Hostname: page-component-6bb9c88b65-znhjv Total loading time: 0 Render date: 2025-07-28T03:15:32.881Z Has data issue: false hasContentIssue false
  • English
  • Français

Investigating the effect of carbon leakage on the environmental Kuznets curve using luminosity data

Published online by Cambridge University Press:  03 July 2017

Arne Steinkraus Open the ORCID record for Arne Steinkraus [Opens in a new window]
Arne Steinkraus*
Affiliation:
Institute of Economics, TU Braunschweig, Spielmannstraße 9, 38106 Braunschweig, Germany. Tel: +0049 531 391 2567. E-mail: a.steinkraus@tu-braunschweig.de
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper studies the effect of carbon leakage on the environmental Kuznets curve (EKC) using satellite nighttime light data. It shows that nighttime lighting is an important variable for estimating carbon dioxide emissions that is superior to other existing indicators and covers all countries in the world, finding evidence of an inverted-U shaped relationship between light and, thus, greenhouse gas emissions and income, with a turning point at approximately US$50,000. However, the relationship is primarily driven by changes in the structure of international trade, implying strong carbon leakage effects. Consequently, environmental regulations that become operative in only one part of the world may fail without global coordination.

Information

Type
Research Article
Information
Environment and Development Economics , Volume 22 , Special Issue 6: Recent Advances in Empirical Analysis on Growth and Environment , December 2017 , pp. 747 - 770
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Akbostanci, E., Türük-Asik, S., and Tunc, G.I. (2009), ‘The relationship between income and environment in Turkey: is there an environmental Kuznets curve?’, Energy Policy 37(3): 861–867.Google Scholar
Apergis, N. and Ozturk, I. (2015), ‘Testing environmental Kuznets curve hypothesis in Asian countries’, Ecological Indicators 52: 16–22.Google Scholar
Arrow, K., Bolin, B., Costanza, R., et al. (1996), ‘Economic growth, carrying capacity, and the environment’, Environment and Development Economics 1(1): 104–110.CrossRefGoogle Scholar
Babiker, M.H. (2005), ‘Climate change policy, market structure, and carbon leakage’, Journal of International Economics 65: 421–445.Google Scholar
Chen, X. and Nordhaus, W.D. (2011), ‘Using luminosity data as a proxy for economic statistics’, Proceedings of the National Academy of Science 108(21): 8589–8594.CrossRefGoogle ScholarPubMed
Chepesiuk, R. (2009), ‘Missing the dark: health effects of light pollution’, Environmental Health Perspectives 117(1): 20–27.Google Scholar
Cole, M.A., Rayner, A.J., and Bates, J.M. (1997), ‘The environmental Kuznets curve: an empirical analysis’, Environment and Development Economics 2(4): 401–416.CrossRefGoogle Scholar
Coscieme, L., Pulselli, F.M., Bastianoni, S., Elvidge, C.D., Anderson, S., and Sutton, P.C. (2014), ‘A thermodynamic geography: night-time satellite imagery as a proxy measure of emergy’, Ambio 43(7): 969–979.Google Scholar
Dinda, S. (2004), ‘Environmental Kuznets curve hypothesis: a survey’, Ecological Economics 49(4): 431–455.CrossRefGoogle Scholar
Doll, C.H., Muller, J.P., and Elvidge, C.D. (2000), ‘Night-time imagery as a tool for global mapping of socioeconomic parameters and greenhouse gas emissions’, Ambio 29(3): 157–162.Google Scholar
Eichner, T. and Pethig, R. (2011), ‘Carbon leakage, the green paradox, and perfect future markets’, International Economic Review 52(3): 767–805.Google Scholar
Elvidge, C.D., Imhoff, M.L., Baugh, K.E., et al. (2001), ‘Night-time lights of the world: 1994–1995’, Journal of Photogrammetry and Remote Sensing 56(2): 81–99.Google Scholar
Elvidge, C.D., Hsu, F.C., Baugh, K.E., and Ghosh, T. (2013), ‘National trends in satellite-observed lighting’, Global Urban Monitoring and Assessment through Earth Observation 23: 97–118.Google Scholar
Falchi, F., Cinzano, P., Elvidge, C.D., Keith, D.M., and Haim, A. (2011), ‘Limiting the impact of light pollution on human health, environment and stellar visibility’, Journal of Environmental Management 92(10): 2714–2722.Google Scholar
Felder, S. and Rutherford, T.F. (1993), ‘Unilateral CO2 reductions and carbon leakage: the consequences of international trade in oil and basic materials’, Journal of Environmental Economics and Management 25: 162–176.CrossRefGoogle Scholar
Galeotti, M., Lanza, A., and Pauli, F. (2006), ‘Reassessing the environmental Kuznets curve for CO2 emissions: a robustness exercise’, Ecological Economics 57(1): 152–163.Google Scholar
Gallaway, T., Olsen, R.N., and Mitchell, D.M. (2010), ‘The economics of global light pollution’, Ecological Economics 69: 658–665.Google Scholar
