Analysis and Prediction of the Coupling and Coordinated Development of Green Finance–Environmental Protection in China
Abstract
:1. Introduction
2. Literature Review
2.1. Development and Research Status of Green Finance in China
2.2. Progress and Research Status of Environmental Protection in China
2.3. Research Status of Coupling and Coordinated among Systems
3. Source of Data and Methods of Research
3.1. Source of Data
3.2. Methods of Research
3.2.1. Method of Measuring the Coupling and Coordinated Level of GE System
- 1.
- Range method.
- 2.
- Entropy method.
- 3.
- Coupling coordination degree model.
3.2.2. Prediction of Coupling and Coordinated Level of GE System
4. Results of Research
4.1. Measurement Results of GE System Coupling and Coordinated Level
4.2. Prediction Results of GE System Coupling and Coordinated Level
5. Conclusions and Discussion
6. Suggestions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
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First-Level Indicators | Second-Level Indicators | Unit | Index Attribute |
---|---|---|---|
Green finance | the issuing scale of green bonds | One hundred million yuan | + |
the completed investment in treatment of industrial pollution this year | Ten thousand yuan | + | |
A-share market value of energy-saving and environmental protection enterprise | yuan | + | |
the investment of environmental health of municipal public facilities in organized towns | Ten thousand yuan | + | |
Environmental protection | carbon dioxide emissions | Thousand ton | - |
forest coverage rate | % | + | |
the harmless treatment volume of domestic waste | Ten thousand ton | + | |
sulfur dioxide emissions | Ten thousand ton | - |
Second-Level Indicators | Average Weight |
---|---|
the issuing scale of green bonds | 0.2956 |
the completed investment in treatment of industrial pollution this year | 0.1226 |
A-share market value of energy-saving and environmental protection enterprise | 0.2840 |
the investment of environmental health of municipal public facilities in organized towns | 0.1929 |
carbon dioxide emissions | 0.0365 |
forest coverage rate | 0.0771 |
the harmless treatment volume of domestic waste | 0.1159 |
sulfur dioxide emissions | 0.0399 |
Coupling and Coordinated Degree | Coupling and Coordinated Degree Level | Range | Classification |
---|---|---|---|
[0, 0.1) | Extreme disharmony | 0 | Disharmonized decline |
[0.1, 0.2) | Severe disharmony | ||
[0.2, 0.3) | Moderate disharmony | ||
[0.3, 0.4) | Mild disharmony | ||
[0.4, 0.5) | On the verge of disharmony | Intermediate transition | |
[0.5, 0.6) | Barely coordination | ||
[0.6, 0.7) | Primary coordination | Coordinated lifting | |
[0.7, 0.8) | Intermediate coordination | ||
[0.8, 0.9) | good coordination | ||
[0.9, 1) | High-quality coordination |
