ACTA
WASAENSIA
No. 90
Business Administration 35
Accounting and Finance
Timo Salmi – Ilkka Virtanen
Economic Value Added
A simulation analysis of the trendy,
owner-oriented management tool
UNIVERSITAS WASAENSIS
VAASA 2001
Reviewer Professor, CEO Teemu Aho
Teemuaho Oy
Raatimiehenkatu 18
FIN-53100 Lappeenranta
Finland
ACTA WASAENSIA
Contents
Abstract 4
1. Introduction 5
2. Categories of Previous Research 6
3. Research Problem and Approach Selection 8
4. The Simulation Engine 9
5. Producing EVA and Key Financial Ratios 13
6. Input Data Description 16
7. Effect of the Cost Components 17
8. Effect of Growth Strategies 20
9. Signaling Financial Distress 23
10. Conclusion 23
Appendix 1. List of Symbols 26
Appendix 2. Example Simulated Time Series. 27
References 30
ACTA WASAENSIA
Abstract
Salmi, Timo and Ilkka Virtanen (2001). Economic Value Added: A simulation analysis of
the trendy, owner-oriented management tool. Acta Wasaensia No. xx, 33 p.
The value-based management performance measure EVA introduced by Stern Stewart &
Co. is an incarnation of the underlying residual income (RI) concept. The concept is
evaluated and compared with traditional profitability measures within a controlled
simulation framework. It is observed that EVA is very sensitive to its cost of equity
component, but it is unexpectedly insensitive to its cost of debt component under regular
conditions. EVA and its variability are observed to be strongly affected by the firm's
growth policies because of leverage effects. EVA is observed to be much more unstable
than the traditional return on investment and directly related to the return on equity
measure. Methodologically, the paper demonstrates the advantages of using a controlled
simulation approach in financial research.
Timo Salmi, Department of Accounting and Finance, and Ilkka Virtanen, Department of
Mathematics and Statistics, University of Vaasa, P.O. Box 700, FIN-65101 Vaasa,
Finland.
Email: ts@uwasa.fi
itv@uwasa.fi
Key words: Simulation; Residual income; Economic Value Added; Return on investment;
Return on equity
Acknowledgments: We gratefully acknowledge the financial support from Jenny and Antti
Wihuri foundation for the research. Our thanks are due to professors Teemu Aho and Erkki
K. Laitinen for useful insights.
ACTA WASAENSIA 5
1. Introduction
The success of the firm depends on its management having theoretically sound and in
practice operational tools for planning, decision making and monitoring. Developing new
management accounting and decision tools is a very current subject both in business and
consultation practice, as well as in academic research. During the last few years this
development has become even more prominent thanks to several new techniques and
concepts, both financial and non-financial. These include Activity Based Management,
Balanced Scorecard, Benchmarking, Total Quality Management, and the Economic Valued
Added (EVA) and Market Value Added (MVA) variants.
The firm has a number of stakeholders with differing, sometimes conflicting goals. The
stakeholders include the owners, lenders, management, personnel, customers, suppliers and
creditors, government and regulatory agencies. In corporate governance agency theory the
managers are regarded as agents of the owners in stockholders' wealth-maximization.
Among the management tools EVA, in particular, emphasizes the interests of the owners.
The concept of the economic value added is similar to the traditional accounting concept of
Residual Income (RI); see Stark and Thomas (1998:446) and their references. The concept
emerges in several variations and incarnations including the trade-marked Stern Stewart &
Co's EVA with its copious accounting adjustments (Stewart 1991, Stewart 1994, Stern,
Stewart & Chew 1995, and Stern Stewart & Co. 1997).
In line with the theory of finance the RI derivative EVA is commonly advocated as a
management tool because the goal of the firm is to add to the value of the owners' wealth.
In other words, the owners expect a maximum compensation over the cost of the capital
invested in the firm. A central question concerning EVA is how sensitive this management
tool is to the changes in its various components, management policies and external
economic factors.
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Despite the unambiguous theoretical definition, applying EVA even in its pure, theoretical
format is not straight-forward. EVA is defined as the difference between the firm's profit
and cost of all capital employed, i.e. the weighted average cost of debt and equity.
Measuring the profit of the firm and measuring the components of the cost of capital is
problematic both in theory and in practice. In particular, measuring the cost of equity is a
highly involved issue. A simulation approach is used in this paper to better facilitate
investigating the behavior of EVA under varying management policies and cost conditions.
2. Categories of Previous Research
The origins of the value added concepts date all the way back to the early 1900's
(Bromwich & Walker, 1998:392). The concept resurfaced in 1990's much thanks to the
consulting firm Stern Stewart & Co's successful launching of the economic value added as
the trademark EVA and the subsequent adoption by several major corporations. The
ensuing research work in literature roughly falls into three categories.
