CapitalBudgetinginSmallFirms June2006 Final

THE CAPITAL BUDGETING DECISIONS OF SMALL BUSINESSES

Morris G. Danielson* St. Joseph’s University

Philadelphia, PA

Jonathan A. Scott Temple University Philadelphia, PA

June 2006

We acknowledge the helpful comments of Jacqueline Garner, William Petty, and participants at the 2005 Financial Management Association and Eastern Finance Association Conferences.

* Corresponding author: Erivan K. Haub School of Business, Saint Joseph’s University, Philadelphia, PA 19131; Phone: (610) 660-1606; E-mail: [email protected]


Abstract

This paper uses survey data compiled by the National Federation of Independent Busi-

ness to analyze the capital budgeting practices of small firms. While large firms tend to rely on the discounted cash flow analysis favored by finance texts, many small firms evaluate projects using the payback period or the owner’s gut feel. The limited education background of some business owners and small staff sizes partly explain why small firms use these relatively unso-phisticated project evaluation tools. However, we also identify specific business reasons—including liquidity concerns and cash flow estimation challenges—to explain why small firms do not exclusively use discounted cash flow analysis when evaluating projects. These results sug-gest that optimal investment evaluation procedures for large and small firms might differ. [G31]


This paper analyzes the capital budgeting practices of small firms. The U.S. Small Busi-

ness Administration estimates that small businesses (which they define as firms with fewer than

500 employees) produce 50 percent of private GDP in the U.S., and employ 60 percent of the pri-

vate sector labor force. Many small businesses are service oriented, but according to the 1997

Economic Census over 50 percent are in agriculture, manufacturing, construction, transportation,

wholesale, and retail—all industries requiring substantial capital investment. Thus, capital in-

vestments in the small business sector are important to both the individual firms and the overall

economy.

Despite the importance of capital investment to small firms, most capital budgeting sur-

veys over the past 40 years have focused on the investment decisions of large firms (examples

include Moore and Reichardt, 1983, Scott and Petty, 1984, and Bierman, 1993). An exception is

Graham and Harvey (2001), who compare the capital budgeting practices of small and large

firms. Even their small firms are quite large, however, with a revenue threshold of $1 billion

used to separate firms by size. Indeed, less than 10 percent of their sample report revenues below

$25 million. Thus, Graham and Harvey’s results do not directly address the investment decisions

of very small firms.1

There are several reasons small and large firms might use different criteria to evaluate

projects. First, small business owners may balance wealth maximization (the goal of a firm in

capital budgeting theory) against other objectives—such as maintaining the independence of the

business (Ang, 1991, Keasey and Watson, 1993)—when making investment decisions. Second,

small firms lack the personnel resources of larger firms, and therefore may not have the time or

1 The Federal Reserve Board of Governor’s Survey of Small Business Finance serves as the data source in many studies of small business finance. The firms in the Board of Governor’s Survey tend to be much smaller than the firms in the Graham and Harvey (2001) sample; in the 1993 Board of Governor’s survey, 83 percent of the firms report revenues under $1 million. The firms in the Graham and Harvey sample, therefore, are much larger than firms typically included in studies of small business finance.

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the expertise to analyze projects in the same depth as larger firms (Ang, 1991). Finally, some

small firms face capital constraints, making project liquidity a prime concern (Petersen and Ra-

jan, 1994, and Danielson and Scott, 2004). Because of these small firm characteristics, survey

results on the capital budgeting decisions of large firms are not likely to describe the procedures

used by small firms.

To document the capital budgeting practices of small businesses, defined here as firms

with fewer than 250 employees, we use survey data collected for the National Federation of Inde-

pendent Business (NFIB) Research Foundation by the Gallup Organization. The results include

information about the types of investments the firm makes (e.g., replacement versus expansion),

the primary tools used to evaluate projects (e.g., discounted cash flow analysis, payback period),

the firm’s use of other planning tools (e.g., cash flow projections, capital budgets, and tax plan-

ning activities), and the owner’s willingness to finance projects with debt. The survey also in-

cludes demographic variables that allow us to examine the relations between capital budgeting

practice and firm characteristics such as size, sales growth, industry, owner age, owner education

level, and business age.

Not surprisingly, we find small and large firms evaluate projects differently. While large

firms tend to rely on the discounted cash flow calculations favored by capital budgeting theory

(Graham and Harvey, 2001), small firms most often cite “gut feel” and the payback period as

their primary project evaluation tool. Less than 15 percent of the firms claim discounted cash

flow analysis as their primary criterion, and over 30 percent of the firms do not estimate cash

flows at all when they make investment decisions. The very smallest of the surveyed firms (firms

with 3 employees or fewer) are significantly less likely to make cash flow projections, perhaps

because of time constraints.

Certainly a lack of sophistication contributes to these results, as over 50 percent of the

small-business owners surveyed do not have a college degree. Yet, there are also specific busi-

ness reasons why discounted cash flow analysis may not be the best project evaluation tool for

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every small firm. For example, 45 percent of the sample would delay a promising investment

until it could be financed with internally generated funds, suggesting the firms face real (or self-

imposed) capital constraints.2

We also find that the most important class of investments is “replacement” for almost 50

percent of the firms. Discounted cash flow calculations may not be required to justify replace-

ment investments if the owner is committed to maintaining the firm as a going concern, and if the

firm has limited options about how and when to replace equipment.

