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Domicián Má é, Im an Sa ihasan,
Józse Popp, Judi Oláh
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Economics & Sociology, Vol. 11, No. 3, 2018
THE ROLE OF REGIONAL
DIFFERENCES IN IMMIGRATION:
THE CASE OF OECD COUNTRIES
Domicián Má é,
Uni e si y o Deb ecen,
Facul y o Economics and Business,
Deb ecen, Hunga y,
E-mail:
[email p o ec ed]
Im an Sa ihasan,
Uni e si y o Deb ecen,
Ká oly Ih ig Doc o al School
Deb ecen, Hunga y,
E-mail:
[email p o ec ed]
Józse Popp,
Uni e si y o Deb ecen,
Facul y o Economics and Business,
Deb ecen, Hunga y,
E-mail:
[email p o ec ed]
Judi Oláh,
Uni e si y o Deb ecen,
Facul y o Economics and Business,
Deb ecen, Hunga y,
E-mail: [email p o ec ed]
Recei ed: Ap il, 2018
1s Re ision: May, 2018
Accep ed: Augus , 2018
DOI: 10.14254/2071-
789X.2018/11-3/12
ABSTRACT. Despi e physical, cul u al, economic and
o he obs acles, millions o people ha e ecen ly
emig a ed om one coun y o ano he in sea ch o a
be e li e. Consequen ly, he impo ance o his esea ch
opic has g own o e ime. Analysis o his egional
app oach is based on he OECD censuses, and i s
unique Da abase on Immig an s (DIOC), which makes i
possible o gene a e a wide a ie y o c oss- abula ions
on he cha ac e is ics o asylum-seeke s by he coun y
o hei bi h. The aim o his s udy is o con ibu e o
li e a u e by analysing he ole o egional di e ences in
mig a ion mo e closely in e ms o he impo ance o
mig a ion egula ion policies in he OECD coun ies.
Acco ding o he esul s based on Bina y Logis ic (Logi )
and Linea (OLS) Reg ession models, he educa ional
a ainmen , age, sex and he place o bi h o mig an s
a e ela ed in di e en ways o hei egion o o igin.
Mo eo e , male mig an s a e mo e skilled han emales,
mig an s who a e mo e educa ed a e olde han he less
skilled, and o eign-bo n mig an s seemed o be olde
han na i e-bo n mig an s. The e is also addi ional
e idence sugges ing ha di e en egions and coun ies
migh ollow di e en policies and no ms o admission
o mig an s. The e o e, o hcoming mig a ion
go e nance p og ams ha aim o acili a e he labou
ma ke in eg a ion o mig an s should also ake in o
conside a ion hei egional cha ac e is ics.
JEL Classi ica ion
: K37, J21,
J15
Keywo ds:
mig a ion; egionalism; educa ional a ainmen , aging,
OECD.
Má é, D., Sa ihasan I., Popp, J., & Oláh, J. (2018). The Role o Regional
Di e ences in Immig a ion: The Case o OECD Coun ies. Economics and
Sociology, 11(3), 190-206. doi:10.14254/2071-789X.2018/11-3/12
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In oduc ion
Regions o he wo ld accoun o di e en p opo ions in he global numbe o
mig an s. The o igin o in e na ional mig an s has become inc easingly di e si ied o e he
pas wo decades (Uni ed Na ions, 2017). Asia and Eu ope hos ed o e 60% o all
in e na ional mig an s wo ldwide in 2017, wi h nea ly 80 million li ing in Asia and 78
million in Eu ope. No h Ame ica hos ed he hi d la ges numbe o in e na ional mig an s
(58 million), ollowed by A ica (25 million), La in Ame ica and he Ca ibbean (10 million),
and Oceania (8 million) (UN, 2017). Asia, Eu ope and No h Ame ica accoun ed o o e
85% o he inc ease in he numbe o in e na ional mig an s be ween 1990 and 2017. Thus,
be ween 2010 and 2017, A ica expe ienced he second as es annual g ow h, wi h he
a e age o 1.1 million pe annum (Figu e 1).
Figu e 1. A e age annual change in he numbe o in e na ional mig an s by majo egions o
o igin, 1990-2017 (millions)
Sou ce: Au ho s’ own compila ion based on Uni ed Na ions (UN, 2017).
The la es wa e o immig a ion in he pos -c isis pe iod (2010-2015) is unlike p e ious
wa es in e ms o skill and o igin s uc u e. Bu zynski, Docquie , & Rapopo (2018) ha e
shown ha he wel a e e ec s o immig a ion a e e y he e ogeneous ac oss skill g oups,
coun ies o des ina ion, and immig a ion wa es. Fo ins ance, he la es wa e pe iod o
immig a ion is less skilled and b ings ewe bene i s. The wel a e impac o ecen mig a ion
lows ha e been bene icial o 69% o he non-mig an OECD esiden s, and o 83% o non-
mig an ci izens in 22 iches OECD coun ies. The leading bene icia ies a e mainly
adi ional immig a ion coun ies; hei gains a e ex ensi e due o he en y o immig an s
om non-OECD coun ies (Aub y, Bu zyński, & Docquie , 2016).
