Author：LI Zheng
Introduction
International Institute of Green Finance (IIGF) of the Central University of Finance and Economics (CUFE) regularly conducts a multi-dimensional assessment of the provincial-level green development in China. In 2020, for the third time in a row, IIGF released The Evaluation Report of Provincial Green Finance Development in China (2020)
BACKGROUND
IIGF regularly conducts a multi-dimensional assessment of the provincial-level green development in China. In July 2017, the Standing Committee of the State Council decided to launch Pilot Zones for Green Finance Reform and Innovation (Green Finance Pilot Zones) in Guangdong, Guizhou, Jiangxi, Zhejiang, and Xinjiang, marking the beginning of comprehensive development of green finance in China.
After the first year of Green Finance Pilot Zones’ operation, IIGF published The Evaluation Report of Provincial Green Finance Development in China (2020). Through impartial evaluation of: local policy progression, promotion of green finance concepts, improved capacity of local authorities, and progress in market infrastructure, the report reviewed progress and summarized the status of green finance in various provincial-level administrative regions in China.
China Provincial Green Finance Index 2020
After three years of Green Finance Pilot Zones operation, the IIGF has published an updated and optimized indicator system to calculate the Provincial Green Finance Index and updated it with the most recent data. The report also compared local experiences in promoting green finance, analyzed the main problems in the acceleration of green finance in various provinces, and identified the future challenges and opportunities. The results of the report could support development of the green financial system in China.
The Index evaluates performance and progress made in green finance in all 31 provinces, autonomous regions, and municipalities directly under the Central Government and it includes Green Finance Pilot Zones. Results of this research supported by detailed analysis of the local cases, can serve as valuable decision-making references that can be used for designing green finance blueprints and providing specific support to various regions in China.
The updated indicator system presented in the 2020 evaluation report more accurately and comprehensively reflects the status of green finance on a provincial level, at the same time making the indicator system more scientific and objective. The scoring results of the 2020 Provincial Green Finance Index are shown in the table below.
2020 Evaluation Results
Table 1. Evaluation results of the green finance development index of each province (autonomous region, municipality directly under the Central Government) in the 2020 evaluation cycle
| Province (autonomous region, municipality directly under the Central Government) | Policy advancement | Market behavior | Overall | |||
| Position | Score | Position | Score | Position | ||
| Beijing | 23.37 | 9 | 33.73 | 1 | 57.10 | 1 |
| Zhejiang | 30.43 | 3 | 26.61 | 3 | 57.04 | 2 |
| Guangdong | 29.29 | 4 | 27.27 | 2 | 56.56 | 3 |
| Jiangxi | 31.62 | 2 | 18.36 | 5 | 49.98 | 4 |
| Jiangsu | 26.97 | 5 | 19.69 | 4 | 46.65 | 5 |
| Sichuan | 31.70 | 1 | 14.43 | 14 | 46.13 | 6 |
| Fujian | 23.35 | 10 | 15.44 | 11 | 38.79 | 7 |
| Guizhou | 23.49 | 8 | 12.72 | 16 | 36.21 | 8 |
| Gansu | 26.19 | 6 | 8.89 | 23 | 35.08 | 9 |
| Xinjiang | 23.60 | 7 | 10.83 | 19 | 34.42 | 10 |
| Anhui | 19.00 | 14 | 14.92 | 13 | 33.92 | 11 |
| Inner Mongolia | 22.66 | 11 | 11.01 | 18 | 33.67 | 12 |
| Shandong | 15.51 | 18 | 16.56 | 6 | 32.07 | 13 |
| Shanghai | 16.34 | 16 | 15.64 | 9 | 31.99 | 14 |
| Hunan | 19.69 | 12 | 12.17 | 17 | 31.87 | 15 |
| Hebei | 14.59 | 20 | 16.07 | 7 | 30.66 | 16 |
| Hubei | 14.87 | 19 | 15.78 | 8 | 30.65 | 17 |
| Chongqing | 19.51 | 13 | 10.22 | 20 | 29.73 | 18 |
| Shanxi | 14.29 | 21 | 15.30 | 12 | 29.60 | 19 |
| Henan | 12.97 | 25 | 15.52 | 10 | 28.49 | 20 |
| Shaanxi | 14.29 | 22 | 13.66 | 15 | 27.95 | 21 |
| Guangxi | 18.61 | 15 | 7.93 | 26 | 26.54 | 22 |
| Qinghai | 16.08 | 17 | 6.93 | 29 | 23.01 | 23 |
| Heilongjiang | 13.97 | 23 | 8.28 | 24 | 22.25 | 24 |
| Hainan | 13.06 | 24 | 7.87 | 27 | 20.94 | 25 |
| Yunnan | 10.11 | 30 | 9.93 | 21 | 20.04 | 26 |
| Tianjin | 10.27 | 28 | 9.16 | 22 | 19.43 | 27 |
| Liaoning | 10.13 | 29 | 8.13 | 25 | 18.25 | 28 |
| Jilin | 11.07 | 26 | 6.64 | 30 | 17.72 | 29 |
| Ningxia | 10.41 | 27 | 6.97 | 28 | 17.38 | 30 |
| Tibet | 7.28 | 31 | 1.04 | 31 | 8.31 | 31 |
According to the 2020 evaluation results, the total score earned by the provinces ranged between 8.31 points to 57.10 points. The areas where Green Finance Pilot Zones were located performed better and were in the forefront of the scorecard. It demonstrates that the provinces with pilot zones have taken national-level pilot work seriously and currently play the leading role in promoting green finance in China.
Beijing, Zhejiang, Guangdong, Jiangxi, and Jiangsu were the top 5 performers. The scores among provinces in the Southwest, Northwest, and Eastern regions of China were highly variable. The three provinces in Northeast China (Heilongjiang, Jilin, and Liaoning) were falling behind mainly due to insufficient policy support.
Methodology
The specific steps taken to create the indicator system:
(1) allocate standardized scores to each province’s indicators
(2) determine the weight of the each indicator
(3) based on the score and weight of each indicator, calculate the green finance development index.
Step 1: For qualitative indicators, the score that meets the condition gets 100, and the score that does not meet the requirement gets 0.
For quantitative indicators, the same time point indicators are used for horizontal comparison and standardized scoring.
- For positive indicators, the better the indicator value, the higher the score.
For example:
| Take the score of indicator A of Province X: 100×(AX—Amin)÷(Amax—Amin) Amax is the maximum value of indicator A in province X, and Amin is the minimum value of indicator A in province X. |
- For the negative indicators, the higher the indicator, the lower the score.
For example:
| Take the score of indicator B of Province X: 100-100×(BX-Bmin)÷(Bmax-Bmin) Bmax is the maximum value of indicator B in province X, and Bmin is the minimum value of indicator B in province X. |
In particular, since the data obtained in this report comes from public sources, in case of encounters with undisclosed, uncertain, or hard to verify data, 0 points were granted.
Step 2: Determining the weight assigned to the index
The index weight assignment for the 2020 evaluation system follows the expert scoring method established in 2019 index system. Weights of secondary indicators were determined through questionnaire survey of 20 experts from various sub-fields of green finance with rich practical experience. To avoid the excessive number of third-level indicators that would affect the expert’s scoring accuracy, the experts only assigned the weights to the second-level indicators. More significant indicators were given greater weight to enhance the scientific approach of the evaluation system.
Limitations
The primary data used for scoring in this report comes from the Provincial Green Finance Database created by the IIGF. At present, all data in the database come from public sources, which ensures the data’s fairness. However, the comprehensiveness of the collected data might have been compromised, therefore, the evaluation results may vary.
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