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Econometric modelling of carbon dioxide emissions and concentrations, ambient temperatures and ocean deoxygenation

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  • Alok Bhargava

Abstract

This paper analysed several longitudinal data sets for investigating the dynamic inter‐relationships between CO2 emissions and atmospheric concentrations, ambient temperatures and ocean acidification and deoxygenation. The methodological framework addressed issues such as the use of temperature ‘anomalies’, diffusion of CO2 to atmospheric stations, distributional misspecification and non‐stationarity of errors affecting empirical models, and use of spline functions for modelling trends in temperatures. Longitudinal data on CO2 emissions for 163 countries and atmospheric CO2 concentrations at 10 stations, ambient temperatures from over 8,500 weather stations and seawater composition from over 380,000 oceanographic stations were analysed for 1985–2018 by estimating dynamic random effects models using maximum likelihood methods. The main findings were that CO2 emissions exhibited rapid upward trends at the country level, while minimum and maximum temperatures showed cyclical patterns; economic activity and population levels were associated with higher CO2 emissions. Second, there were gradual upward trends in annual and seasonal temperatures compiled at weather stations, and atmospheric CO2 concentrations were significantly associated with higher temperatures in the hemispheres. Third, there was a steady decline in dissolved oxygen levels, and the interactive effects of water temperatures and pH levels were significant. Overall, the results underscore the benefits of reducing CO2 emissions for ambient temperatures and for ocean deoxygenation. Synergies between CO2 emissions, ambient temperatures and ocean acidification are likely to exacerbate the melting of polar ice.

Suggested Citation

  • Alok Bhargava, 2022. "Econometric modelling of carbon dioxide emissions and concentrations, ambient temperatures and ocean deoxygenation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 178-201, January.
  • Handle: RePEc:bla:jorssa:v:185:y:2022:i:1:p:178-201
    DOI: 10.1111/rssa.12732
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    References listed on IDEAS

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    1. Alok Bhargava & J. D. Sargan, 2006. "Estimating Dynamic Random Effects Models From Panel Data Covering Short Time Periods," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 1, pages 3-27, World Scientific Publishing Co. Pte. Ltd..
    2. A. Bhargava & L. Franzini & W. Narendranathan, 2006. "Serial Correlation and the Fixed Effects Model," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 4, pages 61-77, World Scientific Publishing Co. Pte. Ltd..
    3. Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-174, January.
    4. Alok Bhargava, 2006. "Identification and Panel Data Models with Endogenous Regressors," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 3, pages 49-60, World Scientific Publishing Co. Pte. Ltd..
    5. Magnus, Jan R. & Melenberg, Bertrand & Muris, Chris, 2011. "Global Warming and Local Dimming: The Statistical Evidence," Journal of the American Statistical Association, American Statistical Association, vol. 106(494), pages 452-464.
    6. Martin Heimann & Markus Reichstein, 2008. "Terrestrial ecosystem carbon dynamics and climate feedbacks," Nature, Nature, vol. 451(7176), pages 289-292, January.
    7. Wang, C. Y. & Wang, Suojin & Carroll, R. J., 1997. "Estimation in choice-based sampling with measurement error and bootstrap analysis," Journal of Econometrics, Elsevier, vol. 77(1), pages 65-86, March.
    8. Sargan, J D, 1980. "Some Tests of Dynamic Specification for a Single Equation," Econometrica, Econometric Society, vol. 48(4), pages 879-897, May.
    9. Alok Bhargava, 2006. "Wald Tests And Systems Of Stochastic Equations," World Scientific Book Chapters, in: Econometrics, Statistics And Computational Approaches In Food And Health Sciences, chapter 2, pages 29-48, World Scientific Publishing Co. Pte. Ltd..
    10. Anderson, T. W. & Hsiao, Cheng, 1982. "Formulation and estimation of dynamic models using panel data," Journal of Econometrics, Elsevier, vol. 18(1), pages 47-82, January.
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