Journal of Resources and Ecology ›› 2021, Vol. 12 ›› Issue (2): 155-164.DOI: 10.5814/j.issn.1674-764x.2021.02.003
• Land Use Efficiency • Previous Articles Next Articles
LI Qiuying1, LIANG Longwu2,3, WANG Zhenbo2,3,*()
Received:
2020-09-01
Accepted:
2020-11-25
Online:
2021-03-30
Published:
2021-05-30
Contact:
WANG Zhenbo
Supported by:
LI Qiuying, LIANG Longwu, WANG Zhenbo. Spatiotemporal Differentiation and the Factors Influencing Eco-efficiency in China[J]. Journal of Resources and Ecology, 2021, 12(2): 155-164.
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URL: http://www.jorae.cn/EN/10.5814/j.issn.1674-764x.2021.02.003
Category | Variable | Units | Mean | Std. dev | Min | Max |
---|---|---|---|---|---|---|
Inputs | Capital (I1) | 108 yuan | 12061.37 | 10861.52 | 323.68 | 54758.30 |
Labor force (I2) | 104 persons | 497.01 | 343.72 | 40.92 | 1973.30 | |
Land resource (I5) | km2 | 1458.72 | 1031.98 | 105.92 | 5266.60 | |
Water super (I3) | 108 t | 201.26 | 150.30 | 22.33 | 1220.00 | |
Energy resource (I4) | 104 t of SCEa | 12943.66 | 8140.66 | 822.00 | 38899.00 | |
Undesirable Outputs | Total waste water (UO1) | 104 t | 169264.71 | 165867.70 | 3396.00 | 938261.00 |
Industrial SO2 emission (UO2) | 104 t | 58.76 | 41.24 | 2.00 | 182.74 | |
Industrial soot emission (UO3) | 104 t | 35.95 | 29.11 | 0.76 | 179.77 | |
Industrial solid wastes emission (UO4) | 104 t | 8621.19 | 7972.33 | 127.00 | 45575.83 | |
Desirable output | GDP (DO1) | 108 yuan | 16900.45 | 15341.25 | 543.32 | 80854.91 |
Table 1 Descriptive statistics for the input and output indicators between 2005 and 2016
Category | Variable | Units | Mean | Std. dev | Min | Max |
---|---|---|---|---|---|---|
Inputs | Capital (I1) | 108 yuan | 12061.37 | 10861.52 | 323.68 | 54758.30 |
Labor force (I2) | 104 persons | 497.01 | 343.72 | 40.92 | 1973.30 | |
Land resource (I5) | km2 | 1458.72 | 1031.98 | 105.92 | 5266.60 | |
Water super (I3) | 108 t | 201.26 | 150.30 | 22.33 | 1220.00 | |
Energy resource (I4) | 104 t of SCEa | 12943.66 | 8140.66 | 822.00 | 38899.00 | |
Undesirable Outputs | Total waste water (UO1) | 104 t | 169264.71 | 165867.70 | 3396.00 | 938261.00 |
Industrial SO2 emission (UO2) | 104 t | 58.76 | 41.24 | 2.00 | 182.74 | |
Industrial soot emission (UO3) | 104 t | 35.95 | 29.11 | 0.76 | 179.77 | |
Industrial solid wastes emission (UO4) | 104 t | 8621.19 | 7972.33 | 127.00 | 45575.83 | |
Desirable output | GDP (DO1) | 108 yuan | 16900.45 | 15341.25 | 543.32 | 80854.91 |
Factor | Indicator | Abbreviation | Unit |
---|---|---|---|
Economic development | Per capita GDP | ED | 104 yuan |
Industrial structure | Secondary industry as a proportion of GDP | IS | % |
Openness | FDI as a proportion of GDP | OP | % |
