Abstract
Public attitudes toward environmental spending have become increasingly divided along party lines, with sharp shifts over the past five decades. This thesis updates and expands on Johnson and Schwadel’s 2019 study by applying a two-level hierarchical linear model to General Social Survey data updated to include data from 2015-2022, capturing how political affiliation, education, race, and economic context interact with broader political and economic contexts to shape environmental attitudes over time. The results show that political affiliation remains the strongest and most reactive predictor of environmental spending attitudes. Republican respondents are significantly more likely to oppose environmental spending, especially under Democratic presidencies. In contrast, Democratic support remains relatively stable across changing political contexts. Education and Age also emerged as significant factors: individuals with more education and younger respondents are more likely to support environmental spending. Race had mixed statistical significance. Income, sex, and unemployment are not significant predictors on their own, but interactions indicate that attitudes may shift based on context. This study reinforces the central role of partisan identity in shaping environmental views and demonstrates how political and economic context can activate or dampen that divide. By incorporating new interaction terms and updated data, the model offers a clearer understanding of how these dynamics have evolved over time. The findings underscore the challenges of building bipartisan support for environmental policy and point to the importance of messaging that considers political context and reactive partisan patterns.
Presenters
Jordan LipnerStudent, Environmental Studies and Political Science, University of Central Florida, Florida, United States
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
Economic, Social, and Cultural Context
KEYWORDS
Demographics, Environmental Spending, Hierarchical Linear Modeling, Ideology, Polarization, Public Opinion
