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Economic policy uncertainty and environmental governance company volatility: Evidence from China

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  • Lv, Wendai
  • Qi, Jipeng
  • Feng, Jing

Abstract

This study primarily investigates whether China’s economic policy uncertainty (EPU) can predict the environmental governance index volatility, which selects companies regarding environmental protection such as sewage treatment, solid waste treatment, air treatment, and energy saving. Empirical results reveal that China’s EPU index can predict the environmental governance index volatility. Furthermore, even during periods of fluctuating volatility and the COVID-19 pandemic, China’s EPU index can reliably forecast the environmental governance index volatility. This paper tries to provide new evidence regarding the connection between EPU and environmental governance companies’ stock volatility.

Suggested Citation

  • Lv, Wendai & Qi, Jipeng & Feng, Jing, 2023. "Economic policy uncertainty and environmental governance company volatility: Evidence from China," Research in International Business and Finance, Elsevier, vol. 64(C).
  • Handle: RePEc:eee:riibaf:v:64:y:2023:i:c:s0275531923000016
    DOI: 10.1016/j.ribaf.2023.101875
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    1. Wu, Jie & Lv, Lin & Sun, Jiasen & Ji, Xiang, 2015. "A comprehensive analysis of China's regional energy saving and emission reduction efficiency: From production and treatment perspectives," Energy Policy, Elsevier, vol. 84(C), pages 166-176.
    2. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. Christou, Christina & Cunado, Juncal & Gupta, Rangan & Hassapis, Christis, 2017. "Economic policy uncertainty and stock market returns in PacificRim countries: Evidence based on a Bayesian panel VAR model," Journal of Multinational Financial Management, Elsevier, vol. 40(C), pages 92-102.
    5. Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2016. "Stock Market Volatility and Learning," Journal of Finance, American Finance Association, vol. 71(1), pages 33-82, February.
    6. Feng Ma & Yaojie Zhang & M. I. M. Wahab & Xiaodong Lai, 2019. "The role of jumps in the agricultural futures market on forecasting stock market volatility: New evidence," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(5), pages 400-414, August.
    7. Ahmed, Zahoor & Asghar, Muhammad Mansoor & Malik, Muhammad Nasir & Nawaz, Kishwar, 2020. "Moving towards a sustainable environment: The dynamic linkage between natural resources, human capital, urbanization, economic growth, and ecological footprint in China," Resources Policy, Elsevier, vol. 67(C).
    8. Zahoor Ahmed & Muhammad Mansoor Asghar & Muhammad Nasir Malik & Kishwar Nawaz, 2020. "Moving towards a sustainable environment: The dynamic linkage between natural resources, human capital, urbanization, economic growth, and ecological footprint in China," Post-Print hal-03557938, HAL.
    9. Lu, Xinjie & Ma, Feng & Wang, Jiqian & Zhu, Bo, 2021. "Oil shocks and stock market volatility: New evidence," Energy Economics, Elsevier, vol. 103(C).
    10. Wang, Yizhong & Chen, Carl R. & Huang, Ying Sophie, 2014. "Economic policy uncertainty and corporate investment: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 227-243.
    11. Donadelli, Michael & Persha, Lauren, 2014. "Understanding emerging market equity risk premia: Industries, governance and macroeconomic policy uncertainty," Research in International Business and Finance, Elsevier, vol. 30(C), pages 284-309.
    12. Yen, Kuang-Chieh & Cheng, Hui-Pei, 2021. "Economic policy uncertainty and cryptocurrency volatility," Finance Research Letters, Elsevier, vol. 38(C).
    13. Anis Omri & Fateh Belaïd, 2021. "Does renewable energy modulate the negative effect of environmental issues on the socio-economic welfare?," Post-Print hal-03271499, HAL.
    14. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    15. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.
    16. Ongsakul, Viput & Treepongkaruna, Sirimon & Jiraporn, Pornsit & Uyar, Ali, 2021. "Do firms adjust corporate governance in response to economic policy uncertainty? Evidence from board size," Finance Research Letters, Elsevier, vol. 39(C).
    17. Arouri, Mohamed & Estay, Christophe & Rault, Christophe & Roubaud, David, 2016. "Economic policy uncertainty and stock markets: Long-run evidence from the US," Finance Research Letters, Elsevier, vol. 18(C), pages 136-141.
