ESRC AQM Studentship: Strategic and Relational Models in International Climate Treaty-Making

Climate change is one of the most pressing societal challenges. While many consider the Paris Agreement a success, President Trump’s 2017 announcement to withdraw the US from the agreement has raised concerns about whether other states will also backtrack. This puts a fundamental, counterfactual question in the spotlight: Would the same announcement by any other country have triggered similar worries?

This seemingly innocuous question highlights a major challenge for our understanding of international cooperation. When governments make decisions about whether to join a treaty, such as the Paris Agreement, they consider two things: First, they are forward-looking and try to assess how their own treaty participation affects the likelihood of others to join the agreement.

Second, governments look backwards to see which countries have already ratified a treaty before deciding on their own action.

Existing statistical approaches ignore these strategic and relational contexts in which specific agreements are made; they only consider a government’s current choice, independent of how their own choice affects future behaviour by others (strategic context) and what to learn from historic ratifications (relational context). This PhD project hence proposes to assess, both substantively and statistically, the relative merits of two advanced quantitative methods: Strategic estimation and the relational event model (REM) to investigate international agreement-making to better understand the nature of government choice over time.

Both methods are new to the study of international agreement-making, so applicants would not be expected to already master these techniques at the beginning of the PhD; extensive training opportunities will be put in place to help the student acquire the necessary skills. An ideal candidate should have a background in political science, international relations, or a related social science with a strong quantitative focus or from (applied) statistics with a strong interest in international relations and climate agreement-making. Any of the following would be an advantage: familiarity with random utility models and/or strategic estimation; familiarity with relational event modelling and/or analysis of dynamic network data; the use of statistical packages, such as R; strong interest in climate change research and international treaty-making.