1. Financial Analysis, Planning and Forecasting Theory and Application By Alice C. Lee San Francisco State University John C. Lee J.P. Morgan Chase Cheng F. Lee Rutgers University Chapter 17 Interaction of Financing, Investment, and Dividend Policies

2. Outline  17.1 Introduction  17.2 Investment and dividend interactions: the interval-vs.- external financing decision  17.3 Interactions between dividend and financing policies  17.4 Interactions between financing and investment decisions  17.5 Implications of financing and investment interactions for capital budgeting  17.6 Debt capacity and optimal capital structure  17.7 The implication of different policies on the beta coefficient determination  17.8 Summary and conclusion  Appendix 17A. Stochastic dominance and its applications to capital-structure analysis with default risk

3. 17.1 Introduction

4. 17.2Investment and dividend interactions: the interval-vs.-external financing decision  Internal financing  External financing

5. 17.2Investment and dividend interactions: the interval-vs.-external financing decision TABLE 17.1 Payout ratio—Composite for 500 firms 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 0.580 0.567 0.549 0.524 0.517 0.548 0.533 0.547 0.612 0.539 0.491 0.414 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 0.405 0.462 0.409 0.429 0.411 0.380 0.416 0.435 0.422 0.399 0.626 0.525 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 0.343 0.559 0.887 0.538 0.439 0.418 0.137 0.852 0.340 0.346 0.327 0.774 1998 1999 2000 2001 2002 2003 2004 2005 2006 0.234 0.435 0.299 0.383 0.040 0.259 0.311 0.282 0.301

6. 17.2Investment and dividend interactions: the interval-vs.-external financing decision (17.1) where p = Profit margin on sales, d = Dividend payout ratio, L = Debt-to-equity ratio, t = Total asset-to-sales ratio. rr = Retention Rate ROE = Return on Equity

7. 17.2Investment and dividend interactions: the interval-vs.-external financing decision Let c = Nominal current assets to nominal sales, f = Nominal fixed assets to real sales, j = Inflation rate. So real sustainable growth is (17.2)

8. 17.3Interactions between dividend and financing policies  Cost of equity capital and dividend policy  Default risk and dividend policy

9. 17.3Interactions between dividend and financing policies (17.3) where g = Compound growth of assets over eight previous years; p = Dividend payout ratio on an annual basis; Lev = Interest charges/[operating revenues – operating expenses]; u = Error term.

10. 17.3Interactions between dividend and financing policies (17.4) where g = Compound growth rate, Lev = Financial risk measured by times interest earned, and F1, F2, F3, F4 = Dummy variables representing levels of new equity financing.

11. 17.3Interactions between dividend and financing policies TABLE 17.2 New-issue ratios of electric utility firms From Van Horne, J. C., and J. D. McDonald, “Dividend policy and new equity financing,” Journal of Finance 26 (1971):507-519. Reprinted by permission. F dummy variable grouping ABCDE New-issue ratio interval Number of firms in interval Mean dividend payout ratio Dummy variable coefficient Dummy variable t-statistic 0 49 0.681 1.86 (1.33) 0.001-0.05 16 0.679 3.23 (2.25) 0.05-0.1 11 0.678 1.26 (0.84) 0.1-0.15 6 0.703 0.89 (0.51) 0.15 and up 4 0.728 N.A. (N.A.)

12. 17.3Interactions between dividend and financing policies (17.5) where S = Total value of the firm’s stock, V = Total firm value, C = Constant coupon payment on the perpetual bonds, r = Riskless rate of interest, L = A complicated risk factor associated with possible default on the required coupon payment. (17.6)

13. 17.4Interactions between financing and investment decisions  Risk-free debt case  Risky debt case

14. 17.4Interactions between financing and investment decisions Maximize dV (xj, yt, Dt, Et) = W, a) Uj = x j - 1  0 (j = 1, 2,..., J); b) = y t - Z t  0 (t = 1, 2,..., T); (17.7) c) = -C t - [y t - y t-1 (1 + (1 - τ)r)] + D t - E t  0,

