Land,
Journal Year:
2024,
Volume and Issue:
13(6), P. 803 - 803
Published: June 5, 2024
Sustainable
agricultural
development
is
a
fundamental
requirement
and
crucial
goal
of
modern
agriculture.
It
also
significant
means
enabling
farmers
to
increase
their
incomes.
This
paper
analyses
the
evolutionary
characteristics,
regional
differences
spatial
convergence
level
sustainable
using
kernel
density
estimation,
Dagum’s
Gini
coefficient
model
based
on
panel
data
from
30
provinces
in
China
2012
2021.The
results
show
that:
(1)
At
development,
at
national
three
major
regions
has
shown
an
upward
trend
with
fluctuations,
average
eastern
central
parts
country
higher
than
average,
western
part
lower
average;
however,
growth
rate
highest
among
regions.
(2)
In
terms
characterised
by
agglomeration,
varying
degrees
polarisation.
(3)
differences,
coefficients
for
as
whole,
within
between
regions,
generally
downward
trend,
interregional
remaining
main
source
overall
differences.
(4)
convergence,
there
σ-convergence
β-convergence
across
positive
spillover
effect.
The
conditional
β
that
region
fastest
convergence.
above
findings
provide
scientific
basis
formulation
policies
related
China.
Structural Change and Economic Dynamics,
Journal Year:
2024,
Volume and Issue:
69, P. 463 - 474
Published: March 16, 2024
This
study
investigates
the
contribution
that
digital
transformation
and
globalization
have
made
to
inclusive,
green
economic
growth.
We
construct
an
inclusive
growth
index
leveraging
28
variables
accounting
for
economic,
environmental
social
performances.
By
exploiting
a
dataset
of
95
countries
spanning
from
2010
2020,
we
regress
on
capturing
investments
in
technologies
degree
trade
capital
openness.
Findings
show
while
does
not
strong
significant
relevance
growth,
are
beneficial.
However,
this
evidence
hold
high
income
countries.
Mathematics,
Journal Year:
2025,
Volume and Issue:
13(9), P. 1514 - 1514
Published: May 4, 2025
This
study
constructed
a
DGC-t-MSV
model
by
integrating
dynamic
correlation
and
Granger
causality
into
the
MSV
framework.
Using
daily
closing
price
data
from
4
January
2022
to
21
November
2024,
it
empirically
analyzed
volatility
spillover
effects
between
China’s
carbon
market
traditional
manufacturing
an
industrial
heterogeneity
perspective.
The
findings
are
as
follows:
(1)
exhibits
significant
unidirectional
on
carbon-intensive
industries,
such
steel,
chemicals,
shipbuilding,
automobile
manufacturing,
with
acting
source.
(2)
Bidirectional
exist
industries
forest
products,
textiles,
construction
engineering,
machinery
predominantly
recipient.
(3)
general
correlations
where
strength
is
positively
associated
industry-level
emissions.
Notably,
significant,
whereas
those
textile
industry
products
relatively
weaker.
Furthermore,
demonstrates
substantially
higher
than
industries.
innovatively
explored
perspective,
providing
policy
implications
for
their
coordinated
development.