1. Mainly professional literature mostly aimed at presenting, promoting or discussing the
EVA concepts in relation to consulting work. While most of this, partly anecdotal,
literature looks at the advantages of the concept, a few critical views also occur in this
category. The seminal work in this first category is Stewart (1991). Subsequent sources
are too numerous for an extensive listing, but for instance there is material such as
Milunovich & Tsuei (1996), Anctil, Jordan & Mukherji (1998), Damodaran (1999),
Mouritsen (1998), Bowen & Wallace (1999), and Dodd & Johns (1999). There also is
much WWW based material such as Mäkelä (1998), Weissenrieder (1999), and Stern
Stewart & Co. (2000).
2. Empirical research literature measuring the strength of the relation between market
returns (or market value) and EVA compared to the relation between market returns and
the traditional income measures. O'Byrne (1996:125) concludes that "EVA, unlike
NOPAT [net operating profit after taxes] or other earnings measures like net income or
ACTA WASAENSIA 7
earnings per share, is systematically linked to market value. It should provide a better
predictor of market value than other measures of operating performance." Also
Uyemura, Kantor & Pettit (1996) arrive at similar conclusions. Stark & Thomas
(1998:445) provide "some support for the advocates of the use of RI for planning and
control" from the market relation. However, Biddle, Bowen & Wallace (1997:331-332)
find "little evidence to support the Stern Stewart claim that EVA is superior to earnings
in its association with stock return or firm values". On the other hand, EVA or RI do not
do decisively worse. Chen & Dodd (1997:331) conclude that EVA measures provide
relatively more information than the traditional measures of accounting in terms of the
stock return association, but that EVA should not entirely replace the traditional
measures since measures such as E/P, ROA and ROE have incremental value in
monitoring firm performance. They also observe that there is no significant difference
between EVA and the traditional RI in terms of the association with stock returns. The
most critical results are by Bao & Bao (1998).
3. Literature looking at EVA as a management tool from the point of view of the
accounting measurement. O'Hanlon & Peasnell (1998) thoroughly discuss EVA as a
value-based performance indicator, Stern Stewart Co's intricate adjustments, EVA
benchmarks, and EVA-base bonuses. Bromwich & Walker (1998) add to the theoretical
discussion by pondering the EVA debate all the way from Hicksian income concepts.
Pfeiffer (2000) considers mathematically EVA vs. discounted cash flow methods for
resolving internal agency problems in decentralized decision making. Besides the
theoretical discussion understanding is needed about the numerical behavior of the EVA
under different conditions and about EVA's numerical relationship to the accounting
measures like Return on Investments (ROI), Return on Equity (ROE) and to economic
profitability measures like the Internal rate of Return (IRR).
ACTA WASAENSIA 8
3. Research Problem and Approach Selection
The partly conflicting results in the earlier literature make it difficult to get a grasp of
EVA’s behavior vis á vis the traditional accounting measures. More information is needed
of the behavior patterns of the EVA measure. The generic research task of this paper is to
observe and assess how the EVA measure behaves under different, realistic financial
conditions and compare it to the simultaneous behavior of the more traditional profitability
indicators such as ROI, ROE and IRR. This general task involves the following, more
detailed research questions:
• How sensitive is EVA to the level of the debt and equity cost components?
• Business firms typically assume different kind of growth strategies. Is EVA
sensitive to the firm's alternative growth strategy choices?
• How steady is EVA? Will it be affected by cyclical business fluctuations and
irregular events in the level of the firm's activities?
• What is the relationship between the behavior of EVA, ROE and ROI?
• Will EVA give consistent signals under different financial developments for
the firm? In particular, will a bankruptcy-bound firm's EVA give a sufficient,
early warning? On the other hand are there circumstances where EVA gives too
prudent a picture under an auspicious future?
To tackle the posed problems suitable cases of firms are needed which highlight each of the
above items. The ordinary option would be to search for representative, actual business
data which would suit the questions. There are, however, complications: 1) suitable,
unambiguous cases have to be found for achieving desired experimental designs, 2) the
unavoidable problems in estimating the components of the cost of capital can affect the
reliability of the results, 3) the practical accounting measurement problems of income
determination and asset valuation must be tackled in the estimation. Instead, we adopt and
extend an approach using simulated financial time-series in the spirit of Henderson,
Peirson & Brown (1992) and Salmi & Virtanen (1997), which represent a controlled
simulation approach. Also other simulation approaches have been applied, such as the
ACTA WASAENSIA 9
"what-if" kind of simulation for EVA decisions in Taylor, Blackall & Haas (1999). The
major advantage of using simulated data is being able to generate different business
situations for observation at will. Simulation also more easily facilitates ceteris paribus
observation of the different cases. The second important advantage of the simulation
approach is the following. The true, economic profit of a business firm is not easily
measured from financial statements. However, in our simulation approach the true
profitability (IRR) of the simulated firm is readily known, since it can be defined as one of
the model's input parameters. Furthermore, the difficulties in defining the correct cost of
equity can consequently be avoided since, adapting Fama & French (1999), the true
profitability of the simulated firm defines the cost of equity.
