Study on the Environmental Efficiency of the Chinese Cement Industry Based on the Undesirable Output DEA Model
Abstract
:1. Introduction
2. Literature Review
3. Methods and Data
3.1. DDF Model
3.2. Environmental Regulation Cost and Regulation Efficiency Loss
3.3. Variables’ Description and Data Source
4. Results and Discussion
4.1. Calculation Results and Analysis of Environmental Efficiency
4.2. Analysis of Compliance Cost and Regulation Efficiency Loss
4.3. Regional Environmental Efficiency Analysis
5. Conclusions and Policy Implication
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variables | Description of Data Source | |
---|---|---|
Input | Fixed assets investment completed (x1) | The statistical scope of fixed assets investment is construction projects with a total planned investment of more than CNY 500,000, and the basic data are from the China Cement Yearbook over the years. |
Employees (x2) | The number of employees of all industrial caliber are selected, and the statistical scope is enterprises above a designated size. The basic data come from the statistical data of the cement manufacturing industry in the China Cement Yearbook, China Statistical Yearbook, and China Labor Statistical Yearbook. | |
Energy consumption (x3) | Equivalent to 10,000 tons of standard coal. The basic data come from the statistical data of the cement manufacturing industry in the China Cement Yearbook, China Statistical Yearbook, and China Energy Statistical Yearbook. | |
Desirable output | Industrial Value added (y) | According to statistics, the annual sales revenue of state-owned enterprises above CNY 5 million is the total sales revenue of state-owned enterprises. The basic data come from the China Cement Yearbook. |
Undesirable output | Dust(smoke) emission (b1) | Dust (smoke) and SO2 are the main pollution sources of the cement manufacturing industry. The basic data come from the statistical data of the cement manufacturing industry in the China Cement Yearbook, China Statistical Yearbook, and China Environmental Yearbook. |
SO2 emission (b2) |
Input | Desirable Output | Undesirable Output | |||||
---|---|---|---|---|---|---|---|
x1 (CNY 100 Million) | x2 (10,000 People) | x3 (0.01 Mtec) | y (CNY 100 Million) | b1 (10,000 ton) | b2 (10,000 ton) | ||
Nation wide | Mean | 25.59 | 4.28 | 420.29 | 43.57 | 17.93 | 3.48 |
Std. Dev. | 29.60 | 3.02 | 341.04 | 45.98 | 13.64 | 2.44 | |
Maximum | 227.45 | 16.25 | 1692.27 | 210.58 | 78.49 | 11.78 | |
Minimum | 0.00 | 0.23 | 17.17 | 0.83 | 0.02 | 0.02 | |
N | 390 | 390 | 390 | 390 | 390 | 390 | |
Eastern | Mean | 19.78 | 4.68 | 481.05 | 52.58 | 13.93 | 3.51 |
Std. Dev | 24.98 | 4.11 | 422.58 | 55.12 | 12.24 | 2.76 | |
