Regional Determinants of Attitudes Toward Immigrants in Germany

Pe e , Julia; Uebelmesse , Silke
A icle — Published Ve sion
Regional De e minan s o A i udes Towa d Immig an s in
Ge many
Jou nal o Regional Science
P o ided in Coope a ion wi h:
John Wiley & Sons
Sugges ed Ci a ion: Pe e , Julia; Uebelmesse , Silke (2025) : Regional De e minan s o A i udes
Towa d Immig an s in Ge many, Jou nal o Regional Science, ISSN 1467-9787, Wiley, Hoboken, NJ,
Vol. 65, Iss. 3, pp. 780-817,
h ps://doi.o g/10.1111/jo s.12763
This Ve sion is a ailable a :
h ps://hdl.handle.ne /10419/323882
S anda d-Nu zungsbedingungen:
Die Dokumen e au EconS o dü en zu eigenen wissenscha lichen
Zwecken und zum P i a geb auch gespeiche und kopie we den.
Sie dü en die Dokumen e nich ü ö en liche ode komme zielle
Zwecke e iel äl igen, ö en lich auss ellen, ö en lich zugänglich
machen, e eiben ode ande wei ig nu zen.
So e n die Ve asse die Dokumen e un e Open-Con en -Lizenzen
(insbesonde e CC-Lizenzen) zu Ve ügung ges ell haben soll en,
gel en abweichend on diesen Nu zungsbedingungen die in de do
genann en Lizenz gewäh en Nu zungs ech e.
Te ms o use:
Documen s in EconS o may be sa ed and copied o you pe sonal
and schola ly pu poses.
You a e no o copy documen s o public o comme cial pu poses, o
exhibi he documen s publicly, o make hem publicly a ailable on he
in e ne , o o dis ibu e o o he wise use he documen s in public.
I he documen s ha e been made a ailable unde an Open Con en
Licence (especially C ea i e Commons Licences), you may exe cise
u he usage igh s as speci ied in he indica ed licence.
h p://c ea i ecommons.o g/licenses/by/4.0/
Jou nal o Regional Science
RESEARCH ARTICLE
Regional De e minan s o A i udes Towa d Immig an s
in Ge many
Julia Pe e
1
| Silke Uebelmesse
1,2
1
F ied ich Schille Uni e si y Jena, Jena, Ge many |
2
CESi o, Munich, Ge many
Co espondence: Julia Pe e ([email p o ec ed])
Recei ed: 26 Ap il 2024 | Re ised: 13 No embe 2024 | Accep ed: 17 Feb ua y 2025
Funding: This wo k is suppo ed by he F ee S a e o Thu ingia and he Eu opean Social Fund (G an Numbe WBV180515).
Keywo ds: a i udes | economic conce ns | immig an s | labo ma ke | policy p e e ences | egional de e minan s | wel a e s a e
ABSTRACT
A i udes owa d immig an s play a c ucial ole in o ing beha io . Such a i udes a e shaped by indi idual cha ac e is ics, bu
also by he en i onmen . This pape examines he ole o egional ac o s in Ge many. We use indi idual‐le el su ey da a and
dis ic ‐le el adminis a i e da a. Speci ically, we examine egional di e ences in economic g ow h, o ing pa e ns, and
immig an cha ac e is ics and hei ela ion o belie s abou and a i udes owa d immig an s. We also use an in o ma ion
expe imen abou he immig an popula ion and assess i s impac on a i udes. We ind ha egional e ec s—o e and abo e
indi idual cha ac e is ics—a e small and depend on he a i udes.
JEL Classi ica ion: C90, D83, F22, J15, R11, R23
1 | In oduc ion
Public a i udes owa d immig an s emain a complex and
mul i ace ed issue, in luenced by a combina ion o economic,
poli ical, and social ac o s. Recen wa es o immig a ion ha e
spa ked con o e sial deba es among he public and policy-
make s in hos coun ies (Halla e al. 2017; Dus mann e al.
2019; Tabellini 2020). A i udes a e likely o be an impo an
de e minan o o ing beha io and policy choices, pa icula ly
in ela ion o immig a ion. They can be linked o conce ns
abou labo ma ke compe i ion and nega i e e ec s on he
wel a e s a e (Mayda 2006). Howe e , people o en lack accu-
a e and comple e in o ma ion abou he immig an popula ion
and he impac o immig an s on he hos economy (Dus mann
and P es on 2007; Facchini and Mayda 2009; O ega and
Pola ieja 2012; Pola ieja 2016). Indi idual cha ac e is ics a e
impo an de e minan s o hese belie s and he esul ing a i-
udes owa d immig an s, bu he egional en i onmen in
which an indi idual li es can also con ibu e o bo h belie s and
a i udes (Ma kaki and Longhi 2013).
Indi iduals o en iden i y wi h he egion in which hey li e,
and his can shape hei sense o iden i y and hei a i udes.
Addi ionally, a pe son's indi idual ou comes can be in luenced
by he economic and social en i onmen o hei egion
(P oshansky e al. 1983; Paasi 2002; Rus enbach 2010; K eme
2022), ha is, one's place o bi h and la e he neighbo hood
can be p edic i e o u u e economic ou comes (Kling e al.
2007; Bosque and O e man 2019). Mo eo e , McNeil e al.
(2023) show ha he economic si ua ion a he bi hplace can
shape a i udes owa d go e nmen al in e en ions and o ing
beha io .
The aim o his pape is o explo e how egional cha ac e is ics
o he economic and poli ical en i onmen and he immig an
popula ion shape indi iduals' a i udes owa d immig an s and
how hese a i udes can be changed by p o iding in o ma ion
abou he immig an popula ion in Ge many.
1
So a , he li -
e a u e on a i udes owa d immig an s has mainly ocused on
indi idual‐le el de e minan s (see Mayda 2006; Alesina e al.
2023; Dylong and Uebelmesse 2024). We aim o ex end his
This is an open access a icle unde he e ms o he C ea i e Commons A ibu ion License, which pe mi s use, dis ibu ion and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly
ci ed.
© 2025 The Au ho (s). Jou nal o Regional Science published by Wiley Pe iodicals LLC.
780 o 886Jou nal o Regional Science, 2025; 65:780–817
h ps://doi.o g/10.1111/jo s.12763
li e a u e by shedding ligh on he ole o egional and, in
pa icula , dis ic ‐le el de e minan s o indi idual belie s
abou he cha ac e is ics o he immig an popula ion and he
esul ing indi idual a i udes owa d immig an s wi h espec o
he wel a e s a e and labo ma ke compe i ion as well as iews
on immig a ion ad an ages and p e e ences o immig a ion
policy. We use da a om wo la ge‐scale ep esen a i e su eys
o he Ge man popula ion, conduc ed in 2020 and 2021, wi h a
o al numbe o obse a ions o mo e han 5700 pa icipan s
which we combine wi h adminis a i e da a a he dis ic le el.
Ou analysis consis s o h ee s eps: i s , we examine he
egional de e minan s o belie s abou immig an s. We hen
examine how hese belie s and o he indi idual‐le el a iables
a ec indi idual a i udes owa d immig an s and policy p e -
e ences, paying pa icula a en ion o he ole o he egional
en i onmen . Finally, we use an in o ma ion p o ision expe i-
men in which esponden s we e p o ided wi h in o ma ion
abou he cha ac e is ics o he immig an popula ion in
Ge many. Because egional cha ac e is ics may shape indi id-
ual belie s and a i udes, he e ec o p o iding in o ma ion
abou he immig an popula ion may also a y by egion.
Responden s om di e en egions may be mo e o less
ecep i e o he in o ma ion and d aw di e en conclusions. In
pa icula , we a e in e es ed in economic and poli ical di e -
ences, as well as di e ences in he cha ac e is ics o he
immig an popula ion.
We hypo hesize ha he local economy may play a ole in
shaping a i udes owa d immig a ion. The unde lying mecha-
nism may ope a e h ough he a ailabili y o jobs in a egion,
whe e esponden s om dis ic s wi h highe economic ou pu
and mo e a ailable jobs may be less conce ned abou labo
ma ke compe i ion om immig an s o ad e se e ec s on he
wel a e s a e. In addi ion, a i udes may a y depending on
whe he a dis ic is expe iencing economic g ow h o down-
u n. Mo e gene ally, imes o c isis, like he COVID‐19 pan-
demic, may ha e a ec ed egions di e en ly leading o di e en
p ospec s o he u u e. O e all, as a consequence, conce ns
may inc ease in less p ospe ous egions wi h less posi i e ou -
looks, which may ansla e in o less suppo i e iews on
immig a ion (Pou aa a and S einha d 2018). Simila ly, he
e ec o p o iding in o ma ion on esponden s' a i udes may
depend on he egional economy.
In addi ion o economic di e ences, o he egional aspec s can
be associa ed wi h a i udes owa d immig an s, abo e all
poli ical di e ences. Mos pa ies ha e immig a ion as pa o
hei pa y pla o ms, bu wi h di e en emphases. Clea ly an i‐
immig a ion pla o ms a e widesp ead among Ge man igh ‐
wing pa ies (Ma x and Naumann 2018). One example is he
Al e na i e o Ge many (A D), which has a clea a ‐ igh and
populis agenda wi h a s ong an i‐immig a ion ocus. This
pa y won 10.3% o he o es in he las ede al elec ion in 2021
(The Fede al Re u ning O ice 2023).
2
A he dis ic le el, he
sha e o he o es anged om 2.8% in he ci y o Müns e
(No h Rhine‐Wes phalia) o 32.5% in he dis ic o Gö li z
(Saxony). In pa icula , “le ‐behind” egions (Fo d and
Goodwin 2017) and egions expe iencing economic ha dship
show an inc ease in igh ‐wing populis o ing (Gozgo 2022).
3
Thus, a egion's poli ical en i onmen may also in luence
na a i es abou immig a ion and shape a i udes. Fu he mo e,
esponden s om igh ‐leaning egions may be less esponsi e
o in o ma ion abou he immig an popula ion and hus less
likely o adjus hei a i udes.
Ano he dimension o ou analysis conce ns egional di e -
ences in he cha ac e is ics o he immig an popula ion. We
ope a ionalize his by looking a he egional sha e o immi-
g an s, he egional unemploymen a e o immig an s, and he
egional sha e o e ugees in he immig an popula ion. Ac-
co ding o he con ac hypo hesis, con ac wi h immig an s can
change indi idual a i udes (Allpo 1958; Pe ig ew 1998;
Paluck e al. 2019). Ge man egions di e in he sha e o
immig an s, wi h egions in he wes e n pa s o Ge many
ha ing highe sha es compa ed o he eas e n pa s o Ge many.
The e o e, a highe p esence o immig an s in one's own egion
may also con ibu e o shaping indi idual a i udes and may
a ec he need o —and he esponsi eness o—in o ma ion
abou he immig an popula ion.
We aim o p o ide insigh s in o he ole o hese dis ic ‐le el
cha ac e is ics in he belie s abou and he a i udes owa d he
immig an popula ion by ocusing on he ela ionship wi h
indi idual‐le el cha ac e is ics. We ind e idence ha egional
cha ac e is ics a e co ela ed wi h he o ma ion o belie s abou
immig a ion. Responden s li ing in egions wi h a highe sha e
o immig an s end o ha e highe and mo e biased belie s o
he sha e o immig an s in Ge many, while esponden s li ing
in egions wi h a highe unemploymen a e o immig an s hold
lowe , and less biased belie s o he unemploymen a e among
immig an s. When examining dis ic ‐le el cha ac e is ics and
a i udes owa d immig a ion, we obse e ha esponden s in
mo e densely popula ed dis ic s end o see mo e he bene i s
o immig a ion. Con e sely, hose in mo e igh ‐wing dis ic s
iew mo e he disad an ages linked o immig a ion and con-
side immig an s as a bu den on he wel a e s a e. Howe e , he
signi ican egional co ela ions a e mos ly o se when we
in oduce indi idual‐le el co a ia es. Thus, he egional impac
beyond indi idual cha ac e is ics is ela i ely small and
depends on he ou come examined. P o iding in o ma ion
abou he immig an popula ion gene ally leads o mo e posi-
i e a i udes owa d immig a ion. The changes in a i udes a e
g ea e in egions wi h lowe A D o e sha es and highe eco-
nomic g ow h. The esul s o he egional sha e o immig an s
a e mo e mixed.
O e all, while he co ela ional e idence poin s o a ole o he
egional en i onmen , we mus e ain om a causal in e p e-
a ion o ou egional‐le el indings ega ding biases in p io
belie s and conce ns abou immig a ion. The egional en-
i onmen may shape indi idual a i udes, bu a he same ime,
indi iduals may shape he cha ac e is ics o hei egional en-
i onmen . Mo eo e , indi iduals, bo h na i es and immig an s,
a e no andomly dis ibu ed ac oss egions. Ra he , hey
choose o li e in pa icula places acco ding o ce ain indi-
idual and egional cha ac e is ics. We will e u n o his issue
la e .