4. The Simulation Engine
The simulation engine used in Salmi & Virtanen (1997) is adopted. It is extended by
incorporating financing into the model. The time-series data generated by the simulation
model facilitates studying varying cost of capital situations, varying profitability situations,
the firm's growth strategies, and various business cycle and irregularities conditions. In
particular, the development of the EVA, and the key financial ratios such as the financial
leverage, ROI, and ROE are observed using the chosen experimental design.
In the simulation model the capital investments are generated by the following multi-
plicative process with an exponential trend, a sinusoidal cycle, and an irregular variation
made up of a normally-distributed noise component and a potential shock component
(1) gt = g0(1+k)t{1 + A sin[(2πt/ Ψ) + φ]}(1 + σz)(1 + δ tτ Y) , t = 1,...,T.
The symbols are listed in Appendix 1. Using this capital investment generating process
produces financial time series which closely resemble the time series profiles observed on
actual business firms. See e.g. the sample of the time series drawn in Salmi et al. (1984:46-
48).
ACTA WASAENSIA 10
The capital investments gt induce subsequent cash inflows which can be defined in terms
of a set of contribution coefficients bi. The contribution coefficients fix a capital
investment's cash flow pattern. The total contribution ft in year t cumulates from the
contributions from the capital investments made in the earlier years
min(N,t) min(N,t)
(2) ft = Σ fti = Σ bi gt-i.
i=1 i=1
The run of the simulation years t = 1,...,T has been omitted for brevity since Formula (1).
Assuming constant returns of scale and constant profitability in the customary fashion, the
contribution coefficients define the profitability of the firm in terms of the internal rate of
return
N
(3) Σ bi (1+r)-i = 1.
i=1
In the numerical simulation a distribution pattern i.e. the shape of the contribution
coefficients must be fixed. The negative binomial distribution corresponding to a typical
product life cycle is used (see Salmi & Virtanen, 1997)
(4) bi = s(i+1) q2 (1-q)i , i = 1,...,N.
Other distribution patterns, such as a uniform pattern or a steadily declining pattern could
also be adopted. Such alternatives are not, however, presented in this paper, since we
observed that they do not substantially affect the nature of the numerical results.
The profit of the accounting period is defined by a simple income statement as the cash
inflows less depreciation less the interest on loans
(5) pt = ft - dt - ht.
ACTA WASAENSIA 11
The common straight-line depreciation method is applied by the simulated firm. Hence the
depreciation, assuming a life-span of N years, is defined by
min(N,t)
(6) dt = Σ (1/N)gt-i .
i=1
The same goes for the alternative depreciation methods as goes for alternative contribution
patterns. They can be omitted from the presentation, since they are not crucial from point of
view of the nature of the numerical results. The interest payments in (5) are defined later by
Formula (9).
The simplified balance sheet of the simulated firm is depicted by Figure 1.
Assets Liabilities +
Owner's equity
Pt Working capital Debt Bt
+ Plant assets Common stock St
Retained earnings Rt
Vt Total Total Vt
Figure 1. The balance sheet in year t.
Ever since Salamon (1982:294) in defining the long-run profitability of the firm it has been
conventional to regard the firm as a series of repetitive capital investments with a fixed
life-span and a fixed cash-flow pattern. Furthermore, it is customary to assume that the
working capital of the firm has the same profitability level as the firm's capital investments.
Hence, we combine the simulated firm's plant assets and its working capital under the same
caption. We define
(7) Pt = Pt-1 + gt - dt.
ACTA WASAENSIA 12
Debt on the ending balance sheet of a year is defined by the beginning debt balance less the
amortization on the old loans plus the new loans
(8) Bt = Bt-1 - at + lt.
The interest payments on a year's outstanding initial debt are calculated using the loan
interest rate
(9) ht = j⋅Bt-1.
The amortization is made in equal installments until the loans' maturity
min(L,t)
(10) at = Σ (1/L)lt-i .
i=1
The capital investment schedule of the simulated firm is defined by (1). The necessary
funding for the capital investments, interest payments, and amortization comes from cash
inflows, and, when not sufficient, from the new loans
gt + ht + at - ft if gt + ht + at - ft > 0
(11) lt =
0, if gt + ht + at - ft ≤ 0.
If the firm generates enough funds internally, no new loans are taken. Instead, the potential
extra funds are paid out as dividends
0, if gt + ht + at - ft > 0
(12) ot =
ft - gt - ht - at, if gt + ht + at - ft ≤ 0.