Maximum | 138.86 | 16.25 | 1692.27 | 210.58 | 59.51 | 11.31 | |
Minimum | 0.00 | 0.23 | 17.17 | 1.80 | 0.02 | 0.02 | |
N | 143 | 143 | 143 | 143 | 143 | 143 | |
Central | Mean | 32.60 | 4.89 | 481.52 | 48.34 | 25.75 | 3.48 |
Std. Dev. | 29.12 | 1.97 | 291.24 | 42.02 | 15.37 | 1.98 | |
Maximum | 117.29 | 11.87 | 1512.50 | 185.50 | 78.49 | 8.95 | |
Minimum | 0.93 | 1.93 | 125.63 | 5.09 | 4.72 | 0.67 | |
N | 104 | 104 | 104 | 104 | 104 | 104 | |
Western | Mean | 26.30 | 3.44 | 315.00 | 31.58 | 16.25 | 3.46 |
Std. Dev | 33.03 | 2.04 | 246.78 | 35.09 | 11.17 | 2.41 | |
Maximum | 227.45 | 9.48 | 1259.48 | 180.89 | 54.71 | 11.78 | |
Minimum | 0.37 | 0.58 | 28.00 | 0.83 | 0.79 | 0.13 | |
N | 143 | 143 | 143 | 143 | 143 | 143 |
Year | Planning (3) | Planning (4) | REL | ERC | ||
---|---|---|---|---|---|---|
γS | 1/(1 + γS) | βW | 1/(1 + βW) | |||
2004 | 0.4410 | 0.6940 | 0.1623 | 0.8604 | 0.2787 | 52.762 |
2005 | 0.4481 | 0.6906 | 0.1766 | 0.8499 | 0.2715 | 60.035 |
2006 | 0.3719 | 0.7289 | 0.1699 | 0.8548 | 0.2020 | 66.815 |
2007 | 0.5865 | 0.6303 | 0.2095 | 0.8268 | 0.3770 | 133.041 |
2008 | 0.7328 | 0.5771 | 0.2365 | 0.8087 | 0.4963 | 179.648 |
2009 | 0.4538 | 0.6879 | 0.2064 | 0.8289 | 0.2473 | 87.564 |
2010 | 0.2205 | 0.8193 | 0.1341 | 0.8818 | 0.0864 | 63.423 |
2011 | 0.4658 | 0.6822 | 0.1274 | 0.8870 | 0.3384 | 199.291 |
2012 | 0.4289 | 0.6999 | 0.2080 | 0.8278 | 0.2209 | 240.551 |
2013 | 0.5325 | 0.6525 | 0.1568 | 0.8644 | 0.3756 | 421.976 |
2014 | 0.4421 | 0.6934 | 0.0836 | 0.9229 | 0.3586 | 621.496 |
2015 | 0.3127 | 0.7618 | 0.1076 | 0.9028 | 0.2051 | 386.268 |
2016 | 0.3645 | 0.7328 | 0.1113 | 0.8999 | 0.2533 | 530.999 |
Mean | 0.4462 | 0.6962 | 0.1608 | 0.8628 | 0.2854 | 234.144 |
Region | Province | 2004 | 2006 | 2008 | 2010 | 2012 | 2014 | 2016 | Mean |
---|---|---|---|---|---|---|---|---|---|
Eastern | Beijing | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.1974 | 0.5511 | 0.0943 |
Tianjin | 0.5453 | 0.1487 | 1.0302 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.3378 | |
Hebei | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0700 | 0.0000 | 0.0000 | 0.0054 | |
Liaoning | 0.4133 | 0.6028 | 0.7779 | 0.4142 | 0.7003 | 0.6107 | 0.8039 | 0.6121 | |
Shanghai | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | |
Jiangsu | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | |
Zhejiang | 0.0615 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0095 | |
Fujian | 0.2911 | 0.2191 | 0.5832 | 0.4911 | 0.7504 | 0.1817 | 0.0000 | 0.3308 | |
Shandong | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | |
Guangdong | 0.0000 | 0.0000 | 0.2923 | 0.4514 | 0.2934 | 0.3634 | 0.4717 | 0.2052 | |
Hainan | 0.0000 | 0.0000 | 1.8510 | 0.0000 | 0.9591 | 0.0000 | 0.0000 | 0.4325 | |