The emainde o he pape is o ganized as ollows. Sec ion 2
discusses he li e a u e. Sec ion 3p esen s ou da a. In
Sec ion 4, we gi e an o e iew o he desc ip i e s a is ics and
781 o 886
ins i u ional se ing. The empi ical model is explained in
Sec ion 5and ou esul s a e discussed in Sec ion 6. Sec ion 7
concludes.
2 | Li e a u e
Ou pape ela es o se e al s ands o he li e a u e. Fi s ,
economic s udies o en ocus on indi idual de e minan s o
a i udes owa d immig an s. Bu a pe son's egional and social
en i onmen also con ibu es o shaping a i udes. Czaika and
Di Lillo (2018) show ha an i‐immig an a i udes a e spa ially
linked ac oss Eu ope. In o he wo ds, close egions ha e mo e
simila a i udes han mo e dis an egions. Howe e , he eco-
nomic li e a u e is a he spa se on his poin . Ha on (2016)
inds ha he sha e o immig an s and he sha e o social
bene i s in GDP play an impo an ole o a i udes owa d
immig an s. Bo h a highe sha e o immig an s and a highe
sha e o social bene i s in GDP a e associa ed wi h mo e neg-
a i e a i udes. B enne and Fe ig (2006) ind ha a e age a -
i udes owa d immig an s in a coun y a e posi i ely co ela ed
wi h GDP pe capi a. Fo La ia, I Ie s (2012) shows ha
people om egions wi h lowe local bi h a e end o ha e
mo e posi i e iews on immig a ion. F a esi e al. (2019) ana-
lyze he dis ibu ion o asylum seeke s in I aly, whe e hey show
ha economic and poli ical cha ac e is ics o he p o inces a e
associa ed wi h he willingness o hos asylum seeke s. Gallegos
To es (2023) inds ha conce ns abou immig an s in Ge many
declined in dis ic s wi h a highe sha e o asylum seeke s a e
he in lux o e ugees in 2015. Simila ly, o I aly, Gamale io
e al. (2023) ha e linked he p esence o locally adminis e ed
e ugee cen e s in municipali ies o lowe le els o igh ‐wing
o ing and p ejudice. Con e sely, Hanga ne e al. (2019) ind
ha esiden s o a G eek island wi h highe exposu e o e u-
gees de eloped las ing nega i e a i udes owa d immig an s.
O he s udies ind a link be ween egional cha ac e is ics and
poli ical a i udes mo e b oadly. In he con ex o he B exi
e e endum, Becke e al. (2017) ind ha a he dis ic ‐le el,
people in a eas wi h lowe incomes and employmen we e mo e
likely o o e o lea e he Eu opean Union. Simila ly, Dijks a
e al. (2020) show ha indi iduals in s uc u ally weak egions
a e mo e opposed owa d EU poli ics. Mo eo e , Lechle (2019)
uses panel da a eg ession and an ins umen al a iable
app oach o show ha , in pa icula , unemployed and low‐
skilled indi iduals li ing in egions wi h a highe sha e o
immig an s om EU membe s a es ha e nega i e a i udes
owa d he Eu opean Union. En o and Lange (2023) a ibu e
ha e c imes, as a o m o an i‐immig an a i udes, o a eas wi h
low sha es o immig an s and a his o ical pa e n o igh ‐wing
o ing. Mo eo e , Mehic (2022) inds ha municipali ies in
Sweden wi h a his o y o an i‐immig an a i udes a e mo e
likely o o e o igh ‐wing populis pa ies. Ou pape con-
ibu es o his s and o li e a u e by p o iding insigh s in o he
ole o egional cha ac e is ics o a i udes owa d immig an s
in Ge many.
Second, he e a e s udies ha ocus on how economic ci cum-
s ances a ec people's a i udes owa d immig an s, especially
du ing imes o economic c isis. Kun z e al. (2017) show ha
an i‐immig an sen imen inc eases when people pe cei e
g ea e economic insecu i y. McGinni y and Kings on (2017)
ind ha in I eland, a i udes owa d immig an s became mo e
nega i e as unemploymen inc eased du ing he inancial c isis.
They also show ha a ecession pa icula ly a ec s he a i udes
o he less educa ed. Ano he aspec is highligh ed by Dancygie
and Donnelly (2013), who ake a look a he inancial c isis o
2008. They show ha in imes o economic ha dship, in-
di iduals educe hei suppo o immig a ion i hei em-
ploymen sec o expe iences an in lux o immig an s. The
poli ical science li e a u e emphasizes ha a i udes owa d
immig an s a e shaped no only by economic conside a ions bu
also by no m‐based and cul u al conce ns. S udies show ha
people a e mo e conce ned abou he cul u al implica ions o
immig a ion in hei coun y han abou i s economic e ec s,
such as he impac on labo ma ke compe i ion and he
edis ibu ion o esou ces wi hin he wel a e s a e
(Hainmuelle and Hopkins 2014; Bansak e al. 2016;
Hainmuelle and Hiscox 2007,2010; Hainmuelle and Hopkins
2015; Snide man e al. 2004; Bas iaens and Pos niko 2020).
This pe spec i e also highligh s ha indi iduals hold s e eo-
ypes and p ejudices agains immig an s (Bu ns and Gimpel
2000; Hjo h 2016). In his pape , we conside economic a io-
nales which may ope a e h ough he local economy and labo
ma ke , bu we also conside he poli ical leanings o a egion
and he cha ac e is ics o he immig an popula ion, bo h o
which may highligh di e en noneconomic a ionales.
Thi d, s udies ha use su ey expe imen s wi h in o ma ion
p o ision in he con ex o mig a ion a emp o coun e gi en
mispe cep ions. Such expe imen s a e equen ly conduc ed in
economics and poli ical science. In gene al, hese s udies show
ha p o iding in o ma ion abou he immig an popula ion can
imp o e people's belie s abou immig a ion and make hem
mo e suppo i e o immig a ion policies (see, e.g., G igo ie
e al. 2020; Haaland and Ro h 2020; Facchini e al. 2022; Dylong
and Uebelmesse 2024 in he economics li e a u e o
Hainmuelle and Hiscox 2010,2007; and Hanga ne e al. 2019
in he poli ical science li e a u e). Alesina e al. (2023) do no
ind ha esponden s change hei suppo o edis ibu ion
a e being p o ided wi h s a is ical in o ma ion abou he
immig an popula ion. Howe e , in o ma ion in he o m o
na a i es shapes people's a i udes owa d immig a ion.
Agains he backg ound o demog aphic change, Boe i e al.
(2024) p o ide in o ma ion abou he unc ioning o he pension
sys em o see how his a ec s a i udes owa d immig an s. This
in e en ion was only e ec i e o esponden s who did no
iden i y wi h an i‐immig an and populis poli ical mo emen s.
We add o his li e a u e by p o iding insigh s in o egional
di e ences in he ea men e ec s o in o ma ion p o ision.
Mo eo e , he abo e su ey expe imen s also documen ha
indi iduals hold biased belie s abou he immig an popula ion,
ha is, inaccu a e es ima es o he sha e o immig an s o o he
indica o s, and ha hese a e impo an d i e s o a i udes.
This links o he li e a u e on immig an innume acy. Mis-
pe cep ions abou mino i y g oups a e sys ema ic and wide-
sp ead, and can lead o eelings o h ea (He da and Di adka
2023). O e es ima ion is ypically associa ed wi h p e e ences
o a mo e es ic i e immig a ion policy (Ci in and Sides 2008;
Go odzeisky and Semyono 2020; Lu z and Bi schnau 2023).
He da (2010) shows ha innume acy is d i en among o he s by
782 o 886 Jou nal o Regional Science, 2025
exposu e o immig an s in he neighbo hood and wa ching
ele ision. The local con ex o an indi idual can ma e o he
accu acy o es ima es, as shown by Wong (2007) o he Uni ed
S a es. In his pape , we highligh he ela ionship be ween he
accu acy o indi idual pe cep ions and he egional en i on-
men including he cha ac e is ics o he immig an popula ion.
Fu he mo e, he pe cei ed eeling o h ea may also ansla e
in o wel a e chau inis ic a i udes owa d immig an s, in pa -
icula lowe p e e ences o edis ibu ion (Ca eja and Ha is
2022). This li e a u e inds ha hese a i udes depend on he
gene osi y o he wel a e s a e (Die meie e al. 2021), indi idual
cha ac e is ics (Hjo h 2016; Fo d and Goodwin 2017) and
economic condi ions (Bell e al. 2023). By ocusing on a i udes
owa d he wel a e s a e and iews on immig a ion ad an ages
as wo o ou ou ou comes, we also pu some emphasis on his
aspec .
3 | Da a and Expe imen al Design
In ou analysis, we aim no only o cap u e indi idual‐le el
de e minan s o belie s abou and a i udes owa d immig an s,
bu also o ocus on egional cha ac e is ics and how hey ela e
o indi idual‐le el ou comes. We use indi idual‐le el da a om
wo ep esen a i e su eys o he Ge man popula ion and
ma ch hem wi h dis ic ‐le el da a based on NUTS‐3 egions.
The e a e 401 dis ic s in Ge many, o which 294 a e coun ies
(Landk eise) and 107 a e independen ci ies (K eis eie S äd e).
In o al, ou da a se consis s o 5698 indi iduals om all 401
Ge man dis ic s. In he su ey and he egional da a, an
immig an is de ined as a pe son li ing in Ge many who does
no ha e Ge man ci izenship. He e we ollow he de ini ion o
he Fede al S a is ical O ice (Fede al S a is ical O ice 2024).
See Table A1 in he appendix o a desc ip ion o he a iables
and Table A3 o summa y s a is ics.
3.1 | Dis ic ‐Le el Da a
In addi ion o indi idual‐le el ac o s, he egional en i onmen
may shape indi iduals' belie s and a i udes. We use adminis-
a i e da a o he 401 coun ies in Ge many. Dis ic ‐le el da a
a e ob ained om INKAR (BBSR Bonn 2023) and he s a is ical
o ices o he ede al and s a e go e nmen s (S a is ical O ices
o he Fede al and S a e Go e nmen s 2024). Ou se o dis ic ‐
le el co a ia es includes indica o s o egional cha ac e is ics
o he immig an popula ion as well as economic and poli ical
cha ac e is ics. Fo immig an popula ion cha ac e is ics, we
epo he sha e o immig an s, he unemploymen a e o
immig an s, and he sha e o e ugees in he immig an popu-
la ion, all o 2020 and a he dis ic le el. To cap u e economic
condi ions, we include GDP pe capi a in 2020 o highligh a
dis ic 's o e all economic ou pu , and egional g ow h in GDP
pe capi a om 2019 o 2020 o accoun o changes in ou pu in
he dis ic . Fo he poli ical dimension, we use he dis ic ‐le el
o e sha e o he igh ‐wing A D pa y in he 2021 ede al
elec ion. Wi h his a iable, we aim o p oxy he poli ical cli-
ma e and o ing beha io in a dis ic wi h espec o igh ‐wing
pa ies wi h an i‐immig an pla o ms. In addi ion, we include
popula ion densi y measu ed in inhabi an s pe km
2
o each
dis ic in 2020 o cap u e whe he esponden s li e in u al o
u ban a eas. We also include an Eas Ge man dummy o
accoun o di e ences be ween Eas and Wes Ge many.
3.2 | Indi idual‐Le el Da a
Da a on indi idual‐le el cha ac e is ics come om wo la ge‐
scale ep esen a i e su eys on a i udes owa d immig an s in
Ge many, conduc ed in No embe /Decembe 2020 and Sep-
embe 2021 among he Ge man adul popula ion. The su eys
a e ep esen a i e in e ms o age, gende , educa ion, and es-
idence in Eas o Wes Ge many. The da a se includes a iables
on he assessmen o he gene al economic si ua ion, belie s
abou immig a ion, economic conce ns abou immig a ion, and
immig a ion policy p e e ences, a iables on he COVID‐19
c isis, and a la ge numbe o socio‐demog aphic cha ac e -
is ics.
4
In o med consen was gi en by all pa icipan s a he
beginning o he su ey; his was a p e equisi e o s a ing he
su ey.
3.3 | Expe imen al Design
In addi ion, he ep esen a i e su eys include an in o ma ion
p o ision expe imen . In he i s s ep, we elici p io belie s
abou he immig an popula ion in Ge many and hus a he
na ional le el. Responden s a e asked abou he sha e o
immig an s and he unemploymen a e o immig an s in
Ge many. We calcula e he absolu e bias in p io belie s as he
di e ence be ween he ac ual alue and he esponden s'
es ima es.
In he second s ep, esponden s a e andomly assigned o one o
h ee ea men g oups o o he con ol g oup. In he i s
ea men g oup, esponden s a e p o ided wi h in o ma ion
on he ac ual sha e o immig an s in Ge many. In he second
ea men g oup, esponden s a e p o ided wi h in o ma ion on
he ac ual unemploymen a e o immig an s in Ge many.
