IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v103y2020i3d10.1007_s11069-020-04100-x.html
   My bibliography  Save this article

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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-020-04100-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11069-020-04100-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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. Bouras V. David & Wesseh Wollo, 2021. "Oligopoly Power, Cross-Market Effects and Demand Relatedness: An Empirical Analysis," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 7, ejes_v7_i.
    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.
    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. Waseem Akhter & Khalid Zaman & Abdelmohsen A. Nassani & Muhammad Moinuddin Qazi Abro, 2020. "Nexus between natural and technical disaster shocks, resource depletion and growth-specific factors: evidence from quantile regression," 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. 104(1), pages 143-169, October.
    2. Soni, Rajat Kumar & Nandan, Tanuj, 2022. "Modeling Covid-19 contagious effect between asset markets and commodity futures in India," Resources Policy, Elsevier, vol. 79(C).
    3. Ana Belén Alonso-Conde & Javier Rojo-Suárez, 2020. "Nuclear Hazard and Asset Prices: Implications of Nuclear Disasters in the Cross-Sectional Behavior of Stock Returns," Sustainability, MDPI, vol. 12(22), pages 1-24, November.

    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. Rangan Gupta & Tahir Suleman & Mark E. Wohar, 2019. "The role of time‐varying rare disaster risks in predicting bond returns and volatility," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 327-340, July.
    2. 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.
    3. Marfè, Roberto & Pénasse, Julien, 2024. "Measuring macroeconomic tail risk," Journal of Financial Economics, Elsevier, vol. 156(C).
    4. Roberto Marfè & Julien Penasse, 2016. "The Time-Varying Risk of Macroeconomic Disasters," Carlo Alberto Notebooks 463, Collegio Carlo Alberto.
    5. Ghaderi, Mohammad & Kilic, Mete & Seo, Sang Byung, 2022. "Learning, slowly unfolding disasters, and asset prices," Journal of Financial Economics, Elsevier, vol. 143(1), pages 527-549.
    6. Isoré, Marlène & Szczerbowicz, Urszula, 2017. "Disaster risk and preference shifts in a New Keynesian model," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 97-125.
    7. Robert Barro & Tao Jin, 2021. "Rare Events and Long-Run Risks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 39, pages 1-25, January.
    8. Levintal, Oren, 2017. "Fifth-order perturbation solution to DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 80(C), pages 1-16.
    9. Wen, Jun & Zhao, Xin-Xin & Chang, Chun-Ping, 2021. "The impact of extreme events on energy price risk," Energy Economics, Elsevier, vol. 99(C).
    10. Sönksen, Jantje & Grammig, Joachim, 2021. "Empirical asset pricing with multi-period disaster risk: A simulation-based approach," Journal of Econometrics, Elsevier, vol. 222(1), pages 805-832.
    11. Sergio Rebelo & Neng Wang & Jinqiang Yang, 2022. "Rare Disasters, Financial Development, and Sovereign Debt," Journal of Finance, American Finance Association, vol. 77(5), pages 2719-2764, October.
    12. Robert Barro & Tao Jin, 2021. "Rare Events and Long-Run Risks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 39, pages 1-25, January.
    13. Qunzi Zhang, 2021. "One hundred years of rare disaster concerns and commodity prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 1891-1915, December.
    14. Jerry Tsai & Jessica A. Wachter, 2015. "Disaster Risk and its Implications for Asset Pricing," NBER Working Papers 20926, National Bureau of Economic Research, Inc.
    15. George P. Gao & Xiaomeng Lu & Zhaogang Song, 2019. "Tail Risk Concerns Everywhere," Management Science, INFORMS, vol. 65(7), pages 3111-3130, July.
    16. Jian Chen & Jiaquan Yao & Qunzi Zhang & Xiaoneng Zhu, 2023. "Global Disaster Risk Matters," Management Science, INFORMS, vol. 69(1), pages 576-597, January.
    17. Seong-Hoon Lee & Yonghun Jung, 2018. "Causal dynamics between renewable energy consumption and economic growth in South Korea: Empirical analysis and policy implications," Energy & Environment, , vol. 29(7), pages 1298-1315, November.
    18. Balcilar, Mehmet & Gupta, Rangan & Nel, Jacobus, 2022. "Rare disaster risks and gold over 700 years: Evidence from nonparametric quantile regressions," Resources Policy, Elsevier, vol. 79(C).
    19. Su, Hao & Ying, Chengwei & Zhu, Xiaoneng, 2022. "Disaster risk matters in the bond market," Finance Research Letters, Elsevier, vol. 47(PA).
    20. Robert Barro, 2023. "r Minus g," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 48, pages 1-17, April.

    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:spr:nathaz:v:103:y:2020:i:3:d:10.1007_s11069-020-04100-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.