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The nexus of renewable energy equity and agricultural commodities in the United States: Evidence of regime-switching and price bubbles

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  • Alola, Andrew Adewale

Abstract

The opportunity cost of producing efficient energy from renewable energy sources especially from agricultural products amid increasing threat of food insecurity has remained policymakers’ nightmare. On this note, this study employed the regime inference (the Markov switching model) to examine the response of renewable energy equity relative to prices of corn, soybean and wheat for the United States over the period 20/01/2012 -2/08/2018. Additionally, the SADF (Supremum Augmented Dickey Fuller) test is further employed to investigate the evidence of speculative bubbles in the prices of the concern commodities. With a significant evidence of regime switching, the study reveals positive impacts of soybean and wheat on the renewable energy equity in both regimes while the impact is negative in the regimes for corn prices. The positive impact of soybean is an indication that the share of renewable energy and share of its export is highest while corn is being recently preferred and consumed as stable food rather than a source of renewable energy. Furthermore, a sparing evidence of explosive process and collapse bubbles is observed in all the examined commodities except for soybeans. Moreover, with the frequency domain Granger causality approach, the results show overwhelming evidence of bidirectional Granger causality especially between renewable energy equity and the agricultural commodities at varying frequencies. Thus, the study offers effective policy frameworks through the lens of renewable energy development and agriculture for the United States and for other similar economies.

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  • Alola, Andrew Adewale, 2022. "The nexus of renewable energy equity and agricultural commodities in the United States: Evidence of regime-switching and price bubbles," Energy, Elsevier, vol. 239(PD).
  • Handle: RePEc:eee:energy:v:239:y:2022:i:pd:s0360544221026268
    DOI: 10.1016/j.energy.2021.122377
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    2. Waseem Khan & Vishal Sharma & Saghir Ahmad Ansari, 2022. "Modeling the dynamics of oil and agricultural commodity price nexus in linear and nonlinear frameworks: A case of emerging economy," Review of Development Economics, Wiley Blackwell, vol. 26(3), pages 1733-1784, August.
    3. Arslan, Muhammed & Yılmaz, Ceyhun, 2022. "Thermodynamic Optimization and Thermoeconomic Evaluation of Afyon Biogas Plant assisted by organic Rankine Cycle for waste heat recovery," Energy, Elsevier, vol. 248(C).
    4. Dai, Yun-Shi & Huynh, Ngoc Quang Anh & Zheng, Qing-Huan & Zhou, Wei-Xing, 2022. "Correlation structure analysis of the global agricultural futures market," Research in International Business and Finance, Elsevier, vol. 61(C).
    5. Kocak, Emrah & Bilgili, Faik & Bulut, Umit & Kuskaya, Sevda, 2022. "Is ethanol production responsible for the increase in corn prices?," Renewable Energy, Elsevier, vol. 199(C), pages 689-696.
    6. Wu, Ruirui & Qin, Zhongfeng & Liu, Bing-Yue, 2022. "A systemic analysis of dynamic frequency spillovers among carbon emissions trading (CET), fossil energy and sectoral stock markets: Evidence from China," Energy, Elsevier, vol. 254(PA).
    7. Alola, Andrew Adewale & Özkan, Oktay & Usman, Ojonugwa, 2023. "Examining crude oil price outlook amidst substitute energy price and household energy expenditure in the USA: A novel nonparametric multivariate QQR approach," Energy Economics, Elsevier, vol. 120(C).
    8. Li, Zhuolun, 2023. "Do geopolitical risk, green finance, and the rule of law affect the sustainable environment in China? Findings from the BARDL approach," Resources Policy, Elsevier, vol. 81(C).
    9. Kübra Akyol Özcan, 2023. "Food Price Bubbles: Food Price Indices of Turkey, the FAO, the OECD, and the IMF," Sustainability, MDPI, vol. 15(13), pages 1-21, June.

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    More about this item

    Keywords

    Agricultural prices; Renewable energy equity; Speculative bubbles; Frequency domain causality; United States;
    All these keywords.

    JEL classification:

    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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