Am ouche, Nawel; Hababou, Moez
A icle
Role o social media in socioeconomic de elopmen : Case
o Facebook
Re iew o Economic Analysis (REA)
P o ided in Coope a ion wi h:
In e na ional Cen e o Economic Analysis (ICEA), Wa e loo, On a io
Sugges ed Ci a ion: Am ouche, Nawel; Hababou, Moez (2022) : Role o social media in socioeconomic
de elopmen : Case o Facebook, Re iew o Economic Analysis (REA), ISSN 1973-3909, In e na ional
Cen e o Economic Analysis (ICEA), Wa e loo (On a io), Vol. 14, Iss. 3, pp. 381-417,
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Role o Social Media in Socioeconomic De elopmen :
Case o Facebook
Nawel Am ouche
Long Island Uni e si y 
Moez Hababou
BNP Pa ibas, NY
To s udy he ole o In o ma ion and Communica ion Technology (ICT) on coun ies’
socioeconomic de elopmen , he pape in es iga es he case o Facebook pene a ion on
imp o ing hei s anding as measu ed ia GNI pe capi a PPP (G oss Na ional Income pe
capi a based on pu chasing powe pa i y). We use ou mac o ac o s ca ego ies (poli ical,
economic, demog aphic, and echnological) in addi ion o Facebook pene a ion pe capi a
in o de o measu e he po en ial in luence o a ious ac o s on he socioeconomic le el
o coun ies. While he analyses o ICT e ec on de elopmen has been he ocus o many
pape s in he pas , he speci ic analysis o social media is sca ce. Compa ed o p e ious
s udies in es iga ing social media ole, we use a la ge da ase co e ing all classes o
coun ies and examine holis ically many ypes o de e minan s using di e en models. In
addi ion, we dis inguish ou pape using he economic classi ica ion o coun ies acco ding
o he Wo ld Bank. Ou s udy indica es ha Facebook pene a ion has a signi ican posi i e
ole on he socioeconomic le el o coun ies, bu such ole a ies depending on he
coun ies’ classi ica ion le el. Besides, he e is a dec easing ma ginal e ec showing he
impo ance o policy make s o assess he complex dynamic behind he cha ac e is ic o
each coun y.
Keywo ds: Facebook pene a ion; Coun y le el analysis; Socioeconomic de elopmen ; Wo ld
Bank classi ica ion.
JEL Classi ica ion: F63.
1 In oduc ion
In o ma ion and Communica ion Technology (ICT) changed ou li es on many le els such as
social, poli ical, educa ional, medical, and business le els (Roz ocki e al. 2019). The impac o
ICT on social s anding (i.e., socie y wellbeing) and economic s anding has a ac ed he
 We hank D . Kamel Jedidi (Columbia Uni e si y) o his eedback on he ini ial e sions o his pape . We
hank D . Shin Haeng Lee (Sejong Uni e si y) o p o iding he da a abou Facebook Pene a ion by coun y.
Am ouche: Associa e P o esso o Ma ke ing, nao[email p o ec ed]; Hababou: Di ec o , Model
Risk Managemen , BNP Pa ibas, NY [email protected].
© 2022 Nawel Am ouche and Moez Hababou. Licensed unde he C ea i e Commons A ibu ion -
Noncomme cial 4.0 Licence (h p://c ea i ecommons.o g/licenses/by-nc/4.0/.
A ailable a h p:// o ea.o g.
Re iew o Economic Analysis 14 (2022) 381-417
382
www.Ro EA.o g
a en ion o many esea che s and p ac i ione s. Many concep ual amewo ks (e.g., Madon
2000; Roz ocki and Weis o e 2016) ha e been p oposed o link he powe o ICT o he social
(e.g., educa ion, heal h, democ acy) and economic de elopmen (e.g., income, economic
p oduc i i y, alle ia ion o po e y).
Following B own and G an (2010), we adop he same de ini ion as Von B aun and
To e o’s (2006) abou ICT. I is any echnology in as uc u e o digi al ecosys em enabling he
c ea ion, collec ion, dis ibu ion, usage and s o age o in o ma ion. Hence, ICT encompasses
o example a ious social media pla o ms, emails, in ane s, ex ane s, e c. B own and G an
(2010) e iewed 184 jou nal a icles and p oceedings linking ICT o de elopmen and
explained ha he e a e wo s eam o esea ch: 1/ s udies ocusing on he e ec o ICT on
de elopmen and 2/ s udies ocusing on he impac o ICT in de eloping coun ies. In addi ion,
we adop he de ini ion o OECD abou social capi al as “ne wo ks oge he wi h sha ed no ms,
alues and unde s andings ha acili a e coope a ion wi hin o among g oups” (OECD, 2001).
Ano he p ojec om OECD (based on he wo k o Sc i ens and Smi h, 2013), de ailed ou
in e p e a ions o he social capi al concep : 1/ Pe sonal ela ionships which is exchanging
in o ma ion ia social ne wo ks, 2/ Social ne wo k suppo which is he ou come o he social
ne wo k, 3/ Ci ic engagemen which is abou ac i i ies such as communi y ac ions, and 4/ T us
and coope a i e no ms which is composed o sha ed alues os e ing mu ual bene i and
coope a ion.
Some s udies ocused on speci ic case analyses such as Ash a e al. (2017) who examined
a communi y le el case o Bangladesh, and Pal ia e al. (2018) who ocused on Pakis an
socioeconomic de elopmen ela ed o he applica ion o ICT ools and p og ams. The p e ious
amewo ks a e desc ip i e and concep ual. In addi ion, a numbe o empi ical s udies (e.g.,
C onin e al. 1991; Colecchia and Sch eye 2002) a e e y limi ed o speci ic economies and
dis ega d o he ypes o egions o coun ies.
In ou pape , we o e an empi ical analysis o a special ype o social media (i.e., he case
o Facebook as a digi al ecosys em and an enhance o social capi al) in o de o in es iga e he
in e play o ICT ( ia Facebook pla o m) on he socioeconomic de elopmen o he majo i y o
coun ies in he wo ld. Fo ha pu pose, we s a i y hese coun ies in o all ou economic le els
acco ding o he Wo ld Bank classi ica ion (de eloped o high income, uppe middle income,
low middle income, and low income). Hence, ou pape joins he i s s eam o esea ch
acco ding o B own and G an (2010) and ocus on examining he e ec o ICT ( ia Facebook
as a digi al ecosys em case) on socioeconomic de elopmen o coun ies ac oss he globe.
As o he ou h qua e o 2020, Facebook use s eached exceeded by a 2500 million use s
(S a is a, 2020), making i he la ges ne wo k connec ing he wo ld. Howe e , does his social
ne wo king sys em gene a e economic g ow h? Ma k Zucke be g, co- ounde o Facebook,
en isioned ha global po e y could be educed h ough In e ne connec i i y (see Zucke be g
AMROUCHE, HABABOU Role o Social Media in Socioeconomic De elopmen
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2014). Howe e , he ques ion is s ill deba able as some s udies showed con adic ing esul s.
Economis s a e also a guing abou i s eal e ec .
