Join the Department of Economics for a critical discussion of predictions in social science research.
Speaker: Séverine Toussaert, University of Oxford.
Abstract
Researchers rely on their beliefs about future outcomes when making important decisions, such as whether to pursue a risky project or to accept a paper for publication.
In recognition of the scientific value of these beliefs, increasingly many researchers are collecting predictions of research results, although the practice is not yet systematic.
Before it becomes so, it could be beneficial to obtain a better understanding of the returns to collecting predictions and the best practices to follow when doing so.
We contribute to this by conducting a narrative review and a quantitative meta-analysis of the literature of participating papers in the social sciences (N=108).
This paper presents preliminary findings from our systematic evaluation and conceptual discussions that address four key themes:
- why predictions are being collected
- who is collecting and providing them
- how this is being done
- whether/when predictions tend to be informative.
We leverage a pooled forecast dataset to tackle the final question.
Our discussion concludes with evidence-based suggestions on best practices and possible next steps for the literature.
About the speaker
Séverine Toussaert is an Associate Professor in Economics at the University of Oxford.
Her research uses a combination of theory and experiments to study topics at the intersection of economics and psychology.
She is particularly interested in behavioural decision theory and applications to health as well as in metascience questions.
One of her main research interests pertains to the study of self-control in different contexts such as weight loss, smoking cessation or work productivity.
Some of her recent research on these topics has been published in Econometrica and the Journal of Economic Theory.
She has also been working with an interdisciplinary team since 2015 on app-delivered behavioural change, particularly in the development of mHealth technologies to help smokers kill their habit.
In metascience, she is interested in how researchers work, and in optimising the peer review process.
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