Dongju Li
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Dongju Li has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Jie Li
School of Statistics and Big Data, Henan University of Economics and Law, Zhengzhou 450046, China
2 shared publications - Tongtong Shen
School of Statistics, Dongbei University of Finance and Economics, Dalian 116021, China
2 shared publications Jie Li
School of Statistics, Dongbei University of Finance and Economics, Dalian, China
1 shared publication- Mengyu Zhang
School of Economics and Management, Wuhan University, Wuhan 430072, China
1 shared publication - Shibing You
School of Economics and Management, Wuhan University, Wuhan 430072, China
1 shared publication Tongtong Shen
School of Statistics, Dongbei University of Finance and Economics, Dalian, China
1 shared publication
Latest Publications
- Top Cited PapersOpen Access
- 7 September 2022
- Published by Frontiers Media SA in Frontiers in Public Health
- Vol. 10, 914707
The impact of social support on the quality of life among older adults in China: An empirical study based on the 2020 CFPS
Background: As aging issues become serious, how to guarantee and improve the quality of life among older adults has become a hot topic in China. This article is aimed to discuss the impact of formal and informal social support on the quality of life among older adults and the differences in gender and urban–rural areas.Methods: The data used in this article are from the 2020 China Family Panel Studies (CFPS). Quality of life is measured from three dimensions of life: satisfaction, self-rated health, and mental state. This article uses the ordered logistic regression model to analyze the impact of social support on life satisfaction and self-rated health, and the binary logistic regression model to analyze the impact of social support on the mental state. The method of Shapley value decomposition further analyzes the contribution of influencing factors to the quality of life.Results: The activities of daily living (ADL) and income significantly impact the quality of life among older adults. Formal and informal social support positively improved the quality of life among older adults, but the effect of informal social support is greater than that of formal social support. The male older adults are significantly better than the female adults across all three dimensions of quality of life. The mental state of urban older adults is better than that of rural older adults.Conclusion: Formal and informal social support should be strengthened to improve the income of older adults. Older adults should be encouraged to participate in social activities and good interpersonal relationships should be established actively. Female older adults should be paid more attention. The proportion of female older adults participating in insurance should be increased, and the family and intergenerational care burden for female older adults should be reduced. The leisure life of urban older adults should be enriched. The basic social insurance and health service systems in rural areas should be improved.
- 7 September 2022
- Published by Frontiers Media SA in Frontiers in Public Health
- Vol. 10, 914707
Top Cited PapersOpen AccessThe impact of social support on the quality of life among older adults in China: An empirical study based on the 2020 CFPS
Background: As aging issues become serious, how to guarantee and improve the quality of life among older adults has become a hot topic in China. This article is aimed to discuss the impact of formal and informal social support on the quality of life among older adults and the differences in gender and urban–rural areas.Methods: The data used in this article are from the 2020 China Family Panel Studies (CFPS). Quality of life is measured from three dimensions of life: satisfaction, self-rated health, and mental state. This article uses the ordered logistic regression model to analyze the impact of social support on life satisfaction and self-rated health, and the binary logistic regression model to analyze the impact of social support on the mental state. The method of Shapley value decomposition further analyzes the contribution of influencing factors to the quality of life.Results: The activities of daily living (ADL) and income significantly impact the quality of life among older adults. Formal and informal social support positively improved the quality of life among older adults, but the effect of informal social support is greater than that of formal social support. The male older adults are significantly better than the female adults across all three dimensions of quality of life. The mental state of urban older adults is better than that of rural older adults.Conclusion: Formal and informal social support should be strengthened to improve the income of older adults. Older adults should be encouraged to participate in social activities and good interpersonal relationships should be established actively. Female older adults should be paid more attention. The proportion of female older adults participating in insurance should be increased, and the family and intergenerational care burden for female older adults should be reduced. The leisure life of urban older adults should be enriched. The basic social insurance and health service systems in rural areas should be improved.
- Open Access
- 9 May 2022
- Published by MDPI AG in Atmosphere
- Vol. 13 (5) , 767
Impact of Environmental Regulation on Efficiency of Green Innovation in China
The implementation of a reasonable and effective environmental regulation policy can compensate for the dual externalities of green technology innovation and improve green innovation efficiency. Therefore, environmental regulation policy has gradually become an effective means of solving ecological environment problems and achieving green industrial transformation. This paper measures the green innovation efficiency of 30 provinces in China from 2009 to 2019 using the SBM (slacks-based measure) of super-efficiency based on the undesirable output. The dynamic panel regression model is established to explore the impact of different environmental regulations on green innovation efficiency and regional differences. The results reveal that the green innovation efficiency of the 30 provinces shows a fluctuating upward trend, but that differences among provinces are relatively significant. There is a nonlinear relationship between environmental regulation and green innovation efficiency. The impact of command-control and market incentive environmental regulations on green innovation efficiency shows inverted N-shaped and U-shaped patterns, respectively. In different regions, the impact of environmental regulation on green innovation efficiency is also different. In order to ensure that environmental regulation promotes green innovation efficiency, some recommendations are proposed for the government, enterprises, and three regions, respectively.
