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Rare disaster and renewable energy in the USA: new insights from wavelet coherence and rolling-window analysis

Author

Listed:
  • Arshian Sharif

    (Universiti Utara Malaysia
    Eman Institute of Management and Sciences)

  • Eyup Dogan

    (Abdullah Gül University)

  • Ameenullah Aman

    (Iqra University)

  • Hafizah Hammad Ahmad Khan

    (Universiti Teknologi MARA)

  • Isma Zaighum

    (Bahria University)

Abstract

The increasing trend of economic and political crises in different parts of the world has made global economies highly vulnerable because of having globally as well as regionally integrated economic systems. In such an environment, switching to alternative energy products, such as renewable energy production, may be devastating. Therefore, the aim of this paper is to provide novel insights for the relationship between rare disaster risks and renewable energy production (REN) of the USA by utilizing the time series monthly data from 1973 to 2016. Using time-varying continuous wavelet power spectrum, the wavelet coherence, and the modified bootstrap rolling-window analysis, the results reveal significant linkages between all the categories of rare disaster risks and renewable energy production. Rare disaster risks and REN are linked with each other, and both the variables have time-varying cyclic and anti-cyclic effects on each other with robust and significant predictability from rare disasters to REN. These findings have novel implications for many stakeholders. For instance, producers of energy may safely switch to renewable energy production since disasters are found to have potential to leave cyclic effect on renewable energy at most.

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  • Arshian Sharif & Eyup Dogan & Ameenullah Aman & Hafizah Hammad Ahmad Khan & Isma Zaighum, 2020. "Rare disaster and renewable energy in the USA: new insights from wavelet coherence and rolling-window analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 2731-2755, September.
    • Handle: RePEc:spr:nathaz:v:103:y:2020:i:3:d:10.1007_s11069-020-04100-x
    DOI: 10.1007/s11069-020-04100-x
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    References listed on IDEAS

