The relationships between population factors and China's carbon emissions: Does population aging matter?
Introduction
According to the Global Carbon Project, the global carbon emissions associated with human activities reached a record high of 36 billion tons in 2013. Meanwhile, China's carbon emissions were the highest globally, accounting for 29%, and China's per capita carbon emissions exceeded those of EU countries for the first time. Long-term, extensive economic growth can lead to excessive energy consumption and environmental deterioration. As one of the signatories to the Kyoto Protocol, China plans to reduce its GHG emissions per unit of GDP in the year 2020 by 40–45% based on 2005 levels [20]. The urgent reduction requirement may slow future economic growth in China.
Currently, a key issue associated with China's population problems is the changing population age structure. As the most populous country in the world, China is rapidly becoming an aging society. Differing from developed countries, China's population aging is characterized by “aging before getting rich”. In 1995, the share of people over 65 was 6.2% in China, increasing to 9.7% in 2013. According to the United Nations, the global average annual growth rate of the aging population will be 2.5% from 1990 to 2020, while this growth rate will be 3.3% in China. For an aging society, China's social insurance system and medical health service system remain far from perfect, particularly in rural areas. Rapid economic growth has played an important role in perfecting the above systems and improving population quality and living standards.
The negative impacts of human activities on the environment have been proven, while the relationships between population aging and carbon emissions remain controversial. Currently, reducing carbon emissions and handling new population problems, especially the aging crisis, are introducing various requirements for China's economic growth. In the stage of the “new normal” economy, China should not only improve their quality of economic development to control carbon emissions but also maintain stable economic growth to improve the endowment insurance system and address new population problems.
Therefore, it is necessary to build an analytical framework to investigate the relationships between population factors and China's carbon emissions. The relationships between population factors and carbon emissions have been previously discussed [8], [39]. However, most studies have focused on population size, population growth and urbanization rate. The impacts of population aging on carbon emissions should be given more attention. Furthermore, China encompasses a vast territory with large socioeconomic differences among the eastern, central and western regions. However, most studies have neglected regional differences [53], [43]. This study investigated the relationships between population factors and China's carbon emissions and further explored the impacts of population aging at the national and regional levels based on the STIRPAT model using panel data from 29 provinces in China from 1997 to 2012. Our study aims to determine how carbon emission levels are connected to population factors and whether the relationship between population aging and carbon emissions differs across regions.
Section snippets
Literature review
The existing literature concerning the relationships between population factors and carbon emissions has mainly focused on three aspects. First, more attention was given to population growth. Through employing the test of causality developed by Granger, [23] proposed a short-term dynamic relationship between carbon dioxide emissions and population growth for the first time. Moreover, based on data from 93 countries from 1975 to 1996, [39] found that global population growth is more than
Model specification
The IPAT model proposed by [14] has been widely employed to study the impacts of human activities on the environment. In the model, I measures environmental effects, P denotes population, A denotes affluence (per capita consumption or production) and T denotes technology (the effect of per unit consumption or production). [41] re-conceptualized IPAT, renaming it ImPACT. They disaggregated T into consumption per unit of GDP (C) and impact per unit of consumption (T). The key limitation of IPAT
Data sources
This paper used panel data from 29 provinces in China from 1997 to 2012. The provincial population factors and GDP per capita data were mainly collected from the China Statistical Yearbook and China's Population and Employment Statistics Yearbook. Furthermore, the energy use and energy consumption data were provided by the China Energy Statistical Yearbook. The provincial carbon emissions were calculated according to the formula and discharge coefficient suggested by the IPCC (2006) (//www.ipcc-nggip.iges.or.jp/
National analysis
As shown in Table 4, the lagged dependent variable (CE(−1)) has a highly significant result in every regression. The coefficient of per capita GDP is positive, but its squared form is negative. This finding is consistent with earlier studies [26], [27]. Energy intensity exhibits a positive coefficient, while urbanization rate has a negative coefficient. They are correlated with carbon emissions.
Regression A is an elementary version that omits additional factors. Population factors are the
Discussion
In addition to population size and population growth, other demographic factors (population distribution, population quality, population living standard and population age structure) are also significantly correlated with carbon emissions. From our empirical results, we identified several meaningful phenomena.
First, population quality promotes China's carbon emissions. This result is consistent with the findings of [5], [24], who indicated that education and total emissions are positively
Conclusions and policy implications
This paper investigates the relationships between population factors and carbon emissions and further explores the impact of population aging on carbon emissions at the national and regional levels based on the STIRPAT model and panel data from 29 provinces in China. Our results show that at the national level, population aging and population quality are positively correlated with China's carbon emissions. The impact of the population living standard on carbon emissions exhibits an urban-rural
Acknowledgments
This research is supported by the Social Science Funds of Fujian Province (No. FJ2015B222) and by the Science and Technology Planning Project of Fujian Province (No. 2016R0088) and also supported by Programs for New Century Excellent Talents in University of Ministry of Education of China (No. NCET-12-0327) and for Young and Middle-aged Teachers' Educational Science Research of Fujian Province (No. JAS150064).
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