Level | Variance Ratio (C) | Small Probability Error (P) | Correlation (R) | Relative_Error_Mean | |
---|---|---|---|---|---|
Good | C ≤ 0.35 | P ≥ 0.95 | R > 0.9 | Accuracy level | |
qualified | 0.35 < C ≤ 0.5 | 0.95 > P ≥ 0.8 | 0.9 ≥ R > 0.8 | excellent | <0.01 |
Barely qualified | 0.5 < C ≤ 0.65 | 0.8 > P ≥ 0.7 | 0.8 ≥ R > 0.7 | qualified | 0.01–0.05 |
unqualified | C > 0.65 | P < 0.7 | 0.7 ≥ R > 0.6 (satisfied) | Barely qualified | 0.05–0.1 |
2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | Mean | |
---|---|---|---|---|---|---|---|---|---|---|---|
Beijing | 0.4699 | 0.4703 | 0.4773 | 0.4635 | 0.4122 | 0.4666 | 0.4650 | 0.4933 | 0.3715 | 0.5280 | 0.4630 |
Tianjin | 0.3235 | 0.3118 | 0.3058 | 0.3118 | 0.3431 | 0.2988 | 0.2950 | 0.2794 | 0.3412 | 0.3828 | 0.3225 |
Hebei | 0.2840 | 0.2953 | 0.3109 | 0.3030 | 0.3261 | 0.2849 | 0.2908 | 0.3565 | 0.2840 | 0.3039 | 0.3013 |
Shanxi | 0.2540 | 0.2709 | 0.2953 | 0.2377 | 0.2413 | 0.2426 | 0.3111 | 0.2621 | 0.2645 | 0.2812 | 0.2660 |
Inner Mongolia | 0.3064 | 0.3213 | 0.3500 | 0.3209 | 0.3092 | 0.2988 | 0.2830 | 0.2758 | 0.2390 | 0.2631 | 0.2978 |
Liaoning | 0.2897 | 0.3116 | 0.3185 | 0.2876 | 0.2712 | 0.2669 | 0.2532 | 0.2338 | 0.2317 | 0.2650 | 0.2750 |
Jilin | 0.2559 | 0.2484 | 0.2500 | 0.2817 | 0.2778 | 0.2581 | 0.2587 | 0.2556 | 0.2641 | 0.2531 | 0.2616 |
Heilongjiang | 0.3176 | 0.2989 | 0.3657 | 0.3408 | 0.3342 | 0.3048 | 0.3132 | 0.3063 | 0.2988 | 0.2903 | 0.3114 |
Shanghai | 0.3920 | 0.3401 | 0.3438 | 0.3154 | 0.3310 | 0.3542 | 0.3736 | 0.3526 | 0.3598 | 0.3611 | 0.3503 |
Jiangsu | 0.4966 | 0.5332 | 0.4703 | 0.4750 | 0.4888 | 0.4929 | 0.4948 | 0.4934 | 0.4021 | 0.5124 | 0.4857 |
Zhejiang | 0.5450 | 0.5541 | 0.5989 | 0.5443 | 0.5428 | 0.5557 | 0.5250 | 0.5513 | 0.5229 | 0.5698 | 0.5486 |
Anhui | 0.3256 | 0.3199 | 0.3861 | 0.2909 | 0.2972 | 0.3185 | 0.3290 | 0.3499 | 0.3363 | 0.3617 | 0.3309 |
Fujian | 0.3609 | 0.3799 | 0.3944 | 0.3731 | 0.4090 | 0.3711 | 0.3819 | 0.3822 | 0.3760 | 0.4287 | 0.3853 |
Jiangxi | 0.3100 | 0.2923 | 0.3204 | 0.2904 | 0.3007 | 0.3033 | 0.3405 | 0.3203 | 0.3311 | 0.3543 | 0.3150 |
Shandong | 0.3966 | 0.4007 | 0.3420 | 0.3997 | 0.4238 | 0.4159 | 0.4131 | 0.4185 | 0.3703 | 0.4956 | 0.4066 |
Henan | 0.3241 | 0.3165 | 0.3687 | 0.3203 | 0.3211 | 0.3487 | 0.3718 | 0.3695 | 0.3549 | 0.4392 | 0.3502 |
Hubei | 0.3490 | 0.3533 | 0.3957 | 0.3713 | 0.3584 | 0.4894 | 0.3773 | 0.4529 | 0.4566 | 0.3800 | 0.3976 |
Hunan | 0.3154 | 0.3591 | 0.3604 | 0.3372 | 0.3479 | 0.3366 | 0.3624 | 0.3489 | 0.3486 | 0.3909 | 0.3472 |
Guangdong | 0.5094 | 0.5355 | 0.4981 | 0.5478 | 0.5572 | 0.5472 | 0.5793 | 0.6116 | 0.5806 | 0.6418 | 0.5582 |
Guangxi | 0.2527 | 0.2559 | 0.2824 | 0.2634 | 0.2988 | 0.2832 | 0.2971 | 0.2920 | 0.3005 | 0.2884 | 0.2795 |