Finally, investments in new product lines are the most important class of investments for

almost one-quarter of the sample firms. Because the ultimate success of this type of investment is

often uncertain, it can be difficult to obtain reliable future cash flow estimates, reducing the value

of discounted cash flow analysis. Thus, our results suggest that optimal methods of capital budg-

eting analysis can differ between large and small firms.

I. Capital Budgeting Theory and Small Firms

Brealey and Myers (2003) present a simple rule managers can use to make capital budgeting

decisions: Invest in all positive net present value projects, and reject those with a negative net present

value. By following this rule, capital budgeting theory says firms will make the set of investment de-

cisions that will maximize shareholder wealth. And, because net present value is a complete measure

of a project’s contribution to shareholder wealth, there is no need for the firm to consider alternative

capital budgeting tools, such as payback period or accounting rate of return.

Yet, small firms often operate in environments that do not satisfy the assumptions underlying

the basic capital budgeting model. And, small firms may not be able to make reliable estimates of

future cash flows, as required in discounted cash flow analysis. We discuss these potential problems

2 Survey participants were asked: “Suppose you had the opportunity to make an investment in your busi-ness that would allow earnings to rise 25 percent within the next two years. The project had minimal risk, but you did NOT have the cash right then to make the investment. Would you most likely . . . ?” The choices included wait until you accumulate enough cash, borrow the money and make the investment, seek an outside investor, and other. Forty-five percent of the respondents selected wait until you accumulate enough cash.

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in detail, and explain why discounted cash flow analysis is not necessarily the one best capital budget-

ing decision tool for every small firm.

A. Capital Budgeting Assumptions and the Small Firm

Capital budgeting theory typically assumes that the primary goal of a firm’s shareholders

is to maximize firm value. In addition, the firm is assumed to have access to perfect financial

markets, allowing it to finance all value-enhancing projects. When these assumptions are met,

firms can separate investment and financing decisions, and should invest in all positive net pre-

sent value projects (Brealey and Myers, 2003).

There are at least three reasons to question the applicability of this theory to small firms.

First, shareholder wealth maximization may not be the objective of every small firm. As Keasey

and Watson (1993, p. 228) point out, an entrepreneur may establish a firm as an alternative to

unemployment, as a way to avoid employment boredom (i.e., as a life-style choice), or as a vehi-

cle to develop, manufacture, and market inventions. In each case, the primary goal of the entre-

preneur may be to maintain the viability of the firm, rather than to maximize its value.3

Second, many small firms have limited management resources, and lack expertise in fi-

nance and accounting (Ang, 1991). Because of these deficiencies, they may not evaluate projects

using discounted cash flows. Providing some support for this conjecture, Graham and Harvey

(2001) find that small-firm managers are more likely to use less sophisticated methods of analy-

sis, such as the payback period.4

The final impediment is capital market imperfections, which constrain the financing op-

tions for small firms. Some cannot obtain bank loans, because of their information-opaqueness

3 In a survey of Swiss firms, Jorg, Loderer, and Roth (2004) find that maintaining the independence of the firm was cited more frequently than shareholder value maximization as a goal of managers. They also find that firms pursuing goals other than shareholder value maximization were less likely to rely on discounted cash flow analysis for investment decisions. 4 The small firms in the Graham and Harvey (2001) have up to $1 billion in annual revenues. Thus, it is likely that many of these firms have more complete management teams than the small firms envisioned by Ang (1991). In contrast, we evaluate the capital budgeting policies of very small firms—our sample in-cludes only firms with less than 250 employees, and over 80 percent of the firms have less than 10 employ-ees—where the problem of incomplete management teams is likely to be most severe.

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and lack of strong banking relationships (e.g., Petersen and Rajan, 1994 and 1995, and Cole,

1998). Ang (1991) notes that access to public capital markets can be expensive for certain small

firms, and impossible for others. These capital constraints can make it essential for small firms to

maintain sufficient cash balances, in order to respond to potentially profitable investments as they

become available (Almeida, Campello, and Weisbach, 2004). Thus, capital constraints provide

small privately held firms with a legitimate economic reason to be concerned about how quickly a

project will generate cash flows (i.e., the payback period).

B. Cash Flow Estimation Issues

In his critique of capital budgeting theory, Booth (1996) describes estimation issues man-

agers must confront when implementing discounted cash flow analysis. He concludes that dis-

counted cash flow analysis is less valuable, the more uncertain the level of future cash flows.

According to this view, discounted cash flow analysis can be applied most directly to projects

with cash flow profiles similar to the firm’s current operations (such as projects extending those

operations). Discounted cash flow analysis will be less valuable to evaluate ventures that are not

directly related to current activities.

Although Booth developed these ideas for large multinational corporations, they can also

be applied to small firms. If a small firm is considering investment in a new product line, future

cash flows cannot be estimated directly from the past performance of the firm’s current opera-

tions. In addition, because of the firm’s scale, market research studies to quantify future product

demand (and cash flows) might not be cost effective. For these reasons, small firms may not rely

exclusively on discounted cash flow analysis when evaluating investments in new product lines.

