The effects of population aging, life expectancy, unemployment rate, population density, per capita GDP, urbanization on per capita carbon emissions

Wang, Qiang; Li, Lejia

doi:10.1016/j.spc.2021.06.029

Cited by 189 publications

(49 citation statements)

References 55 publications

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“…Meanwhile, the higher the population density, the higher the carbon emission level of the regional transportation industry, and there is no carbon reduction effect. This is similar to the previous research view, which believes that an increase in population density will increase greenhouse gas emissions [57,58]. In addition, the increasing proportion of fixed asset investment in the transportation industry has a carbon reduction effect on the transportation industry in the western region, though such an effect is not obvious in other regions.…”

Section: Discussionsupporting

confidence: 88%

The Carbon Emission Reduction Effect of Technological Innovation on the Transportation Industry and Its Spatial Heterogeneity: Evidence from China

Shi

Chan

et al. 2021

Atmosphere

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The carbon reduction effect of technological innovation in the transportation industry is conducive to China’s anticipated realization of carbon neutrality. Therefore, we evaluated carbon emission reduction effect of technological innovation in the transportation industry in China. Based on the panel data of 30 sample provinces in China (excluding Hong Kong, Macao, Taiwan and Tibet) from 2012 to 2018, using the Moran’I index and Getis-Ord Gi index, this paper analyzes the evolutionary trend and spatial autocorrelation of carbon emission in the transportation industry, and analyzes the impact of technological innovation on carbon emission levels of the transportation industry and its spatiotemporal differences by using the geographical and temporal weighted regression (GTWR) model by using ArcGIS 10.4 software. The conclusions are as follows: The carbon emission level of China’s transportation industry generally has been rising steadily, showing a spatial distribution pattern of high emissions in the east and low emissions in the west. The cold spots are concentrated in the western region, and the hot spots are situated in the central and eastern regions. Technological innovation has a carbon reduction effect on the transportation industry in the eastern and north-eastern regions, while the effect in other regions is not obvious. However, there is an obvious “inverted U-shaped” relationship between technological innovation and the transportation industry’s carbon emissions. The technological innovation in the transportation industry will have a significant carbon reduction effect after breaking through the technical pain points. This carbon reduction effect has a higher effect on the western region than on the eastern region. In addition, the economic development level, the fiscal expenditure proportion of the transportation industry, the higher education level, and the proportion of fixed asset investment in the transportation industry have played a positive role in reducing carbon in the transportation industry, but the spatial heterogeneity of this carbon reduction effect is relatively strong. Therefore, during the “14th Five-Year Plan” development period in China, it is necessary to continuously promote the low-carbon development of the transportation industry with technological innovation, while highlighting the differentiated carbon reduction governance, and consolidating the role of talents and fiscal support.

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Section: Discussionsupporting

confidence: 88%

The Carbon Emission Reduction Effect of Technological Innovation on the Transportation Industry and Its Spatial Heterogeneity: Evidence from China

Shi

Chan

et al. 2021

Atmosphere

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“…Thus, for every 1 school enrolment rate, it takes 6 quarters (1.5 years) to yield a 0.10% increase in life expectancy in Nigeria. The positive health effects of school enrolment rate and GDP per capita found in the study are in concord with an earlier conclusion established by Miladinov (2020), Wang and Li (2021) and Sede and Ohemang (2015).…”

