Zero-value cases artificially satisfy causal sufficiency unless theoretically excluded

Evidence

This geometric interpretation of the Possibility Principle offers a solution to an important problem that arises in fuzzy-set analysis. The problem involves what to do with cases that are near the origin (i.e., cases near the (0,0,0) corner). As Ragin notes (2000, 250–51), when testing whether variables are causally sufficient for an outcome, observations with a zero for all the independent variables will always satisfy causal sufficiency and thus artificially inflate the number of … The Possibility Principle solves this problem by eliminating all of these cases with the exception of any impossible-but-happens cases. Ragin advises that one should not include cases with zero values across all independent variables when testing theories of causal sufficiency: the Possibility Principle provides a coherent theoretical rationale for excluding these problematic cases. — Gary Goertz, Social Science Concepts, 1308

Categorization

• XREF: Mirrors the Milgrom insight that full information about all traders is unnecessary — here, cases with no causal inputs carry no analytic weight either.