Although climate change is an urgent problem, behavioural and policy responses have not yet been sufficient to either reduce the volume of greenhouse gas emissions or adapt to a disrupted climate system. Significant efforts have been made to raise public awareness of the dangers posed by climate change. One reason why these efforts might not be sufficient is rooted in people’s need to feel efficacy to solve complex problems; the belief that climate change is unstoppable might thwart action even among the concerned. This paper tests for the effect of fatalistic beliefs on behavioural change and willingness to pay to address climate change using two cross-national surveys representing over 50,000 people in 48 nations. Key policy insights

Background: Access to reliable energy services is increasingly seen as a prerequisite for well-being and human development. Copious research documents the negative consequences that occur when nations specialize in natural resource production, creating a “natural resource curse” or “paradox of plenty”. In this analysis, we evaluate how natural resource dependence, measured as oil and gas production, impacts energy security. Results: Using entropy-balanced fixed effects models, we find that oil and coal production is not associated with shorter times to establish a connection to the electricity grid, fewer outages, or improve electricity access among the population. Conclusions: Nations that produce oil and coal do not seem to have better energy insecurity as a result, representing a distributional inequality. Fossil fuel-producing nations should consider implementing policies that would allow them to retain more wealth from fossil fuel production.

The degree to which risk perceptions are socially constructed versus the result of actual exposure to risk is highly contested; how risk exposure and risk perception influence policy attitudes is also poorly understood. We examine how personal exposure to risk factors impacts risk perceptions and policy support related to air pollution and climate change. Our selection of risk exposure variables is informed by the “mental models” literature, and we employ an array of variables to capture subjective risk perceptions using novel survey data. We find that exposure to risk does little to predict risk perception and has a small influence on policy support. Overall, our findings lend support to a constructionist understanding of risk perception and support for policies related to environmental risks.

Standard mediation techniques for fitting mediation models cannot readily be translated to nonlinear regression models because of scaling issues. Methods to assess mediation in regression models with categorical and limited response variables have expanded in recent years, and these techniques vary in their approach and versatility. The recently developed khb technique purports to solve the scaling problem and produce valid estimates across a range of nonlinear regression models. Prior studies demonstrate that khb performs well in binary logistic regression models, but performance in other models has yet to be investigated. In this article, we evaluate khb‘s performance in fitting ordinal logistic regression models as an exemplar of the wider set of models to which it applies. We examined performance across 38,400 experimental conditions involving sample size, number of response categories, distribution of variables, and amount of mediation. Results indicate that under all experimental conditions, khb estimates the difference (mediation) coefficient and its associated standard error with little bias and that the nominal confidence interval coverage closely matches the actual. Our results suggest that researchers using khb can assume that the routine reasonably approximates population parameters.

Electric bikes (ebikes) are an emerging technology that can partially mitigate many of the challenges facing the United States, such as improving mobility for the elderly and disabled, by mitigating diabetes and obesity, and reducing greenhouse gas emissions. Although ebikes have become increasingly common in the U.S., they have failed to gain significant market penetration despite their great promise. In this paper, we present the results of semi-structured interviews with 47 ebike users from around the U.S. to understand motivations and barriers to ebike use. Following prior research, our results suggest that cost savings and health benefits are the primary motivations behind ebike adoption, while lack of infrastructure is the primary impediment to ebike usage. Other barriers to ebike usage include shaming (primarily from other cyclists) and unwelcoming local policy environments.