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2018 | 27 | 4 |

Tytuł artykułu

Mutual influence of energy consumption and foreign direct investment on haze pollution in China: a spatial econometric approach

Autorzy

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
Based on the data of annual average values of PM₁₀ concentrations in China, this study empirically investigates the spatial autocorrelation of haze pollution in China and the mutual influence of energy consumption and foreign direct investment on haze pollution in China from 2004 to 2014 using the spatial econometric method. Moran’s I values are all above 0 during the 10 years, which indicates that haze pollution in China exists with significant spatial autocorrelation. Then the spatial econometric model estimation results show that energy consumption has a significant and positive effect on haze pollution in China while foreign direct investment has a significant and negative effect on haze pollution. Meanwhile, the regression coefficient of mutual variable of energy consumption and foreign direct investment is 0.063 at the 5% level, which suggests that foreign direct investment plays an important role in regulating the relationship between energy consumption and haze pollution, namely that the aggravation effect of energy consumption on haze pollution will increase with the increase of foreign direct investment. Finally, we provide some policy guidance for controlling haze pollution in China.

Słowa kluczowe

Wydawca

-

Rocznik

Tom

27

Numer

4

Opis fizyczny

p.1743-1752,fig.,ref.

Twórcy

autor
  • School of Business Administration, Guangdong University of Finance and Economics, Guangzhou, China
autor
  • School of Business Administration, Guangdong University of Finance and Economics, Guangzhou, China
autor
  • Public Management School, Guangdong University of Finance and Economics, Guangzhou, China

Bibliografia

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  • 2. REN S., YUAN B., MA X., CHEN X. International trade, FDI (foreign direct investment) and embodied CO₂ emissions: a case study of Chinas industrial sectors. China. Econ. Rev. 28, 123, 2014.
  • 3. CHENG Z., WANG S., JIANG J., FU Q., CHEN C., XU B., YU J., FU X., HAO J. Long-term trend of haze pollution and impact of particulate matter in the Yangtze River Delta, China. Environ. Pollut. 182, 101, 2013.
  • 4. VAN DONKELAAR A., MARTIN R.V., BRAUER M., KAHN R., LEVY R., VERDUZCO C., VILLENEUVE P.J. Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: development and application. Environ. Health. Persp. 118 (6), 847, 2010.
  • 5. WANG L., XU J., YANG J., ZHAO X., WEI W., CHENG D., PAN X., SU J. Understanding haze pollution over the southern Hebei area of China using the CMAQ model. Atmos. Environ. 56, 69, 2012.
  • 6. HAO Y., LIU Y. influential factors of urban PM2.5 concentrations in China: a spatial econometric analysis. J. Clean. Prod. 112, 1443, 2016.
  • 7. TAO M., CHEN L., WANG Z., MA P., TAO J., JIA S. A study of urban pollution and haze clouds over northern China during the dusty season based on satellite and surface observations. Atmos. Environ. 82, 183, 2014.
  • 8. WANG Y., YAO L., WANG L., LIU Z., JI D., TANG G., ZHANG J., SUN Y., HU B., XIN J. Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China. Sci. China. Earth. Sci. 57 (1), 14, 2014.
  • 9. TANG D., LI L., YANG Y. Spatial econometric model analysis of foreign direct investment and haze pollution in china. Pol. J. Environ. Stud. 25(1), 317, 2016.
  • 10. ZHA Y., GAO J., JIANG J., LU H., HUANG J. Normalized difference haze index: a new spectral index for monitoring urban air pollution. Int. J. Remote. Sens. 33 (1), 309, 2012.
  • 11. ZHANG Z., WANG J., CHEN L., CHEN X., SUN G., ZHONG N., KAN H., LU W. Impact of haze and air pollution-related hazards on hospital admissions in Guangzhou, China. Environ. Sci. Pollut. R. 21 (6), 4236, 2014.
  • 12. MA L.M., ZHANG X. The spatial effect of China’s haze pollution and the impact from economic change and energy structure. China. Ind. Econ. 4, 19, 2014. (In Chinese) 13. BAEK J. A new look at the FDI-income-energy-environment nexus: dynamic panel data analysis of ASEAN. Energ. Policy. 91, 22, 2016.
  • 14. HUEBLER M., KELLER A. Energy savings via FDI? Empirical evidence from developing countries. Environ. Dev. Econ. 15 (1), 59, 2010.
  • 15. LI K., QI S. Does FDI increase industrial energy consumption of china? Based on the empirical analysis of Chinese provinces industrial panel data. Emerg. Mark. Financ. Tr. 52 (6), 1305, 2016.
  • 16. HE J. Pollution haven hypothesis and environmental impacts of foreign direct investment: the case of industrial emission of sulfur dioxide (SO₂) in Chinese provinces. Ecol. Econ. 60 (1), 228, 2006.
  • 17. ELLIOTT R.J.R., SUN P., CHEN S. Energy intensity and foreign direct investment: a Chinese city-level study. Energ. Econ. 40, 484, 2013.
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Typ dokumentu

Bibliografia

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Identyfikator YADDA

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