Finally, indi iduals in he hi d ea men g oup ecei e in o -
ma ion on bo h he sha e o immig an s and he unemploymen
a e o immig an s. The con ol g oup ecei es no in o ma ion.
5
In he hi d s ep o he expe imen , esponden s answe ques-
ions abou hei a i udes owa d immig an s and policy p e -
e ences. The ques ions and esponses a e as ollows:
•Wel a e s a e a i udes: “Immig an s pay axes and ecei e
social bene i s om he heal h ca e and social insu ance
sys ems. On balance, do you hink ha immig an s in
Ge many ecei e mo e social bene i s han hey pay axes,
o ha hey pay mo e axes han hey ecei e social bene-
i s?”Answe s: “Recei e mo e social bene i s”(0) o “Pay
mo e axes”(10).
•Labo ma ke a i udes: “Do you hink ha immig an s
a he ake away jobs om wo ke s in Ge many, o ha
hey a he help o c ea e new jobs?”Answe s: “Take jobs
away”(0) o “C ea e new jobs”(1).
783 o 886

•Immig a ion (dis‐)ad an age: “Do you hink immig an s
ha e c ea ed mo e disad an ages o mo e ad an ages o
Ge many in he las 10 yea s? Answe s: “mo e dis-
ad an ages”(0) o “mo e ad an ages”(10).
•Immig a ion policy p e e ences: “Do you hink ha he
numbe o immig an s coming o Ge many each yea
should be:”Answe s: “dec eased a lo /dec eased sligh ly/
s ay he same/inc eased sligh ly/inc eased a lo ?”
The ou come a iables a e coded so ha highe alues indica e
mo e posi i e a i udes. We measu e a i udes owa d he wel-
a e s a e and a i udes owa d he labo ma ke as well as
immig a ion (dis)ad an age on an 11‐poin scale. Immig a ion
policy p e e ences a e measu ed on a 5‐poin scale.
4 | Desc ip i e S a is ics
In he ollowing, we p esen desc ip i e s a is ics on he
egional con ex in Ge many and on belie s abou immig an s.
In pa icula , we ocus on how indi idual belie s as well as
economic and poli ical cha ac e is ics and cha ac e is ics o he
immig an popula ion di e ac oss dis ic s. Desc ip i e s a is-
ics a e p esen ed in Table A3 in he appendix.
4.1 | Regional He e ogenei y
Ge man egions di e subs an ially when i comes o economic
and poli ical indica o s bu also cha ac e is ics o he immig an
popula ion. Those di e ences a e u he desc ibed below
oge he wi h some in o ma ion abou he ins i u ional se ing.
Figu e 1a shows he egional dis ibu ion o he A D's sha e o
he o e in he ede al elec ion in Sep embe 2021. The Al e -
na i e ü Deu schland (A D) was ounded in 2013 wi h a con-
se a i e and Eu oscep ic ocus. In he wake o he 2015 e ugee
c isis, he pa y shi ed o he a igh wi h a populis agenda
and a s ong an i‐immig a ion ocus. The pa y en e ed he
Ge man pa liamen in 2017, whe e i became he hi d la ges
pa y and he la ges opposi ion pa y. O e he yea s, he pa y
has mo ed u he o he igh . I is also ep esen ed in s a e and
local go e nmen s. The pa y has been pa icula ly success ul in
eas e n Ge many, bu also in he sou h and sou h‐wes o he
coun y (Fede al Agency o Ci ic Educa ion 2024). This Eas –
Wes di ide is also clea ly isible in Figu e 1a. The pa y did
be e in eas e n Ge many han in o he pa s o he coun y,
wi h i s highes o e sha e o a ound 30% in eas e n and
sou he n Saxony. We expec a posi i e ela ionship be ween he
A D o e sha e and belie s abou immig a ion, i.e. highe es i-
ma es o he sha e and he unemploymen a e, and a nega i e
ela ionship wi h a i udes owa d immig an s as well as policy
p e e ences.
6
Ge man egions also di e in e ms o economic pe o mance,
as measu ed by GDP pe capi a g ow h and shown in Figu e 1b.
Ou su eys we e conduc ed du ing he COVID‐19 pandemic in
2020 and 2021, a pe iod cha ac e ized by signi ican economic
u bulence. Du ing his ime, Ge many expe ienced a p o-
nounced economic slowdown, ma ked by a decline in GDP and
widesp ead dis up ion ac oss a ious indus ies. The impac o
he pandemic was no uni o m. Di e en sec o s o he econ-
omy we e a ec ed o di e en deg ees. Fo example, he ou -
ism and hospi ali y sec o s we e pa icula ly ha d hi by a el
es ic ions and lockdowns, leading o a signi ican decline in
business ac i i y and a sha p ise in unemploymen . The
manu ac u ing sec o also su e ed om la ge supply chain
p oblems. In addi ion, he geog aphical concen a ion o eco-
nomic ac i i y in Ge many con ibu ed o egional di e ences
in he impac o he pandemic, wi h some a eas expe iencing
mo e se e e economic consequences han o he s (Ge man
Council o Economic Expe s 2020). Figu e 1b shows ha
egions wi h highe g ow h a es a e loca ed in he sou h‐eas
and no h o Ge many, while dis ic s wi h lowe g ow h a es
a e mainly in he cen e and sou h‐wes . GDP pe capi a ell by
a ound 12%–15% in dis ic s wi h a high densi y o manu-
ac u ing in Baden‐Wü embe g and Lowe Saxony and
inc eased by up o mo e han 9% in dis ic s in Ba a ia and
Lowe Saxony. Gi en he economic pe o mance o a dis ic ,
we expec a posi i e ela ionship be ween GDP pe capi a
g ow h and a i udes owa d immig an s as well as policy
p e e ences.
Figu e 1c,d shows ha he immig an popula ion and he sha e
o e ugees in he immig an popula ion a y conside ably
wi hin Ge many. Abou 13% o he Ge man popula ion a e
immig an s, ha is, people li ing in Ge many wi hou Ge man
ci izenship. The majo i y, a ound wo‐ hi ds, a e na ionals o
o he EU and Eu opean coun ies. In 2021, he la ges non‐
Eu opean immig an g oups we e na ionals om Tu key, Sy ia
and A ghanis an (Fede al O ice o Mig a ion and Re ugees
2024a). When immig an s mo e o Ge many, hey end o
concen a e in u ban a eas, bu also in a eas wi h a highe
sha es o ellow na ionals (Demog aphy Pla o m 2024). Since
2015, Ge many has also expe ienced a la ge in low o e ugees,
mainly om Sy ia and A ghanis an, and since 2022 also om
Uk aine (Fede al O ice o Mig a ion and Re ugees 2024a).
Asylum seeke s a e dis ibu ed ac oss he ede al s a es ac-
co ding o he “Königs ein Key,”which is based on he ax
e enues and popula ion o a ede al s a e (Fede al O ice o
Mig a ion and Re ugees 2024b). Hence, his esul s in a di e -
en egional composi ion o immig an s.
Figu e 1c shows ha he sha e o immig an s is highe in he
wes e n and sou he n pa s o Ge many, among o he easons
due o his o ical se lemen pa e ns o mo e a o able eco-
nomic condi ions. On he o he hand, he sha e o e ugees in
he immig an popula ion, as shown in Figu e 1d, is conside -
ably highe in he no he n and eas e n egions o Ge many,
despi e he lowe sha e o immig an s, acco ding o he ”Kö-
nigs ein Key.”As o he unemploymen a e o immig an s,
Figu e 1e shows ha i is ela i ely high in he eas and no h‐
eas o Ge many, despi e he lowe sha e o immig an s in hese
a eas. In line wi h he con ac hypo hesis (Allpo 1958), we
expec a highe sha e o e ugees and immig an s o be associ-
a ed wi h mo e a o able a i udes owa d immig an s and
policy p e e ences.
We ind some impo an co ela ions o he egional cha -
ac e is ics conside ed. Righ ‐wing o ing ends o occu mo e in
eas e n egions wi h lowe GDP g ow h pe capi a. The e, he
784 o 886 Jou nal o Regional Science, 2025
sha e o immig an s is ela i ely low, while he sha e o e u-
gees is a he high as is he unemploymen a e o immig an s.
All o his may shape he belie s and a i udes o esponden s
di e en ly om o he Ge man egions.
4.2 | P io Belie s
In gene al, esponden s ha e biased belie s abou he immig an
popula ion. A he ime o he su ey, he ac ual sha e o
immig an s in Ge many was abou 13% and he ac ual
unemploymen a e o immig an s was abou 15%. Figu e 2
shows he a e age belie s by dis ic . Bo h he sha e and he
unemploymen a e o immig an s a e g ea ly o e es ima ed in
all dis ic s wi h abou 72% o esponden s o e es ima ing
he sha e o immig an s and abou 64% o e es ima ing he
unemploymen a e. On a e age, esponden s belie e ha he
sha e o immig an s is abou 20% and he unemploymen a e o
immig an s is abou 30%. Howe e , belie s a y conside ably a
he dis ic le el. Belie s abou he sha e o immig an s ange
om unde 20% in eas e n Ge man dis ic s o o e 27% in
wes e n Ge man dis ic s. Con e sely, belie s abou he
unemploymen a e o immig an s ange om unde 27% in
sou he n and wes e n Ge man dis ic s o o e 38% in eas e n
Ge man dis ic s. In he eas e n egions, belie s abou he
unemploymen a e a e much mo e upwa dly biased han in he
wes e n egions, while belie s abou he sha e o immig an s a e
on a e age less biased.
Responden s a e likely o base hei a i udes on egional
cha ac e is ics o he immig an popula ion. Regional cha -
ac e is ics may he e o e be mo e explana o y han na ional
a e ages (Anselin 1988). The numbe o immig an s li ing in a
dis ic and hei unemploymen a e may in luence espon-
den s' es ima es o bo h a he na ional le el. Figu e 3pu s his
FIGURE 1 | Regional he e ogenei y. Due o da a es ic ions, he unemploymen a e o immig an s o Ky häuse k eis is no a ailable. The
espec i e yea o he egional a iables is 2020, excep o A D o e sha e, which is aken om he ede al elec ion in 2021.Sou ce: Da a used o
(a–d) come om BBSR Bonn (2023). Da a used o (e) come om S a is ical O ices o he Fede al and S a e Go e nmen s (2024).
785 o 886
in o pe spec i e by ela ing he sha e o immig an s a dis ic
le el (Figu e 3a) and he unemploymen a e o immig an s a
dis ic le el (Figu e 3b) o he espec i e es ima es (belie s) o
Ge many. In bo h cases we ind posi i e ela ionships.
Responden s om dis ic s wi h a highe egional sha e o
immig an s end o expec an e en highe sha e o immig an s
in Ge many, and simila ly o he unemploymen a e o
immig an s. We also see ha in mos eas e n dis ic s he sha e
o immig an s is lowe han in wes e n dis ic s (see Figu e 3a),
while in mos eas e n dis ic s he unemploymen a e o
immig an s is la ge (see Figu e 3b). This is in line wi h ou
obse a ions in Figu e 1c,e.
In gene al, o bo h s a is ics, esponden s seem o base hei
es ima es on hei pe cep ion o he egional en i onmen .
Howe e , esponden s es ima e he sha e o immig an s mo e
accu a ely han he unemploymen a e, as can be seen om he
mo e dispe sed sca e plo o he unemploymen a e in
Figu e 3b compa ed o he less dispe sed sca e plo o he
sha e o immig an s in Figu e 3a.
5 | Empi ical Me hod
5.1 | P io Belie s
We use a linea eg ession model o es ima e he co ela ion
be ween p io belie s abou immig a ion and po en ial indi id-
ual and egional de e minan s o hose belie s as pa o S ep 1
o ou analysis. We es ima e he ollowing OLS model
b
elie s ββXβZ
ε
=+ + +
iii
01 2 (1)
whe e
b
elie s
i
deno es p io belie s abou he sha e o immi-
g an s and he unemploymen a e o immig an s, espec i ely.
X
iis a ec o o indi idual co a ia es and
Z
i
is a ec o o
egional co a ia es. Regional de e minan s include GDP pe
capi a, GDP pe capi a g ow h, igh ‐wing o ing, popula ion
densi y, egional cha ac e is ics o he immig an popula ion
such as he sha e o immig an s, he unemploymen a e o
immig an s, and he sha e o e ugees in he o eign popula ion,
and a dummy o li ing in Eas Ge many. S anda d e o s a e
clus e ed a he dis ic le el.
