A Dynamic Impact Evaluation of the High-Quality Development of China’s Construction Industry Using the Panel Vector Autoregressive Model
Abstract
:1. Introduction
2. Theoretical Analysis and Literature Review
2.1. New Structural Economics
2.2. The Relationship between Environmental Regulation and High-Quality Development
2.3. The Relationship between Property Rights Structures and High-Quality Development
3. Main Variables and Model Specification
3.1. Main Variables
3.1.1. Level of High-Quality Development (HQ)
3.1.2. Environmental Regulation Structures (ERSs)
3.1.3. Property Rights Structures (PRSs)
3.2. Data Sources and Descriptive Statistics
3.3. Panel Vector Autoregressive Model
4. Regional Analysis by K-Means Clustering
4.1. K-Means Clustering
4.2. Cluster Analysis Results
5. Empirical Results and Analysis
5.1. Unit Root Tests
5.2. Cointegration Test
5.3. PVAR Estimation
5.3.1. Lag Selection
5.3.2. PVAR Model Regression
5.4. Granger Causality Test
5.5. Model Stability Test
5.6. Impulse Response
5.6.1. Impulse Response in China
5.6.2. Impulse Response in Region I
5.6.3. Impulse Response in Region II
5.6.4. Impulse Response in Region III
5.7. Variance Decomposition
6. Discussion
7. Conclusions and Contributions
7.1. Conclusions
- (1)
- At the national level, ERS is a positive factor for HQ, whereas PRS is an inhibitor. It can be concluded from the GMM regression results and the granger causality test that there is a unidirectional causality between ERS and HQ and PRS and HQ. According to the regression coefficient, strict environmental regulations will promote the high-quality development of the construction industry, while state-owned property structures will be inhibited at the national level.
- (2)
- ERS has varying impacts on HQ in different regions. The results from the IRFs indicate that the positive effect of ERS on HQ is most significant in provinces with a lower degree of environmental regulations in Region III. The FEVD results suggest that the future ERS will play a relatively important role in influencing HQ in Regions II and III over the next 10 years.
- (3)
- PRS has distinct impacts on HQ in different regions. The results from the IRFs show that the short-term dampening effect of the PRS on HQ is most pronounced in Region I, which exhibits a higher degree of construction development. Conversely, PRS will produce a weak positive effect in the near future in Region III. The FEVD analysis demonstrates that the impact of PRS on HQ becomes more significant as time progresses, compared with ERS.
- (4)
- HQ demonstrates a notably weak differential effect on ERS and PRS across various regions. Additionally, ERS and PRS exhibit distinct interactions, as illustrated by the IRF figures. In different regions, these factors may either promote or inhibit one another. The local government should not ignore the coordination between the environment and property rights. A unilateral increase in the intensity of environmental regulations could significantly impede growth.
7.2. Academic and Practical Contributions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Primary Indicators | Secondary Indicators | Unit | Indicator Attribute |
---|---|---|---|
Industry scale | Gross output value of the construction industry | CNY ten thousand | + |
Number of construction enterprise units | individual | + | |
Number of contracts signed by construction enterprises | Percentage of CNY million | + | |
Completion rate of building area | + | ||
