U azán-Bonells, Ca los Felipe; Rondón-Quin ana, Hugo Alexande ; Za a-Mejía,
Ca los Al onso
A icle
Co ela ion be ween sec o al GDP and he alues o oad
eigh anspo a ion in Colombia
Economies
P o ided in Coope a ion wi h:
MDPI – Mul idisciplina y Digi al Publishing Ins i u e, Basel
Sugges ed Ci a ion: U azán-Bonells, Ca los Felipe; Rondón-Quin ana, Hugo Alexande ; Za a-
Mejía, Ca los Al onso (2024) : Co ela ion be ween sec o al GDP and he alues o oad eigh
anspo a ion in Colombia, Economies, ISSN 2227-7099, MDPI, Basel, Vol. 12, Iss. 8, pp. 1-28,
h ps://doi.o g/10.3390/economies12080205
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Ci a ion: U azán-Bonells, Ca los
Felipe, Hugo Alexande
Rondón-Quin ana, and Ca los
Al onso Za a-Mejía. 2024.
Co ela ion be ween Sec o al GDP
and he Values o Road F eigh
T anspo a ion in Colombia.
Economies 12: 205. h ps://doi.o g/
10.3390/economies12080205
Academic Edi o s: F ancesco Sica,
Elena Di Pi o, Ma ia Rosa ia Sessa,
F ancesco Tajani, Ma ia Rosa ia
Gua ini, Alessio Russo and
Debo a Anelli
Recei ed: 27 June 2024
Re ised: 8 Augus 2024
Accep ed: 12 Augus 2024
Published: 16 Augus 2024
Copy igh : © 2024 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
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dis ibu ed unde he e ms and
condi ions o he C ea i e Commons
A ibu ion (CC BY) license (h ps://
c ea i ecommons.o g/licenses/by/
4.0/).
economies
A icle
Co ela ion be ween Sec o al GDP and he Values o Road
F eigh T anspo a ion in Colombia
Ca los Felipe U azán-Bonells 1,* , Hugo Alexande Rondón-Quin ana 2and Ca los Al onso Za a-Mejía3
1P og ama de Ingenie ía Ci il, Facul ad de Ingenie ía, Uni e sidad Mili a Nue a G anada,
Cajicá250247, Colombia
2Facul ad del Medio Ambien e y Recu sos Na u ales, Uni e sidad Dis i al F ancisco Joséde Caldas,
Bogo á110321, Colombia; [email p o ec ed]
3G upo de In es igación en Ingenie ía Ambien al-GIIAUD, Facul ad del Medio Ambien e y Recu sos
Na u ales, Uni e sidad Dis i al F ancisco Joséde Caldas, Bogo á110321, Colombia; [email p o ec ed]
*Co espondence: ca los.u azan@unimili a .edu.co
Abs ac : A co ela ion be ween economic de elopmen and oad eigh is demons a ed in he
li e a u e e iew p o ided in his pape . This ela ionship was s udied in ela ion o he global g oss
domes ic p oduc (GDP) o he coun ies unde e iew. The e o e, his pape p esen s he alida ion
o his co ela ion in he Colombian case, based no only on global GDP, bu also on he GDP o
each o he main economic sec o s o he coun y. The co ela ion was analyzed using se e al o he
ollowing s a is ical me hods: co ela ion using he non-pa ame ic me hod (Spea man), he causali y
ela ionship using he G ange es , he ela ionship be ween a iables using P incipal Componen
Analysis (PCA), and mul i a ia e co ela ion o es ablish he le el o signi icance o each economic
sec o by means o he p- alue. The s udy concludes ha he bes co ela ion is be ween he GDP o
some economic sec o s and he amoun o eigh anspo ed one yea la e .
Keywo ds: ca go anspo ; co ela ion GDP; Colombia oad ca go index
1. In oduc ion
The impo ance o he pa icipa ion o ca go anspo a ion in any coun y is un-
doub ed, wi h a la ge numbe o documen s ha suppo i h ough he analysis o a ious
indica o s, and i is a undamen al p inciple in anspo a ion economics heo ies. The e-
o e, i is i ally impo an o each coun y o egion o no only ha e s a is ical da a on he
pe o mance o ca go and passenge anspo a ion, bu hey mus also be analyzed wi h
espec o mac oeconomic a iables ha allow o he p ojec ion o hei beha io , and hus
ha e eliable bases o decision making, bo h by go e nmen en i ies and by companies in
he indus ial and anspo a ion sec o s.
This s udy is based on Colombia as a case s udy, because, e en i he e a e o icial
da abases ha eco d mac oeconomic in o ma ion abou he coun y and he oad eigh
anspo sec o , he e is no s udy ha co ela es hem. Addi ionally, i is impo an o
disagg ega e he na ional economy in o i s main sec o s in o de o each be e de ined
conclusions han simply analyzing he beha io o global GDP.
Unde s anding he beha io o economic cycles in pe iods o c isis and i s ela ionship
wi h he amoun o eigh anspo ed in a coun y suppo s planning o he cons uc ion
o imp o emen o oad in as uc u e, which, in he case o a de eloping coun y like
Colombia, becomes a undamen al ool o social and economic g ow h.
In con ex , in he las decade, 3,204,000,000 ons o ca go we e mo ed in Colombia
h oughou all anspo a ion modes, wi h he highes pa icipa ion coming om oad
anspo a ion, wi h 2,574,097,000 ons (80%) (Minis y o T anspo a ion, Republic o
Colombia 2022). Ne e heless, in ecen yea s (2019 o 2023), ca go anspo a ion in Colom-
bia, whe he d y p oduc s (kg) o liquid (gal), has no displayed a signi ican co ela ion
Economies 2024,12, 205. h ps://doi.o g/10.3390/economies12080205 h ps://www.mdpi.com/jou nal/economies
Economies 2024,12, 205 2 o 28
wi h he economic condi ion, measu ed om he na ional g oss domes ic p oduc (GDP).
The abo e is a esul o analyzing he da a p esen ed by he Na ional Adminis a i e
Depa men o S a is ics (DANE) (Na ional Depa men o S a is ics DANE, Republic o
Colombia 2023) and he Minis y o T anspo a ion (Minis y o T anspo a ion, Republic
o Colombia 2023).
Wo ldwide GDP has been ega ded as one o he key indica o s o explain eigh
anspo demand. GDP ules he demand o eigh anspo h ough he size o consume
demand and on he sec o al s uc u e o he economy. In e iewing he s a e o he a in he
ela ionship be ween ca go anspo a ion and economic de elopmen , i is ound ha he
o me d i es he ma ke s o key sec o s o he economy. The e o e, he his o ical beha io
o load indica o s should be co ela ed wi h he economic pe o mance o a coun y o
egion, measu ed om he GDP (Mapa u and Mazumde 2017;Mish a 2019), based on he
p emise ha he in es men in anspo a ion and logis ics has a ele an impac on be e
economic de elopmen indica o s.
This esea ch ocused on oad eigh anspo a ion because i is he mode wi h he
g ea es impac on eigh anspo a ion in Colombia, due o he o og aphic complexi y and
because he egion wi h he highes consump ion o goods and se ices is he capi al ci y
(Bogo á), which is loca ed in he cen al a ea o he map, a om he coas s. Addi ionally,
ail and i e de elopmen o mul imodal ca go anspo a ion does no co e a signi ican
a ea o he coun y. This means ha he oad mode o anspo a ion p esen s da a wi h
highe pa icipa ion han he o he modes o eigh anspo a ion. Usually, he ela ion
be ween economic de elopmen and eigh anspo is used o make o ecas s o u u e
agg ega e eigh lows and olumes. Gene ally, GDP is used as an indica o o economic
ac i i y in a egion o a coun y (Mee sman and Van de Voo de 2013).
Gi en he abo e, he p incipal con ibu ion o his esea ch is he use o he GDP
ime se ies o each o he main sec o s o he economy (es ablished by he go e nmen
en i y ha epo s o icial s a is ics in Colombia, he Na ional Adminis a i e Depa men
o S a is ics). Wi h his in o ma ion and he ime se ies o oad eigh anspo da a, his
pape p esen s a co ela ion analysis be ween he wo a iables, using se e al me hods o
p o en s a is ical alidi y. The causali y o one a iable wi h espec o he o he is also
iden i ied, and he pe iod in yea s in which one a ec s he o he wi h he bes co ela ion
is ob ained.
Finally, in he Discussion sec ion, aspec s esul ing om he main analysis a e e al-
ua ed, such as he signi icance o he pa icipa ion o he di e en economic sec o s in
co ela ion wi h eigh anspo , whe he he co ela ion wi h he global GDP o wi h he
sec o al GDP is be e , and whe he he co ela ion would ha e been e y di e en i he e
had been no COVID-19 pandemic pe iod.
