Revisiting the omitted variables argument: Substantive vs. statistical adequacy

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Akaike-type criteria and the reliability of inference: Model selection versus statistical model specification (2010, methodology): “…that both substantive and statistical information play important roles in learning from data, and in practice empirical models constitute an amalgam of both sources of information, but the role of each type of information has not been delineated in modern statistics; Lehmann (1990), Spanos (2006a).”
Detection of Unfaithfulness and Robust Causal Inference (2008, background): “To test the CFC, intuitively, one needs information about the causal structure in the first place (see Spanos 2006 for an example of testing the CFC with assumptions about causal structure).”