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Multivariate time–frequency interactions of renewable and non-renewable energy markets with macroeconomic factors in India

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Abstract

Renewable-energy and non-renewable-energy markets have different stabilities, with renewable-energy markets more volatile in India due to the role of renewable-energy and non-renewable-energy in society, and also due to the interactions with external markets (such as macroeconomic and financial markets). These interactions are required to be studied in a tri-variate nexus, considering renewable-energy and non-renewable-energy markets as independent variables. In this study, the interactions of renewable-energy and non-renewable-energy markets with macroeconomic markets (Oil, Coal, Natural Gas, Copper, Gold, Interest Rates and Exchange Rates) from 21 December 2012 to 02 December 2022 were studied. Multiple coherence of Short-Time-Fourier-Transforms of the time-series data enabled creating the tri-variate nexuses. Our findings highlight that non-renewable-energy was correlated to stable markets, while Renewable-Energy was correlated to volatile markets, indicating dual investor behavior, with non-renewable-energy prone to long-term shareholding and renewable-energy prone to short-selling. Further, we observed that Oil, Gas and Coal markets interact significantly with renewable-energy market during financial uncertainty, providing opportunity to hedge renewable-energy and increase market stability. In the post-COVID-19 scenario, exchange rates and Gold markets were identified as critical factors for renewable-energy market stabilization in India, since the coherence frequencies decreased from high to low (high to low volatility). This affirms that investors should couple renewable-energy index to Gold and exchange rate indices during the recovery from an economic shock, which could ensure long-term shareholding behavior in the renewable-energy market.

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Data availability

The codes and data used for this research can be found at: https://doi.org/10.17632/c58jmnbyv7.1.

Notes

  1. 5th highest GDP: https://www.weforum.org/agenda/2022/09/india-uk-fifth-largest-economy-world.

  2. 3rd highest Co2 emissions: https://worldpopulationreview.com/country-rankings/carbon-footprint-by-country.

Abbreviations

RE:

Renewable energy

NRE:

Non-renewable energy

GDP:

Gross domestic product

TROP:

Trade openness

VAR:

Vector auto-regression

ARDL:

Auto-regressive distributed lag

STFT:

Short-time Fourier transform

CWT:

Continuous wavelet transform

WTC:

Wavelet coherence

IEA:

International energy agency

BSE:

Bombay stock exchange

BRICS:

Brazil, Russia, India, China, South Africa

GCC:

Gulf Cooperation Council

G7:

Group of seven

PPA:

Power purchase agreement

SP:

Stock price

FOREX:

Foreign exchange rate

CP:

Copper price

CoP:

Commodity price

GP:

Gold price

REE:

Rare earth element

OP:

Oil price

NG:

Natural gas

WTI:

West Texas intermediate

SENSEX:

Stock exchange sensitive index

COMEX:

Commodity exchange

BRENT:

Broom, Rannoch, Etive, Ness and Tarbert

XAU:

Troy ounce of aurum

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Acknowledgements

The authors are grateful for the financial support from the Japan Science and Technology Agency (JST) of Japan for the doctoral studies of Soumya Basu at Kyoto University. The authors are also grateful to data organizations in India, which have furnished macroeconomic data for academic purposes. The corresponding author is also grateful to colleagues Kavin Paul (Paul K.) for proofreading the manuscript.

Funding

This work was supported by JST SPRING, Grant Number JPMJSP2110, given to Soumya Basu.

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  1. Graduate School of Energy Science, Kyoto University, Yoshidahonmachi, Sakyo-Ku, Kyoto, 606-8501, Japan

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Conceptualization, SB and KNI; methodology, SB and KNI.; software, SB; validation, SB, KNI; formal analysis, SB; investigation, SB; resources, SB; data curation, SB; writing—original draft preparation, SB; writing—review and editing, KNI; visualization, SB; supervision, KNI. All authors have read and agreed to the published version of the manuscript.

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Basu, S., Ishihara, K.N. Multivariate time–frequency interactions of renewable and non-renewable energy markets with macroeconomic factors in India. Energy Syst (2023). https://doi.org/10.1007/s12667-023-00617-9

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