15. 17.4Interactions between financing and investment decisions Max W’ = W - L j (x j - 1) - L ft (y t - Z t ) - L ct {-C t - [y t - y t-1 (1 + (1 - τ) r)]} + D t - E t ). (17.7′) (17.8)

16. 17.4Interactions between financing and investment decisions F t - L ft + L ct - L c,t-1 [1 + (1 - τ) r]  0. (17.9) (17.10) (17.11) (17.12)

17. 17.5Implications of financing and investment interactions for capital budgeting  Equity-residual method  After-tax weighted-average, cost-of-capital method  Arditti and Levy method  Myers adjusted-present-value method

18. 17.5Implications of financing and investment interactions for capital budgeting Table 17.3 Definitions of variables R t = Pretax operating cash revenues of the project during period t; C t = Pretax operating cash expenses of the project during period t; dep t = Additional depreciation expense attributable to the project in period t; τ c = Applicable corporate tax rate; I = Initial net cash investment outlay; D t = Project debt outstanding during period t; NP = Net proceeds of issuing project debt at time zero; r t = Interest rate of debt in period t; k e = Cost of the equity financing of the project; k w = After-tax weighted-average cost of capital (i.e., debt cost is after-tax); k AL = Weighted average cost of capital -- debt cost considered before taxes; ρ = Required rate-of-return applicable to unlevered cash-flow series, given the risk class of the project. r, k e, and ρ are all assumed to be constant over time.

19. 17.5Implications of financing and investment interactions for capital budgeting (17.13) (17.14) (17.15) (17.16)

20. 17.5Implications of financing and investment interactions for capital budgeting Table 17.4 Application of four capital budgeting techniques From Chambers, D. R., R. S. Harris, and J. J. Pringle, “Treatment of financing mix in analyzing investment opportunities,” Financial Management 11 (Summer 1982): 24-41. Reprinted by permission. Inputs: 1. = 0.112 2. r = 0.041 3. = 0.46 4. = 0.0802 5. w =.6 MethodNPV resultsDiscount rates 1. Equity-residual 2. After-tax WACC 3. Arditti-Levy WACC 4. Myers APV $230.55 270.32 261.67 228.05 =.112 =.058 =.069 r =.041 and =.0802

21. 17.5Implications of financing and investment interactions for capital budgeting Table 17.5 Inputs for simulation From Chambers, D. R., R. S. Harris, and J. J. Pringle, “Treatment of financing mix in analyzing investment opportunities,” Financial Management 11 (Summer 1982): 24-41. Reprinted by permission. ProjectNet cash inflows per yearProject life 12341234 $300 per year $253.77 per year $124.95 per year $200 per year, years 1-4 $792.58 in year 5 5 years 20 years 5 years For each project the initial outlay is $1000 at time t = 0, with all subsequent outlays being captured in the yearly flows. Debt Schedule 1.Market value of debt outstanding remains a constant proportion of the project ’ s market value. 2.Equal principal repayments in each year. 3.Level debt, total principal repaid at termination of project. Inputs: = 0.112 = 0.085 W = 0.3 r = 0.041 = 0.0986 = 0.46

22. 17.5Implications of financing and investment interactions for capital budgeting Table 17.6 Simulation results From Chambers, D. R., R. S. Harris, and J. J. Pringle, “Treatment of financing mix in analyzing investment opportunities,” Financial Management 11 (Summer 1982): 24-41. Reprinted by permission. Net-present-value under alternative debit schedule ProjectCapital budgetingConstant debt ratioEqual PrincipalLevel debt 12341234 After-tax WACC Arditti-Levy WACC Equity-Residual Myers APV (M&M) Myers APV (M) After-tax WACC Arditti-Levy WACC Equity-Residual Myers APV (M&M) Myers APV (M) After-tax WACC Arditti-Levy WACC Equity Residual Myers APV (M&M) Myers APV (M) After-tax WACC Arditti-Levy WACC Equity Residual Myers APV (M&M) Myers APV (M) 182 160 182 0 -18 0 182 138 182 155 182 179 167 157 182 0 -3 -19 0 182 169 128 119 182 174 147 146 182 187 202 166 182 0 7 32 -10 0 182 186 194 150 182 183 156 182

