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Explaining Tranquility in the Midst of Turbulence:

U.S. Multinationals' Intrafirm Trade, 1966-1997

Subramanian Rangan, INSEAD

Working Paper 336

January 2001

 

The views expressed are those of the author and do not necessarily reflect the policies of the U.S. Bureau of Labor

Statistics or the views of other staff members. This paper was part of the U.S. Bureau of Labor Statistics Conference on

Issues in Measuring Price Change and Consumption in Washington, DC, June 2000.
Explaining Tranquility in the Midst of Turbulence:

U.S. Multinationals’ Intrafirm Trade, 1966-1997

Subramanian Rangan

INSEAD

Bd de Constance

Fontainebleau

France 77305

Email: subramanian.rangan@insead.fr

Tel: 33-1-60.72.43.14

(Paper prepared for the Bureau of Labor Statistics June 5, 2000 conference)

_________________________

I thank Bill Alterman, Catherine Mann, Illian Mihov, Paolo Fulghieri, Robert Lawrence, Raymond

Mataloni, Jeffrey Reuer, Lorraine Eden, Christoph Loch, William Zeile, and Matthew Krepps for helpful 

comments.
2

U.S. international (export and import) prices enter into the calculations of the U.S. GDP 

deflator and the U.S. inflation index. Over the past couple of decades, as the

international sector of the U.S. economy has shot up in relative importance, concern for

the correctness of those international prices has grown too (see Alterman, 1997). Correct 

measurement of international prices is, however, a challenging task made more

complicated by multinational firms’ intrafirm transfer pricing. Considerable research has

been devoted to understanding multinational transfer pricing (see Eden, 2000). By

comparison, however, relatively little has gone into understanding the very driver of the

multinational transfer pricing issue, viz., multinational intrafirm trade. It is, hence, this

latter topic that I want to take up in this paper.

In particular, focusing on one important portion of U.S. intrafirm trade, viz., U.S. 

manufacturing multinationals’ intrafirm exports, I want to address three questions. First,

over the past three or four decades, have U.S. manufacturing multinationals’ intrafirm

exports become more important or less important in total U.S. manufacturing exports? In 

other words, is the complication winding itself up or down? Even among informed

observers, views on the question are split. Some, noting the staggering rise in foreign

direct investment, a growing trend among U.S. firms to multinationalize, and the growth

in intra-industry trade, speculate that over these last decades the relative share of

intrafirm trade must have trended up (and perhaps even sharply so). Others, pointing to 

the tremendous pressures and opportunities for “outsourcing” that U.S. firms have

experienced over this time period, argue that, even in international exchange, arm’s

length transactions must, on balance, have displaced internal ones. As a result, these

latter observers speculate, the relative importance of intrafirm trade must have declined
3

(and perhaps even sharply so). In reality, as I show below, over the thirty years spanning 

1966-1997 (which includes the earliest and the latest year for which relevant data are

currently available), the share of U.S. multinationals’ intrafirm exports in total U.S.

manufacturing exports has remained remarkably stable at around 28 percent (see also

Zeile, 1997).

This brings me to the second question. Considering that the views sketched above 

are not unfounded, how, in the midst of the multinationalization and marketization

turbulence implied in those views, can we explain the relative tranquility in the U.S.

intrafirm export ratio? To put it more simply, what explains the observed pattern in U.S. 

intrafirm exports? Existing theory, an offshoot of transaction cost economics, highlights

failures and inefficiencies in arm’s length trade in intangibles (see the section on

intrafirm trade in Casson, 1990; Caves, 1996). For the most part, though, that theory is 

oriented at the cross-sectional level (i.e., it aims to explain cross-industry variation in

propensity to trade intrafirm), and it does not purport to explain patterns over time. In an 

attempt to do so, I draw upon both relevant micro-level developments (such as advances 

in information technology and the rise in import competition) and attendant shifts in

strategies of U.S. multinationals, and advance some new hypotheses on the drivers of

intrafirm trade.

I then explore those hypotheses with a dataset that I constructed for the purpose. 

To be clear upfront, I should note that the data are far from ideal. For instance, while the 

hypotheses are oriented at the level of the firm, the data are at the industry level. (Firm

level data on most of the relevant variables are simply unavailable.) Further, the set of

firms that underlie these data is mostly but not strictly fixed over the time period studied. 
4

Likewise, in the case of certain industries that are dominated by a few large firms(e.g.,

tobacco), the relevant data are, for confidentiality reasons, suppressed. Those pieces of

data are, hence, missing. Lastly, while the hypotheses developed below are meant to be 

applicable to intrafirm trade in general, the empirical analysis undertaken here is limited

to only one portion, viz., U.S. parents’ exports. I am unable to include intrafirm exports 

of foreign parents due to a lack of data on key independent variables relating to those 

foreign parents. I will nevertheless make some brief remarks about trends in their role in

U.S. intrafirm exports. (Zeile, 1997, and Mataloni, 1999 provide excellent overviews of

the recent data on the import side and on the U.S. operations of foreign parents.)

Despite the limitations mentioned above, it is interesting and, likely, instructive,

to pursue the empirical exploration. As I explain below, for the purpose at hand, industry 

aggregation is not a serious drawback. (In fact, all previous empirical studies of intrafirm

trade have been conducted at the industry level.) Importantly, previous studies have

tended to be cross-sectional rather than longitudinal, and, certainly, none spans such a

long time period as the 30-year period covered here. That, combined with the fact that 

previous studies have not considered the role of factors such as technology advances and 

import competition, makes it likely that the empirical analysis contemplated will shed

new light and help improve our understanding of the phenomenon of multinational

intrafirm trade.

On that assumption, I take up a third question: Looking to the future, what

projections can we make about the relative magnitude of intrafirm trade in total U.S.

trade? To anticipate, let me just say that the analysis below suggests that relative share of 

intrafirm trade is unlikely to decline in the near future. Indeed, the vigilance that the
5

Bureau of Labor Statistics is exhibiting on this issue is warranted, and, pending a

resolution on questions regarding price measurement methodology, should be

maintained.

To recap, focusing on U.S. manufacturing multinationals’ exports, I will first

establish how the share of intrafirm trade has moved over the 30 year period between

1966-1997. I will then attempt, with the aid of some new hypotheses and a novel dataset, 

to empirically explain those past movements. I will conclude with remarks about the

likely future direction that this ratio will take, and offer some comments for the BLS

international price index program.

Intrafirm Shares in U.S. Manufacturing Exports, 1966-97

Figure 1 contains two panels showing movements in U.S. non-fuel manufacturing exports 

between 1966 and 1997. (Note, in both panels, the x-axis runs 1966, 1977, 1982, 

1983,...,1997. Also, henceforth, manufacturing refers to non-fuel manufacturing, and

exports refers to manufacturing exports.) Returning to Figure 1, the panel on the left

shows that between 1966 and 1997 U.S. manufacturing multinationals’ (intrafirm and

total) exports have more or less tracked total U.S. manufacturing exports.

The panel on the right in Figure 1 shows trends in three ratios. These ratios

indicate the relative importance of U.S. multinationals and their intrafirm trade in U.S.

manufacturing exports. Among the three, the key ratio for our purpose is the percentage 

share in total U.S. manufacturing exports that is accounted for by U.S. parent’s intrafirm

exports. This share is depicted by the dotted line that runs lowest in the right-hand panel. 

Its striking characteristic is the stability, between 25 and 30 percent, that it exhibits over 
6

such a long period. The actual (and industry-disaggregated) figures behind this pattern

are presented in the first set of columns in Table 1. 

