Environmental Benefits of the West-East Natural Gas Transmission Project: Cross-Regional Energy Optimization and Transformation for Sustainable Development
Abstract
:1. Background of the Study
2. Literature Review
3. Research Hypothesis
4. Data Selection and Empirical Methods
4.1. Data Sources and Processing
4.1.1. Data Sources
4.1.2. Sample Selection
4.1.3. Data Processing
4.2. Model Design
4.2.1. Basic DID Model
4.2.2. Moderated Effects Model
4.3. Variable Description
4.3.1. Explanatory Variable
4.3.2. Core Explanatory Variables
4.3.3. Adjustment Variables
4.3.4. Control Variables
4.4. Summary and Limitations of the Research Methodology
4.4.1. Summary of Research Methodology
4.4.2. Limitations of Analytical Methods
5. Empirical Findings
5.1. Base DID Model Regression Results
5.2. Moderated Effects Model
5.3. Parallel Trend Testing: An Event Study Approach
5.4. Placebo Testing
5.5. Heterogeneity Analysis
5.5.1. Different Holdings
5.5.2. Different Regions
6. Research Findings and Policy Recommendations
6.1. Conclusions and Discussion of This Study
6.2. Policy Recommendations
6.3. Future Research Directions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
Abbreviation | Explanation |
BRICS | Brazil, Russia, India, China, and South Africa |
CO | Carbon Monoxide |
CSMAR | China Stock Market & Accounting Research Database |
DID | Difference-in-Differences |
ECK | Environmental Kuznets Curve |
ESG | Environmental, Social, and Governance |
GDP | Gross Domestic Product |
Ⅱ | Phase II |
LIN | Linear Interpolation |
WEG | West-East Gas Pipeline |
WEGP | West-East Gas Pipeline Project |
WEGT | West-East Gas Transmission Test |
WTO | World Trade Organization |
SO2 | Sulfur Dioxide |
NOX | Nitrogen Oxides |
PM2.5 | Particulate Matter 2.5 |
CO2 | Carbon Dioxide |
EIA | Environmental Impact Assessment |
R&D | Research and Development |
WENGT | West-East Natural Gas Transmission Project |
ER | Environmental Regulation |
CSDB | China Industrial Enterprises Database |
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Environmental Protection Dimension | Associated Words |
---|---|
Environmental protection objectives | Environmental Protection, Environmental Protection, Green, Clean, Low-carbon, Blue Sky, Green Water, Green Hills |
Target audience: environmental factors | Ecology, Air, Climate |
Target group: environmental pollution | Pollution, Sulfur Dioxide, Chemical Oxygen Demand, Haze, Particulate Matter, Carbon Dioxide, Energy Consumption, Bulk Coal, Coal Combustion, Emissions, Smuggling, Tailpipe Gas |
Environmental protection measures | Energy Saving, Emission Reduction, Desulfurization, Denitrification |
Research Step | Descriptive |
---|---|
Data sources | 1. Chinese Industrial Enterprise Database: data from the National Bureau of Statistics, covering state-owned and non-state-owned industrial enterprises with main business income of CNY 5 million and above. 2. Pollution Database of Chinese Industrial Enterprises: developed by the National Bureau of Statistics and the Ministry of Environmental Protection, covering data on the emission and treatment of 27 industrial pollutants. |