The retained earnings are defined by
(13) Rt = Rt-1 + pt - ot.
ACTA WASAENSIA 13
The level of common stock is kept constant in the simulation, i.e. no new stock issues are
included in the model
(14) St = St-1.
The book value of the firm at the end of each year is calculated from the liabilities plus the
equity side of the balance sheet as
(15) Vt = Bt + St + Rt.
5. Producing EVA and Key Financial Ratios
The previous section presented the construction of the actual simulation engine. The model
involves three main constituents, the input parameters, the actual model with the model
variables, and the output produced by the model. The financial time-series produced by the
model make up its primary output. Furthermore, the model can be customized to produce
the key financial information. This section presents the calculation of EVA and selected
key financial ratios in the framework of the model.
In general terms EVA is defined in this paper in a manner similar to the RI (residual
income) as (see e.g. Biddle et al., 1997:305-306)
(16) EVA = NOPAT - WACC ⋅ Capital
where NOPAT is the net operating profit after taxes and WACC is the weighted average
cost of capital. The trade-marked Stern Stewart & Co's EVA includes accounting
adjustments both in NOPAT and the capital. The adjustments are too proprietary to be
carried out in this paper. Fortunately, it is not to be expected that this has a bearing on the
nature of the results (see e.g. Biddle et al. 1997 and Chen & Dodd 1997). Furthermore, we
ACTA WASAENSIA 14
do not include taxation in our model. Our NOPAT will be the accounting profit before the
interest on loans. This will not affect the general pattern of the results.
In terms of our simulation model the EVA is the profit before interest payments net of a
charge for the cost of all debt and equity capital employed
(17) EVA t = (pt + ht) - ct Vt-1
where the weighted average cost of capital for the year under observation is
calculated from the cost j of debt and cost e of equity
(18) ct = j⋅Bt-1/ Vt-1 + e⋅(St-1 + Rt-1)/ Vt-1.
An alternative format of (18) that emphasizes the effect of leverage on the average cost of
capital can be written as
(18a) ct = e - (Bt-1/ Vt-1)⋅(e-j).
In the above we have chosen to use the initial balances instead of e.g. annual averages of
the balance sheets.
In the finance literature one of the most involved issues is the assessment of the cost of
capital. In particular, assessing the cost of equity is a difficult question both in practice and
theory. In our simulation two alternative ways of defining the cost of equity will be used. In
the above formulas it is given as an external parameter. However, the cost of equity can
also be defined as the firm's internal rate of return (see Fama and French, 1999). Here we
can utilize an important advantage of our simulation approach. The IRR is accurately
known in the simulation.
It is possible to define a theoretical version of the EVA using the economic profit on the
assets net of a charge for the cost of all debt and equity capital employed.
ACTA WASAENSIA 15
(19) TEVAt = rVt-1 - γtVt-1
where the average weighted cost of capital is defined by the rate of interest and the firm's
profitability
(20) γt = j⋅Bt-1/ Vt-1 + r⋅(St-1 + Rt-1)/Vt-1.
The question naturally arises whether the practical EVA (17) vs. the theoretical EVA (19)
will lead to substantially differing results.
The model calculates also traditional financial ratios for profitability. Return on (the
capital) investments is defined by
(21) ROIt = (pt + ht) / Vt-1.
Return on equity is
(22) ROEt = pt / (St-1 + Rt-1).
The firm's financial standing is reflected in its leverage defined by
(23) LEVt = Bt / Vt.
EVA is a measure that is expressed in absolute, monetary terms. Nevertheless, it will be
interesting to compare the behavior of a relative EVA to the firm's ROE and ROI. The
latter is left for the simulation, but the former relation is easily assessed analytically. Define
the relative EVA as
(24) EVARt = EVAt / (St-1 + Rt-1).
ACTA WASAENSIA 16
Using EVA definition (17), the definition of the weighted average cost of capital (18), and
the formula for the interest payments (9), it is readily seen that the relative EVA is just the
return on equity less the cost of equity
(25) EVARt = ROEt - e.
6. Input Data Description
The controllable variables and their variation ranges in the simulation experiments are
given in Table 1. Appendix 2 gives one example of the simulated time-series constituting
the cash flow statement, income statement, balance sheet, and the resultant EVA values
and select financial ratios.
Table 1. The variation of the parameters in the simulation runs.
