Accounting Aggregation and the Entropy Measure: An Experimental Approach.

Abstract The article explores the relationship between entropy measure and the perceived value of information and usefulness of the entropy application to financial statements. The amount of expected information from a message is determined by the amount of uncertainty or, more accurately, by the amount by which the uncertainty can be expected to be reduced as a result of receiving the message. After all, it could be argued by those who favor the presently suggested application of entropy to financial statements that the entropy measure may provide a reasonable approximation to the perceived value of information even though it need not be theoretically related in a systematic fashion to the actual value of information. When the decision situation and the loss from prediction errors are such that the expected value of information is monotone increasing with entropy, a highly positive correlation between the two was experimentally found. In this situation the entropy quantified a probability distribution that was made known to the subjects. But, as presently proposed in accounting, entropy is not intended to quantify a probability distribution of future outcomes relevant to the typical tasks of users of accounting statements.