Accelerating the Improvement of Human Well-Being in China through Economic Growth and Policy Adjustment
Abstract
:1. Introduction
2. Materials
3. Methods
3.1. Revision of GPI
3.2. Wavelet Analysis
3.2.1. XWT
3.2.2. WTC
3.3. Kaya Identity
3.4. LMDI Decomposition Model
4. Result Analysis
4.1. Changes in GPI and GDP
4.2. Response of GPI to GDP on Annual Scale
4.3. Contribution Proportions of Social, Economic, and Ecological Indicators to Increase in GPI
4.4. Relative Contribution of Demographic and Economic Effects to GPI Changes
5. Discussion
5.1. Comparison with Previous Research Results
5.2. The Impacts of Economic Growth and Policy Adjustment on Human Well-Being
5.3. Limitations and Future Research
6. Conclusions
- (1)
- The per capita GPI of China showed an increasing trend with an annual growth rate of 12.43% at the national level from 1995 to 2017. Although the growth rate of the per capita GPI slowed down after 2016, it has not reached the growth threshold.
- (2)
- The changes in the GPI have followed the same pattern as the changes in economic development in China, rather representing the phenomenon of economic growth accompanied by welfare decline that has been reported in some countries and regions.
- (3)
- The contribution rates of most indicators promoting the growth of human well-being showed increasing trends, while the contribution rates of most indicators reducing human well-being declined after 2010, and the growth rates of 9 out of 13 negative indicators showed downward trends.
- (4)
- The improvement of human well-being was mainly driven by economic growth, but it was most sensitive to social factors.
- (5)
- The growth of personal consumption expenditures, the value of domestic labor, ecosystem services value, and net capital growth greatly improved human well-being, accounting for 94.25% of the total contribution of all positive indicators. Income inequality and the cost of leisure time loss were the two main factors that reduced human well-being, accounting for 48.04% of the total contribution of all negative indicators.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Component | Item | Contribution | Classification |
---|---|---|---|
Economic component | Personal consumption expenditures | + | Built |
Income inequality | − | − | |
Services of consumer durables | + | Built | |
Cost of consumer durables | − | Built | |
Value of highways and streets | + | Built | |
Net capital growth | ± | Built | |
Environmental component | Cost of water pollution | − | Natural |
Cost of air pollution | − | Natural | |
Cost of noise pollution | − | Natural | |
Cost of solid waste pollution | − | Natural | |
Cost of other pollution | − | Natural | |
Depletion of non-renewables | − | Natural | |
Cost of climate change | − | Natural | |
Cost of natural disasters | − | Natural | |
Ecosystem service value | + | Natural | |
Social component | Value of domestic labor | + | Human |
Value of volunteer work | + | Human | |
Cost of lost leisure time | − | Human | |
Cost of commuting | − | Human | |
Cost of family breakdown | − | Social | |
Cost of crime | − | Social | |
Non-defensive public expenses on education and health | + | Social | |
Defensive private expenditure on education and health | + | Social | |
Value of higher education | + | Social | |
Cost of underemployment | − | Social | |
Services from public infrastructure | + | Social | |
Cost of auto accidents | − | Social |
Component | Idicators | Method | Data Source |
---|---|---|---|
Economic component | Personal consumption expenditures (+) | The starting point of GPI calculation based on the China Statistical Yearbook. | China Statistical Yearbook |
Income inequality (−) | Personal consumption expenditures × (1−Atkinson index). The specific calculation formula can be found in Long and Ji (2019) [17]. | China Statistical Yearbook | |
Services of consumer durables (+) | Durable goods stock × depreciation rate of 12.5%. | China Statistical Yearbook | |
Cost of consumer durables (−) | Equals the sum of all household expenditure on consumer durables. | China Statistical Yearbook | |
Value of highways and streets (+) | Total expenditures for streets and highways × 7.5% annual value [29]. | China Statistical Yearbook | |
Net capital growth (±) | Equals the difference between newly-added capital investment and the human capital required for such an increment. The specific calculation formula can be found in Long and Ji [17]. | China Statistical Yearbook China Financial Yearbook China Labor Statistical Yearbook China Population and Employment Statistics Yearbook | |
Environmental component | Cost of water pollution (−) | The amount invested by the state in water pollution control. | China Statistical Yearbook China Environmental Statistics Yearbook |
Cost of solid waste pollution (−) | The amount invested by the state in solid waste pollution control. | China Statistical Yearbook China Environmental Statistics Yearbook | |
Cost of air pollution (−) | The amount invested by the state in air pollution control. | China Statistical Yearbook China Environmental Statistics Yearbook | |
Cost of noise pollution (−) | The amount invested by the state in noise pollution control. | China Statistical Yearbook China Environmental Statistics Yearbook | |
Cost of other pollution (−) | The amount invested by the state in other pollution control. | China Statistical Yearbook China Environmental Statistics Yearbook | |
Cost of climate change (−) | Social cost of carbon × total CO2 generated by fossil fuel combustion (USD/ton), USD 89.57/ton in 2000 [37]. | China Statistical Yearbook China Energy Yearbook | |
Depletion of non-renewables (−) | Fossil fuel consumption energy equivalent in oil barrels × substitution cost. The replacement costs of each non-renewable are: oil, USD 17.23/barrel; coal, USD 18.14/t; natural gas, USD 3.66/kCF (based on 1996 figures) [17]. | China Statistical Yearbook China Energy Yearbook | |
