IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i6p1719-d148836.html
   My bibliography  Save this article

Interaction between Industrial Policy and Stock Price Volatility: Evidence from China’s Power Market Reform

Author

Listed:
  • Ye Fan

    (School of Business Administration, China University of Petroleum-Beijing, Beijing 102246, China)

  • Zhicheng Zhang

    (Department of Economics, University of Michigan, Ann Arbor, MI 48104, USA)

  • Xiaoli Zhao

    (School of Business Administration, China University of Petroleum-Beijing, Beijing 102246, China)

  • Haitao Yin

    (Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200052, China)

Abstract

This paper examines how China’s power market reform influences the stock price volatility of listed power companies. We use the Iterative Cumulative Sums of Squares (ICSS) algorithm to identify structural breakpoints in stock prices, then analyze the characteristics of stock price volatility based on the GARCH model and report the impact of power regulation on stock price fluctuations based on the Autoregressive Distributed Lag (ARDL) model. Using data on power stock price index followed by industrial policy issued between 2006 and 2012, we find that: (1) three structural breaks in China’s power stock price volatility were related to the promulgation of power market reform policies; (2) industrial policies promote the reduction of power stock price fluctuations and its impact on power stock price volatility is consistent in the long run; and (3) the recent policies related to renewable energy do not have a very significant impact on the power stock market.