7
5.2 | A i udes abou Immig a ion
The ela ionship be ween indi idual and egional co a ia es
wi h a i udes abou immig an s and policy p e e ences a e
es ima ed wi h he ollowing OLS model
a i ude ββ ea β ea β ea βX
βZε
=+ 1+ 2+ 3+
++
iiiii
i
01 2 3 4
5
(2)
whe e
a i ude
i ep esen s he ou ou come a iables—a i udes
owa d he wel a e s a e, a i udes owa d he labo ma ke ,
iews abou immig a ion ad an age as well as immig a ion
policy p e e ences. The indi idual and egional co a ia es a e
again deno ed by
X
iand
Z
i
, espec i ely. The model now also
includes indica o a iables o he h ee di e en ea men
a ms o ou in o ma ion ea men o es ima e a e age ea -
men e ec s (ATE). The indica o a iables ake he alue 1 i a
esponden was assigned o he espec i e ea men a m and 0
o he wise. The e o e m is
εi
. The s anda d e o s a e again
clus e ed a he dis ic le el.
8
Equa ion (2) is he basis o S eps 2 and 3 o ou analysis.
Rela ed o S ep 2, i allows us o analyze how indi idual and
egion‐speci ic ac o s co ela e wi h a i udes owa d immi-
g an s and policy p e e ences. Fo hese baseline esul s, we
conside only he con ol g oup, i.e., un ea ed indi iduals, o
a oid any in e ac ion wi h he in o ma ion ea men . Rela ed
o S ep 3, we examine he ea men e ec s. We use he ull
sample and ocus on he ATEs. We a e in e es ed in he he -
e ogenei y o ea men e ec s due o egional di e ences.
6 | Resul s
In his sec ion, we i s examine he ole o egional de-
e minan s o biases in p io belie s. In he second s ep, we
FIGURE 2 | Regional dis ibu ion o p io belie s. This igu e shows he answe o esponden s o he ques ions “Now i is abou he sha e o
immig an s in Ge many. Wha do you es ima e, please answe spon aneously: Wha pe cen age o people li ing in Ge many do no ha e Ge man
ci izenship?”and “Now i is abou he unemploymen a e o wo king‐age immig an s in Ge many. Wha do you es ima e, please answe spon a-
neously: Wha pe cen age o hese people a e unemployed?”.
786 o 886 Jou nal o Regional Science, 2025
look a he ou comes, ha is, a i udes owa d immig a ion
and policy p e e ences. We conside he un ea ed ou comes
o he con ol g oup as well as he ea men e ec s,
again ocusing on egional di e ences. Fo be e compa-
abili y, we ha e s anda dized all ou come a iables ac-
co ding o he mean and s anda d de ia ion o he con ol
g oup.
6.1 | P io Belie s
Figu e 4shows he indi idual and egional de e minan s o
biases in p io belie s abou immig a ion (see also Table B1 in
he appendix). Biases in belie s a e calcula ed as he absolu e
di e ence be ween he esponden 's answe and he ue alue.
Posi i e alues indica e a g ea e bias in p io belie s, ha is, a
FIGURE 3 | P io belie s abou immig a ion and he ac ual egional alues. The igu es show he ela ionship be ween he sha e o immig an s a
dis ic le el (a) and he unemploymen a e o immig an s a dis ic le el (b) wi h he espec i e es ima es (belie s) o Ge many. The slope o he
eg ession lines is 0.16 (p= 0.002) in (a) and 0.17 (p= 0.018) in (b).
787 o 886
posi i e a i udes owa d he wel a e s a e and mo e posi i e
iews on immig a ion ad an ages o bo h ypes o dis ic s.
Labo ma ke a i udes o esponden s li ing in dis ic s wi h
low GDP g ow h seem o be inelas ic o in o ma ion p o ision.
Tha is, hese esponden s do no espond o he ea men , as
hey epo insigni ican ea men e ec s. On he con a y,
dis ic s wi h high GDP g ow h show a mo e elas ic esponse o
he ea men . They epo signi ican and posi i e ea men
e ec s a e ecei ing in o ma ion on he sha e o immig an s o
he unemploymen a e o immig an s. The in o ma ion bundle
does no lead o signi ican ea men e ec s o ei he g oup.
We obse e signi ican di e ences in he ea men e ec
be ween he wo ypes o dis ic s on immig a ion policy p e -
e ences when in o ma ion on he sha e o immig an s is p o-
ided. Simila o be o e, esponden s om dis ic s wi h high
GDP g ow h eac mo e signi ican ly posi i ely han espon-
den s om dis ic s wi h low GDP g ow h. The di e ence in he
ea men e ec s be ween he wo ypes o dis ic s is smalle
when in o ma ion on he unemploymen a e o immig an s is
p o ided, while p o iding bo h ypes o in o ma ion does no
lead o di e en and signi ican e ec s.
6.3.4 | Robus ness Checks
We check he obus ness o ou esul s in se e al ways (see
Appendix E o he espec i e ables and igu es). Fi s , we
e un ou analysis wi h egional a iables a he NUTS 2 le el o
see i he esul s hold a a mo e agg ega ed le el. The e a e
some changes ela ed o he di e ences in ea men e ec s
ac oss egions. Howe e , his does no change he o e all
in e p e a ion o ou esul s. Second, he e may be a ia ions a
he s a e le el ha a ec ou esul s. When we include
ca ego ical a iables o he ede al s a es, ou esul s do no
change. Thi d, ou ou come a iables a e measu ed on an
o dinal scale. The e o e, we use o de ed p obi eg ession o
analyze he obus ness o ou esul s. Compa ed o ou OLS
speci ica ion, he in e p e a ion o he ea men e ec s emains
he same.
7 | Conclusion
This pape examines how indi idual a i udes owa d immi-
g a ion and policy p e e ences a e shaped by he egional en-
i onmen . The analysis is based on wo ep esen a i e su eys
o he Ge man popula ion and adminis a i e da a a he dis ic
le el. We analyze egional de e minan s o biases in belie s
abou he immig an popula ion and a i udes. We also examine
how p o iding in o ma ion abou he cha ac e is ics o he
immig an popula ion in Ge many, ha is, hei sha e and
unemploymen a e, changes a i udes di e en ly in egions
ha di e in economic and poli ical cha ac e is ics and in he
cha ac e is ics o hei immig an popula ion.
We ind ha egional cha ac e is ics a e co ela ed wi h he o -
ma ion o belie s abou and a i udes owa d immig a ion. How-
e e , he co ela ions depend on he ype o a i udes examined
and become insigni ican when indi idual con ols a e added.
Focusing on he in o ma ion e ec s, we ind ha in o ming
esponden s abou he cha ac e is ics o he immig an pop-
ula ion can inc ease posi i e a i udes owa d immig a ion.
The ea men e ec s appea o be ela i ely simila o di -
e en dis ic ‐le el cha ac e is ics, as hecon idencein e -
als be ween he subg oups mos ly o e lap. Howe e , he e is
some e idence ha di e en ypes o in o ma ion a e pe -
cei ed di e en ly in di e en dis ic s. B oadly speaking,
esponden s om dis ic s ha a e economically be e o ,
ha e lowe sha es o igh ‐wing o e s and lowe sha es o
immig an s seem o espond mo e posi i ely o he ea men .
Fu he mo e, a i udes owa d he labo ma ke seem o be
mos in luenced by he egional en i onmen . This may be
because esponden s pe cei e labo ma ke compe i ion wi h
immig an s a he dis ic le el, and hus he egional con ex ,
in addi ion o indi idual cha ac e is ics, and his con ibu es
o shaping hese a i udes.
Policymake s should ake in o accoun ha belie s abou and
a i udes owa d immig an s a e shaped no only by indi idual
cha ac e is ics bu also by he egional con ex . The e o e,
in o ma ion campaigns o policy in e en ions may ha e di -
e en e ec s depending on he egion in which hey a e im-
plemen ed. Howe e , i should be no ed ha he local poli ical
en i onmen is also endogenously shaped by indi idual cha -
ac e is ics and he egional con ex .
So a we ha e only examined he sho ‐ e m ela ionship
be ween he egional en i onmen and belie s abou and a i-
udes owa d immig an s. A eas o u u e esea ch would be o
examine changes in belie s and a i udes o e ime and he ole
o he egional economic and social con ex . In addi ion, ou
analysis is based on ep esen a i e su eys o he Ge man
popula ion. Ex ending ou analysis o o he coun ies would
he e o e p o ide insigh s in o whe he he ela ionship
be ween belie s abou and a i udes owa d immig a ion is mo e
egion o coun y speci ic.
Acknowledgmen s
We hank he pa icipan s o he Jena Economic Resea ch Wo kshop
(JERW), he Wo kshop on Empi ical Mic oeconomics and Applied
Econome ics, he Wo kshop o he Cen al‐Ge man Doc o al P og am
Economics (CGDE), he Young Economis s' Mee ing (YEM), he
Annual Mee ing o he Ve ein ü Socialpoli ik (V S) and he Ruh
G adua e School Doc o al Con e ence (RGS) o help ul commen s and
discussions. IRB app o al o he wo su eys including he in o ma ion
expe imen was ob ained a he Ins i u ional Re iew Boa d (IRB) o he
Facul y o Economics and Business Adminis a ion a F ied ich Schille
Uni e si y Jena (da ed No embe 25, 2020 and Sep embe 11, 2021).
This wo k is suppo ed by he F ee S a e o Thu ingia and he Eu opean
Social Fund (G an Numbe WBV180515). Open Access unding en-
abled and o ganized by P ojek DEAL.
Con lic s o In e es
The au ho s decla e no con lic s o in e es .
Da a A ailabili y S a emen
The da a ha suppo he indings o his s udy a e a ailable om he
co esponding au ho upon easonable eques .
794 o 886 Jou nal o Regional Science, 2025

Endno es
1
In ou s udy, immig an s a e ega ded as people li ing in Ge many
wi hou Ge man ci izenship.
2
A he ede al elec ions in Sep embe 2021, campaigns mos ly
e ol ed a ound issues such as he COVID‐19 pandemic o clima e
change.
3
In he ecen s a e elec ions, he A D came i s in Thu ingia
and second in Saxony and B andenbu g—in each case wi h close o
o sligh ly abo e 30% o he o es.
4
We d opped esponden s om he second wa e i hey had al eady
pa icipa ed in he i s wa e, as we used he same su ey p o ide
o bo h wa es.
5
All indi iduals a e also asked abou hei pos e io belie s abou bo h
ac s a he end o he su ey.
6
Remembe ha we ha e coded he a iables so ha highe alues
indica e mo e posi i e a i udes owa d immig a ion.
7
Ou esul s do no change when we use di e en clus e ing me hods.
8
As a obus ness checks, we p esen esul s o a speci ica ion wi h
dis ic ixed e ec s in Table D2; di e en egional speci ica ions a e
p esen ed in Sec ion 6.3.4.
9
To be e unde s and i de e minan s o p io belie s di e be ween
o e es ima o s o unde es ima o s, we spli up he sample in o a
g oup which includes hose who ha e o e es ima ed bo h he sha e
o immig an s and he unemploymen a e o immig an s, and a
g oup which includes hose who ha e unde es ima ed bo h.
Tables B2 and B3 in he appendix show he de e minan s o biased
belie s espec i ely o esponden s who join ly o e ‐o unde -
es ima e p io belie s. Responden s who join ly o e es ima e show a
simila pa e n in de e minan s o p io belie s abou he sha e o
immig an s. Fo he unemploymen a e o immig an s, nega i e
co ela ions wi h he popula ion densi y and A D o e sha e pe sis ,
e en a e adding indi idual co a ia es. Fo esponden s who join ly
unde es ima e, egional co a ia es do no seem o play a ole o
de e minan s o p io belie s. This may also be due o he lowe
sample size.
10
Table D2 p esen s esul s wi h dis ic ixed e ec s.
11
Fo be e unde s anding i di e en ea men e ec s o o e -
es ima o s o unde es ima o s may explain he obse ed pa e ns,
we spli up he sample in o one g oup which includes hose who
ha e o e es ima ed bo h he sha e o immig an s and he
unemploymen a e o immig an s and one g oup which includes
hose who ha e unde es ima ed bo h. Figu e D1 shows ha join
o e es ima o s espond signi ican ly and posi i ely o all ou
in o ma ion ea men s wi h he excep ion o a i udes owa d he
labo ma ke whe e we ind he same ade‐o pa e n as o he
ull sample. Fo join unde es ima o s, on he con a y, we ind
mos ly insigni ican e ec s. This means ha in o ming hese
pa icipan s ha he sha e o immig an s and he unemploymen
a e a e highe han es ima ed does no lead o mo e nega i e
a i udes. The only excep ion is hei iew on immig a ion
ad an age which signi ican ly dec eases when he in o ma ion
bundle is p o ided and which may explain he insigni ican e ec
o he ull sample.
12
No e ha we always con ol o all he o he egional cha ac e is ics
in ou eg essions.
Re e ences
Alesina, A., A. Miano, and S. S an che a. 2023. “Immig a ion and
Redis ibu ion.”Re iew o Economic S udies 90, no. 1: 1–39.
Allpo , G. W. 1958. The Na u e o P ejudice (Ab idged). Doubleday.
Anselin, L. 1988. Spa ial Econome ics: Me hods and Models. Kluwe
Academic Publishe s.
Bansak, K., J. Hainmuelle , and D. Hanga ne . 2016. “How Economic,
Humani a ian, and Religious Conce ns Shape Eu opean A i udes
Towa d Asylum Seeke s.”Science 354, no. 6309: 217–222.
