A Study on the Changes of Green Total Factor Productivity in Chinese Cities under Resource and Environmental Constraints
Abstract
:1. Introduction
2. Literature Review
3. Research Methodology, Selection of Indicators, and Data Sources
3.1. Research Methodology
3.1.1. Mixed Distance Function (Epsilon-Based Measure Model)
3.1.2. EBM–Window Model
3.1.3. EBM–Window–Malmquist–Luenberger Exponential Model
3.2. Selection of Indicators and Data Sources
3.2.1. Input Factor Indicators
3.2.2. Output Factor Indicators
4. Analysis of Green Total Factor Productivity Changes in Chinese Cities
4.1. Analysis of the Evolution of the Spatial and Temporal Patterns of Green Total Factor Productivity in Cities
4.2. Analysis of Green Total Factor Productivity Changes in Typical Cities
4.3. Analysis of Changes in City Size and Green Total Factor Productivity
4.4. Analysis of Changes in Urban Class and Green Total Factor Productivity
5. Conclusions and Recommendations
5.1. Conclusions
5.2. Recommendations
5.3. Research Limitations and Prospects
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Year | North–East | East | Central | West | Countrywide |
---|---|---|---|---|---|
2006–2007 | 73.53% | 63.95% | 53.75% | 63.86% | 62.19% |
2007–2008 | 88.24% | 77.91% | 70.00% | 67.47% | 73.85% |
2008–2009 | 44.12% | 58.14% | 61.25% | 60.24% | 57.95% |
2009–2010 | 70.59% | 55.81% | 38.75% | 40.96% | 48.41% |
2010–2011 | 29.41% | 54.65% | 53.75% | 66.27% | 54.77% |
2011–2012 | 52.94% | 67.44% | 66.25% | 74.70% | 67.49% |
2012–2013 | 58.82% | 52.33% | 46.25% | 31.33% | 45.23% |
2013–2014 | 29.41% | 73.26% | 68.75% | 67.47% | 65.02% |
2014–2015 | 76.47% | 81.40% | 77.50% | 73.49% | 77.39% |
2015–2016 | 79.41% | 84.88% | 82.50% | 78.31% | 81.63% |
2016–2017 | 76.47% | 90.70% | 82.50% | 73.49% | 81.63% |
2017–2018 | 97.06% | 75.58% | 65.00% | 72.29% | 74.20% |
2018–2019 | 41.18% | 61.63% | 73.75% | 56.63% | 61.13% |
2019–2020 | 97.06% | 95.35% | 92.50% | 80.72% | 90.46% |
Average Percentage | 60.97% | 69.68% | 64.93% | 63.01% | 65.98% |
Average number of GTFP > 1 cities | 21 | 60 | 52 | 52 | 187 |
Number of Sample cities | 34 | 86 | 80 | 83 | 283 |
Region | City Name | 2006– 2007 | 2009– 2010 | 2012– 2013 | 2015– 2016 | 2017– 2018 | 2019– 2020 | Geometric Mean | Standard Deviation | Minimum | Maximum |
---|---|---|---|---|---|---|---|---|---|---|---|
North–East | Huludao | 1.1397 | 1.1594 | 0.9318 | 1.2375 | 2.5572 | 1.0440 | 1.0395 | 0.4569 | 0.5340 | 2.5572 |