Urbanization | Proportion of urban population | UR | % |
Technical innovation | Expenditure for R&D as a proportion of GDP | TI | % |
Governance capacity of the environment | Expenditure for environmental protection as a proportion of GDP | EG | % |
CO2 emission intensity | Carbon dioxide emission intensity | EC | t (104 yuan)‒1 |
Traffic conditions | Civil vehicle possession | TR | vehicle |
Table 2 Influencing factor indicators
Factor | Indicator | Abbreviation | Unit |
---|---|---|---|
Economic development | Per capita GDP | ED | 104 yuan |
Industrial structure | Secondary industry as a proportion of GDP | IS | % |
Openness | FDI as a proportion of GDP | OP | % |
Urbanization | Proportion of urban population | UR | % |
Technical innovation | Expenditure for R&D as a proportion of GDP | TI | % |
Governance capacity of the environment | Expenditure for environmental protection as a proportion of GDP | EG | % |
CO2 emission intensity | Carbon dioxide emission intensity | EC | t (104 yuan)‒1 |
Traffic conditions | Civil vehicle possession | TR | vehicle |
Province | 2005‒2016 | 2005‒2010 | 2011‒2016 | Province | 2005‒2016 | 2005‒2010 | 2011‒2016 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Rank | Score | Rank | Score | Rank | Score | Rank | Score | Rank | Score | Rank | Score | |||||
Tianjin | 1 | 1.045 | 2 | 1.028 | 1 | 1.062 | Guangxi | 16 | 0.513 | 15 | 0.441 | 20 | 0.584 | |||
Qinghai | 2 | 1.037 | 1 | 1.089 | 3 | 0.985 | Hubei | 17 | 0.502 | 19 | 0.407 | 17 | 0.597 | |||
Hainan | 3 | 0.974 | 3 | 0.971 | 5 | 0.976 | Liaoning | 18 | 0.501 | 24 | 0.387 | 15 | 0.614 | |||
Shanghai | 4 | 0.921 | 5 | 0.864 | 4 | 0.978 | Jiangxi | 19 | 0.500 | 17 | 0.422 | 21 | 0.579 | |||
Beijing | 5 | 0.918 | 4 | 0.893 | 6 | 0.943 | Sichuan | 20 | 0.495 | 20 | 0.406 | 19 | 0.584 | |||
Guangdong | 6 | 0.839 | 6 | 0.686 | 2 | 0.991 | Ningxia | 21 | 0.486 | 26 | 0.377 | 18 | 0.595 | |||
Jiangsu | 7 | 0.745 | 7 | 0.590 | 7 | 0.901 | Jilin | 22 | 0.486 | 22 | 0.393 | 22 | 0.578 | |||
Shandong | 8 | 0.716 | 8 | 0.551 | 8 | 0.881 | Chongqing | 23 | 0.477 | 25 | 0.387 | 23 | 0.567 | |||
Zhejiang | 9 | 0.686 | 10 | 0.543 | 9 | 0.830 | Anhui | 24 | 0.473 | 21 | 0.393 | 24 | 0.553 | |||
Fujian | 10 | 0.645 | 9 | 0.546 | 10 | 0.743 | Shanxi | 25 | 0.462 | 16 | 0.441 | 27 | 0.483 | |||
Hunan | 11 | 0.581 | 14 | 0.444 | 11 | 0.718 | Yunnan | 26 | 0.460 | 23 | 0.389 | 25 | 0.531 | |||
Hebei | 12 | 0.575 | 11 | 0.478 | 12 | 0.672 | Guizhou | 27 | 0.426 | 29 | 0.352 | 26 | 0.500 | |||
Henan | 13 | 0.544 | 12 | 0.452 | 13 | 0.635 | Heilongjiang | 28 | 0.421 | 27 | 0.375 | 28 | 0.466 | |||
Shaanxi | 14 | 0.530 | 13 | 0.448 | 16 | 0.611 | Gansu | 29 | 0.385 | 28 | 0.361 | 29 | 0.409 | |||