Central | Shanxi | 0.0000 | 0.5955 | 0.5216 | 0.9693 | 1.4939 | 0.0000 | 0.0000 | 0.6935 |
Jilin | 0.9351 | 1.1150 | 1.1018 | 0.0000 | 0.0273 | 1.5529 | 1.9399 | 0.7972 | |
Heilongjiang | 1.1022 | 0.8686 | 1.3360 | 0.0000 | 0.7630 | 0.3246 | 0.2756 | 0.7564 | |
Anhui | 0.6676 | 1.0920 | 0.7245 | 0.0000 | 0.0000 | 0.2397 | 0.0566 | 0.3626 | |
Jiangxi | 1.0160 | 0.7895 | 0.6038 | 0.0000 | 0.0000 | 0.8019 | 0.3906 | 0.4740 | |
Henan | 0.0755 | 0.1098 | 0.4237 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0871 | |
Hubei | 0.3668 | 0.3784 | 0.6155 | 0.0646 | 0.0771 | 0.4199 | 0.2992 | 0.3212 | |
Hunan | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.9362 | 0.6216 | 0.5986 | 0.3358 | |
Western | Sichuan | 0.3772 | 0.3668 | 0.7096 | 0.2102 | 0.3240 | 0.1833 | 0.2552 | 0.3190 |
Chongqing | 0.3173 | 0.0000 | 0.7911 | 0.0000 | 0.0000 | 0.9168 | 0.9029 | 0.6018 | |
Guizhou | 0.9783 | 0.2435 | 0.8688 | 0.7834 | 1.5726 | 0.5647 | 0.4343 | 0.8187 | |
Yunnan | 0.4409 | 0.6247 | 0.8185 | 0.5084 | 1.5762 | 0.8759 | 0.4099 | 0.8272 | |
Shaanxi | 0.8927 | 0.9209 | 0.8290 | 0.1247 | 0.7966 | 0.6233 | 0.3187 | 0.6158 | |
Gansu | 0.7090 | 0.5099 | 0.8494 | 0.0000 | 0.5000 | 0.6687 | 0.6390 | 0.5144 | |
Qinghai | 1.8562 | 0.0000 | 2.2811 | 1.3782 | 0.0000 | 1.1827 | 0.5997 | 1.2624 | |
Ningxia | 0.8197 | 0.7416 | 1.6839 | 1.2191 | 0.3960 | 0.7419 | 0.8500 | 0.9229 | |
Xinjiang | 0.8296 | 0.8505 | 1.4107 | 0.0000 | 0.7842 | 1.4159 | 0.8549 | 0.9112 | |
Guangxi | 0.0000 | 0.3751 | 0.8699 | 0.0000 | 0.8456 | 0.7770 | 0.2845 | 0.4141 | |
Inner Mongolia | 0.5348 | 0.6051 | 1.0120 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.3244 | |
National average | 0.4410 | 0.3719 | 0.7328 | 0.2205 | 0.4289 | 0.4421 | 0.3645 | 0.4462 | |
Eastern average | 0.1192 | 0.0882 | 0.4122 | 0.1233 | 0.2521 | 0.1230 | 0.1661 | 0.1843 | |
Central average | 0.5204 | 0.6186 | 0.6659 | 0.1292 | 0.4122 | 0.4951 | 0.4451 | 0.4785 | |
Western average | 0.7501 | 0.4762 | 1.1022 | 0.3840 | 0.6177 | 0.7228 | 0.5045 | 0.6847 |
Region | Province | 2004 | 2006 | 2008 | 2010 | 2012 | 2014 | 2016 | Mean |
---|---|---|---|---|---|---|---|---|---|
Eastern | Beijing | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 |
Tianjin | 0.0000 | 0.1028 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0722 | |
Hebei | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | |
Liaoning | 0.3913 | 0.3798 | 0.4784 | 0.3683 | 0.3659 | 0.4477 | 0.5092 | 0.4114 | |
Shanghai | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | |
Jiangsu | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | |
Zhejiang | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | |
Fujian | 0.0000 | 0.0000 | 0.1052 | 0.4182 | 0.5586 | 0.0551 | 0.0000 | 0.1492 | |
