Fiscal Decentralization and Local Environmental Pollution in China
Abstract
:1. Introduction
2. Theoretical Analysis and Research Hypotheses
3. Research Design
3.1. Description of the Models and Variables
3.2. Data
3.3. Preliminary Analysis
4. Empirical Test and Scientific Discussion
4.1. Results of Testing Hypothesis 1
4.2. Results of Testing Hypothesis 2
4.3. Further Analysis: Panel Threshold Modeling Results
4.4. Robustness Check
4.5. Scientific Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Zang, J.; Liu, L. Fiscal decentralization, government environmental preference, and regional environmental governance efficiency: Evidence from China. Ann. Reg. Sci. 2020, 65, 1–19. [Google Scholar] [CrossRef]
- Li, G.; He, Q.; Shao, S.; Cao, J. Environmental non-governmental organizations and urban environmental governance: Evidence from China. J. Environ. Manag. 2018, 206, 1296–1307. [Google Scholar] [CrossRef]
- Zhang, J.; Qu, Y.; Li, X.; Miao, X. Effects of FDI on the efficiency of government expenditure on environmental protection under fiscal decentralization: A spatial econometric analysis for China. Int. J. Environ. Res. Public Health 2019, 16, 2496. [Google Scholar] [CrossRef] [Green Version]
- Xue, G.; Pan, X. An empirical analysis of the impact of fiscal decentralization on environmental pollution in China. China Popul. Resour. Environ. 2012, 22, 83–89. [Google Scholar]
- Kunce, M.; Shogren, J. On environmental federalism and direct emission controls. J. Urban Econ. 2002, 51, 238–245. [Google Scholar] [CrossRef]
- Yang, T.; Ye, M.; Pei, P.; Shi, Y.; Pan, H. City branding evaluation as a tool for sustainable urban growth: A framework and lessons from the Yangtze River Delta Region. Sustainability 2019, 11, 4281. [Google Scholar] [CrossRef] [Green Version]
- Blanchard, O.; Shleifer, A. Federalism with and without political centralization: China versus Russia. IMF Staff Pap. 2001, 48, 8. [Google Scholar]
- Nobuo, A.; Masayo, S. Fiscal decentralization contributes to economic growth: Evidence from state-level cross-section data for the United States. J. Urban Econ. 2002, 52, 93–108. [Google Scholar]
- Zhang, P.D. Does local government’s environmental protection really work? An empirical study based on the fiscal decentralization. Econ. Manag. 2018, 40, 25–39. [Google Scholar]
- Liu, L.; Ding, D.; He, J. The welfare effects of fiscal decentralization: A simple model and evidence from China. Qual. Quant. 2019, 53, 417–434. [Google Scholar] [CrossRef]
- Besley, T.; Coate, S. Centralized versus decentralized provision of local public goods: A political economy approach. J. Public Econ. 2003, 87, 2611–2637. [Google Scholar] [CrossRef]
- Tiebout, C.M. A pure theory of local expenditures. J. Political Econ. 1956, 64, 416–424. [Google Scholar] [CrossRef]
- Wildasin, D.E. Interjurisdictional capital mobility: Fiscal externality and a corrective subsidy. J. Urban Econ. 1989, 25, 193–212. [Google Scholar] [CrossRef]
- Buchanan, J.M.; Musgrave, R.A. Public finance and public choice: Two contrasting visions of the State. Public Choice 2001, 106, 196–199. [Google Scholar]
- Shen, J. A simultaneous estimation of environmental Kuznets Curve: Evidence from China. China Econ. Rev. 2006, 17, 383–394. [Google Scholar] [CrossRef]
- List, J.A.; Gerking, S. Regulatory federalism and environmental protection in the United States. J. Reg. Sci. 2000, 40, 453–471. [Google Scholar] [CrossRef]
- Millimet, D.L. Assessing the empirical impact of environmental federalism. J. Reg. Sci. 2010, 43, 711–733. [Google Scholar] [CrossRef]
- Farzanegan, M.R.; Mennel, T. Fiscal Decentralization and Pollution: Institutions Matter. MAGKS Joint Discussion Paper Series in Economics. 2012. Available online: http://hdl.handle.net/10419/73071 (accessed on 5 November 2020).