Data integration | 1. Match the Chinese Industrial Enterprise Database with the pollution database using enterprise-unique identifiers and years to form panel data. 2. Delineate the scope of cities along the route of the first line of the West-East Natural Gas Pipeline Project, and cross-check the data against the “China Natural Gas Pipeline Distribution Map 2013” and local government reports. |
Data processing | 1. Samples with negative or missing sales revenue, total assets, total liabilities, and total fixed assets are deleted. 2. Samples with fewer than eight employees are deleted. 3. Then, 2000 is used as the base period to deflate all nominal variables. 4. Samples of firms founded earlier than 1949 are deleted. |
Model selection | 1. The double-difference model (DID) is used to study the impact of the West-East Natural Gas Pipeline Project on the emission of air pollutants from industrial enterprises. 2. The regulation effect model is used to study the regulation effect of the strength of a local government’s environmental regulation on the emission reduction effect of the West-East Natural Gas Pipeline Project. |
Variable description | 1. Explained variables: air pollutant emission levels of industrial firms (lnSO2 and lnYC, log form). 2. Core explanatory variables: treat (whether it is a pathway city or not) and post (whether it is after full ventilation or not). 3. Moderating variables: local government’s strength of environmental regulation, calculated based on the frequency of environment-related keywords in the working report. 4. Control variables: firm year of the square term, logarithm of total firm assets, fixed asset ratio, debt ratio, holdings, and industry category. |
Main premise | 1. The West-East Natural Gas Pipeline Project has a significant emission reduction effect on industrial enterprises in cities along the route. 2. The increase in the intensity of environmental regulation will enhance the emission reduction effect. 3. There are differences in the emission reduction effect under different corporate governance structures. 4. There are significant regional differences, with the most significant emission reduction effect in the eastern coastal region. |
Outcome testing | 1. The parallel trend test is used to verify the validity of the double-difference model. 2. The placebo test is used to test the impact of other policy shocks. 3. Heterogeneity analysis is carried out to analyze the impact of different holding situations and zones on the effect of emission reductions. |
Variable | (1) | (2) | (3) | (4) | (5) | (6) | (7) |
---|---|---|---|---|---|---|---|
Did | −0.138 *** (0.020) [−0.177, −0.099] | −0.043 ** (0.019) [−0.081, −0.005] | −0.163 *** (0.019) [−0.200, −0.126] | −0.067 ** (0.019) [−0.105, −0.029] | −0.119 *** (0.020) [−0.158, −0.080] | −0.051 *** (0.019) [−0.089, −0.013] | 0.006 (0.016) [−0.026, 0.038] |
Year of business square | NO | NO | −5.54 × 10−5 *** (1.01 × 10−5) [−7.52 × 10−5, −3.56 × 10−5] | −3.96 × 10−5 *** (1.03 × 10−5) [−6.00 × 10−5, −1.92 × 10−5] | −3.88 × 10−5 *** (9.93 × 10−6) [−5.80 × 10−5, −1.96 × 10−5] | −3.46 × 10−5 *** (1.02 × 10−5) [−5.46 × 10−5, −1.46 × 10−5] | 1.90 × 10−5 ** (8.46 × 10−6) [2.43 × 10−6, 3.56 × 10−5] |
Total assets | NO | NO | 0.251 *** (0.004) [0.243, 0.259] | 0.232 *** (0.005) [0.222, 0.242] | 0.298 *** (0.005) [0.288, 0.308] | 0.244 *** (0.005) [0.234, 0.254] | 0.433 *** (0.004) [0.425, 0.441] |