There are also reasons why a small firm may not use discounted cash flow analysis to

evaluate replacement decisions. In many cases, replacing equipment is not a discretionary in-

vestment for a small firm; the firm must replace the equipment to stay in business. In some re-

placement decisions, a small firm may have limited replacement options, and differences in the

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future maintenance costs of the various options can be difficult to forecast.5

Because small firms do not satisfy the assumptions underlying capital budgeting theory,

and because of these cash flow estimation challenges, it would be natural for small firms to

evaluate projects using different techniques than large firms. But, evidence about these differ-

ences is largely anecdotal. We use survey data to document the capital budgeting practices of

small firms, and to provide evidence about whether small-firm project evaluation methods are

related to the type of investment under consideration.

II. Description of Data

The use of survey data to document capital budgeting practices has a long history in the

finance literature.6 Yet, survey results should be interpreted with caution because surveys meas-

ure manager beliefs, not necessarily their actions; survey participants may not be representative of

the defined population of firms; and survey questions may be misunderstood by some participants

(Graham and Harvey, 2001, p. 189). Nonetheless, surveys provide information that cannot be

readily gleaned from financial statements. In particular, surveys can shed light on how firms

make investment and financing decisions, and why they use these approaches.

The data for this study were collected for the NFIB Research Foundation by the Gallup

Organization. The interviews for the survey were conducted in April and May 2003 from a sam-

ple of small firms, defined as a business employing at least one individual in addition to the

owner, but no more than 249. The sampling frame for the survey was drawn at the NFIB’s direc-

tion from the files of the Dun & Bradstreet Corporation. Because the distribution of small busi-

5 Booth (1996) also concludes that discounted cash flow analysis might not be used for replacement deci-sions, but for a different reason. He argues that the payback period combined with judgment can often lead a firm to the correct decision for replacement projects, making discounted cash flow analysis unnecessary. 6 Scott and Petty (1984) summarize the results of 21 early studies of large firm capital budgeting practices. The selection criteria in these studies include membership in the Fortune 500/1000, a minimum level of capital expenditures, size, or stock appreciation in excess of certain benchmarks. In more recent studies, Moore and Reichardt (1983) surveyed 298 Fortune 500 firms, Bierman (1993) looked at 74 Fortune 100 firms, and Graham and Harvey (2001) investigated the behavior of 392 firms chosen from the membership of the Financial Executives Institute and the Fortune 500.

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nesses is highly skewed when ranked by number of employees, interview quotas were used to add

more larger firms to the sample. Once the data were compiled, the responses were weighted to

reflect population proportions based on U.S. Census data, yielding a sample of 792 observations.

Exhibit 1 summarizes the demographic characteristics of the sample—industry, sales

growth, business age, employment, owner education, and owner age. For each attribute, we

group responses into three to five categories.

Insert Exhibit 1 here

Exhibit 1 shows 72 percent of the sample firms are in construction, manufacturing, retail,

or wholesale, all industries requiring substantial capital investments. Service industries, where

capital expenditures may have less importance, account for 20 percent of the sample.

The sample is distributed evenly across four real sales growth categories. The high-

growth category is defined as a cumulative (not annualized) increase of 20 percent or more over

the past two years, and includes 24 percent of the sample firms. At the other extreme, 24 percent

of the firms report two-year sales declines of 10 percent or more. This distribution implies that

approximately 75 percent of the sample firms have experienced an average annualized growth

rate of 10 percent or less over the last two years. Thus, many of the capital budgeting decisions

of small firms may be focused more on maintaining current levels of service and quality, rather

than on expansion.

Similarly, the sample is distributed fairly evenly across four business-age categories,

ranging from six years in business or less (23 percent of the sample), to 21 years in business or

more (27 percent of the sample). The number of years in business could influence both the type

of investments a firm will make and the firm’s planning process. For example, firms in business

longer may have more equipment in need of replacement. A business with a limited operating

history may not be able to obtain a bank loan unless it can demonstrate that it has appropriate

planning processes in place.

The median (mean) number of total employees is 4 (9). Sixteen percent of the firms have

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only one employee, and only 18 percent have 10 or more. Thus, it is likely that many sample

firms do not have complete management teams, and may not have adequate staff to fully analyze

capital budgeting alternatives.

The data in Exhibit 1 also suggest that the educational background of owners could influ-

ence how the firm makes capital budgeting decisions. Over 50 percent of the business owners do

not have a four-year college degree, and only 13 percent have an advanced or professional de-

gree. Therefore, many of the small-business owners may have an incomplete (or incorrect) un-

derstanding of how capital budgeting alternatives should be evaluated.

Finally, 63 percent of the business owners are at least 45 years old, and 32 percent are 55

or older. There is some evidence that older managers evaluate capital investments using less so-

phisticated methods (see Graham and Harvey, 2001).

III. Survey Results

We use the NFIB survey to address three questions concerning the capital budgeting ac-

tivities of small firms. We first consider whether the investment and financing activities of small

firms conform to the assumptions underlying capital budgeting theory. Then, we look at the

overall planning activities of small firms (e.g., use of business plans, consideration of tax implica-

tions) and identify firm characteristics that tend to be present when more sophisticated practices

are in place. Finally, we provide evidence about the specific project evaluation techniques small

firms use (e.g., payback period, discounted cash flow methods). We identify significant differ-

ences between the average responses in various subsets of firms and the overall sample averages

using a binomial Z-score. We use multinomial logit to evaluate how the choice of investment

evaluation tools is related to a set of firm characteristics.

A. Investment Activity

Exhibit 2 describes the investment activities of sample firms. It identifies the firms’ most

important type of investment over the previous 12 months, and reports the percentage of firms

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that will delay a potentially profitable investment until the firm has enough internally generated

cash to fund the project.