- 9 May 2022
- Published by MDPI AG in Atmosphere
- Vol. 13 (5) , 767
Open AccessImpact of Environmental Regulation on Efficiency of Green Innovation in China
The implementation of a reasonable and effective environmental regulation policy can compensate for the dual externalities of green technology innovation and improve green innovation efficiency. Therefore, environmental regulation policy has gradually become an effective means of solving ecological environment problems and achieving green industrial transformation. This paper measures the green innovation efficiency of 30 provinces in China from 2009 to 2019 using the SBM (slacks-based measure) of super-efficiency based on the undesirable output. The dynamic panel regression model is established to explore the impact of different environmental regulations on green innovation efficiency and regional differences. The results reveal that the green innovation efficiency of the 30 provinces shows a fluctuating upward trend, but that differences among provinces are relatively significant. There is a nonlinear relationship between environmental regulation and green innovation efficiency. The impact of command-control and market incentive environmental regulations on green innovation efficiency shows inverted N-shaped and U-shaped patterns, respectively. In different regions, the impact of environmental regulation on green innovation efficiency is also different. In order to ensure that environmental regulation promotes green innovation efficiency, some recommendations are proposed for the government, enterprises, and three regions, respectively.
- Open Access
- 5 April 2022
- Published by MDPI AG in Atmosphere
- Vol. 13 (4) , 584
Decomposition and Decoupling Analysis between HDI and Carbon Emissions
The concept of low carbon is extended to the welfare dimension by considering the relationship between carbon emissions and the Human Development Index (HDI). This paper examines the decoupling between carbon emissions per capita and HDI and the welfare output of carbon emissions by using the data from 189 countries, from 1990 to 2019, as well as decomposes the drivers of the decoupling index and carbon emissions performance (CEP) in the example countries. The results show that most countries that achieve strong decoupling have very high human development, while the worst case is that a few countries with an extremely low human development achieved strong decoupling. Moreover, the status of strong decoupling in most countries is not stable, and there is a risk of transformation to another decoupling status. Although the CEP of most countries has gradually improved, very few countries have high CEP. Economic development effects are the primary inhibitor to achieving and maintaining strong decoupling in example countries. The main drivers of CEP improvement are the carbon productivity effects in the Czech Republic, Germany, and the United Kingdom, and the economic development effects in South Korea and Turkey. The main factors inhibiting the increase of CEP are the energy intensity effect in the Czech Republic, Germany, and the UK, and the welfare effect in South Korea and Turkey. These effects are all related to GDP. Economic activity broadly affects the decoupling index and CEP. Recommendations for maintaining HDI growth and reducing carbon emissions are made for countries with different human development.
- 5 April 2022
- Published by MDPI AG in Atmosphere
- Vol. 13 (4) , 584
Open AccessDecomposition and Decoupling Analysis between HDI and Carbon Emissions
The concept of low carbon is extended to the welfare dimension by considering the relationship between carbon emissions and the Human Development Index (HDI). This paper examines the decoupling between carbon emissions per capita and HDI and the welfare output of carbon emissions by using the data from 189 countries, from 1990 to 2019, as well as decomposes the drivers of the decoupling index and carbon emissions performance (CEP) in the example countries. The results show that most countries that achieve strong decoupling have very high human development, while the worst case is that a few countries with an extremely low human development achieved strong decoupling. Moreover, the status of strong decoupling in most countries is not stable, and there is a risk of transformation to another decoupling status. Although the CEP of most countries has gradually improved, very few countries have high CEP. Economic development effects are the primary inhibitor to achieving and maintaining strong decoupling in example countries. The main drivers of CEP improvement are the carbon productivity effects in the Czech Republic, Germany, and the United Kingdom, and the economic development effects in South Korea and Turkey. The main factors inhibiting the increase of CEP are the energy intensity effect in the Czech Republic, Germany, and the UK, and the welfare effect in South Korea and Turkey. These effects are all related to GDP. Economic activity broadly affects the decoupling index and CEP. Recommendations for maintaining HDI growth and reducing carbon emissions are made for countries with different human development.
- Open Access
- 24 November 2021
- Published by MDPI AG in Atmosphere
- Vol. 12 (12) , 1551
Analysis of Correlation between Quality of Life and Subjective Evaluation of Air Quality—Empirical Research Based on CHARLS 2018 Data
This paper mainly focuses on the relationship between the subjective evaluation of air quality and the quality of life (QOL) of middle-aged and elderly residents in China. The 2018 China Health and Retirement Longitudinal Study (CHARLS) project database is the key sources of data, from which 16,736 valid samples were used in our research. Multivariate linear regression analysis and binomial logistic regression model were applied to detect the impact of the subjective evaluation of air quality on QOL, which was evaluated in two dimensions, which are health utility and experienced utility, using the health utility EQ-5D score and the experienced utility of life satisfaction score. Our results show that there is a significant positive correlation between the subjective evaluation of air quality and the two dimensions of QOL. Age, education, marital status and sleep status also have a relatively great impact on the QOL of residents. This worked studied the overall QOL of middle-aged and elderly residents in China, while policy suggestions regarding high-quality air public goods are also given in the paper.
- 24 November 2021
- Published by MDPI AG in Atmosphere
- Vol. 12 (12) , 1551
Open AccessAnalysis of Correlation between Quality of Life and Subjective Evaluation of Air Quality—Empirical Research Based on CHARLS 2018 Data
This paper mainly focuses on the relationship between the subjective evaluation of air quality and the quality of life (QOL) of middle-aged and elderly residents in China. The 2018 China Health and Retirement Longitudinal Study (CHARLS) project database is the key sources of data, from which 16,736 valid samples were used in our research. Multivariate linear regression analysis and binomial logistic regression model were applied to detect the impact of the subjective evaluation of air quality on QOL, which was evaluated in two dimensions, which are health utility and experienced utility, using the health utility EQ-5D score and the experienced utility of life satisfaction score. Our results show that there is a significant positive correlation between the subjective evaluation of air quality and the two dimensions of QOL. Age, education, marital status and sleep status also have a relatively great impact on the QOL of residents. This worked studied the overall QOL of middle-aged and elderly residents in China, while policy suggestions regarding high-quality air public goods are also given in the paper.