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Oil Production and Carbon Emissions: Spline Analysis of Relationships

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  • R. H. Ilyasov

  • V. A. Plotnikov

Abstract

Obviously, the dynamics of carbon dioxide emissions depends on the volume and structure of consumption of primary energy resources in the economy. The world’s energy consumption shows a growth trend temporarily interrupted during times of economic crisis. The most noticeable decrease in energy consumption in modern history occurred in 2020, which was due to a decline in business activity in the world due to the COVID-19 pandemic. This caused a decrease in carbon emissions (by more than 6% compared to 2019). In the structure of primary energy sources, the largest reduction was in oil consumption. The paper examines the impact of economic crises on the evolution of the mutual link between the dynamics of oil production and carbon dioxide emissions in the world. To detect correlations in local time regions, it is proposed to interpolate process dynamics with cubic splines. Using this toolkit avoids the limitations of classical econometrics on the length of time series. The differentiability of the built spline models allowed us to move on to identifying and analyzing latent correlations in fluctuations in the instantaneous growth rate of oil production volumes and carbon emissions.

Suggested Citation

  • R. H. Ilyasov & V. A. Plotnikov, 2022. "Oil Production and Carbon Emissions: Spline Analysis of Relationships," Administrative Consulting, Russian Presidential Academy of National Economy and Public Administration. North-West Institute of Management., issue 5.
    • Handle: RePEc:acf:journl:y:2022:id:1970
    DOI: 10.22394/1726-1139-2022-5-51-61
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    References listed on IDEAS

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    1. Robert J. Hill & Michael Scholz, 2018. "Can Geospatial Data Improve House Price Indexes? A Hedonic Imputation Approach with Splines," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(4), pages 737-756, December.
    2. Buletova Natalya Yevgenyevna & Gorelova Irina Valerievna & Golomanchuk Ada Vladimirovna & Orlova Yelena Roaldovna, 2015. "New interaction paradigm of ecological, social and economic structures of human activity," Экономика региона, CyberLeninka;Федеральное государственное бюджетное учреждение науки «Институт экономики Уральского отделения Российской академии наук», issue 2, pages 59-71.
    3. Gao, Guangyuan & Meng, Shengwang, 2018. "Stochastic Claims Reserving Via A Bayesian Spline Model With Random Loss Ratio Effects," ASTIN Bulletin, Cambridge University Press, vol. 48(1), pages 55-88, January.
    4. Muddassar Sarfraz & Muhammad Mohsin & Sobia Naseem & Amit Kumar, 2021. "Modeling the relationship between carbon emissions and environmental sustainability during COVID-19: a new evidence from asymmetric ARDL cointegration approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16208-16226, November.
    5. Cui, Zhenyu & Kirkby, Justin Lars & Nguyen, Duy, 2020. "Nonparametric Density Estimation By B-Spline Duality," Econometric Theory, Cambridge University Press, vol. 36(2), pages 250-291, April.
    6. Rajiv D. Banker & Dmitri Byzalov & Shunlan Fang & Byunghoon Jin, 2020. "Operating asymmetries and non-linear spline correction in discretionary accrual models," Review of Quantitative Finance and Accounting, Springer, vol. 54(3), pages 803-850, April.
    7. Serpil Kılıç Depren & Mustafa Tevfik Kartal, 2021. "Prediction on the volume of non‐performing loans in Turkey using multivariate adaptive regression splines approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 6395-6405, October.
    8. Xu, Le & Fan, Meiting & Yang, Lili & Shao, Shuai, 2021. "Heterogeneous green innovations and carbon emission performance: Evidence at China's city level," Energy Economics, Elsevier, vol. 99(C).
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