In summa y, his documen p esen s he alida ion o he co ela ion and causali y
be ween he economic de elopmen o he di e en economic sec o s and he quan i y
o ca go anspo ed by oad. The alida ion was de eloped h ough co ela ion using
he non-pa ame ic me hod (Spea man), he causali y ela ionship using he G ange es ,
he ela ionship be ween a iables using P incipal Componen Analysis, as well as he
applica ion o linea co ela ions o de e mine he le el o signi icance o each o he
independen a iables by means o hei espec i e p- alues, and he signi icance o he
linea i y o he co ela ion by means o he esul ing adjus ed R2and p- alues.
Li e a u e Re iew
In Mexico’s case, Ge man-So o e al. (2023) concluded ha he u baniza ion p ocess
depended on he imp o emen s in anspo a ion, bu anspo a ion equi ed economic
de elopmen . In ano he documen , Lopez-Rod iguez and Pa do-Rincon (2019) s a ed ha
he economic g ow h o a s a e depends la gely on he exchange o p oduc s gene a ed
wi h coun ies in he es o he wo ld, hus highligh ing he ele ance o in e na ional
ade; om his pe spec i e, oad ca go anspo a ion plays a ele an ole in he logis ics
ha suppo he success o comme cial ansac ions ab oad. They conclude ha he land
Economies 2024,12, 205 3 o 28
ca go anspo a ion sec o is one o he mos dynamic segmen s in socie y and ha he
impo ance o anspo a ion o he economy a ises om he impac on he pe o mance o
o he sec o s. The majo i y o p oduce s use anspo a ion in some s age o i s p oduc ion
and dis ibu ion p ocesses, in such a way ha he e iciency and anspo a ion a es a ec
he in e na ional compe i i eness o na ional p oduc s and he well-being o he consume .
In his way, anspo a ion is di ec ly ela ed o he economy.
Alam (2014) s a es ha in es men in oad logis ics co ido s in Sou h Asian coun ies
ha e posi i ely impac ed he egion’s GDP g ow h. In he same heo e ical end, Chen
e al. (2015) de eloped a model based on he economy cycle heo y o p edic ing Shanghai
con aine shipping ma ke c ises. Choi e al. (2018) used six y independen a iables in he
de elopmen o an ea ly-wa ning index, some o which include shipping, shipbuilding,
and inance. McKinnon (2007) exposed he beha io be ween GDP and he oad on km,
which ep esen s wo- hi ds o he UK’s domes ic eigh ma ke , and he eby exe s a
s ong in luence on he ela ionship be ween economic g ow h and he o al eigh on
km. Gao e al. (2016) exposed ha , “As he undamen al and leading indus y o na ional
economic and social de elopmen , he de elopmen o anspo a ion indus y de e mines
he end o economic de elopmen and e lec s he cyclical changes o na ional economy.
F eigh , as he basis o anspo a ion indus y, is closely ela ed o GDP de elopmen ”.
Xue e al. (2023) analyzed (in China’s case) he co ela ion be ween he o e all GDP
and ailway anspo a ion g ow h ends, and concluded ha “ he g ow h a e o ailway
ope a ing mileage in he pe iod o apid economic de elopmen was equal o he economic
g ow h a e, which indica es ha ailway anspo a ion is closely ela ed o economic
de elopmen ”. In o he a icle abou China, Yang (2021) a i med ha he ela ionship
be ween eigh anspo a ion and economic de elopmen is close, and ha de elopmen
p omo es he g ow h o eigh anspo a ion.
In Mexico, he Mexican T anspo Ins i u e concluded ha he co ela ion coe icien
be ween he g oss alue added (GVA) and o al on-kilome e s was 0.930, while he co -
ela ion be ween he GVA and on-kilome e s in mo o anspo a ion was 0.913, also
sugges ing a coupling be ween hei alues. The Mexican T anspo a ion Ins i u e (2009)
and La ee e al. (2011) examined he ela ionship be ween in es men in anspo a ion
in as uc u e capi al and he deb - o-g oss domes ic p oduc (GDP) a io.
Ano he documen analyzed he beha io o he GDP and he numbe o land eigh
ehicles in Slo akia in he pe iod om 1995 o 2015. The au ho s a gued ha he g ow h
o he GDP inc eased he bu den on he oad ne wo k. Mo eo e , we can assume ha
he inc ease in he GDP encou aged he g ow h in he demand o anspo (Va jan e al.
2017). Two o he p e ious au ho s explained in mo e de ail he ela ionship be ween
anspo in e en ion and he di ec and wide impac s in economic pe o mance in
Slo akia and EU coun ies in he pe iod om 2009 o 2015. The co ela ion be ween he
eigh anspo pe o mance and GDP was signi ican because i had an R alue equal o
0.73 (Gnap e al. 2018).
In he case o he U.S.A., oad anspo egis e ed as he highes sha e o GDP com-
pa ed o o he modes o eigh anspo , including ail (U.S.A. Depa men o T anspo a-
ion 2024). Mee sman and Van de Voo de (2013) de eloped a s udy in which he s ong
co ela ion be ween he GDP and oad anspo ( on kms) (be ween 1995 and 2010) in
EU27, he Russian Fede a ion, and he U.S.A. was clea , wi h China being less s ong in
hese las wo e i o ies. Simila ly, Zhang and Cheng (2023) s udied he p opo ion in
which land anspo in as uc u e pa icipa ed in he UK GDP in a way supe io o ha
o ai anspo and ma i ime and i e anspo .
Based on he p e ious pa ag aphs, he high pa icipa ion o oad anspo in a coun-
y’s GDP is suppo ed, a i ming a co ela ion be ween he economy and oad eigh
anspo . Eu ope has de eloped a me hodology ha allows o he s udy o he in e ac ion
be ween he elas ici y o oad eigh anspo s a is ics and mac oeconomic a iables
such as he GDP, including de ailed in o ma ion in he da abase ha no only includes he
amoun o ca go anspo ed, bu also o he s, such as he ypes o ucks (Eu os a 2023).
Economies 2024,12, 205 4 o 28
O he a icles ha also s udy his opic in Eu opean coun ies highligh ha , “In mos
indus ialized coun ies he e has been a s ong posi i e ela ionship be ween economic
and anspo g ow h, and speci ically oad anspo ”; mo eo e , “I is widely accep ed
ha anspo accoun s o a signi ican sha e o he GDP in indus ialized coun ies. Fo
his eason, he co ela ion be ween onne-kilome es and GDP, known as “coupling”, has
adi ionally been applied o o ecas ends in eigh anspo demand” (Alises e al.
2014). The same c i e ion is exp essed by K eibo g and Fosge au (2007): “His o ically,
eigh anspo olumes ( onne-kilome es) and economic ac i i ies ha e ollowed simila
ends”, in he Danish case.
In a s udy de eloped o he Ne he lands, sec o al GDP a ia ions we e used as he
only independen a iable in a p edic ion model o oad eigh anspo a ion. In a
wide ange o de e minan s ha in luence eigh anspo demand, including economic
and logis ical s uc u es, he GDP change in di e en sec o s and he wo ld ade index
we e iden i ied as he mos in luen ial de e minan s on he eigh demand (Asga pou
e al. 2023). In he case o Indonesia, Reza (2013) exposed he end o GDP and ca go
anspo a ion olume (exp essed as logis ics igu es) om he 1990s o 2010, showing a
simila beha io o he wo a iables. Benna han e al. (1992) exposed ha , o de eloped
coun ies (high-income coun ies) and de eloping coun ies (low-income coun ies), he
o al on-kilome e s o eigh anspo by oad a e clea ly explained by he GDP. Road
eigh in de eloped and de eloping ma ke economies shows a e y simila esponse o
a ia ions in he GDP. G enzeback e al. (2013) demons a ed ha a model can be used o
pe o m mac o- o ecas ing, o example, by es ima ing he e ec o he changes in he GDP
on he eigh on-kilome e s by mode in he u u e.
In he case o G eece, Moscho ou (2017) s udied in o ma ion since 2003 o analyze he
impac ha he coun y’s economic ecession had in ecen decades on he GDP da a, and
one o he sec o s mos nega i ely a ec ed was oad eigh anspo a ion.
Leh onen (2006) also concluded ha , in some de eloped coun ies, such as he UK,
he phenomenon o a ‘ ela i e decoupling’ is happening, bu , in many o he coun ies, he
olume o oad eigh anspo is expec ed o con inue ollowing he g ow h o he GDP.
None heless, in he p esen s udy, we can say ha , in he Colombian case, he decoupling
si ua ion is no expec ed o a ise. Beyza la e al. (2014) s udied he causali y be ween he
eal GDP and inland eigh anspo a ion pe capi a in on km. They concluded ha he
ela ionship is bidi ec ional and no homogeneous. This means ha nei he o he wo
indica o s has mo e ele ance as a causal a iable be ween hem.