Bas iaens, I., and E. Pos niko . 2020. “Social S anda ds in T ade
Ag eemen s and F ee T ade P e e ences: An Empi ical In es iga ion.”
Re iew o In e na ional O ganiza ions 15, no. 4: 793–816.
BBSR Bonn. 2023. “INKAR ‐Indica o s and Maps o Spa ial and
U ban De elopmen .”Re ie ed June 22, 2023, F om h ps://www.
inka .de/.
Becke , S. O., T. Fe ze , and D. No y. 2017. “Who Vo ed o B exi ? A
Comp ehensi e Dis ic ‐Le el Analysis.”Economic Policy 32, no. 92:
601–650.
Bell, D. A., M. Valen a, and Z. S abac. 2023. “Pe cep ions and Reali ies:
Explaining Wel a e Chau inism in Eu ope.”Jou nal o Eu opean Social
Policy 33, no. 3: 301–316.
Boe i, T., M. Gamale io, M. Mo elli, and M. Neg i. 2024. “Pay‐as‐They‐
Ge ‐In: A i udes Towa d Mig an s and Pension Sys ems.”Jou nal o
Economic Geog aphy 24, no. 1: 63–78.
Bo jas, G. J. 2006. “Na i e In e nal Mig a ion and he Labo Ma ke
Impac o Immig a ion.”Jou nal o Human Resou ces, XLI 2, no. 2:
221–258.
Bosque , C., and H. G. O e man. 2019. “Why Does Bi hplace Ma e so
Much?”Jou nal o U ban Economics 110: 26–34.
B enne , J., and M. Fe ig 2006. “Iden i ying he De e minan s o
A i udes Towa ds Immig an s: A S uc u al C oss‐Coun y Analysis.”
IZA Discussion Pape s No. 2306.
Fede al O ice o Mig a ion and Re ugees. 2024a. Fo eign Popula ion.
Re ie ed Oc obe 14, 2024, F om h ps://www.BAMF.de/DE/Themen/
Fo schung/Ve oe en lichungen/Mig a ionsbe ich 2022/Auslaendische
Be oelke ung/auslaendischebe oelke ung-node.h ml.
Fede al O ice o Mig a ion and Re ugees. 2024b. Ini ial Dis ibu ion o
Asylum Seeke s (EASY). Re ie ed Oc obe 14, 2024, F om h ps://www.
BAMF.de/EN/Themen/AsylFluech lingsschu z/Ablau Asyl e ah ens/
E s e eilung/e s e eilung-node.h ml.
The Fede al Re u ning O ice . 2023. “Resul s.”Fede al Elec ion 2021.
Re ie ed Janua y 9, 2023, F om h ps://www.bundeswahllei e .de/
bundes agswahlen/2021/e gebnisse.h ml.
Fede al Agency o Ci ic Educa ion. 2024. “In a Nu shell: The A D –
Pa ies in Ge many.”Fede al Agency o Ci ic Educa ion. Re ie ed
Oc obe 14, 2024, F om h ps://www.bpb.de/ hemen/pa eien/pa eien-
in-deu schland/a d/211108/ku z-undbuendig-die-a d/.
Bu ns, P., and J. G. Gimpel. 2000. “Economic Insecu i y, P ejudicial
S e eo ypes, and Public Opinion on Immig a ion Policy.”Poli ical
Science Qua e ly 115, no. 2: 201–225.
Ca d, D. 2009. “Immig a ion and Inequali y.”Ame ican Economic
Re iew 99, no. 2: 1–21.
Ca d, D., and J. DiNa do. 2000. “Do Immig an In lows Lead o Na i e
Ou lows?”Ame ican Economic Re iew 90, no. 2: 360–367.
Ca eja, R., and E. Ha is. 2022. “Thi y Yea s o Wel a e Chau inism
Resea ch: Findings and Challenges.”Jou nal o Eu opean Social Policy
32, no. 2: 212–224.
Ci in, J., and J. Sides. 2008. “Immig a ion and he Imagined Com-
muni y in Eu ope and he Uni ed S a es.”Poli ical S udies 56, no. 1:
33–56.
Czaika, M., and A. DiLillo. 2018. “The Geog aphy o An i‐Immig an
A i udes Ac oss Eu ope, 2002‐2014.”Jou nal o E hnic and Mig a ion
S udies 44, no. 15: 2453–2479.
Dancygie , R. M., and M. J. Donnelly. 2013. “Sec o al Economies,
Economic Con ex s, and A i udes Towa d Immig a ion.”Jou nal o
Poli ics 75, no. 1: 17–35.
795 o 886
Demog aphy Pla o m. 2024. “Fac s ‐Regional Sha e o Immig an s.
Re ie ed Oc obe 14, 2024, F om h ps://www.demog a ie-po al.de/
DE/Fak en/auslaende - egional.h ml.
Die meie , M., J. Niehues, and J. Reinecke. 2021. “Con adic o y Wel-
a e Condi ioning—Di e ing Wel a e Suppo o Na i es Ve sus
Immig an s.”Re iew o In e na ional Poli ical Economy 28, no. 6:
1677–1704.
Dijks a, L., H. Poelman, and A. Rod íguez‐Pose. 2020. “The Geog aphy
o EU Discon en .”Regional S udies 54, no. 6: 737–753.
Dus mann, C., and I. P. P es on. 2007. “Racial and Economic Fac o s in
A i udes o Immig a ion.”B.E. Jou nal o Economic Analysis & Policy 7: 1.
Dus mann, C., K. Vasilje a, and A. PiilDamm. 2019. “Re ugee Mig a ion
and Elec o al Ou comes.”Re iew o Economic S udies 86, no. 5:
2035–2091.
Dylong, P., and S. Uebelmesse . 2024. “Biased Belie s Abou Immi-
g a ion and Economic Conce ns: E idence F om Rep esen a i e
Expe imen s.”Jou nal o Economic Beha io & O ganiza ion 217:
453–482.
En o , H., and M. Lange. 2023. “Re ugees Welcome? Unde s anding
he Regional He e ogenei y o An i‐Re ugee Ha e C ime.”Regional
Science and U ban Economics 101: 103913.
Facchini, G., Y. Ma gali , and H. Naka a. 2022. “Coun e ing Public
Opposi ion o Immig a ion: The Impac o In o ma ion Campaigns.”
Eu opean Economic Re iew 141: 103959.
Facchini, G., and A. M. Mayda. 2009. “Does he Wel a e S a e A ec
Indi idual A i udes Towa d Immig an s? E idence Ac oss Coun ies.”
Re iew o Economics and S a is ics 91, no. 2: 295–314.
Fo d, R., and M. Goodwin. 2017. “B i ain A e B exi : A Na ion
Di ided.”Jou nal o Democ acy 28, no. 1: 17–30.
F a esi, U., M. Pe coco, and P. P oie i. 2019. “Who Welcomes Them?
De e minan s o he Spa ial Dis ibu ion o Asylum Seeke s in I aly.”
Regional S udies 53, no. 1: 118–130.
Gallegos To es, K. 2023. “The 2015 Re ugee In low and Conce ns
O e Immig a ion.”Eu opean Jou nal o Poli ical Economy 78:
102323.
Gamale io, M., M. Luca, A. Roma i, and M. Viskanic. 2023. “Re ugee
Recep ion, Ex eme‐Righ Vo ing, and Composi ional Ameni ies: E i-
dence F om I alian Municipali ies.”Regional Science and U ban
Economics 100: 103892.
Go odzeisky, A., and M. Semyono . 2020. “Pe cep ions and Mis-
pe cep ions: Ac ual Size, Pe cei ed Size and Opposi ion o Immig a ion
in Eu opean Socie ies.”Jou nal o E hnic and Mig a ion S udies 46, no.
3: 612–630.
Gozgo , G. 2022. “The Role o Economic Unce ain y in he Rise o EU
Populism.”Public Choice 190, no. 1: 229–246.
G igo ie , A., C. Ro h, and D. Ub al. 2020. “Does In o ma ion Change
A i udes Towa d Immig an s?”Demog aphy 57, no. 3: 1117–1143.
Haaland, I., and C. Ro h. 2020. “Labo Ma ke Conce ns and Suppo
o Immig a ion.”Jou nal o Public Economics 191, no. 5: 104256.
Hainmuelle , J., and M. J. Hiscox. 2007. “Educa ed P e e ences: Ex-
plaining A i udes Towa d Immig a ion in Eu ope.”In e na ional
O ganiza ion 61, no. 2: 399–442.
Hainmuelle , J., and M. J. Hiscox. 2010. “A i udes Towa d Highly
Skilled and Low‐Skilled Immig a ion: E idence F om a Su ey Ex-
pe imen .”Ame ican Poli ical Science Re iew 104, no. 1: 61–84.
Hainmuelle , J., and D. J. Hopkins. 2014. “Public A i udes Towa d
Immig a ion.”Annual Re iew o Poli ical Science 17: 225–249.
Hainmuelle , J., and D. J. Hopkins. 2015. “The Hidden Ame ican
Immig a ion Consensus: A Conjoin Analysis o A i udes Towa d
Immig an s.”Ame ican Jou nal o Poli ical Science 59, no. 3: 529–548.
Halla, M., A. F. Wagne , and J. Zweimülle . 2017. “Immig a ion and
Vo ing o he Fa Righ .”Jou nal o he Eu opean Economic Associa ion
15, no. 6: 1341–1385.
Hanga ne , D., E. Dinas, M. Ma bach, K. Ma akos, and D. Xe e is.
2019. “Does Exposu e o he Re ugee C isis Make Na i es Mo e Hos-
ile?”Ame ican Poli ical Science Re iew 113, no. 2: 442–455.
Ha on, T. J. 2016. “Immig a ion, Public Opinion and he Recession in
Eu ope.”Economic Policy 31, no. 86: 205–246.
He da, D. 2010. “How Many Immig an s?: Fo eign‐Bo n Popula ion
Innume acy in Eu ope.”Public Opinion Qua e ly 74, no. 4: 674–695.
He da, D., and A. Di adka . 2023. “The Imagined Immig a ion and he
C iminal Immig an : Expanding he Ca alog o Immig an ‐Rela ed
Igno ance.”Mig a ion Le e s 20, no. 1: 71–87.
Hjo h, F. 2016. “Who Bene i s? Wel a e Chau inism and Na ional
S e eo ypes.”Eu opean Union Poli ics 17, no. 1: 3–24.
I Ie s, A. 2012. “Ageing, Local Bi h Ra es and A i udes Towa ds
Immig a ion: E idence F om a T ansi ion Economy.”Regional S udies
46, no. 7: 947–959.
Kling, J. R., J. B. Liebman, and L. F. Ka z. 2007. “Expe imen al Analysis
o Neighbo hood E ec s.”Econome ica 75, no. 1: 83–119.
K eme , A. 2022. “Home Is Whe e he His o y Is: How Today's
Mig a ion in Ge many Is Shaped by Regional Iden i y.”Jou nal o
Regional Science 62, no. 2: 604–638.
Kun z, A., E. Da ido , and M. Semyono . 2017. “The Dynamic
Rela ions Be ween Economic Condi ions and An i‐Immig an Sen-
imen : A Na u al Expe imen in Times o he Eu opean Economic
C isis.”In e na ional Jou nal o Compa a i e Sociology 58, no. 5:
392–415.
Lechle , M. 2019. “Employmen Shocks and An i‐EU Sen imen .”
Eu opean Jou nal o Poli ical Economy 59: 266–295.
Lu z, P., and M. Bi schnau. 2023. “Mispe cep ions Abou Immig a ion:
Re iewing Thei Na u e, Mo i a ions and De e minan s.”B i ish
Jou nal o Poli ical Science 53, no. 2: 674–689.
Ma kaki, Y., and S. Longhi. 2013. “Wha De e mines A i udes o
Immig a ion in Eu opean Coun ies? An Analysis a he Regional
Le el.”Mig a ion S udies 1, no. 3: 311–337.
Ma x, P., and E. Naumann. 2018. “Do Righ ‐Wing Pa ies Fos e Wel-
a e Chau inis ic A i udes? A Longi udinal S udy o he 2015 ‘Re ugee
C isis’in Ge many.”Elec o al S udies 52: 111–116.
Mayda, A. M. 2006. “Who Is Agains Immig a ion? A C oss‐Coun y
In es iga ion o Indi idual A i udes Towa d Immig an s.”Re iew o
Economics and S a is ics 88, no. 3: 510–530.
McGinni y, F., and G. Kings on. 2017. “An I ish Welcome?
Changing I ish A i udes o Immig an s and Immig a ion: The Role
o Recession and Immig a ion.”Economic and Social Re iew 48, no.
3: 253–279.
McNeil, A., D. Luca, and N. Lee. 2023. “The Long Shadow o
Local Decline: Bi hplace Economic Ad e si y and Long‐Te m
Indi idual Ou comes in he UK.”Jou nal o U ban Economics
136: 103571.
