The effect of information complexity on analysts' use of that information

In this study I investigate the relation between information complexity and financial analysts' use of that information. I rank by complexity six tax-law changes enacted by the Tax Reform Act of 1986, and then examine analysts' explicit forecasts of effective tax rates around those changes. I show that analysts' revisions of their forecasts of effective tax rates appear to impound the effects of the less complex tax-law changes but not the more complex changes. Furthermore, as expected, if analysts assimilate less complex (but not more complex) information, the magnitude of the errors in their forecasts of effective tax rates increases with the effects of the more complex tax-law changes, but is unrelated to the less complex changes. Taken together, these results indicate that analysts assimilate less complex information to a greater extent than they assimilate more complex information. Either analysts' abilities to incorporate specific information into their forecasts is a decreasing function of the complexity of that information, or analysts choose not to assimilate complex information because the cost would exceed the benefit. In either case, complexity reduces analysts' use of information. These results demonstrate the importance of considering information attributes, such as complexity, when investigating why analysts' forecasts fail to incorporate all public information.