CAPITAL BUDGETING BY UTILITIES EUGENE F. BRIGHAM and RICHARD H PETTWAY Dr. Brigham, Professor of Finance and Director of the Public Utilitv Research Center. University of Florida, rs author and coauthor of a number of hooks and many articles in finance. Dr. PeUway. Associate Professor of Finance. University of Florida, has published articles in the Journal of Financial and Quanlitaiivc Analysis, the Financial Analysts Journal, and oiher academic fournals. he theory of capital budgeting has been studied extensively in recent years, and there is a growing body of literature describing the capital budgeting techniques employed by industrial firms. However, in spite of the importance of public utilities, virtually no studies relating to these firms' capital budgeting practices have appeared in the financial journals. This article is aimed at this gap. A number of capital investment selection criteria have been identified in the literalurc of finance. The four most frequently mentioned are payback, average rate of return, ARR. internal rate of return. IRR, and net present value, NPV. The NPV method is generally regarded as being the "best" in some the- oretical senses, while the IRR method is a somewhat distant second. Boih payback and ARR, which may be defined in serveral ways, are generally regarded as being distinctly inferior to the two techniques em- ploying discounted cash flow. Although theory has been extended very elegantly in recent years, the basic techniques were specified reasonably well and widely publicized by the latter 195O's. Once basic theories were accepted academi- cally, various researchers questioned whether or nol business practiced what the academic community preached. Istvan [4, 5], Pfiomn [7], and Soldofsky [8] studied this question in the early 196O's and re- ported that relatively few firms employed the recom- mended DCF techniques. The studies by Christy [2], the National Association of Accountants [6], and Terborgh [9], all done in the latter half of the l960"s, indicated an increasing use of DCF methods, but they also showed that the payback and ARR were far more widely used. The most recent studies of national firms, the ones by Klammcr [3] and by Abdelsamad [I], showed a continuation of the trend toward DCF; however. 43% of the firms in Klammer's study were still using a non-DCF method in 1970. Two explanations for the non-use, or at least limited use, of DCF were offered. The first hypoth- esis is that there is simply a learning-and-action lag; the second is that the cost of using a DCF technique may, in some inslances. exceed its benefits. Although neither of these hypotheses has been "proved," our own studies suggest that there is some validity to both. Accordingly, we think thai the use of DCF will increase, but it is most unlikely that any future sttidy will ever find that nil investment decisions are made using a DCF cutoff criterion. Autumn 1973 11 Capital Budgeting in the Utility Sector in our ...

1. CAPITAL BUDGETING BY UTILITIES
EUGENE F. BRIGHAM and
RICHARD H PETTWAY
Dr. Brigham, Professor of Finance and Director of the Public
Utilitv
Research Center. University of Florida, rs author and coauthor
of a
number of hooks and many articles in finance. Dr. PeUway.
Associate Professor of Finance. University of Florida, has
published
articles in the Journal of Financial and Quanlitaiivc Analysis,
the
Financial Analysts Journal, and oiher academic fournals.
he theory of capital budgeting has been studied
extensively in recent years, and there is a growing
body of literature describing the capital budgeting
techniques employed by industrial firms. However, in
spite of the importance of public utilities, virtually
no studies relating to these firms' capital budgeting
practices have appeared in the financial journals. This
article is aimed at this gap.
A number of capital investment selection criteria
have been identified in the literalurc of finance. The
four most frequently mentioned are payback, average
rate of return, ARR. internal rate of return. IRR,
and net present value, NPV. The NPV method is
generally regarded as being the "best" in some the-
oretical senses, while the IRR method is a somewhat

2. distant second. Boih payback and ARR, which may
be defined in serveral ways, are generally regarded as
being distinctly inferior to the two techniques em-
ploying discounted cash flow.
Although theory has been extended very elegantly
in recent years, the basic techniques were specified
reasonably well and widely publicized by the latter
195O's. Once basic theories were accepted academi-
cally, various researchers questioned whether or nol
business practiced what the academic community
preached. Istvan [4, 5], Pfiomn [7], and Soldofsky
[8] studied this question in the early 196O's and re-
ported that relatively few firms employed the recom-
mended DCF techniques. The studies by Christy [2],
the National Association of Accountants [6], and
Terborgh [9], all done in the latter half of the
l960"s, indicated an increasing use of DCF methods,
but they also showed that the payback and ARR
were far more widely used. The most recent studies
of national firms, the ones by Klammcr [3] and by
Abdelsamad [I], showed a continuation of the trend
toward DCF; however. 43% of the firms in
Klammer's study were still using a non-DCF method
in 1970.
Two explanations for the non-use, or at least
limited use, of DCF were offered. The first hypoth-
esis is that there is simply a learning-and-action lag;
the second is that the cost of using a DCF technique
may, in some inslances. exceed its benefits. Although
neither of these hypotheses has been "proved," our
own studies suggest that there is some validity to
both. Accordingly, we think thai the use of DCF
will increase, but it is most unlikely that any future

3. sttidy will ever find that nil investment decisions are
made using a DCF cutoff criterion.
Autumn 1973 11
Capital Budgeting in the
Utility Sector
in our work with public utilities it became appa-
rent almost immediately that their approach to in-
vesting decisions is unlike Ihat of other companies.
Regulation itself has led to a modification of tradi-
tional approaches to capital budgeting. Consider
Exhibit 1. which presents what might be called the
"traditional view" of the capital budgeting process.
Here, the firm takes on projects so long as their
rate of return exceeds the cost of capital, and the
capital budget for the period in question is I*. The
area under the rate of return schedule, but above
the cost of capital schedule, represents what might
be called a "producer's surplus." The area labeled
"producer's deficit" is rejected.
According to traditional regulatory theory, this
conceptual model is not generally applicable to utility
companies. In the regulatory process, a target, or
allowed rate of return, is specified. This return is,
either implicitly or explicitly, recognized as being a
point (perhaps the midpoint) within a range of rates
of return frequently called the "zone of reasonable-
ness." If "good" capital investments cause the actual
rate of return to exceed the upper end of this range,
then a rate reduction is ordered to drive rates back
down to target. Thus, according lo uadiiional re-

4. gulatory theory, the existence of the regulatory pro-
cess will eliminate the "producer's surplus" shown in
Exhibit 1. If the surplus is eliminated by regulatory
action, this means that Ihe least profitable of the se-
lected projects will have a zero NPV, and its IRR
will equal the cost of capital. Hence, the rule of
choosing projects so as lo maximize NPV does not
appear to be operational—at least under the tradi-
tional view of regulatory theory.
Public Utility Investment Decisions in
Today's Environment
The preceding theoretical discussion must be modi-
fied to conform to the reality of the present situation
faced by public utilities.
Rate of Return Patterns Under Inflation. Exhibit
2{A) shows the rate of return pattern facing a typical
utility company when (I) inflation is driving costs up
constantly. (2) prices, which are set by regulatory
action, are increased at discrete intervals, and (3) no
regulatory lag is present. As operating costs rise,
profits and. consequently, the realized return on in-
vestment decline. When the lower control limit is
reached, rates are raised, causing the realized rate of
return to rise to ihe target level. However, continued
inflation causes the cycle to be repeated, and rates of
return are again eroded. The net result is that the
rate of return will, on average, fall below the target
level.
Exhibit 2(B) shows the effects of regulatory lags.
At point A the actual rale of return penetrates the
lower control limit, prompting the company to ask

5. Exhibit 1. Conceptual Model of the Capital Budgeting Process
for an Unregulated Firm
20
IRR, or Marginal Return
on Investment Schedule
Percent
"Producer's
/ Surplus"
/ / J , /
Marginal Cost of
Capital Schedule
/"Producer s
Deficit"
I* Investment
During Period ($)
12 Financial Management
for a rate hearing, which occurs al poinl B. At point
C an order is issued permitting the company to raise
rates, and the rate increase takes effect at point D.
As we have shown it, the actual rate of return
does not return to the target level. The cost figures
generally used in the point B rate cases are those of

6. the most recent past year. If inflation continues, by
the time the new rates take effect, the cost figures
are otitdatcd. that is. they arc too low. Hence, the
calculated utility rates are too low lo return the rate
of return on investment to the target level.
It would, of course, be possible for regulatory au-
thorities to anticipate price increases. In utility par-
lance this is called using a forward test year. Alter-
natively, the regulatory lag could be shortened by
setting the control limits closer to the target rate of
return. Such procedures are beginning to be employed
by regulatory agencies; the automatic fuel adjustment
clause, which permits certain electric utilities to raise
prices automatically when fuel costs rise, is an exam-
ple. However, the past test year is used more fre-
quently than the forward test year, and this has a
negative impact on utility profits under inflationary
conditions.
A Rising Cost of Capital. Controversy exists ocr
measurement of the cost of capital, but because of
an increase in interest rates, no one seriously argties
that it has not risen in recent years. However, be-
cause of regulatory lags, the target rate of return has
generally been set below the actual cost of capital.
Exhibit y illustrates this. From TQ to T ] . the
cost of capital is both stable and equal to the al-
lowed rate of return. At T| the cost of capital be-
gins to rise, and during the interval from T] to TT
the rate of return shortfall widens. At T-?, a rate
case is held, and the allowed rate of return is ad-
justed upward. However, the continuing increase in
the cost of capital causes the cycle to be repeated,
and over the entire period the actual rate of return

7. averages less than the cost of capital. Note also that
the debt cost used in the target rate of return is the
"embedded" cost, or the average cost of all out-
standing debt. If the cost of new debt is above a
company's embedded debt cost-as it has been in re-
cent years for virtually all utilities-then the embedded
eost will rise over time.
Mandatory and Discretionary
Investment Decisions
It is useful to describe now another feature of uti-
lity operations. That is. they are legally required to
make the investments needed to provide service upon
demand. Thus, utility companies' capital investments
may be divided into mandatory and discretionary
investments. This is illustrated in Exhibit 4, where
we show the marginal cost of capital and rate of re-
turn schedules for both investment components. As
we have drawn it, the mandatory category is sub-
stantially larger in dollar terms than the discretionary
category; this seems to be In accord with the actual
situation.
Exhibit 2. Typical Rate of Return Pattern Under Inflationary
Conditions
(a) No Regulatory Lag (b) With Regulatory Lag
Rate of
Return
, y.£per Control Limit
Target (or Allowed)
Rate of Return

8. .Actual Rate
of Return
Lower Control Limit
B
Time
Autumn 1973 13
Exhibit 3. Illustration of Rising Cost of Capital Combined with
Lagged Changes in the Allowed
Rate of Return
Actual Cost
of Capital
Percent
Rate of Return x:
Target (or Allowed)
Rate of Return
Time
Exhibit 4. Capital Budgeting with Mandatory and Discretionary
Investments
Percent
Rate of Return
on Discretionary

9. Investments
Rates of Return
on Mandatory
Cost of Capital
Investment
During Period ($)
Mandatory
Investments
Discretionary
Investments
14 Financial Management
An example will illustrate what is involved. As-
sume that in certain geographic areas a telephone
company may have excess switching capacity, per-
mitting it to earn a relatively high rate of return on
the small investment needed to serve new customers.
Profitable investments of this type give rise to the
area designated as A. On the other hand, in some
other district where existing capacity is fully utilized,
to install a new telephone might require an invest-
ment of $2,000, as opposed to an average plant cost
of $1,000 for each telephone presently in service. The
pricing system used in the regulatory process is, in
general, based on average costs, not marginal costs.
In the absence of an immediate price increase, growth
in the second area necessarily means that the average
rate of return on investment will decline. Thus, in-