The e a e a ious economic, social and physical easons why people emig a e and hey
can usually be classi ied in o push (nega i e incen i es) and pull (posi i e) ac o s
(Bod a sson & Van den Be g, 2013). The main economic eason o choosing o be a mig an
is o seek an imp o ed li e by inding a job, and he d i ing o ces o mig a ion a e highe
wages, human secu i y and wo k oppo uni ies (Cas les, 2013). The economic push ac o s
end o be he exac opposi e o he pull ac o s ha a e associa ed wi h he a ea o des ina ion
(o e popula ion, insu icien numbe o jobs, low wages e c.). Howe e , o he social easons,
i.e. ci il and poli ical igh s, eligious eedom, law and o de , social mobili y, pe sonal
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sa e y, and peace, oge he wi h o he a ac i e en i onmen al ac o s (clima e, seaside
loca ion e c.) all make a des ina ion coun y a ac i e o po en ial immig an s.
These economic, poli ical and social incen i es exis wo ldwide, hus in luencing
in e na ional mig a ion o e ecen decades (Ozgu & Deniz, 2014). The economic
cha ac e is ics o mig an s and hei mo i a ions o mo ing a y by age g oup and by
mig an s a us (Philip, Macleod, & S ockdale, 2013). Se e al s udies (McInnis 1971;
Milling on, 2000 e c.) demons a e he e is a posi i e ela ionship be ween he age o
esponsi eness and he economic gains om mig a ion. Hence, younge mig an s ha e g ea
adap abili y o new challenges when en e ing he labou ma ke o a des ina ion coun y.
Mo eo e , egional di e ences - including wage and age dispa i ies e c. - can a ec mig a ion
as well (Hun , 2012). Essen ially, people mig a e om low-income o high-income egions,
which inc eases he mobili y cos o mig a ion. This p esump ion ocuses almos exclusi ely
on he size and di ec ion o popula ion lows ac oss egions (Bo jas, B ona s, & T ego, 1992).
Thus, he ela ionship be ween mig a ion, age, educa ion, seg ega ion and dis ance ha e been
discussed in many economic s udies (Schwa z, 1976;, Muese , 1989; Iceland, 2017 e c.).
Al hough mig an s ypically ans e om lowe o highe income egions, mig a ion lows
inc ease wi h highe educa ion and educe wi h aging. Ne e heless, he economic impac o
mig a ion depends on he numbe and he educa ion le el o mig an s and also on how well
educa ion o mig a ing indi iduals ma ches hei u u e occupa ions (Quinn & Rubb, 2005).
The skill- and o igin-mix o mig a ion o he OECD has e ol ed o e ime.
Meanwhile, many OECD coun ies ha e been a emp ing o a ac quali ied human esou ces
om ab oad, since knowledge-based and p og essi e economies need o sus ain hei
economic g ow h (Dumon & Lamai e, 2005). I is bene icial o hese coun ies o acqui e
mig an s who ha e solid educa ion and well-de eloped skills in o de o imp o e hei
economic pe o mance, since i has been widely acknowledged ha educa ion and skills
oge he a e he majo sou ces o economic p ospe i y (Flisi, Me oni, & Ve a-Toscano, 2016).
These in en ions a e highly dependen on he ime ame in ol ed, i.e. educa ion has a g ea e
in luence on long‐ e m mig a ion decisions (Williams e al., 2018). Mo eo e , he in luence
o mig a ion may lead o changes in he a e age le els o educa ion in des ina ion coun ies
and gene a e educa ional ex e nali ies and new incen i es o human capi al in es men s
(Dus mann & Gli z, 2011).
Fu he mo e, each mig an is a sou ce o pe sonal consump ion expendi u e, which is
also ans e ed among he egions. Di Gio anni, Le chenko, & O ega (2015) compa ed
wel a e wi h le els o mig a ion om he c oss-coun y global analysis pe spec i e, and
ound ha na i es in hose coun ies (Canada, Aus alia) ha ecei ed high le els o mig a ion
a e be e o due o a g ea e p oduc a ie y a ailable in consump ion and as in e media e
inpu s. Meanwhile, in he sho un, skilled and unskilled na i es end o expe ience wel a e
changes wi h opposi e signs. Ini ial s udies ha e discussed he p ocess o unde s anding he
ela ionships be ween ade, mig a ion, and egional changes (Fou nie , 1989). Meanwhile,
educa ion sys ems and social policies a e no simila ac oss egions, while socioeconomic
s a us and e hnocul u al a angemen s o immig an s di e ge conside ably. Such
cha ac e is ics o mig a ion may be associa ed wi h egional di e ences in he educa ion
ou comes. Mig a ion also has economic, social and cul u al consequences o bo h he o igin
and he des ina ion coun ies. This phenomenon is signalled by he absence o social ba ie s,
pa icipa ion in mains eam ins i u ions, in e ma iage wi h hos coun y na i es, and deg ees
o sel -iden i ica ion by immig an s as na i es (Beck, Co ak, & Tienda, 2012).
