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On Spurious Causality, CO 2 , and Global Temperature

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  • Philippe Goulet Coulombe

    (Département des Sciences Économiques, Université du Québec à Montréal, Montréal, QC H2L 2C4, Canada)

  • Maximilian Göbel

    (Lisbon School of Economics and Management, Universidade de Lisboa, 1200-781 Lisboa, Portugal)

Abstract

Stips et al. (2016) use information flows (Liang (2008, 2014)) to establish causality from various forcings to global temperature. We show that the formulas being used hinge on a simplifying assumption that is nearly always rejected by the data. We propose the well-known forecast error variance decomposition based on a Vector Autoregression as an adequate measure of information flow, and find that most results in Stips et al. (2016) cannot be corroborated. Then, we discuss which modeling choices (e.g., the choice of CO 2 series and assumptions about simultaneous relationships) may help in extracting credible estimates of causal flows and the transient climate response simply by looking at the joint dynamics of two climatic time series.

Suggested Citation

  • Philippe Goulet Coulombe & Maximilian Göbel, 2021. "On Spurious Causality, CO 2 , and Global Temperature," Econometrics, MDPI, vol. 9(3), pages 1-18, September.
    • Handle: RePEc:gam:jecnmx:v:9:y:2021:i:3:p:33-:d:630626
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