A further problem with the data stems from the grouping of different industries into standard categories. The groupings can hide differences in cyclical sensitivity among industries, which confuses the effect of different economic conditions with the differences in relative tax burdens. This is clearly the case in the Financial Industry category. High interest rates in the sample period benefited insurance companies, but hurt real estate and banking companies. Since all three were grouped together in the same category, the effect of the interest rate cycle was mixed together with underlying differences in tax burdens.

In addition, the different categories contain a widely varying number of firms. Among other problems, this makes the selection of the statistical measure for the "average" tax burden somewhat complicated, and renders impossible the calculation of a measure of variation of the tax burden. [19]

One further aggregation problem arises from the special credits allowed smaller businesses under the SBT, which lower their relative tax burdens. Those industry categories containing a large number of small businesses will have a lower relative tax burden, merely because of the size of the firms in the category. [20]

The groupings of industries into standard categories can hide differences between the industries. In the Financial Industry category, banks, insurance companies, and real estate companies are grouped together, even though substantial differences exist among the three in business operation. Conclusions about a group cannot be generalized to all its components without further analysis of disaggregated data.