10. vestment here will correspond to area B in Exhibit
4.
Companies do have a certain amount of discretion
in supplying new types of service or in making cost-
reducing replacement decisions. For example, electric
utilities are sometimes able to negotiate special rates
for large industrial customers who seek to purchase
interruptabie power, and it is possible for these uti-
lities to earn a rate in excess of cost of capital. Sim-
ilarly, companies may install new and lower-cost gen-
erating equipment to replace obsolete equipment, and
the returns on such investments might also exceed
cost of capital. Discretionary investments such as these
give rise to the "producer's surplus" shown as area
C in Exhibit 4.
If area B exceeds the sum of areas A and C, and
if regulatory lags are long, then the existence of
mandatory investment will cause an erosion of rate
of return.
When inflated operating costs, a rising cost of
capital, mandatory investments, and regulatory lags
are combined, the net result is a substantial diver-
gence between the cost of capital and the actual rate
of return on total investment. Exhibit 5 illustrates
this situation, and the questionnaire results described
later suggest strongly that this is indeed the current
situation for utilities. Consequently, incremental in-
vestment with high IRR's or NPV's would indeed
benefit the companies, and their high incremental
profits would not be reduced by regulatory actions.
Thus, it would seem that the rationale against utili-
ties' use of the DCF methods is less valid than
under the static conditions assumed in traditional

11. theory.
The Public Utilities' Investment
Acceptance Criterion
When choosing among competing projects, the
utility industry selects projects whose future costs,
when discounted at the cost of capital, are lowest.
Future costs, or revenue requirements as they are
frequently called, include the following items: (1)
labor, fuel, repair parts, and other operating costs;
(2) depreciation; (3) property ta.xes; (4) income taxes;
and (5) a return on the capital invested in the pro-
Exhibit 5, Combined Effect of Rising Costs, a Rising Cost of
Capital, and Regulatory Lag
Cost of Cap i t a l
Percen t
Actual Rate of Return
Time
Autumn 1973 15
ject. The sum of these cost items, all discounted at
the current (marginal) cost of new capital, is the
present value of revenue requirements.
Utility theory assumes that customers' cash pay-
ments will actually equal revenue requirements; hence,
the annual revenue requirement is really the expected

12. annual cash flow. Also, note that if revenues arc
exactly equal to revenuerequirements,asutility theory
assumes they will be, the NPV of any project, or at
least the NPV of the total investment required to
provide a class of service, will be zero.
The PV of annual cost criterion is applied in two
separate but related ways. First, for mandatory in-
vestments sales revenues are simply disregarded on the
grounds that they will be the same regardless of
which mutually exclusive project is chosen. In other
words, an electric company may project a requirement
to generate an additional 10 million kilowatts to
meet service demands, then set about deciding how
to provide this added capacity. The theoretically best
method—given the assumed level of demand—is the
one having the lowest present value of future revenue
requirements.
The other way in which the PV of cost criterion
is used, and this holds especially when a new type
of service not presently offered is being considered,
involves (I) calculating the minimum revenue require-
ments associated with the new service, then (2) con-
ducting some type of demand/regulatory analysis to
see if the project will in fact produce revenues equal
to its estimated revenue requirements. To illustrate,
suppose a telephone company is considering providing
data transmission service to a group of business
firms. Several switching systems might be used, so
they are analyzed to determine the one with the low-
est present value of revenue requirements. The com-
pany would then attempt to determine whether or not
actual revenues, given the proposed price structure,
would be sufficient to meet the projected revenue re-
quirements. If projected revenues are sufficient, then

13. the project would be undertaken. If they are not,
then the project might be deferred, abandoned, or
the company might discuss with the regulatory com-
mission and the prospective users the possibility of
setting higher rates for the service. This type of anal-
ysis is really quite similar to the orthodox NPV
method. Note, however, that it is used only for dis-
cretionary (cost saving or new product) investments.
However, mandatory investments are far more impor-
tant for most utility companies.
We should note two objections utility executives
have raised against the NPV method. First, they
point out that no explicit revenue projections are re-
quired to use the minimum PV of cost method, but
revenues are required to calculate the NPV. We sug-
gest that revenue projections are no more difficult
for most utilities than they are for most industrial
companies, so this objection to NPV seems of ques-
tionable validity. Second, they pointed out that utility
revenues are generated by a complex system, yet
most investment decisions relate to only one part of
the system. We would agree that the PV of annual
cost method is quite appropriate whendecidingwhich
of two replacement transformers is best and it is
known for certain that replacement must occur. How-
ever, it seems preferable to us to explicitly consider
revenues when analyzing major system additions be-
fore the fact, rather than to assume the necessary
rate increases.
The Questionnaire Results
At the outset of the project, the plan was to rep-
licate the type of survey thai others had done, ex-

14. cept that regulated utilities would be sampled rather
than unregulated industrial companies. For the reasons
cited above, however, we developed a new question-
naire, designed to provide answers to the following
set of questions with respect to utilities:
1. What selection techniques are used when choos-
ing among alternative investments?
2. How do they account for risk differences among
projects?
3. Do they conduct post-audits?
4. Do they experience periods of capital rationing,
and if so, how is this problem handled?
5. What is their most difficult problem encountered
in the capital budgeting process?
6. What is the average embedded (historical)
cost of capital, and how does it compare to the cur-
rent (marginal) cost of capital?
7. What capital costs, embedded or current, are
used as the hurdle or discount rate?
8. What is the allowed, or target, rate of return,
and how does this rate compare to the actual rea-
lized rate of return for the current year?
9. Is dividend policy influenced by either capital
requirements (investment opportunities) or by condi-
tions in the capital markets?
The Sample Companies

15. During questionnaire development, it became ap-
parent that dissimilarities made it impossible to survey
electric, gas. telephone and water utilities with the
same questions. We concentrated on the 116 electric
utilities listed on the Compustat public utility tapes,
which account for 99.5% of privately-owned electric
16 Financial Management
company assets. Questionnaires were sent to the chief
financial officer of each company. Forty-six percent
of the sample completed and returned our question-
naire. We compared the responding and nonrespond-
ing firms with respect to size and location, and we
found no significant differences. The questionnaires
were completed in the fall of 1972.
Project Selection Criteria
We asked the following question: "What invest-
ment selection technique or techniquesdoes your com-
pany use when choosing among alternative projects?
If more than one standard is used, please indicate
the approximate percentage of the total dollar volume
of investment that is evaluated by each method."
The responses are given in E.xhibit 6.
Several comments should be made about the results
shown. First, most individualcompaniesactuallyindi-
cated thai they use only methods I. 2, and 5. Nine-
ty-four percent, or 50 out of 53 of the companies,
use the DCF method (minimum PV of reventie re-
quirements) to analyze at least some of their capital

16. Exhibit 6. Project Selection Methods Employed
by Eleetric Utilities, 1972
Perccnl of loial
dollar volume of
capital expcndittiics
evaluated by mcUiod
in a typical year*
1. "Urgency": Capital expendi-
tures required lo restore service
after a system breakdown
2. No formal analysis is made; in-
stead, Ihe judgment of the de-
cision maker is relied upon
3. Pick project with lowest lolal
"first costs" (i.e., the lowest
iniiial costs)
4. Pick project with the lowest
present value (PV) of initial
cosi
5. Pick project with the lowest
PV of annual costs
4.1%
17.8
7.4

17. 1.7
69.0
100.0%
•The pcrcel1tage^ given here are unweighted averages of
the individual questionnaire responses.
•"Companies that use the equated or level annual charge
method are included in this group. Generally, revenue
requirements equals ihe expected first cost of the project
multiplied by an annual cosl percentage which consisls of
expected eost of money, property and income taxeb, de-
preciation, and maintenance costs.
projects. This contrasts with Klammcr finding that
only 57% of the Fortune 500 industrial companies
used a DCF mehlod.
As indicated earlier, discretionary invcsttiients are
generally accepted only if the utility's manager thinks
revenue requirements will be realized. If expected reve-
nues equal reventie requirements, then e.pected NPV
wili equal zero, while if expected revenues e.xceed
revenue requirements, NPV will be positive. Thus, to
the extent that discretionary investments are handled
in this manner, utilities do, in effect, use the NPV
method.
Most respondents indicated that at least some pro-
jects are accepted on the basis of urgency, and our
discussions with utility e.xecutives lead us to conclude
that the urgency criterion is eminently reasonable.
Similarly, almost all the companies indicated that some
projects are accepted without formal analysis, relying

18. instead upon judgment. A typical example is the
worn out transformer, which the engineer decides to
replace with whatever new transformer he believes to
be the best. As with the urgency criterion, our dis-
cussions with utility e.xeeutives convinced us that the
nonuse of formal capital budgeting procedures for
this set of projects does not necessarily imply ineffi-
cient or unsophisticated management. Rather, it sug-
gests a conscious comparison of the costs of follow-
ing formal procedures versus the benefits gained by
using informal procedures.
Adjustments for Risk
If all projects under consideration are not equally
risky, then this fact should be taken into account.
The two procedures most commonly recommended in
the finance literature are (I) the use of risk-adjusted
discount rates and (2) the use of certainty equiva-
lents. Exhibit 7 shows what electric utility companies
actually do. First, no respondent indicated that his
company used certainty equivalents, and only about
15% of the companies use the risk-adjusted discount
rate technique.
This is not to say, however, that most electric uti-
lity companies indicated no formal recognition of risk
differentials; 58% of the companies did acknowledge
risk in some manner. The two most commonly used
procedures are (1) sensitivity analysis of cost and
revenues under alternative conditionsabout investment
alternatives; and {2)an arbitrary downward adjustment
in the expected life of an abnormally risky project.
It is interesting that utilities do formally analyze
risk to a greater extent than the Fortune 500 indus-

19. trial companies. Klammer found that only 40% of
the industrial firms surveyed explicitly analyze risk
versus 58% of the utility companies.
Autumn 1973
17
Exhibit 7. Procedures Used to Account for
Differing Degrees of Project Risk
Primary
method
used**
Secondary
method used (if
an indicated)*'
1. Raise the cost of
capital used in cal-
culating revenue
requirements for
riskier projects
2. Adjust downward
the e.xpccled life if
the project is more
risky than normal
3. No formal differ-
entiation is recog-
nized

20. 4. Use ''sensitivity
analysis" (i.e..
formally consider
what will happen
lo eosts and reve-
nues under alterna-
tive conditions,
and use this infor-
mation in a judg-
mental manrtcT to
reach a decision as
to the best alierna-
tive)
4.4%
1.0
42.3
10.4%
8.4
42.3
100.0%
*Only 32.5% of the responding ciimpanics indicated thnl
they used two methods to account for riiik differentials.
•*The percentages given here are unweighted averages of
the indiiduai questionnaire responses.
Post-Audits of Investment Projects

21. Post-audits supposedly lead to better capital bud-
geting by (I) uncovering serious weaknesses or sys-
tematic biases and (2) stimulating decision makers to
be more careful.
Exhibit 8 shows tlic percentage of the electric
companies that conduct post-audits. The table is di-
vided into two sections, one for residential and com-
mercial investments, the other for industrial invest-
ments. The primary reason for using this breakdown
is that industrial service is frequently discretionary,
and some utility executives feel that p9st-audit$ are
more applicable for investments of this type. The
table also recognizes that post-audits can be made
separately for construction costs, operating costs, and
operating revenues.
Exhibit 8. Post-Audits of Investment Projects
Percentage of respondents
thai conduct post-audit*.
Post-audit
of initial
outlay costs
Post-audit of
operating costs
Posl-audii of
operating revenues
Rcsiitcniial and
conimi-rciai
rnM-'stmtrnts

22. Industrial
service
investments
60.9% 63.0%
30.2% 38.6%
25.6% 35.7%
Only a little over 60% of the titilities conduct
post-audits. This compares with Klammcr's finding
that 88% of the largest industrial firms employed
post-audit^i of construction costs. One explanation
given by a utility company executive for his own
company's lack of interest in construction cost post-
audits for all projects relates to the very long con-
struction periods sometimes involved. Today it takes
an average of 14 years to plan and build a nuclear
plant. With such a long time frame, the initial cost
estimates are simply not relevant. Early estimates are
avaiiabie and could be looked up and analyzed, but
why bother? This executive also suggested that a
considerable amount of utility investment is done under
fixed cost contracts, and post-audits are obviously not
useful in these instances.
Exhibit ii also shows that post-audits of operating
costs and operating revenues are not conducted gen-
erally. A noticeably larger percentage, however, of
industrial as opposed to commercial residential pro-
jects are subjected to post-audits. The principal reason
for the companies" infrequent use of operating cost-
revenue post-audits is. apparently, that since most of
their investments are mandatory, they simply must be

23. made regardless of either the operating cost of the
project or its revenues.
Capital Rationing
Exhibit 9 indicates that 40% of the companies
surveyed have been subject to capital rationing. Of
the firms, 89% indicated that in response to funds
shortage they would apply for a rate increase. If a
rate increase were granted, then their higher earning
power would presumably enable them to obtain the
capital necessary for making alt "identified and justi-
fiable" investments.
If rate increases were not granted. 75% of the
companies indicated that they would eliminate or
postpone those projects that would be least likely to
18 Financial Management
Exhibit 9. Capital Rationing in the Electric Utility industry
I. Percentage of respondents that have
experienced capital raiioning
during the past 5 years*
II. Procedures for dealing with Capital
raiioning
1. Apply for a rate increase
2. Eliminate or postpone thoie projects that
are least likely lo meet revenue requirements

24. 3. Lca!>e fixed assets
4. Make less capital intc^^ive incstments
(i.e.. accept Ihe al(erna[ic with ihc
lower first cost or initial outlay)
Have had
Capital
Raiioning
40%
Percentage of rcspondcnis
thai indicated their firm
would l.-ike the action noted
89%
75%
55%
' . periixl of capital rationing is defined as a period when the
firm could not obtain sufficient funds at or below its allowed
rate of return to make all its identified and justifiable
investments.
meet revenue requirements, and over half the com-
panies indicated that they would lease rather than
purchase fixed assets. The willingness to lease was
somewhat surprising, but apparently utilitycompanies
that are strapped for capital are increasingly resorting
to leasing arrangements. The fourth alternative men-
tioned was to make less capital intensive investments.