Suihua | 0.9342 | 1.2299 | 1.0223 | 1.4041 | 1.4318 | 1.0451 | 1.1834 | 0.4523 | 0.7384 | 2.6280 | |
Siping | 0.9980 | 0.9942 | 1.0374 | 0.9253 | 2.0536 | 1.1170 | 1.0249 | 0.3207 | 0.7320 | 2.0536 | |
Songyuan | 0.9325 | 1.8005 | 1.2169 | 1.1956 | 1.5830 | 1.0803 | 1.0468 | 0.3214 | 0.6128 | 1.8005 | |
Heihe | 1.1397 | 1.0133 | 1.2224 | 1.6091 | 1.3772 | 1.0887 | 1.0189 | 0.2984 | 0.5971 | 1.6091 | |
Shaungyashan | 1.0565 | 1.1676 | 0.9056 | 1.1212 | 1.7441 | 1.0551 | 1.0625 | 0.2391 | 0.7726 | 1.7441 | |
Jiamusi | 1.1337 | 1.0640 | 0.9535 | 1.2562 | 1.4639 | 1.1050 | 1.0117 | 0.2489 | 0.3345 | 1.4639 | |
Dalian | 1.1404 | 1.0162 | 1.0649 | 1.5723 | 1.1540 | 1.0978 | 1.0830 | 0.2401 | 0.7202 | 1.6207 | |
Tieling | 1.0124 | 0.9509 | 1.1914 | 1.1193 | 1.6481 | 0.8777 | 1.0447 | 0.2297 | 0.6015 | 1.6481 | |
Panjin | 0.9341 | 1.1129 | 1.0278 | 1.0358 | 0.8673 | 1.0517 | 1.0153 | 0.1402 | 0.8306 | 1.3669 | |
Geometric Mean | 1.0385 | 1.1320 | 1.0517 | 1.2302 | 1.5273 | 1.0541 | 1.0520 | 0.2796 | 0.6298 | 1.8078 | |
East | Yunfu | 0.9947 | 1.1075 | 0.7694 | 1.3748 | 1.3105 | 1.3881 | 1.0547 | 0.9852 | 0.2311 | 4.5365 |
Zhaoqing | 0.9143 | 1.2266 | 0.7819 | 0.8829 | 0.9564 | 1.2276 | 1.0515 | 0.6441 | 0.5155 | 3.2915 | |
Chaozhou | 0.7675 | 0.9190 | 2.9883 | 0.9725 | 1.0636 | 1.2281 | 1.1003 | 0.5386 | 0.7675 | 2.9883 | |
Shaoxing | 0.9633 | 1.0148 | 2.6947 | 1.0224 | 1.0567 | 1.1965 | 1.1206 | 0.4434 | 0.9633 | 2.6947 | |
Langfang | 1.1052 | 0.9890 | 1.0863 | 1.1482 | 2.4346 | 1.1300 | 1.1037 | 0.4037 | 0.7210 | 2.4346 | |
Xingtai | 1.0653 | 0.9433 | 1.0396 | 1.0698 | 1.1100 | 1.0369 | 1.0377 | 0.1309 | 0.8460 | 1.3963 | |
Hengshui | 0.9642 | 1.3598 | 1.0807 | 1.3198 | 1.0757 | 1.1645 | 1.1171 | 0.3407 | 0.8151 | 2.1963 | |
Weihai | 0.8957 | 0.7836 | 1.4884 | 1.0388 | 1.3479 | 1.1305 | 1.1196 | 0.2955 | 0.7836 | 1.9615 | |
Liaocheng | 1.0925 | 1.4581 | 1.6727 | 0.9858 | 1.2062 | 1.1577 | 1.1000 | 0.2756 | 0.5553 | 1.6727 | |
Jining | 1.0207 | 1.0285 | 1.3753 | 1.0170 | 1.2530 | 1.1209 | 1.0817 | 0.2439 | 0.7283 | 1.7764 | |
Geometric Mean | 0.9732 | 1.0656 | 1.3509 | 1.0738 | 1.2363 | 1.1749 | 1.0883 | 0.3745 | 0.6520 | 2.3543 | |
West | Weinan | 1.3620 | 0.6918 | 0.8497 | 1.0034 | 1.1448 | 1.1035 | 1.0517 | 0.1998 | 0.6918 | 1.4685 |
Baise | 0.9554 | 0.9076 | 0.8280 | 1.0705 | 1.0145 | 0.8664 | 1.0389 | 0.7149 | 0.3853 | 3.5121 | |
Ordos | 1.3230 | 0.8343 | 1.0767 | 1.3554 | 1.1927 | 1.0930 | 1.1454 | 0.5064 | 0.7428 | 2.8052 | |
Jinchang | 1.7152 | 0.9447 | 0.8891 | 0.9507 | 1.2230 | 0.9978 | 0.9943 | 0.2772 | 0.6127 | 1.7152 | |