A 2015 Deloi e Repo ound empi ically ha Facebook has a global economic impac . The
s udy ocused on companies’ sales and included ma ke ing e ec s ( acili a ing ma ke ing
e o s and en ep eneu ship), pla o m e ec s (o e ing pla o ms o apps’ de elope s and
os e ing inno a ion) and connec i i y e ec s (s imula ing p oduc s’ pu chase and spilling o e
da a consump ion). Acco ding o he epo , Uni ed S a es is he la ges bene icia y in e ms o
economic in luence (wi h $100 billion e enues and 1076 housands jobs c ea ed), ollowed by
Uni ed Kingdom ($11 billion e enues and 154 housand jobs c ea ed), hen B azil ($10 billion
e enues and 231 housand jobs c ea ed). The s udy ecei ed con o e sial eedback om
economis s. As epo ed by Albe go i (2015), some economis s ques ioned he s udy
assump ions. O he s a i m ha Facebook is jus he esul o using and accessing he In e ne
wi h no ecip ocal e ec . Finally, ano he g oup o economis s app o es Facebook impac bu
disag ees abou he magni ude epo ed by Deloi e. Indeed, he cen al ques ion ha consul ing
companies and economis s a e deba ing is whe he Facebook is signi ican ly boos ing he
economic well-being o coun ies.
Flo ida (2010) examined he case o US and pe o med di e en co ela ion analyses
be ween social media me ics (Ne ospex social index o NPSI p o ided by Ne P ospex 2010)
and a ious mac o ac o s o each US s a e. The s udy ound ha social media is highly and
posi i ely co ela ed wi h economic ou pu , income, high ech indus y, human capi al
(measu ed ia educa ion le el), a is ic and cul u ally c ea i e jobs, and openness o di e si y.
Howe e , social media has a modes posi i e co ela ion wi h inno a ion (measu ed ia he
numbe o pa en s as a p oxy a iable).
To ou knowledge, only one academic s udy looked empi ically a he e ec o social media
on he economic de elopmen a he coun y le el. Dell’Anno e al. (2016) used a g ow h
eg ession model and included social media pene a ion index (combina ion o Facebook and
o he ypes o social ne wo ks’ use s) o es i s impac on GDP pe capi a. They ound
unexpec edly, in he majo i y o es ed models, ha social media has signi ican nega i e e ec
on economic g ow h. Thei a ionale is ha social media augmen s in o ma ion cos and
possible dis ac ion due o swi ching be ween labo and en e ainmen . O he s udies ocused
only on he in luence o social media on business pe o mance o go e nmen wo kabili y and
ask enhancemen , and did no ake a mac o look a he coun y le el.
In ou pape , we explo e he e ec o Facebook pene a ion, among o he mac o- ac o s, on
coun ies’ socioeconomic de elopmen ia na ional income le el. The esea ch ques ion is
impo an as i could help many coun ies su e ing om low socioeconomic s anding o
implemen e ec i e solu ions. I is also bene icial o high-income coun ies as i con ibu es
o u he enhancing hei socioeconomic de elopmen . Ou pape explo e his cen al ques ion
by assessing he de e minan s o he socioeconomic le el o 160 coun ies and inco po a e
Re iew o Economic Analysis 14 (2022) 381-417
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Facebook pene a ion as one o he po en ial de e minan s. We use di e en app oaches in o de
o look o esul s’ con e gence and suppo ou conclusions. Ou s udy is among he i s wo ks
o explo e such ques ion. Hence, we p opose ou indings as ini ial g ound ha needs u he
con i ma ion in u u e esea ch by u ilizing la ge da ase , longe da a ame, and addi ional
models.
We con ibu e o he li e a u e on many no el poin s. Fi s , as sugges ed by Sein e al.
(2018), we o e a holis ic app oach o s udy he ICT e ec by in es iga ing he impac o
a ious ac o s (poli ical, echnological, economic and demog aphic) on he socioeconomic
le el o 160 coun ies ac oss all economic classes (as de ined by he Wo ld Bank). Mo eo e ,
by u ilizing GNI pe capi a PPP as p oxy, ou s udy explo es he b oade impac o ICT on he
socioeconomic de elopmen o coun ies, a he han on i s domes ic economic ou pu (as
measu ed by GDP pe capi a). Second, we ocus on Facebook, which is he mos popula social-
ne wo k pla o m in he Wo ld in 151 coun ies ou o 167 coun ies as o Janua y 2020 (Vincos
Blog, 2020), a he han a combina ion o social media si es as did Dell’Anno e al. (2016). The
pu pose o ocusing only on Facebook is o isola e he e ec o one speci ic social ne wo king
si e. Thi d, we assess he e ec o Facebook pene a ion on coun ies’ socioeconomic le el
using a ious me hods and models in o de o in es iga e he possible con e gence o ou
esul s and each indings ha a e mo e obus . Fou h, we examine he po en ial di e en ial
e ec o Facebook pene a ion on di e en classes o coun ies o: 1/ e i y i he esul s in he
whole sample could be eplica ed o each class o coun ies, 2/ e i y i he esul is
cha ac e is ic o each Wo ld Bank class. Qu eshi (2015) p oposed di e en le els o analysis
o he e ec o ICT on de elopmen such as egion, ins i u ion, indi idual, and coun y. Fi h,
we use a la ge da ase , o e mul iple yea s and a la ge numbe o coun ies, which p o ides
mo e alidi y o he empi ical indings o he s udy. Finally, we in es iga e a ious ypes o
e ec o Facebook, which was no he conce n o p e ious s udies.
Ou indings show ia di e en models ha Facebook has consis en ly a signi ican posi i e
e ec on he socioeconomic de elopmen o coun ies. In addi ion, i could ha e di e en
shapes o e ec e lec ing a mo e complex ela ionship be ween social media usage and he
economic s anding han simply a signi ican posi i e e ec . The ype o e ec also depends on
he cha ac e is ics o he coun y based on he Wo ld Bank classi ica ion. We ied se e al
s a is ical echniques namely he O dina y Leas Squa es (OLS) model, he ixed e ec model,
and he andom e ec model. All models con i med he po en ial posi i e e ec o Facebook
as well as i s diminishing e ec o e ime. The issue o causali y he e should be emphasized as
i is deba able whe he mo e social media pene a ion in a coun y leads o be e economy o
be e economy in a coun y leads o highe usage o social media. As we will discuss la e in
he pape , we ha e in oduced some mi igan s in he esea ch design o add ess possible e e se
causali y.

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The pape is o ganized as ollows o he emaining pa s. Sec ion 2 explains he p e ious
s udies ha looked a he ela ionship be ween social media and businesses, go e nmen
agencies, indi iduals, o he economic s anding o coun ies. Sec ion 3 p o ides a desc ip ion
o he me hodology and a summa y o he da a ope a ionaliza ion. Sec ion 4 explains he
econome ic analyses ia di e en models. Sec ion 5 p esen s a discussion o he esul s.
Sec ion 6 o e s p ac ical and manage ial implica ions o ou esea ch. Finally, Sec ion 7
concludes by o e ing pe spec i es o explo e in u u e s udies.
