An active debate has emerged about the political viability of market-based versus non-market-based policies to address climate change. As carbon pricing policies face significant political challenges, some have argued that regulatory policies are a better option because they do not highlight consumer energy prices and can be linked to other economic and social priorities. Yet, no study has compared communication strategies for regulatory versus price-based climate policies in practice. This paper fills that gap through a qualitative content analysis of framing strategies for Ontario's 2016 cap-and-trade program for greenhouse gas emissions, and Virginia's 2020 clean energy mandate. Results largely confirm the paper's primary hypothesis that similar financial frames will be used as or more frequently for the regulatory policy as for the price-based policy, complicating any theory that regulatory policies will face an easier political path due to their different messaging options.

A natural experiment is a real-world situation that generates as-if random or haphazard assignment to treatment. Geographic or administrative boundaries can be exploited as natural experiments to construct treated and control groups. Previous research has demonstrated that matching can help enhance these designs by reducing imbalances on observed covariates. An important limitation of this empirical approach, however, is that the results are inherently local. While the treated and control groups may be quite similar to each other, they could be substantially different from the target population of interest (e.g., a country). We propose a simple design inspired by the idea of template matching to construct generalizable geographic natural experiments. By matching our treated and control groups to a template (i.e., the target population), we obtain groups that are similar to the target population of interest and to each other, which can increase both the internal and external validity of the study.