25. Perceived Problem Areas in Capital
Budgeting
Far and away their most serious problem in the
eyes of utility executives is obtaining permission from
environmental protection agencies and. or the Atomic
Energy Commission to build new generating plants.
No other factor was considered to be a serious pro-
blem by even half as many respondents.
The remainder of Exhibit 10 was somewhat sur-
prising. We expected the companies to have trouble
estimating annual costs and revenues and cost of
capital, but obviously they do not consider these esti-
mates 10 be serious problems. In retrospect, it is
easy to see why this is so. The cost of capita! for
utility companies is, rightly or wrongly, determined
in rate cases. Also, capital budgeting techniques
used tend to suppress revenue estimates; reenue
shortfalls are supposed to be made up by rate
increases. Further, the companies frequently assume
that, once a project is in operation, the regulatory
process will provide sufficient revenues to cover oper-
ating costs.
It is also interesting to examine the second col-
umn in the table headed **A Fairly Serious Pro-
blem." Many items not consideied to be "very
serious" are considered, nevertheless, to be "fairly
serious". For example, estimating the annual oper-
ating costs of a project, response 9 in E.hibit 10, is
not generally considered to be a very serious pro-
blem, but it is considered to be a fairlv serious one.
Cost of Capital, Allowed Rates of

26. Return, and Realized Rates of Return
The average after-tax current cost of capital. 9.3%,
indicated in Exhibit 11, is well above the indicated
embedded cost of capital. 8.0%. This differential is,
presumably, caused by the fact that the embedded
cost of debt for most companies is well below the
current rate of interest on long-term bonds. It is also
interesting to note that the average allowed rate of
return as prescribed by regulatory authorities, 7.6%,
is below the indicated 8.0% aerage embedded cost
of capital. There are a large number of rate cases in
process across the country today, and allowed rates
of return will presumably be increased somewhat.
The last item shown in Exhibit II. the current
rate of return on inestment. is substantially lower
than either the allowed rate of return or the cost of
capital. Thus, the situations shown in both Exhibits
2 and 5 seem to exist today.
Autumn 1973 19
Exhibit 10. Percei>ed Problem Areas in Capital Budgeting
Obtaining rcgulalory approval for new plants from
environmental
protcelion agencies and/or AEC
Specification of first cost or capital requirements of a new
investment
Estimation of the cosl and availability of llie input
factors (i.e., fuel, labor)

27. Estimation of ihc project's economic life giving regard
lo bolh demand factors and obsolescence of ihe
invcsiment due to new technology
Estimation of when the plant will be placed in service
Making incstmcnis that should be profitable, given demand
and technology factors, but thai are nol allowed lo earn
their expected return by regulatory authorities
Making sure all reasonable alternatives have been considered
Specification of the effects of inflation on annual costs
in general
Estimation of annual operating cost of the project
Predicting the needs of the franchise area in advance
Esiimaiion of annual revenue attributed to the project
Specification of a "cost of money" or cost of capital
Estimation of project life from a wear/iear standpoint
Perccni of Respondents Stating that
the Indicated F-'actor is:
A Very A Fairly Not at
Scriouii Serious all
Problem Problem Serious
75

28. 35
34
17
43
47
22
32
30
23
23
21
21
19
19
19
2
43
45

29. 43
43
55
51
50
33
25
44
26
25
34
34
24
28
31
48
58
54

30. The Cost of Capital Used as the
"Hurdle Rate"
We asked the companies to indicate which cost of
capital, the embedded cost or the current (or mar-
ginal) cost, was used in llie capital budgeting pro-
cess. The oorwhclming majority of tlie companies
used cither the current cost of capital or a figure
very close to the current cost; no company used the
embedded cost of capital when analyzing new invest-
ments.
Dividend Policy
At least some of ihe writinjjs in finance suggest
that companies should alter their dividend payout
policies as changes occur in either investment oppor-
tunities or in capital market conditions. Todetermine
whether or nol utility companies do adjust their di-
vidend policies, we asked the following: It has been
suggested that utility companies'dividend policies may
be affected hy capital investment opportunities or
requirements and by capital market conditions (i.e.,
ihe slate of stock and bond markets). For example,
in a period of high investment demand and light
money, companies might not increase dividends if
earnings increased, thus reducing the payout ratio,
or they might even cut dividends in order to con-
serve capital. Recognizing that it might take several
years to effect such u change, do you think that
your own company's dividend policy would be
affected by:
Percent responding:

31. Yes No
a. Changes in capital expenditure
opportunities or requirements?
b. Capital market conditions?
34%
40'̂ ,, 60%
According to the respondents, only about one-third
of ihc utility companies' dividend policies are ad-
justed in response lo changing investment oppor-
tunities or capital market conditions.
20 Financial Management
Exhibit U . Cost of Capital, Allowed Rates
of Return, and Realized Rates of Return,
Electric Companies, 1972*
!, Average After-Tax Current (or Marginal)
Cost of Capital 9..V'',
2. Average After-Tax Embedded Cost of
Capiial 8.0%
3. Allowed, or Target, Rate of Return as
Prescribed by Regulatory Agencies 7.6%
4. Current Actual Rate of Return on Investment 1 .IX
•The cost of equity capital is defined as the rate of return

32. on book equity thai was authorized if a rate caî e was
recently concluded, or the rate of return most likely to be
allowed if a rate case were lo be decided now. The
problems encountered when attempting to measure the
cost of equity are well known, and il is possible iha[
Commission-determined costs of capital arc seriously over-
or undersuued. We have simply avoided this issue by
accepting ihe Commission's estimates.
It should be noled that iho figures given are returns on
hook equity, which may be different from investors' re-
quired rates of return on market values. For a discussion
of this point, sec the discussion of A.A. Robichek in the
1971 AT&T rate ease (FCC Doeket No. 19129) or
E.F. Brigham in the 1972 Conisal rate case (FCC Doeket
No. 16070).
Also, it should be noted thai different companies cm-
ploy different rate base valuation methods (i.e.. original
cost vs. "fair value"), and different rates of relurn on
these different rate bases are appropriate. Such differences
were considered in ihe study upon which Exhibit II is
based.
Source: Eugene F. Brigham and Richard H. Pettway.
"Capital Budgeting in ihe Public Utility Sector."
University of Florida, Public Uliiily Research
Center. Working Paper No. 3-73. October 1973.
One thing was very clear from comments attached
to the questionnaire—the utility company executives
very definitely think thai the market price of their
stock is influenced by dividend policy. Quite a few
respondents made note of the fact that Potomac
Electric Power Company, in a well-known case, took
exactly the action suggested inourquestionnaire, and,

33. apparently as a resull of this action, the price of the
stock dropped precipitously. Academicians mighl ar-
gue that the stock price declined because of other
factors, but it would be hard to convince a number
of utility company executives that ihis was ihc case.
Conclusions
Under inflation the established pattern of rate
regulation has nol worked oui as utility Ihcory as-
sumes, and, as a resull, the utility companies have
been placed in a difficult position. On the one hand,
they must make whatever invcsttneni is necessary to
meet service demands, yet rising costs, coupled wiih
prices of their products ihat rise only with a lag,
have caused rates of return to erode. Thus, many
utilities are placed in a position where they must ac-
cept projects whose internal rates of return are less
than their cost of capital.
Frotii a survey we conclude the following abou(
capital budgeting by electric utilities.
1. Utility companies use a DCF selection criterion
(minimum PV of revenue requirements) to a greater
extent than do the Fortune 500 industrials. This dif-
fercniial usage probably results from the fact that the
utilities arc large and capital intensive, make very
long-term investments, and can estimate cash flows
better than firms more subject to competitive pres-
sures.
2. Utilities seem to recognize risk differentials
among projects to at least as great an extent as do
industrial companies, but since these differences can-

34. not generally be quantified, they influence project se-
lection in a judgmental manner, not through a for-
mal technique such as certainty equivalents or risk-
adjusted discount rales.
3. Utility companies do not employ post-audits
of investment projects to as large an extent as do in-
dustrial firms.
4. Capital rationing is becoming a problem for
utililies. Their first reaction is lo seek rate increases
which will enable them to raise additional funds, but
if rate increases are nol forthcoming, then projects
will be eliminated or postponed, assets will be leased,
or less capital intensive alternatives will be accepted.
5. Utility companies do not generally consider in-
put estimates to be a very serious problem. Inter-
estingly, they overwhelmingly consider obtaining ap-
proval for new generating plants from environmental
protection agencies or the AEC lo be the single most
difficult aspect of capital budgeting.
6. The current cost of capital exceeds ihe embedded
cost, and this cost exceeds both Ihe allowed and rea-
lized rates of return. This situation has given rise to
a large number of pending rate cases.
7. When utiiiiies use the discounted cash flow tech-
niques, they use the marginal cost of capital as a
hurdle rale.
8. The majority of the companies Indicated thai
their dividend policy is nol influenced by capital
needs or by capita! market conditions, al least not in
the short run.

35. Overall, the electric companies seem to be oper-
ating largely in a manner that, while different be-
cause of their regulatory environment, is generally
Autumn 1973 21
consistent wiih the types of capital budgeting tech-
niques recommended in the aeadeniic literature. How-
ever, we do feel that public utilities should at least
consider employing the NPV method ralhcr than ihc
PV of annual cost method for both discretionary and
mandatory system expansion investments. While dif-
ficulties would certainly be encountered in making
these calculations, the NPV method would provide
valuable data on the explicit impact of expansion on
both profitability and revenue requirements.
REFERENCES
1. Mouslafa Abdclsamad. A Guide to CapitalE.xpemtiture
Analysis, New York, AMACOM. American Management
Association, 1973.
2. George A. Christy, Cupiial Budgeting—Curreni Pruc-
lices and Their Efficiency, Eugene, Oregon, Bureau of
Business & Economic Research, University of Oregon.
1966.
3. Gordon R. Corey. "The Avcrch and Johnson Pro-
position: A Critical Analysis," Bell Journai (Spring
1971). pp. 358-373.