The aim o his s udy is o con ibu e o li e a u e by analysing he ole o egional
di e ences o mig a ion mo e closely in e ms o he impo ance o mig a ion egula ion
policies in he OECD coun ies. The signi icance o ou egional pe spec i e is o explain he
complexi y o mig a ion cha ac e is ics in di e en socie ies, aking in o accoun spa ial and
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geog aphic aspec s. Conside ing he consequences o popula ion dis ibu ion, age, and gende
s uc u e e c. can be compa ible wi h he in eg a ion pu poses o mig a ion policies (Findlay
& Mulde , 2015). Assuming also ha common mig a ion policies do no wo k p ope ly, he e
is no unique solu ion o social and economic p oblems o mig a ion in e ms o inequali ies.
The e ec s o hese inequali ies in mig a ion on he places o o igin and des ina ion a e also
in luenced by a p ocess called mig a ion selec i i y. Hence, ce ain indi iduals a e mo e
likely o mig a e, based on hei pe sonal and sociodemog aphic cha ac e is ics.
The es o his pape is o ganized as ollows. The nex (1) sec ion summa izes he
b ie concep ual amewo k o mig a ion heo ies wi h a egional pe spec i e. Then, in sec ion
2, logis ics (Logi ) and linea (OLS) eg ession analyses a e ca ied ou wi h c oss-coun y
s a is ics in o de o in es iga e how gende , aging, place o bi h, and educa ional a ainmen
di e ences a e ela ed o egional cha ac e is ics o mig an s. Finally, based on hese esul s,
he pape ends wi h some policy implica ions and conclusions (Sec ion 4). Howe e , ou
mo i a ion is no only o sugges a easible poin o e e ence o esea che s, o enhance he
e ec i eness o policies, o educe he nega i e consequences o mode n sla e y, bu also o
ou line u he esea ch di ec ions in his in e na ional pe spec i e ela ed o he quali y o
mig a ion egula ion ac oss coun ies in he in e es s o human de elopmen o e ime.
1. Li e a u e e iew
The no ion o mig a ion is commonly unde s ood as a mo emen om one loca ion o
ano he o he pu pose o ei he empo a y o pe manen se lemen . This may in ol e long-
dis ance a eling, ac oss o wi hin he bo de s o a coun y om one egion o ano he wi h a
dis inc ly di e en cul u al, poli ical o social e c. en i onmen (Biswas, McHa dy, & Nolan,
2005). The de elopmen o mig a ion occu s when an indi idual decides ha i is p e e able
o mo e a he han o s ay, and whe e he di icul ies o mo ing seem o be mo e han o se
by he expec ed ewa ds. Popula ion mo emen s a e esponses o dis inc condi ions and
ela ed inciden s, which people encoun e bo h in places o o igin and des ina ion.
The ea ly heo ies o mig a ion we e mos ly ocused on domes ic mig a ion, and we e
closely ela ed o loca ion models om egional economics and he economics o geog aphy.
E. G. Ra ens ein i s de eloped he ‘law o mig a ion’, which classi ied mig an s by he
dis ance o eloca ion (Ra ens ein, 1885). Acco ding o Ra ens ein’s laws o mig a ion, mos
mig an s mo e only a sho dis ance and usually o la ge ci ies ha g ow apidly and end o
be popula ed by mig an s om nea by u al a eas. Thus women a e mo e likely o mig a e
han men, he ou -mig a ion is in e sely ela ed o in-mig a ion, and a majo mig a ion wa e
will gene a e a compensa ing coun e wa e (G eenwood, 1997).
In his ea ly app oach, local mig an s mo ed wi hin he coun y, o only om he
coun y o hei bi h o bo de coun ies (Kose & Sal , 1997). The e o e, a se ies o analyses
a emp ed o explain and p edic mig a ion pa e ns bo h wi hin and be ween na ions. The
basic and addi ional laws o mig a ion subsequen ly eme ged o se e as he s a ing poin o
all se ious models o mig a ion pa e ns. One o hese laws ela ing o he gende gap asse ed
ha sho -dis ance mig an s a ou numbe ed longe dis ance ones, and women domina ed
wi hin coun ies. The ou come o hese endencies led o an in e se ela ionship be ween he
olume o mig a ion and he dis ance be ween he home and des ina ion coun ies.