    18. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    19. Yue Zhu & Ziyuan Sun & Shiyu Zhang & Xiaolin Wang, 2021. "Economic Policy Uncertainty, Environmental Regulation, and Green Innovation—An Empirical Study Based on Chinese High-Tech Enterprises," IJERPH, MDPI, vol. 18(18), pages 1-19, September.
    20. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    21. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    22. Jianguo Liu & Jared Diamond, 2005. "China's environment in a globalizing world," Nature, Nature, vol. 435(7046), pages 1179-1186, June.
    23. Wen, Fenghua & Li, Cui & Sha, Han & Shao, Liuguo, 2021. "How does economic policy uncertainty affect corporate risk-taking? Evidence from China," Finance Research Letters, Elsevier, vol. 41(C).
    24. Engelhardt, Nils & Krause, Miguel & Neukirchen, Daniel & Posch, Peter N., 2021. "Trust and stock market volatility during the COVID-19 crisis," Finance Research Letters, Elsevier, vol. 38(C).
    25. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    26. Steven J. Davis & Dingqian Liu & Xuguang Simon Sheng, 2022. "Stock Prices and Economic Activity in the Time of Coronavirus," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 70(1), pages 32-67, March.
    27. Hossein Asgharian & Ai Jun Hou & Farrukh Javed, 2013. "The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH‐MIDAS Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(7), pages 600-612, November.
    28. Chen, Liming & Du, Ziqing & Hu, Zhihao, 2020. "Impact of economic policy uncertainty on exchange rate volatility of China," Finance Research Letters, Elsevier, vol. 32(C).
    29. Liang, Chao & Ma, Feng & Li, Ziyang & Li, Yan, 2020. "Which types of commodity price information are more useful for predicting US stock market volatility?," Economic Modelling, Elsevier, vol. 93(C), pages 642-650.
    30. Ma, Feng & Wang, Ruoxin & Lu, Xinjie & Wahab, M.I.M., 2021. "A comprehensive look at stock return predictability by oil prices using economic constraint approaches," International Review of Financial Analysis, Elsevier, vol. 78(C).
    31. Yu, Honghai & Fang, Libing & Sun, Wencong, 2018. "Forecasting performance of global economic policy uncertainty for volatility of Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 931-940.
    32. Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
    33. Thomas C. Chiang, 2021. "Geopolitical risk, economic policy uncertainty and asset returns in Chinese financial markets," China Finance Review International, Emerald Group Publishing Limited, vol. 11(4), pages 474-501, March.
    34. Wang, Ziwei & Li, Youwei & He, Feng, 2020. "Asymmetric volatility spillovers between economic policy uncertainty and stock markets: Evidence from China," Research in International Business and Finance, Elsevier, vol. 53(C).
    35. Luo, Yan & Zhang, Chenyang, 2020. "Economic policy uncertainty and stock price crash risk," Research in International Business and Finance, Elsevier, vol. 51(C).
    36. Li, Tao & Ma, Feng & Zhang, Xuehua & Zhang, Yaojie, 2020. "Economic policy uncertainty and the Chinese stock market volatility: Novel evidence," Economic Modelling, Elsevier, vol. 87(C), pages 24-33.
    37. Ji, Qiang & Zhang, Dayong & Zhao, Yuqian, 2020. "Searching for safe-haven assets during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 71(C).
    38. Dawar, Ishaan & Dutta, Anupam & Bouri, Elie & Saeed, Tareq, 2021. "Crude oil prices and clean energy stock indices: Lagged and asymmetric effects with quantile regression," Renewable Energy, Elsevier, vol. 163(C), pages 288-299.
    39. B., Anand & Paul, Sunil, 2021. "Oil shocks and stock market: Revisiting the dynamics," Energy Economics, Elsevier, vol. 96(C).
    40. Wang, Lu & Ma, Feng & Liu, Jing & Yang, Lin, 2020. "Forecasting stock price volatility: New evidence from the GARCH-MIDAS model," International Journal of Forecasting, Elsevier, vol. 36(2), pages 684-694.
    41. Raza, Syed Ali & Zaighum, Isma & Shah, Nida, 2018. "Economic policy uncertainty, equity premium and dependence between their quantiles: Evidence from quantile-on-quantile approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 2079-2091.
    42. Feng Ma & Xinjie Lu & Lu Wang & Julien Chevallier, 2021. "Global economic policy uncertainty and gold futures market volatility: Evidence from Markov regime‐switching GARCH‐MIDAS models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1070-1085, September.
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    2. Ouyang, Minhua & Xiao, Hailian, 2024. "Tail risk spillovers among Chinese stock market sectors," Finance Research Letters, Elsevier, vol. 62(PB).

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