Neijiang | 1.3421 | 1.3765 | 0.7052 | 0.9674 | 0.8642 | 1.0905 | 1.0247 | 0.1845 | 0.7052 | 1.3765 | |
Longnan | 0.9494 | 1.1013 | 0.7543 | 1.1093 | 2.1810 | 0.9153 | 1.0507 | 0.3434 | 0.7443 | 2.1810 | |
Shangluo | 0.7397 | 0.9263 | 0.8692 | 1.0197 | 1.1038 | 1.1126 | 1.0414 | 0.1563 | 0.7397 | 1.3217 | |
Lijiang | 0.8958 | 1.3724 | 0.9909 | 1.0345 | 0.9148 | 1.1579 | 1.0673 | 0.2349 | 0.5281 | 1.4026 | |
Guangan | 0.9080 | 0.9892 | 0.9362 | 1.0365 | 1.0414 | 1.0261 | 0.9814 | 0.1564 | 0.5529 | 1.2139 | |
Guyuan | 1.3032 | 0.9639 | 1.1916 | 1.1092 | 1.2936 | 0.8317 | 1.0661 | 0.1603 | 0.8317 | 1.3032 | |
Geometric Mean | 1.1143 | 0.9905 | 0.8988 | 1.0606 | 1.1582 | 1.0136 | 1.0453 | 0.2552 | 0.6395 | 1.7137 | |
Central | Shangrao | 0.9142 | 0.8924 | 0.2602 | 1.1411 | 1.0747 | 0.8917 | 1.0885 | 0.9715 | 0.2602 | 4.4204 |
Huanggang | 0.8541 | 1.1227 | 1.0279 | 1.0299 | 1.0471 | 1.0478 | 1.0107 | 0.1024 | 0.8541 | 1.2192 | |
Datong | 0.9364 | 1.9704 | 0.9384 | 0.9211 | 0.7377 | 1.1110 | 0.9877 | 0.3698 | 0.4206 | 1.9704 | |
Xuchang | 0.9867 | 0.9061 | 1.0308 | 2.2451 | 1.2105 | 1.1122 | 1.1155 | 0.3374 | 0.8569 | 2.2451 | |
Luan | 1.1232 | 1.0506 | 1.3185 | 1.6100 | 0.3180 | 0.9161 | 1.0317 | 0.3108 | 0.3180 | 1.6100 | |
Shuozhou | 1.0173 | 0.9099 | 0.7901 | 0.9901 | 1.3194 | 1.1486 | 1.0493 | 0.2956 | 0.7292 | 1.9367 | |
Pingxiang | 0.8789 | 0.6434 | 0.8159 | 1.1120 | 0.9900 | 1.0327 | 1.0379 | 0.2915 | 0.6434 | 1.9211 | |
Luohe | 1.0344 | 0.9882 | 0.9749 | 1.1184 | 1.0078 | 1.2049 | 1.0681 | 0.2190 | 0.9573 | 1.8097 | |
Yichang | 1.3735 | 0.7406 | 0.9865 | 1.0818 | 0.9677 | 1.0457 | 1.0538 | 0.2494 | 0.7394 | 1.7115 | |
Xuancheng | 0.7039 | 0.8531 | 1.0879 | 1.1942 | 0.9987 | 0.8575 | 0.9640 | 0.2476 | 0.5798 | 1.5616 | |
Geometric Mean | 0.9683 | 0.9632 | 0.8634 | 1.2006 | 0.9139 | 1.0309 | 1.0398 | 0.2919 | 0.5876 | 1.9228 |
City Scale | Criteria for Classification | Number of Cities | 2006–2007 | 2008–2009 | 2010–2011 | 2012–2013 | 2014–2015 | 2015–2016 | 2016–2017 | 2017–2028 | 2018–2019 | 2019–2020 | Geometric Mean |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Small City | <500 k | 73 | 0.9980 | 1.0659 | 1.0245 | 0.9369 | 1.0416 | 1.0934 | 1.0522 | 1.1376 | 1.0288 | 1.0600 | 1.0420 |
Medium-sized City | 500–1000 k | 109 | 1.0385 | 1.0094 | 1.0317 | 0.9857 | 1.0595 | 1.0964 | 1.1057 | 1.0922 | 1.0413 | 1.0872 | 1.0516 |
Type II Large City | 1000–3000 k | 66 | 1.0494 | 1.0062 | 1.0219 | 0.9948 | 1.0696 | 1.0891 | 1.1234 | 1.1389 | 1.0519 | 1.0788 | 1.0558 |