Mehic, A. 2022. “Regional Aspec s o Immig a ion‐Rela ed Changes in
Poli ical P e e ences.”Jou nal o Regional Science 62, no. 5: 1386–1413.
O ega, F., and J. G. Pola ieja. 2012. “Labo ‐Ma ke Exposu e as a
De e minan o A i udes Towa d Immig a ion.”Labou Economics 19,
no. 3: 298–311.
Paasi, A. 2002. “Bounded Spaces in he Mobile Wo ld: Decons uc ing
‘Regional Iden i y’.”Tijdsch i oo Economische en Sociale Geog a ie
93, no. 2: 137–148.
Paluck, E. L., S. A. G een, and D. P. G een. 2019. “The Con ac
Hypo hesis Re‐E alua ed.”Beha iou al Public Policy 3, no. 2: 129–158.
796 o 886 Jou nal o Regional Science, 2025
Pe ig ew, T. F. 1998. “In e g oup Con ac Theo y.”Annual Re iew o
Psychology 49, no. 1: 65–85.
Pola ieja, J. G. 2016. “Labou ‐Ma ke Compe i ion, Recession and An i‐
Immig an Sen imen s in Eu ope: Occupa ional and En i onmen al
D i e s o Compe i i e Th ea .”Socio‐Economic Re iew 14, no. 3: 395–417.
Pou aa a, P., and M. F. S einha d . 2018. “Bi e ness in Li e and A i-
udes Towa ds Immig a ion.”Eu opean Jou nal o Poli ical Economy 55,
no. 1: 471–490.
P oshansky, H. M., A. K. Fabian, and R. Kamino . 1983. “Place‐
Iden i y: Physical Wo ld Socializa ion o he Sel .”Jou nal o
En i onmen al Psychology 3, no. 1: 57–83.
Rus enbach, E. 2010. “Sou ces o Nega i e A i udes Towa d Immi-
g an s in Eu ope: A Mul i‐Le el Analysis.”In e na ional Mig a ion
Re iew 44, no. 1: 53–77.
Ge man Council o Economic Expe s. 2020. O e coming he Co o-
na i us C isis Toge he : S eng hening Resilience and G ow h. Annual
Repo 2020/2021. Wiesbaden.
Snide man, P. M., L. Hagendoo n, and M. P io . 2004. “P edisposing
Fac o s and Si ua ional T igge s: Exclusiona y Reac ions o Immig an
Mino i ies.”Ame ican Poli ical Science Re iew 98, no. 1: 35–49.
S a is ical O ices o he Fede al and S a e Go e nmen s. 2024.
13211‐02‐05‐4: Unemploymen by Selec ed G oups o People and
Unemploymen Ra es ‐Annual A e age ‐(F om 2009) Regional Dep h:
Dis ic s and Ci ies, Regional Da abase Ge many. Re ie ed Oc obe 4,
2024, F om h ps://www. egionals a is ik.de/genesis/online#as uc u e.
Fede al S a is ical O ice. 2024. Fo eign Popula ion. Re ie ed Sep em-
be 30, 2024, F om h ps://www.des a is.de/DE/Themen/Gesellscha -
Umwel /Be oelke ung/Be oelke ungss and/Glossa /auslaendische-
be oelke ung.h ml.
Tabellini, M. 2020. “Gi s o he Immig an s, Woes o he Na i es:
Lessons F om he Age o Mass Mig a ion.”Re iew o Economic S udies
87, no. 1: 454–486.
Wong, C. J. 2007. “‘Li le‘and ‘Big’Pic u es in Ou Heads: Race, Local
Con ex , and Innume acy Abou Racial G oups in he Uni ed S a es.”
Public Opinion Qua e ly 71, no. 3: 392–412.
Appendix A
Da a Desc ip ion and Summa y S a is ics
See Table A2.
TABLE A1 | Va iable desc ip ion o indi idual‐le el su ey da a.
Va iable name Yea Range Desc ip ion/ques ion in su ey
Belie s:
Belie : sha e o immig an s 2020/
2021
Nume ical “Now i is abou he sha e o immig an s in Ge many. Wha do you
es ima e, please answe spon aneously: Wha pe cen age o people
li ing in Ge many do no ha e Ge man ci izenship?”. Hin ex
(clickable ia ques ion ma k icon): “The pe cen age is unde s ood he e
as he numbe o immig an s pe 100 inhabi an s in Ge many.”
Absolu e di e ence be ween esponden s answe and he ue alue.
Belie : unemploymen a e o
immig an s
2020/
2021
Nume ical “Now i is abou he unemploymen a e o wo king‐age immig an s in
Ge many. Wha do you es ima e, please answe spon aneously: Wha
pe cen age o hese people a e unemployed.”Hin ex (clickable ia
ques ion ma k icon): “The pe cen age is unde s ood he e as he numbe
o unemployed pe sons pe 100 immig an s o wo king age in Ge many.
Immig an s a e conside ed unemployed i hey a e egis e ed as
unemployed wi h he Fede al Employmen Agency. Asylum seeke s and
ole a ed pe sons a e included in he unemploymen a e i hey ha e a
wo k pe mi bu no job and a e egis e ed as unemployed.”
Absolu e di e ence be ween esponden s answe and he ue alue.
Ou comes:
Wel a e s a e a i udes 2020/
2021
Nume ical (0–10) “Do you hink ha immig an s in Ge many ge mo e in bene i s han
hey pay in axes, o pay mo e in axes han hey ge in bene i s?”
Labo ma ke a i udes 2020/
2021
Nume ical (0–10) “A e immig an s mo e likely o ake jobs away om wo ke s in
Ge many o a e hey mo e likely o help c ea e new jobs?”
Immig a ion ad an age
a i udes
2020/
2021
Nume ical (0–10) “Do you hink immig an s ha e c ea ed mo e disad an ages o mo e
ad an ages o Ge many in he las 10 yea s?”
Immig a ion Policy P e e ences 2020/
2021
Nume ical (1–5) “Do you hink ha he numbe o immig an s coming o Ge many
each yea should be dec eased a lo / dec eased sligh ly / s ay he same /
inc eased sligh ly / inc eased a lo ?”
Con ol a iables:
Conce ns abou immig a ion 2020/
2021
Nume ical (0–10) Conce ns abou immig a ion o Ge many
Conce ns abou economic
de elopmen
2020/
2021
Nume ical (0–10) Conce ns abou economic de elopmen in Ge many
(Con inues)
797 o 886
TABLE A1 | (Con inued)
Va iable name Yea Range Desc ip ion/ques ion in su ey
Conce ns abou COVID‐19
c isis
2020/
2021
Nume ical (0–10) Conce ns due o he COVID pandemic
A i ude owa d cul u al
di e si y
2020/
2021
Nume ical (0–10) “I is be e o a coun y i almos e e yone has he same cus oms and
adi ions.”
Poli ical a i ude 2020/
2021
Nume ical (0–10) Measu es a esponden 's gene alized poli ical a i ude on an 11‐poin
scale om 0 o “Le ” o 10 o “Righ ”
Age g oup 2020/
2021
Nume ical (1–5) Responden 's age g oup acco ding o he anges: 16–29, 30–39, 40–49,
50–64, 65 and abo e
Educa ion 2020/
2021
Nume ical (1–3) Responden 's educa ion based on highes school‐lea ing ce i ica e
acco ding o he anges: low, medium, high.
Household size 2020/
2021
Nume ical Numbe o pe sons li ing in a esponden 's household
Income 2020/
2021
Nume ical (1–5) Responden 's household ne income in Eu o acco ding o he anges:
Below 1500, 1500–2500, 2500–3500, 3500–4500, 4500 and abo e
Female 2020/
2021
Bina y Indica es a esponden 's gende
Employed 2020/
2021
Bina y Indica es whe he a esponden is employed
Pa ne 2020/
2021
Bina y Indica es whe he a esponden li es in a pa ne ship
Mig a ion backg ound 2020/
2021
Bina y Indica es whe he a esponden o one o hei pa en s was bo n ou side
o Ge many
Eas Ge many 2020/
2021
Bina y Indica es whe he a esponden li es in Eas Ge many (excluding
Be lin)
Su ey wa e 2020/
2021
Bina y Indica es whe he a esponden ook pa in he i s o second wa e o
he su ey
TABLE A2 | Va iable desc ip ion o dis ic ‐le el da a (NUTS‐3).
Va iable name Yea Range Desc ip ion
Popula ion densi y 2020 Nume ical Regional popula ion pe km
2
A D o e sha e 2021 Nume ical Regional o e sha e o A D du ing he ede al elec ions in Ge many
in 2021
GDP pe capi a 2020 Nume ical Regional g oss domes ic p oduc in EUR 1000 pe inhabi an
GDP pe capi a g ow h 2020 Nume ical Regional g ow h o GDP pe capi a wi h espec o 2019
Sha e o immig an s 2020 Nume ical Regional sha e o immig an s in Ge many
Unemploymen a e o immig an s 2020 Nume ical Regional unemploymen a e o immig an s
Sha e o e ugees in he immig an popula ion 2020 Nume ical Regional sha e o e ugees in he immig an popula ion
No e: INKAR Da abase (BBSR Bonn 2023) and s a is ical o ices o he ede al and s a e go e nmen s (S a is ical O ices o he Fede al and S a e Go e nmen s 2024).
TABLE A3 | Summa y s a is ics.
Mean SD Minimum Maximum
Indi idual
Wel a e s a e a i udes 3.86 2.45 0.00 10.00
Labo ma ke a i udes 5.25 2.40 0.00 10.00
Immig a ion ad an age a i udes 4.28 2.65 0.00 10.00
(Con inues)
798 o 886 Jou nal o Regional Science, 2025
TABLE A3 | (Con inued)
Mean SD Minimum Maximum
Immig a ion policy p e e ences 2.20 1.02 1.00 5.00
Belie : sha e o immig an s (%) 13.45 13.73 0.00 84.00
Belie : unemploymen a e o immig an s (%) 20.43 20.01 0.00 84.00
Conce ns abou immig a ion 5.88 3.23 0.00 10.00
Conce ns abou economic de elopmen 6.18 2.53 0.00 10.00
Conce ns abou COVID‐19 c isis 5.58 2.89 0.00 10.00
A i ude owa d cul u al di e si y 5.22 2.94 0.00 10.00
Poli ical a i ude 4.71 1.91 0.00 10.00
Household size 2.14 1.31 0.00 20.00
Eas Ge many 0.15 0.36 0.00 1.00
Female 0.51 0.50 0.00 1.00
Employed 0.53 0.50 0.00 1.00
Pa ne 0.63 0.48 0.00 1.00
Mig a ion backg ound 0.23 0.42 0.00 1.00
Age g oup
16–29 0.16 0.37 0.00 1.00
30–39 0.16 0.37 0.00 1.00
40–49 0.15 0.36 0.00 1.00
50–64 0.27 0.45 0.00 1.00
65 and abo e 0.25 0.43 0.00 1.00
Educa ion
Low educa ion 0.34 0.47 0.00 1.00
Medium educa ion 0.32 0.46 0.00 1.00
High educa ion 0.34 0.48 0.00 1.00
Income
Below 1500 EUR 0.25 0.43 0.00 1.00
1500–2500 EUR 0.29 0.45 0.00 1.00
2500–3500 EUR 0.23 0.42 0.00 1.00
3500‐–4500 EUR 0.14 0.35 0.00 1.00
4500 EUR and abo e 0.09 0.29 0.00 1.00
Su ey wa e 1.59 0.49 1.00 2.00
Regional
Popula ion densi y ( esiden s pe km
2
) 1087.82 1251.24 35.58 4789.84
Vo e sha e A D (%) 10.05 5.48 2.87 32.53
GDP pe capi a (1000 EUR) 41.32 16.43 16.66 167.12
GDP pe capi a g ow h (%) −2.74 2.45 −14.70 9.16
Sha e o immig an s (%) 13.20 6.07 2.24 36.94
Unemploymen a e o immig an s (%) 15.69 6.05 4.90 34.50
Re ugees as sha e o immig an popula ion (%) 19.71 9.06 0.00 63.77
Obse a ions 5698
799 o 886

TABLE A4 | Co ela ions wi h Eas ‐Ge many dummy.
Eas Ge many
Popula ion densi y ( esiden s pe km
2
)−0.184
Vo e sha e A D (%) 0.814
GDP pe capi a (1000 EUR) −0.254
GDP pe capi a g ow h (%) 0.182
Sha e o immig an s (%) −0.505
Unemploymen a e o immig an s (%) 0.243
Re ugees as sha e o immig an
popula ion (%)
0.493
Obse a ions 5698
TABLE B1 | Indi idual and egional de e minan s o biases in p io belie s.