The heo e ical backg ound o in e na ional mig a ion is mainly g ounded in he
consump ion app oach a ou ed by u ban and egional economis s and which ocuses
p ima ily on domes ic mig a ion. G eenwood (1993) poin s ou ha by he ea ly 1980s, he
‘equilib ium’ pe spec i e on mig a ion sugges ed people mig a e o ake ad an age o
egional income di e ences. The elemen a y idea behind his pe spec i e is ha people
mig a e o adjus hei consump ion o equen changes in incomes, p ices, he supply o
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goods and se ices and hei u ili y unc ions e c. (Rosen, 1974). The no ion ha people
mig a e in esponse o spa ial di e ences in ameni ies was also p oposed by Tiebou (1956),
who a gued ha an impo an ac o explaining why people mo e om one locali y o ano he
is di e ences in he quali y o public goods, such as police and i e p o ec ion, educa ion,
hospi als, cou s and o he acili ies. Ne e heless, he idea has no been applied o he s udies
o in e na ional mig a ion in e ms o i s egula ed na u e and he ela i ely highe cos s o
in e na ional mo emen .
Thus, he empi ical esul s om na ional analyses only con ibu ed o he e i ica ion
o mig a ion heo ies, and o iden i ying po en ial di e ences be ween (in e )na ional
de e minan s o mig a ion, so as o become he g oundwo k o egional economic policies
(Jando á & Pale a, 2015). Ne e heless, acco ding o he ‘push and pull’ gene al heo y o
mig a ion, immig a ion is de e mined by a summa ized compa ison o a wide ange o
posi i e ac o s in des ina ion coun ies and a ious nega i e ones in he o iginal place o
esidence (Rahmandous , 2011). In o he wo ds, mig a ion is selec i e and ends o conside
posi i e (pull) ac o s which occu in he mig a ion des ina ion a ac ing mig an s o he
coun y o des ina ion (Kain h, 2009). Mo eo e , nega i e (push) easons also occu , which in
some ci cums ances d i e mig an s o lea e hei coun ies o o igin o des ina ion egions.
Meanwhile, in he sociological li e a u e on mig a ion, he ole o he communi y o amily
and iends a he des ina ion is o en e e ed o as a ela ionship. The banding oge he o
p e ious mig an s om a simila e hnic o egional backg ound is also e e ed o as a mig an
ne wo k, based on he linguis ic simila i y be ween speci ic a eas (Chiswick & Mille , 2014).
E idence also suppo s he idea ha immig an s end o concen a e whe e ea lie na ionals
ha e se led because he cos o adap ing o a no el socie y is mi iga ed by he p esence o
esiden s amilia wi h bo h he sou ce and des ina ion coun y cul u es. The le el o spa ial
mobili y is la ge , ce e is pa ibus, when he e bal and cul u al en i onmen in he des ina ion
coun y is amilia (Rephann & Venca asawmy, 2000).
In ou opinion, no unique immig a ion heo y has ye been de ised which can
comple ely explain egional mig a ion dispa i ies. Thus, he e is s ill a big gap be ween heo y
and empi ical e idence, and much needs o be done on he heo e ical side o his li e a u e, as
well. One o he g ea es challenges o mig a ion heo is s is o o ganize all hypo he ically
ele an ac o s in o one cohe en amewo k ha will speci y hei in e ac ion wi h each o he
in an empi ically es able o m and he eby se e as a guide o u u e esea ch. Consequen ly,
mo e s udies a e needed using many econome ic models, da a se s, ime pe iods, coun ies,
and eplica ions o exis ing s udies be o e economis s can ha e enough con idence in he
esul s o hei own s a is ical s udies o immig a ion.
2. Da a and me hodological app oach
This esea ch uses he Da abase on Immig an s in OECD Coun ies (DIOC) which
p o ides de ailed in o ma ion on he census da a o immig an s (OECD, 2018). This unique
da abase makes i possible o gene a e an ex ensi e a ie y o c oss- abula ions on he
cha ac e is ics o he mig an inhabi an s in OECD coun ies by hei coun y o bi h. The
la es a ailable elease includes a speci ic a ea co e ing age, gende , na ionali y, place o bi h
and du a ion o s ay e c.