Shandong | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | |
Guangdong | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.1078 | 0.0083 | |
Hainan | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.8036 | 0.0000 | 0.0000 | 0.1317 | |
Central | Shanxi | 0.0000 | 0.5151 | 0.4435 | 0.6191 | 0.5124 | 0.0000 | 0.0000 | 0.4111 |
Jilin | 0.3854 | 0.3787 | 0.2745 | 0.0000 | 0.0000 | 0.0000 | 0.5061 | 0.1840 | |
Heilongjiang | 0.3439 | 0.3816 | 0.4869 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.2051 | |
Anhui | 0.0000 | 0.1232 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0156 | |
Jiangxi | 0.0000 | 0.0000 | 0.0909 | 0.0000 | 0.0000 | 0.1147 | 0.1659 | 0.0683 | |
Henan | 0.0629 | 0.0649 | 0.2947 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0498 | |
Hubei | 0.1684 | 0.1098 | 0.2430 | 0.0646 | 0.0000 | 0.0000 | 0.0520 | 0.1137 | |
Hunan | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.7099 | 0.0000 | 0.0709 | 0.0706 | |
Western | Sichuan | 0.2971 | 0.2833 | 0.4682 | 0.0000 | 0.0000 | 0.0225 | 0.0000 | 0.1392 |
Chongqing | 0.3169 | 0.0000 | 0.4321 | 0.0000 | 0.0000 | 0.0817 | 0.0816 | 0.1483 | |
Guizhou | 0.6769 | 0.2301 | 0.4859 | 0.5911 | 0.7329 | 0.0000 | 0.0000 | 0.3852 | |
Yunnan | 0.1716 | 0.2120 | 0.3196 | 0.2478 | 0.4934 | 0.0891 | 0.2157 | 0.2824 | |
Shaanxi | 0.5652 | 0.5289 | 0.4156 | 0.1247 | 0.4881 | 0.3440 | 0.2684 | 0.3813 | |
Gansu | 0.4439 | 0.3530 | 0.4018 | 0.0000 | 0.0000 | 0.4780 | 0.2934 | 0.2651 | |
Qinghai | 0.0000 | 0.0000 | 0.0000 | 0.8248 | 0.0000 | 0.0000 | 0.0000 | 0.0634 | |
Ningxia | 0.4053 | 0.3859 | 0.5673 | 0.7638 | 0.3199 | 0.0000 | 0.5877 | 0.4495 | |
Xinjiang | 0.2184 | 0.3028 | 0.4825 | 0.0000 | 0.6044 | 0.5889 | 0.4768 | 0.3829 | |
Guangxi | 0.0000 | 0.2492 | 0.4343 | 0.0000 | 0.6505 | 0.2854 | 0.0027 | 0.2114 | |
Inner Mongolia | 0.4219 | 0.4949 | 0.6716 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.2236 | |
National average | 0.1623 | 0.1699 | 0.2365 | 0.1341 | 0.2080 | 0.0836 | 0.1113 | 0.1608 | |
Eastern average | 0.0356 | 0.0439 | 0.0530 | 0.0715 | 0.1571 | 0.0457 | 0.0561 | 0.0703 | |
Central average | 0.1201 | 0.1967 | 0.2292 | 0.0855 | 0.1528 | 0.0143 | 0.0994 | 0.1398 | |
Western average | 0.3197 | 0.2764 | 0.4254 | 0.2320 | 0.2990 | 0.1718 | 0.1751 | 0.2666 |
Region | Province | γS | βW | REL | ERC |
---|---|---|---|---|---|
Eastern | Beijing | 0.0943 | 0.0000 | 0.0943 | 13.310 |
Tianjin | 0.3378 | 0.0722 | 0.2656 | 11.474 | |
Hebei | 0.0054 | 0.0000 | 0.0054 | 7.164 | |
Liaoning | 0.6121 | 0.4114 | 0.2007 | 89.822 | |
Shanghai | 0.0000 | 0.0000 | 0.0000 | 0.000 | |
Jiangsu | 0.0000 | 0.0000 | 0.0000 | 0.000 | |
Zhejiang | 0.0095 | 0.0000 | 0.0095 | 3.716 | |
Fujian | 0.3308 | 0.1492 | 0.1816 | 65.307 | |