    as
    1. Shahzad, Syed Jawad Hussain & Naifar, Nader & Hammoudeh, Shawkat & Roubaud, David, 2017. "Directional predictability from oil market uncertainty to sovereign credit spreads of oil-exporting countries: Evidence from rolling windows and crossquantilogram analysis," Energy Economics, Elsevier, vol. 68(C), pages 327-339.
    2. Mantalos Panagiotis, 2000. "A Graphical Investigation of the Size and Power of the Granger-Causality Tests in Integrated-Cointegrated VAR Systems," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 4(1), pages 1-18, April.
    3. Elbasha, Elamin H. & Roe, Terry L., 1995. "Environment in Three Classes of Endogenous Growth Models," Bulletins 7474, University of Minnesota, Economic Development Center.
    4. Robert J. Barro & Tao Jin, 2011. "On the Size Distribution of Macroeconomic Disasters," Econometrica, Econometric Society, vol. 79(5), pages 1567-1589, September.
    5. Luís Aguiar-Conraria & Maria Soares, 2011. "Oil and the macroeconomy: using wavelets to analyze old issues," Empirical Economics, Springer, vol. 40(3), pages 645-655, May.
    6. Sadorsky, Perry, 2012. "Modeling renewable energy company risk," Energy Policy, Elsevier, vol. 40(C), pages 39-48.
    7. Kim, Kyeongseok & Park, Hyoungbae & Kim, Hyoungkwan, 2017. "Real options analysis for renewable energy investment decisions in developing countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 918-926.
    8. Henk Berkman & Ben Jacobsen & John B. Lee, 2017. "Rare disaster risk and the expected equity risk premium," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(2), pages 351-372, June.
    9. Zafar, Muhammad Wasif & Shahbaz, Muhammad & Sinha, Avik & Sengupta, Tuhin & Qin, Quande, 2020. "How Renewable Energy Consumption Contribute to Environmental Quality? The Role of Education in OECD Countries," MPRA Paper 100259, University Library of Munich, Germany, revised 08 May 2020.
    10. Shahbaz, Muhammad & Zeshan, Muhammad & Afza, Talat, 2012. "Is energy consumption effective to spur economic growth in Pakistan? New evidence from bounds test to level relationships and Granger causality tests," Economic Modelling, Elsevier, vol. 29(6), pages 2310-2319.
    11. Chen, Wei-Ming & Kim, Hana & Yamaguchi, Hideka, 2014. "Renewable energy in eastern Asia: Renewable energy policy review and comparative SWOT analysis for promoting renewable energy in Japan, South Korea, and Taiwan," Energy Policy, Elsevier, vol. 74(C), pages 319-329.
    12. Bhattacharya, Anindya & Kojima, Satoshi, 2012. "Power sector investment risk and renewable energy: A Japanese case study using portfolio risk optimization method," Energy Policy, Elsevier, vol. 40(C), pages 69-80.
    13. Alper, Aslan & Oguz, Ocal, 2016. "The role of renewable energy consumption in economic growth: Evidence from asymmetric causality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 953-959.
    14. Demirer, Riza & Gupta, Rangan & Suleman, Tahir & Wohar, Mark E., 2018. "Time-varying rare disaster risks, oil returns and volatility," Energy Economics, Elsevier, vol. 75(C), pages 239-248.
    15. Alvarez-Herranz, Agustin & Balsalobre-Lorente, Daniel & Shahbaz, Muhammad & Cantos, José María, 2017. "Energy innovation and renewable energy consumption in the correction of air pollution levels," Energy Policy, Elsevier, vol. 105(C), pages 386-397.
    16. Menyah, Kojo & Wolde-Rufael, Yemane, 2010. "CO2 emissions, nuclear energy, renewable energy and economic growth in the US," Energy Policy, Elsevier, vol. 38(6), pages 2911-2915, June.
    17. Liu, Ximei & Zeng, Ming, 2017. "Renewable energy investment risk evaluation model based on system dynamics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 782-788.
    18. Xavier Gabaix, 2012. "Variable Rare Disasters: An Exactly Solved Framework for Ten Puzzles in Macro-Finance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 127(2), pages 645-700.
    19. Wu, Yunna & Wang, Jing & Ji, Shaoyu & Song, Zixin, 2020. "Renewable energy investment risk assessment for nations along China’s Belt & Road Initiative: An ANP-cloud model method," Energy, Elsevier, vol. 190(C).
    20. Zapata, Hector O & Rambaldi, Alicia N, 1997. "Monte Carlo Evidence on Cointegration and Causation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 59(2), pages 285-298, May.
    21. Francois Gourio, 2012. "Disaster Risk and Business Cycles," American Economic Review, American Economic Association, vol. 102(6), pages 2734-2766, October.
    22. Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2019. "Exchange rate returns and volatility: the role of time-varying rare disaster risks," The European Journal of Finance, Taylor & Francis Journals, vol. 25(2), pages 190-203, January.
    23. Aviral Tiwari & Niyati Bhanja & Arif Dar & Faridul Islam, 2015. "Time–frequency relationship between share prices and exchange rates in India: Evidence from continuous wavelets," Empirical Economics, Springer, vol. 48(2), pages 699-714, March.
    24. Aguiar-Conraria, Luís & Azevedo, Nuno & Soares, Maria Joana, 2008. "Using wavelets to decompose the time–frequency effects of monetary policy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2863-2878.
    25. Gatzert, Nadine & Kosub, Thomas, 2016. "Risks and risk management of renewable energy projects: The case of onshore and offshore wind parks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 982-998.