23. 17.5Implications of financing and investment interactions for capital budgeting a) Operating flows = (R t - C t - dep t )(1 - τ c ) + dept = ($4000 - $1000 - $500)(1 - 0.46) + $500 = $1850. b) Financial flows = τ c rD t = (0.46)(0.09)($3600) = $149.04 c) k w = wr(1 - τ c ) + (1 - w)k e = (0.6)(0.09)(1 - 0.46) + (1 - 0.6)(0.15) = (0.029) + (0.06) = 0.089. d)

24. 17.6Debt capacity and optimal capital structure Table 17.7 Acceptance-rejection criteria *In the special instance where both relationships are strict equalities the firm is, of course, indifferent in attitude toward the project. AcceptRejectIndeterminate and or

25. 17.6Debt capacity and optimal capital structure R e = WR p - R d (W - 1), (17.17) R e = R d + W(R p - R d ), (17.17a) S e = WS p. (17.18)

26. 17.6Debt capacity and optimal capital structure (17.19) (17.20) (17.18a)

27. 17.6Debt capacity and optimal capital structure (17.21) (17.22) (17.22a)

28. 17.6Debt capacity and optimal capital structure (17.22a′) where = Cost of financing a project, ρ pe = Correlation between R p and R e, S p = Estimated standard deviation of R p, S e = Estimated standard deviation of R e.

29. 17.6Debt capacity and optimal capital structure (17.23) (17.24) (17.25)

30. 17.6Debt capacity and optimal capital structure (17.26) (17.27) (17.28)

31. 17.6Debt capacity and optimal capital structure (17.29) ks = 0.09 + (0.16 - 0.09)(1.5) = 0.195.

32. 17.6Debt capacity and optimal capital structure Table 17.8 Valuation information for Project X A. Project Cash-Flow Information 1. NOI = $18,000 2. Project maturity = infinity 3. Marginal tax rate for ABC = 45% 4. Initial cash outlay = $800,000 B. Required Return Information 1. R f = 0.09 2. R m = 0.16 3. β 0 = 1.5 C. Debt-Capacity Information 1. Standard deviation in project cash flows = $8,000 2. Correlation between firm and project cash flows = 0.5 3. Cost of new debt, r = 0.10

33. 17.6Debt capacity and optimal capital structure Fig. 17.1 (a) Distribution of unencumbered cash flows for ABC Company.

34. 17.6Debt capacity and optimal capital structure Fig. 17.1 (b) Distribution of unencumbered cash flows after project is undertaken.

35. 17.6Debt capacity and optimal capital structure D = DSC/kd = ($12,643.75)  (0.10) = $126,438. (17.25′)

36. 17.7 The implication of different policies on the beta coefficient determination  Impact of Financing Policy on Beta Coefficient Determination  Impact of Production Policy on Beta Coefficient Determination  Impact of Dividend Policy on Beta Coefficient Determination

37. 17.7 The implication of different policies on the beta coefficient determination (17.25’) (17.31)

38. 17.7 The implication of different policies on the beta coefficient determination where r = the risk-free rate, = return on the market portfolio, = random price disturbances with zero mean,, an elasticity constant b = contribution of labor to total output = the market price of systematic risk (17.32)

39. 17.7 The implication of different policies on the beta coefficient determination (17.33)

40. 17.7 The implication of different policies on the beta coefficient determination (17.34) where p = expected price of output µ = reciprocal of the price elasticity of demand, w = expected wage rate = random shock in the wage rate with zero mean are as defined in Equation (17.30)

41. 17.7 The implication of different policies on the beta coefficient determination = the firm’s systematic risk when the market is informationally imperfect and the information asymmetry can be resolved by dividends. = the firm’s systematic risk when market is informaitonally perfect. = a signaling cost incurred if firm’s net after-tax operating cash flow X falls below the promised dividend D. = firm’s dividend payout ratio. = cumulative normal density function in term of payout ratio. (17.35)