36. 4. Donald F. Istvan. Capital Expenditure Decisions:
Haw They arc Made in Large Corporations. Bloomington,
Indiana, Bureau of Business Research, Indiana University,
1961.
5. Donald F. Istvan, "The Hconomie Evaluation ofCap-
it;il Expenditures," ' The Journal of Business {9(}).
6. Nat ional Assoeiation of Accountants , Financial Anal-
ysis to Guide Capiial Expenditure Decisions. Research
Report 43. New York. Niiiional .Association of Accoun-
tants. 1967.
7. Norman P, Pflonin, "Managing Capital Expendi-
tures," Studies in Business Policy, 107, New York. The
National Industrial Conference Board, 1963.
8. Robert M. Soldofsky, "Capital Budgeting Praetiees in
Small Manufacturing Companies," .Siudie.s in the Factor
Markets for Small Business Firms, Ames, Iowa, Iowa
State University, 1963.
9. George Tcrborgh, Business Investment Management.
a MAPI Study and Manual. Washington. D.C.. Ma-
chinery and Allied Products Institute and Council for
Teehnologica! Advancement. 1967.
22 Financial Management

37. Capital Budgeting and Political Risk:
Empirical Evidence
Martin Holmén
Department of Economics, Uppsala University, Uppsala,
Sweden
Bengt Pramborg
Swedbank, SE-105 34 Stockholm, Sweden
Abstract
This paper surveys and investigates Swedish firms’ use of
capital budgeting techniques for
foreign direct investments. We document that the use of the
theoretically correct net
present value method decreases with the political risk in the
host country, and that the use
of the Payback method increases with the political risk. We
conclude that in the presence
of capital market imperfections, unsystematic and country-
specific political risks are
important. Because these risks are difficult to estimate
(rendering high deliberation costs)
managers are inclined to use simple rules of thumb for their
capital budgeting decisions.
Our results can partly explain why surveys find that alternative
methods such as the
Payback method are frequently used despite their theoretical
drawbacks.
1. Introduction

38. Several authors have pointed out that the way capital budgeting
is taught
and practiced presents a paradox (see, e.g., Weingartner, 1969;
Mao, 1970;
Stanley and Block, 1984; Arnold and Hatzopoloulos, 2000).
Typically,
students in corporate finance are taught that a project will
increase the
shareholder value if its net present value (NPV) is positive. The
NPV is
computed by forecasting the project’s cash flow and discounting
it at a
discount rate reflecting the price charged by the capital markets
for the cash
flow risk. For investors with well-diversified portfolios, only
the project’s
systematic risk affects its value: its idiosyncratic risk should
not be
considered. Capital market imperfections such as costly external
financing
and bankruptcy costs are mostly ignored when it comes to the
way capital
budgeting is taught (Stulz, 1999).
1

39. The authors would like to thank Annika Alexius, Fredrik
Berchtold, James Dean, Nils Gottfries,
Niclas Hagelin, Mattias Hamberg, Juha-Pekka Kallunki, Ted
Lindblom, Lars Norden, Thomas J.
O’Brien, Jonas Råsbrant, Iwan Meier, and Stefan Sjögren for
their valuable comments. Comments
from participants at the 2005 SNEE conference, the 2006 FMA
European Conference, the EFMA
2006 Annual Conference, and at seminars at University of
Gothenburg, Stockholm University, and
Uppsala University are also acknowledged. Financial support
from Jan Wallander and Tom
Hedelius Research Foundation is gratefully acknowledged.
Journal of International Financial Management and Accounting
20:2 2009
r 2009 Blackwell Publishing Ltd., 9600 Garsington Road,
Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148,
USA.
In practice, the NPV method is used extensively, but it is by no
means
the only technique used. Alternative methods, such as the
Payback method
and the use of earnings multiples, are also common. The
payback is seen as
possibly the most seriously flawed method, because it ignores
the time value
of money and cash flows beyond an arbitrary cut-off date.

40. Surprisingly,
Graham and Harvey (2001) report that 57 per cent of the CFOs
in their
survey of US firms always or almost always use the Payback
method in
capital budgeting decisions, as compared with the 76 per cent
(75 per cent)
using the NPV method [internal rate-of-return (IRR)]. The use
of the
Payback method seems even more popular in Europe, as
reported by
Brounen et al. (2004). They find the Payback method to be the
most
frequently used method among firms in the United Kingdom,
Germany,
and France, and it is also very common in the Netherlands,
where it is the
second most popular method after the NPV.
In this paper, we provide survey evidence on firms’ capital
budgeting
methods for foreign direct investments (FDIs) and we
investigate the
potential impact of idiosyncratic country-specific political risk
on the

41. capital budgeting process.
2
We provide evidence as to whether such risks
may help explain why firms rely on alternative methods, such as
the
Payback method, despite their theoretical flaws. Political risks
are most
likely to be associated with high deliberation costs, i.e.,
substantial
resources spent to make estimates of cash flows and the risk
profiles
for FDIs in countries with high political risk.
3
It is possible that
managers avoid these costs by using rules of thumb, such as the
Payback
method, instead of the more information intensive, and
therefore costly,
NPV method. If so, this would support the theoretical concept
of
bounded rationality, according to which decision makers, when
facing
high deliberation costs, use rules of thumb in an effort to
approximate

42. optimality (Baker et al., 2004).
We survey Swedish firms and combine the survey responses
with unique data from the Swedish central bank on each firm’s
FDIs
per country and the Economist Intelligence Unit’s (EIU)
political risk
indices. This dataset enables us to approximate the political risk
of each
firm’s portfolio of FDIs and test (i) whether political risks are
related to
the choice of capital budgeting method and (ii) whether firms
adjust the
chosen methods for political risks. Previous research has
explored how
various firm and manager characteristics correlate with the
choice of
capital budgeting method. However, as far as we know, the
relation
between firms’ investment risk characteristics and the choice of
capital
budgeting method has not previously been explored.
106 Martin Holmén and Bengt Pramborg
r 2009 Blackwell Publishing Ltd.

43. The survey responses suggest that a majority of firms make
adjust-
ments for country-specific political risks when evaluating FDIs.
In
addition, many firms indicated that they use different decision
criteria
for FDIs in countries with higher political risk (developing
countries) as
compared with FDIs in countries with lower political risk
(developed
countries). Our cross-sectional analysis indicates that when
firms evalu-
ate FDIs, the use of the NPV method decreases and the use of
the
Payback method increases with political risk. Possibly,
managers find it
problematic to assess political risk when using the NPV method
and are
therefore more likely to rely on the Payback method as a rule-
of-thumb
when these risks are significant. This supports the argument of
Baker et

44. al. (2004) of bounded rationality in the capital budgeting
process.
The paper makes two general contributions to the capital
budgeting
literature. First, because political risks most likely are
unsystematic, our
findings highlight the importance of market imperfections in
capital
budgeting. Second, the tendency to use the Payback method
instead of
the NPV method when there are substantial unsystematic risks,
documen-
ted in the paper, can partly explain why a number of surveys
have found
the Payback method to be frequently used, despite its
theoretical draw-
backs (see, e.g., Graham and Harvey, 2001; Sandahl and
Sjögren, 2003).
The rest of the paper is organized as follows. The next section
provides a
discussion on the discrepancy between theoretical
recommendations and
corporate practice and our research questions. Section 3
contains a descrip-

45. tion of the questionnaire and the data. We also define the
variables used in
the empirical analysis. In Section 4, we present our results.
Finally, Section 5
concludes and puts our results into the perspective of earlier
literature on
possible explanations as to why firms frequently use the
Payback method.
2. Arguments for using alternative methods
Earlier empirical research has shown the use of alternative
methods to
the NPV to be very common (Graham and Harvey, 2001;
Sandahl and
Sjögren, 2003; Brounen et al., 2004; Liljeblom and Vaihekoski,
2004).
The common use of the Payback period is seen as especially
surprising.
4
Several possible explanations for the use of the Payback method
have
been discussed in the literature. Weston and Brigham (1981, p.
405)
suggest that it may be rational for cash constrained firms to use
this

46. method. If an investment project does not create positive cash
flows at an
early stage, the firm will cease its operations and will therefore
not receive
positive future cash flows, or else will not have the resources to
pursue
Capital Budgeting and Political Risk 107
r 2009 Blackwell Publishing Ltd.
other investments during the next few years. Other suggested
explana-
tions for the use of the Payback method is that it may be used
by
managers to approximate the riskiness of a project (Mao, 1970;
Ehrhardt
and Brigham, 2003, p. 265), that it can approximate the option
value of
waiting to invest (Boyle and Guthrie, 1997; McDonald, 2000)
5
, and that
it can be explained by the lack of sophistication of management
(Graham
and Harvey, 2001).
6

47. In this paper, we focus on capital market imperfections and
deliberation
costs as explanations for the use of the Payback method. With
perfect
capital markets, unsystematic risks should not be of any
importance.
Investors with well-diversified portfolios can diversify
unsystematic risk
and their required return reflects systematic risk only.
Therefore, rational
value-maximizing managers should evaluate investment projects
using the
NPV rule, with a discount rate reflecting systematic risk.
Because country-
specific political risk most likely is unsystematic, it should not
influence the
required rate of return.
7
However, markets are not perfect, and theoretical
advances within the fields of corporate risk management and
capital
structure have shown that total risk may be of importance for
financial
management.

48. 8
In fact, Harvey (2000) and Mishra and O’Brien (2005) find
that total risk is the most significant risk factor in explaining ex
ante equity
returns in emerging markets.
It might be argued that effects of political risks could be
included by
rational managers in an NPV analysis. Several authors have
discussed
and modeled how firms should incorporate political risk in their
capital
budgeting and a number of ad hoc adjustments to the discount
rate have
been developed by investment banks (e.g., Godfrey and
Espinosa, 1996).
Many of these models employ equity market return volatility as
a risk
factor, based on political risk intuition.
9
Other, more theoretical models
are often relatively difficult to implement (see, e.g., Clark,
1997, 2003;
Mahajan, 1990; Pointon and Hooper, 1995; and Shapiro, 1978).
Further-

49. more, political risks may be non-linear, and a complication is
that they
are usually accessible as qualitative judgments only, such as a
scaling
from one to five (which is what we use in this paper). Erb et al.
(1996a)
show that country risk measures are correlated with future
equity returns
and equity valuation. However, translating political risk
measures into
estimates of probabilities and expected shortfalls or risk
premiums in the
capital budgeting process is complex, especially as the
estimated para-
meters may change over time. Therefore, estimating the effects
of events
in politically risky countries incurs high deliberation costs.
Because
managers have limited available resources, they may be inclined
to use
108 Martin Holmén and Bengt Pramborg
r 2009 Blackwell Publishing Ltd.

50. rules of thumb to avoid these costs and proxy for the optimal
decision.
Baker et al. (2004) argue that boundedly rational managers cope
with
complexity by using rules of thumb in financial management
that ensure
an acceptable level of performance and, hopefully, avoid severe
bias.
10
As an example, consider the risk that the host country will
expropriate
the firm’s FDI. The risk of expropriation is probably negligible
until the
project is fully developed (Mahajan, 1990). However, at some
point in
time, the risk of expropriation and the associated cost of
financial distress
increase significantly.
11
Thus, the present value of expected cash flow
declines significantly after this point in time and the FDI’s NPV
is, to a
large extent, determined by the short-term cash flows.
Furthermore, the

51. deliberation costs associated with correctly estimating the risk
of
expropriation and the cost of financial distress beyond this
point might
be high. Focusing on the short-term cash flows using the
Payback
method as a rule of thumb under these conditions may, in fact,
(i)
roughly approximate an optimal decision by the NPV method
and (ii)
avoid large deliberation costs.
Based on the above discussion, we set out to answer two
research
questions: First, we investigate whether firms rely less on the
NPV
method and more on rules of thumb when there are large
investment-
specific risks for which data is difficult to access or evaluate; in
this case
political risk. We specifically ask how firms’ use of the NPV
method and
the Payback method is affected by political risk in the host
country. If the
deliberation cost were positively correlated with political risk,

52. we would
expect to find an increased use of rules of thumb (Payback
method) with
increased political risk.
Second, we investigate if firms adjust the capital budgeting
methods
for political risk in the host country. We document the use of
several
adjustment methods, and cross-sectionally investigate whether
firms
adjust the payback period based on the level of political risk. If
the
deliberation cost increases with political risk, firms may be
inclined to
shorten the payback period, in effect reducing the forecast
period
necessary for making decisions. Segelod (2000), using a survey
and
follow-up interviews with executives, finds that managers
shorten the
payback period when political risk is higher. Based on this, we
expect
that firms will shorten the payback period when making
investments in