- Fredriksson, P.G.; Mani, M.; Wollscheid, J.R. Environmental Federalism: A Panacea or Pandora’s Box for Developing Countries? World Bank Policy Research Working Paper No. 3847; World Bank: Washington, DC, USA, 2006. [Google Scholar]
- Kuai, P.; Yang, S.; Tao, A.; Zhang, S.; Khan, Z.D. Environmental effects of Chinese-style fiscal decentralization and the sustainability implications. J. Clean. Prod. 2019, 239, 118089. [Google Scholar] [CrossRef]
- He, Q. Fiscal decentralization and environmental pollution: Evidence from Chinese panel data. China Econ. Rev. 2015, 36, 86–100. [Google Scholar] [CrossRef]
- Zhang, K.; Wang, J.; Cui, X. Fiscal decentralization and environmental pollution: A perspective of carbon emission. China Ind. Econ. 2011, 10, 67–77. [Google Scholar]
- Pang, R.; Zheng, D.; Shi, M.; Zhang, X. Pollute first, control later? Exploring the economic threshold of effective environmental regulation in China’s context. J. Environ. Manag. 2019, 248, 109275. [Google Scholar] [CrossRef] [PubMed]
- Qian, Y.; Weingast, B.R. Federalism as a commitment to preserving market incentives. J. Econ. Perspect. 1997, 11, 83–92. [Google Scholar] [CrossRef]
- Du, J.; Fang, H.; Jin, X. The “growth-first strategy” and the imbalance between consumption and investment in China. China Econ. Rev. 2014, 31, 441–458. [Google Scholar] [CrossRef]
- Li, Z.; Yang, S. Fiscal decentralization, government innovation preferences and regional innovation efficiency. Manag. World 2018, 34, 29–42. [Google Scholar]
- Wu, X.; Wang, J. Fiscal decentralization, environmental protection expenditure and haze pollution. Resour. Sci. 2018, 40, 851–861. [Google Scholar]
- Hong, Y.; Yuan, Y.; Chen, L. Fiscal decentralization, environmental fiscal policy and local environmental pollution: Analysis of threshold effect and spatial spillover effect based on double dimensions of income and expenditure. J. Shanxi Univ. Financ. Econ. 2018, 40, 1–15. [Google Scholar]
- Grossman, G.M.; Krueger, A.B. Environmental Impacts of a North America Free Trade Agreement; NBER Working Paper 3914; MIT Press: Cambridge, MA, USA, 1991. [Google Scholar]
- Schreifels, J.J.; Fu, Y.; Wilson, E.J. Sulfur dioxide control in China: Policy evolution during the 10th and 11th Five-year Plans and lessons for the future. Energy Policy 2012, 48, 779–789. [Google Scholar] [CrossRef]
- Greaney, T.M.; Li, Y.; Tu, D. Pollution control and foreign firms’ exit behavior in China. J. Asian Econ. 2017, 48, 148–159. [Google Scholar] [CrossRef]
- Zhang, Y.; Gong, L. The Fenshuizhi reform, fiscal decentralization and economic growth in China. Econ. Q. 2005, 5, 75–108. [Google Scholar]
- Li, Z.; Li, J.; He, B. Does foreign direct investment enhance or inhibit regional innovation efficiency? Evidence from China. Chin. Manag. Stud. 2018, 12, 35–55. [Google Scholar] [CrossRef] [Green Version]
- Wang, S. The Political Logic of China’s Fiscal Transfer Payments. Strategy Manag. 2002, 3, 47–54. [Google Scholar]
- He, J.; Wang, H. Economic structure, development policy and environmental quality: An empirical analysis of environmental Kuznets Curves with Chinese municipal data. Ecol. Econ. 2012, 76, 49–59. [Google Scholar] [CrossRef] [Green Version]
