FRBSF Economic Letter
2004-09; April 9, 2004
Do Differences in Countries' Capital Composition Matter?
CSIP Notes appears
on an occasional basis. It is prepared under the auspices
of the Center for the Study of Innovation and Productivity
within the FRBSF's Economic Research Department.
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There are enormous differences among countries in terms of what
kinds of capital equipment they use. These differences are reflected
in patterns of imports for the most part, since, except for a few
highly advanced, equipment-producing countries, most countries
import the vast majority of their equipment. To see how extreme
the differences between countries' capital composition can be,
consider the example of Ireland and Equatorial Guinea. In 1997,
over one-third of the equipment Ireland imported was in the high-tech
category "Office, Computing, and Accounting Machinery" (OCAM),
while only 3% was in "Fabricated Metal Products" (cutlery,
hand tools, general hardware, etc.). In the same year, over one-third
of the equipment imported by the western African nation of Equatorial
Guinea was fabricated metal products and only 1% was in the OCAM
category.
This Economic Letter explores three questions that arise
in light of such striking differences in the composition of capital
equipment
among countries: (1) Why do these differences exist? (2) Are
the differences in capital composition correlated with differences
in per capita income between countries like Equatorial Guinea
and
Ireland? (3) If so, why do certain types of capital have stronger
positive correlations with income per capita than other types
of capital?
The variation in the composition of capital equipment
imports
For any type of equipment, one can point to pairs of countries
with wildly different import shares, such as those of Ireland
and Equatorial Guinea in relation to imports of OCAM and Fabricated
Metal Products. In fact, analyzing imports data on 165 countries,
Caselli and Wilson (2004) find that, for any type of equipment
one looks at, there is tremendous variation across countries
in
how much that type contributes to total equipment imports (even
after excluding outliers like Ireland and Equatorial Guinea). Caselli
and Wilson and others, have shown that the composition of equipment
imports closely matches the composition of equipment
investment (imports minus exports plus domestic production),
especially for smaller economies. Examining the mix of equipment
imports among
countries then gives a good picture of the differences in
the composition of equipment used in the production processes of
these countries.
In particular, the sizable variation across countries in
the
composition of equipment imports tells us that there is sizable
variation in
the composition of equipment use, which, unlike imports,
is unobserved for a large number of countries.
Why does capital
composition differ so much across countries?
It makes sense to think that businesses and governments around
the world decide on the kinds of capital to use (and in what
proportions to use them) by weighing the costs and benefits
of various possible combinations of equipment types. Clearly,
the
costs and benefits associated with a particular composition
of capital vary from country to country and from business to
business
within a country. For example, Equatorial Guinea presumably
uses proportionately far fewer computers than Ireland by intention.
Part of the reason could be that it costs much more to ship
computers
to businesses in Equatorial Guinea because the country's transportation
infrastructure is less well developed—in fact, Equatorial
Guinea has no paved roads. But this reason doesn't hold up, because
such costs also would affect other types of equipment, such
as
Fabricated Metal Products, which Equatorial Guinea does import.
So we can conclude that, on average, computers provide a lower
net benefit, relative to other types of equipment, in Equatorial
Guinea than they do in Ireland.
In Caselli and Wilson (2004),
the authors construct a formal model of capital composition,
and find that the share of any particular
type of capital in a country's total capital stock is determined
by two factors. The first factor is the capital type's productivity
in that country relative to the productivity of all other types
in that country; for example, in a country like Equatorial Guinea,
which is dominated by agriculture and has a very small professional
services sector, computers will have fewer productive uses than
farm machinery. The second factor is the degree of technical
substitutability between different capital goods; for example,
since farm machinery
and computers are not perfect substitutes (a computer cannot
plow a field) some of both are needed. Of these two factors,
though,
only the first can explain the differences in capital composition
across countries. That is because only the first factor varies
by countries. The second factor—the degree of technical substitutability
between different capital goods—is a universal characteristic
of those capital goods; in other words, no matter what country
we consider, computers still can't plow fields. Therefore, the
cross-country variation in a type of capital's share of total
capital is entirely a result of cross-country variation in the
productivity
of that type of capital relative to other types.
For instance,
in the case of Ireland and Equatorial Guinea, the Caselli-Wilson
model would suggest that Ireland has a higher
share of computers and a lower share of fabricated metal products
than
Equatorial Guinea because in Ireland computers are more productive
than fabricated metal products. In other words, Ireland has
a comparative advantage in using computers, and Equatorial Guinea
has a comparative advantage in using fabricated metal products. This is true,
even
if the absolute productivity of using both types of capital
is higher in Ireland than in Equatorial Guinea.