The most important type of investment is replacement for 46 percent of the sample firms.

Firms in service industries were more likely than the average sample firm to select this response,

and those in construction and manufacturing were less likely. Firms with the highest growth rates

and those in business less than six years were less likely than the average sample firm to report

replacement activity as the primary investment type. Finally, the importance of replacement ac-

tivity increases with the age of the business owner; it is significantly less than the overall sample

mean when the business owner is younger than 44.7

Projects to extend existing product lines are shown as the primary investment activity for

21 percent of the sample firms. Construction and manufacturing firms select this response at a

higher rate than the overall sample average. The remaining subsample averages are not signifi-

cantly different from the overall sample averages (at the 5 percent significance level).

Investments in new product lines are reported as the most frequent investment for 23 per-

cent of the sample firms. Firms in the service industry were less likely than the average sample

firm to select this response. Firms with the highest growth rates were more likely (than the over-

all sample average) to be expanding into new product lines, while those with the lowest growth

rate were less likely. The oldest firms were also less likely than the average firm to be consider-

ing expansion into new product lines.

Exhibit 2 also suggests that many small firms face real (or self-imposed) capital con-

straints. Forty-five percent of the sample firms report they would delay a promising investment

7 The significance of the subsample entries depends on the difference between the subsample mean and the overall sample mean in a given column, and on the number of observations in the subsample (most of these numbers appear in Exhibit 1). Thus, it is possible for two subsamples to have similar response percentages, one significant and the other not. For example, 54 percent of the service firms identify replacement as the primary investment type, while 55 percent of the firms in the “other” industry category select this invest-ment type. This response percentage is significantly different from the overall sample average for service firms, but not for the “other” firms. As shown in Exhibit 1, there are twice as many service industry firms.

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until it could be financed with internally generated funds (wait for cash). Firms most likely to

wait for cash include the youngest firms, the smallest firms, and those whose owner does not

have a college degree. As these firms are likely to face capital market constraints, this result sup-

ports the prediction in Almeida, Campello, and Weisbach (2004) that capital constraints will

make a firm more likely to save cash. Firms with older owners are also slightly more likely to

wait for cash than firms with younger owners.

These results suggest three reasons small firms might not follow the prescriptions of capi-

tal budgeting theory when evaluating projects. First, it is noteworthy that replacement activity is

the most important type of investment for almost half of the sample firms. If replacing old

equipment is necessary for the firm to remain in business, the owner’s capital budgeting decision

is essentially a choice between replacing the machine and staying in business, or closing the busi-

ness and finding employment elsewhere. In this case, maintaining the viability of the firm as a

going concern, rather than maximizing its value, might be the owner’s primary objective.

Second, the results suggest that many small firms place internal limits on the amount they

will borrow. Thus, many small firms cannot (or choose not to) separate investment and financing

decisions, contrary to capital budgeting theory.

Finally, the results suggest that the personal financial planning considerations of business

owners may affect the investment and financing decisions of small firms. In particular, older

owners are more conservative in their strategies than younger owners (older owners focus more

on replacement activity and are more likely to report that they will wait for cash). These results

conflict with an assumption of capital budgeting theory: that the transferability of ownership in-

terests (at low cost) allows managers to separate the planning horizon of a business from the

planning horizon of its owners.

B. Planning Activity

Exhibit 3 analyzes three dimensions of each firm’s planning environment: how frequently

firms estimate cash flows in making capital budgeting decisions; whether they have written busi-

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ness plans; and whether they consider tax implications in making capital budgeting decisions.


Exhibit 3 reports that only 31 percent of the sample firms have a written business plan.

Over 30 percent of the sample firms do not estimate future cash flows when making investment

decisions, and 26 percent of the firms do not consider the tax implications of investment deci-

sions. Thus, many small firms do not have a formal planning system that guides capital budget-

ing decisions.

Firms with the highest growth rates (over 20 percent growth) are more likely to use each

of these planning tools, particularly written business plans and consideration of tax effects. Simi-

larly, firms that extend existing product lines or invest in new lines of business engage in more

planning activities than the average sample firm. As firms expand, they use up more of their bor-

rowing capacity, reducing their future financial flexibility (assuming that they face capital con-

straints). For these firms, it may be essential to plan ahead, so the firm is not forced to pass up

promising opportunities in the future.

Newer firms (less than 6 years old) and younger owners (less than 45 years old) are more

likely than other firms to use written business plans. This is an expected result, given that banks

require evidence of planning before extension of credit to firms with short operating histories.

The smallest firms (three or fewer employees) are less likely to make cash flow projec-

tions, while firms with ten or more employees are more likely to make these estimates. This find-

ing supports conjectures made by Ang (1991) and Keasey and Watson (1993) that personnel con-

straints (incomplete management teams) may hamper small firms in planning.

The planning activities of small firms are also strongly related to the educational back-

ground of the business owner. If the business owner does not have a college degree, the firm is

less likely than the average firm to make cash flow projections or to use written business plans. If

the business owner has an advanced/professional degree, the firm is more likely to engage in such

activities.

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C. Project Evaluation Methods

Exhibit 4 summarizes responses about the primary tool firms use to assess a project’s fi-

nancial viability: payback period, accounting rate of return, discounted cash flow analysis, “gut

feel,” or combination. The most common response is the least sophisticated, gut feel—selected

by 26 percent of the sample firms.8


The use of gut feel is strongly related to the business owner’s educational background.

