ha
expo ing wha mos o he coun ies expo inc eases job oppo uni ies in SSA. This sug-
ges s ha coun ies wi h limi ed echnological capabili ies can ge a oo hold in in e -
na ional ma ke s by expo ing i ems wi h low disco e y cos s. Simila ly, he ac ha he
coe icien on CX is nega i e o he Asian sample, despi e lacking p ecision, sugges s ha
he egion is app oaching a poin whe e indus ial expansion and job c ea ion h ough
low- echnology expo s may no longe be a iable op ion. This oppo uni y is abou o
Table 8 Ex ended labo demand model by egion: IV-panel ixed e ec s
SSA MENA LAC ASIA DVPG CEE OECD
Ln (V) 0.3352*** 0.3631*** 0.2503*** 0.4066*** 0.3084*** 0.3115*** 0.6764***
(0.0502) (0.0350) (0.0335) (0.0286) (0.0158) (0.0220) (0.0139)
M/(M+Y) 0.0784 −0.6395*** −0.6473*** −0.2628** −0.3702*** −0.4983*** 0.0200
(0.1441) (0.1099) (0.1161) (0.1159) (0.0599) (0.0836) (0.0494)
X/Y 0.0002 0.0338 0.0430*** −0.0012 0.0188*** 0.0068 0.0126***
(0.0308) (0.0335) (0.0088) (0.0084) (0.0060) (0.0102) (0.0033)
Ln (w)−0.4880*** −0.4128*** −0.3239*** −0.4079*** −0.3674*** −0.2919*** −0.6771***
(0.0344) (0.0240) (0.0253) (0.0245) (0.0124) (0.0194) (0.0122)
Ln (w)*s 0.0731*** 0.0209*** 0.0747*** 0.1174*** 0.0378*** 0.0203*** 0.0989***
(0.0107) (0.0033) (0.0087) (0.0102) (0.0027) (0.0017) (0.0032)
Ln (HS) 1.0269*** 0.1124
b
2.2233*** 0.2012 0.2922*** 0.7878*** 0.1813
d
(0.2831) (0.0762) (0.4782) (0.3500) (0.0565) (0.1338) (0.1194)
Ln (CX) 0.4071
a
0.0289 0.1368 −0.1497 0.0705 0.1752 0.0307
(0.2527) (0.1928) (0.1635) (0.1641) (0.0964) (0.1902) (0.0542)
I/Y 0.4089** 0.0925** −0.0805 0.0234 0.0315
c
−0.0067 0.0810
b
(0.1927) (0.0418) (0.0641) (0.0246) (0.0201) (0.0189) (0.0547)
Cons an −2.9992 4.1023*** −10.0472*** 4.0980* 3.5978*** −1.3813 0.1106
(2.1329) (1.1365) (3.3685) (2.3353) (0.6381) (1.3317) (0.9039)
Obse a ions 534 1104 1322 1551 4511 2211 6357
Numbe o indus ies 57 131 201 148 537 352 716
No e: See no es unde Table 4.HS is he numbe o six-digi expo i ems in a 4-digi indus y, CX is he numbe o
compe ing coun ies, and I/Y is he in es men a e. Supe sc ip s a,b,c, and d ep esen s a is ical signi icance a 11, 13,
14, and 12 %, espec i ely
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 23 o 36
a ail i sel o low-cos coun ies in A ica. The o he in e es ing esul in Table 8 is he
posi i e and signi ican ela ionship be ween in es men and employmen in de eloping
coun ies as a g oup wi h he excep ion o LAC. I is s iking ha he employmen e ec s
o in es men a e la ge and highly signi ican o manu ac u ing indus ies in SSA.
In Table 9, we allow he coe icien s o he new a iables o a y ac oss echnology-
based indus y ca ego ies. Medium- and high- echnology indus ies o de eloping coun-
ies a e me ged oge he o economize on obse a ions. The esul s show ha labo de-
mand in de eloping coun ies inc eases signi ican ly as new expo i ems (HS) a e added
o bo h LT and he combined MT/HT indus ies. Howe e , he employmen bene i s a e
subs an ially la ge in he MT/HT indus ies e lec ing pe haps g ea e possibili ies o di-
e si ica ion in mo e ad anced indus ies. This is consis en wi h Hausmann e al. (2007)
whe e g ow h in pe capi a income inc eases wi h he in oduc ion o new p oduc s in
echnologically ad anced indus ies. P oduc adding also helps de eloped coun ies c ea e
manu ac u ing jobs bu only in he HT indus ies; e en hen, he coe icien on HS is
ba ely signi ican . The coe icien on CX ha p oxies he compe i i eness o expo ma -
ke s a he indus y le el is nega i e o he mos pa as would be expec ed bu s a is i-
cally insigni ican . Fo LT indus ies in de eloping coun ies, howe e , an inc ease in he
numbe o compe ing coun ies seems o inc ease employmen .
