From the course: Financial Modeling and Forecasting Financial Statements

Forecast interest and income taxes

From the course: Financial Modeling and Forecasting Financial Statements

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Forecast interest and income taxes

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Here is another look at Hahn Company's forecasted income statement for year two, given the preliminary assumptions. Now, interest expense depends on how much interest-bearing debt a company has. In year one, Hahn Company reported interest expense of $30, with a bank loan payable of $300. These numbers imply that the interest rate on Hahn's loans is 10%. That's $30 divided by $300. Because the bank loan payable is expected to increase to $400 in year two, Hahn can expect interest expense of $40. That's 400 times 10%. Of course, interest rates are not constant. A careful forecast would require looking at the current level of interest rates in the economy and making any necessary adjustments. For example, if loan interest rates for companies of Hahn's riskiness have increased from 10% to 12%, then a better forecast of year two interest expense is $48, that's $400 times 12%. Now, income tax expense is determined by how much pre-tax income a company has. And the most reasonable assumption to make is that a company's income tax rate equal to income tax expense divided by pre-tax income will stay constant from year to year. If this reasonable assumption applied here, Hahn's tax rate in year two would be the same as the tax rate in year one, which was 43%. When applied to the forecasted pre-tax income for year two of $105, the income tax expense in year two would be a total of $45. That's $105 times 43%. However, in this case, a drastic change in forecasted income tax law indicates that the income tax rate in year two will be 60%. of being $45, income tax expense will be $63. That's $105 times 60%. Yikes! Now one other thing, the quality of this forecast is only as good as the assumptions that underlie it. In order to determine how much impact the assumptions can have, it is often useful to conduct a sensitivity analysis. This involves repeating the forecasting exercise using a set a set of pessimistic and a set of optimistic assumptions. Thus, one can construct a worst case scenario, standard case, and a best case scenario to use this in making decisions with the forecasted numbers. Now, let's step back and look at this forecasted income statement for year two. Is there anything disturbing or unsettling or fishy about the numbers here? Well, if we assume that all of the assumptions we used in making the forecast are reasonable, then this is actually a pretty bad news forecast. Bad news? Absolutely. We are forecasting a 50% increase in sales. Our people are going to work and sweat and think of innovative marketing approaches and attract new customers and substantially increase our volume of business in year two. And for what? The bottom line is that all this work will only increase net income by 5%, from $40 in year one to a forecasted $42 in year two. How is this possible for sales to go up so much and net income to go up so little? Well, take a look at the income before taxes line. Actual income before taxes in year one was $70. Forecasted income before taxes in year two, $105. Perfect, that represents precisely a 50% increase. We see that all of the disappointing news in this forecasted year two income statement stems from the expected increase in income tax rates. If tax rates were to remain unchanged in year two, then the 50% sales increase would lead to a 50% net income increase from $40 to $60. Go ahead and check my math. What this means is that in this example, the forecasted income statement indicates that the expectation of greatly increased tax rates suggests that it might not make sense to go to all of the effort to increase sales by 50%. Running through this financial modeling and forecasting exercise might cause us to change our plans completely.

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