Natural experiments are an ingenious way to estimate causal effects in situations where randomised experiments are not possible. They have emerged as a standard topic in statistics, data science and econometrics, with The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2021 awarded to David Card, Joshua D. Angrist and Guido W. Imbens for showing what conclusions about cause and effect can be drawn from natural experiments. The approach has spread to other fields and revolutionised empirical research. Recent years have seen a significant rise in both methodological and empirical research on causality. Our call provides an opportunity to encapsulate and present the most interesting and innovative recent leading work in this area, with relevance to the present developments within the many aspects of artificial intelligence.
Motivated by the statistical and computational challenges that are inherent to methodologies targeting causal inferences, there has been significant renewed interest in the area in recent years. The
RSS Discussion Paper Meetings Committee, along with the RSS Sections on
Emerging Applications and
Research Section are jointly inviting submissions of discussion papers on the innovative usages of causal natural experiments in statistics and data science. Submitted papers can cover any methodological or applied aspect or theoretical underpinning on the topic. Examples of topics of interest include (but are not restricted to):
- Natural experiments as complement for randomised experiments;
- Instrumental variable strategies and LATE;
- Longitudinal causal designs, such as difference-in-differences and synthetic control;
- Machine learning and causality for observational data;
- Causality and artificial intelligence;
- Developments of graphical causal approaches;
- Natural experiments and causality for time series and network data;
- Innovative and emerging applications of natural experiments in environmental sciences, health, biology, chemistry, education, physics, sociology, economics, robotics and other areas;
- Open data practices, open source intelligence and natural experiments.
Papers selected for publication will be presented at a multi-paper discussion meeting held at the RSS International Conference in September 2026, and subsequently published in one of the series of
Journal of the Royal Statistical Society (JRSS), together with all contributions to the discussion at the meeting itself or submitted in writing shortly afterwards. All submitted papers are refereed, both for their scientific quality and their potential to generate discussion. Papers that meet the first criterion but not the second may, with the agreement of the authors, be referred to the editors of the Journal for review as a regular paper.
Submitted papers should be substantially shorter than is typical for a single‐paper discussion meeting (16 pages max excluding supplementary material, following standard JRSS formatting instructions). We shall employ a two-step process to expedite the peer review process.
Full details are as follows:
- Abstract submission. Authors are invited to send a single‐page abstract (400 words max) of their proposed paper to Judith Shorten, the RSS Journals Manager (journal@rss.org.uk) by 6 June 2025.
- Full paper submission. Notification of accepted abstracts will be made by 11 July 2025 together with an invitation to submit a full paper. Full papers (16 pages max) should then be submitted via manuscript central to the most appropriate journal series (A, B or C) selecting the “Discussion Paper” option. The deadline for full paper submission is 7 November 2025.
- Refereeing. All papers received by 7 November 2025 will be refereed using the Society’s standard criteria for discussion meeting papers (scientific quality and potential to generate discussion).
- Final versions of accepted papers will be ready for pre‐printing by mid‐2026.
Informal enquiries about the call can be made by email to the Discussion Papers Editor, Ben Swallow,
bts3@st-andrews.ac.uk.