As for the other two ratios plotted in the right-hand side panel in Figure 1, the 

solid line at the top depicts U.S. manufacturing multinationals’ total share in U.S.

manufacturing exports. Note, that share includes U.S. parents’ arm’s length exports as

well. Glancing at Table 1, we can see that from its high of 70 percent in 1977, that total 

share has been declining steadily, and, in 1997, it stood at 57 percent. Finally, the dashed 

line in the middle of the right-hand side panel in Figure 1 depicts the intrafirm share in

U.S. parents’ total exports. As can be seen from the chart, and more clearly from the 

figures in Table 1, this share has been rising gradually over the last two decades and now 

stands at nearly 50 percent (49.6 to use the exact figure in Table 1).

It should be easy to see that the dotted line (i.e., intrafirm share in total U.S. trade) 

is simply the product of the solid line (i.e., multinational share in total U.S. trade)

multiplied into the dashed line (i.e., intrafirm share in total multinational trade). We thus 

have at least a mechanical explanation for the relative flatness of U.S. parents’ intrafirm

share in total U.S. exports: the multinational share in total U.S. trade has been declining

but the intrafirm share in multinational trade has been rising. The behavior of U.S. firms 

that participate in the economy’s international sector has apparently been subject to some 

real but opposing influences. For that reason, those shifts don’t stand out in a summary

indicator such as intrafirm trade in total U.S. trade.

Before delving into those opposing influences, let me refer to Table 2, which

contains some summary data on U.S. multinationals and their foreign operations. The

figures in this table suggest that, measured in terms of the number of U.S. parents and
7

foreign affiliates, multinationalization has been growing. Also, as indicated by the foreign

employment share in U.S. parents’ total employment, the relative importance of their

foreign operations has grown, rising from 21 percent in 1966 to 36 percent in 1997. As I 

will show below, this latter development has had a significant effect on U.S. intrafirm

trade.

To round out the overall picture on U.S. manufacturing exports (and also give a

glimpse of the role of foreign multinationals) I tabulate some other data in Table 3. 

There first notice that over the past twenty years as foreign multinationals have

established manufacturing operations in the United States, their total and intrafirm

exports as a share of U.S. exports have risen sharply (going from 3.8 and 1.5 percent

respectively in 1977 to 11.4 and 5.9 percent in 1997). The trend is similar for foreign

parents’ U.S. affiliates that are engaged in wholesale trade. Thus, in 1997, one-sixth of 

U.S. exports were accounted for by the U. S. affiliates of foreign parents. If the intrafirm 

exports of these foreign parents are added to the intrafirm exports of U.S. parents, then, 

as shown in the last row of the table, the “total” intrafirm share in U.S. manufacturing

exports has trended up from an estimated 32 percent in 1977 to 39 percent in 1997.

Over the same period, the share of U.S. exports accounted for by purely domestic 

enterprises has nearly doubled (rising from 12 to 22 percent). The relative displacement 

has been absorbed in U.S. parents’ share in total U.S. exports. In round numbers, U.S. 

manufacturing and wholesale parents’ shares in U.S. exports have declined from 70 and 

11 percent respectively in 1977, to 57 and 5 percent in 1997. In total, therefore, there has 

been a displacement of nearly 20 percentage points.
8

Having reviewed these longitudinal patterns in U.S. multinational and intrafirm

trade, I will now turn to explanations of those patterns. My primary focus will, of course, 

be on explaining intrafirm trade and its evolution.

Explaining Intrafirm Trade

In terms of theory, as noted at the outset, the existing literature has addressed itself

mainly to cross-industry variations in intrafirm trade. In particular, that literature has

emphasized two factors. First, research (or R&D) intensity has been advanced as a key 

explanator. The argument is that in research-intensive industries firms are less able to

rely on arm’s length markets. Those markets are not congenial for transacting intangible 

(research) inputs and outputs. On the other hand, the internal mode, though likely more 

costly, is better-suited to mitigating certain serious downside risks (e.g., the

misappropriation of proprietary knowledge). Hence, firms in R&D intensive sectors are

more likely to internalize their exchange transactions (see Caves, 1996).

This preceding transaction costs-industrial organization logic has been coupled

with the trade aspect of international business to explain the propensity of firms to engage 

in intrafirm cross-border trade. With few exceptions (see, for example, Benvignati,

1990), the R&D-intensity perspective has found broad empirical support (see Lall, 1978; 

Buckley and Pearce, 1979; Helleiner and Lavergne, 1979; Sleuwagen, 1985; Kobrin,

1991).

A second factor that is mentioned in explanations of intrafirm trade is the role of

plant-level scale economies. Where the benefits of plant-level scale economies outweigh

costs of transport, firms are more likely to centralize operations and distribute
9

intermediate or finished goods (see Brainard, 1997). In empirical studies, however, the

scale variable has not always performed as expected (see Helleiner and Lavergne, 1979; 

Benvignati, 1990; Kobrin, 1991). Researchers have suggested that weak results on this

variable reflect the difficulty in correctly measuring and operationalizing scale

economies.1

Beyond the R&D and scale factors highlighted in the cross-section-focused 

literature, I want to advance two other sets of factors as potential explanators of the

evolution of intrafirm trade. Consider first a variable that I will refer to as multinational 

intensity. In simple terms, this variable is a measure of the relative magnitude and depth

of firms’ foreign operations. Firms set up operations in a foreign country when the

volume of anticipated sales in the local or regional market grows large enough to justify

the extra costs involved. The establishment of foreign operations tends, over time, to 

have two important influences on trade.

One, as firms grow their foreign presence, i.e., as they increase their multinational

intensity, they grow too their ability to penetrate local and regional market. The volume 

of business they conduct with existing foreign customers grows; they acquire new foreign

customers; and, importantly, they become more likely to introduce second and

subsequent product lines into the market. As a consequence, other things equal, as

multinational intensity rises, the share of multinational trade in total trade between home 

and abroad should tend to rise as well.

Two, as firms deepen their operations abroad, it becomes optimal to source more 

inputs locally. Of course, not all inputs can be sourced locally. There will likely remain 

 

1 While R&D and scale factors have received most attention in the existing literature, certain other factors, 

such as advertising intensity and locational factors, have also been mentioned in the literature (see the 
10

certain proprietary or scale-sensitive inputs that firms will want to continue to source

non-locally (typically, from home). Trade in these inputs is, however, more likely to be 

conducted intrafirm than at arm’s length. What is more, once an affiliate is established

abroad, it may act as an “inducement to indulge in transfer-price manipulations” (Lall,

1978: 216), and trade between home and abroad is more likely to be channeled via the 

affiliate. For these reasons, other things equal, as the intensity of foreign operations 

rises, parents’ trade between home and abroad will tend to become more intrafirm.2

Another relatively recent development that is likely to push up intrafirm trade

shares is something I will refer to as multinational horizontal specialization. In

horizontal specialization, multinational firms allocate worldwide or at least regional

responsibility for the production of certain intermediates and finished products to

operations in specific countries (see Yi, 2000). Thus product A might be made (for world 

supply) in country X, while product B might be made in country Z (again, for world

supply). This manner of within-firm cross-geographic specialization is reported (at least

anecdotally) to have risen in the last couple of decades. The trend is being driven, it is 

thought, by such factors as increasing competition (and the attendant pressures for greater 

efficiency), the rising impact of exchange rate changes (and the quest by firms for a

structural hedge), and increasingly common regional content requirements. Regardless,

other things equal, an increase in multinational horizontal specialization is likely to be 

accompanied by an increase in the internalization of trade. After all, the workability and 

 

studies mentioned in Caves, 1996: 32-33).

2

To be clear, although the preceding hypotheses have not received explicit attention or much empirical 

scrutiny in the commonly cited studies of intrafirm trade, they are not entirely novel either. In fact, 

referring to studies by Swedenborg (1979) and others, Caves (1996: 33) has written, “The heavy 

participation of foreign subsidiaries in trade the and the complementarity of interaffiliate trade with their 

local production (and sales) activities is well established.”
11

net benefits of such a strategy must call for greater intrafirm coordination. The latter is

more likely to be achieved when trade flows are intrafirm.