2 Li e a u e Re iew
Following he holis ic amewo k o Sein e al. (2018) o s udy ICT e ec , ou pape ouches a
h ee le els o he amewo k: he i s le el is he digi al ecosys em by ocusing on Facebook
pene a ion as a special case o social media pla o ms o s udy. A he second le el, he
socioeconomic de elopmen is measu ed by he GNI pe capi a PPP (pu chasing powe pa i y)
o each coun y. The GNI is de ined by OECD as “g oss domes ic p oduc , plus ne eceip s
om ab oad o compensa ion o employees, p ope y income and ne axes less subsidies on
p oduc ion.” OECD, 2020). Hence, GNI pe capi a is conside ed a good p oxy o he social
and economic wellbeing o a coun y, as i p o ides a mo e comple e pic u e o a coun y’s o al
economic income, ega dless o i s sou ce. Compa ed o GDP pe capi a measu ing he alue
o domes ic p oduc ion and ou pu , GNI pe capi a PPP is he alue o domes ic and o eign
p oduc ion aking in o accoun he pu chasing powe pa i y as a measu e o socioeconomic
de elopmen . Hence, ou s udy will ocus on he b oade impac o ICT on he socioeconomic
de elopmen o coun ies, a he han on hei domes ic economic ou pu (as measu ed by GDP
pe capi a). A he hi d le el, he ans o ma i e p ocess is based on he a ie y o ac o s used
in ou s udy in o de o unco e he in e ela ionship be ween poli ics, echnology, demog aphy
and economic con ex on he o e all de elopmen s anding o each coun y.
A numbe o s udies in es iga ed he e ec o ICT on he economic s anding. Lee e al.
(2017) p o ided a li e a u e e iew o hese pape s. To illus a e, C onin e al. (1991) used ime
se ies analysis o US da a and ound ha elecommunica ion in as uc u e posi i ely
in luenced economic g ow h. Analyzing OECD coun ies, Colecchia and Sch eye (2002)
ound ha ICT had con ibu ed posi i ely o economic g ow h and he magni ude o he posi i e
e ec is idiosync a ic o he coun y. Analyzing de eloped and de eloping coun ies,
Papaioannou and Dimelis (2007) also ound a posi i e impac o ICT on labo p oduc i i y
g ow h wi h s onge impac o de eloped coun ies. Howe e , he e a e pape s ha showed a
con o e sial e ec such as Lee e al. (2005) who ound ha ICT in es men s imp o ed
p oduc i i y le els o de eloped and newly indus ialized economies, bu ha was no he
esul o de eloping coun ies.
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P e ious esea ch ha speci ically examined he social media e ec on socioeconomic
de elopmen used di e en uni s o s udy such as go e nmen , indi idual, as well as a na owe
lis o coun ies. Fo example, some s udies examined he bene i o social media on businesses
(e.g., Aghakhani e al. 2018; Chen e al. 2012; Goh e al. 2013; Pen ina e al. 2013; Rishika e
al. 2013). O he s udies ocused on he e ec on E-go e nmen (e.g., G aham 2014;
Landsbe gen 2010; Ve degem and Ve leye 2009). Howe e , he bene i o social media on
coun ies’ economic le el is s ill an open ques ion. Di e en pape s examined also he e ec o
social capi al (Ellison e al. 2007; Munzel e al. 2018; S ein ield e al. 2008) h ough
in ol emen in social ne wo ks on people wel a e (G oo e al. 2007; Helliwell and Pu nam
2005; Winkelmann 2009; Allco e al. 2020). They a gued ha pa icipa ing in social ac i i ies
and being pa o a g ea e ne wo k ha e a posi i e in luence on people in e ms o hei well-
being and sel -wo h. Ne e heless, Winkelmann (2009) did no ind signi ican mode a ing
e ec o social capi al on people wel a e when hey a e unemployed. Allco e al. (2020) ound
ha , by s udying he case o Facebook using an expe imen , deac i a ing social media imp o ed
o line ac i i ies, educed poli ical pola iza ion, and boos ed social wel a e. . I a ec ed also
pos de-ac i a ion by educing online pe sis ence and Facebook alua ion. O he s udies
p o ided ei he desc ip i e o empi ical e idence ha social capi al and ne wo ks ha e an added
alue in e ms o job c ea ion and o he economic bene i s (A idi 2011; Cal o-A mengol and
Jackson 2004; Fe nandez e al. 2000; Hann e al. 2011; Waldinge 1997;). Fo ins ance, Hann
e al. (2011) showed empi ically ha ne wo king on Facebook c ea e ies be ween apps’
de elope s which helps imp o e i ms’ employmen and c ea e signi ican bene i o he
indus y. Choudhu y (2018) desc ibed he ole o mul iple languages and mobile echnology in
enhancing he sp ead o Facebook in de eloped and de eloping coun ies. O he s udies
ocused on he e ec o social media on a pa icula economic a iable such as Oz u k and
Ci ci (2014) who s udied he e ec o numbe o wee s and Twi e sen imen on he
mo emen o exchange a e.
Dell’Anno e al. (2016) s udied he ela ionship be ween social media (measu ed as a
combina ion o social media si es’ use s depending on he a ailable da a o Facebook,
Linkedin, Twi e and Google +) and he coun y ou pu (GDP pe capi a). They used a g ow h
eg ession model (be ween 2007 and 2012) and s udied he case o 83 coun ies. One da a
limi a ion in he pape is i s ep esen a i eness o ce ain geog aphies. Fo ins ance, he s udy
only included 9 ou o 54 A ican coun ies. They ound ha social media has a signi ican
nega i e e ec on economic g ow h. They explained ha social media could augmen
in o ma ion and ansac ion cos s due o he con en clu e , and could lead o labo dis ac ion
due o inclina ion o leisu e and en e ainmen . They p oposed hough an opposing hypo hesis
ha social media could induce he di usion o knowledge, which ul ima ely helps he economic
g ow h. Howe e , hey we e no able o ind e idence o such a posi i e e ec .
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Vi enu-Sackey (2020) examined he e ec o a ious social media (i.e., Facebook,
YouTube, Twi e and Pin e es ) on economic g ow h. They ocused on GDP as a esponse
a iable and s udied he case o 198 coun ies on a span o ime be ween 2009 and 2017. They
ound ha social media could ha e posi i e o nega i e economic e ec and ixed b oadband,
in e ne use s and echnology in as uc u e a e he majo de e minan s. Pa icula ly, Facebook
has nega i e e ec on economic g ow h due o p obably he clu e o con en and high
ansac ion cos o sea ch o in o ma ion, subs i u ion e ec be ween leisu e and labo , and he
non-mone a y ype o social media ha accoun s pa ially o GDP. The limi a ion o he pape
is ha i ocuses on GDP ins ead o GNI, which as discussed ea lie does no ully cap u e he
economic income o a coun y. Mo eo e , he eg esso s a e limi ed o ixed b oadband, in e ne
use s, in es men s, educa ion a he e ia y le el only, labo a e, and ade. O he po en ial
de e minan s such as ne wo k eadiness, mobile subsc ip ion, inno a ion, all le els o
educa ion, ou ism, li e expec ancy, peace index, and u banism a e omi ed. In addi ion, he
s udy did no clus e he coun ies in o classes o a ious economic le els o examine he e ec
based on he idiosync asy and economic speci ici ies o he coun ies.