- Shi, T.; Yang, S.; Zhang, W.; Zhou, Q. Coupling coordination degree measurement and spatiotemporal heterogeneity between economic development and ecological environment: Empirical evidence from tropical and subtropical regions of China. J. Clean. Prod. 2020, 244, 118739. [Google Scholar] [CrossRef]
- Liu, K.; Lin, B.Q. Research on influencing factors of environmental pollution in China: A spatial econometric analysis. J. Clean. Prod. 2019, 206, 356–364. [Google Scholar] [CrossRef]
- Wu, L.; Kaneko, S.; Matsuoka, S. Driving forces behind the stagnancy of China’s energy-related co-emissions from 1996 to 1999: The relative importance of structural change, intensity change and scale change. Energy Policy 2005, 33, 319–335. [Google Scholar] [CrossRef]
- Zheng, Y. The support of the central government to minority areas in recent years. Rev. Econ. Res. 2010, 3, 18–22. [Google Scholar]
- Sigman, H. Decentralization and Environmental quality: An international analysis of water pollution levels and variation. Land Econ. 2014, 90, 114–130. [Google Scholar] [CrossRef]
- Adam, A.; Delis, M.D.; Kammas, P. Fiscal decentralization and public sector efficiency: Evidence from OECD countries. Econ. Gov. 2014, 15, 17–49. [Google Scholar] [CrossRef] [Green Version]
- Blanchard, O.; Shleifer, A. Federalism with and without political centralization: China vs. Russia in transitional economics: How much progress? IMF Staff Pap. 2001, 48, 171–179. [Google Scholar]
- Shih, V.; Adolph, C.; Liu, M. Getting ahead in the communist party: Explaining the advancement of central committee members in China. Am. Political Sci. Rev. 2012, 106, 166–187. [Google Scholar] [CrossRef] [Green Version]
- Onofrei, M.; Vatamanu, A.F.G.; Bostan, I.; Filip, B.F.; Popescu, C.L.; Jitaru, G. Impacts of the allocation of governmental resources for improving the environment. An empirical analysis on developing European countries. Int. J. Environ. Res Public Health 2020, 17, 2783. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Variables | Description | Mean | SD | Min | Max |
---|---|---|---|---|---|
EP | Industrial SO2 emission/land area (tons/km2) | 5.349 | 6.848 | 0.163 | 57.723 |
FD1 | Per capita fiscal revenue of local government/per capita fiscal revenue of central government | 1.189 | 0.983 | 0.348 | 5.379 |
FD2 | Per capita fiscal expenditure of local government/per capita fiscal expenditure of central government | 5.946 | 2.925 | 2.308 | 14.660 |
GEP1 | Per capita fiscal environmental protection expenditure (CNY hundred) | 2.368 | 1.625 | 0.315 | 11.879 |
GEP2 | Fiscal environmental protection expenditure/total fiscal expenditure (%) | 3.022 | 1.115 | 0.846 | 7.520 |
GDP | GDP per capita (CNY ten thousand) | 3.212 | 1.900 | 0.654 | 10.320 |
FDI | Foreign direct investment/GDP (%) | 2.409 | 1.871 | 0.068 | 8.198 |
ST | No of patents granted per 10,000 persons | 5.976 | 8.030 | 0.350 | 43.312 |
IS | Value added of the secondary industry/total value-added (%) | 47.746 | 7.906 | 19.738 | 61.500 |