To recap, higher levels of multinational intensity should lead to both a higher

share of intrafirm trade and a higher multinational share in total U.S. trade. Higher levels 

of horizontal specialization should lead to higher intrafirm share in multinational trade. 

The view that, over the last three decades, the levels of multinational intensity and

horizontal specialization have trended up is not very controversial. (Data reviewed in

Table 2 and some to be reviewed below support this view.) In fact, it is these sorts of

trends that adherents of the “multinationalization” school focus on, and, on the basis of

which they conjecture that intrafirm trade has trended up.

Adherents of the “marketization” school, meanwhile, focus on forces that push

down the share of intrafirm trade. I will discuss two important forces that fall in this

category. First and foremost is the technology of coordinating economic exchange. I

will simply refer to this as technology. The argument is as follows: as the relative cost of 

conducting arm’s length exchange declines, firms’ relative reliance on arm’s exchange

should rise (see Lawrence, 1995). Equally, if not more importantly, as the relative

benefits of coordinating across arm’s length catch up with the benefits of internal

coordination, firms’ relative reliance on arm’s exchange should rise. Accordingly, other

things equal, as the benefit-cost ratio of coordination-enabling technology rises,

multinational intrafirm trade shares should decline.

Further, advances in this technology should enable economic exchange that would 

otherwise call for either special organizational complements (such as those offered by the 

multinational form) or minimum size or both. In other words, as this technology
12

advances, purely domestic firms should be able to and should engage more and more in

international trade. Therefore, other things equal, as the benefit-cost ratio of

coordination-enabling technology rises, the multinational share in total U.S. trade should 

decline. 

3

In reality there is some empirical and considerable anecdotal evidence (not only in

the electronics and the computer industry, but also in apparel and the auto sector) that

over these past decades firms are increasingly embracing vertical specialization and

relying more on “outsourcing” (see, Lawrence, 1995; Magretta, 1998). Prime among the 

forces that go into explaining this trend is the advance of microprocessor (and the related 

communication, computing, and storage technologies that they drive). Accordingly, in

the empirical exercise below, I will rely on crude estimates of trends over time in the

benefit-cost ratio of computer microprocessors.

The second force highlighted by the “marketization” school is a rise in

competition. As firms confront greater product (and financial) market competition, they

tend to divest “non-core” businesses, rely more on outsourcing, and return to their “core 

competencies.” Hence, for reasons similar to those discussed above, other things equal, 

the greater the competition, the greater should be the role of arm’s length trade and the 

lesser the role of intrafirm trade.

 

3

To illustrate the technology hypothesis, I will provide a simple hypothetical example. Induced by 

technology, a multinational firm spins-off some of its operations into a separate firm. The two firms, 

subsequently, maintain their export behavior. Imagine firm A used to export 10 units, 5 of them intrafirm. 

Assume the division it spun-off accounted for 3 of the exported units (all of which used to be exported 

intrafirm). After the spin-off, the two smaller units still export 7 and 3 units respectively. But the

multinational now has an intrafirm ratio of only 2/7 (as opposed to 5/10). The smaller unit (which now, 

say, is not a multinational) continues to export 3 units. Under such a scenario, we would have more 

exporters, which is consistent with the facts. We would also see both a decline in the multinational share in 

U.S. exports, and a decline in the intrafirm share of multinational exports.
13

Empirical Analysis of Intrafirm Export Shares in U.S. Manufacturing, 1966-97

Dataset

To explore the preceding hypotheses, I constructed a panel dataset that included (i)

estimates of the three multinational and intrafirm U.S. export ratios plotted in the righthand panel in Figure 1, and (ii) indicators of the independent variables discussed above. 

Most of the data come from three sources: the U.S. Census Bureau, the U.S. Bureau of

Economic Analysis, and the OECD. The data items and data sources are listed in

Appendix 1.

In terms of coverage, the panel contains dependent and independent variables for 

the years 1966, 1977, 1982, 1987, 1992, and 1997. The years 1966 and 1997 are the 

earliest and latest years for which data on the dependent variable are available. Further, 

except for 1997, the other years are ones in which the BEA conducted benchmark

(population-level) surveys of U.S. parents’ foreign operations. Last, but not least, the fact 

that the years are spaced wide apart should help mitigate problems of serial 

autocorrelation.

Sector focus, as noted at the outset, is limited to manufacturing (which, as a

sector, still dominates the U.S. trade picture). Within manufacturing, the data are

disaggregated at the 2-digit SIC-level. That is the level of detail at which the BEA

tabulates most of its data on U.S. multinationals and their foreign operations. The same 

reason (BEA detail of reporting) guides the choice of the seventeen two-digit industries 

included in the analysis.4 Together, the six time periods—1966, 1977, 1982, 1989, 1994, 

1997—and seventeen 2-digit industries give a maximum of 102 observations.

 

4

 The seventeen 2-digit industries covered are: food and beverages; chemicals and drugs; primary metals; 

fabricated metals; machinery; electrical and electronic equipment; motor vehicles; other transport (mainly 
14

Each observation aggregates, for a given period and industry, relevant data for the 

subset of firms (all U.S. multinationals or all U.S. firms) that underlie that sector. It is, 

thus, possible (though, given the variables in question, not very probable) that such

aggregation masks wide variations in the behavior of individual firms within a given

sector. The ideal would be to obtain firm level data, but these are simply not publicly

available (and that too for this long a time period). Fortunately, since there is no reason

to believe that such masking systematically affects particular sectors or time periods, one 

should still be able to glean useful insights from the empirical exercise.

Variables

Table 4 lists and describes the dependent and independent variables. The primary

dependent variable in the analysis is PIFUSX. This variable indicates U.S.

manufacturing multinationals’ intrafirm exports as a percentage of U.S. manufacturing

exports. There are two secondary dependent variables. PXUSX indicates U.S.

multinationals’ total exports as a percentage of U.S. exports. PIFXPX indicates U.S.

multinationals’ intrafirm exports as a percentage of their own total exports.5 Table 4

describes the independent variables so I will not repeat here.6 That table also shows the 

bivariate correlations among the variables. At 0.97, the bivariate correlation between

 

aircraft); textile products and apparel; lumber, wood, and furniture; paper and allied products; printing and 

publishing; rubber products; miscellaneous plastics; glass products; stone, clay, and nonmetallic mineral 

products; and instruments and related products. Tobacco products, shown in Tables 1 and 2, is excluded in 

the analysis due to erratic data.

5

 Just to clarify, in these dependent variable labels, the P stands for U.S. parents (i.e., U.S. multinationals); 

IF stands for intrafirm; X stands for exports; US stands for United States. These capitalized letters are 

combined to indicate the ratio under consideration.

6

Except I want to point out that it is in order to circumvent exchange rate and inflation issues that I use 

employee counts rather than (the more conventional) foreign assets or sales figures to measure the 

multinational intensity variable (PMNEINT).
15

TIME (a time trend) and the variable labeled TECH is the highest. Not surprisingly,

TIME is also highly correlated with U.S. GDP and import competition.

Empirical Estimation

For the purposes of empirical estimation, I employ a fixed effects panel model. This

choice is motivated by three reasons, all in keeping with the econometrics literature on

panel data (see Hsiao, 1985; and Baltagi, 1995). First, the data cover the “population”

(rather than a random sample) of U.S.-based manufacturing multinationals. Second,

inferences are to be made only for that population. Third, there are certain relatively

stable “effects” that vary across industry but that are not explicitly included in the model. 