Owners without a college degree resort to it most frequently, and owners with advanced degrees

least. The use of gut feel is also inversely related to a firm’s use of planning tools. Firms with

written business plans and firms that make cash flow projections are significantly less likely to

rely on gut feel.

While the use of gut feel is concentrated in the least sophisticated of small firms, it is also

widely used by firms that make primarily replacement investments. A firm may have limited op-

tions when it replaces equipment, and estimating future cash flows (i.e., incremental maintenance

costs or efficiency gains) for each option might be difficult. For example, if a firm must replace a

delivery truck, it may be difficult for the firm to estimate differences in the future annual operat-

ing costs of two replacement vehicles under consideration. Moreover, if an investment is neces-

sary for the firm’s survival (and the owner is committed to maintaining the business as a going

concern), the maximization of firm value may not be the business owner’s primary objective.

Instead, the owner may simply look for the alternative promising the required level of perform-

ance at the most reasonable cost. Thus, it is not surprising to find that small business owners use

relatively unsophisticated methods of analysis to evaluate replacement options.

Gut feel is also used extensively by firms in the service industry. Although some service

firms make substantial capital expenditures, the investments of many service firms might be lim-

8 Vos and Vos (2000) report “intuition” as the most frequently used project evaluation technique in a sur-vey of 238 small New Zealand businesses.

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ited to business vehicles or office equipment. Because a firm’s primary considerations when

evaluating this type of purchase decision may be cost, reliability, and product features, structuring

a discounted cash flow analysis of these investments can be difficult.

Payback period is the second most common response, selected by 19 percent of the sam-

ple. The payback period is used slightly more often by firms that will wait for cash, as expected.

Firms using the payback period are significantly more likely than other firms to estimate future

cash flows (because cash flow estimates are required for this calculation). Finally, use of the

payback period appears to increase with the formal education of the business owner.

These results suggest that the payback period conveys important economic information in

at least some circumstances. For example, the payback period can be a rational project evaluation

tool for small firms facing capital constraints (i.e., firms that do not operate in the perfect finan-

cial markets envisioned by capital budgeting theory). In this case, projects that return cash

quickly could benefit a firm by easing future cash flow constraints.

The accounting rate of return is the next most frequent choice, identified by 14 percent of

the firms as their primary evaluation method. The use of accounting rate of return increases with

firms’ growth rates; it is significantly higher than the sample mean for firms entering new lines of

business. Each of these characteristics can indicate high borrowing needs. The accounting rate

of return is thus especially important if a firm must provide banks with periodic financial state-

ments, or is required to comply with loan covenants based on financial statement ratios.

The most theoretically correct method—discounted cash flow analysis—is the primary

investment evaluation method of only 12 percent of the firms. Not surprisingly, owners with ad-

vanced/professional degrees are most likely to use this method; 17 percent of these firms identify

it as their primary evaluation tool. Firms with written business plans and those that consider the

tax implications of investments are also significantly more likely to use discounted cash flow

techniques. Thus, firms using this project evaluation method are among the most sophisticated of

the small firms.

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Firms extending existing product lines are also significantly more likely to use discounted

cash flow analysis. This result is evidence that discounted cash flow analysis is most useful when

evaluating projects with cash flow profiles similar to current operations (such as projects extend-

ing existing product lines), because it is easier to obtain reliable cash flow estimates in this case.

Another noteworthy finding is that 18 percent of the firms in business less than six years

use this method, the most of any age group. Although younger firms are less likely to have com-

plete management teams in place, it is also possible that banks may encourage newer firms to

demonstrate adequate planning (and project evaluation) procedures before qualifying for credit.

Of the specific evaluation techniques firms could choose from, combination of methods

was selected least often, by 11 percent of firms. Use of this approach does not appear to be

strongly related to any of the firm characteristics listed in Exhibit 4.

The results in Exhibit 4 are very different from results in Graham and Harvey (2001).

Approximately 75 percent of their firms evaluate projects using estimates of project net present

value or internal rate of return. The vast majority of their firms also appear to consider multiple

measures of project value in making investment decisions. However, even the smaller firms in

the Graham and Harvey study are much larger than the firms in our sample, and are thus more

likely to have complete management teams. It is therefore not surprising that their firms use

more sophisticated methods of project analysis.

D. Multivariate Analysis

To provide a multivariate perspective on how small firms make investment decisions, we

use multinomial logit to jointly identify factors influencing the choice of a project evaluation tool.

This technique is appropriate when an unordered response, such as a set of project evaluation

tools, has more than two outcomes.

Exhibit 5 reports the results of this exercise; gut feel is the omitted category. Thus, the

coefficients listed in Exhibit 5 should be interpreted as the increase (a positive coefficient) or the

reduction (a negative coefficient) in the log odds between the evaluation tool specified and gut

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feel.


The results show that firms using any of the formal investment evaluation tools are more

likely to make cash flow projections than firms using gut feel. Firms using the accounting rate of

return, discounted cash flow, or a combination of methods are more likely to consider tax impli-

cations when they evaluate projects. These results corroborate the results in Exhibit 4—firms

using gut feel to evaluate projects have much less structured planning environments than other

firms.

