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Partisan asymmetry in temporal stability of climate change beliefs

Abstract

Existing literature on climate change beliefs in the US suggests that partisan polarization begets climate change polarization and that the climate beliefs of those on both sides of the partisan divide are firmly held and invariable. Here, we use data from a large panel survey of Oklahoma residents administered quarterly from 2014 through 2018 to challenge this perspective. Contrary to the expectation of rough symmetry in partisan polarization on climate change, we find that partisans on the political right have much more unstable beliefs about climate change than partisans on the left. An important implication is that if climate beliefs are well anchored on the left, but less so on the right, the latter are more susceptible to change. We interpret this to suggest that, despite polarizing elite rhetoric, public beliefs about climate change maintain the potential to shift towards broader acceptance and a perceived need for action.

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Fig. 1: Aggregate beliefs about climate change among Oklahoma panellists.
Fig. 2: The distribution of variation in panellist’s beliefs about climate change.
Fig. 3: Time-series trends in sample panellist’s beliefs about climate change.
Fig. 4: Influence of ideology and partisanship on variation in climate change beliefs.
Fig. 5: Influence of salience and cues from scientists on variation in climate change beliefs.

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Data availability

M-SISNet data and metadata are available at: http://crcm.ou.edu/epscordata/.

Code availability

R code for the current study is available on GitHub: https://github.com/ripberjt/msisnet.

References

  1. IPCC: Summary for Policymakers. In Global warming of 1.5°C (eds Masson-Delmotte, V. et al.) 32 (Cambridge Univ. Press, 2008).

  2. Saad, L. Americans Concerned as Ever about Climate Change (Gallup, 2019).

  3. Ritchie, E. J. Fact checking the claim of a major shift in climate change opinion. Forbes (30 January 2019).

  4. Hamilton, L. C. Data Snapshot: Public Acceptance of Human-Caused Climate Change is Gradually Rising (Carsey School of Public Policy, University of New Hampshire, 2017).

  5. Hornsey, M. J., Harris, E. A., Bain, P. G. & Fielding, K. S. Meta-analyses of the determinants and outcomes of belief in climate change. Nat. Clim. Change 6, 622–626 (2016).

    Article  Google Scholar 

  6. McCright, A. M., Charters, M., Dentzman, K. & Dietz, T. Examining the effectiveness of climate change frames in the face of a climate change denial counter-frame. Top. Cogn. Sci. 8, 76–97 (2016).

    Article  Google Scholar 

  7. Kahan, D. Why we are poles apart on climate change. Nature News 488, 255 (2012).

    Article  CAS  Google Scholar 

  8. Saad, L. Half in U.S. Are Now Concerned Global Warming Believers (Gallup, 2017).

  9. Leiserowitz, A. et al. Climate Change in the American Mind: October 2017 (Yale Program on Climate Change Communication, George Mason University Center for Climate Change Communication, 2017).

  10. Kahn, M. E. & Kotchen, M. J. Business cycle effects on concern about climate change: the chilling effects of recession. Clim. Change Econ. 2, 257–273 (2011).

    Article  Google Scholar 

  11. Mildenberger, M. & Leiserowitz, A. Public opinion on climate change: is there an economy–environment tradeoff? Environ. Pol. 26, 801–824 (2017).

    Article  Google Scholar 

  12. Dunlap, R. E., McCright, A. M. & Yarosh, J. H. The political divide on climate change: partisan polarization widens in the US. Environ. Sci. Pol. Sustain. Dev. 58, 4–23 (2016).

    Article  Google Scholar 

  13. Carmichael, J. T. & Brulle, R. J. Elite cues, media coverage, and public concern: an integrated path analysis of public opinion on climate change, 2001–2013. Environ. Pol. 26, 232–252 (2017).

    Article  Google Scholar 

  14. Tesler, M. Elite domination of public doubts about climate change (not evolution). Pol. Commun. 35, 306–326 (2018).

    Article  Google Scholar 

  15. Howe, P. D., Marlon, J. R., Mildenberger, M. & Shield, B. S. How will climate change shape climate opinion? Environ. Res. Lett. 14, 113001 (2019).

    Article  Google Scholar 

  16. Moore, F. C., Obradovich, N., Lehner, F. & Baylis, P. Rapidly declining remarkability of temperature anomalies may obscure public perception of climate change. Proc. Natl Acad. Sci. USA 116, 4905–4910 (2019).

    Article  CAS  Google Scholar 

  17. Ripberger, J. T. et al. Bayesian versus politically motivated reasoning in human perception of climate anomalies. Environ. Res. Lett. 12, 114004 (2017).

    Article  Google Scholar 

  18. McCright, A. M., Marquart-Pyatt, S. T., Shwom, R. L., Brechin, S. R. & Allen, S. Ideology, capitalism, and climate: explaining public views about climate change in the United States. Energy Res. Soc. Sci. 21, 180–189 (2016).