Hainan | 0.2035 | 0.2088 | 0.1925 | 0.1989 | 0.2079 | 0.2192 | 0.2287 | 0.2262 | 0.2292 | 0.2988 | 0.2182 |
Chongqing | 0.2582 | 0.3046 | 0.2985 | 0.2883 | 0.3067 | 0.2948 | 0.3535 | 0.3168 | 0.3053 | 0.3640 | 0.3098 |
Sichuan | 0.4274 | 0.4184 | 0.4631 | 0.4342 | 0.4098 | 0.3847 | 0.3942 | 0.4944 | 0.4065 | 0.4142 | 0.4231 |
Guizhou | 0.2474 | 0.2393 | 0.2581 | 0.2461 | 0.2489 | 0.2609 | 0.2648 | 0.2964 | 0.2978 | 0.3444 | 0.2669 |
Yunnan | 0.2597 | 0.2755 | 0.2734 | 0.2453 | 0.2673 | 0.2497 | 0.2614 | 0.3428 | 0.3162 | 0.3229 | 0.2802 |
Shanxi | 0.3776 | 0.3803 | 0.3841 | 0.3530 | 0.3725 | 0.3387 | 0.3465 | 0.3550 | 0.3571 | 0.3416 | 0.3632 |
Gansu | 0.2052 | 0.2393 | 0.2153 | 0.1895 | 0.1707 | 0.2035 | 0.2001 | 0.2111 | 0.2435 | 0.2096 | 0.2116 |
Qinghai | 0.1671 | 0.1590 | 0.1461 | 0.1577 | 0.1688 | 0.1893 | 0.1616 | 0.1716 | 0.1982 | 0.1590 | 0.1685 |
Ningxia | 0.1748 | 0.1889 | 0.2141 | 0.2199 | 0.2004 | 0.2263 | 0.1929 | 0.2012 | 0.2052 | 0.2010 | 0.2019 |
Xinjiang | 0.2047 | 0.1868 | 0.2207 | 0.2035 | 0.1985 | 0.2013 | 0.1952 | 0.2304 | 0.1926 | 0.1964 | 0.2027 |
Mean | 0.3201 | 0.3257 | 0.3367 | 0.3204 | 0.3248 | 0.3269 | 0.3305 | 0.3417 | 0.3262 | 0.3548 | |
Level | Mild disharmony | Mild disharmony | Mild disharmony | Mild disharmony | Mild disharmony | Mild disharmony | Mild disharmony | Mild disharmony | Mild disharmony | Mild disharmony |
Eastern Region | Central Region | Western Region | Northeast Region | Nationwide | ||||||
---|---|---|---|---|---|---|---|---|---|---|
Test Index | Value | Result | Value | Result | Value | Result | Value | Result | Value | Result |
C | 0.5562 | Barely qualified | 0.4130 | qualified | 0.4801 | qualified | 0.2927 | qualified | 0.3796 | qualified |
P | 0.8 | qualified | 0.900 | qualified | 0.8 | qualified | 1 | good | 0.9 | qualified |
R | 0.7547 | satisfied | 0.6853 | satisfied | 0.6235 | satisfied | 0.7122 | satisfied | 0.7096 | satisfied |
Rel_Error_Mean | 0.0240 | qualified | 0.0288 | qualified | 0.0198 | qualified | 0.0255 | qualified | 0.0198 | qualified |
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Li, S.; Wang, G.; Yang, L.; Geng, J.; Zhu, J. Analysis and Prediction of the Coupling and Coordinated Development of Green Finance–Environmental Protection in China. Sustainability 2022, 14, 9777. https://doi.org/10.3390/su14159777
Li S, Wang G, Yang L, Geng J, Zhu J. Analysis and Prediction of the Coupling and Coordinated Development of Green Finance–Environmental Protection in China. Sustainability. 2022; 14(15):9777. https://doi.org/10.3390/su14159777
Chicago/Turabian StyleLi, Shanshan, Gaoweijia Wang, Li Yang, Jichao Geng, and Junqi Zhu. 2022. "Analysis and Prediction of the Coupling and Coordinated Development of Green Finance–Environmental Protection in China" Sustainability 14, no. 15: 9777. https://doi.org/10.3390/su14159777