O he s udies in es iga ed he ole o In e ne and b oadband on global economic s a us
(e.g., Aud e sch 2007; Choi 2003; DeP ince e al. 1999; Rome 1990). Following such
li e a u e, we hypo hesize and conjec u e ha , while In e ne could play a ole in boos ing
economic p oduc i i y and coun ies de elopmen , social media (and speci ically Facebook as
he la ges global ne wo k) should c ea e ies ha could in u n be economically bene icial o
coun ies. Ou pape di e s om Dell’Anno e al. (2016) on many aspec s. Fi s , we conside
a much la ge sample including 160 coun ies. Second, we only ocus on Facebook use s ins ead
o combining di e en social media si es in o de o isola e he speci ic e ec o ha digi al
ecosys em pla o m. Thi d, we use a panel spanning o e 3 yea s ins ead o jus conside ing a
g ow h a e be ween wo dis an yea s. The panel s udy o e s mo e insigh in o he
ans o ma i e p ocess om ICT (in ou pape Facebook pla o m) o economic de elopmen .
Fou h, we do no include da a om inancial c isis (2008-2011) , and we a he used he phase
a e he c isis 2011 o 2013, o he ollowing easons: 1/ i s , we we e unable o p ocu e
esea ch da a p io o 2010, 2/ second, he inclusion o he peak o he inancial c isis (G ea
Recession) could ha e dis u bed he esul s and conclusions o ou analysis as economic g ow h
we e la gely in luenced by majo ex ao dina y economic policies decisions, 3/ hi d, he
numbe o Facebook use s did no ma e ialized un il 2011. Fo ins ance, he global numbe o
FB use s as o 2008 Q3 was only 100 million use s compa ed o 680 million use s as o 2011
Q1 (S a is a, 2020), and 4/ las ly, we examine he a ia ion o social media e ec by classes o
coun ies, which was no pa o Dell’Anno e al. (2016) s udy.
We include many a iables as po en ial co a ia es in e ms o poli ical, echnological,
economic, and demog aphic ac o s. Dell’Anno e al. (2016) used pa en applica ions,
echnological index, p opensi y o capi al accumula ion, labo o ce a e, school en ollmen ,
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ade openness, and echnological in as uc u e (such as b oadband subsc ibe s, se e s’ usage
and In e ne use s). We use simila ac o s bu di e en p oxies (see Table 2 in he nex sec ion
Desc ip ion o da a). These ac o s a e widely ecognized as e lec ing socioeconomic s anding
(e.g., Cas elló-Climen and Doménech 2008; Coulombe and McKay 1996; Cze nich e al. 2011;
Jo dan 2004; He e al. 2010; Hoynes e al. 2006; Woola d and Klasen 2007). Fo example, on
he echnological e ec , Cze nich e al. 2011 showed ha 10% inc ease o b oadband
pene a ion con ibu es o he inc ease o pe capi a g ow h by 0.9 o 1.5% o a sample o
OECD coun ies be ween 1996–2007. On he poli ical e ec , Cos alli e al. (2017) showed he
economic cos o e hnic ac ionaliza ion o 20 wa coun ies ha expe ienced an a e age
annual loss o GDP pe capi a exceeding 17%. Cebula and Eks om (2009) in es iga ed he
e ec o economic ac o s OECD coun ies be ween 2004 and 2007. Thei indings indica ed
ha economic g ow h inc eases o highe le els o ade, business and mone a y eedom, and
p o ec ion o p ope y igh s. They examined also he e ec o poli ical ac o s and ound ha
he economic g ow h is in luenced posi i ely by he poli ical s abili y o a coun y and i s
con ol o co up ion. On he demog aphic e ec , a numbe o s udies showed he posi i e e ec
o educa ion on he economic s anding o coun ies. To illus a e, Mankiw e al. (1992) and
Ba o (1991) examined he educa ional e ec o bo h he indus ialized and he less-de eloped
coun ies. They ound ha schooling has a signi ican posi i e in luence on GDP g ow h.
We conside GNI pe capi a PPP ( alue o domes ic and o eign p oduc ion aking in o
accoun he pu chasing powe pa i y) as a measu e o socioeconomic de elopmen ins ead o
GDP pe capi a ( alue o domes ic p oduc ion and ou pu ). Indeed, he GNI is app op ia e in
ou s udy because i includes he addi ional economic inpu o coun ies ac oss bo de s
acili a ed ia he In e ne usage and he globaliza ion o Facebook as he la ges social media
si e. The GNI a iable has been used in di e en economic s udies such as Dao (2008), Dao
(2014) and Asabe e e al. (2016). Ou pape di e s also om Vi enu-Sackey (2020) by
ocusing on a b oade esponse a iable GNI ins ead o GDP. We also include many omi ed
explana o y a iables such as ne wo k eadiness, mobile subsc ip ion, inno a ion, all le els o
educa ion, ou ism, li e expec ancy, peace index, u banism, e c. We examine he e ec o
Facebook on g oup o coun ies based on hei economic s anding (high, middle and low-
income le els).
Con a y o Dell’Anno e al. (2016) and Vi enu-Sackey (2020) s udies, ou indings show
ia di e en models ha Facebook (when i is isola ed om o he social media pla o ms) has
consis en ly a signi ican posi i e e ec on socioeconomic de elopmen o coun ies. In
addi ion, i could ha e di e en e ec shapes such as a posi i e and a dec easing in luence
e lec ing a mo e complex ela ionship be ween social media usage and he economic s anding
o coun ies. The ype o e ec depends on he cha ac e is ics o he coun y and i s Wo ld Bank
classi ica ion. We no e ha Dell’Anno e al. (2016) s udy was no ocusing only on he e ec
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4 Models and Econome ic Analyses
In designing he esea ch ( o all models below), we chose o app oxima e he coun ies’
economic de elopmen wi h he GNI pe capi a PPP ins ead o he GDP. The GNI pe capi a
PPP exp esses he socioeconomic s anding o coun ies uni o mly and be e cap u es he
economic ou pu o na ions by also aking in o accoun he con ibu ion o na ionals li ing
ab oad. Knowing ha we a e in es iga ing he socioeconomic e ec o Facebook as a social
ne wo king si e o each coun y, he In e ne e ec anscends he bo de s and could b ing
economic inpu o economic ha m due o in e na ional exchange, accessibili y (enhanced ia
mobile de ices i he in as uc u e o b oadband is a chaic o limi ed) and in e ac i i y. We
also obse ed a e y s ong co ela ion be ween log GDP and log GNI (co ela ion coe icien
= 0.99), which indica es ha his s udy’s inding a e s ill alid i we used log GDP as dependen
a iable.
A majo and common heo e ical issue in economics is e e se causali y. Wi hin he con ex
o ou s udy, he ques ion is whe he social media leads o a be e economy o i a be e
economy leads o mo e social media usage. The Wo ld Bank classi ies coun ies acco ding o
hei GNI, which yields o coun ies g ouped in he same clus e o simila economic
cha ac e is ics. This mi iga es he conce n wi h e e se causali y as he economic models a e
es ima ed o coun ies wi h compa able economic s anding. We also obse e ha be e
economies (as ca ego ized by he Wo ld Bank classi ica ion) do no necessa ily ansla e in o
highe social media pene a ion (see Fig. 1). We also p e e calib a ing he economic models
by Wo ld Bank classi ica ion as no only i con ols o he cu en economic s anding o
coun ies bu also be e es ima es he dis inc i e d i e s wi hin each class.