Suggested Citation

  • Ye Fan & Zhicheng Zhang & Xiaoli Zhao & Haitao Yin, 2018. "Interaction between Industrial Policy and Stock Price Volatility: Evidence from China’s Power Market Reform," Sustainability, MDPI, vol. 10(6), pages 1-19, May.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:6:p:1719-:d:148836
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/6/1719/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/6/1719/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Meng, Ming & Mander, Sarah & Zhao, Xiaoli & Niu, Dongxiao, 2016. "Have market-oriented reforms improved the electricity generation efficiency of China's thermal power industry? An empirical analysis," Energy, Elsevier, vol. 114(C), pages 734-741.
    2. Du, Limin & Mao, Jie & Shi, Jinchuan, 2009. "Assessing the impact of regulatory reforms on China's electricity generation industry," Energy Policy, Elsevier, vol. 37(2), pages 712-720, February.
    3. Mariacristina Piva & Marco Vivarelli, 2018. "Is Innovation Destroying Jobs? Firm-Level Evidence from the EU," Sustainability, MDPI, vol. 10(4), pages 1-16, April.
    4. Blattberg, Robert C & Gonedes, Nicholas J, 1974. "A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices," The Journal of Business, University of Chicago Press, vol. 47(2), pages 244-280, April.
    5. Kevin Lo, 2015. "Governing China’s Clean Energy Transition: Policy Reforms, Flexible Implementation and the Need for Empirical Investigation," Energies, MDPI, vol. 8(11), pages 1-10, November.
    6. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    7. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-1153, December.
    8. Ming, Zeng & Song, Xue & Lingyun, Li & Yuejin, Wang & Yang, Wei & Ying, Li, 2013. "China's large-scale power shortages of 2004 and 2011 after the electricity market reforms of 2002: Explanations and differences," Energy Policy, Elsevier, vol. 61(C), pages 610-618.
    9. Ma, Chunbo & He, Lining, 2008. "From state monopoly to renewable portfolio: Restructuring China's electric utility," Energy Policy, Elsevier, vol. 36(5), pages 1697-1711, May.
    10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    11. Huiru Zhao & Haoran Zhao & Sen Guo & Fuqiang Li & Yuou Hu, 2016. "The Impact of Financial Crisis on Electricity Demand: A Case Study of North China," Energies, MDPI, vol. 9(4), pages 1-13, March.
    12. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
    13. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    14. Fama, Eugene F, 1990. "Stock Returns, Expected Returns, and Real Activity," Journal of Finance, American Finance Association, vol. 45(4), pages 1089-1108, September.
    15. Wang, Ping & Moore, Tomoe, 2009. "Sudden changes in volatility: The case of five central European stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(1), pages 33-46, February.
    16. Hammoudeh, Shawkat & Li, Huimin, 2008. "Sudden changes in volatility in emerging markets: The case of Gulf Arab stock markets," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 47-63.
    17. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    18. Babikir, Ali & Gupta, Rangan & Mwabutwa, Chance & Owusu-Sekyere, Emmanuel, 2012. "Structural breaks and GARCH models of stock return volatility: The case of South Africa," Economic Modelling, Elsevier, vol. 29(6), pages 2435-2443.
    19. Theologos Dergiades & Costas Milas & Theodore Panagiotidis, 2017. "An assessment of the inflation targeting experience," Bank of Estonia Working Papers wp2017-11, Bank of Estonia, revised 09 Nov 2017.
    20. Narayan, Paresh Kumar & Zheng, Xinwei, 2010. "Market liquidity risk factor and financial market anomalies: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 18(5), pages 509-520, November.
    21. Perron, Pierre, 1997. "Further evidence on breaking trend functions in macroeconomic variables," Journal of Econometrics, Elsevier, vol. 80(2), pages 355-385, October.
    22. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    23. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    24. Theologos Dergiades & Lefteris Tsoulfidis, 2009. "Revisiting Residential Demand for Electricity in Greece: New Evidence from the ARDL Approach to Cointegration," Discussion Paper Series 2009_12, Department of Economics, University of Macedonia, revised Jun 2009.
    25. Malik, Farooq, 2003. "Sudden changes in variance and volatility persistence in foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 13(3), pages 217-230, July.
    26. Robin L. Lumsdaine & David H. Papell, 1997. "Multiple Trend Breaks And The Unit-Root Hypothesis," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 212-218, May.
    27. Rushdi, Mustabshira & Kim, Jae H. & Silvapulle, Param, 2012. "ARDL bounds tests and robust inference for the long run relationship between real stock returns and inflation in Australia," Economic Modelling, Elsevier, vol. 29(3), pages 535-543.
    28. Beltratti, A. & Morana, C., 2006. "Breaks and persistency: macroeconomic causes of stock market volatility," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 151-177.
    29. Theologos Dergiades & Lefteris Tsoulfidis, 2011. "Revisiting residential demand for electricity in Greece: new evidence from the ARDL approach to cointegration analysis," Empirical Economics, Springer, vol. 41(2), pages 511-531, October.
    30. Adnan Kasman, 2009. "The impact of sudden changes on the persistence of volatility: evidence from the BRIC countries," Applied Economics Letters, Taylor & Francis Journals, vol. 16(7), pages 759-764.