Parameter Symbol Values
First capital investment g0, P0 100.00
First level of debt B0 70.00
First level of common stock S0 30.00
First level of retained earnings R0 0.00
Growth rate k 0.04, 0.08, 0.12, 0.16
True internal rate of return r 0.04, 0.06, 0.08, 0.12
Interest rate on loans j 0.00 – r
Cost of equity e 0.00, 0.05, 0.08, 0.12
Maturity of loans L 5
Business cycle amplitude A 0.50
Business cycle length Ψ 6 years
Technical phase adjustment φ π/6
Noise term σ 0.20
Shock timing τ ∞ (no shock)
Shock coefficient Y 0
Life-span of capital investments N 20
Length of observation period n 13 (years 22-34)
The selected combinations of the different input sets will become evident below in
discussing the results for the research questions posed.
ACTA WASAENSIA 17
7. Effect of the Cost Components
To study the effect of the cost components, the behavior of EVA and the select financial
ratios is simulated under different profitability situations. We fix here the growth rate at 8%
and vary the profitability around the fixed growth figure to emulate different profitability
situations. We consider a firm with a weak profitability (4%) situation, a modest
profitability (6%), a reasonable profitability (8%) where profitability equals the growth
rate, and a good profitability (12%).
The cost of loans can be considered an external variable determined by the interest rate on
the markets. In the simulation runs the loan interest rate is varied all the way up from 0%
(to see one end of an extreme case) to the long-run profitability of the firm's capital
investments (the internal rate of return). Interest rates beyond the IRR are not considered,
because a firm would not be viable under such circumstances.
The measurement of the cost of equity is an involved issue both in practice and theory. One
relevant way of looking at the concept, especially in connection with EVA, is regarding the
cost of equity as the owners' required return on the capital they invest in the firm. In the
simulation runs the cost of equity is varied from the extreme case of 0% up to a maximum
of 12%. In particular, in line with Fama & French (1999), the case where the cost of equity
is made equal to the IRR is interesting as a benchmark. The special strength of the
simulation approach, as compared to empirical data from actual business observations, is
that the true IRR will be available without any bias.
The first question before it is conductive to observe EVA's behavior is to see under what
loan costs the firm can stay generally viable. In a rudimentary framework one can observe
what happens to the firm's leverage as a function of the load interest rate and the firm’s
profitability. Figure 2 delineates the mean leverage for the observation period (years 22-34
in the simulation, c.f. Appendix 2). As is to be expected, if the firm’s growth rate
constantly exceeds its profitability, the firm's situation is not tenable in the long run. In
Figure 2, when the profitability of the firm is 4% and it tries to grow at a rate of 8%, not
ACTA WASAENSIA 18
even practically costless loans can keep the firm afloat. On the other hand, when the
profitability (12%) clearly exceeds the firm's growth rate (8%), the leverage curve is very
flat until a sudden, steep upwards slope at the growth level. At normal profitability figures
(6%, 8%) the leverage increases smoothly along the cost of loans.
0
10
20
30
40
50
60
70
80
90
100
0.0 2.0 4.0 6.0 8.0 10.0 12.0
Loan interest rate %
Le
ve
ra
ge
%
r=6%
r=8%
r=12%
r=4%
Figure 2. Leverage as a function of the loan interest rate and profitability; growth k=8%,
cost of equity e=5%.
Next consider the behavior of EVA for the different levels of cost of loans under different
levels of cost of equity, i.e. the shareholders' requirement of return. Figure 3 delineates the
results for the case of balanced growth and profitability.
ACTA WASAENSIA 19
-100.0
0.0
100.0
200.0
300.0
400.0
500.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0
Loan interest rate %
EV
A
$
e=0%
e=5%
e=8%
e=12%
Figure 3. EVA as a function of the loan interest rate and the required rate of return on
equity; growth k=8%, profitability r=8%.
When the required rate of return, i.e. the cost of equity equals the firm's true profitability (e
= r = 8% in the figure) in line with Fama and French, it is evident from all our simulation
results that the cost of loans has very little effect on the EVA of a viable firm.
The theoretically correct cost of equity is not necessarily available to the stakeholders. In
actual practice the cost of equity / required rate of return is determined on an ad hoc basis
or estimated from market based data. This situation is exemplified in Figure 3 by the case
of e = 5%. It is readily seen that on the other hand EVA stays insensitive to the cost of
loans, but on the other hand the absolute level of EVA is significantly affected.
It is also evident from the figure, that if the required rate of return is set unrealistically by
the shareholders (e = 12% or e = 0% in Figure 3), EVA's behavior becomes more drastic.
By definition, a comparison of the practical EVA (17) and theoretical TEVA (19) is
relevant only when the required rate of return is set at the (true, but in practice unknown)
profitability of the firm. Under these circumstances the EVA and TEVA figures are very
close. This result is similar to the results concerning the economist's vs. accountant's
ACTA WASAENSIA 20
valuation of the firm's profits. For a further discussion and references see e.g. Salmi &
Virtanen (1997:21).
The results in this section indicate, somewhat contrary to the intuitive expectations, that (as
long loans can be secured at viable rates), EVA is almost unaffected by the cost of loans.