Independent Variable | Full Sample | Excluding Minority Provinces | ||
---|---|---|---|---|
FD1 | FD2 | FD1 | FD2 | |
FD | 7.234 ** (3.103) | 0.751 (0.658) | 9.670 *** (1.870) | 2.693 ** (1.202) |
GDP | −0.988 (3.898) | 8.995 (7.252) | −4.927 (5.564) | 4.298 (5.195) |
GDP2 | 0.692 (0.514) | −0.288 (0.399) | 1.182 ** (0.536) | 0.181 (0.397) |
FDI | −0.335 (0.300) | −0.063 (0.188) | −0.988 *** (0.300) | −0.844 ** (0.405) |
ST | −0.202 * (0.107) | −0.158 * (0.087) | −0.133 (0.078) | −0.131 (0.082) |
IS | 0.086 (0.108) | 0.093 (0.120) | 0.027 (0.076) | 0.037 (0.083) |
_cons | −5.311 (8.216) | −16.513 (17.421) | 0.256 (8.151) | −13.888 (12.329) |
province fixed effects | Yes | Yes | Yes | Yes |
time dummies | Yes | Yes | Yes | Yes |
N | 270 | 270 | 207 | 207 |
Independent Variable | Full Sample | Excluding Minority Provinces | ||||||
---|---|---|---|---|---|---|---|---|
FD1 | FD2 | FD1 | FD2 | |||||
FD | 6.177 ** (2.679) | 6.218 ** (2.697) | 1.334 (0.939) | 0.932 (0.745) | 7.975 *** (2.237) | 8.168 *** (2.362) | 1.334 * (1.197) | 2.494 * (1.241) |
GEP1t-1*FD | −0.277 (0.184) | −0.069 (0.048) | −0.205 (0.142) | −0.046 (0.036) | ||||
GEP2t-1*FD | −0.609 * (0.345) | −0.082 (0.051) | −0.482 * (0.242) | −0.083 * (0.041) | ||||
GDP | −4.883 (5.048) | −3.197 (4.176) | −1.343 (4.333) | 2.779 (3.244) | −9.361 (8.927) | −9.174 (8.871) | −5.538 (7.809) | −4.500 (7.914) |
GDP2 | 1.173 * (0.590) | 0.913 * (0.489) | 0.485 (0.393) | −0.072 (0.360) | 1.520 * (0.797) | 1.434 * (0.769) | 0.740 (0.542) | 0.559 (0.538) |
FDI | −0.228 (0.307) | −0.204 (0.284) | −0.091 (0.232) | −0.056 (0.197) | −0.756 ** (0.358) | −0.740 ** (0.339) | −0.681 * (0.391) | −0.677 * (0.384) |
ST | −0.121 ** (0.051) | −0.122 ** (0.050) | −0.073 * (0.042) | −0.064 (0.045) | −0.057 (0.063) | −0.067 (0.059) | −0.042 (0.056) | −0.044 (0.055) |
IS | 0.085 (0.110) | 0.080 (0.108) | 0.085 (0.113) | 0.070 (0.105) | 0.085 (0.100) | 0.074 (0.100) | 0.072 (0.090) | 0.070 (0.089) |
_cons | −0.186 (5.640) | −0.770 (4.810) | −3.424 (6.867) | −5.683 (7.461) | 7.165 (10.939) | 7.725 (10.851) | 1.457 (9.408) | 1.105 (9.368) |
province fixed effects | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
time dummies | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
N | 240 | 240 | 240 | 240 | 184 | 184 | 184 | 184 |
Independent Variable | Threshold | F Stat | Prob | Crit10 | Crit5 | Crit1 | Threshold Estimator | |
---|---|---|---|---|---|---|---|---|
Full sample | ||||||||
FD1 | Single | 140.51 | 0.000 | 25.262 | 35.009 | 63.286 | Th-1 | 1.102 |
Double | 135.34 | 0.000 | 17.455 | 26.905 | 49.597 | Th-21 Th-22 | 1.102 3.510 | |
Triple | 105.42 | 0.113 | 111.896 | 134.894 | 203.689 | Th-3 | 3.535 | |
FD2 | Single | 106.55 | 0.000 | 25.261 | 33.256 | 52.899 | Th-1 | 1.102 |
Double | 79.49 | 0.000 | 23.058 | 28.581 | 40.528 | Th-21 Th-22 | 1.102 3.510 | |
Triple | 53.70 | 0.253 | 66.119 | 77.026 | 94.912 | Th-3 | 3.535 | |
Excluding minority provinces | ||||||||
FD1 | Single | 87.66 | 0.000 | 16.295 | 20.406 | 35.816 | Th-1 | 3.510 |