The es ima ions a e mainly based on bina y logis ic (Logi ) eg ession models (see
Equa ion 1, 2, 3, 4, 5 and 6) ha a e equen ly used o apply o a bina y dependen a iable o
di e en egions. The Logi eg ession me hod was i s de eloped by Cox (1958) o es ima e
he p obabili y o a bina y esponse based on one o mo e p edic o (o independen )
a iables. In o de o analyse whe he educa ional a ainmen , age, sex and he place o bi h

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o mig an s ela e di e en ly o hei egion o bi h he ollowing models a e es ed in each
case o he mig an s obse ed i:
𝐷𝐴𝑓𝑟𝑖𝑐𝑎𝑖= 𝛽𝑜+ 𝛽1𝐸𝑑𝑢𝑖+ 𝛽2𝐴𝑔𝑒𝑖+ 𝛽3𝐷𝑆𝑒𝑥𝑖+ 𝛽4𝐷𝐹𝑏𝑜𝑟𝑛𝑖+𝑖 (1)
𝐷𝐴𝑠𝑖𝑎𝑖= 𝛽𝑜+ 𝛽1𝐸𝑑𝑢𝑖+ 𝛽2𝐴𝑔𝑒𝑖+ 𝛽3𝐷𝑆𝑒𝑥𝑖+ 𝛽4𝐷𝐹𝑏𝑜𝑟𝑛𝑖+𝑖 (2)
𝐷𝐸𝑢𝑟𝑜𝑝𝑒𝑖= 𝛽𝑜+ 𝛽1𝐸𝑑𝑢𝑖+ 𝛽2𝐴𝑔𝑒𝑖+ 𝛽3𝐷𝑆𝑒𝑥𝑖+ 𝛽4𝐷𝐹𝑏𝑜𝑟𝑛𝑖+𝑖 (3)
𝐷𝑁_𝐴𝑚𝑒𝑟𝑖𝑐𝑎𝑖= 𝛽𝑜+ 𝛽1𝐸𝑑𝑢𝑖+ 𝛽2𝐴𝑔𝑒𝑖+ 𝛽3𝐷𝑆𝑒𝑥𝑖+ 𝛽4𝐷𝐹𝑏𝑜𝑟𝑛𝑖+𝑖 (4)
𝐷𝑂𝑐𝑒𝑎𝑛𝑖𝑎𝑖= 𝛽𝑜+ 𝛽1𝐸𝑑𝑢𝑖+ 𝛽2𝐴𝑔𝑒𝑖+ 𝛽3𝐷𝑆𝑒𝑥𝑖+ 𝛽4𝐷𝐹𝑏𝑜𝑟𝑛𝑖+𝑖 (5)
𝐷𝑆&𝐶_𝐴𝑚𝑒𝑟𝑖𝑐𝑎𝑖= 𝛽𝑜+ 𝛽1𝐸𝑑𝑢𝑖+ 𝛽2𝐴𝑔𝑒𝑖+ 𝛽3𝐷𝑆𝑒𝑥𝑖+ 𝛽4𝐷𝐹𝑏𝑜𝑟𝑛𝑖+𝑖 (6)
The dependen a iables a e dummies dis inguished by he mig an s’ di e en egion
o bi h, i.e. DA ica is = 1 i he mig an is bo n in A ica, 0 = o he wise. Respec i ely,
DAsia e e s o Asia, DEu ope o Eu ope, DN_Ame ica o No h Ame ica, DOceania o
Oceania, and DS&C_Ame ica indica es Sou h and Cen al Ame ica. The i s independen
a iable is (Edu), whe e he de ailed educa ional le els (1-6) a e based on he In e na ional
S anda d Classi ica ion o Educa ion (ISCED) as de ined by UNESCO (2011). The nex
con ol a iable is (Age), which is di ided in o he ollowing age g oup ca ego ies: 1 = 0-14;
2 = 15-24; 3 = 25-34; 4 = 35-44; 5 = 45-54; 6 = 55-64; 7 = 65+. The (DSex) dummy no es he
gende di e ences; namely, 1 i he mig an is emale, 0 i male. The subsequen con ol
dummy a iable (DFbo n) indica es whe he he mig an is o eign- o na i e-bo n. Acco ding
o he OECD (OECD, 2017), o eign-bo n immig an s include all hose who ha e e e
mig a ed om hei coun y o bi h o hei cu en coun y o esidence. Thus, a na i e-bo n
ci izen o a coun y is one whose mig an pa en s’ place o bi h is he hos coun y. (ε) is he
e o e m.
Based on he p e iously epo ed (1-6) Equa ions, he cu en s udy o ms he
ollowing hypo heses:
H1: A ican mig an s a e less likely o be educa ed, olde , o eign-bo n and emale
han o he mig an s.
H2: Asian mig an s a e less likely o be educa ed, olde , o eign-bo n and emale han
o he mig an s.
H3: Eu opean mig an s a e less likely o be educa ed, olde , o eign-bo n and emale
han o he mig an s.
H4: No h Ame ican mig an s a e less likely o be educa ed, olde , o eign-bo n and
emale han o he mig an s.
H5: Oceanian mig an s a e less likely o be educa ed, olde , o eign-bo n and emale
han o he mig an s.
H6: Sou h and Cen al Ame ican mig an s a e less likely o be educa ed, olde ,
o eign-bo n and emale han o he mig an s.
In o de o exempli y he alidi y o ou esul s, and e i y ha educa ional a ainmen ,
and age o mig an s ela e di e en ly o hei egion o bi h, addi ional me hodologies a e
needed o cla i y he egional cha ac e is ics o mig a ion. Fo ins ance, linea OLS
eg essions. Consequen ly, a linea (OLS) eg ession model is used o highligh he egional
di e ences among ou e alua ions.