To summarize, we draw the following conclusion
Under normal circumstances EVA is determined foremost by the firm’s
profitability as long as the required rate of return is set as the finance
theory dictates.
8. Effect of Growth Strategies
The firm may adopt different growth strategies in relation to its profitability - as long as
sufficient funds can be obtained to finance the growth. To examine the consequences of
different growth strategies for a profitability of 8% we produce the cases of slow (k=4%),
normal (k=8%), fast (k=12%) and very fast growth (k=16%).
0
200
400
600
800
1000
1200
1400
1600
22 23 24 25 26 27 28 29 30 31 32 33 34
Year
EV
A
k = 4%
k = 8%
k = 12%
Ending leverage = 22.5%
Ending leverage = 57.8%
Ending leverage = 74.8%
k=16%
Ending leverage = 86.1%
Figure 4. Annual EVA figures for different growth strategies; profitability r=8%, cost of
equity e=5%, loan interest rate j=6%.
ACTA WASAENSIA 21
Figure 4 shows that the more aggressive the growth policy the more sensitive the EVA.
This goes both for the level and the variability of the annual EVA figures.
The mechanism that causes this behavior is rather obvious. At higher growth rates (with
respect to the firm's profitability) more and more financial leverage is needed to keep the
firm and the growth going. The increase in EVA and its variability comes through two
effects. As a physical phenomenon, the growth increases the level of the earnings
component as such. As a financial phenomenon, the increasing financial leverage gears
upwards the returns earned on the shareholder's equity and thus adds economic value to the
shareholders.
It should be noted that the results in Figure 4 are obtained in a Modigliani-Miller type of
setting. In other words, the calculations are performed under unchanging risk, fixed return
requirements and non-increasing loan costs for the different growth levels.
To conclude
The (absolute) EVA figure and its variability are strongly affected by the
firm's growth policy choices.
In business practice EVA is a measure that is applied in absolute, monetary terms.
Nevertheless, it is interesting to compare the behavior of a relative EVA to ROE and ROI.
It was already shown in (25) that there is a one-to-one correspondence between the relative
EVA and the firm's ROE, which are only separated by the firm's cost of equity. This fact
may be a good explanation for the empirical results such as Biddle, Bowen & Wallace
(1997) and Chen & Dodd (1997) not finding evidence of an EVA supremacy over net
income in explaining the firms' stock returns.
Figure 5 delineates the behavior of the relative EVA at the different growth strategies in
comparison with ROI.
ACTA WASAENSIA 22
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
22 23 24 25 26 27 28 29 30 31 32 33 34
Year
EV
A
R
et
ur
n
k=16%
k=12%
k=8%
k=4%
ROI, k=8%
Figure 5. Annual relative EVA figures for different growth strategies; profitability
r=8%, cost of equity e=5%, loan interest rate j=6%.
The behavior of the relative EVA shows both similar and different features as the absolute
EVA. Again, the variability is significant. The more aggressive the growth policy the more
sensitive the EVA. Despite the variability, the mean levels of the relative EVAs stay fairly
constant. The mean levels are determined by the growth strategies.
ROI behaves differently. It is a very good approximation of the profitability of the firm’s
capital investments, i.e. the firm's IRR. There is very little fluctuation in the ROI figure.
ROI is a highly robust measure. This result is in line with the results in Salmi & Virtanen
(1997).
The relative EVA figure level and variability of the relative EVA are
strongly affected by the firm's growth policy choices. The traditional ROI
is a very robust measure of the firm’s underlying profitability.
Furthermore, the results show that on an annual level the EVA figures are affected by
cyclical business fluctuations (and irregular events). On the other hand, the further,
unreported simulation experiments done in the project, show that average nature of the
EVA results are not affected by the cycles.
ACTA WASAENSIA 23
9. Signaling Financial Distress
Does EVA warn of an approaching bankruptcy? The different kinds of bankruptcy
definitions have to be considered: The economic bankruptcy where the value of the firm
becomes negative, and the legal bankruptcy where the firm is foreclosed.
Figure 3 indicates that, as is expected, if the firm is unable to earn profits in excess of the
required return, EVA will go negative. However, the behavior under increasing loan
interest rates is counter-intuitive. The answer would thus seem to be at most a qualified yes
for EVA acting as a financial distress warning, as far as the economic value distress
definition is used. The key issue is whether the owners have set a reasonable required
return. If not, a perfectly sound firm will falsely appear to be in distress.
Consider legal bankruptcy in the light of Figure 4. In practice, firms that develop an
extremely high leverage will in many cases either go bankrupt, or at could be taken over for
a restructuring. At least if risk premiums are not included, strongly leveraged (growth)
firms will have higher and higher EVAs. Hence, the absolute EVA measure could be
dangerously susceptible as a distress warning device.