53. countries with relatively high political risk.
Our research questions are related to Erb et al. (1996b). Using
country
credit risk ratings, they construct expected equity returns and
equity volati-
lity estimates for 135 countries, many of which did not have a
functioning
Capital Budgeting and Political Risk 109
r 2009 Blackwell Publishing Ltd.
equity market at the time. The expected hurdle rates and
volatility estimates
are then used to develop payback measures related to the
statistical concept
of hitting time. The equity investors can then compare the
hitting time with
his or her expectations about political and economic risks. In
our capital
budgeting framework, the corporate manager evaluating a FDI
when
deliberation costs are high, e.g., no equity market in the host
country,

54. will rely on the Payback method. Furthermore, the higher the
political risk,
the shorter the required payback period.
3. Data and Method
In this section, we discuss the survey design, present the
questionnaire,
and detail the sampling procedure including the robustness tests
we
performed. In addition, we discuss the choice of firm
characteristic
variables and the limitations of the data.
3.1 Survey Design and Sample Collection Procedure
Several surveys concerning firms’ capital budgeting practices
have been
conducted. Most of these focus on how capital budgeting
methods vary
with firm characteristics and over time.
12
Our survey and research design
differ from previous surveys in some dimensions. First, we
focus on
capital budgeting for FDIs and survey firms’ use of different
capital

55. budgeting methods for this purpose.
Second, we survey how firms manage political risks when
investing
abroad. Several authors have suggested that firms could manage
political
risks by pre-investment planning, e.g., buying insurance,
structuring the
investment, and/or developing local stakeholders.
13
We survey to what
extent firms actually use these pre-investment strategies to
manage
political risks. In addition, we survey whether firms use more
stringent
investment criteria and/or different decision criteria when
investing in
countries with high political risk.
Third, we relate each firm’s capital budgeting methods to its
actual portfolio of FDIs. Thus, we are able to investigate
whether the
capital budgeting methods of a firm with its entire FDIs in low-
risk

56. countries differ from the methods used by firms with some of
their FDIs
in high-risk countries. In particular, we focus the analysis on
whether
firms are more likely to use the Payback method instead of the
theoretically correct NPV method when the risk of expropriation
is
perceived to be high.
110 Martin Holmén and Bengt Pramborg
r 2009 Blackwell Publishing Ltd.
The questionnaire was deliberately kept as short as possible in
an
attempt to increase the response rate. In this paper, we use three
questions from the survey (see Appendix A for an English
translation):
Popularity of different capital budgeting methods: The first
question
asked respondents rank how often they use each of a number of
capital
budgeting methods.
Methods to manage country-specific political risk: Respondents

57. were
asked to rank how often they use each of a number of methods
to manage
country-specific risks. These methods include the adjustments
of cash
flows and discount rates as well as e.g., purchasing political
risk insurance.
Different decision criteria: Finally, the respondents were asked
to
indicate whether they use different decision criteria for
investments in
developing countries and developed countries.
In September 2003 with a follow-up in November the same year
the
questionnaire was sent to the CFOs of the Swedish firms that
had
responded to a survey from the Swedish central bank
(Riksbanken) in the
spring of 2003, regarding how much FDI the firm had invested
as of
December 2002 (we exclude firms that replied that they had no
FDIs). A
total of 497 firms met the criteria and 200 responded, 72 of
which only

58. answered after the follow-up. From the 200 responses, 145 are
usable (54
firms responded that the questions were irrelevant for them, for
example
because the FDIs had been made some years before. For one
firm there is
no accounting data).
14
The ratio of usable responses to the total number
of recipients is 0.291. Compared with other surveys, e.g.,
Graham and
Harvey (2001) and Brounen et al. (2004), with response rates of
0.12, and
0.05, respectively, this is a high response rate.
We performed two tests to check for response bias. First, we
compared
respondents to non-respondents by means of Wilcoxon rank sum
tests,
on nine variables.
15
This test indicates no response bias with one
exception: respondents were significantly larger than non-
respondents.

59. Then, we compared the respondents that answered directly to
the firms
that only responded after a reminder. This second test, also
using
Wilcoxon rank sum tests on nine variables, indicated no
response bias.
To check whether it can be expected that the documented size
bias will
affect our conclusions, we used a classification, similar to that
of Graham
and Harvey (2001), and Brounen et al. (2004), where firms were
considered small if they had total sales of oUSD100 million,
mid-sized
if their sales were in the range USD100–1,000 million, and
large if their
sales exceeded USD1,000 million. We used the currency
exchange rate
SEK/USD as of December 31, 2002, which equals 8.75, to
translate SEK
Capital Budgeting and Political Risk 111
r 2009 Blackwell Publishing Ltd.
denominated numbers into USD. Using this classification, 63

60. (50) of the
usable responses are from small (mid-sized) firms and 32 are
from large
firms.
16
Thus, the sample mainly contains smaller firms. We expect that
any possible bias will not seriously affect our findings, because
the
numbers of firms in the respective category indicate that we
should be
able to distinguish size effects cross-sectionally.
3.2 Firm Characteristics
Because we sent the questionnaire to firms that responded to the
Riksbank that they had FDIs, we have ascertained that we have
a
sample containing firms with FDIs. Further, the Riksbank
survey asked
respondents to specify their FDIs on a country-by-country basis,
which
the Riksbank has kindly let us share. Our final sample of 145
firms
reported a total of 1,152 FDIs to the Riksbank and the average
firm had

61. FDIs in eight countries representing on average 25 per cent of
its assets.
17
Because the Riksbank data gives us information as to in which
countries
firms have FDI, we can calculate a measure of the political risk
to which
these FDIs are exposed. From the EIU, we gather information
for 61
countries on expropriation risk (and other indices on political
risk). Using
this data, we create a firm-specific political risk variable, which
is defined
as the weighted average of the EIU index values over the period
1995–
2002.
18
The weights are the proportion of total FDI in each country. The
firms in our sample have FDIs in 4120 countries, so our index is
not
complete. However, for most firms, the index covers more than
90 per
cent of total FDI. For the 13 firms with lower index coverage,
there are
only six countries missing, namely the three Baltic states,

62. Bermuda,
Luxembourg, and the United Arab Emirates. For these
countries, we set
the risk measure on par with countries we estimated to be
similar in terms
of political risk.
19
We also use robustness tests to handle these countries,
which are discussed below.
We complement the data from the survey and the risk indices
with
publicly available information on firm characteristics. Table 1
reports
descriptive statistics for our sample and formalizes our variable
definitions.
Earlier surveys (see, e.g., Graham and Harvey, 2001) have
found that larger
firms, highly levered firms, and public firms more commonly
use the NPV
method. Therefore, we include these variables as explanatory
variables
(Size, Leverage, and Public, as defined in Table 1). It is also
possible that

63. managers in public firms and larger firms are more
sophisticated and
therefore less likely to use the Payback method (Graham and
Harvey,
112 Martin Holmén and Bengt Pramborg
r 2009 Blackwell Publishing Ltd.
Capital Budgeting and Political Risk 113
Table 1. Descriptive statistics
Variable Definition Source Q1 Median Q3 Mean
Panel A: Firm characteristics
Size Total assets (MSEK) FR 477 2,005 6,218 3,610
Leverage Long term debt � total assets FR 0.09 0.21 0.35 0.25
Liquidity Current assets � short-term debt FR 1.31 1.71 2.46
2.49
Fixed asset ratio Fixed assets � total assets FR 0.88 0.94 0.98
0.91
Investment rate (Yearly change in fixed assets1
depreciation) � fixed assets
FR �0.02 0.08 0.21 0.13
Public Indicator variable for listed firms SSE — — — 0.35
Industry Indicator variable for firms in
capital intense industries
RB — — — 0.66

64. %FDI Foreign direct investment �
total assets
RB, FR 0.06 0.18 0.35 0.25
Exprop Risk
a
A country-weighted average
of expropriation risk
RB, EIU 1 1 1.07 1.10
GDP growth A country-weighted GDP
per capita growth rate (%)
RB, WB 2.59 2.90 3.29 3.04
Source Q1 Median Q3 Mean
Panel B: Country data
Expropriation risk in countries with FDI
[total no. is 61 (67)]
EIU 1 (1) 1 (1.5) 2 (2) 1.65 (1.67)
GDP growth in countries with FDI
(total no. is 67)
WB 2.16 3.23 4.12 3.30
Top five countries with FDI: RB
No. of firms Total amount

65. 1. Norway (81) 1. USA (28.3%)
2. Denmark (73) 2. Germany (12.9%)
3. Finland (71) 3. Great Britain (11.7%)
4. Germany (63) 4. The Netherlands (7.2%)
5. Great Britain (56) 5. Denmark (5.6%)
The table displays variable definitions and descriptive statistics.
Panel A displays firm
characteristics, and Panel B displays statistics on host countries.
All variables are defined using
book values unless otherwise stated. The data sources are: FR,
Financial Reports ending in the
year 2002; SSE, The Stockholm Stock Exchange; RB,
Riksbanken (the Swedish Central Bank);
EIU, the Economist Intelligence Unit; and WB, the World Bank.
The risk of expropriation
rating scores countries between 1 and 5, with 5 indicating
highest risk and 1 lowest risk. The
descriptive statistics include: Q1, the first quartile; median; Q3,
the third quartile; and the mean
value. Panel B displays country statistics on: the average value
from 1995 to 2002 of the
expropriation index for countries with FDIs, where the risk of
expropriation rating scores
countries between 1 and 5, with 5 indicating highest risk and 1
lowest risk; and the average value
from 1995 to 2002 of GDP growth per capita. Panel B displays
statistics on the top five countries
in terms of how many sample firms that had FDIs in the country
(the values in parentheses
include six countries for which the authors assigned a political
risk index, see footnote 10); and
on the top five counties regarding how much FDI the country
received (percentage of total FDI
in parenthesis).
a

66. The EIU index originally runs from ‘‘1’’ 5 riskiest to ‘‘5’’ 5
safest. As we want to interpret
riskier countries as having higher values, our index is calculated
as Exprop Risk 5 �(EIU index
– 6), which creates an index that runs from ‘‘1’’ 5 safest to ‘‘5’’
5 riskiest.
EIU, Economist Intelligence Unit.
r 2009 Blackwell Publishing Ltd.
2001). Graham and Harvey (2001) also find that firms with high
leverage
use most capital budgeting methods more often than those with
low
leverage (a notable exception is the Payback method).
As suggested by Weston and Brigham (1981, p. 405), it may be
rational for cash constrained firms to use the Payback method.
We
include liquidity (Liquidity) to proxy for this and, in addition,
we include
the investment rate (Investment rate) to proxy for how much
capital the
firm needs. Firms with low liquidity and a high investment rate
may be
more inclined to use the Payback method.

