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The role of biodiversity and energy transition in shaping the next techno-economic era

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  • Shen, Lihua
  • Zhou, Jianan

Abstract

Destructive extreme weather caused by climate change causes severe biodiversity loss, prompting us to accelerate the energy transition to net-zero emissions to achieve green sustainability goals. Thus, this paper aims to examine the relationship between biodiversity risks and the energy transition. We choose to use four indicators—carbon emissions (COE), the energy financial market (COE), climate policy uncertainty (CPU), and the world production industry (WPI)—to characterize the energy transition process and use newly constructed global biodiversity attention indicator (GBAI) to characterize biodiversity risks. We find a significant feedback relationship between the GBAI and the COE (CPU), which also confirms the close connection between climate and biodiversity. Second, we find a long-term feedback mechanism between the GBAI and COE (CPU\WPI), but only the GBAI and the COE have a feedback mechanism in the short term. Finally, the impact of the GBAI on the COE (CPU) occurs over a short period, while the impact of the COE (WPI) on the GBAI occurs over multiple periods. Therefore, these detectable feedback relationships prompt us to adjust short- and long-term environmentally friendly policies related to climate and carbon emissions.

Suggested Citation

  • Shen, Lihua & Zhou, Jianan, 2024. "The role of biodiversity and energy transition in shaping the next techno-economic era," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
  • Handle: RePEc:eee:tefoso:v:208:y:2024:i:c:s0040162524004980
    DOI: 10.1016/j.techfore.2024.123700
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    as
    1. Mensi, Walid & Rehman, Mobeen Ur & Maitra, Debasish & Al-Yahyaee, Khamis Hamed & Vo, Xuan Vinh, 2021. "Oil, natural gas and BRICS stock markets: Evidence of systemic risks and co-movements in the time-frequency domain," Resources Policy, Elsevier, vol. 72(C).
    2. Lau, Chi Keung & Mahalik, Mantu Kumar & Rather, Kashif Nesar & Gozgor, Giray, 2023. "The impact of green quality of the energy consumption on carbon emissions in the United States," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 850-860.
    3. Lu, Feng-bin & Hong, Yong-miao & Wang, Shou-yang & Lai, Kin-keung & Liu, John, 2014. "Time-varying Granger causality tests for applications in global crude oil markets," Energy Economics, Elsevier, vol. 42(C), pages 289-298.
    4. Danyang Cheng, 2024. "Advancing towards carbon-neutral events," Nature Climate Change, Nature, vol. 14(1), pages 19-19, January.
    5. Umar, Muhammad & Farid, Saqib & Naeem, Muhammad Abubakr, 2022. "Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis," Energy, Elsevier, vol. 240(C).
    6. Costanza, Robert & d'Arge, Ralph & de Groot, Rudolf & Farber, Stephen & Grasso, Monica & Hannon, Bruce & Limburg, Karin & Naeem, Shahid & O'Neill, Robert V. & Paruelo, Jose, 1998. "The value of the world's ecosystem services and natural capital," Ecological Economics, Elsevier, vol. 25(1), pages 3-15, April.
    7. Su, Chi-Wei & Yuan, Xi & Tao, Ran & Shao, Xuefeng, 2022. "Time and frequency domain connectedness analysis of the energy transformation under climate policy," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    8. Gozgor, Giray & Paramati, Sudharshan Reddy, 2022. "Does energy diversification cause an economic slowdown? Evidence from a newly constructed energy diversification index," Energy Economics, Elsevier, vol. 109(C).
    9. Hong, Yanran & Wang, Lu & Ye, Xiaoqing & Zhang, Yaojie, 2022. "Dynamic asymmetric impact of equity market uncertainty on energy markets: A time-varying causality analysis," Renewable Energy, Elsevier, vol. 196(C), pages 535-546.
    10. Granger, Clive W. J. & Huangb, Bwo-Nung & Yang, Chin-Wei, 2000. "A bivariate causality between stock prices and exchange rates: evidence from recent Asianflu," The Quarterly Review of Economics and Finance, Elsevier, vol. 40(3), pages 337-354.
    11. Bahmani-Oskooee, Mohsen & Chang, Tsangyao & Ranjbar, Omid, 2016. "Asymmetric causality using frequency domain and time-frequency domain (wavelet) approaches," Economic Modelling, Elsevier, vol. 56(C), pages 66-78.
    12. Emodi, Nnaemeka Vincent & Emodi, Chinenye Comfort & Murthy, Girish Panchakshara & Emodi, Adaeze Saratu Augusta, 2017. "Energy policy for low carbon development in Nigeria: A LEAP model application," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 247-261.
    13. R. Scott Hacker & Abdulnasser Hatemi-J, 2005. "A test for multivariate ARCH effects," Applied Economics Letters, Taylor & Francis Journals, vol. 12(7), pages 411-417.
    14. Christiane Baumeister & James D. Hamilton, 2019. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks," American Economic Review, American Economic Association, vol. 109(5), pages 1873-1910, May.
    15. Qin, Meng & Zhu, Yujie & Xie, Xin & Shao, Xuefeng & Lobonţ, Oana-Ramona, 2024. "The impact of climate risk on technological progress under the fourth industrial era," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    16. Shuping Shi & Stan Hurn & Peter C B Phillips, 2020. "Causal Change Detection in Possibly Integrated Systems: Revisiting the Money–Income Relationship [Energy Consumption and Economic Growth in the United States]," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 18(1), pages 158-180.