To con i m he esea ch conclusions, we in es iga e nume ous econome ic echniques,
including he pooled OLS model wi h ime e ec , he ixed e ec model wi h / wi hou ime
e ec , and he andom e ec model wi h ime e ec . Besides, we in es iga ed he OLS model
by con olling o he GNI a a cons an da e.
4.1 The Pooled OLS Model wi h Time E ec
This model is used as a e e ence o o he models. We include in equa ion (1) a ious p oxy
o mac o a iables ( echnological, poli ical, demog aphic, and economic a iables) as well as
he Facebook posi i e and quad a ic e ec .
𝐿𝑜𝑔 𝐺𝑁𝐼𝑖𝑡 = 𝛼 + 𝜆𝐹𝐵𝑖𝑡 + 𝛾𝐹𝐵𝑠𝑞𝑖𝑡 + 𝛽𝑋𝑖𝑡 + 𝛿1𝑌𝑒𝑎𝑟12 + 𝛿2𝑌𝑒𝑎𝑟13 + 𝑒𝑖𝑡 (1)
whe e 𝐿𝑜𝑔 𝐺𝑁𝐼𝑖𝑡 ep esen s he dependen a iable GNI o each coun y i and ime (panel o
3 yea s om 2011 o 2013). The es ima o 𝛼 is he o e all in e cep e m o he whole model.
The ec o
i
X
includes he me ic independen a iables lis ed in Table 2 (excep he

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Facebook pene a ion as linea and quad a ic e m). The

= (β1,…, βk)′ is a ec o o
es ima o s co esponding o he e ec o each independen a iable (1 o k). The independen
a iables con ol o obse ed he e ogenei y be ween coun ies.

is he linea e ec o
Facebook pene a ion on Log GNI, and

deno es he dec easing o enhancing ma ginal e ec
(depending on he sign o he es ima o ) o Facebook pene a ion. The es ima o s 𝛿 co espond
o he ime e ec (as dummy a iables whe e 2011 is aken as a e e ence yea ) and e lec s he
dynamic e olu ion o a coun y’s socioeconomic de elopmen o e ime. We assume ha
i
e
is no mally dis ibu ed wi h mean ze o and a iance σ2 o all (i, ).
4.2 The Fixed E ec Model wi h Time E ec
Using he wi hin es ima o , his model con ols o unobse ed he e ogenei y ha pooled OLS
canno handle. Indeed, he e a e ixed cha ac e is ics be ween coun ies and sys ema ic coun y-
le el di e ences such as egula ions, geog aphic size, e c. ha a e p obably co ela ed wi h he
included independen a iables and ha pooled OLS does no ake in o accoun . We eplica e
he same independen a iables as he OLS model and ake in o accoun a ime e ec (as dummy
a iables) ha could e lec a a ia ion o e ime o he coun y socioeconomic de elopmen .
In he ixed e ec model, he in e cep is ime-in a ian and is speci ic o each obse a ion (in
ou pape each coun y). The model is w i en as ollows in equa ion (2):
𝐿𝑜𝑔 𝐺𝑁𝐼𝑖𝑡 = 𝛼𝑖+ 𝜆𝐹𝐵𝑖𝑡 + 𝛾𝐹𝐵𝑠𝑞𝑖𝑡 + 𝛽𝑋𝑖𝑡 + 𝛿1𝑌𝑒𝑎𝑟12 + 𝛿2𝑌𝑒𝑎𝑟13 + 𝑒𝑖𝑡 (2)
whe e 𝛼𝑖 ep esen s he ixed e ec ha summa izes he unobse ed, ime-in a ian , coun y
speci ic-e ec . Thei dis ibu ion is assumed o be no oo a om no mali y. This model
assumes ha unobse able ixed coun y cha ac e is ics a e in a ian o e ime and could be
co ela ed o he independen a iables.
4.3 The Random E ec Model wi h Time E ec
This model, also called a a iance componen s model o e o -componen model, akes in o
accoun a speci ic e o s uc u e and con ols o he unobse ed he e ogenei y o he da a.
While he ixed e ec model assumes ha he indi idual speci ic e ec is co ela ed wi h he
independen a iables, he andom e ec model assumes ha hese e ec s a e unco ela ed o
he independen a iables (see Woold idge 2005) and ha he a ia ion ac oss coun ies is
andom. Howe e , he impo an di e ence be ween bo h models is he co ela ion o no wi h
he independen a iables a he han he s ochas ic e ec s (G eene 2008). The model is w i en
as ollows in equa ion (3):
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𝐿𝑜𝑔 𝐺𝑁𝐼𝑖𝑡 = 𝛼𝑖+ 𝜆𝐹𝐵𝑖𝑡 + 𝛾𝐹𝐵𝑠𝑞𝑖𝑡 + 𝛽𝑋𝑖𝑡 + 𝛿1𝑌𝑒𝑎𝑟12 + 𝛿2𝑌𝑒𝑎𝑟13 + 𝑢𝑖𝑡 (3)
The es ima o s 𝛼𝑖 ep esen he andom indi idual unobse ed he e ogenei y, and 𝑢𝑖𝑡 is an
independen e m called “idiosync a ic e o ” o “idiosync a ic dis u bance” changing ac oss i
and (see Woold idge 2010). This e m is a combined e o composed o he wi hin en i y e o
and he be ween en i y e o (see To es-Reyna 2007).
5 Resul s and Discussion
We s udy wo phases in o de o in es iga e he ole played by Facebook pene a ion on he
socioeconomic de elopmen o coun ies. The i s phase includes he whole sample wi h all
classes. Hence, we pe o m di e en eg ession analyses o he whole sample. The second
phase uses he bes ype o eg ession model o phase 1, and apply i o each class sepa a ely
in o de o examine he idiosync a ic cha ac e is ics o each class in e ms o Facebook e ec
on hei socioeconomic s anding. We elimina e wo a iables om he independen a iables
lis namely he inno a ion index and he In e ne use due o hei high mul icollinea i y (VIF
exceeding 5 when hey a e p esen in he OLS model). The emaining a iables VIF a e lis ed
in Table 11 in he appendix. We use he so wa e R o gene a ing Tables 5 o 8.
5.1 Resul s o Phase 1
We epo below he esul s o phase 1 using di e en s a is ical models. Fi s , we compa e he
OLS model o he ixed e ec model and he andom e ec model. I is clea om Table 5 ha
he e a e some o e lap o signi ican a iables be ween he h ee models. The echnological
ac o is p edominan ly signi ican such as mobile pene a ion and Facebook pene a ion. We
no ice ha Facebook does no only ha e a posi i e e ec bu has also a signi ican dec easing
e ec . The esul highligh s he dec easing ma ginal e ec o Facebook. Based on Table 6, he
ixed e ec model is he p e e ed echnique o e he andom (based on he Hausman es ) and
he OLS models (based on he F es o indi idual e ec ).