What are the sources
of such comparative advantages? Caselli and Wilson identify various
country-specific factors, such
as the education
level of the workforce, the kinds of products that the country
specializes in, the enforcement of intellectual property
rights, and the financial and overall levels of development in
the
country. The authors demonstrate that these specific factors
do in fact
explain part of the variation in capital composition across
countries; at the same time, the majority of the variation
is left unexplained,
suggesting that many important factors remain to be identified.
Are
differences in capital composition related to differences in
per capita income?
Per capita income, like capital composition, differs
enormously across nations. For example, according to one measure
used
by the World Bank, in 2001, per capita income in the U.S.
was 65
times
that of Tanzania. The question then arises: Is capital
composition correlated with per capita income? The answer is
yes. Caselli
and Wilson examined data on several broad types of capital
for 118
countries in 1995; for each country, they calculated the
correlation between its per capita income and each capital
type's share
of total capital (as reflected by imports). Figure 1 presents
a
summary of the results. Computers and related equipment
have the highest
correlation with per capita income; professional goods,
electrical equipment, communications equipment, and aircraft
also are
positively correlated. In contrast, non-electrical equipment,
fabricated
metal products, motor vehicles, and other transportation
equipment are
negatively related to income. These correlations between
capital composition and per capita income, together with
the fact that
differences in capital composition are at least as large
as the differences in per capita income, lead to the conclusion
that
capital composition has the potential to explain a large
part
of the variation
in per capita income.
An important caveat, however, is
that we cannot say whether there is a causal link between capital
composition and
income. The
positive correlations may simply reflect the fact that
both capital composition
and per capita income are driven by the same underlying
factors, such as the educational level of the workforce.
Even using
multivariate regression techniques to control for the
effect on income of
education, infrastructure, and other factors that are
correlated with both
income and capital composition may not solve the problem,
as there are likely to be still other such factors that
are unobserved.
Thus, establishing whether there is a causal link from
capital composition to per capita income remains an important
area
for future research.
Why are some capital types more positively related to income
than others? The answer seems to be that some capital types embody
more technology than others. Figure 2 plots the correlation
results
from Figure
1 against a measure of the global research and development (R&D) "intensity" for
each capital type; the R&D intensity is defined as the worldwide
sum of R&D spending on that capital type divided by the worldwide
sales of that capital type. (Note that the measure of R&D intensity
is based on data from R&D and sales only for OECD countries;
however, as other studies have shown, the vast majority of the
R&D and production of capital goods is done in a small number
of advanced OECD countries.) The R&D intensity of a capital
type can be thought of as a proxy for the level of technology embodied
in it.
Clearly, capital types that embody more advanced technology tend
to have a more positive relationship with income per capita. For
example, of our nine broad equipment categories, Professional Goods
(e.g., scientific instruments) ranked second in the amount of worldwide
R&D devoted to the category relative to sales. It also had
the second highest correlation with income per capita. These results
should not be too surprising. In fact, it is perfectly consistent
with the notion that there are spillovers from "producers" of
innovation (in this case, advanced, R&D-performing countries)
to the users of innovations (less advanced, importing countries).
Wilson (2002) showed that the same phenomenon occurs at the industry
level within the U.S.; that is, industries that invest (import)
proportionately more in R&D-intensive capital goods tend to
have higher productivity (income per worker).
Conclusion
The potential causal link from the
composition of capital equipment to income in a country raises
some tantalizing possibilities. If
there is a causal link, the empirical findings discussed in this
Economic Letter suggest that the capital technology generated by
the research efforts of advanced countries and the higher levels
of productivity this technology enables may spill over to countries
in the rest of the world through their capital imports. Moreover,
countries appear to choose the composition of their capital and,
hence, the level of technology embodied in their capital, based
on country-specific factors that may, in turn, determine the productivity
of different technologies in that country. Thus, country-specific
factors like human capital, infrastructure, legal institutions,
financial development, and so forth, which likely have direct effects
on income per capita, also may have an indirect effect by encouraging
investment in those types of capital goods that embody the most
technology. For example, increasing educational levels in a nation
may increase national productivity not only because workers are
more able to perform complex tasks (regardless of the equipment
they have to use), but also because the presence of educated workers
raises the benefits of importing high-tech equipment which enables
higher productivity.
Daniel Wilson
Economist References
[URLs accessed March 2004.]
Caselli, Francesco, and Daniel J. Wilson.
2004. "Importing
Technology." Journal of Monetary Economics 51 (January), pp.
1-32.
Feenstra, Robert C. 2000. "World Trade
Flows, 1980-1997." Mimeo.
http://data.econ.ucdavis.edu/international/pdf/wtf.pdf
Wilson, Daniel
J. 2002. "Is Embodied Technological Change
the Result of Upstream R&D? Industry-Level Evidence." Review
of Economic Dynamics 5(2) (April), pp. 342-362.
http://ideas.repec.org/a/red/issued/v5y2002i2p285-317.html
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