    Article  Google Scholar 

  19. Krehbiel, K. Pivotal Politics: A Theory of US Lawmaking (University of Chicago Press, 1998).

  20. Deeg, K., Lyon, E., Leiserowitz, A., Maibach, E., & Marlon, J. Who is changing their mind about global warming and why? (Yale Program on Climate Change Communication, 2019).

  21. Smith, T. W. Recalling attitudes: an analysis of retrospective questions on the 1982 GSS. Public Opin. Quart. 48, 639–649 (1984).

    Article  Google Scholar 

  22. Dex, S. The reliability of recall data: a literature review. Bull. Sociol. Methodol. 49, 58–89 (1995).

    Article  Google Scholar 

  23. Palm, R., Lewis, G. B. & Feng, B. What causes people to change their opinion about climate change? Ann. Am. Assoc. Geogr. 107, 883–896 (2017).

    Google Scholar 

  24. Jenkins-Smith, H. et al. The Oklahoma meso-scale integrated socio-geographic network: a technical overview. J. Atmos. Oceanic Technol. 34, 2431–2441 (2017).

    Article  Google Scholar 

  25. Howe, P., Mildenberger, M., Marlon, J. & Leiserowitz, A. Geographic variation in opinions on climate change at state and local scales in the USA. Nat. Clim. Change 5, 596–603 (2015).

    Article  Google Scholar 

  26. Burstein, P. The impact of public opinion on public policy: a review and an agenda. Pol. Res. Quart. 56, 29–40 (2003).

    Article  Google Scholar 

  27. Converse, P. E. Changing conceptions of public opinion in the political process. Public Opin. Quart. 51, S12–S24 (1987).

    Article  Google Scholar 

  28. Zaller, J. R. The Nature and Origins of Mass Opinion (Cambridge Univ. Press, 1992).

  29. Bassili, J. N. & Fletcher, J. F. Response-time measurement in survey research a method for CATI and a new look at nonattitudes. Public Opin. Quart. 55, 331–346 (1991).

    Article  Google Scholar 

  30. Yan, T. & Tourangeau, R. Fast times and easy questions: the effects of age, experience and question complexity on web survey response times. Appl. Cogn. Psychol. 22, 51–68 (2008).

    Article  Google Scholar 

  31. Krosnick, J. A. Response strategies for coping with the cognitive demands of attitude measures in surveys. Appl. Cogn. Psychol. 5, 213–236 (1991).

    Article  Google Scholar 

  32. Converse, P. E. in Handbook of Political Science (eds Greenstein, F. I. & Polsby, N. W.) 75–170 (Addison-Wesley, 1975).

  33. Zaller, J. & Feldman, S. A simple theory of the survey response: answering questions versus revealing preferences. Am. J. Pol. Sci. 36, 579–616 (1992).

    Article  Google Scholar 

  34. Tourangeau, R., Rips, L. J. & Rasinski, K. The Psychology of Survey Response (Cambridge Univ. Press, 2000).

  35. Hoffman, A. J. The growing climate divide. Nat. Clim. Change 1, 195–196 (2011).

    Article  Google Scholar 

  36. McCright, A. M. & Dunlap, R. E. The politicization of climate change and polarization in the American public’s views of global warming, 2001–2010. Sociol. Quart. 52, 155–194 (2011).

    Article  Google Scholar 

  37. Hamilton, L. C., Hartter, J., Lemcke-Stampone, M., Moore, D. W. & Safford, T. G. Tracking public beliefs about anthropogenic climate change. PLoS ONE 10, e0138208 (2015).

    Article  Google Scholar 

  38. Kahan, D., Jenkins‐Smith, H. & Braman, D. Cultural cognition of scientific consensus. J. Risk Res. 14, 147–174 (2011).

    Article  Google Scholar 

  39. Kahan, D. M. et al. The polarizing impact of science literacy and numeracy on perceived climate change risks. Nat. Clim. Change 2, 732–735 (2012).

    Article  Google Scholar 

  40. Grant, J. On climate change, John Kasich marches to a different beat. The Allegheny Front (11 March 2016).

  41. Gladwell, M. The Tipping Point: How Little Things Can Make A Big Difference (Abacus, 2006).

  42. Centola, D., Becker, J., Brackbill, D. & Baronchelli, A. Experimental evidence for tipping points in social convention. Science 360, 1116–1119 (2018).

    Article  CAS  Google Scholar 

  43. Sunstein, C. R. How Change Happens (Michigan Institute of Technology Press, 2019).

  44. Gardina, J. The tipping point: legal epidemics, constitutional doctrine, and the defense of marriage act. Vermont Law Rev. 34, 291 (2009).

    Google Scholar 

  45. Lohmann, S. The dynamics of informational cascades: the Monday demonstrations in Leipzig, East Germany, 1989–91. World Pol. 47, 42–101 (1994).

