Croatia’s Economic Integration in EU’s Regional Supply Chains: Panel Data Quantile Regression
Logistics,
Год журнала:
2025,
Номер
9(2), С. 48 - 48
Опубликована: Апрель 1, 2025
Background:
Recent
global
disruptions
have
exposed
the
vulnerability
of
international
supply
chains,
prompting
a
shift
toward
regionalization
to
enhance
economic
resilience.
As
European
Union
(EU)
member,
Croatia
has
an
opportunity
strengthen
its
integration
into
EU
regional
value
chains
(RVCs),
fostering
stability
and
competitiveness.
This
study
examines
Croatia’s
RVCs
impact.
Methods:
Using
panel
data
from
UNCTAD–Eora
database
(2000–2019),
this
applies
quantile
regression
(PDQR)
analyse
trade
relationships
with
Member
States.
Unlike
traditional
models,
PDQR
captures
variations
in
dynamics
across
different
levels
activity,
providing
more
detailed
understanding
Results:
The
findings
show
that
strengthens
at
higher
quantiles
(τ
=
0.75–0.85),
reflecting
ability
scale
exports
during
expansions.
Lower
0.05–0.25)
display
stable
but
less
dynamic
patterns,
suggesting
need
for
targeted
policy
interventions
chain
Strong
linkages
Germany,
Austria,
Slovenia,
Hungary,
Italy
highlight
comparative
advantage
high-value
sectors.
Conclusions:
supports
resilience
These
provide
insights
policymakers
optimize
participation
mitigate
vulnerabilities.
By
demonstrating
benefits
quantile-based
analysis,
advances
discourse
on
integration.
Язык: Английский
Engagement in global value chains and export quality: Micro evidence from manufacturing firms in a developing country
Journal of International Trade & Economic Development,
Год журнала:
2025,
Номер
unknown, С. 1 - 23
Опубликована: Фев. 10, 2025
Язык: Английский
Does AI Application Matter in Promoting Carbon Productivity? Fresh Evidence from 30 Provinces in China
Sustainability,
Год журнала:
2023,
Номер
15(23), С. 16261 - 16261
Опубликована: Ноя. 24, 2023
Artificial
intelligence
(AI)
is
an
important
force
leading
to
a
new
round
of
scientific
and
technological
revolution,
as
well
promoting
the
realization
dual
carbon
goals
China.
Determining
how
take
advantage
AI
during
green
industrial
transformation
propelling
participation
in
global
value
chains
are
great
importance
In
this
paper,
we
carefully
study
influencing
mechanism.
The
Batik
Variable
Method
then
applied
measure
robot
penetration
industries
across
30
provinces
China
from
2010
2019.
Furthermore,
intermediate
threshold
effect
models
constructed
using
three
crucial
variables.
estimates
reveal
critical
findings:
firstly,
application
has
significant
positive
on
productivity,
conclusion
still
valid
after
series
robustness
tests.
Secondly,
heterogeneity
test
shows
that,
compared
with
central
western
regions,
east
stronger
more
productivity
over
time.
Thirdly,
optimization
human
capital
improvement
innovation
level
both
play
partial
mediating
roles
process,
manufacturing
agglomeration
nonlinear
adjustment
relationship
between
productivity.
conclusions
provide
references
for
further
optimizing
expanding
scenarios
AI,
thereby
contributing
high-quality
economic
development
Язык: Английский
Assessing the predictive ability of information globalization under global value chains‐environmental sustainability nexus in the BRICS economies: A nonparametric causality approach
Natural Resources Forum,
Год журнала:
2024,
Номер
unknown
Опубликована: Июнь 23, 2024
Abstract
The
expansion
of
cross‐border
information
and
production
resources
is
facilitated
by
globalization
through
the
transfer
fresh
ideas,
products,
technologies,
business
models.
This
encourages
globalization's
potential
to
achieve
environmental
other
technological
advancements
in
meantime
helps
make
greener
possible
value‐added
trade.
Prior
research,
however,
largely
ignored
this
aspect
global
value
chains'
studies.
In
order
anticipate
carbon
emissions
(CO2)
BRICS
economies,
novel
study
aims
assess
significance
participation
chains
(GVCs)
(ING).
innovative
research
uses
nonparametric
causality‐in‐quantiles
techniques
on
quarterly
data
from
1995Q1
2018Q4
quantify
for
causality‐in‐variance
causality‐in‐mean
because
there
might
not
be
any
causation
at
first
stage
but
higher‐order
interdependencies.
results
show
that
GVC
ING
had
high
predictive
capability
emissions,
indicating
asymmetry
regarding
sustainability.
Additionally,
asserted
a
significant
interaction
effect
when
it
comes
forecasting
pollution
levels
chosen
nations.
provision
financial
R&D
assistance
energy
efficiency
green
production,
as
well
use
mass
social
media
raise
awareness
among
firms
participating
chains,
may
assist
achieving
SDG
13
Cope26's
goal
reducing
2030.
finding
contributes
crucial
insights
policymakers
enhances
discourse
sustainable
hones
inside
GVCs.
proposes
prioritizing
transparency,
worldwide
measures,
motivations
eco‐friendly
advances
improve
sustainability
Policymakers
are
encouraged
foster
public–private
associations
cohesive
endeavors
diminishing
CO2
emanations
Язык: Английский
Optimising manufacturing growth: when to decouple from global value chains?
Journal of Social and Economic Development,
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 19, 2024
Abstract
In
this
paper,
we
empirically
examine
how
increasing
forward
and
backward
global
value
chains
(GVC)
linkages
affect
manufacturing
growth
in
a
set
of
low-
middle-income
countries
for
the
period
1995–2018.
Using
panel
data
methodologies
fixed-effects,
quantile,
threshold
regressions,
find
that
relationship
between
these
is
nonlinear.
Our
results
reveal
there
positive
(BL)
growth,
but
once
BL
exceed
11–20%
range,
becomes
negative.
Similarly,
FL
can
drive
up
to
certain
threshold,
beyond
which
it
no
longer
boosts
may
even
start
reduce
it.
The
negative
GVC
attributed
‘in–out–in’
theory
participation.
Based
on
findings,
identify
benefit
from
participation
those
will
decoupling
GVCs.
Язык: Английский