In o he s udy ega ding China, Wang e al. (2021) es ablished ha he demand o
eigh anspo a ion shows an in e ed U-shaped end wi h economic de elopmen ,
and ha he e a e egional cha ac e is ics ha de ine ha ela ionship. Diaz e al. (2016)
p oposed, o B azil, a model ha ela es he impac o a iables, such as in es men and he
ex ension o anspo a ion in as uc u e, popula ion g ow h, and a el demand, on he
GDP’s po en ial. In he case o India, Ghosh and Dinda (2022) showed a s ong linea end
co ela ion be ween he GDP pe capi a (GDPPC) and he anspo a ion in as uc u e
index (TRNINF) o he pe iods om 1989 o 2017.
The GDP is also signi ican ly co ela ed wi h he a e o mo o iza ion in ci ies, wi h he
numbe o Twen y Equi alen Uni s (TEUs) anspo ed, and wi h he alue o in es men s
in anspo a ion in as uc u e, among o he ela ionships wi h he anspo a ion sec o
(Rod igue 2024).
In he Colombian case, Caicedo (2013) and Gómez (2016) analyzed he ela ionship
be ween na ional economic de elopmen and he amoun o ca go anspo ed by oad.
Howe e , hey did no pe o m a s a is ical o compa a i e analysis o he indica o s.
Gonzalez e al. (2022) exposed he di e ence be ween he g ow h o na ional GDP in
Colombia (2005 o 2019) and he beha io o he o al ons o ca go anspo ed (2015 o
2020). The i s indica o showed an inc easing beha io wi h a low de ia ion, and he
second indica o showed a seasonal cyclical beha io . The documen concluded ha “ he
COVID-19 pandemic had a nega i e e ec on he g ow h o he eigh o wa ding sec o in
Economies 2024,12, 205 5 o 28
Colombia. Due o he di e en es ic ions de ined by he apid expansion o he pandemic,
eigh anspo a ion s opped g owing as i was doing in p e ious yea s”, and ha “ he
analysis can help planne s implemen policies o imp o e eigh anspo beha io and
eac o unusual u u e economic pe iods”.
By analyzing he igu es eco ded by he “Anua io de anspo e de ca ga y logís ica
2014” (F eigh anspo a ion and logis ics yea book 2014) by he In e -Ame ican De elop-
men Bank (IADB 2014) conce ning he GDP pe capi a and he domes ic ca go anspo ed
by oad o A gen ina, Belize, B azil, Chile, Colombia, Cos a Rica, El Sal ado , Gua emala,
Hondu as, Mexico, Nica agua, Panama, Pa aguay, and U uguay, an R
2
o only 0.25 is
ob ained. This means ha he amoun o ca go anspo ed in he main La in Ame ican
coun ies has no ela ionship wi h he gene al economic beha io o he espec i e coun y.
This is one o he ew documen s ha does no ag ee wi h he hypo hesis aised.
The Banco de Desa ollo de Ame ica La ina (CAF) (De elopmen Bank o La in Ame -
ica and he Ca ibbean 2014) published he “Logis ics P o ile o La in Ame ica. Wo kshop
on ca go anspo a ion and logis ics”, p esen ing he main ac ion s a egies in he egion,
bu he documen does no analyze he economic impac o he in e en ions.
The Economic Commission o La in Ame ica and he Ca ibbean (ECLAC) published
he ollowing: “ he es ima ion o he po en ial load demand acili a es he op imiza ion
o he supply h ough an e icien alloca ion o esou ces and hus sa is y he demand,
con e ging on he de elopmen o he coun ies a he pace es ablished by hei objec i es,
ha is, he endowmen in as uc u e allows he expec ed GDP g ow h”. This a i ies
he ela ionship be ween economic de elopmen (measu ed based on he beha io o
i e economic sec o s) and he condi ion o ca go anspo a ion o ou La in Ame ican
coun ies (ECLAC 2017).
In ano he documen , ECLAC (2018) s a es he ollowing: “ he eigh mobili y and
logis ics sec o s a e sec o s ha equi e g ea e a en ion and ision in he u u e, gi en ha
hey p o ide he se ices ha o m he “blood” ha eeds he coun ies using in as uc u e
as dis ibu ion a e ies. As has been shown, he u u e de elopmen o eme ging economies,
including he LAC egion i sel , will equi e eigh anspo a ion se ices o g ea e
olume, quali y and di e si ica ion” (ECLAC 2018).
O he au ho s ha e ound ha he e is a spa ial dis ibu ion ela ionship be ween
he economic pe o mance o a coun y and he amoun o ca go anspo ed. This is an
impo an analysis o u u e esea ch ha analyzes he economic beha io and he ca go
anspo ed be ween neighbo ing coun ies, as in he case o he “Andean a ea” in Sou h
Ame ica (Boldizsá e al. 2023).
In he li e a u e e iewed abo e, we ind ha he e is no documen ha analyzes
he ecen his o ical co ela ion be ween he beha io o he economy and he amoun o
ca go anspo ed by oad, o i ha co ela ion indica es which o he wo a iables can be
conside ed he dependen one. This alida es he con ibu ion o his a icle o he s a e
o knowledge, especially in de eloping egions such as La in Ame ica, and in pa icula
Colombia. Finally, he ques ion o be esol ed h ough his esea ch is as ollows: does he
pe o mance o he economic sec o s allow o he es ablishmen o a s a is ically s ong
co ela ion o de e mine he sho - e m beha io o ca go olumes anspo ed by oad?
2. Me hods
The economic heo y o anspo a ion, se o h in he li e a u e e iew, indica es
ha a g ea e amoun o eigh anspo ed in a coun y should be co ela ed wi h a
be e economic condi ion. To s udy he beha io o hese a iables, he ollowing om
Colombia’s o icial da a we e used: he global GDP and he GDP o 11 economic sec o s
[Cons uc ion, Comme ce (wholesale and e ail; epai o mo o ehicles and mo o cycles;
anspo a ion and s o age; accommoda ion and ood se ices), Real Es a e Ac i i ies,
P o essional Ac i i ies (p o essional, scien i ic, and echnical ac i i ies; adminis a i e
and suppo se ices ac i i ies), Ag obusiness (ag icul u e, li es ock, hun ing, o es y
and ishing), Finance ( inancial and insu ance ac i i ies), Mining (exploi a ion o mines
Economies 2024,12, 205 6 o 28
and qua ies), Manu ac u ing Indus ies, Home Public Se ices (supply o elec ici y, gas,
s eam, and ai condi ioning; wa e dis ibu ion; was ewa e e acua ion and ea men ,
was e managemen and en i onmen al sani a ion ac i i ies), Communica ions (in o ma ion
and communica ions) and Public Adminis a ion (public adminis a ion and de ense;
manda o y social secu i y plans; educa ion; human heal h ca e and social se ices ac i i ies)
be ween he yea s 2015 and 2022, using he alue o cu en p ices in billions o Colombian
pesos (COP) (qua e ly) da a om he Na ional Depa men o S a is ics DANE, Republic
o Colombia (2023) (Table A1).
The in o ma ion used co esponding o ca go anspo a ion includes indica o s o
ca go anspo ed by land (Logis ics Co ido s in Colombia be ween 2019 and 2023) in qua -
e ly alues om he Minis y o T anspo a ion, Republic o Colombia (2023) (Table A2).
The me hodology applied was o co ela e economic and oad eigh anspo a ion
a iables, i s in he same ime se ies, and hen in ime se ies in which one a iable
begins one o wo yea s be o e he o he . In each case, wo analyses we e pe o med: a.
wi h he ime se ies o he economic a iables s a ing be o e he ime se ies o he ca go
anspo a ion; b. wi h he eigh anspo ime se ies s a ing be o e he GDP ime se ies.
The di e ence in he beginning o he ime se ies in ended o de e mine whe he
he e was a g ea e co ela ion: i he economic a iables we e ini ially hose o eigh
anspo a ion, o he opposi e. In he i s si ua ion, i was deduced ha i was he beha io
o he economy ha in luenced he pe o mance o ca go anspo a ion in a pe iod o ime
equal o he o e lap o he ime se ies. In he second si ua ion, i would be he beha io o
he anspo ed ca go ha would indica e he u u e da a o he economy (GDP).
In he case o he same ime se ies, he da a (sec o al GDP and ca go anspo ed)
co espond o a pe iod o i e consecu i e yea s (2019 o 2023). Fo he ime se ies wi h a
di e ence in he beginning, i is as ollows:
a.
GDP da a s a one yea ea lie : GDP se ies (2019 o 2023) and eigh se ies (2020
o 2024).
b.
GDP da a s a wo yea s ea lie : GDP se ies (2017 o 2021) and eigh se ies (2019
o 2023).
c.
F eigh da a s a one yea ea lie : F eigh se ies (2019 o 2023) and GDP se ies (2020
o 2024).
d.
F eigh da a s a wo yea s ea lie : F eigh se ies (2019 o 2023) and GDP se ies (2021
o 2025).