Simila o Dell’Anno e al. (2016), we con ol o he GNI a a cons an da e in o de o ha e
con e gence o he OLS (we chose 2001 as a con ol da e). The yea 2001 no iced a slowdown
as pa o he ea ly 2000 majo con ac ion in global economic g ow h (see Tapia 2013). The
choice o he yea is hen app op ia e o use as a con ol yea in o de o de angle he economic
s anding in la e yea s. The esul s o he new model con olling o GNI2001 and he i s OLS
model ha e many simila i ies in e ms o alues’ es ima es and signi icance o a iables (excep
o li e expec ancy). Facebook pene a ion is again con i med as an impo an signi ican
a iable and he dec easing e ec is highligh ed in his model.
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Table 5. Compa ing di e en models o he whole sample (all classes included)
OLS model
Fixed e ec model
Random e ec model
OLS model wi h con ol GNI2001
Va iable
Es ima e
S anda d
E o
Es ima e
S anda d
E o
Es ima e
S anda d
E o
Es ima e
S anda d
E o
In e cep
FB
FBsq
U ban
Mobile
T ade
Unemp
Tou ism
Li eExp
Educ
Ne Read
Peace
Yea 12
Yea 13
GNI2001
4.65485
0.02359
-0.00034
0.00967
0.00581
0.00019
0.00038
0.00052
0.00690
1.83780
0.37178
0.01237
-0.03669
-0.05084
0.35783***
0.00501***
0.00008***
0.00130***
0.00077***
0.00074
0.00362
0.00029*
0.00511
0.23951***
0.05441***
0.06745
0.04887
0.05006
0.00465
-0.00006
0.00662
0.00052
-0.00030
-0.00822
-0.000006
0.00345
0.03697
-0.00197
-0.06197
0.02902
0.05582
0.00159***
0.00002***
0.00678
0.00024**
0.00061
0.00202***
0.00020
0.00702
0.26528
0.01561
0.02568**
0.00560***
0.00839***
0.00568
-0.00007
0.02021
0.00054
-0.00009
-0.00846
0.00033
0.03035
1.2892
0.04146
-0.07543
0.00949
0.02082
0.00176***
0.00002***
0.00213***
0.00026**
0.00062
0.00214***
0.00021
0.00545***
0.02417***
0.01694**
0.02821***
0.00547*
0.00720***
5.104
0.02359
-0.00034
0.00541
0.00572
-0.00016
0.00039
0.00007
0.00874
2.0491
0.15665
0.06366
-0.01517
-0.02208
0.00002
0.31803***
0.00442***
0.00007***
0.00120***
0.00068***
0.00066
0.00321
0.00026
0.00451*
0.02121***
0.05148***
0.05967
0.04315
0.04423
0.000002***
𝑅2
0.862
0.529
0.656
0.891
***Signi ican a 0.01; **Signi ican a 0.05; * Signi ican a 0.1
Table 6. Compa ison es s be ween models
Tes s
P-Value
Al e na i e Hypo hesis
Decision
Lag ange Mul iplie Tes
OLS (null) e sus Random
< 2.2e-16
Signi ican e ec s
P e e ence o he andom e ec model
F Tes o indi idual e ec
OLS (null) e sus Fixed
< 2.2e-16
Signi ican e ec s
Mo e suppo o he ixed e ec model
Hausman Tes
Random (null) e sus Fixed
0.0001314
One model is inconsis en
Mo e suppo o he ixed e ec model
o consis en es ima es
5.2 Resul s o Phase 2
As he ixed e ec model was he p e e ed one in he o e all sample, we choose o apply ha
ype o model o each class. We compa e all classes wi h he o al sample in he de ailed Table
7 and he summa y Table 8. We pe o m he eg ession on all a iables including he ime
e ec . Nex , we elimina e he ime e ec as we no ice ha i dilu es he signi icance o many
o he independen a iables. We add one inal model o Class 1 whe e we elimina e he
quad a ic e ec o Facebook (FBsq). Finally, we elimina e T ade because i is cons an ly non-
signi ican in all models. This inding is consis en wi h he Wo ld Bank G oup (2015) analysis.
The low elas ici y o T ade o he economic s anding has been analyzed be ween 1970 and 2013
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by Wo ld Bank G oup (2015) and many easons we e pu o h in o de o explain such
dec easing e ec in ecen yea s compa ed o p e ious decades. The i s eason is he
e olu ion o communica ion echnology and jus -in- ime p oduc ion p ocesses, which a ec ed
he s uc u e o he global alue chain. The second eason e lec ed in he changes o agg ega e
demand is mainly due o he global in es men le el. The hi d eason is he dec ease o ade
inance due o he inancial egula ions such as he Base III egula ions. Finally, he highe ade
p o ec ion could ha e some damping e ec on he ela ionship be ween T ade and he economic
s anding, and mainly he slowe speed o libe aliza ion du ing he 2000s. Besides, a ious
academic s udies showed opposing esul s conce ning he T ade-economy ela ionship while
some s udies ound posi i e associa ion (e.g., Chang e al. 2009; Jouini 2015; Tekin 2012),
o he s ound a U shaped ela ionship (e.g., Zahonogo 2016), and ano he g oup ound nega i e
o e en no associa ion (e.g., Musila and Yiheyis 2015; Singh and Ta lok 2011; Ulaşan 2015).
Ou Model 1 (wi h ime e ec ) shows ha only he o al sample, Classes 2 and 4 incu a
signi ican posi i e e ec o Facebook as well as i is dec easing ma ginal e ec ( see Table 7).
Howe e , ocusing on Model 2 (wi hou ime e ec ), all classes as well as he o al sample incu
a signi ican e ec o Facebook as well as addi ional a iables appea o ha e a signi ican
in luence (posi i e and dec easing e ec o ei he one o he e ec ). I seems ha he ime
a iables supp ess some o he ac o s’ in luence on he economy. This is pa ly due o he s ong
co ela ion wi h ime a iables, o he sho ime panel (only 3 yea s).
Focusing on Model 2 o he o al sample (wi hou ime e ec ), he esul shows he posi i e
signi ican e ec o Facebook pene a ion, mobile, li e expec ancy, u banism, ne wo k
eadiness on economic de elopmen . The esul sheds ligh on he g owing impo ance o
echnological ac o s on he economic s anding o coun ies. A he opposi e, Unemploymen
and Peace ha e signi ican nega i e e ec on he socioeconomic de elopmen . The lowe he
unemploymen le el and he highe he poli ical s abili y o a coun y, he highe he wellbeing
and de elopmen o i s economy. Besides, we ob ain again he nega i e e ec o Facebook
squa e highligh ing a quad a ic ela ionship wi h he economic de elopmen and he dec easing
e ec .
Following he s eps o Models 2 o 4, we conclude ha he e ec o Facebook is consis en
on each class excep Class 1 whe e he posi i e e ec appea s only when we elimina e he ime
e ec , he ade a iable and he quad a ic e ec . The eason could be ha his class is
composed o highly de eloped coun ies and he e ec o Facebook eached a ma u i y. In o he
wo ds, Facebook in luence is dilu ed in ecen yea s compa ed o p obably ea lie di usion o
Facebook (2007 o 2010). Hence, i becomes mo e di icul o cap u e i s in luence on
de eloped coun ies. Focusing on Model 3 and (Model 4 o Class 1), we no ice ha he posi i e
Facebook e ec is s onge in Class 4 as exp(0.09707)=1.1019, ollowed by Class 2 as
exp(0.01009)=1.0101, hen Class 3 as exp(0.00992)=1.0099, and Class 1 as
exp(0.00286)=1.0028. This means ha an inc ease in Facebook use o 1% in each class
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espec i ely lead o a highe GNI in Class 4 by 10.19%, by 1.01% in Class 2, by 0.99% in Class
3, and by 0.28% in Class 1. I seems ha he e ec o Facebook in Classes 2 and 3 a e e y
simila in magni ude.