Sha e o immig an s Unemploymen o immig an s
(1) (2) (3) (4)
Popula ion densi y −0.108*** −0.070*** 0.002 −0.008
(0.027) (0.021) (0.016) (0.016)
A D o e sha e 0.032 0.041*0.080*** −0.019
(0.019) (0.023) (0.017) (0.021)
GDP pe capi a 0.013 0.024 0.005 0.005
(0.021) (0.018) (0.016) (0.016)
GDP pe capi a g ow h −0.010 −0.011 0.005 0.003
(0.016) (0.013) (0.014) (0.013)
Sha e o immig an s 0.115*** 0.117*** −0.077*** −0.048*
(0.035) (0.030) (0.026) (0.025)
Unemploymen a e o immig an s 0.022 0.013 −0.005 −0.007
(0.024) (0.018) (0.018) (0.017)
Sha e o e ugees −0.022 0.008 0.006 −0.001
(0.024) (0.018) (0.023) (0.021)
Conce ns abou immig a ion 0.163*** 0.198***
(0.016) (0.018)
Conce ns abou economic de elopmen 0.049*** 0.047***
(0.015) (0.014)
Conce ns abou COVID‐19 c isis −0.010 −0.068***
(0.013) (0.014)
A i ude owa d cul u al di e si y −0.021 0.058***
(0.019) (0.018)
Poli ical a i ude 0.017 0.034**
(0.017) (0.016)
Age g oup −0.130*** 0.025*
(0.014) (0.015)
Educa ion −0.217*** −0.051***
(0.015) (0.015)
(Con inues)
Appendix B
P io Belie s
800 o 886 Jou nal o Regional Science, 2025
TABLE B1 | (Con inued)
Sha e o immig an s Unemploymen o immig an s
(1) (2) (3) (4)
Household size 0.057*** 0.023
(0.017) (0.014)
Income −0.122*** −0.067***
(0.014) (0.015)
Female 0.432*** 0.196***
(0.025) (0.025)
Employed 0.056** 0.001
(0.027) (0.031)
Pa ne 0.067** 0.038
(0.029) (0.026)
Mig a ion backg ound 0.144*** 0.003
(0.031) (0.029)
Eas Ge many −0.053 0.285***
(0.067) (0.057)
Su ey wa e 0.082*** 0.019
(0.023) (0.027)
Cons an 0.000 −0.445*** 0.001 −0.197***
(0.016) (0.044) (0.013) (0.052)
Obse a ions 5698 5698 5698 5698
R
2
0.007 0.185 0.019 0.121
Adjus ed
R
2
0.006 0.181 0.018 0.117
No e: This able shows indi idual and egional de e minan s o biases in p io belie s abou he immig an popula ion. S anda d e o s clus e ed a dis ic le el.
*p
<
0.10; **p
<
0.05; ***p
<
0.01.
TABLE B2 | De e minan s o biases in p io belie s: join o e es ima o s.
Sha e o immig an s Unemploymen o immig an s
(1) (2) (3) (4)
Popula ion densi y −0.149*** −0.108*** −0.032 −0.051**
(0.037) (0.028) (0.022) (0.022)
A D o e sha e 0.036 0.045 0.057** −0.061**
(0.032) (0.036) (0.024) (0.030)
GDP pe capi a 0.037 0.062*0.025 0.018
(0.034) (0.032) (0.025) (0.025)
GDP pe capi a g ow h −0.017 −0.021 0.023 0.016
(0.025) (0.021) (0.019) (0.018)
Sha e o immig an s 0.151*** 0.149*** −0.069*−0.040
(0.052) (0.045) (0.038) (0.036)
Unemploymen a e o immig an s 0.015 0.011 −0.001 −0.007
(0.033) (0.026) (0.026) (0.025)
Sha e o e ugees −0.000 0.029 0.015 0.005
(0.034) (0.026) (0.032) (0.031)
(Con inues)
801 o 886
TABLE B2 | (Con inued)
Sha e o immig an s Unemploymen o immig an s
(1) (2) (3) (4)
Conce ns abou immig a ion 0.173*** 0.185***
(0.027) (0.028)
Conce ns abou economic de elopmen 0.058** 0.032
(0.025) (0.021)
Conce ns abou COVID‐19 c isis −0.001 −0.078***
(0.020) (0.020)
A i ude owa d cul u al di e si y −0.022 0.036
(0.029) (0.027)
Poli ical a i ude 0.024 0.065***
(0.025) (0.022)
Age g oup −0.196*** 0.043**
(0.023) (0.021)
Educa ion −0.295*** −0.018
(0.024) (0.021)
Household size 0.057** 0.023
(0.026) (0.020)
Income −0.156*** −0.078***
(0.023) (0.023)
Female 0.481*** 0.106**
(0.039) (0.042)
Employed 0.041 0.011
(0.043) (0.044)
Pa ne 0.066 −0.007
(0.047) (0.041)
Mig a ion backg ound 0.196*** −0.000
(0.049) (0.041)
Eas Ge many −0.010 0.350***
(0.101) (0.086)
Su ey wa e 0.101** −0.040
(0.039) (0.037)
Cons an 0.458*** −0.212*** 0.470*** 0.349***
(0.025) (0.077) (0.019) (0.078)
Obse a ions 2784 2784 2784 2784
R
2
0.010 0.199 0.016 0.088
Adjus ed
R
2
0.008 0.192 0.014 0.081
No e: This able shows indi idual and egional de e minan s o biases in p io belie s abou he immig an popula ion o esponden who join ly o e es ima ed he sha e
and unemploymen a e o immig an s. S anda d e o s clus e ed a dis ic le el.
*p
<
0.10; **p
<
0.05; ***p
<
0.01.
802 o 886 Jou nal o Regional Science, 2025
TABLE B3 | De e minan s o biases in p io belie s: join unde es ima o s.
Sha e o immig an s Unemploymen o immig an s
(1) (2) (3) (4)
Popula ion densi y −0.014 −0.008 −0.011 0.003
(0.011) (0.013) (0.010) (0.011)
A D o e sha e 0.012 0.023 0.021*0.039**
(0.010) (0.015) (0.011) (0.018)
GDP pe capi a 0.018 0.015 −0.001 −0.004
(0.012) (0.012) (0.010) (0.011)
GDP pe capi a g ow h −0.005 −0.007 −0.003 −0.005
(0.009) (0.009) (0.008) (0.008)
Sha e o immig an s −0.018 −0.019 0.011 0.016
(0.016) (0.016) (0.016) (0.016)
Unemploymen a e o immig an s 0.007 0.003 −0.006 −0.016
(0.010) (0.010) (0.011) (0.010)
Sha e o e ugees −0.010 −0.004 −0.006 0.005
(0.011) (0.012) (0.014) (0.013)
Conce ns abou immig a ion −0.009 0.003
(0.012) (0.010)
Conce ns abou economic de elopmen −0.003 −0.021**
(0.009) (0.008)
Conce ns abou COVID‐19 c isis 0.001 0.007
(0.009) (0.008)
A i ude owa d cul u al di e si y −0.011 −0.009
(0.010) (0.009)
Poli ical a i ude −0.001 −0.016**
(0.009) (0.008)
Age g oup 0.004 −0.005
(0.009) (0.009)
Educa ion −0.004 −0.036***
(0.009) (0.008)
Household size 0.016** 0.015**
(0.008) (0.006)
Income −0.013 −0.026***
(0.009) (0.007)
Female −0.001 0.059***
(0.016) (0.015)
Employed 0.017 0.016
(0.018) (0.017)
Pa ne −0.010 0.009
(0.017) (0.015)
Mig a ion backg ound 0.016 0.028
(0.020) (0.019)
Eas Ge many −0.035 −0.060
(0.040) (0.045)
(Con inues)
803 o 886
TABLE D5 | T ea men e ec he e ogenei y: GDP pe capi a g ow h.
Wel a e s a e Labo ma ke Immig. ad an age Immig. policy
(1) (2) (3) (4)
Panel A: Dis ic s wi h high GDP pe capi a g ow h
In o Sha e 0.087** 0.097** 0.076*0.149***
(0.042) (0.042) (0.039) (0.034)
In o Unemploymen 0.166*** 0.090** 0.092** 0.075**
(0.044) (0.042) (0.035) (0.035)
In o Bundle 0.071 0.046 0.029 0.058
(0.046) (0.047) (0.041) (0.042)
Obse a ions 2666 2666 2666 2666
R
2
0.323 0.308 0.475 0.542
Adjus ed
R
2
0.317 0.301 0.470 0.537
Wel a e s a e Labo ma ke Immig. ad an age Immig. policy
(1) (2) (3) (4)
Panel B: Dis ic s wi h low GDP pe capi a g ow h
In o Sha e 0.097** 0.026 0.090** 0.033
(0.041) (0.041) (0.035) (0.032)
In o Unemploymen 0.071*−0.027 0.054*0.032
(0.040) (0.042) (0.031) (0.031)
In o Bundle 0.125*** −0.023 0.024 0.043
(0.043) (0.041) (0.033) (0.035)
Obse a ions 3032 3032 3032 3032
R
2
0.318 0.348 0.484 0.538
Adjus ed
R
2
0.312 0.342 0.479 0.534
No e: This able shows he ea men e ec s o in o ma ion p o ision in dis ic s wi h high and low GDP pe capi a g ow h. The sample was spli along he median. The
eg ession includes indi idual and egional con ol a iables. Indi idual con ols include belie s abou he sha e o immig an s in Ge many, belie s abou he
unemploymen a e o immig an s in Ge many, conce ns abou immig a ion, conce ns abou economic de elopmen , conce ns abou he COVID‐19 c isis, a i udes
owa d cul u al di e si y, poli ical a i udes, age, educa ion, household size, income, gende , employmen s a us, pa ne , mig a ion backg ound, and an indica o o he
su ey wa e. Regional con ols include li ing in Eas Ge many, popula ion densi y, A D o e sha e, GDP pe capi a, GDP pe capi a g ow h, sha e o immig an s,
unemploymen a e o immig an s, and sha e o e ugees. S anda d e o s a e clus e ed a he dis ic le el.
*p
<
0.10; **p
<
0.05; ***p
<
0.01.
810 o 886 Jou nal o Regional Science, 2025

Appendix E
Robus ness Checks
Di e en Regional Speci ica ions
Analysis a he NUTS 2 Le el
We also un ou analysis wi h egional co a ia es a he NUTS 2 le el,
which oughly co esponds o Regie ungsbezi ke in Ge many, o see i
ou esul s hold a a highe , i.e. less disagg ega ed, adminis a i e le el.
Table E1 shows he esul s o egional he e ogenei y based on a ia ion
a he NUTS 2 le el in he sha e o immig an s, he A D o e sha e, and
GDP g ow h. The e a e some di e ences in he signi icance le els, o
example, we do no ind signi ican di e ences in labo ma ke a i udes
be ween egions wi h low and high sha es o immig an s. Ne e heless,
he in e p e a ions o he o e all pa e n o he e ogenei y ac oss he
di e en ypes o egions emain he same. Figu e E1 p esen s he
esul s g aphically allowing o an easy compa ison wi h ou dis ic ‐
le el esul s.
Analysis Wi h Fede al S a e Fixed E ec s
Ano he conce n migh be ha a ia ions a he s a e le el, o example,
ce ain policies, migh in luence ou esul s. We add ess his conce n by
including ca ego ical a iables o he Ge man ede al s a es, ha is,
s a e ixed e ec s, o accoun o changes a he s a e le el. The esul s
a e shown in Table E2. Compa ed o he main speci ica ion, he esul s
emain almos he same. We can he e o e conclude ha con olling o
s a e ixed e ec s does no al e ou esul s. Figu e E2 p esen s he
esul s g aphically allowing o an easy compa ison wi h ou dis ic ‐
le el esul s.
O de ed P obi
Ou ou come a iables can also be seen as o dinal dependen a iables,
o example, wel a e s a e a i udes anging om 0 ( ecei e mo e ben-
e i s) o 10 (pay mo e axes) o immig a ion policy p e e ences anging
om 1 (dec ease a lo ) o 5 (inc ease a lo ). Thus, we could also employ
an o dinal eg ession model o e alua e ea men e ec s. Table E3
displays ou comes o an o de ed p obi eg ession. Gi en he signs o
he coe icien s, he in e p e a ion o he ea men e ec s is compa able
o he o iginal speci ica ion. See Figu e E3 o he esul s in compa ison
wi h ou OLS esul s.
FIGURE D1 | T ea men e ec s: compa ison o join o e es ima o s
and join unde es ima o s. The sample is spli in esponden s who
join ly o e ‐o join ly unde es ima e he sha e o immig an s and he
unemploymen a e o immig an s. Fo join o e es ima o s, he com-
pa ison is wi h hose who a mos o e es ima e one s a is ic; o join
unde es ima o s, he compa ison is hose who a mos unde es ima e
one s a is ic. S anda d e o s clus e ed by dis ic s. The 90% con idence
in e als displayed. In o al, 2784 esponden s join ly o e es ima e bo h
he sha e o immig an s and he unemploymen a e o immig an s and
853 join ly unde es ima e bo h. The eg ession includes indi idual and
egional con ol a iables. Indi idual con ols include belie s abou he
sha e o immig an s in Ge many, belie s abou he unemploymen a e
o immig an s in Ge many, conce ns abou immig a ion, conce ns
abou economic de elopmen , conce ns abou he COVID‐19 c isis,
a i udes owa d cul u al di e si y, poli ical a i udes, gende , age,
educa ion, income, pa ne , household size, employmen s a us,
mig a ion backg ound, and an indica o o he su ey wa e. Regional
con ols include li ing in Eas Ge many, popula ion densi y, A D o e
sha e, GDP pe capi a, GDP pe capi a g ow h, sha e o immig an s,
unemploymen a e o immig an s, and sha e o e ugees.