The analyses a e p esen ed wi h a maximum o wo yea s o di e ence in he beginning
o he ime se ies because he esul s ob ained wi h h ee and ou yea s o di e ence p esen
lowe co ela ion alues han hose ob ained wi h a di e ence o wo yea s. This means ha
he da a ob ained wo yea s apa show ha , a e only one yea o di e ence be ween he
ime se ies, he co ela ion dec eases. The da a used in he esea ch a e only a ailable un il
he yea 2023, bu , in o de o ex end he ime se ies, he da a we e p ojec ed un il he yea
2025. Fo his, he ollowing ins uc ion was used in R S udio (2023.12.0) s a is ical so wa e:
p edic (objec = linea ized da a se ies, newda a = da a_g oup, in e al = “con i-
dence”, le el = 0.95)
2.1. Analysis o he No mali y o Va iables o Es ablish Whe he o Use a Pa ame ic o
Non-Pa ame ic Co ela ion Me hod
The s a is ical beha io o he sec o al and global GDP da a se ies was analyzed
using he p- alue o he Dickey–Fulle and Shapi o–Wilk es s o es ablish seasonali y and
no mali y, espec i ely. The da a se ies do no mo e a ound a cen al alue, bu inc ease
(see Sec ion 3.1). This indica es ha he e is no seasonali y in he se ies. I is also obse ed
ha he e is no inc easing endency owa ds he mean o he da a and a educ ion in he
alue a he wo ex emes; ha is, he e is no shape simila o a Gaussian bell, which
indica es ha he e is no no mal dis ibu ion in he se ies.
The Shapi o–Wilk es p- alue esul s we e <0.05 o all o he a iables. Tha means
ha he a iables do no ha e a no malized dis ibu ion, which alida es he use o he non-
Economies 2024,12, 205 7 o 28
pa ame ic Spea man co ela ion me hod (Ramachand an and Tsokos 2015). The s a emen s
in R S udio so wa e o he Dickey–Fulle and Shapi o–Wilk es s a e as ollows:
ad . es (da a_se ies, al e na i e = “s a iona y”), and
shapi o. es (da a_se ies)
2.2. Analysis o he Co ela ion be ween Va iables by Non-Pa ame ic Me hod (Spea man)
The ho alues esul ing om applying he Spea man me hod es ablished which o
he indica o s co ela ed signi ican ly wi h he o he s (economy s. eigh anspo a ion)
and wi h how many yea s o di e ence. Rho alues close o 1.0 indica e a s ong co ela ion
be ween a iables, while, i he alue is close o 0.0, i is conside ed ha he e is no
co ela ion (Figu es 4–8) (Hauke and Kossowski 2011;Khalid e al. 2019,2022;Rehman
e al. 2018).
The Spea man’s ho alue o he co ela ion be ween a iables was de e mined in R
S udio so wa e using he ollowing s a emen :
Cha .co ela ion (da a_g oup, me hod = “spea man”).
2.3. Analysis o he Co ela ion be ween Va iables by he P incipal Componen s Me hod (PCA)
As an addi ional s ep, he co ela ion be ween a iables was co obo a ed using he
P incipal Componen s Analysis (PCA) me hod using he ollowing R S udio s a emen s:
da a. ame_name<- p comp(da a_g oup, scale = TRUE)
iz_pca_ a (da a. ame_name, epel = TRUE)
As a esul o he PCA es , he ela ionship be ween he a iables can be iden i ied
g aphically. I he ec o s o he a iables a e simila in di ec ion and magni ude, wi h a
small angle be ween hem, he co ela ion is s ong and di ec . I he di ec ion be ween
ec o s ends o be 180
◦
apa , he co ela ion is s ong bu in e se. I he di ec ion be ween
ec o s is close o 90
◦
, i is conside ed ha he e is no a good co ela ion be ween he
a iables (Figu e 9). The compa ison o he ends o he se ies o independen a iables
was ca ied ou g aphically (Figu e 10).
2.4. Analysis o Causali y be ween Va iables Using he G ange Tes
As a complemen a y analysis o he de e mina ion o he signi icance in he co ela ion
pa ame e s be ween he a iables, a es was pe o med o de e mine i he e was a causal
ela ionship be ween hem. Fo his pu pose, he G ange es was used, which in R S udio
used he ollowing ins uc ion:
g ange es (independen a iable da a~dependen a iable da a,o de = 1,da a =
da a base)
The causali y be ween he a iables was checked i he p- alue (P (>F)) was less
han 0.05.
2.5. Analysis o he Valida ion o a Mul i a ia e Model
To es ablish which economic sec o s ha e he g ea es signi icance wi h he beha io
o oad eigh anspo , he p- alue esul ing om a co ela ion be ween a iables was
analyzed. The ollowing commands we e hus pe o med using R S udio:
Linea modelling name<- lm(dependen a iable~independen a iable 1 + inde-
penden a iable 2 + . . . independen a iable n, da a = da a_ ile)
> summa y(Linea modelling name)
The summa y esul s p o ide he adjus ed R
2
alue and he p- alues o he inde-
penden a iables o de ine whe he he e is a s a is ical alidi y in he ela ionship o
he a iables. I he adjus ed R
2
is g ea e han 0.7 and he p- alue is less han 0.05, he
o mula ion o an explana o y model be ween a iables is s a is ically alid (Sha ma and
Ka 2018).
Economies 2024,12, 205 8 o 28
3. Resul s
This sec ion p esen s he esul s o he da a analysis. Sec ion 3.1 desc ibes he be-
ha io o he ime se ies o each o he h ee a iables o oad eigh in he coun y.
Sec ions 3.2–3.4
p esen , o di e en ime lags, he Spea man ho alues when co ela ing
he global GDP and ha o all economic sec o s wi h espec o he h ee a iables o oad
eigh anspo ed. Sec ion 3.5 s udies he ela ionship analysis be ween a iables using
he P incipal Componen Analysis me hod. Sec ion 3.6 analyzes he causali y be ween he
economy and anspo using he G ange causali y es . Sec ion 3.7 uses he applica ion o
linea co ela ion o de e mine he le el o signi icance o each o he independen a iables
by means o hei espec i e p- alues, and he signi icance o he linea i y o he co ela ion
by means o he adjus ed R2and he esul ing p- alues.
3.1. Desc ip i e S a is ical Analysis o F eigh T anspo a ion Va iables
The ime se ies o he h ee eigh anspo a ion a iables a e non-seasonal. The
Dickey–Fulle es gi es a p- alue esul g ea e han 0.05 o he h ee a iables, as ollows:
0.30 o he o al ips, 0.23 o he o al in kilog ams, and 0.38 o he o al in gallons.
Fu he mo e, hese a e also no se ies wi h no mal dis ibu ions. Applying he Shapi o–
Wilk no mali y es , he p- alues we e g ea e han 0.05, as ollows: 0.18 o he o al numbe
o ips, 0.24 o he o al numbe in kilog ams, and 0.15 o he o al numbe o gallons. The
non-no mali y o he se ies alida es he use o he non-pa ame ic Spea man co ela ion
me hod and he esul ing ho alue o de ine i s alidi y be ween wo a iables. Bo h
non-seasonali y and non-no mali y in he da a se ies can be seen g aphically in Figu es 1–3.
Economies 2024, 12, x FOR PEER REVIEW 8 o 30
2.5. Analysis o he Valida ion o a Mul i a ia e Model
To es ablish which economic sec o s ha e he g ea es signi icance wi h he beha io
o oad eigh anspo , he p- alue esul ing om a co ela ion be ween a iables was
analyzed. The ollowing commands we e hus pe o med using R S udio:
Linea modelling name<- lm(dependen a iable~independen a iable 1 +
independen a iable 2 + … independen a iable n, da a = da a_ ile)
> summa y(Linea modelling name)
The summa y esul s p o ide he adjus ed R
2
alue and he p- alues o he independ-
en a iables o de ine whe he he e is a s a is ical alidi y in he ela ionship o he a i-
ables. I he adjus ed R
2
is g ea e han 0.7 and he p- alue is less han 0.05, he o mula ion
o an explana o y model be ween a iables is s a is ically alid (Sha ma and Ka 2018).
3. Resul s
This sec ion p esen s he esul s o he da a analysis. Sec ion 3.1 desc ibes he beha -
io o he ime se ies o each o he h ee a iables o oad eigh in he coun y. Sec ions
3.2–3.4 p esen , o diffe en ime lags, he Spea man ho alues when co ela ing he
global GDP and ha o all economic sec o s wi h espec o he h ee a iables o oad
eigh anspo ed. Sec ion 3.5 s udies he ela ionship analysis be ween a iables using
he P incipal Componen Analysis me hod. Sec ion 3.6 analyzes he causali y be ween he
economy and anspo using he G ange causali y es . Sec ion 3.7 uses he applica ion
o linea co ela ion o de e mine he le el o signi icance o each o he independen a -
iables by means o hei espec i e p- alues, and he signi icance o he linea i y o he
co ela ion by means o he adjus ed R
2
and he esul ing p- alues.
