Extra Empirical Project 2 The politics of carbon taxation
Learning objectives
In this project, you will:
- create dummy variables to simplify data
- use column charts to visualize the distribution of public support for economic policies
- create tables to examine how public support varies across different groups
- understand how survey experiments can be used to test causal arguments
- calculate and create visualizations for differences in beliefs and policy preferences between treatment and control groups
- conduct hypothesis tests and calculate and interpret p-values for differences in means
- evaluate the strengths and weaknesses of survey experiments.
Key concepts
- Concepts needed for this project: dummy variable, conditional mean, Likert scale, correlation, causation, p-value, (for extension task) confidence interval
- Concepts introduced in this project: information provision survey experiment
CORE projects
This empirical project is related to material in:
The authors of this project are:
David Hope: Senior Lecturer in Political Economy at King’s College London
Julian Limberg: Senior Lecturer in Public Policy at King’s College London
Eileen Tipoe: Reader in Economics at Queen Mary University of London.
June 2026
Introduction
Climate change is one of today’s most pressing policy issues. Empirical Project 1 investigated the extent of climate change: how we can measure it and how we can determine what is causing it. Empirical Project 11 examined how economists measure willingness to pay for climate change mitigation.
In this project, we will focus on one policy that economists have long advocated as a crucial tool for addressing climate change: carbon taxation. While a running theme of The Economy 2.0 is that economists often disagree, carbon taxation is one area where there is a strong consensus. In 2019, The Wall Street Journal published the ‘Economists’ Statement of Carbon Dividends’, which (as of April 2026) carries the signatures of over 3,600 US economists, including four former Chairs of the Federal Reserve and 28 Nobel Prize winners. The first point of the statement strongly backs a carbon tax to deal with global climate change:
A carbon tax offers the most cost-effective lever to reduce carbon emissions at the scale and speed that is necessary. By correcting a well-known market failure, a carbon tax will send a powerful price signal that harnesses the invisible hand of the marketplace to steer economic actors towards a low-carbon future.
A similar statement on carbon pricing, formulated by the European Association of Environmental and Resource Economists, received over 1,770 signatures from economists worldwide.
Despite the forceful backing of economists, carbon taxes have not been that widely adopted by governments around the world. In 2025, only 28% of global greenhouse gas emissions were covered by carbon pricing instruments. The major obstacle to governments introducing carbon taxes is not economic but political: they are unpopular with the public. This highlights an important broader point about economic policies: they do not take place in a vacuum. Politicians need to take account of public opinion when setting economic policies, as they may pay an electoral cost (like being voted out of office) if they push through unpopular policies. A better understanding of what drives public support and opposition to carbon taxation is therefore crucial for this policy lever to be more widely implemented by governments around the world.
This project focuses on the politics of carbon taxation. In Part 1, we will use public opinion data from the UK to measure the level of support for carbon taxation and examine how it differs across groups with different characteristics and beliefs. In Part 2, we will explore some explanations for a prominent recent phenomenon in environmental politics: rural backlashes against carbon taxation (like the 2018–2020 ‘Gilet Jaunes’ protests in France or the rural resistance to the carbon tax introduced in British Columbia in Canada in 2008).
- information provision survey experiment
- A research methodology where survey respondents are randomly assigned to receive different information. Researchers then look at how the information provided affects respondents’ beliefs and preferences. Information provision survey experiments are a useful tool for testing causal arguments about what drives people’s economic policy preferences.
The project will utilize the novel dataset collected by the researchers David Hope, Julian Limberg, and Yves Steinebach, which features in their 2026 article ‘Unequal treatment perceptions and rural backlashes against carbon taxation’. In this article, the researchers carried out an information provision survey experiment, which is a methodology that is used increasingly by social scientists to examine what drives people’s preferences for economic policies. During Part 2 of the project, you will also learn how information provision survey experiments can be a valuable tool for testing causal arguments, and you will evaluate the strengths and weaknesses of this research methodology.
Acknowledgements
The authors would like to thank Shivam Gujral for his help in creating the walk-throughs and instructions for Google Sheets and Python.