Exhibit 5 also identifies factors that differentiate between firms attaching primary impor-

tance to the various investment evaluation tools. The results suggest that capital constraints and

the type of investment (e.g., replacement, expand product line, new product line) can influence

how firms evaluate projects.

The wait for cash coefficient is positive and significant for both payback period and dis-

counted cash flow analysis. These results suggest that firms committed to funding projects inter-

nally are not necessarily irrational or unsophisticated. Instead, the decision to wait for cash might

be an acknowledgment that the firm does not operate in a perfect financial market, and faces capi-

tal constraints. Because the firm knows it may not be able to fund all valuable projects, it will

evaluate projects using the payback period (to help it allocate investment funds over a multiyear

horizon) or discounted cash flow analysis (to help it identify the best projects).

The accounting rate of return is frequently the choice of firms pursuing either growth

strategy: expand product line or new product line. The coefficients for both of these variables are

positive and significant for accounting rate of return. As a firm grows, it may need to raise new

capital, either by obtaining a bank loan or by attracting new equity investors. In either case, the

firm’s historical and projected financial statements will be used to communicate information

about the firm to investors. The accounting rate of return can be valuable to firms pursuing

growth strategies because it provides information about how a project will affect a firm’s finan-

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cial statements (and its ability to meet accounting-based loan covenants).

The importance of discounted cash flow analysis depends on the type of growth the firm

is pursuing. The coefficient for expanding an existing product line is positive and significant for

discounted cash flows, but the coefficient for new product line is not. Firms will use discounted

cash flows to evaluate projects that extend existing product lines because future cash flow esti-

mates can be based on past performance in this case. But, if it is contemplating a new product

line, where obtaining future cash flow estimates can be difficult, the firm is less likely to use a

discounted cash flow method of analysis.

IV. Summary

Firms with fewer than 250 employees analyze potential investments using much

less sophisticated methods than those recommended by capital budgeting theory. In par-

ticular, survey results show these businesses use discounted cash flow analysis less fre-

quently than gut feel, payback period, and accounting rate of return.

Many small-business owners have limited formal education, and their firms may

have incomplete management teams. Therefore, a lack of financial sophistication is an

important reason why the capital budgeting practices of small firms differ so dramatically

from the recommendations of theory. Small staff sizes also constrain the amount of capi-

tal budgeting analyses the firms can perform. Beyond this, there are also substantive rea-

sons a small firm might choose to use methods other than discounted cash flow analysis

to evaluate projects.

The primary reason is that many small businesses do not operate in the perfect

capital markets that capital budgeting theory assumes. Most of the firms in our sample

are very small (with fewer than 10 employees); they have short operating histories (al-

most half have been in business under 10 years), and their owners are not college edu-

17

cated. These characteristics may limit their bank credit, posing credit constraints. If so,

these firms may be required to finance some future investments using internally gener-

ated funds, and it would not be surprising for the owners to consider measures of project

liquidity (such as the payback period) when making investment decisions.

Second, many of the investments that small firms make cannot easily be evaluated

using the discounted cash flow techniques recommended by capital budgeting theory.

Many investments by small firms are not discretionary (a firm either makes a specific in-

vestment or it goes out of business), and future cash flows can be difficult to quantify.

For example, if a firm is introducing a new product line, estimates of future cash flows

can be imprecise (and market research studies required to obtain better cash flow esti-

mates may not be cost effective). When future cash flows cannot be easily estimated,

discounted cash flow analysis may not provide a reliable estimate of a project’s contribu-

tion to firm value, and it is not surprising that a firm might resort to gut feel to analyze

the investment.

For these reasons, small firms face capital budgeting challenges that differ from

those faced by larger firms. Thus, it is possible that optimal capital budgeting methods

for large and small firms may differ. However, a fully integrated capital budgeting the-

ory—identifying the conditions under which discounted cash flow analysis is appropri-

ate—has yet to be developed. The question of how to better tailor the prescriptions of

capital budgeting theory for small firms remains unanswered.

18

References

Almeida, H., M. Campello, and M. Weisbach, 2004, “The Cash Flow Sensitivity of Cash,” Jour-nal of Finance 59 (No. 4, August), 1777–1804.

Ang, J., 1991, “Small Business Uniqueness and the Theory of Financial Management,” The

Journal of Small Business Finance 1 (No. 1), 1–13. Bierman, H., 1993, “Capital Budgeting in 1992: A Survey, ” Financial Management 22 (No. 3,

Autumn), 24. Booth, L., 1996, “Making Capital Budgeting Decisions in Multinational Corporations,” Manage-

rial Finance 22 (No. 1), 3–18. Brealey R. and S. Myers, 2003, Principles of Corporate Finance, New York, McGraw-

Hill/Irwin. Cole, R., 1998. “The Importance of Relationships to the Availability of Credit,” Journal of Bank-

ing and Finance 22 (Nos. 6–8, August) , 959–977. Danielson, M. and J. Scott, 2004. “Bank Loan Availability and Trade Credit Demand,” Financial

Review 39 (No. 4, November), 579–600. Graham J. and C. Harvey, 2001. “The Theory and Practice of Corporate Finance: Evidence from

the Field,” Journal of Financial Economics 60 (Nos. 2–3, May), 187–243. Jorg, P., Loderer, C., Roth, L., 2004, “Shareholder Value Maximization: What Managers Say and

What They Do,” DBW Die Betriebswirtschaft 64 (No. 3), 357–378.