The di e ence be ween classes in e ms o combina ion o ac o s a ec ing hei economies
is no coun e in ui i e because each class has speci ic cha ac e is ics and he ac o s in luencing
hei economic de elopmen a y ac oss classes. Focusing on Model 3, while some a iables
ha e a majo in luence on he economy o one class o coun ies, o he s migh ha e mo e
in luence on o he classes. Fo example, while mobile pene a ion seems o ha e signi ican and
posi i e e ec on Class 1, i does no seem o ha e any e ec on o he classes. The explana ion
could be ha in ad anced economies, businesses s ongly le e age sma phone de ices as an
addi ional channel o dis ibu ion and paymen . Howe e , his migh no be he case in less
de eloped coun ies whe e he echnological in as uc u e and paymen me hods h ough
sma phone de ices a e no as sophis ica ed as de eloped coun ies. The Peace index seem o
be p e alen in Class 3 and Class 4 and no signi ican in Class 1 and Class 2. The esul is
in ui i e as mos ad anced coun ies al eady enjoy poli ical s abili y. Howe e , poli ical
des abiliza ion has a dis inc and mo e di e en ia ed e ec in less de eloped coun ies. The
ne wo k eadiness has a signi ican posi i e impac only in Class 1 and Class 3, which sugges s
ha ad ances in esea ch and de elopmen , and he sophis ica ed use o in o ma ion and
communica ion echnologies ma e o high income-le el coun ies, bu i is less in ui i e o
Class 3. A possible a ionale o a non-signi ican e ec in ce ain classes could be due o he
lack o echnological in as uc u e and ech skills in Class 4 and he signi icance o o he
a iables ha o e shadow he ne wo k eadiness o Class 2.
We es ed he e ec o he esponse lag by adding “LogLagGNI” in Model 3 and we ound
he he expec ed posi i e e ec o he p e ious yea GNI on he ollowing yea . This dynamic
e ec o GNI o e ime is expec ed as measu es o economic ou pu end o be posi i ely
au oco ela ed o e sho ho izons and nega i ely au oco ela ed o e longe ho izons (Cogley
and Nason 1995).
Conside ing he Model 3 wi h he lag e ec as he bes model, we es ed a numbe o
esiduals and po en ial model issues. Fi s , we do no deem ha he e is a need o es o c oss-
sec ional dependence gi en ha we ha e a panel o ew yea s and la ge numbe o cases. Bal agi
(2012) explained ha c oss-sec ional dependence is a p oblem o panel da a wi h long ime
se ies. Howe e , i is no a p oblem o small panel da a wi h ew yea s and la ge numbe o
cases. Se ial co ela ion es ing also applies o mac o panels no small ime-se ies da a simila
o ou da ase . A numbe o esidual es s ha e been pe o med, namely es o no mali y,
he e oscedas ici y, and se ial co ela ions. Acco ding o Fig. 2, he no mali y is no iola ed.

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Fig. 2. Tes o No mali y
We measu ed he Du bin Wa son (DW) using he package lm es . This DW does no ake in o
accoun he s uc u e o esiduals in o conside a ion. In his case, DW = 2.2887 wi h p- alue =
0.9995 (se ially unco ela ed unde he null o no se ial co ela ion in idiosync a ic e o s). We
also measu ed he gene alized Bha ga a e al. (1982) Panel Du bin-Wa son Tes using BNF
s a is ic and LBI. The alues a e espec i ely DW = 1.4288 and LBI = 2.2859. The alues o
DW seem o po en ially ha e se ial co ela ion based on he gene alized DW. Howe e , we
should no e ha he gene alized DW is mo e app op ia e o longe ime se ies da a (Bha ga a
e al. 1982) while ou da a includes only 3 yea s. We applied he gene alized DW o addi ional
sc u iny o any po en ial issue.
Mo eo e , we checked o he e oscedas ici y by measu ing he B eusch-Pagan es and we
ound BP = 3633.6 and p- alue < 0.001 which sugges s ha he e is a he e oscedas ici y issue.
To ix he e oscedas ici y issue, we un he ixed model wi h Robus Co a iance Ma ix
Es ima o s. In addi ion, o ix he he e oscedas ici y and he po en ial se ial co ela ion issues,
we applied he A ellano me hod. We ob ain he esul s in Tables 7 Model 3. The esul s emain
unchanged compa ed o he comple e sample wi h lag e ec be o e applying he A ellano
me hod.
O e all, he esul s indica e ha Facebook pene a ion plays a posi i e ole as an economic
enable and enhance o he socioeconomic de elopmen . They also poin o nume ous d i e s
o economic de elopmen including supe io echnological in as uc u e, ne wo k in e ac i i y
and inno a ion, educing ba ie s and censo ship o social media, assu ing poli ical s abili y,
in es ing in u banism, and inally, educa ing indi iduals, businesses and go e nmen o icials
o c ea e s onge and mo e e ec i e ies h ough social media.
