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Tobin’s Q: Valuing Small Capitalization Companies

INTRODUCTION

James Tobin, a professor at Yale University, hypothesized that
the combined market value of all the companies on the stock
market should be about equal to their replacement costs. Tobin
developed a model to illustrate his concept, named it Tobin’s Q
after himself and was awarded the Nobel Prize in Economics for
his trouble. Tobin’s Q measurement is elegant in its simplicity,
and as such has much appeal in investment circles where
investors and analysts continuously seek simple means to explain
complex economic and business relationships.

Tobin’s Q is a perennial topic in business school curricula and
occasionally turns up as a topic of investment newsletters. Yet
the measure is not a common component in securities research and
is not given a high profile in many of the financial services
such as those provided by Bloomberg or Thomson Financial. Some
fans of James Tobin, who passed away in 2002, believe that
today’s investors do not fully appreciate the relevance of his
work, known as Portfolio Selection Theory of which the Q measure
is one part.

While not meant to be exhaustive, we review here the use of
Tobin’s Q as a measure of valuation. We also look at the
application of Tobin’s Q in valuing companies in the small-cap
sector.

TOBIN’S Q DEFINED

Put simply, Tobin’s Q is a measure of performance comparing two
valuations of the same assets. Tobin’s Q is the ratio of the
market value of a firm’s assets as measured by the market value
of its outstanding stock and debt (enterprise value) to the
replacement cost of the firm’s assets. If a company is worth
more than its value based on what it would cost to rebuild it,
then excess profits are being earned. “It is common sense,”
wrote Tobin, “that the incentive to make new capital investments
is high when the securities giving title to their future
earnings can be sold for more than the investment costs.”

Tobin’s Q was quickly adopted by a variety of different fields
within economics, including microeconomics, finance and the
study of investment. Economists took the Q measure an additional
step to “Marginal Q” to illuminate the firm’s investment
decisions, which are made at the margin. The measure gained
prominence in 1990s market boom, when researchers noted that the
overall value of Tobin’s Q looked unreasonably high relative to
historic norms.

In their recent book Valuing Wall Street: Protecting Wealth in
Turbulent Markets Andrew Smithers and Stephen Wright extended
the record of the Q measure back to 1900, covering three
previous secular bull market peaks. They found the value of Q at
the 1960′s peak (1.06) was the lowest of the three, with the
highest (1.35) occurring in 1929. Thus it appears markets tend
to rise significantly above one at major market peaks. The
run-up from 1996 to 2000 found Tobin’s Q approaching 2.0. The
most recent measurement of 0.98 implies a more reasonable
valuation of market conditions.

Indeed, for most of past 100 years, the ratio has been below
1.0, implying that stocks were undervalued. However, after each
of the stock peaks in 1929, 1968 and 2000, the Q has crashed to
around 0.4 and stayed there for a long time. Ratio bottoms
(1920, 1950 and 1982) are spaced around 30 years apart.

HISTORICAL APPLICATIONS

Over the years, economists, investors and market watchers have
used Tobin’s Q for a variety of purposes. For investors it
greatest value has likely been as a timing tool, but its
usefulness in explaining industry structure or characterizing
management should not be overlooked.

Market Timing Tool

In Valuing Wall Street, Smithers and Wright teach investors how
to avoid losing money in the stock market by understanding and
using Tobin’s Q. The book explains that many times throughout
history the stock market has gone through euphoric periods where
stocks are extremely overvalued. By learning and applying the Q
ratio, Smithers and Wright suggest an investor can measure and
track the market and determine when investments are at high risk.

Viewed as a messenger of unwelcome news, Tobin’s Q had fallen
out of favor in the early 1990s, when calculations began
suggesting that U.S. stocks were overvalued. The 2000-2002 bear
market ultimately held up the validity of that call. (1) Thus we
find a number of market advice columns still discussing Tobin’s
Q. Sharelynx Gold, at www.sharelynx.com, features a comparison
of the Dow/Gold Ratio, Average U.S. House/Gold Ratio and Tobin’s
Q. Sharelynx Gold specializes in charts and focuses on designing
and developing precious metal indices, indicators and technical
analysis for evaluating the gold sector.