42. 17.8 Summary and conclusion In this chapter we have attacked many of the irrelevance propositions of the neoclassical school of finance theory, and in so doing have created a good news-bad news sort of situation. The good news is that by claiming that financial policies are important, we have justified the existence of academicians and a great many practicing financial managers. The bad news is that we have made their lot a great deal more difficult as numerous tradeoffs were investigated, the more general of these comprising the title of the chapter. In the determination of dividend policy, we examined the relevance of the internal-external equity decision in the presence of nontrivial transaction costs. While the empirical evidence was found to be inconclusive because of the many variables that could not be controlled, there should be no doubt in anyone’s mind that flotation costs (incurred when issuing new equity to replace retained earnings paid out) by themselves have a negative impact on firm value. But if the retained earnings paid out are replaced whole or in part by debt, the equity holders may stand to benefit because the risk is transferred to the existing bondholders -- risk they do not receive commensurate return for taking. Thus if the firm pursues a more generous dividend-payout policy while not changing the investment policy, the change in the value of the firm depends on the way in which the future investment is financed.

43. 17.8 Summary and conclusion The effect that debt financing has on the value of the firm was analyzed in terms of the interest tax shield it provides and the extent to which the firm can utilize that tax shield. In Myers’ analysis we also saw a that a limit on borrowing could be incorporated so that factors such as risk and the probability of insolvency would be recognized when making each capital-budgeting decision. When compared to other methods widely used in capital budgeting, Myers’ APV formulation was found to yield more conservative benefit estimates. While we do not wish to discard the equity-residual, after-tax weighted cost-of-capital method or the Arditti-Levy weighted cost-of-capital method, we set forth Myers’ method as the most appropriate starting point when a firm is first considering a project, reasoning that if the project was acceptable following Myers’ method, it would be acceptable using the other methods -- to an even greater degree. If the project was not acceptable following the APV criteria, it could be reanalyzed with one of the other methods. The biases of each method we hopefully made clear with the introduction of debt financing.

44. 17.8 Summary and conclusion Section 17.6 outlined practical procedures for attaining optimal capital structures subject to probability-of-insolvency constraints or costs incurred attributable to the risky debt financing. If management is able to specify the tolerance for risk, or the rate at which monitoring costs are incurred, then an upper limit on debt capacity can be stated as the amount of interest expense the firm can afford. In the case of regulated firms, we also consider capital-structure decisions, in light of the inability of the equity holders to acquire the benefits of the interest tax shield; and we concluded that regulated firms, in the best interests of their shareholders and of society, should issue debt only to the extent it does not jeopardize the equity stake or the existence of the firm. In section 17.7, we have discussed how different policies can affect the determination of beta coefficient. In essence, this chapter points out the vagaries and difficulties of financial management in practice. Virtually no decision concerning the finance function can be made independent of the other variables under management’s control. Profitable areas of future research in this area are abundant; some have already begun to appear in the literature under the heading “simultaneous-equation planning models.” Any practitioner would be well advised to stay abreast of developments in this area.

45. Appendix 17A. Stochastic dominance and its applications to capital-structure analysis with default risk 17.A.1 INTRODUCTION 17.A.2 CONCEPTS AND THEOREMS OF STOCHASTIC DOMINANCE 17.A.3 STOCHASTIC-DOMINANCE APPROACH TO INVESTIGATING THE CAPITAL- STRUCTURE PROBLEM WITH DEFAULT RISK 17.A.4 SUMMARY

46. Appendix 17A. Stochastic dominance and its applications to capital-structure analysis with default risk (17.A.1) (17.A.2a) (17.A.2b) where G(t) ≠ F(t) for some t. (17.A.3)

47. Appendix 17A. Stochastic dominance and its applications to capital-structure analysis with default risk

48. (17.A.4) (17.A.5) (17.A.6)

49. Appendix 17A. Stochastic dominance and its applications to capital-structure analysis with default risk (17.A.7) (17.A.8) (17.A.9)

50. Appendix 17A. Stochastic dominance and its applications to capital-structure analysis with default risk 17.A.4 SUMMARY In this appendix we have tried to show the basic concepts underlying stochastic dominance and its application to capital-structure analysis with default risk. By combining utility maximization theory with cumulative-density functions, we are able to set up a decision rule without explicitly relying on individual statistical moments. This stochastic- dominance theory can then be applied to problems such as capital-structure analysis with risky debt, as was shown earlier.