These include the relative importance of transport costs, advertising intensity, and the

feasibility of (or susceptibility to) outsourcing. Due to differences in the “modularity” of

intermediates, outsourcing is more feasible in certain industries (such as autos and

electronics) than in others (such as chemicals and metals). This modularity factor is hard 

to measure but likely important. Industry dummies should help pick up such effects. (In

any case, simple OLS results are presented as well.)

I should also add that although the data span a thirty-year period, the stability in 

the subset of firms that drive the values of the variables is likely to be quite high. This is 

because that subset is composed of the large U.S. multinationals that have long populated 

the Fortune 500 lists. Also, because compliance with the BEA survey is mandated by the 

U.S. government, self-selection is not an issue. Accordingly, the empirical design is not 

subject to some of the classic limitations associated with panel data (see Baltagi, 1995: 6-

7).
16

The equations to be estimated are variants of the following:7

Intrafirm Share in U.S. Exportsit = ai + b *R & D/Salesit + g *Multinational Intensity it

+d *Multinational Horizontal Specialization it + e * Import Competitionit

+z *Technologyit + h * Scaleit +q *Timet+ i

it .

Results

Consider first the results shown in Table 5. The dependent variable there is PIFUSX, i.e., 

U.S. parent’s intrafirm exports as percent of total U.S. exports. As column 1 shows, two 

of the key variables of interest, PMNEINT, i.e., multinational intensity, and TECH, i.e., 

advances in coordination-enabling technology, both perform as hypothesized. The

coefficient on the former is positive and exhibits the highest t-stat, and the coefficient on

the latter is negative and takes the second highest t-stat. On the other hand, the third 

variable of interest, IMPCOMP (the competition variable), is statistically significant but

takes a positive and not, as hypothesized, a negative sign.

Before discussing that puzzling but interesting result, I want to briefly review the 

other two models in Table 5. The model in column 2 includes TIME (in place of TECH) 

and its results are virtually unchanged from those in column 1. Given the near perfect

correlation between TIME and TECH, that finding is not surprising. The results

presented in column 3 are the simple OLS results. There too, the signs and significance 

of the key variables remain unchanged.

As for the other variables, R&D/Sales does not take significance in the first two 

models in this table, but does so in the third model, which does not include the industry

 

7 Readers wondering why regular trade variables such as income and exchange rates are not included are 
17

dummies. That would suggest that the latter are picking up the R&D factor. The SCALE 

variable perform as expected in the first two models, but not in the simple OLS model. 

There is not much to say about the industry dummies except to note that the ones that 

took statistically significant coefficients do appear to be the advertising or modularity

intensive industries such as chemicals (which includes pharma and toiletries) ,

machinery, and autos.8

Let me now return to the competition variable IMPCOMP. Recall, greater

competition, it was argued, would be associated with greater focus on core businesses

and greater outsourcing (and arm’s length trade). But, at least as far as these empirical

results go, it appears that the first response is what dominates here and what leads to

higher intrafirm trade. The explanation would go as follows. In response to competition, 

multinational parents divest non-core businesses and refocus on core businesses and

operations. Now, parents’ propensity to engage in intrafirm trade is likely to be higher in 

core than in non-core business. Accordingly, as competition rises (and as the core to

non-core business ratio rises), the multinational intrafirm trade share rises too. If this is 

the chain of causation, then IMPCOMP should also take a positive and significant

coefficient in the model where PIFXPX, intrafirm share in parents total exports, is the

dependent variable. (I will turn to that dependent variable momentarily.) 

But another logic might also help explain the positive relationship between the

share of multinational intrafirm trade and IMPCOMP. Perhaps multinationals are better

placed to survive the onslaught of import competition. Hence, an increase in import

competition could lead to a larger share for intrafirm trade in total not (only) because of

 

reminded that the dependent variables are all share variables.
18

refocus on the core and an attendant rise in intrafirm shares, but because the multinational

to non-multinational ratio rose. To the extent this is a part of the story, we would expect 

IMPCOMP to take a significant and positive sign in the model where PXUSX,

multinational exports in total U.S. exports, is the dependent variable.

Before moving on to that model, let me summarize by saying that the results in

table 5 strongly support the view that both the forces of multinationalization and the

forces of marketization have been at work, and, as hypothesized, they influence intrafirm

in expected but opposing directions. This, it would seem, is what explains the tranquility 

in the U.S. intrafirm export ratio that is observed even in the midst of the turbulence

unleashed by the forces of technology and globalization. I will say more about this in the 

concluding discussion.

Turn now to Table 6, which presents the results of the regressions explaining

PXUSX, U.S. multinationals’ exports as a share of total U.S. exports.9 The results in

Table 6 are entirely consistent with those in Table 5. Again, as shown in column 1,

multinational intensity (which has risen as more firms have multinationalized, and as

firms have multinationalized more) pushes up, as hypothesized, the multinational share in

total U.S. exports. TECH takes a negative and statistically significant coefficient. That is, 

coordination-enabling technology pushes down, as hypothesized, the multinational share

in total U.S. exports. It is interesting to note that the coefficient on the TIME

trend(shown in column 2), while positive, takes only borderline statistical significance. 

 

8

 If data on advertising intensity were available for the industries and years covered, that variable could be 

entered separately.

9

The independent variables used in the models in Table 6 are virtually the same as those in the previous 

table. MNEHSP, the horizontal specialization variable is not relevant here and is not used; and the 

R&D/Sales ratio is for all U.S. firms in an industry (and not just for U.S. multinationals as was the case in 

Table 5).
19

While one should not read too much into this, that result would appear to strengthen the 

TECH story.

Surprisingly, IMPCOMP does not take significance in any of the models in Table 

6. That is, increases in the level of import competition do not lead to increases in the

share of U.S. exports accounted for by U.S. multinationals. Thus, the survivor bias

explanation is not supported in these data. Of course, this means that the import

competition variable must work via PIFXPX, U.S. multinationals’ intrafirm exports as a

share of U.S. multinationals’ total exports.

Table 7 shows the results of the models where PIFXPX is the dependent variable. 

And, indeed, IMPCOMP is positive and statistically significant here. Given that the other 

independent variables control for technology (or a time trend) and multinational intensity, 

this result is consistent with the hypothesis that multinational parents responded to import 

competition by cutting to core businesses. In turn, their propensity to trade intrafirm

rises.

A second interesting finding in Table 7 is that TECH continues to be negative and 

significant. That is, TECH not only reduced multinationals’ share in total U.S. trade, it

also reduced the intrafirm share in multinationals’ own trade. This lends further support

to the marketization (or vertical specialization) view. Also, PMNEHSP, the horizontal

specialization variable shows signs of life in this table (see column 3). In the raw data

(not shown) it is clear that horizontal specialization (i.e., affiliate-affiliate trade) is

trending up, and the results here give at least some support for the view that that

development is pushing up, as one would expect, multinationals’ propensity to internalize

cross-border trade. Lastly, it is noteworthy that in this table the R&D variable takes
20

significance even in models that include the industry dummies. Perhaps this is not

surprising, because the theoretical reasoning around R&D-intensity is really strongest for

the dependent variable in this table (as compared to those in the two previous ones).10

Alternative Explanations

As with most empirical patterns, here too there are several possible alternative

explanations and I want to address three in particular. The first one relates to the mix of 

industries over this thirty year period. Could it be that over the 1966-1997 period the 

composition of sub-industries in U.S. manufacturing exports has become less R&D

intensive? The answer is no. First, R&D is a control variable in the models estimated 

above. Second, even at the level of the overall manufacturing sector, U.S. exports come 

more not less from R&D-intensive industries. The same is true for the intrafirm exports 

made by U.S. multinationals.