Proportion of fixed assets | NO | NO | 0.366 *** (0.019) [0.329, 0.403] | 0.442 *** (0.021) [0.400, 0.484] | 0.315 *** (0.019) [0.278, 0.352] | 0.433 *** (0.021) [0.392, 0.474] | 0.289 *** (0.018) [0.254, 0.324] |
Debt ceiling | NO | NO | 0.369 × 10−4 (0.001) [−0.001, 0.002] | 0.101 *** (0.014) [0.073, 0.129] | 0.001 (8.79 × 10−4) [−0.001, 0.003] | 0.101 *** (0.014) [0.073, 0.129] | −7.86 × 10−6 (7.96 × 10−4) [−0.001, 0.001] |
Holdings | NO | NO | YES | YES | YES | YES | YES |
Industry sector | NO | NO | YES | YES | YES | YES | YES |
Year-fixed effect | NO | NO | NO | NO | YES | YES | YES |
City-fixed effect | NO | NO | NO | NO | YES | YES | YES |
Constant term (math.) | 9.545 *** (0.007) [9.531, 9.559] | 8.843 *** (0.007) [8.829, 8.857] | 6.256 *** (0.058) [6.142, 6.370] | 6.218 *** (0.057) [6.106, 6.330] | 6.243 *** (0.062) [6.121, 6.365] | 5.876 *** (0.060) [5.758, 5.994] | 5.597 *** (0.054) [5.491, 5.703] |
Adjusted R-squared | 0.018 | 0.013 | 0.165 | 0.135 | 0.172 | 0.135 | 0.163 |
Sample size | 351,665 | 336,678 | 315,033 | 302,317 | 315,033 | 302,317 | 348,952 |
Variable | (1) | (2) | (3) | (4) | (5) | (6) |
---|---|---|---|---|---|---|
−0.122 *** (0.027) [−0.175, −0.069] | 0.040 (0.028) [−0.015, 0.095] | −0.155 *** (0.028) [−0.209, −0.101] | −0.030 (0.029) [−0.086, 0.026] | −0.072 *** (0.029) [−0.129, −0.016] | −0.035 (0.030) [−0.094, 0.023] | |
Year of business squared | NO | NO | −5.31 × 10−5 *** (1.16 × 10−5) [−7.58 × 10−5, −3.04 × 10−5] | −2.83 × 10−5 *** (1.16 × 10−5) [−5.1 × 10−5, −5.64 × 10−6] | −3.39 × 10−5 *** (−1.14 × 10−5) [−5.63 × 10−5, −1.15 × 10−5] | −2.3 × 10−5 *** (1.15 × 10−5) [−4.56 × 10−5, −4.25 × 10−7] |
Total assets | NO | NO | 0.249 *** (0.005) [0.240, 0.259] | 0.235 *** (0.005) [0.226, 0.245] | 0.293 *** (0.005) [0.283, 0.303] | 0.244 *** (0.005) [0.234, 0.253] |
Proportion of fixed assets | NO | NO | 0.397 *** (0.021) [0.356, 0.437] | 0.457 *** (0.022) [0.413, 0.500] | 0.354 *** (0.021) [0.314, 0.394] | 0.454 *** (0.022) [0.411, 0.498] |
Debt ceiling | NO | NO | 0.125 *** (0.017) [0.093, 0.158] | 0.118 *** (0.017) [0.084, 0.151] | 0.123 *** (0.016) [0.092, 0.153] | 0.117 *** (0.017) [0.084, 0.150] |
Holdings | NO | NO | YES | YES | YES | YES |
Industry sector | NO | NO | YES | YES | YES | YES |
Year fixed effects | NO | NO | NO | NO | YES | YES |
City fixed effect | NO | NO | NO | NO | YES | YES |
Constant term (math.) | 9.579 *** (0.010) [9.559, 9.599] | 8.835 *** (0.010) [8.815, 8.855] | 6.176 *** (0.064) [6.050, 6.302] | 6.181 *** (0.062) [6.059, 6.303] | 5.854 *** (0.064) [5.728, 5.980] | 6.120 *** (0.063) [5.996, 6.244] |
Adjusted R-squared | 0.002 | 0.002 | 0.165 | 0.140 | 0.172 | 0.141 |
Sample size | 294,957 | 283,524 | 259,596 | 250,348 | 259,596 | 250,348 |
Variable | Publicly Held | Publicly Held | Foreign Holding | Foreign Holding | Privately Held | Privately Held |
---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | |
Did | −0.301 *** (0.048) [−0.395, −0.207] | −0.212 *** (0.045) [−0.301, −0.123] | −0.466 *** (0.084) [−0.631, −0.301] | −0.521 *** (0.073) [−0.663, −0.378] | −0.140 *** (0.029) [−0.198, −0.082] | −0.163 *** (0.029) [−0.220, −0.106] |
Year of business squared | −8.51 × 10−5 *** (1.48 × 10−5) [−1.14 × 10−4, −5.61 × 10−5] | −7.46 × 10−5 *** (1.49 × 10−5) [−1.038 × 10−4, −4.53 × 10−5] | 8.73 × 10−5 (9.47 × 10−5) [−9.83 × 10−5, 2.73 × 10−4] | 4.29 × 10−5 (1.075 × 10−4) [−1.679 × 10−4, 2.537 × 10−4] | −1.1 × 10−5 (2.01 × 10−5) [−5.04 × 10−5, 2.83 × 10−5] | −6.78 × 10−6 (2.14 × 10−5) [−4.87 × 10−5, 3.51 × 10−5] |
