The Effect Of Causality And Specificity On Data Use

A subset of recent research on auditor judgments under uncertainty has focused on their possible use of heuristics in making audit judgments (e.g., Joyce and Biddle [1981], Johnson [1983], and Swieringa et al. [1976]). However, Libby [1981] notes that one heuristic may be used in a particular decision context to explain different judgments depending on what data are attended to. Tversky and Kahneman [1980] and Ajzen [1977] argue that individuals tend to organize events in terms of causeeffect relations, and a crucial feature affecting attention to and use of data is whether the data fit into a causal link concerning the judgment variable. Presumably, individuals will attend to data that have a causal interpretation to a greater extent than data that have equal informativeness (diagnosticity) but are noncausal. In contrast, Bar-Hillel [1980] suggests that the central notion in explaining data use is relevance. That is, individuals order data depending on their perceived degree of relevance to the target decision, and causality is merely sufficient, but not necessary, in inducing relevance. Another factor of relevance is the level of specificity of the data. If some data refer to a population and other data refer to some subset of the population, the latter would be more relevant for judgments about a member of that subset. In this paper I present the results of two experiments designed to test for the effect of causality and specificity on the use of financial data. A