We propose that causal attribution involves searching for underlying mechanism information (i.e., the processes underlying the relationship between the cause and the effect). This processing account can explain both the conjunction effect (i.e., conjunctive explanations being rated more probable than their components) and the discounting effect (i.e., the effect of one cause being discounted when another cause is already known to be true). When two explanations cohere with respect to a single mechanism, they would be judged to be more likely than a single explanation which partly supports that mechanism. When the two explanations imply two separate mechanisms, one would be discounted. In Experiment 1, both effects occurred with mechanism-based explanations but not with covariation-based explanations in which the cause-effect relationship was phrased in terms of statistical covariations without referring to mechanisms. In Experiments 2 and 3, the amount of the discounting and conjunction effects varied depending on the relationships between specific mechanisms in the two given explanations. We discuss why the current results pose difficulties for previous attribution models. (C) 1996 Academic Press, Inc.