Another alternative explanation relates to country mix issues. Could it be that the 

reason TECH is significant is that it is highly correlated with TIME, which itself is

significant and negative because it is correlated with a rise in the share of U.S. exports

destined for developing countries? Due to factors such as political instability and

smaller size of foreign markets, multinational trade with developing countries tends to be

more likely to take place at arm’s length. This country mix variable, however, cannot

 

10 The results in Table 7 are also less exposed to a drawback in the dataset that relates to industry 

classification. The BEA provides multinational and affiliate trade data by industry of parent (and that is the 

classification used in the paper). The Census Bureau reports trade data by product. The extent of the 

overlap is no doubt high, but it is far from complete. In Table 7, since both the numerator and the 

denominator in the dependent variable come from the BEA, the industry classification problem is 

mitigated.
21

explain why multinationals’ share in U.S. exports has declined. The technology story can 

explain that key pattern.11

A third alternative explanation for the tranquility in intrafirm trade shares is

related to the role of inward foreign direct investment. The story is simply that the reason 

U.S. multinational share in U.S. exports have declined is not because of technology and 

such, but rather because foreign firms operating in the United States now account for a

big portion of U.S. exports. While that is certainly true, this does not explain why

IMPCOMP does not come out negative and significant in the models (in Table 6) where 

U.S. multinationals share is the dependent variable. It also does not explain why

technology takes a negative sign in models (in Table 7) where intrafirm share in U.S.

multinationals exports is the dependent variable. Lastly, as we saw in Table 3, the

biggest jump in U.S. exporters comes from the “other U.S. entities” category (which

excludes both U.S. and foreign multinationals).

Thus, these alternative explanations (nor the others that I have considered), can

readily refute the hypotheses and interpretation offered above. 

Discussion 

If we abstract up a level, we can see what the preceding empirical results really suggest. 

Over the past two or three decades, three exogenous forces have been influencing the

scope of U.S. multinationals. Shifts in the scope, in turn, get reflected in the relative

share of trade that is conducted intrafirm. I will elaborate briefly.

There are three dimensions to the scope of the firm. Vertical scope refers to the 

extent of internalization of activities in a given business. As outsourcing rises and the

 

11 Product by country data needed to empirically sort out this alternative explanation is not available.
22

firm engages in fewer activities, vertical scope declines. Horizontal scope refers to the 

number and diversity of businesses that the firm is engaged in. As the tendency rises to 

divest non-core businesses and refocus on core businesses, firms’ horizontal scope

declines. Geographic scope refers to number and diversity of countries that firms operate 

in. As more firms expand to more countries abroad, their geographic scope rises.

Advances in coordination-enabling technology have led U.S. multinationals to

decrease their vertical scope and outsource more. In turn, their need and propensity to 

internalize trade has declined. Hence, increases in TECH were associated with decreases 

in multinational and intrafirm trade. On the other hand, the increase in competition has

led U.S. multinationals to decrease their horizontal scope and refocus on core businesses. 

In turn, U.S. multinationals’ propensity to internalize trade has increased. Hence,

increases in IMPCOMP were associated with increases (rather than decreases in)

intrafirm trade. Lastly, liberalization and economic growth abroad have led U.S.

multinationals to increase their geographic scope and expand abroad. In turn, their 

overall share of U.S. international trade has risen and their opportunity and propensity to 

internalize international trade has risen. Hence, increases in MNEINT were associated

with increases in multinational and intrafirm trade.

The influence of the preceding contemporaneous developments have, at least at

the level of the overall manufacturing sector, been roughly equal and opposing. It is as a 

result that the share of intrafirm trade in total U.S. trade has appeared relatively stable

over the past three decades.

Taking stylistic liberty, I depict in Figure 2 the above described pattern of

evolution in the scope of U.S. multinational firms. As can be seen in that figure, the
23

emerging pattern resembles a “cone.” To be clear, real confirmation of such a pattern

will have to await further empirical work (preferably with firm-level data). Still, the

considerable anecdotal evidence that is available is not at odds with the spirit of Figure 2.

Conclusion

Reminding readers that this study has only scratched the empirical surface of the

intrafirm trade issue, let me turn to the question: Looking forward, what are the likely

prospects for intrafirm trade? To address this question, I would like to refer back to the 

“exogenous” drivers. I will discuss technology first, and then globalization and

competition.

Clearly, in the wake of the internet and the virtual industrial marketplaces being

established on its back, one must believe that firms are likely to further reduce their

vertical scope in the foreseeable future. After all, the technology of the internet could

make the benefits of arm’s length coordination rise even as its costs fall. Again,

anecdotal evidence indicates that outsourcing is likely to be intensified in the internet

economy.12 A point that is implicit here is that as arm’s length trade grows more and 

better coordinated, the operational and managerial distinction between “arm’s length”

and “intrafirm” is likely to diminish. One would have to refer to “strictly” arm’s length

trade versus the regular kind where information and interests between buyer and seller

are somewhat aligned. All in all, the internet could pick up where the microprocessor 

left off and it could continue to power the TECH variable and its effects on intrafirm

trade.

 

12 CISCO, the famous router manufacturer, apparently has 35 factories making its products, of which it 

owns only four.
24

On the other hand, there are a set of equally important (but slightly more

complicated) reasons why intrafirm trade could trend up. First, foreign parents are

multinationalizing with unprecedented enthusiasm and many of them are entering the

United States. This increase in the number of foreign multinationals with affiliates in the

United States is likely to push up U.S. intrafirm trade. We saw indirect evidence for this 

in Table 1. But consider Figure 3, which plots intrafirm trade intensity against foreign 

presence intensity. The relationship is striking. If a firm has an affiliate in country A,

then chances are high that its trade with country A will be internalized. (The benefits for 

doing so are many and some of them lead to the doorstep of the transfer pricing issue.) 

The preceding pattern must explain why research-intensive firms do any arm’s

length trade at all. Their arm’s length trade must be concentrated with countries where

they do not yet have affiliates. The intrafirm trade ratios in foreign affiliate-U.S. parent 

shown in Table 8 lend strong support to this hypothesis. Looking down the last column

of that table one would hardly be able to distinguish between high and low R&D

industries. Essentially, when a parent has an affiliate abroad and that affiliate trades with 

the parent’s home country, then the trade gets internalized.

But what drives the likelihood of establishing a foreign affiliate? The size of the

local, national, or regional market. And therein lies the second point. As foreign

markets grow, U.S. parents will be more likely to establish affiliates abroad. As that

happens, U.S. parents’ intrafirm trade propensity is going to rise. Accordingly, the

establishment of U.S. affiliates by foreign parents and of foreign affiliates by U.S. parents 

is going to keep powering PMNEINT, which, in turn, is going to keep pushing up

intrafirm trade shares.
25

The upshot is that technology and multinationalization are again likely to be

pushing intrafirm trade shares in opposite directions. Another way to guess the likely

direction of intrafirm share in total U.S. exports is look at the two underlying patterns:

multinational share in total and the intrafirm share in multinational trade. As we saw

above, the share of MNE trade in total U.S. trade has been trending down. If that trend 

accelerates, then even if intrafirm share in MNE trade rises, the net figure may go down. 

Yet, multinationals simply cannot be counted out. Rising trade, especially in

manufactures of a high-tech or high-touch nature leads to multinationalization. Likewise, 

inward foreign direct investment often provokes outward foreign direct investment; and

so on. What is more, the share of intrafirm trade in multinationals’ total trade has,

despite improvements in technology (and reduced transactions costs), been trending up. 

Increased multinationalization, increased horizontal specialization, and a return to core

competencies all appear to have “caused” this outcome.

Accordingly, if the decline in multinationals’ total share of U.S. trade reverses

itself (a probable but not certain development) , we could see intrafirm shares in total

U.S. trade rising (and perhaps sharply). But, over the near future (say over the next five 

years), one cannot rule out (and one must rule in) the continuation of the pattern of the 

last thirty years.