Type I Large City | 3000–5000 k | 14 | 1.0421 | 1.1315 | 1.0142 | 1.0099 | 1.0871 | 1.0816 | 1.1050 | 1.0517 | 1.0445 | 1.0597 | 1.0533 |
Super-large City | 5000–10,000 k | 14 | 1.0534 | 1.1067 | 1.0120 | 1.0456 | 1.0980 | 1.1605 | 1.1404 | 1.1107 | 1.0488 | 1.0918 | 1.0796 |
Super City | >10,000 k | 7 | 1.0615 | 1.1169 | 0.9984 | 1.0264 | 1.0693 | 1.0906 | 1.0798 | 1.0169 | 1.0410 | 1.1184 | 1.0745 |
Countrywide | 283 | 1.0403 | 1.0716 | 1.0171 | 0.9993 | 1.0707 | 1.1016 | 1.1007 | 1.0904 | 1.0427 | 1.0824 | 1.0594 |
City Classification | Number of Cities | 2006– 2007 | 2008– 2009 | 2010– 2011 | 2012– 2013 | 2014– 2015 | 2015– 2016 | 2016– 2017 | 2017– 2018 | 2018– 2019 | 2019– 2020 | Geometric Mean |
---|---|---|---|---|---|---|---|---|---|---|---|---|
First-tier City | 5 | 1.0938 | 1.0997 | 0.9777 | 1.0868 | 1.0365 | 1.0692 | 1.1077 | 1.0385 | 1.0287 | 1.1361 | 1.0685 |
Second-tier Developed City | 8 | 1.0554 | 1.0929 | 1.0252 | 1.0712 | 1.0821 | 1.1894 | 1.1351 | 1.0659 | 1.0896 | 1.0888 | 1.0777 |
Second-tier Moderately Developed City | 16 | 1.0420 | 1.1320 | 1.0369 | 0.9931 | 1.1046 | 1.1288 | 1.1287 | 1.1426 | 1.0211 | 1.0878 | 1.0761 |
Second-tier Less Developed City | 7 | 1.0374 | 1.0225 | 0.9187 | 1.0172 | 1.1048 | 1.0928 | 1.0445 | 1.0400 | 1.0075 | 1.0670 | 1.0445 |
Third-tier City | 57 | 1.0639 | 1.0842 | 1.0376 | 1.0304 | 1.0520 | 1.1052 | 1.1232 | 1.1510 | 1.0277 | 1.0858 | 1.0650 |
Fourth-tier City | 105 | 1.0199 | 1.0053 | 1.0061 | 0.9599 | 1.0718 | 1.0867 | 1.0999 | 1.0921 | 1.0850 | 1.0799 | 1.0492 |
Fifth-tier City | 85 | 1.0176 | 1.0181 | 1.0499 | 0.9528 | 1.0406 | 1.0891 | 1.0697 | 1.1185 | 1.0006 | 1.0644 | 1.0399 |
Countrywide | 283 | 1.0306 | 1.0351 | 1.0257 | 0.9784 | 1.0615 | 1.0956 | 1.0950 | 1.1124 | 1.0416 | 1.0767 | 1.0518 |
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Fu, L.; Zhang, S.; Guo, S. A Study on the Changes of Green Total Factor Productivity in Chinese Cities under Resource and Environmental Constraints. Sustainability 2024, 16, 1658. https://doi.org/10.3390/su16041658
Fu L, Zhang S, Guo S. A Study on the Changes of Green Total Factor Productivity in Chinese Cities under Resource and Environmental Constraints. Sustainability. 2024; 16(4):1658. https://doi.org/10.3390/su16041658
Chicago/Turabian StyleFu, Lei, Siyuan Zhang, and Sidai Guo. 2024. "A Study on the Changes of Green Total Factor Productivity in Chinese Cities under Resource and Environmental Constraints" Sustainability 16, no. 4: 1658. https://doi.org/10.3390/su16041658