Research Information System
25th International Conference on Environmental Economics, Policy and International Environmental Relations, Praha, Czech Republic, 23 - 24 November 2023
There is a growing concern about environmental pollution and
its effects on individuals’ wellbeing and health. Due to limited energy supply,
increasing energy demand, and the increasing negative effects of environmental
degradation, more and more attention has been paid to sustainable energy
resources around the globe. Most of the studies analyze both the effects of
renewable energy use and pollutants on health-related variables in specific
regions. However, there is a paucity of research assessing the impact of
renewable energy consumption on self-reported health. The aim of this study is
to examine the impact of environmental degradation on self-reported health with
a particular emphasis on the mediating role of renewable energy use.
This paper utilizes a unique dataset that links micro-level
data with the country-level data. While the micro-level data is based on the
latest country surveys from 6th (2010-2014) and 7th
(2017-2022) Waves of the World Values Survey (WVS) database, the macro-level
data is obtained from the World Development Indicators (WDI) database. Overall,
the sample covers 86,745 individuals for 57 countries.
The two equations system employed in
this paper is presented as follows:
|
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(1) |
|
|
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(2) |
where 
denotes the ordinal variable of individual
self-reported health and
denotes the variables of the
environmental degradation, which are the logarithm of
per capita, the logarithm of 
, and the logarithm of 
, respectively. i and j denote the
individual and country, respectively. ɛ indicates error terms. 
and
are a k×1 vector of covariates.
The presence of unobserved variables
that affect both of the dependent variables may lead to a correlation between
the error terms of Equations (1) and (2), leading to endogeneity problems. In
order to account for the possible endogeneity issues in the modelling, this
paper utilizes the
Conditional Mixed Process (CMP) model based on a general seemingly unrelated
regression (SUR) in which dependent variables are considered independent from
each other.
Our findings show that environmental degradation hinders
self-reported health. The impact of 
is larger than those of and because is used to measure the aggregated impact of multiple
pollutants. Health declines with age. As the level of income and education
increases, people become healthier. Females are less healthy than males.
Additionally, renewable energy consumption reduces environmental degradation,
which in turn improves self-reported health. The
correlation coefficient between the disturbances of the pairs of equations is statistically
significant and negative, implying that single equation modelling may fail to
capture the interdependencies of outcome variables.
This paper has important policy suggestions. First, the use
of renewable energy sources reduces not only the risk of climate change but
also the external costs of local pollution. In this regard, the diffusion of renewable
energy is of great importance especially in developing countries with the
serious health damage due to the local pollution. Second, the carbon pricing
would play an important role in the introduction of renewable energy. Feed-in
tariffs scheme and renewable portfolio standards can also promote renewable
energy use.