A variation of the market timing tool comes from market maven
Jeremy Grantham, who uses Tobin’s Q as a guide for long-term
asset allocation. In the January 2005 issue of his quarterly
newsletter entitled GMO, Grantham discusses market cycles and
admonishes investors that the anticipated market low following
the 2000 bubble has not net fully played out. For the short-term
Grantham uses current market valuation along with the January
Effect and the Presidential Cycle. For the long-term Grantham
makes allocation decisions based on a slow, steady regression to
the mean, which is loosely based on normalized profit margins
and valuations.

Merger and Acquisitions

Analyzing mergers and acquisitions is another of the more
valuable of uses for Tobin’s Q. The Q model relates investment
to the firm’s stock market valuation, which is meant to reflect
the present discounted value of expected future profits. Under
certain assumptions about the firm’s technology and competitive
environment, the ratio of the stock market value of the firm to
its replacement cost (Tobin’s Q) should be a sufficient
incentive for investment by the company.

Industry Research

Tobin’s Q has also proven valuable in analyzing certain
industries. Indeed, researchers have found a distinct
relationship between Q measures and industry market structure.
Market structure consists of those factors that are supposed to
determine the competitiveness of an industry, affecting market
performance through the conduct or behavior of firms (pricing,
advertising, entry deterrence).

Firms with high Q ratios tend to have unique products and
factors of production while firms with low Q ratios are
typically relatively competitive or tightly regulated
industries. An economist, Michael Salinger found Tobin’s Q a
better measure of monopoly profits than indices of single-period
profitability because it measures long-run monopoly power. For
example, empirical tests of the relationship between Tobin’s Q
and measures of market structure and unionization provide
evidence that unions do capture monopoly rents in the U.S.
economy. (4)

LIMITATIONS

Despite its appeal to researchers, educators and portfolio
managers, Tobin’s Q has detractors. Tobin’s insight was based on
the view that the market value of installed capital summarizes
the incentive to invest. Recent research on measurement error
suggests that the Q measure may not be correctly calculated if
there are “bubbles” in stock market valuations that are
persistent over time and that are correlated with fundamental
value. (6) Although Tobin’s Q is typically correlated with
investment in empirical studies, researchers have found that the
relationship is sometimes weak and often dominated by the direct
effect of cash flow on investment. (7)

Findings for U.S. data suggest that much, if not all, of the
significance of cash-flow variables in conventional estimates of
Tobin’s Q investment equations can be attributed to the failure
of Tobin’s Q to capture all relevant information about expected
profitability of current investment of cash flows. Economists at
Northwestern University concluded that Tobin’s Q is too
forward-looking relative to the investment decision. The
excessively forward-looking information in Tobin’s Q predicts
future adoptions of “frontier” technology and in this way is a
better predictor of long-run investment than of short-run
investment. By contrast cash flow reflects only current
technology and demand. Thus short-run investment is better
predicted by the firm’s cash flow. (8)

Furthermore, the volatility of firms’ market value greatly
exceeds the volatility of the fundamentals that they supposedly
summarize. Economists at Wharton School of the University of
Pennsylvania and the Kellogg School of Management at
Northwestern University demonstrated that models based on growth
options can address this situation as well as that of cash
effects. (9) They argue the presence of growth options, such as
an upgrade in technology, causes fluctuation in firm valuation
that are not match by current variation in cash flows.

Another major sticking point is related to measurement. For Q to
be meaningful, it is necessary to accurately measure both the
market value and replacement cost of a firm’s assets. It is
usually possible to get an accurate estimate for market value of
a firm’s asset by summing the values of the outstanding
securities of that company. It is an entirely different task to
estimate the replacement costs of those assets since the balance
sheet reflects historical value not replacement value and
ignores some intangibles altogether.

For example, a trio of researchers recently demonstrated that
information technology (IT) assets contribute to a firm’s
performance potential and, if included in the calculation, have
a significantly positive association with Tobin’s Q value. (10)
The bulk of valuation work has relied exclusively on
accounting-based measure of firm performance, which largely
ignore IT’s contribution to performance dimensions such as
strategic flexibility and intangible value. In a study that used
data from 1988-1993, the inclusion of the IT expenditure
variable in the Tobin’s Q model significantly increased the
variance explained in Q.