Inner Mongolia | 15 | 0.515 | 18 | 0.412 | 14 | 0.618 | Xinjiang | 30 | 0.339 | 30 | 0.313 | 30 | 0.364 |
Table 3 Annual average scores for eco-efficiency and provincial rankings between 2005 and 2016, 2005 and 2010, and 2011 and 2016
Province | 2005‒2016 | 2005‒2010 | 2011‒2016 | Province | 2005‒2016 | 2005‒2010 | 2011‒2016 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Rank | Score | Rank | Score | Rank | Score | Rank | Score | Rank | Score | Rank | Score | |||||
Tianjin | 1 | 1.045 | 2 | 1.028 | 1 | 1.062 | Guangxi | 16 | 0.513 | 15 | 0.441 | 20 | 0.584 | |||
Qinghai | 2 | 1.037 | 1 | 1.089 | 3 | 0.985 | Hubei | 17 | 0.502 | 19 | 0.407 | 17 | 0.597 | |||
Hainan | 3 | 0.974 | 3 | 0.971 | 5 | 0.976 | Liaoning | 18 | 0.501 | 24 | 0.387 | 15 | 0.614 | |||
Shanghai | 4 | 0.921 | 5 | 0.864 | 4 | 0.978 | Jiangxi | 19 | 0.500 | 17 | 0.422 | 21 | 0.579 | |||
Beijing | 5 | 0.918 | 4 | 0.893 | 6 | 0.943 | Sichuan | 20 | 0.495 | 20 | 0.406 | 19 | 0.584 | |||
Guangdong | 6 | 0.839 | 6 | 0.686 | 2 | 0.991 | Ningxia | 21 | 0.486 | 26 | 0.377 | 18 | 0.595 | |||
Jiangsu | 7 | 0.745 | 7 | 0.590 | 7 | 0.901 | Jilin | 22 | 0.486 | 22 | 0.393 | 22 | 0.578 | |||
Shandong | 8 | 0.716 | 8 | 0.551 | 8 | 0.881 | Chongqing | 23 | 0.477 | 25 | 0.387 | 23 | 0.567 | |||
Zhejiang | 9 | 0.686 | 10 | 0.543 | 9 | 0.830 | Anhui | 24 | 0.473 | 21 | 0.393 | 24 | 0.553 | |||
Fujian | 10 | 0.645 | 9 | 0.546 | 10 | 0.743 | Shanxi | 25 | 0.462 | 16 | 0.441 | 27 | 0.483 | |||
Hunan | 11 | 0.581 | 14 | 0.444 | 11 | 0.718 | Yunnan | 26 | 0.460 | 23 | 0.389 | 25 | 0.531 | |||
Hebei | 12 | 0.575 | 11 | 0.478 | 12 | 0.672 | Guizhou | 27 | 0.426 | 29 | 0.352 | 26 | 0.500 | |||
Henan | 13 | 0.544 | 12 | 0.452 | 13 | 0.635 | Heilongjiang | 28 | 0.421 | 27 | 0.375 | 28 | 0.466 | |||
Shaanxi | 14 | 0.530 | 13 | 0.448 | 16 | 0.611 | Gansu | 29 | 0.385 | 28 | 0.361 | 29 | 0.409 | |||
Inner Mongolia | 15 | 0.515 | 18 | 0.412 | 14 | 0.618 | Xinjiang | 30 | 0.339 | 30 | 0.313 | 30 | 0.364 |
Group | First | Second | Third | Fourth | Fifth | Sixth |
---|---|---|---|---|---|---|
Scores | > 1.00 | 0.80‒1.00 | 0.60‒0.80 | 0.50‒0.60 | 0.40‒0.50 | < 0.4 |
Number of provinces | 2 | 4 | 4 | 9 | 9 | 2 |
Proportion (%) | 6.67 | 13.33 | 13.33 | 30.00 | 30.00 | 6.67 |
Table 4 Provincial eco-efficiency value distribution across China
Group | First | Second | Third | Fourth | Fifth | Sixth |
---|---|---|---|---|---|---|
Scores | > 1.00 | 0.80‒1.00 | 0.60‒0.80 | 0.50‒0.60 | 0.40‒0.50 | < 0.4 |
Number of provinces | 2 | 4 | 4 | 9 | 9 | 2 |
Proportion (%) | 6.67 | 13.33 | 13.33 | 30.00 | 30.00 | 6.67 |
Fig. 4 Eco-efficiency volatility ratio values for the 30 Chinese provinces between 2005 and 2016 Notes: Hong Kong, Macao, Taiwan and Tibet were excluded due to limited data availability.