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Tables 7. Summa y esul s o ixed e ec models by class and all sample
Model 1: Fixed e ec models wi h ime e ec
Samples
Class 1
Class 2
Class 3
Class 4
All sample
Va iables
Es ima e
P alue
Es ima e
P alue
Es ima e
P alue
Es ima e
P alue
Es ima e
P alue
FB
FBsq
U ban
Mobile
T ade
Unemp
Tou ism
Li eExp
Educ
Ne Read
Peace
Yea 12
Yea 13
-0.00071
0.00003
-0.01219
0.00071
-0.00034
-0.01
0.00003
0.01484
0.11938
0.05902
-0.01858
0.00617
0.01599
0.7131
0.154
0.3253
0.0304 *
0.5044
<.0001***
0.8301
0.3558
0.6985
0.0269 *
0.6306
0.4844
0.1974
0.00694
-0.0001
0.01396
0.00010
0.00048
0.00056
-0.00113
0.00692
-0.084
0.01286
0.01339
0.02271
0.05922
0.005 **
0.0064 **
0.1334
0.7445
0.6715
0.8847
0.1114
0.4811
0.8378
0.5886
0.7275
0.0114 *
<.0001***
-0.00212
-0.00005
-0.00559
-0.00096
0.00115
-0.00598
0.00044
-0.00881
-1.98829
-0.00173
-0.06816
0.06642
0.13924
0.5222
0.5165
0.5891
0.0811 ‘’
0.308
0.1772
0.3675
0.6049
0.1994
0.9429
0.0455 *
<.0001***
<.0001***
0.09324
-0.00473
-0.03507
0.00066
-0.00405
-0.22252
-0.00237
-0.01979
1.26840
-0.05225
-0.12946
0.01187
0.00106
0.0029 **
0.0116 *
0.3629
0.6379
0.3202
0.0105 *
0.567
0.5442
0.1411
0.4537
0.2467
0.7613
0.9867
0.00466
-0.00007
0.00662
0.00052
-0.0003
-0.00822
-0.000006
0.00345
0.03697
-0.00195
-0.06197
0.02902
0.05582
0.0037 **
0.0036 **
0.33
0.031 *
0.6184
<.0001***
0.9747
0.6228
0.8892
0.9006
0.0164 *
<.0001***
<.0001***
𝑹𝟐
0.66229
0.6735
0.85333
0.69796
0.529
Signi icance :: >0.0001 ‘***’; >0.01 ‘**’ ; >0.05 ‘*’ ; >0.1 ‘ ’
Model 2: Fixed e ec models wi hou ime e ec
Samples
Class 1
Class 2
Class 3
Class 4
All sample
Va iables
Es ima e
P alue
Es ima e
P alue
Es ima e
P alue
Es ima e
P alue
Es ima e
P alue
FB
FBsq
U ban
Mobile
T ade
Unemp
Tou ism
Li eExp
Educ
Ne Read
Peace
-0.000004
0.00004
-0.01249
0.00054
-0.00036
-0.00934
0.00005
0.02642
0.12312
0.06706
-0.02005
0.9983
0.0829 ‘’
0.3049
0.0753 ‘’
0.4815
<.0001***
0.7289
0.0597 ‘’
0.6899
0.0006***
0.5933
0.01005
-0.0001
0.03653
-0.00011
-0.00071
-0.00628
-0.00126
0.01992
-0.46571
0.03413
0.01673
0.0001***
0.008 **
<.0001***
0.7338
0.5251
0.1039 ‘’
0.1044 ‘’
0.0547 ‘’
0.2912
0.1789
0.6889
0.00973
-0.00017
0.00276
-0.00013
0.00052
-0.00798
0.00129
0.08846
-0.97084
0.06289
-0.09585
0.0419 *
0.1245
0.8613
0.873
0.735
0.2366
0.0858 ‘’
<.0001***
0.6781
0.0769 ‘’
0.0548 ‘’
0.09213
-0.00472
-0.03626
0.00074
-0.00277
-0.21962
-0.00241
-0.01811
1.43185
-0.06692
-0.16108
0.0016 **
0.0088 **
0.2086
0.5784
0.4109
0.0067 **
0.5356
0.3579
0.0692 ‘’
0.2957
0.0805 ‘’
0.00709
-0.00006
0.02792
0.00042
-0.00037
-0.01067
0.00007
0.02483
-0.11232
0.02534
-0.07202
<.0001***
0.0137 *
<.0001***
0.1006 ‘’
0.5508
<.0001***
0.741
0.0002***
0.6905
0.113
0.0083 **
𝑅2
0.65395
0.59706
0.64568
0.69419
0.4608
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Model 3: Fixed e ec models wi hou ime e ec and T ade a iable
Samples
Class 1
Class 2
Class 3
Class 4
All sample
All sample wi h Lag e ec
Va iables
Es ima e
P alue
Es ima e
P alue
Es ima e
P alue
Es ima e
P alue
Es ima e
P alue
Es ima e
P alue
FB
FBsq
U ban
Mobile
Unemp
Tou ism
Li eExp
Educ
Ne Read
Peace
LagLogGNI
-0.00017
0.00004
-0.01227
0.00054
-0.00931
0.00004
0.02832
0.04034
0.06522
-0.02145
0.927
0.0592 ‘’
0.3122
0.0753 ‘’
<.0001***
0.7576
0.0394 *
0.8872
0.0007 ***
0.5663
0.01009
-0.0001
0.03644
-0.00011
-0.00613
-0.00123
0.01947
-0.4781
0.03320
0.01705
0.0001***
0.0077 **
<.0001***
0.7486
0.1104
0.1116
0.0588 ‘’
0.2765
0.1886
0.6822
0.00992
-0.00018
0.00273
-0.00012
-0.00804
0.00133
0.08803
-0.96668
0.06228
-0.09519
0.0358 *
0.0965 ‘’
0.862
0.8843
0.2298
0.0708 ‘’
<.0001***
0.6774
0.0775 ‘’
0.0547 ‘’
0.09707
-0.00492
-0.03498
0.00053
-0.20648
-0.00256
-0.02017
1.31314
-0.05845
-0.14452
0.0007***
0.0058**
0.2218
0.6858
0.0085**
0.5087
0.3003
0.0872 ‘’
0.3515
0.1047 ‘’
0.00706
-0.00006
0.027951
0.00041
-0.01066
0.00007
0.02504
-0.14677
0.02517
-0.07162
<.0001***
0.015*
<.0001***
0.1051 ‘’
<.0001***
0.7503
0.0002***
0.5947
0.1151
0.0085**
0.00686
-0.00006
0.02693
0.00041
-0.01033
0.00012
0.02539
-0.1408
0.02368
-0.07212
0.05684
<.0001***
0.01203*
<.0001***
0.10729
<.0001***
0.56890
0.00015***
0.60810
0.13659
0.00779**
0.04533*
𝑅2
0.65205
0.59508
0.64508
0.68776
0.46018
0.46715
Model 3: Fixed e ec models wi h A ellano me hod
Model 3: Fixed e ec models wi h Robus Co a iance Ma ix Es ima o s
All sample wi h Lag e ec
All sample wi h Lag e ec
Va iable
Es ima e
P alue
Va iable
Es ima e
P alue
FB
FBsq
U ban
Mobile
Unemp
Tou ism
Li eExp
Educ
Ne Read
Peace
LagLogGNI
0.00686
-0.00006
0.02693
0.00041
-0.01033
0.00012
0.02539
-0.14078
0.02368
-0.07212
0.05684
0.000932***
0.012221 *
<.0001***
0.109107
<.0001***
0.550242
0.019829 *
0.519745
0.175505
0.017551 *
0.074404 ‘’
FB
FBsq
U ban
Mobile
Unemp
Tou ism
Li eExp
Educ
Ne Read
Peace
LagLogGNI
0.00686
-0.00006
0.02693
0.00041
-0.01033
0.00012
0.02539
-0.14078
0.02368
-0.07212
0.05684
0.000932***
0.012221 *
<.0001***
0.109107
<.0001***
0.550242
0.019829 *
0.519745
0.175505
0.017551 *
0.074404 ‘’
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Model 4: Fixed e ec models wi hou ime e ec , T ade a iable and FBsq
Class 1
Va iable
Es ima e
P alue
FB
U ban
Mobile
Unemp
Tou ism
Li eExp
Educ
Ne Read
Peace
0.00286
-0.01284
0.00048
-0.00911
0.00006
0.02599
0.04714
0.06691
-0.02165
0.0037 **
0.2968
0.1175
<.0001***
0.6621
0.0607 ‘’
0.8702
0.0006 ***
0.568
𝑅2
0.63825
Table 8. Summa y esul s o ixed e ec models ac oss di e en samples
Va iables
FB
FBsq
U ban
Mobile
T ade
Unemp
Tou ism
Li eExp
Educ
Ne Read
Peace
Yea 12
Yea 13
Model 1: Fixed e ec model wi h ime e ec
Class1
+
-
-
+
Class2
+
-
+
+
Class3
-
-
+
+
Class4
+
-
-
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