Double | 59.87 | 0.000 | 12.751 | 16.843 | 29.619 | Th-21 Th-22 | 1.102 3.510 | |
Triple | 108.53 | 0.583 | 206.299 | 224.478 | 284.917 | Th-3 | 3.535 | |
FD2 | Single | 87.70 | 0.000 | 20.116 | 25.375 | 38.862 | Th-1 | 1.102 |
Double | 66.34 | 0.000 | 17.892 | 24.083 | 35.044 | Th-21 Th-22 | 1.102 3.510 | |
Triple | 54.28 | 0.653 | 116.280 | 127.437 | 148.921 | Th-3 | 3.535 |
Independent Variable | Threshold Interval | Full Sample | Excluding Minority Provinces | ||
---|---|---|---|---|---|
FD1 | FD2 | FD1 | FD2 | ||
FD | (GEP1 ≤ 1.102) | 8.295 *** (1.541) | 1.828 ** (0.782) | 9.794 *** (1.548) | 2.799 *** (0.982) |
(1.102 < GEP1 ≤ 3.510) | 6.049 *** (1.559) | 1.022 (0.602) | 8.237 *** (1.578) | 2.017 ** (0.830) | |
(GEP1 > 3.510) | 4.264 *** (0.998) | 0.554 (0.471) | 6.472 *** (1.225) | 1.531 ** (0.669) | |
GDP | −7.679 *** (2.673) | 0.030 (2.971) | −10.687 ** (5.186) | −2.852 (2.579) | |
GDP2 | 1.479 *** (0.431) | 0.634 ** (0.274) | 1.837 *** (0.619) | 0.905 ** (0.394) | |
FDI | −0.248 (0.197) | −0.066 (0.156) | −0.551 *** (0.190) | −0.224 (0.209) | |
ST | −0.134 *** (0.038) | −0.117 *** (0.033) | −0.078 (0.047) | −0.149 *** (0.045) | |
IS | 0.060 (0.055) | 0.106 (0.079) | 0.039 (0.055) | 0.122 (0.080) | |
_cons | 4.437 (3.380) | −7.820 (8.209) | 7.547 (5.422) | −6.761 (6.446) | |
province fixed effects | Yes | Yes | Yes | Yes | |
time dummies | Yes | Yes | Yes | Yes | |
N | 270 | 270 | 207 | 207 |
Independent Variable | Full Sample | Excluding Minority Provinces | ||
---|---|---|---|---|
FD1 | FD2 | FD1 | FD2 | |
FD | 2.202 *** (0.570) | 0.363 (0.402) | 3.573 *** (0.961) | 1.745 ** (0.659) |
GDP | 1.649 (4.015) | 3.714 (3.927) | −2.036 (3.962) | −3.302 (5.732) |
GDP2 | 0.288 (0.422) | 0.059 (0.411) | 0.642 (0.504) | 0.626 (0.612) |
FDI | −0.184 (0.212) | −0.101 (0.195) | −0.490 * (0.267) | −0.537 * (0.301) |
ST | −0.136 * (0.072) | −0.118 * (0.066) | −0.092 (0.056) | −0.085 (0.058) |
IS | 0.046 (0.107) | 0.048 (0.110) | 0.019 (0.097) | 0.014 (0.090) |
_cons | −3.769 (5.801) | −6.156 (6.288) | 1.987 (4.158) | 2.094 (4.824) |
province fixed effects | Yes | Yes | Yes | Yes |
time dummies | Yes | Yes | Yes | Yes |
N | 270 | 270 | 207 | 207 |
Independent Variable | Full Sample | Excluding Minority Provinces | ||||||
---|---|---|---|---|---|---|---|---|
FD1 | FD2 | FD1 | FD2 | |||||
FD | 2.577 * (1.297) | 2.344 ** (0.570) | 1.141 * (0.651) | 0.678 (0.519) | 3.765 ** (1.681) | 3.764 ** (1.531) | 2.203 *** (0.745) | 2.080 ** (0.767) |
GEP1t-1* FD | −0.334 (0.234) | −0.086 * (0.049) | −0.310 (0.238) | −0.090 (0.061) | ||||
GEP2t-1* FD | −0.597 * (0.234) | −0.117 * (0.063) | −0.565 * (0.316) | −0.147 ** (0.077) | ||||
GDP | −4.779 (7.631) | −2.195 (7.631) | −6.448 (8.836) | −1.477 (6.411) | −11.540 (10.758) | −10.324 (9.997) | −15.908 (12.989) | −13.662 (12.352) |
GDP2 | 1.231 (1.005) | 0.791 (1.005) | 1.170 (0.935) | 0.519 (0.600) | 1.734 (1.245) | 1.438 (0.993) | 1.902 (1.265) | 1.508 (1.067) |
FDI | −0.187 (0.225) | −0.168 (0.225) | −0.213 (0.260) | −0.170 (0.232) | −0.482 (0.315) | −0.482 (0.297) | −0.605 * (0.333) | −0.602 * (0.321) |
