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The Impact of Exogenous Pollution on Green Innovation

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  • Wang, Ying
  • Woodward, Richard T.
  • Liu, Jingyue

Abstract

Does environmental quality affect firms’ activities that might improve that quality? In this paper, we use China's public heating policy as a quasi-experiment to investigate the impact of exogenous pollution differences on green innovation behavior. We use a regression discontinuity model, and carry out a suite of robustness tests. We consistently find that firms located in cities with an exogenous source of heavy pollution tend to adopt green innovation at a lower rate while we find no difference in the rate at which they adopt non-green innovation. We find a strong causal effect: being north of the boundary, where pollution levels are higher, leads firms to adopt less green innovation. Firms located in the heating areas report roughly 1 less green innovation per billion RMB of assets, a substantial difference given the average number of green innovations per billion RMB of assets of northern firms is 0.641.
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  • Wang, Ying & Woodward, Richard T. & Liu, Jingyue, 2021. "The Impact of Exogenous Pollution on Green Innovation," 2021 Annual Meeting, August 1-3, Austin, Texas 312705, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea21:312705
    DOI: 10.22004/ag.econ.312705
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    References listed on IDEAS

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    1. Keele, Luke J. & Titiunik, Rocío, 2015. "Geographic Boundaries as Regression Discontinuities," Political Analysis, Cambridge University Press, vol. 23(1), pages 127-155, January.
    2. David S. Lee & Thomas Lemieux, 2010. "Regression Discontinuity Designs in Economics," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June.
    3. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    4. Wenlong He & Rui Shen, 2019. "ISO 14001 Certification and Corporate Technological Innovation: Evidence from Chinese Firms," Journal of Business Ethics, Springer, vol. 158(1), pages 97-117, August.
    5. Paul Lanoie & Jérémy Laurent‐Lucchetti & Nick Johnstone & Stefan Ambec, 2011. "Environmental Policy, Innovation and Performance: New Insights on the Porter Hypothesis," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 20(3), pages 803-842, September.
    6. Douglas Almond & Yuyu Chen & Michael Greenstone & Hongbin Li, 2009. "Winter Heating or Clean Air? Unintended Impacts of China's Huai River Policy," American Economic Review, American Economic Association, vol. 99(2), pages 184-190, May.
    7. Brunnermeier, Smita B. & Cohen, Mark A., 2003. "Determinants of environmental innovation in US manufacturing industries," Journal of Environmental Economics and Management, Elsevier, vol. 45(2), pages 278-293, March.
    8. Sebastian Calonico & Matias D. Cattaneo & Rocío Titiunik, 2015. "Optimal Data-Driven Regression Discontinuity Plots," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1753-1769, December.
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    Cited by:

    1. Han Long & Gen‐Fu Feng & Qiang Gong & Chun‐Ping Chang, 2023. "ESG performance and green innovation: An investigation based on quantile regression," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 5102-5118, November.
    2. Jing Tang & Shilong Li, 2022. "How Do Environmental Regulation and Environmental Decentralization Affect Regional Green Innovation? Empirical Research from China," IJERPH, MDPI, vol. 19(12), pages 1-16, June.

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    Keywords

    Environmental Economics and Policy; Research Methods/Statistical Methods; Productivity Analysis;
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