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

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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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Notes

  1. https:// sites.duke.edu/icbdata.

  2. This consists of 8 categories that we have created for rare disaster risks namely, all disasters, violent, war, violent break, protracted, major power, grave, and crisis severity.

  3. Homoscedasticity is a state where the variance of error term remains the same across all the values. Heteroscedasticity is a state of violation of homoscedasticity when the variance of error term does not remain the same. This study follows the tests of Hurn et al. (2015) and Shi et al. (2016) for heteroscedastic-consistent versions. Their studies find that heteroscedastic-consistent tests should be given more emphasis; therefore, this study mainly focuses on the heteroscedastic-consistent estimates.

  4. The ICB (https://sites.duke.edu/icbdata/) provides an overview of these crises events.

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Authors and Affiliations

  1. Othman Yeop Abdullah Graduate School of Business, Universiti Utara Malaysia, Sintok, Kedah, Malaysia

    Arshian Sharif

  2. Department of Business Administration, , Eman Institute of Management and Sciences, Karachi, Pakistan

    Arshian Sharif

  3. Department of Economics, Abdullah Gül University, Kayseri, Turkey

    Eyup Dogan

  4. Assistance Professor, Department of Business Administration, Iqra University, Karachi, Pakistan

    Ameenullah Aman

  5. Faculty of Business and Management, Universiti Teknologi MARA, 08400, Merbok, Kedah, Malaysia

    Hafizah Hammad Ahmad Khan

  6. Assistant Professor, Department of Management Sciences, Bahria University, Karachi, Pakistan

    Isma Zaighum

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  1. Arshian Sharif
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  2. Eyup Dogan
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  3. Ameenullah Aman
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Correspondence to Eyup Dogan.

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Appendix

Appendix

1.1 Variable definitions

We have followed Berkman et al. (2011, 2017) for creating the rare disaster risks variables. For these variables, we use the monthly count for the risk factors falls under various mentioned groups.

(1) a violent break (Violent Break) includes all the crises that starts with a violent act, (2) a violent (Violent) crisis includes all the crises that comprises either serious clashes or full-scale war, (3) a war (War) includes all the crises that involves full-scale wars, (4) all crises that involve grave value threats (Grave Threat), (5) protracted conflicts (Protracted) include all crises with protracted conflict, protracted crisis outside this conflict, and (6) major power (Major Power) includes the crises only if at least one superpower or great power is there in both side of conflict. Finally, we also construct a crisis severity index (Crisis Severity Index) that summarizes different aspects of crisis severity into one measure by aggregating the six variables above.

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Sharif, A., Dogan, E., Aman, A. et al. Rare disaster and renewable energy in the USA: new insights from wavelet coherence and rolling-window analysis. Nat Hazards 103, 2731–2755 (2020). https://doi.org/10.1007/s11069-020-04100-x

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