10. Conclusion
During the 1990's value based management has made a strong entry in the assortment of
management tools in the form of EVA as marketed in particular by Stern Stewart & Co.
Research literature on the subject has roughly taken three different lines: the practical
advocating consultation-line literature, the empirical share-returns predictor performance
literature, and the theoretical accounting measurement discussion approach. The current
paper examined the behavior of EVA under different, characteristic circumstances using
controlled, simulated financial data.
ACTA WASAENSIA 24
The central idea of EVA is subtracting the cost of capital from the firm's profits to measure,
as the term indicates, the economic additional value produced by the firm to its owners
over the weighted cost of the capital employed. This raised the question of the effect of the
debt and equity cost components on the behavior of EVA. It was observed that under
realistic (with respect to the firm's profitability) required returns (cost of equity) the loan
interest rate has little effect on the EVA's behavior until the cost of loans approaches the
firm's profitability. This insensitivity can be considered a somewhat unforeseen result with
respect to the intuitive expectations of EVA's behavior. On the other hand, as is expected,
EVA behaves in a linear fashion with respect to the cost of equity.
Business firms may and do adopt different growth strategies in relation to their profitability
levels, ranging from conservative to aggressive. A interesting current example of the
aggressive growth strategy choices have been the new information technology companies.
It was confirmed in this paper that EVA and its variability are strongly affected by the
firm's growth policy choices. This result is in line with expectations because the
consequent increasing financial leverage gears up the return earned on the shareholders
equity.
The results have also a bearing on the debate of the relative merits of the value-based
measures against the properties of traditional accounting measures. It was observed that
even under regular economic circumstances (the relative) EVA is much more unstable than
the traditional return on investment (ROI) measure. Furthermore, as was shown in the
mathematical derivations, there is one-to-one correspondence between (the relative) EVA
and the traditional return on equity (ROE). These findings subject to doubt the potential
claims on EVA's supremacy over the more traditional accounting measures.
Traditional financial ratios are commonly used also for distress prediction. It was observed
that EVA does not have incremental value in the predicting.
Besides the results arrived at concerning EVA and its relation to the traditional accounting
profitability measures, this paper goes to demonstrate the good applicability of the
ACTA WASAENSIA 25
controlled simulation approach in financial research. The major advantages of the
simulation approach are the ability to emulate different business situations at will and to
facilitate a plausible ceteris paribus scrutiny of the relevant cases.
ACTA WASAENSIA 26
Appendix 1. List of Symbols
Input parameters
g0 = initial level of capital investments
k = growth rate of the capital investments
A = amplitude of the cycle
Ψ = length of the cycle
φ = technical phase adjustment for the cycle
σ = standard deviation of the random fluctuation in the capital expenditures
Y = capital investment shock coefficient
τ = the year of the capital investment shock (τ = ∞) for no shock in the
simulation)
T = length of the simulation period
bi = relative contribution from capital investment i years back
N = life-span of a capital investment project (the same for all capital
investments)
r = internal rate of return of the simulated firm, for the given bi and N
q = shape parameter for negative binomial distribution
s = scaling factor for negative binomial distribution
j = interest rate on loans
L = maturity of loans
e = cost of equity
Model variables
gt = capital investments in year t
z = random variable following the (0,1)-normal distribution
δ tτ = Kronecker's delta, δ tτ = 1 when t = τ, and 0 otherwise
ft = cash inflow in year t
fti = absolute contribution (cash-inflow) in year t from capital investment i
years back
pt = accounting profit in year t
ht = interest on loans in year t
dt = depreciation in year t
Pt = plant assets plus working capital at the end of year t
Bt = debt at the end of year t
St = common stock at the end of year t
Rt = retained earnings at the end of year t
Vt = book value of the firm at the end of year t
at = amortization of loans in year t
lt = new loans taken in year t
ot = dividends paid out in year t
ct = weighted average cost of capital for year t
γt = "theoretical" weighted average cost of capital for year t
ACTA WASAENSIA 27
Output variables
EVAt = economic value added in year t
TEVAt = economic value added in year t based on the internal rate of return
EVARt= relative economic value added in year t
ROIt = return on investments
ROEt = return on equity
LEVt = leverage
Appendix 2. Example Simulated Time Series.
Growth 8%, IRR 8%, interest rate on debt 6%, cost of equity 5%, negative binomial
contribution distribution, straight-line depreciation, amplitude 50% for business cycles,
noise 20%, no shock.