    31. Chihyoun Ahn & Mi-Ok Kim & Hyung-Rok Jung, 2017. "The Effects of Operational Structure Change on Performance after Seasoned Equity Offerings," Sustainability, MDPI, vol. 10(1), pages 1-17, December.
    32. Malik, Farooq & Hammoudeh, Shawkat, 2007. "Shock and volatility transmission in the oil, US and Gulf equity markets," International Review of Economics & Finance, Elsevier, vol. 16(3), pages 357-368.
    33. Mou, Dunguo, 2014. "Understanding China’s electricity market reform from the perspective of the coal-fired power disparity," Energy Policy, Elsevier, vol. 74(C), pages 224-234.
    34. Zhang, Sufang & Andrews-Speed, Philip & Li, Sitao, 2018. "To what extent will China's ongoing electricity market reforms assist the integration of renewable energy?," Energy Policy, Elsevier, vol. 114(C), pages 165-172.
    35. Yingyuan Guo & Xingneng Xia & Sheng Zhang & Danping Zhang, 2018. "Environmental Regulation, Government R&D Funding and Green Technology Innovation: Evidence from China Provincial Data," Sustainability, MDPI, vol. 10(4), pages 1-21, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Yongli & Zhang, Fuli & Zhang, Yuanyuan & Wang, Xiaohai & Fan, Lisha & Song, Fuhao & Ma, Yuze & Wang, Shuo, 2019. "Chinese power-grid financial capacity based on transmission and distribution tariff policy: A system dynamics approach," Utilities Policy, Elsevier, vol. 60(C), pages 1-1.
    2. Wang, Ze & Gao, Xiangyun & An, Haizhong & Tang, Renwu & Sun, Qingru, 2020. "Identifying influential energy stocks based on spillover network," International Review of Financial Analysis, Elsevier, vol. 68(C).
    3. Zhifeng Dai & Huiting Zhou, 2020. "Prediction of Stock Returns: Sum-of-the-Parts Method and Economic Constraint Method," Sustainability, MDPI, vol. 12(2), pages 1-13, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. F. Dilvin Taşkin & Efe Çağlar Çağlı & Umut Halaç, 2016. "The impact of oil price shocks on the volatility of the Turkish stock market," International Journal of Accounting and Finance, Inderscience Enterprises Ltd, vol. 6(1), pages 1-23.
    2. Charles, Amélie & Darné, Olivier, 2014. "Volatility persistence in crude oil markets," Energy Policy, Elsevier, vol. 65(C), pages 729-742.
    3. Hasanov, Akram Shavkatovich & Poon, Wai Ching & Al-Freedi, Ajab & Heng, Zin Yau, 2018. "Forecasting volatility in the biofuel feedstock markets in the presence of structural breaks: A comparison of alternative distribution functions," Energy Economics, Elsevier, vol. 70(C), pages 307-333.
    4. Erragragui, Elias & Hassan, M. Kabir & Peillex, Jonathan & Khan, Abu Nahian Faisal, 2018. "Does ethics improve stock market resilience in times of instability?," Economic Systems, Elsevier, vol. 42(3), pages 450-469.
    5. Bruce Q. Budd, 2018. "The transmission of international stock market volatilities," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(1), pages 155-173, January.
    6. Charfeddine, Lanouar & Ajmi, Ahdi Noomen, 2013. "The Tunisian stock market index volatility: Long memory vs. switching regime," Emerging Markets Review, Elsevier, vol. 16(C), pages 170-182.
    7. King, Daniel & Botha, Ferdi, 2015. "Modelling stock return volatility dynamics in selected African markets," Economic Modelling, Elsevier, vol. 45(C), pages 50-73.
    8. Kumar, Dilip, 2015. "Sudden changes in extreme value volatility estimator: Modeling and forecasting with economic significance analysis," Economic Modelling, Elsevier, vol. 49(C), pages 354-371.
    9. Dimitrios Kartsonakis-Mademlis & Nikolaos Dritsakis, 2022. "Asymmetric volatility transmission in Japanese stock market in the presence of structural breaks," The Japanese Economic Review, Springer, vol. 73(4), pages 647-677, October.
    10. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    11. Dutta, Shantanu & Essaddam, Naceur & Kumar, Vinod & Saadi, Samir, 2017. "How does electronic trading affect efficiency of stock market and conditional volatility? Evidence from Toronto Stock Exchange," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 867-877.
    12. Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
    13. Huang, Alex YiHou & Peng, Sheng-Pen & Li, Fangjhy & Ke, Ching-Jie, 2011. "Volatility forecasting of exchange rate by quantile regression," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 591-606, October.
    14. Köksal, Bülent, 2009. "A Comparison of Conditional Volatility Estimators for the ISE National 100 Index Returns," MPRA Paper 30510, University Library of Munich, Germany.
    15. Clements, A. & Silvennoinen, A., 2013. "Volatility timing: How best to forecast portfolio exposures," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 108-115.
    16. Ardia, David & Bluteau, Keven & Boudt, Kris & Catania, Leopoldo, 2018. "Forecasting risk with Markov-switching GARCH models:A large-scale performance study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 733-747.
    17. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    18. Ahmad Zubaidi Baharumshah & Akram Hasanov & Stilianos Fountas, 2011. "Inflation and inflation uncertainty: Evidence from two Transition Economies," Discussion Paper Series 2011_05, Department of Economics, University of Macedonia, revised Apr 2011.
    19. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, August.
    20. Nidhi Choudhary & Girish K. Nair & Harsh Purohit, 2015. "Volatility In Copper Prices In India," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-26, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:6:p:1719-:d:148836. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.