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Evolving Temperature Dynamics in Canada: Preliminary Evidence Based on 60 Years of Data

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  • Robert Amano
  • Marc-André Gosselin
  • Julien McDonald-Guimond

Abstract

Recent discussions on climate change have led to an interest in its potential impact on economic phenomena and public policy. In this paper, we focus on one aspect of the climate change question by documenting the time-series properties of temperatures across Canada. In particular, we examine the evolving dynamics of daily average temperature and diurnal temperature range (the difference between the daily maximum and minimum temperatures at a given location) for select Canadian cities using data from the past 60 years. While rising mean temperature levels in Canada and elsewhere has been well documented, research exploring the other elements of temperature dynamics using modern econometric methods and rich model specifications are sparse. To fill in this gap, we extend the work of Diebold and Rudebusch (2019) and examine the evolution of daily temperature averages, volatility, seasonality and duration. This new evidence provides economists exploring issues related to climate change with a better understanding of the nature of Canadian temperature dynamics and their magnitudes.

Suggested Citation

  • Robert Amano & Marc-André Gosselin & Julien McDonald-Guimond, 2021. "Evolving Temperature Dynamics in Canada: Preliminary Evidence Based on 60 Years of Data," Staff Working Papers 21-22, Bank of Canada.
    • Handle: RePEc:bca:bocawp:21-22
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    References listed on IDEAS

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    1. Solomon Hsiang & Robert E. Kopp, 2018. "An Economist's Guide to Climate Change Science," Journal of Economic Perspectives, American Economic Association, vol. 32(4), pages 3-32, Fall.
    2. Simon Dietz & Frederick van der Ploeg & Armon Rezai & Frank Venmans, 2021. "Are Economists Getting Climate Dynamics Right and Does It Matter?," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 8(5), pages 895-921.
    3. Diebold, Francis X. & Göbel, Maximilian & Goulet Coulombe, Philippe & Rudebusch, Glenn D. & Zhang, Boyuan, 2021. "Optimal combination of Arctic sea ice extent measures: A dynamic factor modeling approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1509-1519.
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    6. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    7. Glenn D. Rudebusch, 2019. "Climate Change and the Federal Reserve," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
    8. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
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    Cited by:

    1. Ho, Anson T.Y. & Huynh, Kim P. & Jacho-Chávez, David T. & Vallée, Geneviève, 2023. "We didn’t start the fire: Effects of a natural disaster on consumers’ financial distress," Journal of Environmental Economics and Management, Elsevier, vol. 119(C).

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    More about this item

    Keywords

    Climate change; Econometric and statistical methods;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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