Implications for the BLS International Price Index

Based on this paper’s data and analysis, I have three brief comments for the BLS

International Price program:
26

(i) The special attention that the department has paid to the intrafirm trade and transfer

pricing issue is warranted and should be maintained. While the share of intrafirm trade

has declined in a few industries, it has, in general, not subsided over the past three

decades. In fact, if the U.S. operations of foreign multinationals are taken into account, 

the share of intrafirm trade has grown. The pattern not only appears set to continue into 

the future, it may even be that the share of intrafirm trade rises further. The transfer

pricing complication is, in other words, not about to wind itself down.

(ii) Since multinational firms themselves engage in both intrafirm and arm’s length trade

(and since the two sets of prices are often different in levels and changes in levels), it

might be useful, even for deflation purposes, to collect and use the two sets of prices on

two different sets of trade values. If only intrafirm or only arm’s length prices are used to 

deflate all exports, then trade volumes might be incorrectly estimated. Of course, the

burden on participating firms will be higher, and the Bureau will, no doubt have to come 

up with ways(such as internet reporting) to ease the burden.

(iii) Setting aside the question of legal and financial feasibility, I would suggest surveying 

final customers, at least in selected foreign markets. Even if done on a narrow basis, this 

could be valuable not only as a check on what is reported domestically, but also from the 

point of view of researchers that use the international price index for studies relating to 

U.S. firm’s foreign pricing practices. 
27

Appendix 1

Data Sources

Item

U.S. manufacturing exports

U.S. parents’ intrafirm exports

U.S. parents’ total exports

U.S. industry R&D as a percentage of current 

output

U.S. parents’ R&D as a percentage of sales

U.S. parents’ foreign and total employment

Affiliate-to-affiliate trade share in U.S.

majority-owned foreign affiliates’ sales

Imports, exports, and production in U.S.

industry

GDP in U.S. industry (in constant dollars)

Computing power (millions of instructions per 

second) per dollar

Plant scale (employees per establishment) in 

U.S. industry

Data Source

U.S. Bureau of the Census, Statistical Abstract of the 

United States, various issues.

U.S. Bureau of Economic Analysis, United States Direct 

Investment Abroad, various issues.

U.S. Bureau of Economic Analysis, United States Direct 

Investment Abroad, various issues.

OECD, Research and Development in Industry, various 

issues. Also (for 1966) Statistical Abstract of the United 

States: 1971; and (for 1997) National Science

Foundation/ Division of Science Resource Studies,

Survey of Industrial Research: 1997.

U.S. Bureau of Economic Analysis, United States Direct 

Investment Abroad, various issues.

U.S. Bureau of Economic Analysis, United States Direct 

Investment Abroad, various issues.

U.S. Bureau of Economic Analysis, United States Direct 

Investment Abroad, various issues.

OECD, The OECD STAN Database for Industrial

Analysis, various issues.

OECD, The OECD STAN Database for Industrial

Analysis, various issues. Also (for 1966) Statistical 

Abstract of the United States: 1971; and U.S. BEA/ 

Industry Economics Division, 1947-1997, GDP in

current dollars.

Estimated from Decision Resources, Inc., Spectrum. 

Frederic G. Withington, “The resurgence of the

mainframe computer,” March, 1997, 93: 1-11.

U.S. Bureau of the Census, Statistical Abstract of the 

United States, various issues. Also, (for 1992) Census of 

Manufactures: 1992; and (for 1997) Economic Census, 

1997.
28

References

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Benvignati, Anita, 1990. “Industry determinants and ‘differences’ in U.S. intrafirm and

arms-length exports.” The Review of Economics and Statistics, August (3): 481-488.

Brainard, S. Lael, 1997. “An empirical assessment of the proximity-concentration tradeoff between multinational sales and trade.” The American Economic Review, 87(4): 520-

544.

Buckley, Peter J. and R. D. Pearce, 1979. “Overseas production and exporting by the 

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Casson, Mark (ed.), 1990. Multinational corporations. Hants: Edward Elgar Publishing.

Caves, Richard E., 1996. Multinational enterprises and economic analysis, Cambridge: 

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29

Eden, Lorraine, 2000. “International intrafirm trade, transfer pricing and the BLS

international price program.” Paper prepared for the Bureau of Labor Statistics,

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Helleiner, Gerald K. and Real Lavergne, 1979. “Intra-firm trade and industrial exports to 

the United States.” Oxford Bulletin of Economics and Statistics, 41 (November): 297-

311.

Hsiao, Cheng, 1985. Analysis of panel data. Cambridge: Cambridge University Press.

Kobrin, Stephen, 1991. “An empirical analysis of the determinants of global integration.” 

Strategic Management Journal, 12: 17-31.

Lall, Sanjaya, 1978. “The pattern of intra-firm exports by U.S. multinationals.” Oxford 

Bulletin of Economics and Statistics, 40 (August): 209-222.

Lawrence, Robert Z., 1995. Single world, divided nations? Washington, D.C.:

Brookings Institution Press.

Magretta, Joan, 1998. “Fast, global, and entrepreneurial: Supply chain management,

Hong Kong style. An interview with Victor Fung,” Harvard Business Review, 

September-October: 103-114.
30

Mataloni, Raymond, Jr., 1999. “U.S. multinational companies: Operations in 1997.” 

Survey of Current Business, 79 (July): 8-35.

Sleuwagen, L, 1985. “Monopolistic advantages and the international operations of firms:

Disaggregated evidence from U.S.-based multinationals.” Journal of International

Business Studies, 16 (Fall): 125-133.

Swedenborg, Briggita, 1979. The multinational operations of Swedish firms: An analysis 

of determinants and effects. Stockholm: Industrial Institute for Economic and Social

Research.

Yi, Kei-Mu, 2000. “Can vertical specialization explain the growth of world trade?”

Federal Reserve Bank of New York, Staff Reports, No. 96, January.

Zeile, William, 1997. “U.S. intrafirm trade in goods.” Survey of Current Business, 

77(February): 23-38.
Figure 1. Intrafirm and total share of U.S. multinational parents' exports in total U.S. non-coal, non-petroleum exports, 1966-97

(X-axis scale--the time line--is not continuous)

Index of the nominal value of U.S. exports U.S. parents' intrafirm exports

(1966 = 100) (1966 = 100)

- - - Intrafirm exports of U.S. parents in manufacturing - - - Intrafirm share in total U.S. (non-fuel) manufacturing exports

-- -- Total exports of U.S. parents in manufacturing -- -- Intrafirm share in manufacturing parents' total U.S. exports

----- Total U.S. (non-fuel) manufacturing exports ----- Manufacturing parents' total share in U.S. (non-fuel) manufacturing exports

Source: U.S. Department of Commerce, Statistical Abstract of the United States , various issues; U.S. Direct Investment Abroad , various issues.

100

600

1,100

1,600

2,100

2,600

3,100

3,600

1966 1982 1984 1986 1988 1990 1992 1994 1996

0%

20%

40%

60%

80%

100%

1966 1982 1984 1986 1988 1990 1992 1994 1996
Figure 2. Gross patterns and drivers in the evolution of the scope of U.S. multinational firms 

Vertical

Scope

Horizontal

Scope

Geographic

Scope

Technology

Competition

Liberalization and

economic development

abroad
Figure 3. U.S. parents’ foreign presence and their share of goods exports that is intrafirm, selected countries, 1994.

