Abstract
Based on the spillover effects of pollution and shareholder value theory, this paper constructs a regression discontinuity model using panel data from Chinese manufacturing companies for the period 2015–2020. Using the 'Qinling-Huaihe' line as an instrumental variable, we employ a two-stage least squares approach to estimate the impact mechanism of air pollution on Corporate Shareholder Responsibility Performance (CSRP). The baseline regression results indicate that air pollution significantly inhibits CSRP. Furthermore, we have tested the robustness of these results through sensitivity tests, including bandwidth selection and polynomial-order selection for the assignment variable, adjustments to the time window, the inclusion of omitted variables, the removal of off-site relocated firms, and the replacement of independent and instrumental variables. Additionally, we have found that the relationship between air pollution and CSRP varies among different environmental attributes and regional characteristic subgroups. Mechanistic analyses indicate that the relationship between air pollution and CSRP is positively moderated by environmental regulation and CEO duality. However, economic policy uncertainty does not exert a moderating effect. Additionally, air pollution inhibits CSRP by reducing corporate cash holdings, causing brain drain, and decreasing investment in R&D. Therefore, the control of air pollution is imperative. Environmental governance can be strengthened by broadening financing channels and creating stable institutional environments, thereby enhancing CSRP. Our findings carry significant implications for the development of government macro-policies and corporate environmental decisions.
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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Acknowledgements
The work of author Darko B. Vukovic for his contribution in the paper (investigation, writing—review and editing, supervision, and project administration) has been supported by the RUDN University Strategic Academic Leadership Program (in Priority-2030 RUDN program). The manuscript has supported by RSF for the project No. 22-28-01553 (Making Smart Decisions in the Face of Uncertainty in Russia: Investing and Forecasting in a Crisis). Acknowledgement refers to the author Darko B. Vukovic, who study in-depth examination of an extended set of explanatory variables in complex econometric modeling, that can be used to perform the predictive risk.
Funding
1. This research is funded by the China Scholarship Council (Grant No. 202008090357) for Xiaowei Ding. 2. The manuscript has funded by RSF for the project No. 22-28-01553, for author Darko Vukovic.
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Appendices
Appendix A: Classification of industry environmental attributes
Environmental attributes | Industry category |
|---|---|
Non-heavy polluting industries | Manufacture of measuring instrument; manufacture of special purpose machinery; manufacture of railway, shipbuilding, aerospace and other transportation equipment; manufacture of tobacco; manufacture of automobile; manufacture of articles for culture, education and sport activity; manufacture of general purpose machinery; manufacture of electrical, machinery and equipment; metal products, machinery and equipment repair; manufacture of textile wearing and apparel; ancillary activities for exploitation; printing, reproduction of recording media; manufacture of computers, communication, and other electronic equipment; manufacture of rubber and plastic; other manufactures; manufacture of furniture; others; extraction of petroleum and natural gas; manufacture of metal products; manufacture of medicines |
Heavy polluting industries | Mining and washing of coal; manufacture of leather, fur, feather and related products and footwear; production and supply of gas; processing of timber, manufacture of wood, bamboo, rattan, palm, and straw products; mining of other ores; utilization of waste resources; mining and processing of ferrous metal ores; manufacture of wine, drinks and refined tea; manufacture of textile; manufacture of chemical fibers; manufacture of foods; manufacture of raw chemical materials and chemical products; smelting and pressing of non-ferrous metals; smelting and pressing of ferrous metals; processing of petroleum, coking, processing of nuclear fuel; production and supply of electric power and heat power; manufacture of paper and paper products; mining and processing of non-metal ores; processing of food from agricultural products; manufacture of non-metallic mineral products; mining and processing of non-ferrous metal ores |
Appendix B: List of acronyms
Abbreviations | Full name |
|---|---|
OLS | Ordinary least squares |
2SLS | Two-stage least squares |
NBS | National Bureau of Statistics of China |
CSMAR | China Stock Market and Accounting Research Database |
AIC | Akaike information criterion |
PM2.5 | Particulate matter less than or equal to 2.5 microns in diameter |
AQI | Air quality index |
PM10 | Particulate matter less than or equal to 10 microns in diameter |
CO | Carbon monoxide |
SO2 | Sulfur dioxide |
CSY | China Statistical Yearbook |
CESY | China Environment Statistical Yearbook |
COD | Chemical oxygen demand |
IPE | Industry pollutant emissions |
ITA | Industry total assets |
RPEI | Ratio of pollutant emissions to total assets for each industry |
IPEIAI | Industry pollution emission intensity average annual index |
NCEI | National centers for environmental information |
NOAA | National oceanic and atmospheric administration |
SOEs | State-owned enterprises |
Non-SOEs | Non-state-owned enterprises |
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Ding, X., Vukovic, D.B., Shams, R. et al. Does air pollution affect corporate shareholder responsibility performance?: Analysis of regression discontinuity design based on the "Qinling-Huaihe" line. Environ Dev Sustain (2023). https://doi.org/10.1007/s10668-023-04063-6
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DOI: https://doi.org/10.1007/s10668-023-04063-6
Keywords
- Air pollution
- Qinling-Huaihe line
- Shareholder responsibility performance
- Regression discontinuity design
- Impact mechanism
- China