Keasey K. and R. Watson, 1993, Small Firm Management: Ownership, Finance and Perform-ance, Oxford, Blackwell.

Moore J. and A. Reichert, 1983. “An Analysis of the Financial Management Techniques Cur-

rently Employed by Large U.S. Corporations,” Journal of Business Finance and Accounting 10 (No. 4, Winter), 623–645.

Petersen, M. and R. Rajan, 1994. “The Benefits of Firm-Creditor Relationships: Evidence from

Small Business Data,” Journal of Finance 49 (No. 1, March), 3–37. Petersen, M. and R. Rajan, 1995. “The Effect of Credit Market Competition on Lending Relation-

ships,” Quarterly Journal of Economics 60 (No. 2, May), 407–444. Scott, D. Jr., and W. Petty II, 1984. “Capital Budgeting Practices in Large American Firms: A

Retrospective Analysis and Synthesis,” Financial Review 19 (No. 1, March), 111–123. Vos, A. and E. Vos, 2000. “Investment Decision Criteria in Small New Zealand Businesses,”

Small Enterprise Research 8 (No. 1), 44–55.

Exhibit 1Sample Description

No. of Obs % of TotalIndustry

Service 155 20Construction/manufacturing 194 24Retail/wholesale 378 48Other 65 8

Real 2-year sales growth 20 percent or higher 194 2410-19 percent 179 23+/- 10 percent 200 25-10 percent or lower 187 24No answer 32 4

Business age< 6 years 183 236-10 years 173 2211-20 years 213 2721+ years 216 27No answer 7 1

Employment1 127 162-3 233 294-10 287 3610+ 145 18

Owner education levelLess than college degree 415 52College degree 260 33Advanced/prof. degree 105 13No answer 12 2

Owner age< 35 years 81 1035-44 years 194 2445-54 years 244 3155+ years 255 32No answer 18 2

Total 792 100

The weighted distributions of the responses to the National Federation of Independent Business' Reinvesting in the Business Survey conducted by the Gallup Organization.

Exhibit 2Investment Activity

Replace

Expand Existing Product

New Product

Line OtherWait for

CashIndustry

Service 54++ 21 16– – 3 42Construction/manufacturing 30– – 31++ 28+ 1– – 42Retail/wholesale 49 18 24 5 45Other 55 12– 22 9++ 56

Real 2-year sales growth 20 percent or higher 37– – 24 31++ 5 4510-19 percent 52 21 21 3 50+/- 10 percent 50 22 23 3 35-10 percent or lower 47 20 16– – 5 47

Business age< 6 years 38– – 23 26 4 526-10 years 40 27+ 27 2 4411-20 years 51 16– 24 3 3821+ years 51 20 17– – 6 45

Employment1 47 20 20 5 582-3 47 20 21 4 434-10 42 25+ 26 2– 4310+ 48 19 23 5 37

Owner education levelLess than college degree 44 21 23 4 49College degree 45 20 23 4 38Advanced/prof. degree 53 22 23 1 44

Owner age<35 years 33– – 23 29 9++ 4235-44 years 38– – 23 28 4 3845-54 years 49 21 23 1– – 4955+ years 51 20 19 4 47

Total 46 21 23 4 45

Type of Investment Recently Made

Percentage distributions are presented for the question, "Measured in dollars, what was the purpose of the largest share of the investments made in your business in the last 12 months?" The last column presents the percentage of all firms that would delay investments until they could be financed internally with cash. ++ (– –) indicates that the cell percentage is significantly greater than (less than) the column total, at a 5% significance level, and + (–) indicates that the cell percentage is significantly greater than (less than) the column total, at a 10% significance level, using a binomial Z-score.

Exhibit 3

Make CF Projections

Written Business Plan

Taxes Calculated/ Considered

Industry Service 71 34 72Construction/manufacturing 68 32 71Retail/wholesale 70 30 75Other 67 27 83+

Real 2-year sales growth 20 percent or higher 74 38++ 79+

10-19 percent 66 29 75+/- 10 percent 68 28 74-10 percent or lower 70 29 68

Business age< 6 years 80++ 46++ 79+

6-10 years 71 28 7211-20 years 71 28 7221+ years 58– – 23– – 74

Employment1 61– – 35 752-3 64– 24– – 774-10 72 33 7210+ 81++ 36 74

Owner education levelLess than college degree 65– 27– 73College degree 73 35 75Advanced/prof. degree 81++ 38 83++

Owner age<35 years 80 40+ 7335-44 years 73 37+ 7845-54 years 69 34 7355+ years 66 21– – 74

Wait for cash 69 32 77Investment type

Replacement 67 23– – 72Expand existing product 71 37+ 76New product line 74 42++ 80+

Other 81 49+ 83Total 69 31 74

Investment Planning Tools

Planning Tools

Responses are presented to three questions about planning tools used in the evaluation of capital investments. "Make CF Projections" presents the percentage of respondents who said they typically make cash flow projections prior to making a major investment in their business. "Written Business Plan" presents the percentage of respondents who said they had a written business plan projecting the major investments planned over the next few years. "Taxes Calculated/Considered" presents the percentage of respondents who reported they typically calculated or considered the tax implications of a major investment in their business. ++ (– –) indicates that the cell percentage is significantly greater than (less than) the column total, at a 5% significance level, and + (–) indicates that the cell percentage is significantly greater than (less than) the column total, at a 10% significance level, using a binomial Z-score.