67. Because it is possible that there may be industry effects
(Graham and
Harvey, 2001; Sandahl and Sjögren, 2003), we include an
industry
dummy for firms in capital intense industries. We define
manufacturing,
construction, transport, and real estate as capital intense
industries
(Industry), which is similar to the classification used by Graham
and
Harvey (2001).
20
In addition, we include the ratio of fixed assets to total
assets (Fixed Asset Ratio) as an alternative proxy for firms’
investments
in fixed assets. Graham and Harvey (2001) used an additional
classifica-
tion: a dummy variable for utilities. However, there are only
four utilities
in our sample, so this classification is not meaningful for us.
Finally, we include variables to reflect different aspects of
firms’
FDIs. The first variable (%FDI) measures the proportion of
FDIs of

68. total assets, which can be interpreted as being a proxy for how
important
FDIs are to a firm. The second variable measures the implied
expropria-
tion risk of a firm’s FDIs (Exprop Risk), which is the value-
weighted
average of each host country’s expropriation risk. This variable
is
clarified by an example. If a firm has 25 per cent of its FDIs in
Norway
(index values for 2002: Expropriation risk 5 1), and 75 per cent
of its
FDIs in Indonesia (expropriation risk 5 4), it will have a value
for
Exprop Risk of (0.25n110.75n4) 5 3.25. Our final variable is the
value-
weighted GDP-per-capita growth of the host countries where a
firm has
FDIs (GDP growth), for which we use the same weighting as for
the
Exprop Risk variable. Proxying for the growth rate of
investment cash
flows, GDP growth in the host country may affect the value of
waiting to

69. invest and McDonald (2000) and Boyle and Guthrie (1997)
suggest that
the Payback method may approximate this option value. Thus,
by
including a GDP growth variable, we attempt to control for this
alternative explanation to why firms use the Payback method.
Addition-
ally, Segelod (2000) found that firms may adjust their payback
periods
when they make capital budgeting decisions based on the
growth
prospects of the host country.
114 Martin Holmén and Bengt Pramborg
r 2009 Blackwell Publishing Ltd.
Panel B in Table 1 shows descriptive statistics at the host
country
level. The expropriation risk index is quite skewed and most
countries
(31 countries out of 61) have the lowest possible ranking of
‘‘1’’. Only a
few countries have an index value larger than ‘‘2’’ (the numbers

70. in
parentheses include the six countries with the authors’ assigned
risk, see
footnote 19). Further, countries are ranked based on how much
FDI they
have received. It can be seen that Norway is the country where
most
sample firms had FDIs (81 firms), followed by other countries
in
Northern Europe. In contrast, the country that received the
largest
amount of FDIs is the United States (28 per cent), followed by
North
European economies.
Table 2 displays Spearman rank correlations of the firm chara-
cteristic variables used in this study. The rank correlations
indicate
that larger firms are associated with higher leverage, lower
liquidity,
more fixed assets, and that they are more likely to be public
firms.
Moreover, larger firms are exposed to higher expropriation risk.
It is

71. also evident that firms in capital intense industries have a larger
proportion of their assets as FDIs, and that those with large
proportions
of FDIs are exposed to a higher expropriation risk. Finally, we
note
that FDIs with a higher expropriation risk also are those with
higher
GDP growth.
The data collection procedure described above enables us to use
a
unique dataset to analyze important aspects of firms’ capital
budgeting
methods. However, a number of drawbacks should be kept in
mind.
First, there is a timing issue that we cannot resolve with the
present data
set. We have access to how much FDI each firm had invested in
2002, but
we have no information as to when each investment was made.
Thus,
responses regarding capital budgeting practices do not
necessarily
specifically relate to the FDIs reported in the database. Second,
we

72. have information on a country-by-country basis for each firm,
but not on
a project level. Therefore, several investments made over a
possibly long
period of time may be included in the same FDI number. Third,
the data
provided on FDIs is accounting numbers. FDIs may have
different
economic values than accounting values, caused by e.g.,
inflation and
standardized depreciation schedules.
The usual limitations of survey research apply, where a major
caveat is
that responses represent beliefs. We cannot verify that the
beliefs coincide
with actions, and we cannot be certain the respondents were
interpreting
the questions correctly.
21
Among other reasons, these potential short-
comings suggest that our findings should be further
investigated.
22

73. Capital Budgeting and Political Risk 115
r 2009 Blackwell Publishing Ltd.
116 Martin Holmén and Bengt Pramborg
T
a
b
le
2
.
S
p
e
a
rm
a
n
ra
n
k
c
o
rr
e
la
ti
o
n
s,
fi
rm

74. c
h
a
ra
c
te
ri
st
ic
s
L
e
v
e
ra
g
e
L
iq
u
id
it
y
F
ix
e
d
a
ss
e
t

75. ra
ti
o
In
v
e
st
m
e
n
t
ra
te
P
u
b
li
c
In
d
u
st
ry
%
F
D
I
E
x
p

76. ro
p
R
is
k
G
D
P
g
ro
w
th
S
iz
e
0
.1
5
n
�
0
.2
6
n
n
n
0
.2
2

77. n
n
n
�
0
.0
6
0
.2
9
n
n
n
0
.1
8
n
n
�
0
.1
1
0
.1
6
n
n
�
0
.0

78. 7
L
e
v
e
ra
g
e
�
0
.0
2
0
.2
6
n
n
n
0
.0
3
�
0
.0
2
0
.0
6
�

79. 0
.0
7
0
.1
2
�
0
.0
0
L
iq
u
id
it
y
�
0
.1
4
�
0
.2
1
n
n
�
0
.1
2

80. 0
.0
7
0
.2
1
n
n
0
.1
0
�
0
.0
3
F
ix
e
d
a
ss
e
t
ra
ti
o
�
0
.0
1

81. �
0
.1
1
0
.0
6
�
0
.0
6
0
.0
9
0
.0
6
In
v
e
st
m
e
n
t
ra
te
�
0

82. .0
2
0
.0
1
�
0
.1
2
�
0
.1
5
n
�
0
.0
6
P
u
b
li
c
�
0
.1
0
0
.0

83. 5
0
.0
6
0
.0
4
In
d
u
st
ry
0
.1
7
n
n
0
.1
0
�
0
.1
0
%
F
D
I

84. 0
.1
8
n
n
�
0
.0
1
E
x
p
ro
p
R
is
k
0
.2
2
n
n
n
T
h
e
ta
b
le
re
p
o

85. rt
s
S
p
e
a
rm
a
n
R
a
n
k
c
o
rr
e
la
ti
o
n
c
o
e
ffi
c
ie
n
ts
fo
r
fi
rm
c

86. h
a
ra
ct
e
ri
st
ic
v
a
ri
a
b
le
s.
T
h
e
fi
rm
c
h
a
ra
c
te
ri
st
ic
v
a
ri
a
b
le

87. s
a
re
d
e
fi
n
e
d
a
s
fo
ll
o
w
s:
S
iz
e
is
th
e
b
o
o
k
v
a
lu
e
o
f
to
ta

88. l
a
ss
et
s;
L
ev
e
ra
g
e
is
lo
n
g
-t
e
rm
d
e
b
t
d
iv
id
e
d
b
y
to
ta
l
a
ss
et

89. s;
L
iq
u
id
it
y
is
th
e
ra
ti
o
o
f
c
u
rr
e
n
t
a
ss
et
s
to
sh
o
rt
-t
e
rm
d
e

90. b
t;
F
ix
e
d
A
ss
et
R
a
ti
o
is
th
e
ra
ti
o
o
f
fi
x
e
d
a
ss
e
ts
to
to
ta
l
a

91. ss
e
ts
;
%
F
D
I
is
th
e
b
o
o
k
v
a
lu
e
o
f
fo
re
ig
n
a
ss
e
ts
to
to
ta
l
a

92. ss
e
ts
;
In
v
e
st
m
e
n
t
ra
te
is
th
e
c
h
a
n
g
e
in
fi
x
e
d
a
ss
et
s
fr
o

93. m
th
e
p
re
v
io
u
s
y
e
a
r
p
lu
s
d
ep
re
c
ia
ti
o
n
;
P
u
b
li
c
is
a
n
in
d

94. ic
a
to
r
v
a
ri
a
b
le
th
a
t
is
a
ss
ig
n
e
d
th
e
v
a
lu
e
o
f
o
n
e
fo
r
li
st
e

95. d
fi
rm
s;
In
d
u
st
ry
is
a
n
in
d
ic
a
to
r
v
a
ri
a
b
le
th
a
t
is
a
ss
ig
n
e

96. d
th
e
v
a
lu
e
o
f
o
n
e
fo
r
fi
rm
s
in
c
a
p
it
a
l
in
te
n
si
v
e
in
d
u
st

97. ri
e
s;
E
x
p
ro
p
R
is
k
is
d
efi
n
e
d
a
s
th
e
v
a
lu
e
w
e
ig
h
te
d
e
x
p
ro
p

98. ri
a
ti
o
n
ri
sk
o
f
th
e
fi
rm
’s
F
D
Is
.
E
x
p
ro
p
ri
a
ti
o
n
ri
sk
e
st

99. im
a
te
s
a
re
c
o
ll
e
ct
e
d
fr
o
m
E
IU
C
o
u
n
tr
y
F
o
re
c
a
st
s.
T

100. h
e
ri
sk
o
f
e
x
p
ro
p
ri
a
ti
o
n
ra
ti
n
g
sc
o
re
s
c
o
u
n
tr
ie
s
b
et
w
e

101. e
n
1
a
n
d
5
,
w
it
h
5
b
ei
n
g
h
ig
h
a
n
d
1
b
e
in
g
n
o
n
-e
x
is
te
n

102. t.
S
ig
n
ifi
c
a
n
c
e
is
in
d
ic
a
te
d
a
s
fo
ll
o
w
s:
n
1
0
%
le
v
e
l;
n

103. n
5
%
le
v
e
l;
n
n
n
1
%
le
v
el
.
T
h
e
n
u
m
b
er
o
f
o
b
se
rv
a

104. ti
o
n
s
is
1
4
2
.
F
D
I,
fo
re
ig
n
d
ir
e
c
t
in
v
es
tm
e
n
ts
.
r 2009 Blackwell Publishing Ltd.

105. 4. Results
This section contains our main results. First, in Section 4.1, we
report on
the survey results and perform univariate tests (pairwise rank
correla-
tions). The indicated relationships are further investigated in
Section 4.2
using cross-sectional regressions.
4.1 Descriptive Statistics and Univariate Tests
The first question of the survey asked respondents to rank how
often they
used different capital budgeting methods. Figure 1 displays the
results.
The first six bars from the left in the figure show the proportion
of firms
that used each method at least seldom. It is evident that a
majority of
firms used each method, except real options. Further, the result
suggests
that firms that adopted a method used it quite frequently, real
options
once more being the exception. However, few firms (12 per
cent)

106. used Real Options, and those that used the method did so
relatively
Capital Budgeting and Political Risk 117
33%
24% 22%
31%
25%
16%
10% 15%
26%
13%
11%
19% 12%
15%
18%
9%
9%
8%
7%
9%

107. 6%
40%
0%
25%
50%
75%
100%
NPV IRR Earnings
multiples
Payback Accounting
return
Payback vs
NPV
Always Almost Always Sometimes Seldom
Real options
Figure 1. The Relative Popularity of Different Capital
Budgeting Methods.
The first six bars on the left in the figure display the proportion
of firms
that used each capital budgeting method for foreign direct
investments

108. decisions and the frequency of usage for each method,
respectively. The last
bar displays the proportion of firms that used the Payback
method more
often than net present value (NPV) (the number of observations
is 143).
r 2009 Blackwell Publishing Ltd.
infrequently. These results are broadly in line with those of
Graham and
Harvey (2001) and Brounen et al. (2004). The right-most bar
shows the
proportion of firms that used the Payback method more often
than the
NPV method. Forty per cent of the sample firms used payback
more
often than the NPV, confirming the importance of the Payback
method
for FDI investment decisions. In fact, another 32 per cent used
the
Payback method equally often as the NPV, and only 28 per cent
of the
sample firms used the NPV more often than the Payback
method.