3.1. Desc ip i e S a is ical Analysis o F eigh T anspo a ion Va iables
The ime se ies o he h ee eigh anspo a ion a iables a e non-seasonal. The
Dickey–Fulle es gi es a p- alue esul g ea e han 0.05 o he h ee a iables, as ol-
lows: 0.30 o he o al ips, 0.23 o he o al in kilog ams, and 0.38 o he o al in gallons.
Fu he mo e, hese a e also no se ies wi h no mal dis ibu ions. Applying he Shapi o–
Wilk no mali y es , he p- alues we e g ea e han 0.05, as ollows: 0.18 o he o al num-
be o ips, 0.24 o he o al numbe in kilog ams, and 0.15 o he o al numbe o gallons.
The non-no mali y o he se ies alida es he use o he non-pa ame ic Spea man co e-
la ion me hod and he esul ing ho alue o de ine i s alidi y be ween wo a iables.
Bo h non-seasonali y and non-no mali y in he da a se ies can be seen g aphically in Fig-
u es 1–3.
Figu e 1. To al ips da a se ies.
Figu e 1. To al ips da a se ies.
Economies 2024, 12, x FOR PEER REVIEW 9 o 30
Figu e 2. To al kilog ams da a se ies.
Figu e 3. To al gallons da a se ies.
3.2. Co ela ion Analysis in he Same Yea
Co ela ions we e ca ied ou o he da a o he dependen and independen a ia-
bles in he same yea s. Tha is, he alues o he dependen a iable in 2019 we e co ela ed
wi h he alues o he independen a iable(s) o ha same yea . In he same way, he
da a we e co ela ed un il he yea 2025, ob aining he ollowing ho Spea man alues
(Figu e 4).
Figu e 4. Rho alues o he co ela ion be ween he global and sec o GDP s. h ee indica o s o
ca go anspo ed by oad. Qua e ly accoun s be ween he yea s 2019 and 2023 o he GDP and
ca go (same yea ).
Figu e 2. To al kilog ams da a se ies.
Economies 2024,12, 205 15 o 28
Table 3. The P (>| |) esul o he mul i a ia e co ela ion. To al kilog ams as he dependen a iable.
P (>| |)
(In e cep ) 0.03166
Ag obusiness 0.08454
Mining 0.00579
Manu ac u e 0.26004
Home_public_se ices_supply 0.01007
Comme ce 0.04755
In o_communica ions 0.23613
Financial_insu ance 0.1828
Real_s a e 0.50482
P o essional_ac i i ies 0.00501
Public_adminis a on_Educa ion_Social_heal h_se ices
0.03735
Table 4. The P (>| |) esul o he mul i a ia e co ela ion. To al gallons as dependen a iable.
P (>| |)
(In e cep ) 0.016158
Ag obusiness 0.039086
Mining 0.00091
Manu ac u e 0.044918
Home_public_se ices_supply 0.002344
Comme ce 0.013044
In o_communica ions 0.45973
Financial_insu ance 0.13569
Real_s a e 0.942539
P o essional_ac i i ies 0.000658
Public_adminis a on_Educa ion_Social_heal h_se ices
0.007769
Table 5. Adjus ed R
2
and P (>| |) esul s o he co ela ion be ween he global GDP and ca go
anspo a iables as dependen a iables.
Adjus ed R2P (>| |)
To al a els 0.5952 0.0000411
To al kilog ams 0.5471 0.0001167
To al gallons 0.6955 0.00000298
Thus, he quan i y anspo ed ( o al a el) is a dependen a iable o a yea (n), he
mul i a ia e eg ession da a o sec o al GDPs is ound in Table 2, and he adjus ed R
2
is
0.7682, wi h a p- alue o 0.0003515. The esul s alida e he mul i a ia e co ela ion be ween
he numbe o ca go ips and he economic sec o s in Colombia. The adjus ed R
2
is g ea e
han 0.7 and he p- alue o he co ela ion is less han 0.05. The mos signi ican economic
sec o s a e hose wi h a p- alue o less han 0.05, including Ag obusiness, Mining, Home
Public Se ices Supply, Comme ce, P o essional Ac i i ies, and Public Adminis a ion,
Educa ion, and Social Heal h Se ices (Table 2).
Fo he quan i y anspo ed ( o al kilog ams) as a dependen a iable o a yea (n),
he mul i a ia e eg ession da a o he sec o al GDPs is ound in Table 3, and he adjus ed
R
2
is 0.7611, wi h a p- alue o 0.00356. Like wi h o al a els, he esul s alida e he
mul i a ia e co ela ion be ween he numbe o ca go ips and he economic sec o s in
Colombia. The adjus ed R
2
is g ea e han 0.7 and he p- alue o he co ela ion is less
han 0.05. The mos signi ican economic sec o s a e hose wi h a p- alue o less han 0.05,
including Ag obusiness, Mining, Home Public Se ices Supply, Comme ce, P o essional
Ac i i ies, and Public Adminis a ion, Educa ion, and Social Heal h Se ices (Table 3).
Fo he quan i y anspo ed ( o al gallons) as a dependen a iable o a yea (n), he
mul i a ia e eg ession da a o he sec o al GDPs is ound in Table 4, and he adjus ed
R
2
is 0.8921, wi h a p- alue o 0.0001238. Like wi h p e ious cases, he esul s alida e
Economies 2024,12, 205 16 o 28
he mul i a ia e co ela ion be ween he numbe o ca go ips and he economic sec o s
in Colombia. The adjus ed R
2
is g ea e han 0.7 and he p- alue o he co ela ion is less
han 0.05. The mos signi ican economic sec o s a e hose wi h a p- alue o less han 0.05,
including Ag obusiness, Mining, Home Public Se ices Supply, Comme ce, P o essional
Ac i i ies, and Public Adminis a ion, Educa ion, and Social Heal h Se ices (Table 4).
Finally, we p esen he uni a ia e co ela ion da a be ween he global GDP as an
independen a iable and he quan i y o ca go anspo ed one yea la e . They we e
analyzed o each o he h ee ca go a iables (Table 5).
The esul s in Table 5 alida e he co ela ions be ween he global GDP and oad
eigh a iables. Howe e , he linea i y o he co ela ions is less eliable because he
adjus ed R
2
alues a e lowe han in he mul i a ia e co ela ions (<0.7). This demons a es
he impo ance o ca ying ou an analysis o he pe o mance o he anspo sec o , no
only in e ms o o e all GDP, bu also in e ms o a mul i a ia e ela ionship wi h di e en
economic sec o s.
This in o ma ion is essen ial in he in as uc u al planning p ocess by he s a e and
p i a e indus ies, and is a ool o he p ojec ions o he eigh anspo business sec o .
4. Discussion
The main objec i e o his s udy was o de e mine he pe o mance o he GDP o he
economic sec o s so o p edic he amoun o ca go anspo ed by oad in Colombia.
The end o he ho alue was compa ed o he cases s udied. The analysis o
a iables whose igu es co esponded o he da a se ies o he same yea s (bo h se ies
s a ed in he same yea ) (Figu e 4) p esen ed ho alues <0.7 o 73% o he economic
sec o s, and <0.68 o he global GDP. The e o e, he e is non-highly signi ican co ela ion
be ween he wo da a se s.
Fo he co ela ions ha es ima ed ha he amoun o ca go anspo ed ma ked he
beha io o he GDP (one and wo yea s s a ing be o e he ca go da a), he esul s ended
owa ds ho alues o medium and low signi icance ( ho < 0.5). The endency owa ds
hese low alues means ha he e is no signi ican co ela ion be ween he a iables. Fo
he co ela ions in which he beha io o he GDP was co ela ed wi h he beha io o
he amoun o ca go anspo ed many yea s la e (one and wo yea s s a ing be o e he
GDP da a), he ho alues imp o ed he co ela ions signi ican ly. In he analysis wi h a
one-yea di e ence (Figu e 6), he bes co ela ions a e p esen ed, since 82% o he economic
sec o s p esen ed ho alues >0.8, and he global GDP oo. Howe e , he cons uc ion
sec o egis e ed ho alues ending owa d ze o, which ules i ou o he ma hema ical
p edic ion model.
4.1. The Di e en Beha io o he Cons uc ion Sec o
Conce ning he las issue, he di e ence in he pe o mance o he cons uc ion sec o
is no only obse ed in Figu e 9. Figu e 10 shows ha he cycle o he cons uc ion sec o
is di e en om ha o he o he sec o s analyzed. The end in he cons uc ion sec o
( he ed poin s in Figu e 10) is clea ly di e en om ha o o he economic sec o s. The
cons uc ion sec o shows a ho izon al end, while ha o he o he sec o s shows an
inc easing end. They only ha e simila beha io in he pe iod be ween 2020 and 2021 ( he
COVID-19 pandemic), in which a dec easing peak is eco ded. Tha is why he cons uc ion
sec o does no show a co ela ion wi h he o he economic sec o s in he indica o o i s
pa icipa ion in he na ional GDP. The inc easing beha io o he sec o al GDP coincides
wi h he also inc easing beha io o he eigh anspo a iables obse ed in Figu es 1–3.