    17. Shuping Shi & Peter C. B. Phillips & Stan Hurn, 2018. "Change Detection and the Causal Impact of the Yield Curve," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 966-987, November.
    18. Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
    19. Ferreira, João J.M. & Fernandes, Cristina I. & Ferreira, Fernando A.F., 2020. "Technology transfer, climate change mitigation, and environmental patent impact on sustainability and economic growth: A comparison of European countries," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    20. Zhang, Hailing & Liu, Changxin & Wang, Can, 2021. "Extreme climate events and economic impacts in China: A CGE analysis with a new damage function in IAM," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    21. Liang, Chao & Umar, Muhammad & Ma, Feng & Huynh, Toan L.D., 2022. "Climate policy uncertainty and world renewable energy index volatility forecasting," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    22. Ren, Xiaohang & Zhang, Xiao & Yan, Cheng & Gozgor, Giray, 2022. "Climate policy uncertainty and firm-level total factor productivity: Evidence from China," Energy Economics, Elsevier, vol. 113(C).
    23. Sun, Yunpeng & Jia, Ruoya & Razzaq, Asif & Bao, Qun, 2024. "Social network platforms and climate change in China: Evidence from TikTok," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    24. Breitung, Jorg & Candelon, Bertrand, 2006. "Testing for short- and long-run causality: A frequency-domain approach," Journal of Econometrics, Elsevier, vol. 132(2), pages 363-378, June.
    25. Lau, Chi Keung & Gozgor, Giray & Mahalik, Mantu Kumar & Patel, Gupteswar & Li, Jing, 2023. "Introducing a new measure of energy transition: Green quality of energy mix and its impact on CO2 emissions," Energy Economics, Elsevier, vol. 122(C).
    26. Omri, Anis & Ben Jabeur, Sami, 2024. "Climate policies and legislation for renewable energy transition: The roles of financial sector and political institutions," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    27. G. Andrew Karolyi & John Tobin‐de la Puente, 2023. "Biodiversity finance: A call for research into financing nature," Financial Management, Financial Management Association International, vol. 52(2), pages 231-251, June.
    28. Kuramochi, Takeshi, 2015. "Review of energy and climate policy developments in Japan before and after Fukushima," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 1320-1332.
    29. Dong, Liang & Gu, Fumei & Fujita, Tsuyoshi & Hayashi, Yoshitsugu & Gao, Jie, 2014. "Uncovering opportunity of low-carbon city promotion with industrial system innovation: Case study on industrial symbiosis projects in China," Energy Policy, Elsevier, vol. 65(C), pages 388-397.
    30. Xi, Yue & Huynh, Anh Ngoc Quang & Jiang, Yushi & Hong, Yanran, 2023. "Energy transition concern: Time-varying effect of climate policy uncertainty on renewables consumption," Technological Forecasting and Social Change, Elsevier, vol. 192(C).
    31. Chishti, Muhammad Zubair & Sinha, Avik & Zaman, Umer & Shahzad, Umer, 2023. "Exploring the dynamic connectedness among energy transition and its drivers: Understanding the moderating role of global geopolitical risk," Energy Economics, Elsevier, vol. 119(C).
    32. Giglio, Stefano & Kuchler, Theresa & Stroebel, Johannes & Zeng, Xuran, 2023. "Biodiversity Risk," SocArXiv n7pbj_v1, Center for Open Science.
    33. Hong, Yanran & Cao, Shijiao & Xu, Pengfei & Pan, Zhigang, 2024. "Interpreting the effect of global economic risks on crude oil market: A supply-demand perspective," International Review of Financial Analysis, Elsevier, vol. 91(C).
    34. Ulf Riebesell, 2008. "Acid test for marine biodiversity," Nature, Nature, vol. 454(7200), pages 46-47, July.
    35. Al-mulali, Usama, 2011. "Oil consumption, CO2 emission and economic growth in MENA countries," Energy, Elsevier, vol. 36(10), pages 6165-6171.
    36. Adams, Samuel & Adedoyin, Festus & Olaniran, Eniola & Bekun, Festus Victor, 2020. "Energy consumption, economic policy uncertainty and carbon emissions; causality evidence from resource rich economies," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 179-190.
    37. Sinha, Avik & Bekiros, Stelios & Hussain, Nazim & Nguyen, Duc Khuong & Khan, Sana Akbar, 2023. "How social imbalance and governance quality shape policy directives for energy transition in the OECD countries?," Energy Economics, Elsevier, vol. 120(C).
    38. Felix Creutzig & Peter Agoston & Jan Christoph Goldschmidt & Gunnar Luderer & Gregory Nemet & Robert C. Pietzcker, 2017. "The underestimated potential of solar energy to mitigate climate change," Nature Energy, Nature, vol. 2(9), pages 1-9, September.
    39. Bhattacharjee, Somudeep & Das, Ivan & Nandi, Champa, 2023. "A data-centric analysis of climate change in India: A reflection on electricity sector," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
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    More about this item

    Keywords

    Biodiversity; Energy transition; Breakpoint detection; Granger causality; Long-short term;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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