811 o 886
TABLE E1 | T ea men e ec he e ogenei y: NUTS 2 le el.
Abo e median Below median
Wel a e
s a e
Labo
ma ke
Immig.
ad .
Immig.
policy
Wel a e
s a e
Labo
ma ke
Immig.
ad .
Immig.
policy
(1) (2) (3) (4) (5) (6) (7) (8)
Panel A: Sha e o immig an s
In o Sha e 0.103*0.002 0.077*0.043 0.088** 0.118*** 0.096*** 0.128***
(0.052) (0.045) (0.041) (0.037) (0.043) (0.036) (0.029) (0.030)
In o
Unemploymen
0.107** −0.009 0.046*0.005 0.142*** 0.075 0.101*** 0.093***
(0.037) (0.027) (0.024) (0.021) (0.033) (0.047) (0.019) (0.028)
In o Bundle 0.145*** −0.012 0.018 0.040 0.061*0.019 0.023 0.045
(0.039) (0.039) (0.033) (0.043) (0.035) (0.040) (0.034) (0.028)
Obse a ions 2860 2860 2860 2860 2843 2843 2843 2843
R
2
0.318 0.349 0.491 0.535 0.320 0.311 0.466 0.541
Panel B: A D o e sha e
In o Sha e 0.107** 0.098** 0.102** 0.081** 0.087*0.030 0.076** 0.091**
(0.049) (0.037) (0.037) (0.039) (0.046) (0.048) (0.033) (0.031)
In o
Unemploymen
0.117*** 0.042 0.079*** 0.027 0.134*** 0.025 0.076*** 0.070**
(0.035) (0.049) (0.025) (0.027) (0.034) (0.030) (0.017) (0.026)
In o Bundle 0.069** −0.044 0.016 0.019 0.138*** 0.052 0.031 0.070
(0.029) (0.041) (0.031) (0.026) (0.044) (0.036) (0.033) (0.042)
Obse a ions 2702 2702 2702 2702 3001 3001 3001 3001
R
2
0.331 0.308 0.459 0.525 0.308 0.344 0.493 0.546
Panel C: GDP g ow h
In o Sha e 0.127*** 0.139*** 0.128*** 0.137*** 0.068 0.004 0.053 0.039
(0.043) (0.037) (0.033) (0.035) (0.050) (0.040) (0.035) (0.030)
In o
Unemploymen
0.153*** 0.083 0.094*** 0.085** 0.104*** −0.009 0.058** 0.017
(0.035) (0.048) (0.019) (0.030) (0.035) (0.030) (0.023) (0.021)
In o Bundle 0.096** 0.044 0.042 0.046 0.109*** −0.017 0.007 0.039
(0.040) (0.046) (0.041) (0.037) (0.037) (0.034) (0.027) (0.035)
Obse a ions 2585 2585 2585 2585 3118 3118 3118 3118
R
2
0.329 0.317 0.473 0.540 0.318 0.340 0.485 0.539
No e: This able shows esul s a he NUTS 2 le el. The eg ession includes indi idual and egional con ol a iables. Indi idual con ols include belie s abou he sha e o
immig an s in Ge many, belie s abou he unemploymen a e o immig an s in Ge many, conce ns abou immig a ion, conce ns abou economic de elopmen , conce ns
abou he COVID‐19 c isis, a i udes owa d cul u al di e si y, poli ical a i udes, gende , age, educa ion, income, pa ne , household size, employmen s a us, mig a ion
backg ound, and an indica o o he su ey wa e. Regional con ols include li ing in Eas Ge many, popula ion densi y, A D o e sha e, GDP pe capi a, GDP pe capi a
g ow h, sha e o immig an s, unemploymen a e o immig an s, and sha e o e ugees. S anda d e o s clus e ed a he NUTS 2 le el.
*p
<
0.10; **p
<
0.05; ***p
<
0.01.
812 o 886 Jou nal o Regional Science, 2025
FIGURE E1 | Robus ness check: NUTS‐2 le el esul s compa ed o dis ic ‐le el esul s. This igu e g aphically compa es he es ima ion esul s
om Table E1 o NUTS‐2 (panel b) wi h he o iginal esul s on he dis ic ‐le el (panel a).
813 o 886
TABLE E2 | T ea men e ec he e ogenei y: s a e ixed e ec s.
Abo e median Below median
Wel a e
s a e
Labo
ma ke
Immig.
ad .
Immig.
policy
Wel a e
s a e
Labo
ma ke
Immig.
ad .
Immig.
policy
(1) (2) (3) (4) (5) (6) (7) (8)
Panel A: Sha e o immig an s
In o Sha e 0.071*−0.009 0.083** 0.057*0.153*** 0.189*** 0.086** 0.134***
(0.038) (0.039) (0.034) (0.031) (0.052) (0.051) (0.043) (0.046)
In o
Unemploymen
0.110*** 0.016 0.075** 0.031 0.148*** 0.066 0.070*0.083**
(0.038) (0.037) (0.031) (0.031) (0.050) (0.054) (0.037) (0.038)
In o Bundle 0.134*** 0.001 0.045 0.065*0.064 0.028 −0.007 0.015
(0.042) (0.039) (0.032) (0.036) (0.046) (0.051) (0.044) (0.039)
Obse a ions 3657 3657 3657 3657 2041 2041 2041 2041
R
2
0.327 0.348 0.488 0.530 0.310 0.307 0.469 0.557
Panel B: A D o e sha e
In o Sha e 0.104** 0.041 0.081*0.055 0.090** 0.076** 0.090*** 0.098***
(0.052) (0.055) (0.045) (0.046) (0.036) (0.037) (0.032) (0.029)
In o
Unemploymen
0.137*** −0.032 0.061 0.009 0.113*** 0.064*0.080*** 0.070**
(0.049) (0.053) (0.041) (0.044) (0.038) (0.039) (0.029) (0.029)
In o Bundle 0.116** −0.002 0.023 −0.004 0.106** 0.016 0.023 0.075**
(0.048) (0.050) (0.045) (0.041) (0.043) (0.040) (0.032) (0.034)
Obse a ions 2066 2066 2066 2066 3632 3632 3632 3632
R
2
0.322 0.295 0.451 0.518 0.319 0.352 0.497 0.550
Panel C: GDP g ow h
In o Sha e 0.082*0.103** 0.074*0.151*** 0.104** 0.027 0.094*** 0.032
(0.044) (0.044) (0.040) (0.035) (0.042) (0.043) (0.035) (0.033)
In o
Unemploymen
0.166*** 0.093** 0.095*** 0.075** 0.073*−0.021 0.054*0.036
(0.045) (0.045) (0.036) (0.036) (0.042) (0.043) (0.032) (0.033)
In o Bundle 0.073 0.050 0.033 0.061 0.133*** −0.022 0.023 0.044
(0.047) (0.049) (0.042) (0.043) (0.045) (0.042) (0.033) (0.036)
Obse a ions 2666 2666 2666 2666 3032 3032 3032 3032
R
2
0.328 0.312 0.479 0.544 0.323 0.353 0.488 0.542
No e: The eg ession includes ede al s a e ixed e ec s. The eg ession includes indi idual and egional con ol a iables. Indi idual con ols include belie s abou he
sha e o immig an s in Ge many, belie s abou he unemploymen a e o immig an s in Ge many, conce ns abou immig a ion, conce ns abou economic de elopmen ,
conce ns abou he COVID‐19 c isis, a i udes owa d cul u al di e si y, poli ical a i udes, gende , age, educa ion, income, pa ne , household size, employmen s a us,
mig a ion backg ound, and an indica o o he su ey wa e. Regional con ols include li ing in Eas Ge many, popula ion densi y, A D o e sha e, GDP pe capi a, GDP
pe capi a g ow h, sha e o immig an s, unemploymen a e o immig an s, and sha e o e ugees. S anda d e o s clus e ed a he dis ic le el.
*p
<
0.10; **p
<
0.05; ***p
<
0.01.
814 o 886 Jou nal o Regional Science, 2025
FIGURE E2 | Robus ness check: dis ic ‐le el esul s wi hou and wi h s a e ixed e ec s. This igu e g aphically compa es he es ima ion esul s
wi h s a e ixed e ec s om Table E2 (panel b) wi h he o iginal esul s wi hou s a e ixed e ec s (panel a).
815 o 886

TABLE E3 | T ea men e ec he e ogenei y: o de ed p obi eg ession.
Abo e median Below median
Wel a e
s a e
Labo
ma ke
Immig.
ad .
Immig.
policy
Wel a e
s a e
Labo
ma ke
Immig.
ad .
Immig.
policy
(1) (2) (3) (4) (5) (6) (7) (8)
Panel A: Sha e o immig an s
In o Sha e 0.088*−0.009 0.123** 0.101** 0.192*** 0.228*** 0.127** 0.246***
(0.048) (0.047) (0.049) (0.052) (0.065) (0.062) (0.062) (0.079)
In o
Unemploymen
0.141*** 0.011 0.111** 0.060 0.199*** 0.085 0.111** 0.162**
(0.048) (0.046) (0.044) (0.052) (0.063) (0.065) (0.053) (0.066)
In o Bundle 0.165*** 0.009 0.066 0.110*0.070 0.020 −0.016 0.035
(0.053) (0.051) (0.046) (0.058) (0.060) (0.063) (0.063) (0.067)
Obse a ions 3657 3657 3657 3657 2041 2041 2041 2041
Pseudo
R
2
0.092 0.100 0.146 0.268 0.085 0.087 0.138 0.292
Panel B: A D o e sha e
In o Sha e 0.139** 0.058 0.124*0.122 0.117*** 0.091** 0.135*** 0.170***
(0.066) (0.066) (0.066) (0.076) (0.045) (0.046) (0.047) (0.051)
In o
Unemploymen
0.184*** −0.032 0.095*0.033 0.148*** 0.074 0.118*** 0.124**
(0.063) (0.063) (0.058) (0.072) (0.047) (0.049) (0.042) (0.051)
In o Bundle 0.138** 0.001 0.023 0.008 0.133** 0.022 0.042 0.132**
(0.061) (0.062) (0.065) (0.066) (0.054) (0.051) (0.046) (0.057)
Obse a ions 2066 2066 2066 2066 3632 3632 3632 3632
Pseudo
R
2
0.089 0.084 0.133 0.263 0.089 0.101 0.148 0.283
Panel C: GDP g ow h
In o Sha e 0.122** 0.121** 0.114** 0.268*** 0.124** 0.036 0.141*** 0.060
(0.054) (0.055) (0.057) (0.059) (0.052) (0.053) (0.052) (0.057)
In o
Unemploymen
0.233*** 0.103*0.141*** 0.158** 0.086*−0.030 0.086*0.047
(0.056) (0.055) (0.051) (0.062) (0.052) (0.055) (0.047) (0.055)
In o Bundle 0.103*0.057 0.045 0.108 0.153*** −0.026 0.037 0.072
(0.061) (0.061) (0.059) (0.069) (0.056) (0.054) (0.049) (0.059)
Obse a ions 2666 2666 2666 2666 3032 3032 3032 3032
Pseudo
R
2
0.092 0.089 0.141 0.280 0.090 0.102 0.145 0.276
No e: This able shows esul s o ea men e ec he e ogenei y es ima ed wi h an o de ed p obi eg ession. The eg ession includes indi idual and egional con ol
a iables. Indi idual con ols include belie s abou he sha e o immig an s in Ge many, belie s abou he unemploymen a e o immig an s in Ge many, conce ns abou
immig a ion, conce ns abou economic de elopmen , conce ns abou he COVID‐19 c isis, a i udes owa d cul u al di e si y, poli ical a i udes, gende , age, educa ion,
income, pa ne , household size, employmen s a us, mig a ion backg ound, and an indica o o he su ey wa e. Regional con ols include li ing in Eas Ge many,
popula ion densi y, A D o e sha e, GDP pe capi a, GDP pe capi a g ow h, sha e o immig an s, unemploymen a e o immig an s, and sha e o e ugees. S anda d
e o s clus e ed a he dis ic le el.
*p
<
0.10; **p
<
0.05; ***p
<
0.01.
816 o 886 Jou nal o Regional Science, 2025
FIGURE E3 | Robus ness check: O de ed p obi esul s compa ed o OLS esul s. This igu e compa es he o de ed p obi es ima ion esul s om
Table E3 o he o iginal OLS esul s.
817 o 886