Graphical Models of Causation (WITHDRAWN)
Paul Huenermund · Academy of Management Proceedings · 2017
The computer science and artificial intelligence literature provides powerful tools for causal inference with observational data based on graphical models of causation. A paper by Durand and Vaara (2009), which introduced causal graph modeling to the strategy literature, has been criticized by Ellsaesser et al. (2014). In this paper I develop a counter-critique of Ellsaesser et al. and show that the objections they put forward are unjustified. I then proceed to illustrate the advantages of graphical models for causal inference in management research.