Section: Air Pollutionsupporting

confidence: 90%

Air pollution trajectories and life expectancy in Nigeria

Nwani

2022

IJSE

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PurposeThe purpose of the study is to examine the relationship between air pollution and life expectancy considering the roles of institutional quality, agricultural output, foreign direct investment (FDI) and other socio-economic variables in Nigeria from 1981Q1 to 2019Q4.Design/methodology/approachThe study employed spliced quarterly data from annual series collected from the World Bank development indicators and Central Bank of Nigeria. The dynamic multivariate models were analysed using the vector error correction mechanism (VECM), variance decomposition and Granger causality techniques.FindingsThe VECM result indicated a statistically significant adverse effect of air pollution on life expectancy. However, institutional quality, gross domestic product per capita, agricultural output, government social expenditure and school enrolment rate ameliorate the adverse health effects of air pollution, while FDI had mixed effects on life expectancy at different significance levels and at varying lag lengths. The Granger causality result revealed a uni-directional causality from air pollution to life expectancy; bidirectional causal chain between agriculture, FDI, government social expenditure and life expectancy, while a uni-directional causal linkage run from life expectancy to income per head and from school enrolment to life expectancy respectively. However, there is no evidence of causation between institutional quality and life expectancy due to weak institutional quality, but foreign direct invest causes carbon emission in a uni-directional manner in line with pollution haven hypothesis.Research limitations/implicationsThe study's modelling is limited by not considering the resource curse variable in the model due to paucity of data. Nigeria is the biggest crude oil exporter in Africa and ranks 13th globally with daily output of about 2.4 m barrels. Thus, the negation of resource curse in air pollution–life expectancy nexus de-emphasises the effectiveness of rich resources on health and environment. Future studies could address this limitation by incorporating resource curse in environmental-health models for Nigeria.Practical implicationsIt is imperative for the country to adopt stringent anti-air pollution strategies that would establish a balance between FDI attraction and agricultural expansion to the benefits of her citizens' longevity. Also, education should be considered as a strategic action to enhance life expectancy through expansion in the provision, accessibility and affordability to improved school enrolment rate. The choice of quarterly time series over annual data helped to establish the current relationship between air pollution and life expectancy using efficient estimators.Originality/valueThe study contributes to literature by disaggregating yearly series into quarterly series, which has implications for the efficiency of the estimates, unlike earlier studies which ignored this fundamental process. The result of this study produced reliable policy direction for improvement in life expectancy in an emerging economy since quarterly estimates are more robust and reliable for forecasting than its yearly counterpart. The outcome of the study extended the original tenets of the Grossman's health stock theory using the environmental Kuznets curve (EKC) and pollution haven hypotheses (PHH).

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“…In addition, green finance also provides material conditions for the market labor force to flow from polluting enterprises to green production departments. This transfer of the labor force not only reduces the unemployment rate but also promotes the upgrading of industrial structures and green economic transformation, thus influencing carbon emissions (Wang and Li, 2021). Therefore, the decline in the unemployment rate is closely related to the increase in green talent and carbon emissions.…”

Section: Introductionmentioning

confidence: 99%

The effect of green finance and unemployment rate on carbon emissions in china

Cui

Wang²,

Irfan³

et al. 2022

Front. Environ. Sci.

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China’s economy has developed rapidly since the reform and opening up, but under the long-term traditional extensive development model, energy consumption is excessive and carbon emissions rank first in the world. Therefore, how to reduce carbon emissions is a current hot issue in China. Although many scholars have found that green finance is the basic driving force to promote carbon emission reduction, its role path is diverse, and it still needs to be explored in width and depth. Especially in the green transformation stage of the economy, the potential unemployment risk is also a matter of concern. This study selects 30 provincial panel data from the Chinese mainland for the 2004–2019 years to investigate the impact of green finance on carbon emissions from the perspective of unemployment using ordinary least square (OLS), generalized method of moments (GMM), and mediating effect models. In addition, in order to avoid the bias of regression results caused by the cross-section dependence of the data, the feasible generalized least squares (FGLS) and the panel-corrected standard errors (PCSE) models are used for the robust test after correction. The findings show that 1) green finance has a significant inhibitory impact on carbon emissions; 2) green finance has significantly reduced the unemployment rate; 3) carbon emissions increase significantly with increasing the unemployment rate; and 4) there is regional heterogeneity in the effect of green finance on carbon emissions in eastern, central, and western China. Green finance in the eastern and central regions significantly inhibits carbon emissions, especially in the central region, while insignificantly in the western region. 5) According to the OLS and mediating effect regression results, economic growth and environmental regulation play a significant positive role in promoting carbon emissions. This study has theoretical reference significance for accelerating the realization of the dual carbon goal and alleviating phased unemployment.

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The effects of population aging, life expectancy, unemployment rate, population density, per capita GDP, urbanization on per capita carbon emissions

Cited by 189 publications

References 55 publications

The Carbon Emission Reduction Effect of Technological Innovation on the Transportation Industry and Its Spatial Heterogeneity: Evidence from China

The Carbon Emission Reduction Effect of Technological Innovation on the Transportation Industry and Its Spatial Heterogeneity: Evidence from China

Air pollution trajectories and life expectancy in Nigeria

The effect of green finance and unemployment rate on carbon emissions in china

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