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𝐸𝑑𝑢𝑖= 𝛽𝑜+ 𝛽1𝐴𝑔𝑒𝑖+ 𝛽2𝐷𝑆𝑒𝑥𝑖+ 𝛽3𝐷𝐹𝑏𝑜𝑟𝑛𝑖+ 𝛽4𝐷𝐴𝑓𝑟𝑖𝑐𝑎𝑖+ 𝛽5𝐷𝐴𝑠𝑖𝑎𝑖+
𝛽6𝐷𝐸𝑢𝑟𝑜𝑝𝑒𝑖+ 𝛽7𝐷𝑁_𝐴𝑛𝑒𝑟𝑖𝑐𝑎𝑖+ 𝛽8𝐷𝑂𝑐𝑒𝑎𝑛𝑖𝑎𝑖+𝑖
(7)
𝐴𝑔𝑒𝑖= 𝛽𝑜+ 𝛽1𝐸𝑑𝑢𝑖+ 𝛽2𝐷𝑆𝑒𝑥𝑖+ 𝛽3𝐷𝐹𝑏𝑜𝑟𝑛𝑖+ 𝛽4𝐷𝐴𝑓𝑟𝑖𝑐𝑎𝑖+ 𝛽5𝐷𝐴𝑠𝑖𝑎𝑖+
𝛽6𝐷𝐸𝑢𝑟𝑜𝑝𝑒𝑖+ 𝛽7𝐷𝑁_𝐴𝑛𝑒𝑟𝑖𝑐𝑎𝑖+ 𝛽8𝐷𝑂𝑐𝑒𝑎𝑛𝑖𝑎𝑖+𝑖
(8)
No e ha he Sou h and Cen al Ame ican egion a iable was omi ed in o de o
con ol and a oid he ‘dummy- ap’ p oblem. The dummy a iable ap is a phenomenon in
which he independen a iables a e mul icollinea and wo o mo e a iables a e highly
co ela ed, i.e. one a iable can be p edic ed om he o he s. Mo eo e , based on Equa ions 7
and 8, he ollowing o ms o he hypo heses can be also e i ied:
H7: Female mig an s a e less educa ed han males.
H8: Fo eign-bo n mig an s a e less educa ed han na i e-bo n mig an s.
H9: Mig an s ha a e mo e educa ed a e olde han less educa ed mig an s.
H10: Male mig an s a e olde han emales.
H11: Fo eign-bo n mig an s a e younge han na i e-bo n mig an s.
3. Conduc ing esea ch and esul s
Table 1, 2 and 3 ep esen he co esponding esul s o ou es ima ions in each model.
In o de o ake accoun o he e ec o egional di e ences we ocus sepa a ely on mig an s
by egion o bi h and assume ha hey ha e di e en educa ional, age, gende and o igin o
bi h cha ac e is ics compa ed o he o he egions. In all obse ed logis ic (Logi ) eg ession
models (see Tables 1 and 2), he dependen a iable indica es he mig an s’ egion o bi h. A
he bo om sec ions o hese ables a e he p opo ion o a iances explained by he p edic o s
(measu ed by Cox and Shell’s, and Nagelke ke’s pseudo R2). Howe e , he R2 s a is ics o
hese models a e ela i ely small, hanks o a la ge numbe o obse a ions. Acco ding o he
Omnibus (F- es ) and HL- es s, he explained a iances in a se o da a a e signi ican ly
g ea e han he unexplained a iance.
In he case o A ica and Eu ope, we ound a signi ican nega i e ela ionship be ween
he educa ional a ainmen and he egion o bi h. Al hough he e ec o educa ion does no
seem o be la ge in No h, Sou h and Cen al Ame ica and Oceania, in hese models he e was
a posi i e co ela ion. In o he wo ds, A ican, Asian and Eu opean mig an s end o be less
educa ed han o he s. In he case o A ica, Asia, Oceania, and Sou h and Cen al Ame ica age
nega i ely associa ed wi h egion o bi h a iables, which indica es ha in hese egions
mig an s a e mo e likely o be younge han he o he egions. Ne e heless, i he e a e wo
mig an s and one o hem comes om Eu ope o No h Ame ica, he/she will be signi ican ly
olde han he o he .
Mo eo e , gende di e ences can be ound in only a ew cases. A ican mig an s end
o be male, wi h Eu opean and Sou h and Cen al Ame icans ending o be emale. Measu ing
he o igin o bi h di e ences, we can also claim ha Asian, and Sou h and Cen al Ame ican
mig an s a e signi ican ly mo e likely o be o eign-bo n. F om he esul s i can be claimed
ha No h Ame icans asylum seeke s and mig an s om Oceania end o be na i e-bo n.
Al hough, he s ong H1, H2, H3, H4, H5 and H6 hypo heses should be ejec ed, based on he
esul s i can be claimed ha he educa ional a ainmen , age, sex and he place o bi h o
mig an s ela e di e en ly o hei egion o bi h.
