AS Sponsored Workshop. October 14-15, 2021 GESIS – Leibniz Institute for the Social Sciences in Mannheim. Organizers: Sebastian E. Wenz, Nora Müller, and Klaus Pforr (GESIS)   Understanding how an intervention or treatment did or would change the course of the world or how a particular state of the world came about, requires an understanding of cause and effect. The currently dominant perspective of counterfactual causality was subject of two AS sponsored workshops in 2019 and 2020. This third workshop builds on both by addressing a specific but fundamental topic in causal inference: effect heterogeneity. Effect heterogeneity is present whenever individual-level causal effects deviate from the average effect. Traditionally, social scientists have been tackling effect heterogeneity mainly through interaction terms. Recently, technically more ...
...  advanced and substantively different approaches—e.g., parametric and nonparametric techniques based on propensity scores, quantile regression models—have gained popularity and are subject of ongoing debates. This workshop picks up on these recent approaches and debates from three different angles:
  • Interpretation of heterogeneous effects
  • Estimating heterogeneous effects with observational and experimental data
  • Machine learning techniques for specification search
Keynotes will be given by Jennie E. Brand (UCLA), and Richard Breen (Nuffield College, Oxford University). See full Call for Applications here (submission deadline 30 June, 2021).
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