Economies 2024,12, 205 17 o 28
Economies 2024, 12, x FOR PEER REVIEW 17 o 30
4. Discussion
The main objec i e o his s udy was o de e mine he pe o mance o he GDP o
he economic sec o s so o p edic he amoun o ca go anspo ed by oad in Colombia.
The end o he ho alue was compa ed o he cases s udied. The analysis o a i-
ables whose igu es co esponded o he da a se ies o he same yea s (bo h se ies s a ed
in he same yea ) (Figu e 4) p esen ed ho alues <0.7 o 73% o he economic sec o s, and
<0.68 o he global GDP. The e o e, he e is non-highly signi ican co ela ion be ween
he wo da a se s.
Fo he co ela ions ha es ima ed ha he amoun o ca go anspo ed ma ked he
beha io o he GDP (one and wo yea s s a ing be o e he ca go da a), he esul s ended
owa ds ho alues o medium and low signi icance ( ho < 0.5). The endency owa ds
hese low alues means ha he e is no signi ican co ela ion be ween he a iables. Fo
he co ela ions in which he beha io o he GDP was co ela ed wi h he beha io o he
amoun o ca go anspo ed many yea s la e (one and wo yea s s a ing be o e he GDP
da a), he ho alues imp o ed he co ela ions signi ican ly. In he analysis wi h a one-
yea diffe ence (Figu e 6), he bes co ela ions a e p esen ed, since 82% o he economic
sec o s p esen ed ho alues >0.8, and he global GDP oo. Howe e , he cons uc ion sec-
o egis e ed ho alues ending owa d ze o, which ules i ou o he ma hema ical p e-
dic ion model.
4.1. The Diffe en Beha io o he Cons uc ion Sec o
Conce ning he las issue, he diffe ence in he pe o mance o he cons uc ion sec o
is no only obse ed in Figu e 9. Figu e 10 shows ha he cycle o he cons uc ion sec o
is diffe en om ha o he o he sec o s analyzed. The end in he cons uc ion sec o
( he ed poin s in Figu e 10) is clea ly diffe en om ha o o he economic sec o s. The
cons uc ion sec o shows a ho izon al end, while ha o he o he sec o s shows an in-
c easing end. They only ha e simila beha io in he pe iod be ween 2020 and 2021 ( he
COVID-19 pandemic), in which a dec easing peak is eco ded. Tha is why he cons uc-
ion sec o does no show a co ela ion wi h he o he economic sec o s in he indica o o
i s pa icipa ion in he na ional GDP. The inc easing beha io o he sec o al GDP coin-
cides wi h he also inc easing beha io o he eigh anspo a iables obse ed in Fig-
u es 1–3.
Figu e 10. Colombia economic sec o s GDP (billions COP). Qua e ly accoun s o he yea s 2019 o
2023.
Figu e 10. Colombia economic sec o s GDP (billions COP). Qua e ly accoun s o he yea s 2019
o 2023.
Figu e 11 shows he non-inc easing end o he Cons uc ion sec o . Figu e 10 clea ly
shows ha , on he con a y, he end o he o he economic sec o s is inc easing. This
gi es g ea e cla i y o he di e en beha io o he Cons uc ion sec o . Figu e 9also
demons a es ha he GDP beha io o he Cons uc ion sec o di e s g ea ly om ha
o he o he economic sec o s, ega dless o i s ela ionship wi h eigh anspo a ion
de elopmen .
Economies 2024, 12, x FOR PEER REVIEW 18 o 30
Figu e 11 shows he non-inc easing end o he Cons uc ion sec o . Figu e 10 clea ly
shows ha , on he con a y, he end o he o he economic sec o s is inc easing. This
gi es g ea e cla i y o he diffe en beha io o he Cons uc ion sec o . Figu e 9 also
demons a es ha he GDP beha io o he Cons uc ion sec o diffe s g ea ly om ha
o he o he economic sec o s, ega dless o i s ela ionship wi h eigh anspo a ion
de elopmen .
In all o he co ela ion analyses pe o med (Figu es 4–8), he ho alues a e in some
cases in e se, in o he s close o ze o, and when hey a e posi i e, hey a e no g ea e han
0.6. The e o e, he Cons uc ion sec o diffe s om he o he s when being conside ed as
an explana o y a iable o he beha io o oad eigh anspo in Colombia.
I is ue ha he Cons uc ion sec o p esen s be e co ela ion alues in Figu e 7,
bu hey a e in e se. E en so, co ela ion analyses we e pe o med o hose ime se ies
pe iods (acco ding o Figu e 7). The esul s o he adjus ed R
2
o he h ee load a iables
we e no g ea e han 0.26. These esul s do no alida e an independen co ela ion o
he GDP o he Cons uc ion sec o and oad eigh anspo in Colombia.
Figu e 11. Colombia Cons uc ion economic sec o GDP end (billions COP). Qua e ly accoun s
o he yea s 2017 o 2025.
As a simila si ua ion, a s udy de eloped in B azil analyzed he ela ionship be ween
in es men in in as uc u e and economic sec o s, i u ned ou ha he Cons uc ion sec-
o was he only one wi h a back linkage. The Ag icul u al, Communica ions, and Indus-
ial sec o s u ned ou o be he key sec o s. This is a si ua ion like he one esul ing om
his s udy (Cen u ião e al. 2024).
4.2. His o ical T end Change Due o he COVID-19 Pandemic
The COVID-19 pandemic esul ed in a decline in he dynamics o he economy, and
i could be p esumed ha his also affec ed he anspo sec o . Figu e 10 clea ly shows
he decline in economic de elopmen o each o he sec o s in 2020.
A i s glance, one migh hink ha he COVID-19 pandemic pe iod ma ked a diffe -
ence in he end in he beha io o anspo ed ca go. Howe e , we ha e ound ha he
da a analyzed, including he economic s a is ical da a du ing he pandemic, do no affec
he his o ical end p io o he pandemic. This can be said because he his o ical beha io
o anspo ed ca go, in he h ee indica o s analyzed, did no egis e a ypical beha io
be ween he yea s 2020 and 2021 because i s end was inc easing (Figu e 12).
Figu e 11. Colombia Cons uc ion economic sec o GDP end (billions COP). Qua e ly accoun s o
he yea s 2017 o 2025.
In all o he co ela ion analyses pe o med (Figu es 4–8), he ho alues a e in some
cases in e se, in o he s close o ze o, and when hey a e posi i e, hey a e no g ea e han
0.6. The e o e, he Cons uc ion sec o di e s om he o he s when being conside ed as an
explana o y a iable o he beha io o oad eigh anspo in Colombia.
I is ue ha he Cons uc ion sec o p esen s be e co ela ion alues in Figu e 7,
bu hey a e in e se. E en so, co ela ion analyses we e pe o med o hose ime se ies
pe iods (acco ding o Figu e 7). The esul s o he adjus ed R
2
o he h ee load a iables
we e no g ea e han 0.26. These esul s do no alida e an independen co ela ion o he
GDP o he Cons uc ion sec o and oad eigh anspo in Colombia.
As a simila si ua ion, a s udy de eloped in B azil analyzed he ela ionship be ween
in es men in in as uc u e and economic sec o s, i u ned ou ha he Cons uc ion sec o
was he only one wi h a back linkage. The Ag icul u al, Communica ions, and Indus ial
sec o s u ned ou o be he key sec o s. This is a si ua ion like he one esul ing om his
s udy (Cen u ião e al. 2024).
Economies 2024,12, 205 18 o 28
4.2. His o ical T end Change Due o he COVID-19 Pandemic
The COVID-19 pandemic esul ed in a decline in he dynamics o he economy, and i
could be p esumed ha his also a ec ed he anspo sec o . Figu e 10 clea ly shows he
decline in economic de elopmen o each o he sec o s in 2020.
A i s glance, one migh hink ha he COVID-19 pandemic pe iod ma ked a di e -
ence in he end in he beha io o anspo ed ca go. Howe e , we ha e ound ha he
da a analyzed, including he economic s a is ical da a du ing he pandemic, do no a ec
he his o ical end p io o he pandemic. This can be said because he his o ical beha io
o anspo ed ca go, in he h ee indica o s analyzed, did no egis e a ypical beha io
be ween he yea s 2020 and 2021 because i s end was inc easing (Figu e 12).
Economies 2024, 12, x FOR PEER REVIEW 19 o 30
(a)
(b)
(c)
Figu e 12. Colombia Cons uc ion economic sec o GDP end (billions o COP). Qua e ly accoun s
o he yea s 2019 o 2024. (a) To al a els; (b) To al kilog ams; (c) To al gallons.