Innovation driven | Technical equipment rate | RMB/person | + |
Power equipment rate | KW/person | + | |
Labor productivity | RMB/person | + | |
Total year-end power of self-owned construction machinery and equipment | Million Kilowatts | + | |
Green development | Sewage treatment rate | Percent | + |
Greening coverage of the completed area | Percent | + | |
Steel consumption with a total output value of CNY 100 million | Tons/CNY 100 million | - | |
Wood consumption with a total output value of CNY 100 million | m3/CNY 100 million | - | |
Cement consumption with a total output value of CNY 100 million | Tons/CNY 100 million | - | |
Open development | The proportion of private enterprises | Percent | + |
The proportion of foreign-invested enterprises | Percent | + | |
The proportion of the output value of private enterprises | Percent | + | |
The proportion of the output value of foreign-invested enterprises | Percent | + | |
Efficiency level | Value-added of the construction industry | CNY ten thousand | + |
Profit margin on production value | Percent | + | |
Employees at the end of the period | Person | + | |
Asset liability ratio | Percent | - |
Primary Indicators | Secondary Indicators | Meaning of the Indicator |
---|---|---|
Explicit environmental regulations | Command-and-control environmental regulations | Investment in environmental pollution control/CNY 100 million |
Market incentive environmental regulations | Income from sewage charges/CNY ten thousand | |
Implicit environmental regulations | Public participatory environmental regulations | The total number of environmental petitions/ individuals |
Variable | Variable Symbol | Meaning |
---|---|---|
Level of high-quality development of the construction industry | HQ | Comprehensive evaluation of the five indicators by principal component analysis |
Environmental regulation structure | ERS | Entropy weight method for calculating environmental regulation structure |
Property rights structure | PRS | The proportion of investment, employment, and revenue output of state-owned units in the national total |
Variable | Obs | Mean | Std. dev | Min | Max | Skewness | Kurtosis | Jarque–Bera |
---|---|---|---|---|---|---|---|---|
HQ | 450 | 2.0819 | 1.1053 | 0.0160 | 6.3750 | 0.7470 | 3.6928 | 50.8501 |
ERS | 450 | 0.1792 | 0.1200 | 0.0506 | 0.9067 | 2.5362 | 11.7488 | 1917.5764 |
PRS | 450 | 0.1656 | 0.0954 | 0.1299 | 0.5443 | 1.3309 | 4.9930 | 207.3230 |
Region | Provinces and Municipalities | Characteristics |
---|---|---|
I | Beijing, Shanghai, Jiangsu, Zhejiang, Shandong, and Guangdong | High-quality level of development, high degree of environmental regulations, and high proportion of state-owned property rights. |
II | Tianjin, Hebei, Liaoning, Shanxi, Fujian, Anhui, Henan, Hubei, Hunan, Sichuan, Chongqing, and Shaanxi | Medium level of quality development, medium level of environmental regulations, and medium share of state ownership. |
III | Inner Mongolia, Jilin, Heilongjiang, Jiangxi, Guangxi, Hainan, Guizhou, Yunnan, Gansu, Qinghai, Ningxia, and Xinjiang | Low quality development, low environmental regulations, and low share of state ownership. |
Region | HQ | ERS | PRS |
---|---|---|---|
China | −4.2426 *** | 1.8874 | −4.4705 |
I | −1.2332 | 1.5030 | 0.3013 * |
II | −1.6397 * | −2.3341 *** | −1.0812 |
III | −1.4258 * | −2.8866 *** | −1.0113 |
Region | ∆HQ | ∆ERS | ∆PRS |
---|---|---|---|
China | −9.9700 *** | −9.2871 *** | −10.4187 *** |
I | −3.5356 *** | −5.2992 *** | −4.8679 *** |
