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This report is constructed as follows: section I introduces the selected firm briefly; section II and Ill gives projected income statement and balance sheet; section IV demonstrates how we calculate FCC, followed by firm value estimation; section V provides a sensitively analysis of firm value to sales growth rate, FCC growth rate In second stage and WAC. I Company Profiles Johnson & Johnson Is a U. S. Multinational medical devices, pharmaceutical and consumer packaged goods manufacturer founded in 1886. Its common stock is a component of the DOD Jones Industrial Average and the company is listed among the Fortune 500.
Johnson & Johnson ranked at the top of Harris Interactive National Corporate Reputation Survey for seven consecutive years up to 2005, was ranked as the world’s most respected company by Baron’s Magazine in 2008, and was the first corporation awarded the Benjamin Franklin Award for Public Diplomacy by the U. S. State Department in 2005 for its funding of international education programs. Johnson & Johnson is headquartered in New Brunswick, New Jersey with the consumer dolls being located in Sicilian, New Jersey.
The corporation Includes some 250 subsidiary companies with operations In over 57 countries and products old In over 175 countries, Johnson & Johnson had worldwide sales of $65 billion for the calendar year of 2011. The accounts In Balance Sheet are projected mainly based on sales and corresponding elaborations are demonstrated in depth in following parts. II Income Statement In this part, we project items in the income statement with various methods, including sales, COGS, SO&A, D&A, interest expense, etc.
All the regression data have been adjusted into real term to obtain real growth rate, then transferred back into nominal growth rate for sales projection. Sales Revenue Sale projection Is based on LOS estimation method with Independent variable year t. Sample years are from 1985 to 2011, with 2008 to 2011 dropped from sample, as the growth rate turns out negative and stands as outline’s. Since sales grow In an exponential way, we take In(sale) as dependent variable and maintain constant term, to improve estimation accuracy and obtain higher R square.
As can be seen from the chart, coefficient between sales and year variable is around 0. 067, which means In(sale) grows by 6. 7% on average in real terms. Real growth rate=EXPO(6. 7%)-1=7. O%. Adjusted by 4% inflation, we derive nominal sale growth rate, 1 1. %. P value is close to O, which indicates an accurate estimation of sales growth. Len real scales R-squared 0. 9954 Ads R-squared 0. 9942 Len real sales Coffee. SST. Err. Year 0. 067688 0. 00 36. 72 0. 00000 0. 06389 0. 07 cons -124. 833600 3. 68 -33. 90 -132. 41860 -1 17. 5 Costs This part contains estimation of COGS, SO. Considering the fact that cost are closely related to revenue, we directly regress this two cost on sales respectively, based on LOS estimation with constant term. Sample years are from 1985 to 2011, no outliers excluded. Regression results are as follows: COGS(1985-2011)=_cons R-squared 0. 893 Ad] R-squared 0. 9889 COGS Coke f. SST. Err. P>let [95% Con. Interval] Sales 0. 2195667 0. 0045566 48. 19 0. 2101823 0. 228951 1 1634. 574 192. 1098 8. 51 1238. 916 2030. 231 SO 0. 961949 0. 005735 51 . 65 0. 2843835 0. 3080064 2219. 719 241 . 7947 9. 18 1721 . 734 2717. 705 As shown in the chart, coefficient between COGS and sales is 0. 22, which means cost changes 22% with 1% change in sales. In the same way, coefficient for SO is 0. 40. Considering the fact that sales and R can interact with each other, R is regressed on year variable t instead of on sales, to eliminate endogenous issue. Since R grows in an exponential way, we take In(R) as dependent variable, in order to derive linear estimation.
Sample years are from 1985 to 2007, with 2008 to 2011 dropped as outliers, which mainly results from financial crisis and its lasting effect on economy as a whole. Len R-squared 0. 988 Ad] R-squared 0. 9874 0. 1048805 0. 0025229 41 . 57 0. 0996338 0. 1101272 -201 . 4125 5. 035796 -21 1 . 885 -190. 9399 As can be seen from the table, coefficient turns out to be 0. 10, which means 1% increase in sales will lead to 10% rise in In(R). When transferred into real growth rate, R grows by 1 1 . 1% on average every year. R square is more than 0. 98, indicating strong explaining power of year variable.
Depreciation & Amortization Since depreciation mainly derives from property, plant and equipment, depreciation estimation is based on regression with PEP. According to LOS estimation without constant term, depreciation takes around 8. 0% of PEP. In the same way, amortization is regressed on intangible assets, with coefficient of 2. 57%. Interest Expenses Interest income and expense are estimated separately, by using average interest income / cash ratio (0. 09), and interest expense / (debt + retained equity) ratio (0. 01), especially, to project interest items.
Tax Rate Tax rate calculation is based on average of historical data, from 1985 to 2011, with an average tax rate of 22%. Ill Balance Sheet Accounts Receivable Accounts Receivable is projected assuming the average collection period, a measure of asset utilization, would be stable if no trigger events occur. Actually, regression on accounts receivable itself has been run, only to finding that there is no significantly steady pattern though. Inventory When forecasting inventory, the historical average in selected years of inventory days is assumed to be continuing.
It is based on similar consideration to projected accounts receivable. Deferred taxes on income Since this account is closely related to income, we calculate the ration of deferred taxes on income to sales instead of assets. It is because estimated value of sales would not be impacted by various assumptions on other accounts that we adopted sales rather than net earnings. Property, plant and equipment Forecast gross fixed assets are mainly based on SFA turnover. Property, plant and equipment, net is then computed by subtracting accumulated depreciation, which has been estimated in the income statement.
Intangible assets & Goodwill We project intangible assets and goodwill according to the ratio of intangible assets & goodwill over sales revenue. In most cases, the total value of intangible assets and goodwill change with total assets proportionately. As the forecasts on total assets may be substantially affected by subjective Judgments, we choose sales revenue as the denominator to get this account standardized. Other assets Other assets are forecasted in the same method as the previous account. Current liabilities As required in the description, we consolidate accounts with similar nature into one account.
Accounts payable, accrued expenses and other accrued items, in this case, are all consolidated into current liabilities. We then run a regression on itself and get Total assets are forecasted by coefficients from the regression on the ratio, sales/ assets. Cash and debt are simultaneously chosen as the plug to match assets and liabilities. To be more specific, we apply the third model described in the class, adjusting cash only when FCC is positive and adjusting both cash and debt if FCC is negative.