Howe e , o con inue he analysis o how much he esul s and conclusions o his
esea ch would ha e changed i he e had been no pandemic, ano he da a able was gen-
e a ed in which he sec o al GDP alues we e eplaced be ween he pe iods 2020-I and
2021-III (Table A3).
Figu e 12. Colombia Cons uc ion economic sec o GDP end (billions o COP). Qua e ly accoun s
o he yea s 2019 o 2024. (a) To al a els; (b) To al kilog ams; (c) To al gallons.
Economies 2024,12, 205 19 o 28
Howe e , o con inue he analysis o how much he esul s and conclusions o his
esea ch would ha e changed i he e had been no pandemic, ano he da a able was
gene a ed in which he sec o al GDP alues we e eplaced be ween he pe iods 2020-I and
2021-III (Table A3).
Wi h he changes in he da abase, assuming ha he e was no pandemic, he Spea man
ho alues we e close o he o iginal ones (Figu e 6). The e we e only be e alues o he
Mining and he Cons uc ion sec o s, al hough his las one s ill shows an in e se end
(Table 6).
Table 6. Spea man ho alues. Da a be ween 2020-I and 2021-III (COVID-19 pandemic) eplaced by
linea end.
Ag o.
Mining Manu .
Home
Public
Se ices
Cons .
Comm.
In o
and
Comm.
Finan.
and
Insu .
Real
S a e
P o .
Ac-
i e.
Public
Adm.
Global
GDP
To al
a el 0.91 0.85 0.90 0.92 −0.72 0.92 0.92 0.92 0.94 0.92 0.94 0.92
To al
kg 0.86 0.77 0.84 0.87 −0.68 0.88 0.88 0.88 0.89 0.88 0.89 0.87
To al
gal 0.92 0.89 0.91 0.92 −0.74 0.93 0.93 0.93 0.94 0.93 0.94 0.93
Abb e ia ions: Ag o.: Ag obusiness; Manu .: Manu ac u e; Cons .: Cons uc ion; Comm.: Comme ce; In o and
Comm.: In o_communica ions; Finan. and Insu .: Financial_insu ance; P o . A i .: P o essional_ac i i ies; Public
Adm.: Public_adminis a on_Educa ion_Social_heal h_se ices.
I is logical o hink ha , wi hou he economic changes caused by he pandemic
be ween 2020 and 2021, he co ela ion be ween he economy and anspo would ha e
mo e signi ican coe icien s. Howe e , his esea ch shows ha he co ela ion emains
alid despi e he change in end in he s a is ics o all he indica o s s udied.
5. Conclusions
The esul s ob ained coincide wi h he p emise ha he economic beha io o he main
coun y’s economic sec o s signi ican ly co ela es wi h he amoun o ca go anspo ed by
oad, bu one yea la e . This is s a ed based on Spea man’s ho alues, since, o all sec o s
excep he Cons uc ion sec o , hey a e g ea e han 0.7 (compa ing Figu es 4,5,7and 8
wi h Figu e 6).
The di e en beha io o he Cons uc ion sec o is con i med in he P incipal Compo-
nen Analysis (PCA) (Figu e 9), in which he ec o o his economic sec o de ia es om
ha o he o he sec o s. In addi ion, when pe o ming he G ange es , he Cons uc ion
sec o is he only one ha does no mee he causali y condi ion, because i has a p- alue
g ea e han 0.05. The o he sec o s achie e he causali y condi ion be ween he sec o al
GDP and he oad eigh anspo indica o s (Table 1).
Ano he aspec analyzed was he signi icance o each o he economic sec o s in he
co ela ion wi h he economic de elopmen acco ding o he p- alues ob ained om he
linea ized mul i a ia e co ela ions o each o he h ee indica o s o anspo ed ca go
(numbe o ips, kilog ams, and gallons). As a esul , i is concluded ha he mul i a ia e
co ela ion be ween he GDP o he economic sec o s and he ca go anspo ed one yea
la e has g ea e s a is ical alidi y han he co ela ion be ween he o e all GDP o he
coun y and he ca go indica o s. This is because, o he i s case, he h ee adjus ed R
2
alues ( o o al a els, o al kilog ams, and o al gallons) a e g ea e han 0.7 and he
p- alue o he co ela ion is less han 0.05. In he second case, he h ee adjus ed R
2
alues
a e lowe (<0.7) (Tables 2–5).
I is alid o assume ha a ime se ies analysis o p edic indica o da a should no
include he nega i e and a ypical changes gene a ed by he COVID-19 pandemic in he
economy. By analyzing he co ela ions and causali ies be ween a iables (Spea man’s
Economies 2024,12, 205 20 o 28
ho and he G ange es p- alue), assuming he abo e p emise, he esul s a e mo e
eliable because he down peak o he da a be ween 2020 and 2021 is elimina ed. Howe e ,
his esea ch e i ied he alidi y o he co ela ion be ween he economy and eigh
anspo by wo king wi h eal his o ical numbe s, ha is, including he consequences o
he pandemic in he da a.
Acco ding o wha is w i en in his sec ion, i is concluded ha , in he Colombian
case, he phenomenon o coupling occu s, and i is a unidi ec ional ela ionship. This
in o ma ion is essen ial in he in as uc u al planning p ocess by he s a e and is a ool o
he p ojec ions o he eigh anspo business sec o .
As o ecommenda ions, i is impo an o inc ease he numbe o s udies ha analyze
he impac be ween economic de elopmen and in as uc u e in La in Ame ica o uni y
he c i e ia and beha io s o he da a se ies. In he egion, he e a e a signi ican numbe
o sou ces ha p o ide o icial da a. Howe e , i is no common o ind documen s in
specialized jou nals ha wo k wi h s a is ical analyses such as he one p esen ed he ein.
A majo limi a ion in conduc ing his esea ch was he lack o simila s udies in majo
coun ies in he La in Ame ican egion ha ha e economic and in as uc u al condi ions
like Colombia. I hese s udies had been ound, a compa a i e analysis o he ela ionship
be ween economic sec o s and he amoun o oad eigh anspo a ion would ha e been
possible.
Thus, in he u u e, we will also s udy he cases o coun ies in he Andean egion
in oad eigh anspo a ion, due o he simila i y o in as uc u al de elopmen wi h
Colombia. The nex s ep in ou in es iga ions is o s udy he igu es o o he means o
ca go anspo a ion, such as ai o sea, bu as an independen analysis. In his case, we
only analyzed Colombia and oad eigh anspo a ion due o he impo ance i has in he
de elopmen o he coun y’s in as uc u e.
Au ho Con ibu ions: Concep ualiza ion, C.F.U.-B.; me hodology, C.F.U.-B. and C.A.Z.-M.; so wa e,
H.A.R.-Q.; alida ion, C.F.U.-B., C.A.Z.-M. and H.A.R.-Q.; o mal analysis, H.A.R.-Q.; in es iga ion,
C.F.U.-B., C.A.Z.-M. and H.A.R.-Q.; esou ces, C.F.U.-B., C.A.Z.-M. and H.A.R.-Q.; da a cu a ion,
H.A.R.-Q.; w i ing—o iginal d a p epa a ion, C.F.U.-B.; w i ing— e iew and edi ing, C.A.Z.-M.;
isualiza ion, C.F.U.-B.; supe ision, H.A.R.-Q.; p ojec adminis a ion, C.F.U.-B., C.A.Z.-M. and
H.A.R.-Q.; unding acquisi ion, C.F.U.-B., C.A.Z.-M. and H.A.R.-Q. All au ho s ha e ead and ag eed
o he published e sion o he manusc ip .
Funding: This esea ch ecei ed no ex e nal unding.
In o med Consen S a emen : No applicable.
Da a A ailabili y S a emen : The o iginal con ibu ions p esen ed in he s udy a e included in he
a icle, u he inqui ies can be di ec ed o he co esponding au ho /s.
Acknowledgmen s: The au ho s wish o acknowledge he a ailable open da a p o ided by he
Na ional Depa men o S a is ics (DANE) and by he Logis ics Po al o he Minis y o T anspo a ion
(Colombia). We also hank he pa icipa ing ins i u ions (Uni e sidad Dis i al F ancisco Joséde
Caldas and Uni e sidad Mili a Nue a G anada, Colombia) o he suppo g an ed o he esea che s.
In he case o he au ho Ca los Felipe U azán-Bonells, i is men ioned ha his is a p oduc o his
academic wo k as a p o esso a he Uni e sidad Mili a Nue a G anada, Colombia.
Con lic s o In e es : The au ho s decla e no con lic s o in e es .