While in es men inc eases job c ea ion in de eloping coun ies as shown in Table 8,
only in LT indus ies does his complemen a i y u n ou o be s a is ically signi ican .
This seems o be consis en wi h he obse ed inc ease in he employmen sha e o LT
Table 9 Ex ended labo demand model by egion and indus y g oup: IV-panel ixed e ec s
De eloping coun ies OECD coun ies
Low- ech Med/high- ech Low- ech Med- ech High- ech
Ln (V) 0.4288*** 0.2261*** 0.7620*** 0.6067*** 0.5924***
(0.0214) (0.0247) (0.0208) (0.0237) (0.0426)
M/(M+Y)−0.2558*** −0.4861*** −0.3644*** −0.4502*** 0.2714***
(0.0811) (0.0859) (0.0877) (0.1002) (0.0898)
X/Y 0.0347*** 0.0172** 0.1199*** 0.1186*** −0.0025
(0.0132) (0.0069) (0.0102) (0.0225) (0.0044)
Ln (w)−0.4815*** −0.3286*** −0.7149*** −0.6477*** −0.6969***
(0.0181) (0.0178) (0.0200) (0.0214) (0.0322)
Ln (w)*s0.1161*** 0.0231*** 0.1374*** 0.0945*** 0.0772***
(0.0066) (0.0031) (0.0061) (0.0053) (0.0074)
Ln (HS) 0.1911*** 0.3515*** 0.0403 −0.1885 0.6140
a
(0.0720) (0.0864) (0.1689) (0.1675) (0.3980)
Ln (CX) 0.2196* −0.1575 −0.0085 0.0970 −0.1306
(0.1235) (0.1465) (0.1118) (0.0679) (0.1206)
I/Y 0.0433* 0.0297 −0.0684 −0.1055 0.2332**
(0.0249) (0.0317) (0.1273) (0.0831) (0.0995)
Cons an 2.1329*** 5.4557*** −0.1446 3.7549*** −0.5908
(0.8238) (0.9565) (1.3057) (1.2790) (3.0254)
Obse a ions 2430 2081 2811 2234 994
Numbe o indus ies 287 250 314 254 114
No e: See no es unde Table 4. HS is he numbe o six-digi expo i ems in a ou -digi indus y, CX is he numbe o
compe ing coun ies, and I/Y is he in es men a e. Supe sc ip s a ep esen s s a is ical signi ican a 13 %
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 24 o 36
Table 13 Regional compa ison o labo demand models: high- echnology in e ac ions
Compa ison wi h ASIA Compa ison wi h OECD
ASIA-MENA ASIA-LAC OECD-ASIA OECD-MENA OECD-LAC
Ln (V) 0.5958 0.3924 0.4011 0.6880 0.4369
(0.0356)*** (0.0529)*** (0.0205)*** (0.0220)*** (0.0362)***
M/(M+Y)−0.1863 −0.4486 0.2039 −0.1864 −0.3298
(0.1886) (0.2695)* (0.1278) (0.1300) (0.1859)*
X/Y −0.1293 0.0825 −0.0057 −0.1251 0.0814
(0.0953) (0.0706) (0.0110) (0.0657)* (0.0487)*
Ln (w)−0.6018 −0.4708 −0.4437 −0.6356 −0.4827
(0.0271)*** (0.0485)*** (0.0142)*** (0.0183)*** (0.0334)***
Ln (w)*s 0.1207 0.0720 0.0488 0.1300 0.0816
(0.0101)*** (0.0140)*** (0.0051)*** (0.0069)*** (0.0097)***
*ln (V)−0.2587 −0.0296 0.2277 −0.0771 0.1865
(0.0434)*** (0.0592) (0.0257)*** (0.0265)*** (0.0389)***
*M/(M+Y) 0.3819 0.6262 −0.0517 0.3236 −0.0824
(0.2601) (0.3116)** (0.1430) (0.1440)** (0.0492)*
*X/Y 0.1283 −0.0842 0.0040 0.1243 0.4767
(0.0966) (0.0719) (0.0138) (0.0662)* (0.1936)**
*ln (w) 0.1534 0.0303 −0.2416 −0.0446 −0.1990
(0.0338)*** (0.0515) (0.0195)*** (0.0224)** (0.0353)***
*ln (w)*s −0.0767 −0.0266 0.0459 −0.0370 0.0121
(0.0122)*** (0.0153)* (0.0067)*** (0.0080)*** (0.0103)
_cons 4.7270 5.3752 3.2307 2.5950 2.8839