Exhibit 4Investment Decision Tools

Payback ARR DCFGut Feel

Combin-ation

Industry Service 18 11 13 33++ 11Construction/manufacturing 19 14 11 22 15+

Retail/wholesale 19 16 13 25 8–

Other 23 6– 9 29 14Real 2-year sales growth

20 percent or higher 15 17 14 26 910-19 percent 26++ 14 11 27 9+/- 10 percent 21 12 11 24 12-10 percent or lower 18 11 14 31 9

Business age< 6 years 21 14 18++ 24 86-10 years 19 10 12 29 911-20 years 17 19++ 13 23 1121+ years 20 11 7– – 28 14

Employment1 22 14 13 25 112-3 20 15 11 25 124-10 16 12 13 28 1010+ 21 16 12 25 9

Owner education levelLess than college degree 18 12 12 29 10College degree 20 18+ 10 23 12Advanced/prof. degree 24 11 17++ 17– – 13

Owner age<35 years 26 10 14 19 1435-44 years 14– – 19++ 18++ 21 1145-54 years 24++ 15 7– – 31+ 1055+ years 16 11 13 27 11

Wait for cash 21 12 15 24 8Investment type

Replacement 20 11 12 31++ 13Expand existing product 20 14 17+ 20– 8New product line 19 20++ 9 23 13Other 21 17 14 14 3

Planning toolsCash flow projection made 23++ 15 14 22– 13Written business plan 19 18+ 16+ 20– – 13Taxes calculated/considered 20 16 14+ 24 12

Total 19 14 12 26 11

Investment Tools

Responses are presented to the question about the investment tools used to assess the financial viability of a major investment in the business. Each of the five responses are reported under Investment Tools. ++ (– –) indicates that the cell percentage is significantly greater than (less than) the column total, at a 5% significance level, and + (–) indicates that the cell percentage is significantly greater than (less than) the column total, at a 10% significance level, using a binomial Z-score.

Exhibit 5Multinomial Logit Results

Coeff Std Err Coeff Std Err Coeff Std Err Coeff Std ErrIndustry

Manufacturing/construction 0.221 0.332 0.512 0.383 0.040 0.399 0.512 0.379Retail/wholesale -0.063 0.287 0.621 0.333 * 0.259 0.334 -0.505 0.362Service/other (omitted)

Real 2-year sales growth 10 percent or higher (omitted)No change (+/- 10 percent) 0.374 0.296 -0.142 0.336 0.347 0.360 0.250 0.35610 percent or lower -0.330 0.305 -0.420 0.338 0.226 0.342 -0.252 0.366

Business ageUnder 6 years (omitted)6-10 years 0.151 0.362 -0.216 0.411 -0.179 0.400 0.349 0.48911-20 years 0.451 0.381 0.924 0.391 ** 0.314 0.403 1.404 0.485 ***

20+ years 0.604 0.384 0.442 0.422 -0.482 0.461 1.671 0.499 ***

EmploymentUnder 4 (omitted)10-Apr -0.666 0.278 ** -0.570 0.310 * -0.346 0.321 -0.838 0.336 **

Over 10 -0.503 0.331 -0.336 0.358 -0.243 0.397 -1.067 0.418 **

Owner education levelCollege (BA or AA) 0.251 0.268 0.299 0.287 -0.206 0.322 0.085 0.327Graduate school 0.915 0.388 ** 0.059 0.461 0.683 0.439 1.104 0.472 **

No college (omitted)Owner age

Under 35 1.367 0.486 *** 0.249 0.578 0.448 0.551 1.712 0.603 ***

35-44 0.448 0.371 0.881 0.374 ** 0.565 0.378 0.803 0.441 *

45-54 0.432 0.296 0.164 0.336 -0.845 0.384 ** 0.089 0.37055 up (omitted)

Wait for cash 0.426 0.241 * -0.084 0.269 0.593 0.280 ** -0.452 0.305Investment type

Replacement (omitted)Expand product line 0.381 0.313 0.640 0.339 * 0.880 0.343 ** -0.018 0.395New product line 0.255 0.305 0.637 0.322 ** 0.031 0.377 0.334 0.361

Planning toolsCash flow projection made 1.297 0.286 *** 0.635 0.296 ** 0.731 0.323 ** 1.157 0.357 ***

Written business plan -0.041 0.275 0.363 0.297 0.422 0.308 0.397 0.322Taxes calculated/considered -0.047 0.274 0.744 0.344 ** 1.020 0.394 *** 0.762 0.388 **

Constant -3.836 1.512 ** -1.849 1.646 -0.461 1.738 -3.402 1.898 *

Mulitnomial logit estimates are presented of the factors that affect the decision tool most frequently used to assess the financial viability of a project. All of the dependent variables are 1/0 variables that take a value of 1 if the method of investment evaluation in each column is reported for large investments. The omitted choice is Gut Feel; thus the significance of the coefficients should be interpreted as the effect on the log odds of the evaluation tool choice relative to Gut Feel. In each case where there is a set of 1/0 variables for the independent variable, the omitted variable is identified and significance should be interpreted relative to this omitted variable. *** indicates significance at the 0.01 level, ** significance at the 0.05 level and * significance at the 0.10 level. The observations included in these estimates are limited to those respondents reporting one of the five investment analysis techniques, which limits the sample size to 583 observations.

CombinationPayback Rate of Return DCF