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Table 1. Resul s o he bina y logis ic (logi ) eg essions in he examined OECD coun ies in
A ica, Asia and Eu ope
Dependen
DA ica
DAsia
DEu ope
Independen
Be a
Wald
EXP(B)
Be a
Wald
EXP(B)
Be a
Wald
EXP(B)
Cons an
-20.98
0.001
0
-4.281
1072.6***
0.013
1.493
1259.2***
4.452
Edu
-0.011
31.6***
0.989
0.001
0.238
1.001
-0.008
21.2***
0.991
Age
-0.027
215.9***
0.974
-0.012
40.8***
0.988
0.038
539.3***
1.039
DSex
-0.048
50.4***
0.953
-0.005
0.471
0.995
0.016
6.7***
1.016
DFbo n
20.011
0.001
0
3.138
582.6***
23.04
-2.503
3893.2
0.081
Obse a ions
491813
Cox and Shell R2
0.06
0.04
0.13
Nagaike R2
0.08
0.06
0.18
Omnibus- es
2766.5***
1984.6***
6346.1***
HL- es
103.2***
32.87***
212.6***
Sou ce: Au ho s’ own compila ion, based on (OECD, 2018)
No es: He e oscedas ici y obus Wald-s a is ics a e in pa en heses. Le e s in he uppe index e e o
signi icance: ***: signi icance a 1 pe cen , **: 5 pe cen , *: 10 pe cen . P- alues wi hou an index mean ha
he coe icien is no signi ican e en a he 10 pe cen le el. HL: Hosme and Lemeshow χ2 es .
Table 2. Resul s o he bina y logis ic (logi ) eg essions in he examined OECD coun ies in
No h Ame ica, Oceania and Sou h and Cen al Ame ica
Dependen
DN_Ame ica
DOceania
DS&C_Ame ica
Independen
Be a
Wald
EXP(B)
Be a
Wald
EXP(B)
Be a
Wald
EXP(B)
Cons an
-3.417
1423.1***
0.033
-2.755
1719.3***
0.064
-3.075
1870.3***
0.046
Edu
0.017
6.6**
1.017
0.029
56.4***
1.030
0.013
33.2***
1.013
Age
0.034
33.1***
1.035
-0.010
8.2***
0.990
-0.010
23.6***
0.990
DSex
-0.022
0.995
0.978
-0.001
0.003
0.999
0.046
35.6***
1.047
DFbo n
-0.834
113.9***
0.434
-0.246
16.3***
0.782
1.390
402.1***
4.016
Obse a ions
491813
Cox and Shell R2
0.01
0.01
0.01
Nagaike R2
0.02
0.02
0.02
Omnibus- es
134.3***
76.98***
711.5***
HL- es
9.123*
97.25***
7.854*
Sou ce: Au ho s’ own compila ion, based on (OECD, 2018)
No es: He e oscedas ici y obus Wald-s a is ics a e in pa en heses. Le e s in he uppe index e e o
signi icance: ***: signi icance a 1 pe cen , **: 5 pe cen , *: 10 pe cen . P- alues wi hou an index mean ha
he coe icien is no signi ican e en a he 10 pe cen le el. HL: Hosme and Lemeshow χ2 es .
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Measu ing he e ec s o aging, gende , and egion o bi h di e ences on educa ional
a ainmen o mig an s (in Models 1 and 2), based on Equa ion 7, can also p o ide e icien
empi ical ools o egional mig a ion policy e o ms. Thus, using Equa ion 8 in ou
eg ession models (3 and 4), he in luence o hese examined a iables on he age o
immig an s is also es ed in a egional con ex . In he case o Models 2 and 4 we only add he
a iables which we e signi ican in Models 1 and 3; he o he s a e omi ed. Howe e , he
adjus ed R2 alues a e qui e low because o he la ge numbe o obse a ions (491,813); he
signi ican F- es s a is ics sugges ha ou linea eg ession speci ica ion should be p e e ed
in all models. The mul i-collinea i y amongs he independen and con ol a iables is es ed
by he a iance in la ion ac o (VIF) in each case. The maximum alues o VIF o each
eg ession coe icien ange om a low o 1.181 o a high o 1.971. This sugges s ha he VIF
alues a e a accep able (less han 10) le els (Hai , 2010). A he bo om sec ion o Table 3, as
a goodness o i (GOF) es o ou eg ession he Kolmogo o –Smi no (K-S) no mali y es s
o he non-s anda dized esiduals a e also epo ed, o check one o he assump ions o he
linea eg ession.