II | −4.5091 *** | −11.8601 *** | −5.4196 *** |
III | −5.5755 *** | −7.2085 *** | −6.0903 *** |
Region | Modified Phillips–Perron Test | Phillips–Perron Test | Augmented Dickey–Fuller Test |
---|---|---|---|
China | 3.2957 *** | −6.1020 *** | −6.0076 *** |
I | 2.0704 ** | −1.4420 * | −1.7893 ** |
II | 1.4164 * | −5.7065 *** | −5.8123 *** |
III | 2.4678 *** | −6.5818 *** | −2.4213 *** |
Region | Lag | AIC | BIC | HQIC |
---|---|---|---|---|
China | 1 | −8.7747 * | −7.7680 * | −8.3756 * |
2 | −8.1743 | −7.0084 | −7.7107 | |
3 | −7.7812 | −6.4342 | −7.2439 | |
I | 1 | −7.9531 * | −7.1373 * | −7.6265 * |
2 | −7.7236 | −6.5853 | −7.2705 | |
3 | −7.3495 | −5.8566 | −6.7596 | |
II | 1 | −8.7328 * | −7.8530 * | −8.3754 * |
2 | −8.1453 | −7.0316 | −7.6927 | |
3 | −6.3332 | −4.9573 | −5.7741 | |
III | 1 | −10.3161 * | −9.1680 * | −9.7570 * |
2 | −10.0477 | −8.8197 | −9.6904 | |
3 | −9.9334 | −8.9402 | −9.4809 |
Region | Variable | HQt−1 | ERSt−1 | PRSt−1 |
---|---|---|---|---|
China | HQ | 0.0865 | 8.1120 *** | −5.3871 *** |
ERS | 0.0001 | 0.7311 *** | −1.1451 *** | |
PRS | −0.0024 | 0.1689 *** | 0.5566 *** | |
I | HQ | 0.0883 | 1.4157 | −16.2496 ** |
ERS | 0.0003 | 0.9152 *** | −0.0772 | |
PRS | 0.0019 | −0.0785 ** | 0.2432 | |
II | HQ | 0.0377 | 7.9106 *** | −10.4267 *** |
ERS | −0.0016 | 0.5320 *** | −0.4703 *** | |
PRS | −0.0067 | 0.2384 *** | 0.5261 *** | |
III | HQ | −0.0913 | 34.7050 *** | −0.4553 |
ERS | 0.0033 | 0.3668 *** | −0.0635 ** | |
PRS | −0.0268 | 2.7607 *** | 0.7782 *** |
Region | Variable | HQ | ERS | PRS |
---|---|---|---|---|
China | HQ | 64.542 *** | 24.511 *** | |
ERS | 0.002 | 13.355 *** | ||
PRS | 0.357 | 12.412 *** | ||
I | HQ | 0.670 | 4.754 ** | |
ERS | 0.005 | 0.342 | ||
PRS | 0.663 | 4.458 ** | ||
II | HQ | 70.387 *** | 32.809 *** | |
ERS | 0.080 | 38.492 *** | ||
PRS | 1.730 | 20.111 *** | ||
III | HQ | 33.488 *** | 0.336 | |
ERS | 2.188 | 6.410 ** | ||
PRS | 2.257 | 25.936 *** |
Region | Period | HQ | ERS | PRS |
---|---|---|---|---|
China | 2 | 81.52 | 11.80 | 6.68 |
4 | 70.88 | 16.88 | 12.24 | |
6 | 69.06 | 17.25 | 13.69 | |
8 | 68.75 | 17.24 | 14.01 | |
10 | 68.71 | 17.23 | 14.06 | |
I | 2 | 66.15 | 0.41 | 33.81 |
4 | 62.29 | 2.08 | 35.62 | |
6 | 60.88 | 4.28 | 34.83 | |
8 | 59.90 | 5.82 | 34.28 | |
10 | 59.20 | 6.91 | 33.89 | |
II | 2 | 69.61 | 21.43 | 8.96 |
4 | 61.80 | 20.68 | 17.52 | |
6 | 60.74 | 20.84 | 18.42 | |
8 | 60.62 | 20.98 | 18.39 | |
10 | 60.61 | 20.99 | 18.39 | |
III | 2 | 74.59 | 25.35 | 0.06 |
4 | 70.82 | 27.04 | 2.14 | |
6 | 69.88 | 26.84 | 3.28 | |
8 | 69.57 | 27.01 | 3.41 | |
10 | 69.53 | 27.05 | 3.41 |
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Li, H.; Yang, X.; Meng, F.; Hou, Y.; Zhang, J.; Zhang, L.; Yang, G.; Liu, J. A Dynamic Impact Evaluation of the High-Quality Development of China’s Construction Industry Using the Panel Vector Autoregressive Model. Buildings 2024, 14, 2871. https://doi.org/10.3390/buildings14092871
Li H, Yang X, Meng F, Hou Y, Zhang J, Zhang L, Yang G, Liu J. A Dynamic Impact Evaluation of the High-Quality Development of China’s Construction Industry Using the Panel Vector Autoregressive Model. Buildings. 2024; 14(9):2871. https://doi.org/10.3390/buildings14092871
Chicago/Turabian StyleLi, Hui, Xin Yang, Fanyu Meng, Yu Hou, Jinshuai Zhang, Lingyao Zhang, Ge Yang, and Jiyu Liu. 2024. "A Dynamic Impact Evaluation of the High-Quality Development of China’s Construction Industry Using the Panel Vector Autoregressive Model" Buildings 14, no. 9: 2871. https://doi.org/10.3390/buildings14092871