Page 51 - Calculating Lost Profits
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variable, such as when a business can absorb more revenue with its current office or warehouse, but at a
               certain point another or a larger location is needed.


               The preceding regression has only one independent or explanatory variable: revenue. However, it is like-
               ly that there are other factors that affect executive compensation. For example, suppose that the fran-
               chise company hired a CFO in 2013. By adding a variable to the regression to address this fundamental
               change, the regression better explains the data, as seen in the following regression output.

        Figure 7.5. Selected Regression Output: Exec. Comp. Expense Regressed Against Revenue and CFO
        Presence



















               As can be seen in the preceding figure, the amount that executive compensation expense increases with
               a change in revenue is now lower (seen with a beta of 0.01, as compared to 0.04 in the single-variable
               regression), and the addition of a CFO is seen to increase annual executive compensation by
               $190,044.28, as seen by the beta on the CFO variable. Also relevant is that the regression with two ex-
               planatory variables accounts for a higher portion of the variability in executive compensation expense,
               as seen by the R-squared of 0.99, as compared to the other regression's R-squared of 0.82. In other
               words, this regression does a better job in explaining variations in executive compensation expense, and
               this expense is not as strongly influenced by changes in revenue as was indicated in the first regression.
               Finally, the t-scores of the two variables (4.16 for revenue and 9.05 for CFO) show that the CFO varia-
               ble has a stronger statistical relationship to changes in executive compensation than do changes in reve-
               nue.

               Courts have, in some situations, looked favorably on the use of regression as a method to evaluate
               whether costs are incremental or variable, or fixed.  fn 6   Of course, simply finding correlation between
               cost increases and revenue increases, and assuming that those increases are a result of increases in reve-
               nue, may be misleading. As in the preceding restaurant and CFO example, it may be that revenue has in-
               creased at the same time as a new executive was hired, and that costs would have been higher, regardless
               of revenue. Or, it may be that the hiring decision was as a result of expansion, which would support
               treating at least some of that expense as incremental.









        fn 6   See, for example, Schneider (Europe) AG v. Scimed Life Sys., Inc., 852 F. Supp. 813 (D. Minn. 1994), aff’d mem., 60 F.3d 839
        (Fed. Cir. 1995).


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