Gaston, K.J., Davies, T.W., Bennie, J., and Hopkins, J. (2012), ‘Reducing the ecological consequences of night-time light pollution: options and developments’, Journal of Applied Ecology 49(6): 1256–1266.CrossRefGoogle ScholarPubMed
Grossman, G.M. (1995), ‘Pollution and growth: what do we know?’, in Goldin, I. and Winters, L.A. (eds), The Economics of Sustainable Development, Cambridge: Cambridge University Press, pp. 19–46.Google Scholar
Grossman, G.M. and Krueger, A.B. (1991), ‘Environmental impacts of a North American free trade agreement’, NBER Working Paper No. 3914, National Bureau of Economic Research, Washington, DC.Google Scholar
Grossman, G.M. and Krueger, A.B. (1996), ‘The inverted-U: what does it mean?’, Environment and Development Economics 1(1): 119–122.CrossRefGoogle Scholar
He, J. and Richard, P. (2010), ‘Environmental Kuznets curve for CO2 in Canada’, Ecological Economics 69(5): 1083–1093.Google Scholar
Henderson, J.V., Storeygard, A., and Weil, D.N. (2012), ‘Measuring economic growth from outer space’, American Economic Review 102(2): 994–1028.Google Scholar
IEA (2006), Light's Labour's Lost – Policies for Energy-efficient Lighting, Paris: OECD, [Available at] https://www.iea.org/publications/freepublications/publication/light2006.pdf.Google Scholar
Jalil, A. and Mahmud, S.F. (2009), ‘Environment Kuznets curve for CO2 emissions: a cointegration analysis for China’, Energy Policy 37(12): 5167–5172.Google Scholar
Kuznets, S. (1955), ‘Economic growth and income inequality’, American Economic Review 49: 1–28.Google Scholar
Kuznets, S. (1963), ‘Quantitative aspects of the economic growth of nations, VIII: the distribution of income by size’, Economic Development and Cultural Change 11: 1–92.Google Scholar
Kyba, C.C.M. and Hölker, F. (2013), ‘Do artificially illuminated skies affect biodiversity in nocturnal landscapes?’, Landscape Ecology 28: 1637–1640.Google Scholar
Lessmann, C. and Seidel, A. (2017), ‘Regional inequality, convergence, and its determinants – a view from outer space’, European Economic Review 92: 110–132.CrossRefGoogle Scholar
Oda, T. and Maksyutov, S. (2011), ‘A very high-resolution (1 km × 1 km) global fossil fuel CO2 emission inventory derived using a point source database and satellite observations of nighttime lights’, Atmospheric Chemistry and Physics 11(2): 543–556.Google Scholar
Ou, J., Liu, X., Li, X., Li, M., and Li, W. (2015), ‘Evaluation of NPP-VIIRS nighttime light data for mapping global fossil fuel combustion CO2 emissions: a comparison with DMSP-OLS nighttime light data’, PloS One 10(9).Google Scholar
Paltsev, S.V. (2001), ‘The Kyoto Protocol: regional and sectoral contributions to the carbon leakage’, Energy Journal 22(4): 53–79.Google Scholar
Panayotou, T. (1993), ‘Empirical tests and policy analysis of environmental degradation at different stages of economic development’, Working Paper No. 238, Technology and Employment Programme, International Labour Office, Geneva.Google Scholar
Rayner, P.J., Raupach, M.R., Paget, M., Peylin, P., and Koffi, E. (2010), ‘A new global gridded data set of CO2 emissions from fossil fuel combustion: methodology and evaluation’, Journal of Geophysical Research: Atmospheres 115: 1–11.Google Scholar
Selden, T.M., Forrest, A.S., and Lockhart, J.E. (1999), ‘Analyzing the reductions in US air pollution emissions: 1970 to 1990’, Land Economics 75(1): 1–21.CrossRefGoogle Scholar
Shafik, N. and Bandyopadhyay, S. (1992), ‘Economic growth and environmental quality, time-series and cross-country evidence’, Working Paper No. WPS0904, World Development Report, Washington, DC.Google Scholar
Shi, K., Chen, Y., Yu, B., et al. (2016), ‘Modeling spatiotemporal CO2 (carbon dioxide) emission dynamics in China from DMSP-OLS nighttime stable light data using panel data analysis’, Applied Energy 168: 523–533.Google Scholar
Solow, R.M. (1974), ‘Intergenerational equity and exhaustible resources’, Review of Economic Studies 41: 29–45.Google Scholar
Stern, D.I., Common, M.S., and Barbier, E.B. (1996), ‘Economic growth and environmental degradation: the environmental Kuznets curve and sustainable development’, World Development 24(7): 1151–1160.Google Scholar
Wu, J., Wang, Z., Li, W., and Peng, J. (2013), ‘Exploring factors affecting the relationship between light consumption and GDP based on DMSP/OLS nighttime satellite imagery’, Remote Sensing of Environment 134: 111–119.Google Scholar
Zoundi, Z. (2017), ‘CO2 emissions, renewable energy and the environmental Kuznets curve, a panel cointegration approach’, Renewable and Sustainable Energy Reviews 72: 1067–1075.Google Scholar
Supplementary material: PDF

Steinkraus supplementary material

Appendix

Download Steinkraus supplementary material(PDF)
PDF 490.5 KB