109. Table 3 displays Spearman rank correlations between the
explanatory
variables (firm characteristics) and the frequency at which each
capital
budgeting method was used. It is evident that the use of the
NPV method
is positively related to firm size and public firms. Furthermore,
firms with
118 Martin Holmén and Bengt Pramborg
Table 3. Spearman rank correlations, question 1
NPV IRR
Earnings
Multiples Payback
Accounting
Return
Real
options
Size 0.52nnn 0.26nnn 0.15n 0.05 0.19nn 0.24nnn
Leverage �0.04 0.04 �0.07 �0.18nn 0.02 0.01
Liquidity �0.17nn �0.06 0.00 �0.01 �0.06 �0.22nnn
Fixed asset ratio 0.22nnn 0.25nnn �0.12 �0.07 0.04 0.08
Investment rate �0.06 �0.02 �0.06 0.06 0.05 0.09
Public 0.29nnn 0.01 0.30nnn 0.05 0.11 0.24nnn
Industry 0.06 0.08 �0.14 �0.05 �0.05 �0.06
%FDI 0.01 �0.01 0.05 �0.04 �0.01 �0.06

110. Exprop Risk �0.05 �0.03 0.00 �0.08 0.05 �0.03
GDP growth 0.00 �0.05 �0.07 �0.00 �0.01 �0.16n
NPV 0.45nnn 0.27nnn 0.05 0.16n 0.23nnn
IRR 0.12 0.15n 0.17nn 0.21nn
Earnings multiples 0.06 0.35nnn 0.20nn
Payback 0.24nnn 0.06
Accounting return 0.12
The table reports Spearman Rank correlation coefficients for
firm characteristic variables and
responses to question one regarding the use of different capital
budgeting methods. The firm
characteristic variables are defined as follows: Size is the book
value of total assets; Leverage is
long-term debt divided by total assets; Liquidity is the ratio of
current assets to short-term debt;
Fixed Asset Ratio is the ratio of fixed assets to total assets;
%FDI is the book value of foreign
assets to total assets; Investment rate is the change in fixed
assets from the previous year plus
depreciation; Public is an indicator variable that is assigned the
value of one for listed firms;
Industry is an indicator variable that is assigned the value of
one for firms in capital intensive
industries; Exprop Risk is defined as the value weighted
expropriation risk of the firm’s FDIs.
Expropriation risk estimates are collected from EIU Country
Forecasts. The risk of expropria-
tion rating scores countries between 1 and 5, with 5 being high
and 1 being non-existent. The
responses to the questions take values from 0 to 4, where a
higher value indicates more often (see
the survey in Appendix A). Significance is indicated as follows:

111. n10% level; nn5% level; nnn1% level.
The number of observations is 142.
FDI, foreign direct investments.
r 2009 Blackwell Publishing Ltd.
low liquidity and a large share of fixed assets used NPV more
frequently.
We also note that public firms were more likely to use earnings
multiples
than other firms. This might be an important metric for these
firms to
consider because they have to communicate their earnings to
analysts
and the public (see, Graham et al., 2006, for survey evidence on
the
importance of reported earnings). There is a negative
correlation between
the use of the Payback method and liquidity, which supports the
notion
that firms that are capital constrained use the Payback method
(Graham
and Harvey, 2001). Finally, we note that all correlations
between the
different capital budgeting methods are positive and most are

112. significant.
This suggests the methods to be complements rather than
substitutes.
The next question asked the respondents to rank how often they
used
a number of pre-specified methods to manage country-specific
risks, and
the final question asked the respondents to indicate whether
they used
different decision criteria in countries with high political risks
versus
countries with low political risks. Figure 2 displays the results.
Capital Budgeting and Political Risk 119
0%
25%
50%
75%
100%
Always Almost Always Sometimes Seldom
Insurance and management Investment criteria
Figure 2. Methods to Manage Country-Specific Political Risk.

113. The first eight bars on the left in the figure display the
proportion of firms
that used each method to manage political risk and the
frequency of usage
for each method, respectively (the numbers of observations are
in the range
134–140). The last bar on the right shows the proportion of
firms that used
different decision criteria for investments in developing
countries as
compared with developed countries (the number of observations
is 117).
r 2009 Blackwell Publishing Ltd.
The left-hand side of the figure shows that the involvement of
local
partners was used by more than 75 per cent of the sample firms
and many
of those firms used this strategy frequently. The second most
used method
was to limit dependence to one partner, while limiting
technology transfer
and purchasing political risk insurance was used by fewer firms.

114. In terms of
adjusting their investment criteria for country-specific political
risks (right-
hand side of the figure), our findings indicate that 450 per cent
of the
sample firms required higher returns, adjusted cash flow and/or
earnings
estimates, and used shorter payback periods. Interestingly,
asked directly,
43 per cent of the respondents indicated that they used different
decision
criteria when making FDIs in countries with high political risk
as compared
with countries with low political risk. Comments we received
include that
the firm ‘‘refrains from investments in countries with high
political risk’’,
that the firm ‘‘uses higher hurdle rates for these investments’’,
and that the
firm ‘‘uses a shorter payback period’’. This suggests that firms
do consider
this (mostly idiosyncratic) risk and that it is an important factor
for firms
making foreign investment decisions.

115. Table 4 displays rank correlations between firm characteristics
and
methods to manage country-specific risks. The positive
correlations be-
tween the methods suggest them to be complements rather than
substitutes.
Moreover, it is noteworthy that for firms with higher
expropriation risk in
their FDIs, it was more common to buy political risk insurance,
require
higher returns, and use shorter payback periods. However,
because larger
firms also are characterized by a higher expropriation risk, size
could
contribute to explain the use of political risk insurance and the
requirement
of higher returns.
This section has provided descriptive statistics and univariate
tests on
firms’ capital budgeting methods for FDIs. To provide further
evidence
as to which factors may explain the use of different methods, in
particular
whether country-specific political risks may explain differences

116. in capital
budgeting methods, we use cross-sectional regressions.
4.2 Cross-Sectional Regressions
In this section, we use cross-sectional regressions to investigate
our
research questions as to whether (1) political risk affects the
choice of
capital budgeting method, and (2) managers adjust the payback
period
based on political risk. The explanatory variable of main
interest to us is
the value-weighted expropriation risk of firms’ portfolios of
FDIs
(Exprop Risk), which serves as a proxy for firm-specific
political risk
120 Martin Holmén and Bengt Pramborg
r 2009 Blackwell Publishing Ltd.
Capital Budgeting and Political Risk 121
T
a
b
le

117. 4
.
S
p
e
a
rm
a
n
ra
n
k
c
o
rr
e
la
ti
o
n
s,
q
u
e
st
io
n
s
2
a
n
d
3
Q

118. u
e
st
io
n
2
Q
u
e
st
io
n
3
B
u
y
in
su
ra
n
c
e
L
im
it
te
c
h
tr
a

119. n
sf
e
r
L
o
c
a
l
p
a
rt
n
e
rs
L
im
it
d
e
p
e
n
d
e
n
c
e
o
n
e

120. p
a
rt
n
e
r
H
ig
h
e
r
re
q
u
ir
e
d
re
tu
rn
/I
R
R
A
d
ju
st
C
F
a
n

121. d
/o
r
e
a
rn
in
g
s
e
st
im
a
te
s
S
h
o
rt
e
r
p
a
y
b
a
c
k
H
ig

122. h
e
r
e
a
rn
in
g
s
m
u
lt
ip
le
s
D
iff
e
re
n
t
d
e
c
is
io
n
c
ri
te
ri

123. a
S
iz
e
0
.2
5
n
n
n
0
.0
7
0
.0
5
0
.0
5
0
.2
5
n
n
n
0
.1
4

124. 0
.0
1
0
.1
5
n
�
0
.0
3
L
e
v
e
ra
g
e
�
0
.0
1
�
0
.0
6
�
0
.0
1

125. �
0
.0
4
0
.0
1
�
0
.0
3
�
0
.0
8
�
0
.0
7
�
0
.0
0
L
iq
u
id
it
y

126. 0
.0
6
0
.1
7
n
n
0
.0
3
0
.0
9
0
.0
2
�
0
.0
7
0
.0
6
0
.0
3

127. 0
.1
6
n
F
ix
e
d
A
ss
e
t
R
a
ti
o
0
.0
3
0
.0
0
0
.0
7
0
.1
1
0
.1

128. 5
n
0
.0
5
0
.0
4
�
0
.0
8
�
0
.0
6
In
v
e
st
m
e
n
t
ra
te
�
0
.0
5

129. �
0
.0
7
�
0
.1
9
n
n
�
0
.0
1
�
0
.1
6
n
�
0
.0
4
�
0
.0
3
�
0

130. .1
0
�
0
.0
5
P
u
b
li
c
0
.1
7
n
n
0
.1
2
0
.0
5
0
.0
0
0
.0
9

131. 0
.1
4
n
0
.0
0
0
.1
5
�
0
.0
3
In
d
u
st
ry
0
.0
4
0
.1
9
n
n
0
.0

132. 5
�
0
.0
2
0
.0
3
�
0
.0
9
0
.0
0
�
0
.0
7
�
0
.1
8
n
%
F
D
I

133. �
0
.0
3
0
.1
6
n
0
.1
4
0
.1
0
0
.1
3
0
.1
2
0
.0
7
0
.1
8
n
n

134. 0
.0
3
E
x
p
ro
p
ri
a
ti
o
n
R
is
k
0
.1
5
n
0
.1
1
0
.0
7
0
.1
3
0

135. .1
7
n
n
0
.1
1
0
.1
9
n
n
0
.1
6
n
�
0
.0
9
G
D
P
g
ro
w
th
�
0
.1

136. 8
n
n
�
0
.1
6
n
0
.1
0
�
0
.0
9
�
0
.0
2
�
0
.0
3
�
0
.1
1
�
0

137. .1
0
�
0
.1
5
B
u
y
in
su
ra
n
c
e
0
.3
8
n
n
n
0
.1
6
n
0
.2
6
n
n
n

138. 0
.2
8
n
n
n
0
.2
4
n
n
n
0
.3
3
n
n
n
0
.3
0
n
n
n
0
.2
1
n
n
L

139. im
it
te
c
h
tr
a
n
sf
e
r
0
.2
4
n
n
n
0
.4
0
n
n
n
0
.2
2
n
n
n
0
.2

140. 6
n
n
n
0
.3
2
n
n
n
0
.3
8
n
n
n
0
.2
1
n
n
L
o
c
a
l
p
a
rt
n
e
rs

141. 0
.5
2
n
n
n
0
.2
6
n
n
n
0
.2
9
n
n
n
0
.2
3
n
n
n
0
.2
8
n
n
n

142. 0
.2
6
n
n
n
L
im
it
d
e
p
e
n
d
e
n
c
e
o
n
e
p
a
rt
n
e
r
0
.3
1
n
n

143. n
0
.2
3
n
n
n
0
.4
3
n
n
n
0
.4
1
n
n
n
0
.2
7
n
n
n
H
ig
h
e
r
re

144. q
u
ir
e
d
re
tu
rn
/I
R
R
0
.5
3
n
n
n
0
.5
6
n
n
n
0
.6
0
n
n
n
0
.1
9

145. n
n
A
d
ju
st
C
F
a
n
d
/o
r
e
a
rn
in
g
s
e
st
im
a
te
s
0
.6
1
n
n
n

146. 0
.5
7
n
n
n
0
.1
5
S
h
o
rt
e
r
p
a
y
b
a
c
k
0
.7
3
n
n
n
0
.2
2

147. n
n
H
ig
h
e
r
e
a
rn
in
g
s
m
u
lt
ip
le
s
0
.3
0
n
n
n
T
h
e
ta
b
le
re
p

148. o
rt
s
S
p
ea
rm
a
n
R
a
n
k
co
rr
el
a
ti
o
n
co
effi
ci
en
ts
fo
r
fi
rm
ch
a
ra
ct

149. er
is
ti
c
v
a
ri
a
b
le
s
a
n
d
re
sp
o
n
se
s
to
q
u
es
ti
o
n
s
2
a
n
d
3
re
g

150. a
rd
in
g
th
e
u
se
o
f
d
iff
er
en
t
m
et
h
o
d
s
to
m
a
n
a
g
e
co
u
n
tr
y
-s
p

151. ec
ifi
c
ri
sk
.
T
h
e
fi
rm
ch
a
ra
ct
er
is
ti
c
v
a
ri
a
b
le
s
a
re
d
efi
n
ed
a
s

152. fo
ll
o
w
s:
S
iz
e
is
th
e
b
o
o
k
v
a
lu
e
o
f
to
ta
l
a
ss
et
s;
L
ev
er
a
g
e
is
lo

153. n
g
-t
er
m
d
eb
t
d
iv
id
ed
b
y
to
ta
l
a
ss
et
s;
L
iq
u
id
it
y
is
th
e
ra
ti
o

154. o
f
cu
rr
en
t
a
ss
et
s
to
sh
o
rt
-t
er
m
d
eb
t;
F
ix
ed
A
ss
et
R
a
ti
o
is
th
e

155. ra
ti
o
o
f
fi
x
ed
a
ss
et
s
to
to
ta
l
a
ss
et
s;
%
F
D
I
is
th
e
b
o
o
k
v
a
lu

156. e
o
f
fo
re
ig
n
a
ss
et
s
to
to
ta
l
a
ss
et
s;
In
v
es
tm
en
t
ra
te
is
th
e
ch
a
n