 Presence = Proportion of mfg. parents with affiliates in country

PROPORTION OF U.S. PARENTS WITH PRESENCE IN THE COUNTRY

INTRAFIRM PROPORTION
Table 1. U.S. manufacturing parents' intrafirm and total exports as a percentage of U.S. manufacturing exports, 1966-97

 U.S. manufacturing parents' intrafirm exports U.S. manufacturing parents' total exports U.S. manufacturing parents' intrafirm exports

Industry as a % of total U.S. manufacturing exports* as a % of total U.S. manufacturing exports* as a % of total U.S. manufacturing parents' exports

1966 1977 1982 1989 1994 1997 1966 1977 1982 1989 1994 1997 1966 1977 1982 1989 1994 1997

Manufacturing 24.5 28.5 24.7 28.8 28.2 28.4 62.8 70.4 64.9 63.0 59.2 57.2 39.0 40.5 38.1 45.6 47.6 49.6

Food and kindred products 7.3 7.3 6.8 9.9 16.3 18.8 24.5 36.9 35.1 64.8 84.8 67.6 29.9 19.7 19.5 15.3 19.2 27.8

Chemicals and allied products 28.5 38.4 30.4 34.6 37.0 34.1 69.0 85.9 80.2 70.8 72.6 60.9 41.3 44.7 37.8 48.8 50.9 56.0

Primary metals products 6.8 21.8 11.3 9.8 6.9 4.5 50.9 95.4 79.8 38.1 34.7 22.2 13.3 22.8 14.2 25.6 19.9 20.1

Fabricated metal products 37.3 9.6 8.7 8.3 9.5 9.3 99.0 33.0 35.9 35.5 25.3 31.4 37.7 29.1 24.1 23.4 37.3 29.6

Industrial machinery and equipment 19.6 24.6 25.3 41.3 37.4 34.6 49.1 58.0 49.8 58.4 57.8 53.3 40.0 42.3 50.9 70.7 64.7 64.8

Electronic and other electric equipment 23.1 29.8 28.7 23.0 24.5 34.0 70.4 87.3 89.5 63.2 56.5 70.0 32.8 34.1 32.1 36.4 43.3 48.6

Motor vehicles and equipment 68.5 66.6 71.6 89.4 70.9 76.7 127.5 92.1 94.9 113.3 91.2 99.3 53.7 72.3 75.5 78.9 77.7 77.3

Other transport (including aircraft) 10.4 9.0 6.3 6.1 5.9 4.3 60.5 130.0 96.7 85.5 82.7 80.2 17.2 6.9 6.5 7.1 7.1 5.3

Tobacco products 17.4 33.8 15.9 4.6 n/a n/a 148.2 173.2 164.1 45.6 n/a n/a 11.7 19.5 9.7 10.2 n/a n/a

Textile products and apparel 4.1 8.0 3.8 4.9 3.4 2.0 13.9 27.7 18.8 16.7 11.5 10.9 29.4 28.8 20.0 29.3 29.6 18.4

Lumber, wood, furniture, and fixtures 3.2 3.6 2.8 2.5 7.0 9.5 8.7 44.6 41.0 48.1 23.7 27.0 36.8 8.0 6.9 5.2 29.7 35.0

Paper and allied products 22.7 22.4 7.0 10.5 24.2 20.6 73.7 57.9 50.5 61.1 87.8 73.0 30.8 38.7 13.8 17.2 27.6 28.2

Printing and publishing 11.3 18.0 9.4 9.4 7.2 7.3 35.3 41.2 28.0 20.6 17.1 19.3 32.0 43.8 33.4 45.4 42.4 37.9

Rubber products n/a 46.3 34.5 23.7 26.1 22.1 n/a 115.0 76.3 47.8 57.5 35.7 49.0 40.3 45.2 49.6 45.4 61.7

Miscellaneous plastics products 20.8 5.7 2.7 12.8 5.9 3.3 55.5 19.2 9.3 30.8 22.9 12.7 37.6 29.7 29.2 41.5 25.9 26.2

Glass products 20.4 13.7 16.2 12.8 7.9 26.1 50.7 56.4 50.2 55.8 53.3 73.3 40.1 24.2 32.3 23.0 14.9 35.6

Stone, clay, and nonmetallic mineral products 31.4 21.1 22.1 17.5 19.2 7.1 68.1 72.7 58.9 40.7 48.6 24.0 46.1 29.0 37.6 43.1 39.5 29.6

Instruments and related products 31.3 43.8 43.3 34.7 30.2 22.4 81.6 67.8 65.6 68.8 50.4 40.2 38.3 64.6 66.0 50.5 59.9 55.7

Source: U.S. export figures are from U.S. Department of Commerce, Statistical Abstract of the United States, various issues; multinational export figures are from 

U.S. Department of Commerce, U.S. Direct Investment Abroad, various issues.

*The U.S. Commerce Department classifies multinational export data by industry of U.S. parent and U.S. export figures by product. This, in some cases, leads to 

estimates of intrafirm shares that are greater than 100 percent of the total.

n/a not available; figures in italics are author's estimates.
35

Table 2. Number of U.S. parents and their foreign affiliates, and foreign employment of U.S. parents in manufacturing, 1966-97

 Foreign employment

Industry Number of U.S. parents* Number of foreign affiliates* Foreign employment (in 000s) in parents' total employment

1966 1977 1989 1997 1966 1977 1989 1997 1966 1977 1989 1997 1966 1977 1989 1997

Manufacturing 936 1,289 1,312 1,501 n/a #### ##### ##### 2,988 5,323 4,490 4,929 21% 31% 31% 36%

Food and kindred products 61 78 63 69 n/a 1,252 1,083 1,097 264 484 496 601 20% 32% 30% 45%

Chemicals and allied products 121 136 173 205 n/a 2,447 3,065 3,330 394 747 724 770 34% 38% 37% 44%

Primary metals products n/a 53 55 65 n/a 552 364 323 92 285 129 117 8% 22% 27% 29%

Fabricated metal products n/a 141 108 123 n/a 529 478 654 178 173 95 158 29% 26% 22% 33%

Industrial machinery and equipment n/a 226 253 260 n/a 1,717 2,075 2,480 409 763 714 786 19% 28% 36% 42%

Electronic and other electric equipment n/a 156 161 209 n/a 1,089 1,298 1,663 472 659 465 639 27% 34% 30% 35%

Motor vehicles and equipment 46 33 50 52 n/a 475 518 802 496 844 776 725 29% 38% 43% 45%

Other transport (including aircraft) n/a 25 31 27 n/a 327 499 467 39 239 208 189 4% 20% 16% 20%

Tobacco products n/a 6 10 6 n/a 111 274 243 9 77 124 71 7% 44% 45% 63%

Textile products and apparel n/a 63 52 53 n/a 385 177 176 85 157 56 68 11% 19% 15% 19%

Lumber, wood, furniture, and fixtures n/a 35 26 35 n/a 108 115 193 69 55 44 85 23% 17% 17% 24%

Paper and allied products n/a 38 40 54 n/a 272 392 541 104 164 162 210 23% 32% 30% 33%

Printing and publishing n/a 46 44 51 n/a 209 233 281 21 47 50 47 8% 16% 12% 13%

Rubber products n/a 19 14 20 n/a 211 126 148 97 233 107 85 34% 44% 45% 37%

Miscellaneous plastics products n/a 26 41 54 n/a 115 243 230 22 16 43 34 27% 20% 29% 25%

Glass products n/a 8 9 13 n/a 103 54 119 42 70 38 66 32% 39% 27% 38%

Stone, clay, and nonmetallic mineral products n/a 23 20 21 n/a 225 109 85 48 80 39 23 28% 40% 31% 25%

Instruments and related products n/a 97 118 126 n/a 659 842 1,030 117 181 202 223 28% 30% 24% 30%

Source: U.S. Department of Commerce, U.S. Direct Investment Abroad , various issues.