Shandong | 0.0000 | 0.0000 | 0.0000 | 0.000 | |
Guangdong | 0.2052 | 0.0083 | 0.1969 | 262.429 | |
Hainan | 0.4325 | 0.1317 | 0.3008 | 16.489 | |
Central | Shanxi | 0.6935 | 0.4111 | 0.2824 | 56.617 |
Jilin | 0.7972 | 0.1840 | 0.6132 | 205.273 | |
Heilongjiang | 0.7564 | 0.2051 | 0.5513 | 114.147 | |
Anhui | 0.3626 | 0.0156 | 0.3470 | 137.903 | |
Jiangxi | 0.4740 | 0.0683 | 0.4057 | 169.598 | |
Henan | 0.0871 | 0.0498 | 0.0373 | 19.070 | |
Hubei | 0.3212 | 0.1137 | 0.2075 | 167.146 | |
Hunan | 0.3358 | 0.0706 | 0.2652 | 306.983 | |
Western | Sichuan | 0.3190 | 0.1392 | 0.1798 | 184.521 |
Chongqing | 0.6018 | 0.1483 | 0.4535 | 234.952 | |
Guizhou | 0.8187 | 0.3852 | 0.4335 | 151.778 | |
Yunnan | 0.8272 | 0.2824 | 0.5448 | 252.294 | |
Shaanxi | 0.6158 | 0.3813 | 0.2345 | 88.807 | |
Gansu | 0.5144 | 0.2651 | 0.2493 | 69.839 | |
Qinghai | 1.2624 | 0.0634 | 1.1990 | 69.530 | |
Ningxia | 0.9229 | 0.4495 | 0.4734 | 45.522 | |
Xinjiang | 0.9112 | 0.3829 | 0.5283 | 120.971 | |
Guangxi | 0.4141 | 0.2114 | 0.2027 | 170.304 | |
Inner Mongolia | 0.3244 | 0.2236 | 0.1008 | 8.901 | |
National average | 0.4462 | 0.1608 | 0.2854 | 101.462 | |
Eastern average | 0.1843 | 0.0703 | 0.1140 | 42.701 | |
Central average | 0.4785 | 0.1398 | 0.3387 | 147.092 | |
Western average | 0.6847 | 0.2666 | 0.4181 | 127.038 |
Model | Test Method | Region | Mean Environmental Inefficiency | Regional Comparison | p |
---|---|---|---|---|---|
Planning (3) | Mann–Whitney U | Eastern | 0.1843 | East and Central | 0.0208 ** |
Mann–Whitney U | Central | 0.4785 | Central and Western | 0.1372 | |
Mann–Whitney U | Western | 0.6845 | West and East | 0.0014 *** | |
Kruskal–Wallis H | Nationwide | 0.4462 | East, Central, and West | 0.0022 *** | |
Planning (4) | Mann–Whitney U | Eastern | 0.0703 | East and Central | 0.0631 * |
Mann–Whitney U | Central | 0.1398 | Central and Western | 0.0390 ** | |
Mann–Whitney U | Western | 0.2666 | West and East | 0.0028 *** | |
Kruskal–Wallis H | Nationwide | 0.1608 | East, Central, and West | 0.0036 *** |
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Tu, H.; Dai, W.; Xiao, X. Study on the Environmental Efficiency of the Chinese Cement Industry Based on the Undesirable Output DEA Model. Energies 2022, 15, 3396. https://doi.org/10.3390/en15093396
Tu H, Dai W, Xiao X. Study on the Environmental Efficiency of the Chinese Cement Industry Based on the Undesirable Output DEA Model. Energies. 2022; 15(9):3396. https://doi.org/10.3390/en15093396
Chicago/Turabian StyleTu, Hongxing, Wei Dai, and Xu Xiao. 2022. "Study on the Environmental Efficiency of the Chinese Cement Industry Based on the Undesirable Output DEA Model" Energies 15, no. 9: 3396. https://doi.org/10.3390/en15093396