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Raising Awareness of Climate Change: Nature, Activists, Politicians?

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  • Daryna Grechyna

Abstract

This paper evaluates the relative importance of natural and human factors in shaping public awareness of climate change. I compare the predictive efficacy of natural factors, represented by air temperature deviations from historical norms, and human factors, encompassing noteworthy political events focused on environmental policies and movements led by environmental activists, in forecasting the salience of climate change topic over weekly and annual horizons using regional European countries’ data. The salience of climate change is proxied by the Google search intensity data. The activists’ movements are measured by weekly Friday for Future strikes. The best-performing predictor in the short term (weeks), is the size of activists’ strikes and in the longer term (years), positive deviations of maximum air temperature from historical norms and political meetings focused on environmental policies. The inter-regional spatial relations, when taken into account, significantly improve the forecasts of the future public interest in climate change.

Suggested Citation

  • Daryna Grechyna, 2024. "Raising Awareness of Climate Change: Nature, Activists, Politicians?," CESifo Working Paper Series 10907, CESifo.
  • Handle: RePEc:ces:ceswps:_10907
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    More about this item

    Keywords

    climate change; activists’ strikes; political meetings; weather;
    All these keywords.

    JEL classification:

    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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