Table 3. Resul s o he OLS eg essions o Equa ions 7 and 8 in he OECD coun ies
examined
Independen a iables
Model 1
Model 2
Model 3
Model 4
Cons an
3.163***
3.172***
3.885***
3.894***
117.981
306.573
181.981
136.407
Edu
0.081***
0.081***
50.744
50.737
Age
0.064***
0.064***
50.744
50.857
DSex
-0.034***
-0.034***
0.007
(-7.115)
(-7.148)
1.229
DFbo n
0.008
-0.101***
-0.101***
0.321
(-3.612)
(-3.611)
DA ica
-0.057***
-0.058***
-0.043***
-0.041***
(-7.508)
(-7.891)
(-4.946)
(-6.002)
DAsia
-0.031***
-0.031***
-0.002
(-4.029)
(-4.293)
(-0.236)
DEu ope
-0.049
-0.051***
0.125***
0.126***
(-6.831)
(-7.278)
15.293
19.981
DN_Ame ica
0.014
0.148***
0.150***
-0.71
6.861
7.13
DOceania
0.045***
0.044***
-0.003
3.706
-3.669
(-0.252)
Obse a ions
491813
Adj. R2
0.06
0.06
0.07
0.07
F- es
344.18***
460.77***
407.21***
651.22***
VIF
1.971
1.821
1.971
1.181
No mali y es o he non-s anda dized esiduals
K-S es
0.123***
0.123***
0.083***
0.083***
Sou ce: own compila ion based on (OECD, 2018)
No es: He e oscedas ici y obus -s a is ics a e in pa en heses. Le e s in he uppe index e e o signi icance:
***: signi icance a 1 pe cen , **: 5 pe cen , *: 10 pe cen . P- alues wi hou an index mean ha he coe icien
is no signi ican e en a he 10 pe cen le el.
F om he egional pe spec i e, he age and educa ional a ainmen ela ed di e en ly o
he egion o bi h. Fo example, as we ound p e iously, A ican, Asian and Eu opean
205
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Józse Popp, Judi Oláh
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UN. (2017). Uni ed Na ions S a is ics Di ision - Classi ica ions Regis y, ISIC Re . 4.
UNESCO. (2011). In e na ional S anda d Classi ica ion o Educa ion
(UIS/2012/INS/10/REV). UNESCO Ins i u e o S a is ics.
Uni ed Na ions. (2017). In e na ional Mig a ion Repo 2017.
an Dalen, H. P., & Henkens, K. (2012). Explaining low in e na ional labou mobili y: he
ole o ne wo ks, pe sonali y, and pe cei ed labou ma ke oppo uni ies. Popula ion,
Space and Place, 18(1), 31-44. h ps://doi.o g/10.1002/psp.642
Williams, A. M., Jephco e, C., Jan a, H., & Li, G. (2018). The mig a ion in en ions o young
adul s in Eu ope: A compa a i e, mul ile el analysis. Popula ion, Space and Place,
24(1), e2123. h ps://doi.o g/10.1002/psp.2123
Zaice a, A. (2014). The impac o aging on he scale o mig a ion (99). IZA Wo kd o Labo .
h ps://doi.o g/doi: 10.15185/izawol.99

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Appendix
Table A.1. Desc ip i e s a is ics o he examined a iables
Minimum
Maximum
Mean
S d. De ia ion
Skewness
Ku osis
S a is ic
S a is ic
S a is ic
S a is ic
S a is ic
S d. E o
S a is ic
S d. E o
Age
1
7
4.13
1.863
-.013
.003
-1.116
.006
Edu
1
6
3.35
1.667
.095
.003
-1.239
.007
DSex
1
2
1.50
.500
-.002
.003
-2.000
.006
DFbo n
0
1
.99
.098
-9.988
.003
97.751
.006
DA ica
0
1
.23
.423
1.266
.003
-.398
.006
DAsia
0
1
.23
.421
1.281
.003
-.359
.006
DEu ope
0
1
.30
.458
.875
.003
-1.234
.006
DN_Ame ica
0
1
.02
.127
7.635
.003
56.298
.006
DOceania
0
1
.05
.220
4.084
.003
14.683
.006
DS&C_Ame ica
0
1
.16
.370
1.822
.003
1.318
.006
Sou ce: own compila ion based on (OECD, 2018)
Table A.2. Pea son co ela ion ma ix o he examined a iables
Edu
Age
DSex
DFbo n
DA ican
DAsian
DEu opean
DN_A.
DOceanian
Edu
1.000
Age
0.072***
1.000
DSex
-0.01**
0.001
1.000
DFbo n
0.000***
-0.009***
0.000
1.000
DA ica
-0.009***
-0.022***
-0.01***
0.054***
1.000
DAsia
0.000
-0.01***
0.000
0.05***
-0.3***
1.000
DEu ope
-0.004***
0.034***
0.004***
-0.114***
-0.362***
-0.361***
1.000
DN_Ame ica
0.004***
0.009***
0.000
-0.016***
-0.072***
-0.071***
-0.086***
1.000
DOceania
0.01***
-0.003**
0.001
-0.006***
-0.126***
-0.126***
-0.152***
-0.03***
1.000
Sou ce: own compila ion based on (OECD, 2018)
No es: Le e s in he uppe index e e o signi icance: ***: signi icance a 1 pe cen , **: 5 pe cen , *: 10 pe
cen . P- alues wi hou an index mean ha he coe icien is no signi ican e en a he 10 pe cen le el.