(0.4310)*** (0.4209)*** (0.2288)*** (0.2335)*** (0.2131)***
N2800 2682 7327 6493 6375
No e: See Appendix A: Table 10 o no es
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 31 o 36

Table 14 Fi s S age Reg ession Resul s o ASIA Co esponding o Table 4
Value added Wage a e Impo pene a ion Expo -ou pu
EXI
ij
−0.2344 0.1321 0.0771 0.0329
0.0468 0.0376 0.0075 0.0254
PPI
ij
−0.0024 −0.0073 −0.0001 −0.0001
0.0006 0.0005 0.0001 0.0003
REXIUS
ij
−0.3890 −0.8549 −0.0297 −0.0513
0.0175 0.0140 0.0028 0.0095
REXIUS
ij -squa ed 0.0057 0.0048 0.0007 −0.0003
0.0012 0.0010 0.0002 0.0007
GDPI
ij
−0.0073 0.0012 −0.0007 −0.0009
0.0008 0.0006 0.0001 0.0004
Ln (w)- wo-digi SIC 0.2787 0.0824 −0.0005 −0.0189
0.0181 0.0145 0.0029 0.0098
GDPI-domes ic 0.0133 0.0117 0.0006 0.0008
0.0007 0.0006 0.0001 0.0004
F s a is ic 108.7 716.34 18.81 8.46
No e: EXI
ij
is a weigh ed a e age exchange a e index o impo supplie coun ies, PPI
ij
is a weigh ed a e age indus y-
speci ic p ice index o impo sou ce coun ies, REXIUS
ij is weigh ed a e age eal exchange a e index o expo des ina ion
coun ies, GDPI
ij
is he agg ega e GDP index o expo des ina ion coun ies applicable o indus y jo an expo ing coun y,
ln (w)- wo-digi SIC is he log o wage a e a he wo-digi SIC le el, and GDPI-domes ic is GDP index a he coun y le el.
Robus s anda d e o s a e in pa en hesis
Table 15 Fi s s age eg ession esul s o SSA co esponding o Table 4
Value added Wage a e Impo pene a ion Expo -ou pu
EXI
ij
0.3426 0.0741 −0.0026 −0.0182
(0.0500) (0.0676) (0.0166) (0.0394)
PPI
ij
−0.0058 −0.0073 −0.0006 −0.0002
(0.0011) (0.0015) (0.0004) (0.0008)
REXIUS
ij
−0.1949 −0.7543 −0.0315 −0.0574
(0.0272) (0.0368) (0.0090) (0.0214)
REXIUS
ij -squa ed −0.0301 0.0044 0.0008 0.0010
(0.0039) (0.0053) (0.0013) (0.0031)
GDPI
ij
−0.0028 0.0004 0.0014 −0.0005
(0.0010) (0.0014) (0.0003) (0.0008)
Ln (w)- wo-digi SIC 0.0779 −0.1010 0.0346 −0.0061
(0.0371) (0.0502) (0.0123) (0.0292)
GDPI-domes ic 0.0098 −0.0082 0.0013 0.0013
(0.0011) (0.0015) (0.0004) (0.0009)
F s a is ic 53.76 89.23 17.98 2.09
No e: See no es o Appendix B: Table 14
Appendix B: Fi s s age eg ession esul s
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 32 o 36
Table 16 Fi s s age eg ession esul s o LAC co esponding o Table 4
Value added Wage a e Impo pene a ion Expo -ou pu
EXI
ij
−0.0815 −0.0554 −0.0028 0.0362
0.0334 0.0330 0.0085 0.0260
PPI
ij
−0.0002 −0.0086 −0.0003 −0.0005
0.0005 0.0005 0.0001 0.0004
REXIUS
ij
−0.0780 −0.6938 −0.0640 −0.0523
0.0124 0.0123 0.0031 0.0097
REXIUS
ij -squa ed −0.0177 −0.0154 0.0030 0.0024
0.0017 0.0017 0.0004 0.0013
GDPI
ij
−0.0016 −0.0011 0.0003 0.0017
0.0010 0.0009 0.0002 0.0007
Ln (w)- wo-digi SIC −0.1089 −0.0095 −0.0149 −0.0138
0.0242 0.0239 0.0061 0.0188
GDPI-domes ic 0.0210 0.0378 0.0011 0.0025
0.0022 0.0022 0.0006 0.0017
F s a is ic 53.98 293.27 31.95 3.98
No e: See no es o Appendix B: Table 14