    Article  Google Scholar 

  46. Gelman, A. Scaling regression inputs by dividing by two standard deviations. Stats Medicine 27, 2865–2873 (2008).

    Article  Google Scholar 

  47. Imai, K., King, G., & Lau, O. Zelig: Everyone’s Statistical Software v.3 (2009).

Download references

Acknowledgements

This study is based on work supported by the National Science foundation under grant no. OIA-1301789. The authors thank M. Henderson, A. Goodin and the University of Oklahoma Public Opinion Learning Laboratory (OU POLL) for their help with survey implementation and data collection.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the design of the study. H.J-S., C.S., J.R., and N.C. contributed to data collection. J.R., H.J-S., and D.C. conducted the data analysis. All authors contributed to writing and editing the paper.

Corresponding authors

Correspondence to Hank C. Jenkins-Smith or Joseph T. Ripberger.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Lawrence Hamilton and the other, anonymous, reviewers for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Comparison of predicted certainty of climate change beliefs of Oklahoma panelists with a cross-section of US adults.

Points indicate conditional mean estimates from linear regression models with covariates in the models set to their average values. Panel (a) shows these estimates by political ideology and (b) shows them by political party. N-sizes are 1,353 for Oklahoma and 1,673 for the US in (a) and 1,353 for Oklahoma and 1,771 for the US in (b). Error bars show 95% confidence intervals.

Source data

Extended Data Fig. 2 Distribution of variation in panelist’s beliefs about climate change by wave count.

Wave count indicates the number of quarterly surveys panelists completed, ranging from 2+ surveys (n=2,115) to all 16 surveys (n=614).

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Extended Data Fig. 3 Prediction of variation in panelist’s beliefs about climate change by wave count.

Points indicate coefficient estimates from models comparable the one shown in Table 1, but the samples used vary by the number of quarterly surveys panelists completed, ranging from 2+ surveys (n=2,097) to all 16 surveys (n=612). Coefficients shown in panel (a) correspond to column 1 in Table 1; (b) corresponds to column 2 in Table 1; and c, corresponds to column 3 in Table 1. Error bars show 95% confidence intervals.

Source data

Extended Data Fig. 4 Distribution of variation in panelist’s beliefs about climate change.

Proportion of panelists (n = 1,380) at each value of within-subject root mean square of successive differences (RMSSD). Percentages indicate the percent of panelists in each bin marked with a red dotted line.

Source data

Extended Data Fig. 5 Time series trends in sample panelist’s beliefs about climate change.

Belief in climate change for random samples of 25 panelists with (a) stable beliefs (RMSSD < 1); 18% of the full sample; (b) somewhat stable beliefs (1 < RMSSD < 2); 22% of the full sample; (c) somewhat unstable beliefs (2 < RMSSD < 3); 12% of the full sample; and (d) unstable beliefs (RMSSD> 3); 48% of the full sample.

Source data

Extended Data Fig. 6 Influence of ideology and partisanship on variation in climate change beliefs.

Conditional mean estimates of within-subject RMSSD for (a) political ideology and (b) political party when the covariates in the linear regression models are set to their average values. Error bars show 95% confidence intervals. N-sizes are 1,374 for (a) and 1,353 for (b).

Source data

Extended Data Fig. 7 The Effects of Salience and Cues from Scientists on variation in climate change beliefs.

Points indicate mean estimates of within-subject RMSSD for (a) issue salience and (b) cues from scientists for panelists identifying as Democrat. For (a), n size for Democrats is 330 and for Republicans is 459. For (b), n size for Democrats is 331 and for Republicans is 464 . Error bars show 95% confidence intervals.

Source data

Extended Data Fig. 8 Influence of ideology and partisanship on variation in beliefs that climate change is or is not occurring.

Conditional estimates of the probability of at least one change in beliefs for (a) political ideology and (b) political party when the covariates in the linear regression models are set to their average values. Error bars show 95% confidence intervals. N-sizes are 1,374 for (a) and 1,353 for (b).

Source data

Extended Data Fig. 9 Influence of the 2016 US election on variation in climate change beliefs.

Points indicate mean estimates of within-subject standard deviation based on (a) political ideology and (b) political party before the 2016 US election (n=1,368) and after the 2016 US election (n=1,345). Error bars show 95% confidence intervals.

Source data

Extended Data Fig. 10 Influence of ideology and partisanship on survey variability.

Conditional mean estimates of survey variability for (a) political ideology and (b) political party when the covariates in the linear regression models are set to their average values. Error bars show 95% confidence intervals. N-sizes are 1,374 for (a) and 1,353 for (b).

Source data

Supplementary information

Supplementary Information

Supplementary Fig. 1, Supplementary Tables 1–5 and Supplementary Note 1.

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Jenkins-Smith, H.C., Ripberger, J.T., Silva, C.L. et al. Partisan asymmetry in temporal stability of climate change beliefs. Nat. Clim. Chang. 10, 322–328 (2020). https://doi.org/10.1038/s41558-020-0719-y

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