Yale Climate Opinion Maps for Strategists

Methods

This site provides estimates of U.S. climate change beliefs, risk perceptions, and policy preferences at the state and local levels – a new source of high-resolution data on public opinion that can inform national, state and local decision-making, policy, and education initiatives. The estimates are derived from a statistical model using multilevel regression with post-stratification (MRP) on a large national survey dataset (n>18,000), along with demographic and geographic population characteristics. The estimates were validated using three different methods. First, cross-validation analyses were conducted within the dataset. The dataset was divided into two sets of respondents, with one part used to run the model and the other kept aside for validation. The model estimates were then compared to the results of the set aside respondents to directly quantify the percentage of correct answers the model predicted. These cross-validation tests were repeated multiple times using different sample sizes and dividing the data in different ways. Second, the model estimates derived from the full dataset were compared to the results of independent, representative state- and city-level surveys conducted in California, Colorado, Ohio, Texas, San Francisco, and Columbus, Ohio in 2013. The mean absolute difference between model estimates and validation survey results was 2.9 percentage points (SD = 1.5) among the four states (CA, TX, OH, CO) and 3.6 percentage points (SD = 2.9) among the two metropolitan areas (Columbus, OH, and San Francisco, CA), well within the margins of error for the survey results alone (at a 95% confidence level). Estimates have also been validated internally through a series of technical simulations. Third, some model estimates were compared with third-party survey data collected by other researchers in previous years.

For the 2016 model estimates, margin of error estimates are based on 95% confidence intervals using 999 bootstrap simulations. These confidence intervals indicate that the 2016 model is accurate to approximately ±7 percentage points at the state and congressional district levels, and ±8 percentage points at the metro and county levels. Such error ranges include the error inherent in the original national surveys themselves, which is typically ±3 percentage points.

The availability of 2014 and 2016 estimates begs the question, what has changed since 2014? From our two national surveys conducted in 2016 (Leiserowitz et al., 2017), We know that public opinions about global warming have generally increased. However, a variety of improvements to our 2016 model, including new data that increase our ability to resolve differences between jurisdictions, may account for any observed shifts in public opinion estimates since 2014. As a result, we recommend caution interpreting any changes over time because we can’t easily disaggregate what is a true shift between 2014 and 2016 and what reflects the model’s improved ability to map climate beliefs at the local scale.

For more details, please see the peer-reviewed paper: Howe, P., Mildenberger, M., Marlon, J.R., and Leiserowitz, A., “Geographic variation in opinions on climate change at state and local scales in the USA,” Nature Climate Change. DOI: 10.1038/nclimate2583.