    26. Menegaki, Angeliki N., 2011. "Growth and renewable energy in Europe: A random effect model with evidence for neutrality hypothesis," Energy Economics, Elsevier, vol. 33(2), pages 257-263, March.
    27. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2017. "Wavelet-based test of co-movement and causality between oil and renewable energy stock prices," Energy Economics, Elsevier, vol. 61(C), pages 241-252.
    28. Jessica A. Wachter, 2013. "Can Time-Varying Risk of Rare Disasters Explain Aggregate Stock Market Volatility?," Journal of Finance, American Finance Association, vol. 68(3), pages 987-1035, June.
    29. Emmanuel Farhi & Xavier Gabaix, 2016. "Editor's Choice Rare Disasters and Exchange Rates," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(1), pages 1-52.
    30. Rietz, Thomas A., 1988. "The equity risk premium a solution," Journal of Monetary Economics, Elsevier, vol. 22(1), pages 117-131, July.
    31. Emi Nakamura & Jón Steinsson & Robert Barro & José Ursúa, 2013. "Crises and Recoveries in an Empirical Model of Consumption Disasters," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(3), pages 35-74, July.
    32. Paresh Kumar Narayan & Stephan Popp, 2010. "A new unit root test with two structural breaks in level and slope at unknown time," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(9), pages 1425-1438.
    33. Sahbi Farhani & Daniel Balsalobre-Lorente, 2020. "Comparing the Role of Coal to Other Energy Resources in the Environmental Kuznets Curve of Three Large Economies," Chinese Economy, Taylor & Francis Journals, vol. 53(1), pages 82-120, January.
    34. Robert J. Barro, 2009. "Rare Disasters, Asset Prices, and Welfare Costs," American Economic Review, American Economic Association, vol. 99(1), pages 243-264, March.
    35. Esteban, Miguel & Portugal-Pereira, Joana, 2014. "Post-disaster resilience of a 100% renewable energy system in Japan," Energy, Elsevier, vol. 68(C), pages 756-764.
    36. Manela, Asaf & Moreira, Alan, 2017. "News implied volatility and disaster concerns," Journal of Financial Economics, Elsevier, vol. 123(1), pages 137-162.
    37. Berkman, Henk & Jacobsen, Ben & Lee, John B., 2011. "Time-varying rare disaster risk and stock returns," Journal of Financial Economics, Elsevier, vol. 101(2), pages 313-332, August.
    38. Kim Sangbae & In Francis Haeuck, 2003. "The Relationship Between Financial Variables and Real Economic Activity: Evidence From Spectral and Wavelet Analyses," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-18, December.
    39. Chang, Tsangyao & Gupta, Rangan & Inglesi-Lotz, Roula & Simo-Kengne, Beatrice & Smithers, Devon & Trembling, Amy, 2015. "Renewable energy and growth: Evidence from heterogeneous panel of G7 countries using Granger causality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1405-1412.
    40. Natalia Nehrebecka & Aneta Dzik-Walczak, 2019. "Collateral and Bank Credit - a Puzzle," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 5, September.
    41. Bhattacharya, Mita & Paramati, Sudharshan Reddy & Ozturk, Ilhan & Bhattacharya, Sankar, 2016. "The effect of renewable energy consumption on economic growth: Evidence from top 38 countries," Applied Energy, Elsevier, vol. 162(C), pages 733-741.
    42. Martin L. Weitzman, 2007. "Subjective Expectations and Asset-Return Puzzles," American Economic Review, American Economic Association, vol. 97(4), pages 1102-1130, September.
    43. Bird, Deanne K. & Haynes, Katharine & van den Honert, Rob & McAneney, John & Poortinga, Wouter, 2014. "Nuclear power in Australia: A comparative analysis of public opinion regarding climate change and the Fukushima disaster," Energy Policy, Elsevier, vol. 65(C), pages 644-653.
    44. Alagappan, L. & Orans, R. & Woo, C.K., 2011. "What drives renewable energy development?," Energy Policy, Elsevier, vol. 39(9), pages 5099-5104, September.
    45. Wu, Jung-Hua & Huang, Yun-Hsun, 2014. "Electricity portfolio planning model incorporating renewable energy characteristics," Applied Energy, Elsevier, vol. 119(C), pages 278-287.
    46. Belloumi, Mounir, 2009. "Energy consumption and GDP in Tunisia: Cointegration and causality analysis," Energy Policy, Elsevier, vol. 37(7), pages 2745-2753, July.
    47. Holburn, Guy L.F., 2012. "Assessing and managing regulatory risk in renewable energy: Contrasts between Canada and the United States," Energy Policy, Elsevier, vol. 45(C), pages 654-665.
    48. Shadman, F. & Sadeghipour, S. & Moghavvemi, M. & Saidur, R., 2016. "Drought and energy security in key ASEAN countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 50-58.
    49. Wüstenhagen, Rolf & Menichetti, Emanuela, 2012. "Strategic choices for renewable energy investment: Conceptual framework and opportunities for further research," Energy Policy, Elsevier, vol. 40(C), pages 1-10.
    50. Gatto, Andrea & Drago, Carlo, 2020. "Measuring and modeling energy resilience," Ecological Economics, Elsevier, vol. 172(C).
    51. Apergis, Nicholas & Payne, James E. & Menyah, Kojo & Wolde-Rufael, Yemane, 2010. "On the causal dynamics between emissions, nuclear energy, renewable energy, and economic growth," Ecological Economics, Elsevier, vol. 69(11), pages 2255-2260, September.
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