Research and Analysis on the Influencing Factors of China’s Carbon Emissions Based on a Panel Quantile Model
Abstract
:1. Introduction
2. Literature Review
3. Data and Models
3.1. Data Description
3.2. Analysis of Carbon Emission Status
3.3. Model Description
4. Empirical Results and Analysis
4.1. Stationary Test
4.2. Results and Discussion of Quantile Regression
5. Conclusions and Suggestions
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variable Symbol | Meaning | Computing Method |
---|---|---|
CE | Carbon emissions | As shown in Formula (1) |
PG | Per capita Disposable income | Provincial Statistical Yearbook |
ST | Industrial structure | Percentage of added value of secondary industry in total GDP |
UR | Urbanization level | Urban population as a percentage of the total population |
FS | Average family size | Total population divided by total households |
TI | Scientific and technological innovation level | Number of patent applications per 10,000 people |
CE | PG | ST | UR | FS | TI | |
---|---|---|---|---|---|---|
Mean | 5.204 | 9.652 | 3.612 | 3.876 | 3.216 | 1.023 |
Median | 5.248 | 9.666 | 3.677 | 3.874 | 3.197 | 0.291 |
Maximum | 7.384 | 11.128 | 3.971 | 4.532 | 4.394 | 11.951 |
Minimum | −0.211 | 8.460 | 2.471 | 2.976 | 2.356 | 0.003 |
Std. Dev. | 0.991 | 0.621 | 0.261 | 0.297 | 0.357 | 1.788 |
Skewness | −1.352 | −0.051 | −1.668 | −0.116 | 0.237 | 3.032 |
Kurtosis | 8.205 | 1.995 | 6.457 | 2.959 | 2.841 | 13.036 |
Jarque–Bera | 817.171 | 24.235 | 548.201 | 1.311 | 5.944 | 3265.320 |
Probability | 0.000 | 0.000 | 0.000 | 0.519 | 0.051 | 0.000 |
Sum | 2966.111 | 5501.564 | 2058.671 | 2209.569 | 1833.325 | 582.975 |
Sum Sq. Dev. | 559.283 | 219.400 | 38.791 | 50.193 | 72.615 | 1819.072 |
Variables | Levels | First Difference | ||
---|---|---|---|---|
Fisher-ADF Test | Fisher-PP Test | Fisher-ADF Test | Fisher-PP Test | |
CE | 22.961 (1.000) | 29.723 (0.999) | 171.092 (0.000) | 335.635 (0.000) |
PG | 25.588 (1.000) | 10.566 (1.000) | 108.885 (0.000) | 158.832 (0.000) |
ST | 26.349 (1.000) | 13.823 (1.000) | 100.521 (0.000) | 124.090 (0.000) |
UR | 81.973 (0.031) | 119.675 (0.000) | 131.938 (0.000) | 237.285 (0.000) |
FS | 67.253 (0.242) | 92.8540 (0.004) | 164.446 (0.000) | 449.673 (0.000) |
TI | 47.3507 (0.882) | 101.904 (0.000) | 213.177 (0.000) | 577.459 (0.000) |
Inspection Method | Inspection Form | Statistical Value | p Value |
---|---|---|---|
Pedroni test | Modified Phillips–Perron t | 6.229 | 0.000 |
Phillips–Perron t | −4.4193 | 0.000 | |
Augmented Dickey–Fuller t | −4.3482 | 0.000 | |
Kao test | Modified Dickey–Fuller t | −1.8535 | 0.031 |
Dickey–Fuller t | −5.5930 | 0.000 | |
Augmented Dickey–Fuller t | −10.3112 | 0.000 |
Variables | OLS | Quantile Statistics | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
10th | 20th | 30th | 40th | 50th | 60th | 70th | 80th | 90th | ||
PG | 0.933 (0.000) | 0.893 (0.003) | 0.943 (0.000) | 0.932 (0.000) | 0.898 (0.000) | 0.823 (0.000) | 0.829 (0.000) | 0.919 (0.000) | 0.859 (0.000) | 0.806 (0.000) |
ST | 1.658 (0.000) | 1.460 (0.000) | 1.648 (0.000) | 1.397 (0.000) | 1.260 (0.000) | 1.580 (0.000) | 1.854 (0.000) | 1.984 (0.000) | 1.923 (0.000) | 1.739 (0.000) |
UR | −1.272 (0.000) | −1.618 (0.000) | −1.838 (0.000) | −1.727 (0.000) | −1.532 (0.000) | −1.116 (0.000) | −0.808 (0.000) | −0.790 (0.000) | −0.702 (0.000) | −0.438 (0.016) |
FS | −1.036 (0.000) | −0.970 (0.017) | −1.087 (0.000) | −1.101 (0.000) | −1.157 (0.000) | −1.042 (0.000) | −0.762 (0.000) | −0.651 (0.000) | −0.786 (0.000) | −0.863 (0.000) |
TI | −0.050 (0.011) | 0.019 (0.615) | −0.014 (0.687) | −0.034 (0.236) | −0.068 (0.004) | −0.067 (0.005) | −0.056 (0.055) | −0.063 (0.045) | −0.032 (0.176) | −0.055 (0.000) |
C | −1.478 (0.192) | −0.103 (0.982) | 0.267 (0.913) | 1.163 (0.494) | 1.596 (0.235) | −0.639 (0.686) | −3.621 (0.063) | −5.228 (0.000) | −4.230 (0.000) | −3.609 (0.000) |
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Liu, Y.; Chang, X.; Huang, C. Research and Analysis on the Influencing Factors of China’s Carbon Emissions Based on a Panel Quantile Model. Sustainability 2022, 14, 7791. https://doi.org/10.3390/su14137791
Liu Y, Chang X, Huang C. Research and Analysis on the Influencing Factors of China’s Carbon Emissions Based on a Panel Quantile Model. Sustainability. 2022; 14(13):7791. https://doi.org/10.3390/su14137791
Chicago/Turabian StyleLiu, Yunlong, Xianlin Chang, and Chengfeng Huang. 2022. "Research and Analysis on the Influencing Factors of China’s Carbon Emissions Based on a Panel Quantile Model" Sustainability 14, no. 13: 7791. https://doi.org/10.3390/su14137791