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Human Activities and Global Warming: A Cointegration Analysis

Author

Listed:
  • Hui Liu

    (Department of Economics, University of Ottawa)

  • Gabriel Rodriguez

    (Department of Economics, University of Ottawa)

Abstract

Do human activities indeed cause global warming? This paper attempts to answer this question by reexamining the time series properties of climate variables and the existence of long-run relationships between them. Double unit root testing shows that most of the radiative forcings of greenhouse gases are integrated of order two. We then apply an I(1) and I(2) cointegrating rank analysis to identify the presence of I(2) components. After identifying a linear combination of I(2) variables that cointegrates to an I(1) process, we proceed with the I(1) cointegrating analysis and we identify two possible cases with different rank specifications. Estimation of the equation for temperature suggests that this variable reacts significantly to the radiative forcings of greenhouse gases in the long-run. This evidence allow us to conclude that human activities affect temperature variations.

Suggested Citation

  • Hui Liu & Gabriel Rodriguez, 2003. "Human Activities and Global Warming: A Cointegration Analysis," Working Papers 0307E, University of Ottawa, Department of Economics.
    • Handle: RePEc:ott:wpaper:0307e
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    Cited by:

    1. Claudio Morana & Giacomo Sbrana, 2017. "Temperature anomalies, radiative forcing and ENSO," Working Paper series 17-06, Rimini Centre for Economic Analysis.
    2. Wang, Ke & Zhang, Jianjun & Cai, Bofeng & Yu, Shengmin, 2019. "Emission factors of fugitive methane from underground coal mines in China: Estimation and uncertainty," Applied Energy, Elsevier, vol. 250(C), pages 273-282.
    3. Matthew T. Holt & Timo Teräsvirta, 2012. "Global Hemispheric Temperature Trends and Co–Shifting: A Shifting Mean Vector Autoregressive Analysis," CREATES Research Papers 2012-54, Department of Economics and Business Economics, Aarhus University.
    4. Francisco Estrada & Pierre Perron, "undated". "Detection and attribution of climate change through econometric methods," Boston University - Department of Economics - Working Papers Series 2013-015, Boston University - Department of Economics.
    5. Holt, Matthew T. & Teräsvirta, Timo, 2020. "Global hemispheric temperatures and co-shifting: A vector shifting-mean autoregressive analysis," Journal of Econometrics, Elsevier, vol. 214(1), pages 198-215.
    6. Torben Schmith & Søren Johansen & Peter Thejll, 2011. "Statistical analysis of global surface air temperature and sea level using cointegration methods," CREATES Research Papers 2011-39, Department of Economics and Business Economics, Aarhus University.
    7. David B. Stephenson & Alemtsehai A. Turasie & Donald P. Cummins, 2023. "More Accurate Climate Trend Attribution by Using Cointegrating Vector Time Series Models," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    8. White Halbert & Granger Clive W.J., 2011. "Consideration of Trends in Time Series," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-40, February.
    9. Alexiadis, Alessio, 2007. "Global warming and human activity: A model for studying the potential instability of the carbon dioxide/temperature feedback mechanism," Ecological Modelling, Elsevier, vol. 203(3), pages 243-256.
    10. Luca Benati, 2023. "Forecasting Global Temperatures by Exploiting Cointegration with Radiative Forcing," Diskussionsschriften dp2308, Universitaet Bern, Departement Volkswirtschaft.

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    More about this item

    Keywords

    Global Warming; Radiative Forcing; Cointegration; I(1) and I(2) Processes; Unit Roots.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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