Abstract
Decades after the scientific community agreed on the existence of human-made climate change, substantial parts of the world’s population remain unaware or unconvinced that human activity is responsible for climate change. Belief in human-made climate change continues to vary strongly within and across different countries. Here I analyse data collected by the Gallup World Poll between 2007 and 2010 on individual attitudes across 143 countries, using a random forest model, to show that country-level conditions like environmental protection, civil liberty, and economic development are highly predictive of individual climate change belief. Individual education and internet access, in contrast, are correlated to climate change awareness, but much less to belief in climate change’s anthropogenic causes. I also identify non-linear pattern in which country-level circumstances relate to individual climate change belief. The local importance of most predictors varies strongly across countries, indicating that each country has its relatively unique set of correlates of climate change belief.
Highlights
The results show that country-level circumstances such as economic development, civil liberties, and environmental protection are highly predictive of individual climate change beliefs
I find individual education and internet access to be strongly predictive of climate change awareness, but much less predictive of belief in climate change’s anthropogenic causes
This analysis discovers novel non-monotonous patterns in which economic development, market liberalism, and carbon emissions are related to individual climate change beliefs
Summary
The results show that country-level circumstances such as economic development, civil liberties, and environmental protection are highly predictive of individual climate change beliefs. More within-case studies and cross-regional comparative analyses are necessary to interpret the observed correlations and to understand how public belief in human-made climate change develops in countries other than English-speaking Western democracies. I approximated missing values in the explanatory variables where ancillary data was available and imputed all remaining missing values with iterative multiple imputation techniques (see Supplementary Tables 4–5).
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