Abb e ia ions
Ag o. Ag obusiness
CAF De elopmen Bank o La in Ame ica and he Ca ibbean
Comm. Comme ce
Cons . Cons uc ion
COP Colombian pesos
COVID co ona i us disease
DANE Na ional Adminis a i e Depa men o S a is ics
Economies 2024,12, 205 21 o 28
ECLAC Economic Commission o La in Ame ica and he Ca ibbean
Finan. & Insu . Financial_insu ance
GDP g oss domes ic p oduc
GDPPC GDP pe capi a
GVA g oss alue added
IADB In e -Ame ican De elopmen Bank
In o & Comm. In o_communica ions
Manu . Manu ac u e
PCA P incipal Componen Analysis
P o . A i . P o essional_ac i i ies
Public Adm. Public_adminis a on_Educa ion_Social_heal h_se ices
UK Uni ed Kingdom
U.S.A. Uni ed S a es o Ame ica
TEU Twen y Equi alen Uni
TRNINF T anspo a ion In as uc u e Index
Economies 2024,12, 205 22 o 28
Appendix A
Table A1. Sec o al and global GDP. Colombia’s da a in billions o Colombian pesos (COP).
Qua e ly
Pe iod Ag obusiness Mining Manu ac u e
Home
Public
Se ices
Supply
Cons uc ion
Come ce In o ma ion and
Communica ions
Financial
and
Insu ance
Real
S a e
P o essional
Ac i i ies
Public
Adminis a on,
Educa ion,
Social Heal h
Se ices
Global_GDP
2017_I 14.784 11.674 26.464 7.159 15.847 39.781 6.551 9.117 19.736 15.428 32.745 225.178
2017_II 14.363 11.257 25.931 7.293 16.390 40.560 6.690 9.697 20.044 15.612 33.495 227.859
2017_III 14.780 11.697 26.168 7.557 16.139 41.326 6.649 9.880 20.411 15.800 34.111 232.030
2017_IV 14.887 12.910 26.458 7.780 16.098 41.385 6.931 10.366 20.785 16.058 34.884 235.404
2018_I 15.048 14.058 27.048 7.835 15.995 42.710 6.872 10.168 21.100 16.451 35.728 240.549
2018_II 15.415 14.443 27.279 8.126 15.611 43.182 7.034 10.698 21.466 16.832 36.356 245.009
2018_III 15.432 14.896 27.640 8.282 16.992 43.545 7.199 10.704 21.947 17.031 37.255 250.176
2018_IV 15.602 14.391 28.191 8.373 16.512 44.271 7.243 11.057 22.312 17.283 37.877 252.057
2019_I 15.624 14.434 27.980 8.730 16.358 45.539 7.174 11.311 22.690 17.665 38.900 256.822
2019_II 16.773 14.945 28.768 8.856 16.391 46.668 7.381 11.686 22.997 18.169 39.334 263.438
2019_III 17.747 14.192 29.260 9.093 16.160 47.715 7.321 12.047 23.266 18.273 40.728 268.314
2019_IV 17.814 14.747 29.823 9.445 16.368 48.344 7.505 11.940 23.435 18.351 40.800 271.494
2020_I 18.155 13.152 28.388 9.655 13.360 48.923 7.470 11.859 23.686 18.425 40.985 267.840
2020_II 18.144 7.867 21.450 9.192 9.309 32.238 6.898 11.818 23.510 16.048 38.841 218.762
2020_III 18.768 10.626 27.699 9.695 11.582 39.171 7.190 12.427 23.795 16.978 41.015 245.173
2020_IV 19.426 11.202 30.202 10.094 12.493 47.448 7.403 12.705 24.052 17.941 42.642 265.966
2021_I 20.241 13.818 31.821 10.390 12.764 50.899 7.709 12.790 24.409 18.873 43.859 280.596
2021_II 21.865 15.091 29.855 10.799 12.448 48.690 7.829 12.824 24.607 19.088 43.395 281.605
2021_III 22.911 17.445 34.774 11.302 12.458 54.985 8.154 13.263 24.894 19.966 46.356 304.916
2021_IV 26.042 20.628 36.789 11.754 14.311 60.787 8.454 13.776 25.227 20.853 46.959 325.468
2022_I 28.783 23.740 39.599 12.487 14.599 62.858 8.809 12.970 25.565 21.797 47.762 344.676
2022_II 30.104 28.687 41.865 13.182 14.853 65.093 9.009 14.880 25.870 22.779 48.998 363.415
2022_III 30.725 30.223 43.258 13.806 15.549 67.410 9.129 14.645 26.315 23.244 49.831 377.709
2022_IV 31.846 27.824 43.747 14.342 15.302 69.297 9.172 14.630 26.685 23.412 49.268 376.722
2023_I 33.806 26.621 45.274 14.925 15.581 71.907 9.325 15.135 27.256 24.155 53.396 392.277
2023_II 33.000 22.675 43.565 15.858 16.074 71.604 9.465 15.251 27.872 24.663 55.677 388.904
2023_III 29.669 23.082 39.889 13.923 14.087 65.260 9.105 15.143 27.713 22.952 52.364 360.685
2023_IV 30.276 23.524 40.429 14.183 14.039 66.293 9.206 15.359 28.020 23.241 53.126 366.050
2024_I 30.884 23.966 40.968 14.444 13.990 67.325 9.306 15.574 28.327 23.531 53.889 371.416
2024_II 31.491 24.408 41.508 14.705 13.941 68.358 9.407 15.790 28.635 23.820 54.651 376.781
2024_III 32.099 24.850 42.047 14.965 13.893 69.390 9.508 16.005 28.942 24.109 55.413 382.147
2024_IV 32.706 25.292 42.586 15.226 13.844 70.423 9.608 16.221 29.249 24.399 56.176 387.512
Economies 2024,12, 205 23 o 28
Table A1. Con .
Qua e ly
Pe iod Ag obusiness Mining Manu ac u e
Home
Public
Se ices
Supply
Cons uc ion
Come ce In o ma ion and
Communica ions
Financial
and
Insu ance
Real
S a e
P o essional
Ac i i ies
Public
Adminis a on,
Educa ion,
Social Heal h
Se ices
Global_GDP
2025_I 33.314 25.733 43.126 15.487 13.795 71.456 9.709 16.436 29.557 24.688 56.938 392.878
2025_II 33.921 26.175 43.665 15.748 13.747 72.488 9.810 16.652 29.864 24.977 57.700 398.243
2025_III 34.529 26.617 44.205 16.008 13.698 73.521 9.910 16.867 30.171 25.267 58.463 403.609
2025_IV 35.136 27.059 44.744 16.269 13.649 74.553 10.011 17.083 30.478 25.556 59.225 408.974
Economies 2024,12, 205 24 o 28
Table A2. Indica o s o ca go anspo ed by land h ough logis ics co ido s. Colombia’s da a.
Qua e ly Pe iod To al T ips To al Kilog ams To al Gallons
2017_I 1,712,139 24,403,893,109 598,805,107
2017_II 1,754,630 24,856,611,315 627,361,966
2017_III 1,797,121 25,309,329,520 655,918,824
2017_IV 1,839,612 25,762,047,726 684,475,682
2018_I 1,882,102 26,214,765,931 713,032,541
2018_II 1,924,593 26,667,484,136 741,589,399
2018_III 1,967,084 27,120,202,342 770,146,258
2018_IV 2,009,575 27,572,920,547 798,703,116
2019_I 2,128,272 28,715,234,440 1,071,545,808
2019_II 2,937,974 39,224,867,127 1,335,159,450
2019_III 2,284,749 30,752,663,253 957,446,070
2019_IV 2,253,100 29,840,117,733 1,002,501,912
2020_I 2,123,129 28,552,312,234 950,074,318
2020_II 1,671,380 22,563,113,345 595,634,532
2020_III 2,124,219 28,234,632,136 745,152,235
2020_IV 2,228,770 29,108,835,203 859,227,950
2021_I 2,261,989 30,174,420,639 898,275,486
2021_II 2,015,411 27,107,307,599 825,454,243
2021_III 2,470,906 33,120,531,267 993,196,511
2021_IV 2,548,051 33,563,269,564 1,064,696,558
2022_I 2,480,903 33,392,600,617 1,180,961,171
2022_II 2,518,905 33,914,633,099 1,189,402,223
2022_III 2,640,869 34,575,554,921 1,216,439,646
2022_IV 2,635,817 33,990,783,320 1,270,543,551
2023_I 2,573,636 33,476,995,991 1,262,474,131
2023_II 2,550,652 32,886,768,444 1,307,820,168
2023_III 3,806,436 46,707,308,514 1,875,156,347
2023_IV 2,859,390 36,627,284,657 1,369,840,285
2024_I 2,901,881 37,080,002,863 1,398,397,143
2024_II 2,944,372 37,532,721,068 1,426,954,002
2024_III 2,986,863 37,985,439,274 1,455,510,860
2024_IV 3,029,353 38,438,157,479 1,484,067,719
2025_I 3,071,844 38,890,875,685 1,512,624,577
2025_II 3,114,335 39,343,593,890 1,541,181,436
2025_III 3,156,826 39,796,312,096 1,569,738,294
2025_IV 3,199,316 40,249,030,301 1,598,295,152