Table A1. Cash flow statement
Year Funds from
operations
New
loans
Capital
expenditure
Amortization Interest
on loans
ft lt gt at ht
0
1
:
21
0.00
8.39
:
503.90
70.00
161.17
:
701.10
100.00
151.36
:
271.45
0.00
14.00
:
775.15
0.00
4.20
:
158.39
22
23
24
25
26
27
28
29
30
31
32
33
34
534.27
559.50
593.90
640.33
723.53
819.94
905.95
951.64
1014.31
1107.32
1270.40
1381.92
1467.61
755.58
902.37
1047.66
1458.55
1563.03
1485.06
1078.88
1416.62
1789.43
2596.99
1877.67
1715.30
1529.64
318.86
451.70
604.02
1048.43
1116.67
927.32
440.87
801.76
1158.04
1969.10
1138.25
996.62
771.56
817.03
859.90
884.72
887.85
973.05
1145.44
1291.33
1326.63
1400.43
1466.60
1673.40
1751.92
1879.20
153.95
150.26
152.81
162.59
196.83
232.23
252.61
239.86
245.26
268.60
336.42
348.68
346.48
ACTA WASAENSIA 28
Table A2. Income statement
Year Cash
inflows
Straight-line
depreciation
Interest
on loans
Operating
income
ft dt ht pt
0
1
:
21
0.00
8.39
:
503.89
0.00
5.00
:
252.49
0.00
4.20
:
158.39
0.00
-0.80
:
93.00
22
23
24
25
26
27
28
29
30
31
32
33
34
534.26
559.50
593.90
640.32
723.52
819.94
905.94
951.63
1014.31
1107.32
1270.40
1381.91
1467.61
258.49
265.83
284.55
312.10
359.07
405.26
439.34
451.44
482.78
536.34
626.88
673.17
704.84
153.95
150.26
152.81
162.59
196.83
232.23
252.61
239.86
245.26
268.60
336.42
348.68
346.48
121.81
143.40
156.53
165.62
167.61
182.43
213.98
260.33
286.26
302.37
307.08
360.06
416.27
Table A3. Balance sheet
Year WC+Plant
assets
Debt Common
stock
Retained
earnings
Total
assets
Pt Bt St Rt Vt
0
1
:
21
100.00
246.36
:
3439.20
70.00
217.17
:
2565.90
30.00
30.00
:
30.00
0.00
-0.80
:
843.29
100.00
246.36
:
3439.20
22
23
24
25
26
27
28
29
30
31
32
33
34
3499.56
3685.44
4004.92
4741.24
5498.84
6020.90
6022.43
6372.76
7048.02
8480.78
8992.15
9315.60
9382.32
2504.45
2546.92
2709.86
3280.56
3870.54
4210.16
3997.70
4087.69
4476.69
5607.08
5811.35
5774.74
5425.18
30.00
30.00
30.00
30.00
30.00
30.00
30.00
30.00
30.00
30.00
30.00
30.00
30.00
965.11
1108.51
1265.05
1430.68
1598.30
1780.73
1994.72
2255.06
2541.32
2843.70
3150.79
3510.85
3927.13
3499.56
3685.44
4004.92
4741.24
5498.84
6020.90
6022.43
6372.76
7048.02
8480.78
8992.15
9315.60
9382.32
ACTA WASAENSIA 29
Table A4. EVA and financial ratios
Year EVAt
ROIt ROEt LEVt WACC
ct
TEVAt
WACC
γt
0
1
:
21
0.00
-2.30
:
53.99
0.0000
0.0339
:
0.0735
0.0000
-0.0270
:
0.1192
0.7000
0.8815
:
0.7461
0.0000
0.0570
:
0.0577
0.00
1.40
:
52.79
0.0000
0.0660
:
0.0646
22
23
24
25
26
27
28
29
30
31
32
33
34
78.15
93.64
99.61
100.87
94.58
101.02
123.45
159.09
172.01
173.81
163.40
201.02
239.23
0.0802
0.0839
0.0839
0.0820
0.0769
0.0754
0.0775
0.0831
0.0834
0.0810
0.0759
0.0788
0.0819
0.1395
0.1441
0.1375
0.1279
0.1148
0.1120
0.1182
0.1286
0.1253
0.1176
0.1069
0.1132
0.1176
0.7156
0.6911
0.6766
0.6919
0.7039
0.6993
0.6638
0.6414
0.6352
0.6612
0.6463
0.6199
0.5782
0.0575
0.0572
0.0569
0.0568
0.0569
0.0570
0.0570
0.0566
0.0564
0.0564
0.0566
0.0565
0.0562
51.31
50.08
50.93
54.19
65.61
77.41
84.20
79.95
81.75
89.53
112.14
116.22
115.49
0.0651
0.0657
0.0662
0.0665
0.0662
0.0659
0.0660
0.0667
0.0672
0.0673
0.0668
0.0671
0.0676
Mean 138.45 0.0803 0.1233 0.6634 0.0568 79.14 0.0665
ACTA WASAENSIA 30
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