Total assets | 0.414 *** (0.010) [0.394, 0.434] | 0.356 *** (0.010) [0.338, 0.374] | 0.245 *** (0.017) [0.212, 0.278] | 0.284 *** (0.016) [0.252, 0.316] | 0.301 *** (0.006) [0.289, 0.313] | 0.258 *** (0.007) [0.245, 0.271] |
Proportion of fixed assets | 0.582 *** (0.046) [0.493, 0.673] | 0.656 *** (0.049) [0.560, 0.751] | 0.557 *** (0.067) [0.422, 0.692] | 0.688 *** (0.075) [0.541, 0.834] | 0.317 *** (0.029) [0.261, 0.373] | 0.449 *** (0.030) [0.390, 0.508] |
Debt ceiling | 0.064 *** (0.016) [0.033, 0.096] | 0.059 *** (0.017) [0.025, 0.093] | 0.247 *** (0.049) [0.151, 0.343] | 0.175 *** (0.053) [0.071, 0.279] | 3 × 10−5 (4.287 × 10−4) [−8.072 × 10−4, 8.732 × 10−4] | 0.207 *** (0.021) [0.165, 0.249] |
Holdings | YES | YES | YES | YES | YES | YES |
Industry sector | YES | YES | YES | YES | YES | YES |
Year-fixed effect | YES | YES | YES | YES | YES | YES |
City-fixed effect | YES | YES | YES | YES | YES | YES |
Adjusted R-squared | 0.297 | 0.256 | 0.098 | 0.100 | 0.115 | 0.083 |
Sample size | 68,952 | 66,030 | 23,451 | 23,227 | 120,299 | 118,165 |
Variable | Eastern Seaboard | National Average | ||
---|---|---|---|---|
(1) | (2) | (3) | (4) | |
Did | −0.286 *** (0.029) [−0.342, −0.230] | −0.077 *** (0.029) [−0.133, −0.021] | −0.119 *** (0.020) [−0.158, −0.080] | −0.051 *** (0.020) [−0.090, −0.013] |
Year of business squared | −2.55 × 10−5 (2.08 × 10−5) [−6.62 × 10−5, 1.52 × 10−5] | −1.55 × 10−5 (2.25 × 10−5) [−5.96 × 10−5, 2.86 × 10−5] | −3.88 × 10−5 *** (9.6 × 10−6) [−5.83 × 10−5, −1.93 × 10−5] | −3.46 × 10−5 *** (1.02 × 10−5) [−5.46 × 10−5, −1.45 × 10−5] |
Total assets | 0.274 *** (0.009) [0.257, 0.291] | 0.210 *** (0.009) [0.192, 0.227] | 0.298 *** (0.005) [0.289, 0.307] | 0.244 *** (0.005) [0.235, 0.253] |
Proportion of fixed assets | 0.350 *** (0.040) [0.271, 0.429] | 0.415 *** (0.044) [0.329, 0.500] | 0.315 *** (0.019) [0.278, 0.351] | 0.433 *** (0.021) [0.393, 0.474] |
Debt ceiling | 0.159 *** (0.028) [0.104, 0.214] | 0.113 *** (0.031) [0.053, 0.173] | 5.158 × 10−4 (8.796 × 10−4) [−1.2082 × 10−3, 2.2399 × 10−3] | 0.101 *** (0.014) [0.074, 0.127] |
Holdings | YES | YES | YES | YES |
Industry sector | YES | YES | YES | YES |
Year-fixed effect | YES | YES | YES | YES |
City-fixed effect | YES | YES | YES | YES |
Adjusted R-squared | 0.166 | 0.127 | 0.172 | 0.135 |
Sample size | 81,622 | 78,754 | 315,033 | 302,317 |
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Qian, J.; Han, X.; Ye, M.; Lv, Y.; Che, J. Environmental Benefits of the West-East Natural Gas Transmission Project: Cross-Regional Energy Optimization and Transformation for Sustainable Development. Energies 2024, 17, 3820. https://doi.org/10.3390/en17153820
Qian J, Han X, Ye M, Lv Y, Che J. Environmental Benefits of the West-East Natural Gas Transmission Project: Cross-Regional Energy Optimization and Transformation for Sustainable Development. Energies. 2024; 17(15):3820. https://doi.org/10.3390/en17153820
Chicago/Turabian StyleQian, Jiaorong, Xuze Han, Mao Ye, Yexin Lv, and Jing Che. 2024. "Environmental Benefits of the West-East Natural Gas Transmission Project: Cross-Regional Energy Optimization and Transformation for Sustainable Development" Energies 17, no. 15: 3820. https://doi.org/10.3390/en17153820