Cost of natural disasters (−) | Data were obtained from China Civil Affairs Bureau. | China Civil Affairs Statistical Yearbook | |
Ecosystem service value (+) | The calculation was based on the value equivalent coefficient per unit area of each ecosystem provided by Costanza et al. [36]. | European Space Agency China Forestry Statistical Yearbook | |
Social component | Value of domestic labor (+) | Hours spent on housework by gender × hourly wage for maids, housecleaners, and cleaners. This study only considered the population aged 15–64. | China Statistical Yearbook China Financial Yearbook Data compilation on time use in 2008 |
Value of volunteer work (+) | Total hours of volunteer work × average opportunity cost (USD/h). This study only considered the population aged 15–64. | China Statistical Yearbook China Financial Yearbook | |
Cost of lost leisure time (−) | Total hours of overtime × average opportunity cost (USD/hr) | China Statistical Yearbook China Population Statistic Yearbook Data compilation on time use in 2008 | |
Cost of commuting (−) | Total hours spent commuting × average opportunity cost (USD/h) + direct costs of vehicle purchase and maintenance. | China Statistical Yearbook China Financial Yearbook | |
Cost of family breakdown (−) | Cost of divorce × number of divorces. The unit cost of divorce in China was USD 20427 in 2004 according to Costanza et al. [25] and Wen [38]. | China Statistical Yearbook China Financial Yearbook | |
Cost of crime (−) | Number of occurrances of each crime × victim cost estimate for each crime. Public security expenditure was substituted for crime cost in this study due to data unavailability. | China Statistical Yearbook | |
Non-defensive public expenses on education and health (+) | Public expenses on education and health (i.e., the government paying for residents as a supplementary consumption expenditure of personal income) can improve welfare. Part of the public expenditure on health and education is defensive, so it does not promote public welfare and hence was excluded [39]. Referring to Pulselli et al. [19] and Bleys [11], non-defensive public education and health expenditure was defined as 50% of all public expenses on education and health. | China Statistical Yearbook China Health Statistics Yearbook | |
Defensive private expenditure on education and health (−) | Part of the personal expenditure on education and health is defensive and was excluded from the personal consumption expenditures calculation. According to the research method of Long and Ji [17], the defensive private expenditure on education and health was defined as 50% of all private education and health expenditure. | China Statistical Yearbook | |
Value of higher education (+) | Number of persons with a bachelor’s degree or higher education × social value of higher education [29]. | China Education Statistics Yearbook | |
Cost of underemployment (−) | Number of underemployed people × unprovided hours of constrained work × average hourly wage rate. | China Statistical Yearbook China Population and Employment Statistics Yearbook | |
Services from public infrastructure (+) | Due to data limitations, the value of public infrastructure in this study was mainly based on the investment of the state in the field of transportation, which was similar to public education/health expenditure. It was not included in the personal consumption expenditures, but was considered. | China Statistical Yearbook | |
Cost of auto accidents (−) | Number of crashes × average cost for injury or fatality (USD/incident). The cost and loss data of automobile accidents were provided by the national transportation department. | China Statistical Yearbook | |
GPI | Algebraic sum of all indicators based on their positive and negative contributions. |
Region | Scope | Period | Study |
---|---|---|---|
US | Utah | 1990–2007 | Berik et al. (2011) [53] |
Chittenden, Vermont Burlington County | 1950–2000 | Costanza et al. (2004) [25] | |
Northeast Ohio | 1950–2005 | Bagstad and Shammin (2012) [54] | |
Hawaii | 2000–2009 | Ostergaard-Klem and Oleson (2013) [55] | |
Fifty states | 2011 | Fox and Erickson (2018) [10] | |
Greece | National | 2000–2012 | Menegaki and Tsagarakis (2015) [23] |
Italy | National | 1960–1990 | Guenno and Tiezzi (1998) [39] |
Siena | 1999 | Pulselli et al. (2006) [19] | |
North, center, and south | 1999–2009 | Gigliarano et al. (2014) [22] | |
Brazil | National | 1970–2010 | Andrade and Garcia (2015) [24] |
Poland | National | 1980–1997 | Gil and Sleszynski (2003) [56] |
Japan | National | 1970–2003 | Makino (2008) [57] |
National | 1970–2003 | Kubiszewski et al. (2013) [8] | |
National (rural and urban) | 1975–2008 | Hayashi (2015) [58] | |
China | National | 1997–2016 | Long and Ji (2019) [17] |
China | National | 1995–2017 | This study |
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Wu, L.; Wang, S.; Bai, X.; Luo, G.; Wang, J.; Chen, F.; Li, C.; Ran, C.; Zhang, S. Accelerating the Improvement of Human Well-Being in China through Economic Growth and Policy Adjustment. Int. J. Environ. Res. Public Health 2022, 19, 12566. https://doi.org/10.3390/ijerph191912566
Wu L, Wang S, Bai X, Luo G, Wang J, Chen F, Li C, Ran C, Zhang S. Accelerating the Improvement of Human Well-Being in China through Economic Growth and Policy Adjustment. International Journal of Environmental Research and Public Health. 2022; 19(19):12566. https://doi.org/10.3390/ijerph191912566
Chicago/Turabian StyleWu, Luhua, Shijie Wang, Xiaoyong Bai, Guangjie Luo, Jinfeng Wang, Fei Chen, Chaojun Li, Chen Ran, and Sirui Zhang. 2022. "Accelerating the Improvement of Human Well-Being in China through Economic Growth and Policy Adjustment" International Journal of Environmental Research and Public Health 19, no. 19: 12566. https://doi.org/10.3390/ijerph191912566