<p class="first" id="d10048020e125">This research examines the heterogeneous dynamic
links among healthcare expenditures,
land urbanization, and CO2 emissions across the development levels of China. To this
end, data of 27 Chinese provinces are considered from 1999 to 2018. Theoretically,
this research developed a healthcare expenditures-augmented Stochastic Impacts of
Regression by Population, Affluence, and Technology (STIRPAT) model to incorporate
healthcare expenditures as a determinant of affluence. Empirically, this research
established a system of simultaneous equations based on the healthcare expenditures-augmented
STIRPAT model to estimate the links among the variables. As a pre-analysis, second-generation
Westerlund cointegration is applied and found the long-term equilibrium association
among the variables. The long-run estimations and short-run causality are done by
employing dynamic common correlated effects mean group method (DCCEMGM) and Dumitrescu-Hurlin
causality. A heterogeneous long-run equilibrium linkage is confirmed to exist among
the variables of interest. Concerning the long-run estimates, firstly, the healthcare
expenditures growth and land urbanization exhibited a bilateral positive link. Secondly,
CO2 emissions and healthcare expenditures growth manifested the existence of a bilateral
positive link. And thirdly, a unilateral positive (negative) link is revealed to exist
from a linear term (squared term) of land urbanization to CO2 emissions. Concerning
the short-run results, firstly, a bilateral causal bond exists between the land urbanization
and healthcare expenditures growth. Secondly, a bilateral causal bond prevails between
CO2 emissions growth and healthcare expenditures growth. Finally, a unilateral causal
bond is operational from land urbanization to CO2 emissions growth. In terms of the
nature of the link, the long-run findings are consistent across the data samples.
However, considering the degree of influence, heterogeneity is confirmed across the
development levels for both long- and short-run. It infers that relatively more (less)
developed regions showed relatively strong (weak) influence. Based on empirical findings,
relevant policies are recommended.
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