Table 17 Fi s s age eg ession esul s o OECD co esponding o Table 4
Value added Wage a e Impo pene a ion Expo -ou pu
EXI
ij
−0.1835 −0.0197 0.0155 0.0443
0.0195 0.0142 0.0066 0.0206
PPI
ij
−0.0056 −0.0118 0.0000 −0.0005
0.0002 0.0002 0.0001 0.0002
REXIUS
ij
−0.3381 −0.8440 −0.0367 −0.1030
0.0054 0.0039 0.0018 0.0057
REXIUS
ij -squa ed 0.0063 0.0193 0.0011 0.0040
0.0010 0.0007 0.0003 0.0010
GDPI
ij
−0.0057 −0.0009 0.0005 0.0005
0.0003 0.0002 0.0001 0.0004
Ln (w)- wo-digi SIC 0.0842 0.0272 −0.0197 −0.0333
0.0079 0.0058 0.0027 0.0084
GDPI-domes ic 0.0140 0.0140 0.0004 −0.0003
0.0003 0.0002 0.0001 0.0004
F s a is ic 366.11 2974 85.45 40.67
No e: See no es o Appendix B: Table 14
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 33 o 36
Table 18 Fi s s age eg ession esul s o CEE co esponding o Table 4
Value added Wage a e Impo pene a ion Expo -ou pu
EXI
ij
0.1079 0.2663 0.0136 −0.0074
0.0314 0.0285 0.0060 0.0239
PPI
ij
−0.0016 −0.0045 −0.0003 −0.0006
0.0004 0.0004 0.0001 0.0003
REXIUS
ij
−0.2813 −0.6260 −0.0306 −0.0670
0.0066 0.0060 0.0013 0.0050
REXIUS
ij -squa ed −0.0228 −0.0454 −0.0037 −0.0058
0.0020 0.0018 0.0004 0.0015
GDPI
ij
0.0016 0.0039 0.0005 0.0000
0.0007 0.0007 0.0001 0.0005
Ln (w)- wo-digi SIC 0.0521 0.0043 −0.0122 −0.0223
0.0171 0.0155 0.0033 0.0130
GDPI-domes ic 0.0047 0.0060 −0.0001 −0.0002
0.0003 0.0003 0.0001 0.0002
F s a is ic 210.77 774.19 36.84 10.7
No e: See no es o Appendix B: Table 14
Table 19 Fi s s age eg ession esul s o MENA co esponding o Table 4
Value added Wage a e Impo pene a ion Expo -ou pu
EXI
ij
−0.1983 −0.0764 0.0321 0.0317
0.0329 0.0311 0.0076 0.0181
PPI
ij
−0.0028 −0.0079 −0.0002 −0.0007
0.0006 0.0006 0.0001 0.0003
REXIUS
ij
−0.2730 −0.7793 −0.0182 −0.0407
0.0106 0.0101 0.0024 0.0059
REXIUS
ij -squa ed 0.0074 0.0231 0.0007 0.0011
0.0008 0.0008 0.0002 0.0004
GDPI
ij
0.0026 0.0026 0.0001 −0.0004
0.0009 0.0009 0.0002 0.0005
Ln (w)- wo-digi SIC 0.0452 0.0030 −0.0111 0.0080
0.0254 0.0240 0.0058 0.0140
GDPI-domes ic 0.0007 −0.0002 0.0006 0.0027
0.0013 0.0013 0.0003 0.0007
F s a is ic 154.17 456.14 11.36 4.73
No e: See no es o Appendix B: Table 14
Shi e aw and Hailu IZA Jou nal o Labo & De elopmen (2016) 5:3 Page 34 o 36
Appendix C
Compe ing in e es s
The IZA Jou nal o Labo & De elopmen is commi ed o he IZA Guiding P inciples o Resea ch In eg i y. The au ho s
decla e ha hey ha e obse ed hese p inciples.
Acknowledgemen s
We hank Be hanu Abegaz and Pe e McHen y o hei commen s and sugges ions. We a e also g a e ul o he
impo an commen s p o ided by a e e ee and he edi o o IZA-JOLD ha helped us imp o e he pape .
Responsible edi o : Da id Lam
Au ho de ails
1
The College o William and Ma y Williamsbu g, Vi ginia, USA.
2
UNDP (Uni ed Na ion De elopmen P og amme), New
Yo k, USA.
Recei ed: 25 Augus 2015 Accep ed: 15 Janua y 2016
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