ST | −0.100 * (0.058) | −0.104 (0.058) | −0.098 (0.062) | −0.085 (0.058) | −0.028 (0.071) | −0.046 (0.075) | −0.030 (0.065) | −0.035 (0.067) |
IS | 0.091 (0.140) | 0.080 (0.140) | 0.089 (0.138) | 0.072 (0.135) | 0.097 (0.144) | 0.099 (0.151) | 0.095 (0.128) | 0.097 (0.135) |
_cons | 1.318 (7.234) | 1.318 (5.958) | 3.039 (7.430) | 0.270 (5.709) | 12.374 (12.062) | 12.714 (11.839) | 16.323 (15.043) | 15.573 (14.590) |
province fixed effects | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
time dummies | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
N | 240 | 240 | 240 | 240 | 184 | 184 | 184 | 184 |
Independent Variable | Threshold | F stat | Prob | Crit10 | Crit5 | Crit1 | Threshold Estimator | |
---|---|---|---|---|---|---|---|---|
Full sample | ||||||||
FD1 | Single | 158.10 | 0.000 | 25.297 | 39.239 | 94.247 | Th-1 | 3.510 |
Double | −31.52 | 1.000 | 20.743 | 41.584 | 118.515 | Th-21 Th-22 | 3.227 3.637 | |
FD2 | Single | 106.33 | 0.000 | 21.041 | 29.135 | 62.301 | Th-1 | 3.510 |
Double | −19.86 | 1.000 | 21.740 | 28.010 | 38.898 | Th-21 Th-22 | 3.227 3.637 | |
Excluding minority provinces | ||||||||
FD1 | Single | 139.48 | 0.000 | 13.607 | 27.008 | 48.670 | Th-1 | 3.510 |
Double | 176.61 | 0.000 | 13.628 | 18.795 | 33.543 | Th-21 Th-22 | 3.535 3.535 | |
FD2 | Single | 123.94 | 0.000 | 16.081 | 25.662 | 49.220 | Th-1 | 3.510 |
Double | 50.32 | 0.003 | 16.077 | 19.670 | 26.322 | Th-21 Th-22 | 3.535 3.570 |
Independent Variable | Threshold Interval | Full Sample | Excluding Minority Provinces | ||
---|---|---|---|---|---|
FD1 | FD2 | FD1 | FD2 | ||
FD | (GEP1 ≤ 3.510) | 3.824 *** (1.104) | 1.114 (0.657) | 2.279 ** (0.885) | 5.038 *** (1.001) |
(GEP1 > 3.510) | 1.261 (1.031) | 0.511 (0.422) | 1.477 ** (0.708) | 2.392 ** (1.120) | |
GDP | −6.433 (7.742) | −3.259 (7.849) | 6.406 * (3.514) | −14.481 * (8.244) | |
GDP2 | 1.641 * (0.821) | 1.128 (0.850) | −0.209 (0.257) | 2.293 * (0.890) | |
FDI | −0.170 (0.202) | −0.107 (0.218) | −0.179 (0.208) | −0.303 (0.189) | |
ST | −0.128 *** (0.037) | −0.114 *** (0.043) | −0.156 *** (0.055) | −0.084 ** (0.034) | |
IS | 0.074 (0.094) | 0.087 (0.114) | 0.056 (0.084) | 0.078 (0.087) | |
_cons | 1.788 (7.954) | −3.109 (7.467) | −14.434 (9.585) | 13.413 (8.425) | |
province fixed effects | Yes | Yes | Yes | Yes | |
time dummies | Yes | Yes | Yes | Yes | |
N | 270 | 270 | 207 | 207 |
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Guo, S.; Wen, L.; Wu, Y.; Yue, X.; Fan, G. Fiscal Decentralization and Local Environmental Pollution in China. Int. J. Environ. Res. Public Health 2020, 17, 8661. https://doi.org/10.3390/ijerph17228661
Guo S, Wen L, Wu Y, Yue X, Fan G. Fiscal Decentralization and Local Environmental Pollution in China. International Journal of Environmental Research and Public Health. 2020; 17(22):8661. https://doi.org/10.3390/ijerph17228661
Chicago/Turabian StyleGuo, Shufen, Ludi Wen, Yanrui Wu, Xiaohang Yue, and Guilian Fan. 2020. "Fiscal Decentralization and Local Environmental Pollution in China" International Journal of Environmental Research and Public Health 17, no. 22: 8661. https://doi.org/10.3390/ijerph17228661