Researchers have developed numerous methods for computing Q, and
several studies have found that choice of method can affect
statistical and economic inference substantially. Although
sophisticated algorithms to compute the components of Tobin’s Q
from accounting data can add to measurement quality, all such
efforts still leave a substantial part of the variation in any
proxy for Q unexplained. The measurement error problem with
Tobin’s Q must stem from issues such as aggregation and
unobservable assets.

PRACTICAL APPLICATIONS IN THE SMALL-CAP SECTOR

In the preceding section, we cited measurement error as one of
the weaknesses in Tobin’s Q since it is based on accounting
values that fail to acknowledge current values of historic
assets or the contribution of intangibles to creating value in a
company. It is reasonable to think that net worth underestimates
the true value of a business, and the Q might be “reading high”
in today’s economy. Some make adjustments to the calculation by
taking the book value of a company, adding back accumulated
depreciation, and making appropriate adjustments for price
changes in different classes of assets from the time of
purchase. According to Michael Alexander, author of a newsletter
entitled “Stock Cycles,” an alternative is a valuation model
based on Price to Resources (as measured by retained earnings)
serves to incorporate the intangible element.

While these procedures neutralize some of the difficulties, we
take the view that the weakness in Tobin’s Q in its traditional
form could be its strength as a valuation measure for companies
in the small-cap sector.

Indeed, the small-cap company is often in an early stage of
development when cash flows from the sale of its products for
services have not yet materialized. Furthermore, new businesses
are more likely to be based on intellectual capital as it has
become the preeminent resource for creating economic wealth.
(12) Tangible assets such as property, plant and equipment
continue to be important factors in the production of both goods
and services. However, their relative importance has decreased
through time as the importance of intangible knowledge-based
assets has increased. (13)

Methodologies that link intangible value to accounting measures
of performance, such as return on investment, capture only
tangible value components, with little consideration for
intangible worth. Though these measures may have worked well for
typical industrial-age companies, they don’t work for new
knowledge-based companies, where intellectual processes and
services are the primary value drivers. Because of the
substantial learning curve associated with the uses of
intellectual property, such investments often take years to add
value to a company and are more likely to be reflected in future
profit streams. (13)

So how does an investor assess the value of such things as
information systems, brand names, trade secrets, production
processes, distribution channels, and work-related competencies?

We advocate turning Tobin’s Q on its head and using its
imperfection as the basis for analysis. Since Tobin’s Q compares
a company’s market value to the replacement value of its
physical assets, for those companies wherein the ratio of market
value over book value (Tobin’s Q) is significantly greater than
one, the measure implies the “intangible value” in brands,
reputation, knowledge or innovativeness that business analysts
and shareholders are aware of and value.

The difference between market value and replacement value is the
implied value of the intangibles. The next step is to evaluate
whether that measure is reasonable (fair valuation) or
unreasonable (overvalued or undervalued). The analyst is called
to determine from what elements the intangible value arises. Is
it a matter of patent ownership, brand name, or first-mover
status? What are the implied cash flow streams? Is the market
opportunity large enough for the company to capture the sales
that would generate such cash flows? Is the company’s operating
structure efficient or bloated and a drain on sales? Does the
company have a reasonable system to get its product to the
end-user? CONCLUSION

It is clear that Tobin’s Q is valuable in predicting the
likelihood of market appreciation or decline, takeover activity
or the rate of future capital expenditures. We also see merits
for using Tobin’s Q for company-specific research as a reality
check on valuation in the small-cap sector, where the
“irrational exuberance” cited by Federal Research Chairman
Greenspan is often rampant. The analysis we advocate using
Tobin’s Q could be measured or simply observed. Either way, we
believe the process could bring structure and integrity to the
valuation of small capitalization companies.

About the Author

Debra Fiakas, CFA is a seasoned, credentialed investment
professional with a diversified and successful track record as a
research analyst and as an investment banker. Her decade-plus
career includes solid experience in all aspects of the equity
capital markets with particular emphasis on emerging growth
companies operating in the technology sectors. Ms. Fiakas is
also the principal member of Crystal Equity Research, LLC.

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