Factor | China | East | Central | West | Northeast |
---|---|---|---|---|---|
ED | 0.452 (8.30) | ‒0.058 (‒0.43) | 0.131*** (1.04) | 0.471** (3.95) | ‒0.465 (‒3.77) |
IS | 0.132*** (‒1.50) | ‒1.009 (‒3.19) | 0.949** (4.50) | 0.821*** (2.73) | ‒0.590** (‒2.67) |
OP | 0.130*** (‒0.43) | 0.030*** (0.88) | ‒0.096 (‒2.67) | 0.190 (5.71) | ‒0.104*** (‒3.56) |
UR | 0.545** (‒4.33) | 1.400** (4.01) | ‒0.309** (‒0.99) | ‒1.035*** (‒3.59) | 0.881 (‒1.66) |
TI | 0.041** (‒0.38) | 0.014* (‒0.38) | 0.027* (‒1.77) | 0.105** (‒3.49) | ‒0.036 (‒1.61) |
EG | 0.056** (2.59) | 0.029 (0.52) | 0.014*** (‒0.79) | 0.077** (‒1.53) | 0.074*** (‒1.31) |
EC | ‒0.048*** (‒2.89) | ‒0.237*** (‒2.21) | ‒0.184*** (‒5.20) | ‒0.020 (‒1.07) | ‒0.044 (‒0.41) |
TR | ‒0.062* (‒3.76) | ‒0.085** (2.27) | ‒0.030** (‒1.00) | ‒0.080 (‒3.11) | 0.574 (6.28) |
constant | ‒1.520*** (-2.77) | ‒6.737 (0.668) | 1.488 (1.69) | 0.843*** (0.88) | 4.222*** (1.93) |
R2 | 0.526 | 0.583 | 0.833 | 0.658 | 0.871 |
F-statistic | 29.660 | 16.474 | 20.315 | 19.146 | 17.921 |
Table 5 Panel data regression results encompassing time fixed effects
Factor | China | East | Central | West | Northeast |
---|---|---|---|---|---|
ED | 0.452 (8.30) | ‒0.058 (‒0.43) | 0.131*** (1.04) | 0.471** (3.95) | ‒0.465 (‒3.77) |
IS | 0.132*** (‒1.50) | ‒1.009 (‒3.19) | 0.949** (4.50) | 0.821*** (2.73) | ‒0.590** (‒2.67) |
OP | 0.130*** (‒0.43) | 0.030*** (0.88) | ‒0.096 (‒2.67) | 0.190 (5.71) | ‒0.104*** (‒3.56) |
UR | 0.545** (‒4.33) | 1.400** (4.01) | ‒0.309** (‒0.99) | ‒1.035*** (‒3.59) | 0.881 (‒1.66) |
TI | 0.041** (‒0.38) | 0.014* (‒0.38) | 0.027* (‒1.77) | 0.105** (‒3.49) | ‒0.036 (‒1.61) |
EG | 0.056** (2.59) | 0.029 (0.52) | 0.014*** (‒0.79) | 0.077** (‒1.53) | 0.074*** (‒1.31) |
EC | ‒0.048*** (‒2.89) | ‒0.237*** (‒2.21) | ‒0.184*** (‒5.20) | ‒0.020 (‒1.07) | ‒0.044 (‒0.41) |
TR | ‒0.062* (‒3.76) | ‒0.085** (2.27) | ‒0.030** (‒1.00) | ‒0.080 (‒3.11) | 0.574 (6.28) |
constant | ‒1.520*** (-2.77) | ‒6.737 (0.668) | 1.488 (1.69) | 0.843*** (0.88) | 4.222*** (1.93) |
R2 | 0.526 | 0.583 | 0.833 | 0.658 | 0.871 |
F-statistic | 29.660 | 16.474 | 20.315 | 19.146 | 17.921 |
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