157. g
e
in
fi
x
ed
a
ss
et
s
fr
o
m
th
e
p
re
v
io
u
s
y
ea
r
p
lu
s
d
ep
re
ci
a
ti

158. o
n
;
P
u
b
li
c
is
a
n
in
d
ic
a
to
r
v
a
ri
a
b
le
th
a
t
is
a
ss
ig
n
ed
th
e
v

159. a
lu
e
o
f
o
n
e
fo
r
li
st
ed
fi
rm
s;
In
d
u
st
ry
is
a
n
in
d
ic
a
to
r
v
a

160. ri
a
b
le
th
a
t
is
a
ss
ig
n
ed
th
e
v
a
lu
e
o
f
o
n
e
fo
r
fi
rm
s
in
ca
p
it

161. a
l
in
te
n
si
v
e
in
d
u
st
ri
es
.
E
x
p
ro
p
R
is
k
is
d
efi
n
ed
a
s
th
e
v
a
lu

162. e
w
ei
g
h
te
d
ex
p
ro
p
ri
a
ti
o
n
ri
sk
o
f
th
e
fi
rm
’s
F
D
Is
.
E
x
p
ro

163. p
ri
a
ti
o
n
ri
sk
es
ti
m
a
te
s
a
re
co
ll
ec
te
d
fr
o
m
E
IU
C
o
u
n
tr
y

164. F
o
re
ca
st
s.
T
h
e
ri
sk
o
f
ex
p
ro
p
ri
a
ti
o
n
ra
ti
n
g
sc
o
re
s
co
u
n
tr

165. ie
s
b
et
w
ee
n
1
a
n
d
5
,
w
it
h
5
b
ei
n
g
h
ig
h
a
n
d
1
b
ei
n
g
n
o
n
-e

166. x
is
te
n
t.
T
h
e
re
sp
o
n
se
s
to
q
u
es
ti
o
n
2
ta
k
e
v
a
lu
es
fr
o
m
0

167. to
4
,
w
h
er
e
a
h
ig
h
er
v
a
lu
e
in
d
ic
a
te
s
m
o
re
o
ft
en
,
a
n
d
th

168. e
re
sp
o
n
se
s
to
q
u
es
ti
o
n
3
ta
k
e
th
e
v
a
lu
es
0
5
n
o
a
n
d
1
5

169. y
es
(s
ee
th
e
su
rv
ey
in
th
e
A
p
p
en
d
ix
).
S
ig
n
ifi
ca
n
ce
is
in
d
ic
a
te

170. d
a
s
fo
ll
o
w
s:
n
1
0
%
le
v
e
l;
n
n
5
%
le
v
e
l;
n
n
n
1
%
le

171. v
el
.
T
h
e
n
u
m
b
er
o
f
o
b
se
rv
a
ti
o
n
s
is
1
3
4
fo
r
q
u
e
st
io
n

172. 2
,
a
n
d
1
1
7
fo
r
q
u
e
st
io
n
3
.
F
D
I,
fo
re
ig
n
d
ir
e
c
t
in
v
es
tm

173. e
n
ts
.
r 2009 Blackwell Publishing Ltd.
exposure. We also include a number of control variables as
discussed in
Section 3.2.
Table 5, panel A, displays the results from logit regressions.
Models 1
and 2 include indicator variables representing the use of the
NPV method
and the Payback method, respectively. The third model’s
dependent
variable is an indicator variable set to one for firms using the
Payback
method more frequently than the NPV method. All estimated
regression
models are adjusted for heteroskedasticity according to White
(1980).
Model 1 indicates the use of the NPV method to decline with
the risk of
expropriation. The coefficient for expropriation risk is

174. negatively sig-
nificant at the 10 per cent level, i.e., firms are less likely to use
the NPV
method when political risk is high. Model 2 provides evidence
that firms
more frequently rely on the Payback method when the perceived
expropriation risk is high. In model 2, the coefficient for
expropriation
risk is positively significant at the 5 per cent level. Model 3
presents
stronger results in line with our expectations. The dependent
variable
indicates whether the firm uses the Payback method more
frequently
than the NPV method when evaluating FDI. The coefficient for
expro-
priation risk is positively significant at the 5 per cent level.
These results
are consistent with managers using the Payback method as a
rule of
thumb to avoid high deliberation costs.
Supporting the evidence of Graham and Harvey (2001), we find
larger

175. and public firms to be more likely to use the NPV method,
while firms
with a large proportion of fixed assets are more likely to use
both the NPV
method and the Payback method. This result is counter to the
findings of
Graham and Harvey (2001) who find opposite signs in their
(univariate)
analysis. Leverage is negatively related to the Payback method,
but we
find no significant relation to the use of the NPV method. Our
proxies
for cash constraints and capital needs (Liquidity, Investment
Rate, and
the capital intense Industry Dummy) are insignificant in all
models.
Similarly, the GDP growth in the host country is insignificant in
all
models.
In panel B of Table 5, we report further evidence on the choice
of
capital budgeting method using ordered logit models. In model
1 the
dependent variable is equal to 0 if NPV is never used, 1 if NPV

176. is seldom
used, 2 if NPV is sometimes used, 3 if NPV is almost always
used and 4 if
NPV is always used when evaluating FDIs. The second model is
similar,
but includes the use of the Payback method as the dependent
variable. In
Model 3 the dependent variable is equal to the frequency (0–4)
at which
payback is used when evaluating FDIs minus the frequency at
which
122 Martin Holmén and Bengt Pramborg
r 2009 Blackwell Publishing Ltd.
Capital Budgeting and Political Risk 123
Table 5. Logit and ordered logit regressions with the frequency
at which the
NPV method and the Payback method, respectively, are used
when evaluating
Foreign Direct Investments
Panel A: Logit Regressions Panel B: Ordered Logit Regressions
Model 1
NPV

177. Model 2
payback
Model 3
payback
versus NPV
Model 1
NPV
Model 2
payback
Model 3
payback
versus NPV
Exprop Risk �1.419 2.864 2.001 �1.654 0.863 1.860
(�1.72)n (2.53)nn (2.03)nn (�2.13)nn (1.18) (2.45)nn
%FDI 0.778 �1.117 �0.499 0.432 �0.210 �0.720
(0.62) (�1.09) (�0.54) (0.46) (�0.26) (�0.89)
Public dummy 1.278 0.115 �0.766 0.658 0.187 �0.477
(2.41)nn (0.23) (�1.79)n (1.81)n (0.53) (�1.44)
Size 0.480 0.140 �0.367 0.479 0.054 �0.218
(2.73)nnn (1.15) (�3.41)nnn (4.28)nnn (0.69) (�3.46)nnn
Leverage �1.237 �3.894 �0.703 �0.695 �2.169 �1.223
(�1.22) (�3.11)nnn (�0.81) (�0.73) (�2.47)nn (�1.31)
Fixed asset ratio 4.022 3.799 �0.961 3.647 1.497 �0.537
(1.89)n (1.91)n (�0.52) (2.44)nn (0.98) (�0.52)

178. Liquidity 0.069 0.112 �0.058 0.039 0.039 �0.010
(0.91) (1.16) (�1.30) (1.10) (1.11) (�0.53)
Investment rate �0.300 �0.209 0.394 �0.186 0.079 0.144
(�0.78) (�0.38) (0.84) (�0.51) (0.26) (0.50)
Industry dummy �0.301 �0.608 �0.260 �0.166 �0.139 �0.250
(�0.52) (�1.09) (�0.62) (�0.41) (�0.43) (�0.77)
GDP growth �0.104 �0.469 �0.401 0.096 �0.217 �0.222
(�0.39) (�1.38) (�1.59) (0.44) (�0.97) (�0.93)
Prob4F 0.019 0.080 0.003 0.000 0.451 0.000
No. of
observations 1/0
97/44 112/30 56/86
Total no. of
observations
142 142 142 142 142 142
The table reports estimated logit (panel A) ordered logit
regressions (Panel B) with the frequency at which the
NPV method and the Payback method are used when evaluating
Foreign Direct Investments (FDIs). In
panel A Model 1 (Model 2) the dependent variable is equal to 1
if NPV (Payback) is used when evaluating
FDIs, and zero otherwise. In panel A Model 3 the dependent
variable is equal to one if Payback is used more
frequently than NPV when evaluating FDIs, and zero otherwise.
In panel B Model 1 (Model 2) the
dependent variable is equal to 0 if NPV (Payback) is never
used, 1 if NPV (Payback) is seldom used, 2 if NPV
(Payback) is sometimes used, 3 if NPV (Payback) almost

179. always, and 4 if NPV (Payback) is always used
when evaluating FDIs. In panel B Model 3, the dependent
variable is equal to the frequency at which
Payback (0 to 4) is used when evaluating FDIs minus the
frequency at which NPV (0 to 4) is used when
evaluating FDIs. Thus, the variable varies between �4 and 4.
Coefficients are reported with z-values in
parenthesis. Reported z-values are asymptotically robust to
heteroskedasticity (White, 1980). Significance is
indicated as follows:
n10% level; nn5% level; nnn1% level.
The number of observations is 142. Exprop Risk is defined as
the value weighted expropriation risk of the
firm’s FDIs. Expropriation risk estimates are collected from
EIU Country Forecasts. The risk of
expropriation rating scores countries between 1 and 5, with 5
being high and 1 being non-existent.
%FDI is equal to the book value of the firm’s all FDIs divided
by the book value of the total assets. Public
Dummy is equal to one if the firm is listed on a stock exchange,
and zero otherwise. Size is equal to the
natural logarithm of the book value of total assets at the end of
2002. Leverage is equal to the book value
of long-term debt divided by the book value of total assets at
the end of 2002. Fixed Asset Ratio is equal to
fixed assets divided by total assets. Liquidity is the ratio of
current assets to short-term debt. Investment
rate is equal to the change in fixed assets from the previous year
plus depreciation. Industry dummy is
equal to one if the firm is active in a capital intense industry,
and zero otherwise. GDP growth is equal to
the value weighted GDP growth per capita 1995–2002 in the
countries where the firm has FDIs.
r 2009 Blackwell Publishing Ltd.

180. NPV is used when evaluating FDIs. Thus, the variable can
assume values
between �4 and 4.
The results are similar to those reported in panel A. The
frequency at
which NPV is used declines with the risk of expropriation. The
coefficient
for expropriation risk is negatively significant at the 5 per cent
level in
model 1, but insignificant in model 2. It is positive and
significant at the 5
per cent level in model 3; once more in line with our
expectations. The
results for the control variables are also similar to those
reported above,
i.e., large and public firms more frequently use the NPV method
while the
fixed asset ratio (leverage) is positively (negatively) related to
the use of
the NPV method (Payback method). In sum, our results suggest
that
country-specific political risks affect the choice of capital
budgeting

181. method for FDIs.
Now, we turn our attention to our second research question:
whether
managers are more likely to shorten the payback period if they
are exposed
to higher political risk. Table 6 displays the results from our
cross-sectional
regressions. In panel A, the dependent variable is an indicator
variable
which is set to one if a firm shortens the payback period to
manage political
risk and zero otherwise (see, question 2.e in Appendix A). In
panel B, the
dependent variable represents how often the firms use a shorter
payback
period to manage political risk. It is evident that none of the
firm
characteristic variables contribute to explain this method,
except Exprop
Risk and GDP Growth. The first models in each panel, for
which all
variables are included, can be rejected by an F-test; an
indication that they
are mis-specified. Only including Exprop Risk and GDP

182. Growth, the
models cannot be rejected. Thus, it seems as if the major
determinants of
the practice of adjusting the payback period are project-specific
risk and
return (as proxied by political risk and the GDP growth of the
host
country). A potential explanation for our results is that
managers make
adjustments to cope with the trade-off of reducing deliberation
costs
(shortening the payback period when the political risk is higher,
thereby
reducing the need to make longer term projections), and
approximating
optimality as far as possible (lengthening the payback period
when
expected growth is higher, capturing more of the long-term
profitability).
We perform a number of robustness tests for the choice of
capital
budgeting method. First, we test for the probability of reverse
causality,
i.e., are firms more likely to invest in countries with high