*Figures for number of U.S. parents and foreign affiliates in 1966 and 1977 are author's estimates. Estimates are made from the available data and the assumption that 50 and 70% of the parents

and affiliates would have met the $3 million cutoff that is in use starting in 1982. The cutoff prior to 1982 was $500,000.

n/a not available; figures in italics are estimates.
Table 3. Intrafirm shares in U.S. non-coal, non-petroleum manufacturing exports accounted for by 

U.S. and foreign multinational enterprises, 1966-97

Non-coal, non-petroleum U.S. manufacturing 

exports (in millions of current dollars) 

Percentage shares 

 Total

 Shipped by U.S. parents in manufacturing 

 To their majority-owned foreign affiliates 

 Shipped by U.S. parents in wholesale trade 

 To their majority-owned foreign affiliates 

 Shipped by U.S. manufacturing affiliates of 

 foreign parents 

 To their parents and affiliates 

 Shipped by U.S. wholesale trade affiliates of 

 foreign parents 

 To their parents and affiliates 

 Shipped by other U.S. entities 

Total intrafirm share in non-coal, nonpetroleum U.S. manufacturing exports*

Source: Author’s estimates based on data from U.S. Department of Commerce, Statistical Abstract of

the United States , various issues; U.S. Direct Investment Abroad , various issues; Foreign Direct

Investment in the U.S., various issues. 

n/a = not available. 

* The total intrafirm share figure for 1966 is an underestimate since it excludes foreign parents’

exports; the true figure is likely to be slightly higher (around 27 or 28 percent). On the other hand, the

total intrafirm share figures for 1989 and 1997 are likely to be overestimates. The latter double count

some U.S. exports by U.S. parents that are themselves U.S. affiliates of foreign parents.

1997

22,088 

100.0

62.8 

24.5 

6.5 

0.9 

n/a 

n/a 

n/a 

n/a 

n/a 

25.4

1966 1977 1989

Figures are in percent unless stated otherwise

Year

93,544 

100.0

70.4 

27.5 

10.8 

0.7 

3.8 

1.5 

3.1

1.9 

11.9

31.6

272,260 

100.0

62.8 

29.0 

5.8 

0.6 

11.7

4.9 

6.8

4.6 

12.8

39.1

589,208 

100.0

57.2 

28.2 

4.7 

1.0 

11.4 

5.9 

5.3

3.5 

21.3 

38.6
Table 4. Descriptive statistics and zero-order correlations for variables related to U.S. intrafirm exports in manufacturing, 1966-97

Variable name and description

Num. 

of obs.

Mean Variable

(s.d.)

PIFXUSX U.S. parents’ intrafirm exports 

as a percentage of total U.S. exports 

PXUSX U.S. parents’ total exports 

as a percentage of total U.S. exports 

PIFXPX U.S. parents’ intrafirm exports 

as a percentage of U.S. parents’ total exports 

PRDSALE U.S. parents’ R&D as a percentage 

of sales 

USRDSALE U.S. industry R&D as a 

percentage of current output 

PMNEINT U.S. parents’ foreign employment 

as a percentage of their total employment 

PMNEHSP Affiliate-affiliate trade share in 

U.S. majority-owned foreign affiliates’ sales 

IMPCOMP Imports as a percentage of 

apparent consumption in U.S. industry 

OUTPUT Log of GDP in U.S. industry (in 

constant dollars) 

TECH Computing power per dollar [inverse of 

log(price/millions of instructions per second)] 

SCALE Plant scale in U.S. industry 

[log((employees/establishment) 2)] 

TIME [1966 = 1, 1977 = 12, ..., 1997 = 32]

2 3 4 5 6

1. 

2. 

3. 

4. 

5. 

6. 

7. 

8. 

9. 

10. 

11. 

12.

0.67 

1.00

-0.04 

-0.17 

0.07 

0.09 

-0.00 

0.24 

0.36 

0.57 

0.61 

0.97 

-0.15 

1.00

0.82 

0.21 

1.00

0.50 

0.47 

0.45 

1.00

0.66 

0.46 

0.56 

0.36 

0.00 

1.00

0.20 

0.50 

0.03 

0.69 

1.00

0.53 

0.17 

0.60 

0.52 

0.15 

0.53 

1.00

0.39 

0.09 

0.41 

0.35 

0.19 

0.37 

0.66 

1.00

0.17 

-0.06 

0.31 

0.33 

0.16 

0.28 

0.46 

0.49 

1.00

-0.05 

-0.17 

0.07 

0.10 

0.00 

0.25 

0.35 

0.56 

0.57 

1.00

0.39 

0.64 

0.04 

0.38 

0.52 

0.27 

0.12 

0.18 

0.00 

-0.14 

1.00

20.7 

(17.8) 

55.6 

(27.6) 

35.6 

(17.5) 

2.5 

(2.2) 

2.9 

(3.9) 

28.2 

(9.6) 

12.1 

(6.0) 

10.1 

(8.2) 

5.1 

(0.5) 

0.9 

(0.0) 

8.4 

(1.3) 

19.1 

(10.6)

101

101 

102 

102 

102 

102 

102 

102 

102 

102 

102 

102

7 8 9 10 11 12
Table 5. Regressions explaining intrafirm shares in total U.S. manufacturing exports, 1966-97

Variable (1) (2) (3)

Constant 

PRDSALE U.S. parents’ R&D as a percentage 

of sales 

PMNEINT U.S. parents’ foreign employment 

as a percentage of their total employment 

PMNEHSP Affiliate-affiliate trade share in U.S. 

majority-owned foreign affiliates’ sales 

IMPCOMP Imports as a percentage of apparent 

consumption in U.S. industry 

TECH Computing power per dollar [inverse of 

log(price/millions of instructions per second)] 

SCALE Plant scale in U.S. industry 

[log((employees/establishment) 2)] 

TIME 

Industry dummies

Chemicals 

Primary metal 

Fabricated metal 

Machinery 

Electrical 

Motor vehicles and equipment 

Other transport (mainly aircraft) 

Other industry dummies 

No. of observations 

Adj. R2 

F-stat 

Durbin-Watson

n/s not shown but included in the model. ***, **, and * indicate significance at the 1%, 5%, and 10%

levels respectively. The dependent variable is PIFXUSX U.S. parents’ intrafirm exports as a percentage

of total U.S. exports. Observations are from seventeen 2-digit manufacturing industries (excluding

tobacco) and six time periods: 1966, 1977, 1982, 1994, 1989, and 1997. The reference industry is food.

-58.28 

(-2.45) 

0.43 

(0.57) 

0.61 

(4.31) 

-0.05 

(-0.19) 

0.51 

(2.43) 

6.47 

(2.37) 

-0.33 

(-3.50) 

15.28 

(3.03) 

-8.74 

(-1.43) 

10.42 

(2.50) 

17.53 

(2.96) 

0.07 

(0.10) 

35.07 

(4.07) 

-9.18 

(-1.24) 

n/s

101 

0.89 

38.68 

2.10

** 

***

**

** 

*** 

*** 

** 

*** 

*** 

***

9.41 

(0.74) 

1.38 

(2.18) 

0.92 

(6.42) 

0.39 

(1.32) 

0.51 

(2.37) 

-450.57 

(-4.45) 

1.25 

(1.21) 

101 

0.60 

25.99 

0.76

** 

*** 

** 

*** 

***

-47.64 

(-2.03) 

0.59 

(0.78) 

0.63 

(4.51) 

-0.07 

(-0.28) 

0.54 

(2.60) 

-262.24 

(-3.79) 

7.00 

(2.59) 

14.39 

(2.86) 

-9.55 

(-1.57) 

10.88 

(2.65) 

17.15 

(2.95) 

-1.54 

(-0.22) 

32.99 

(3.81) 

-10.58 

(-1.47) 

n/s 

101 

0.90 

39.70 

2.08

** 

***

**

***

** 

*** 

** 

*** 

*** 

***
39

Table 6. Regressions explaining U.S. manufacturing parents’ share in total U.S. manufacturing 

exports, 1966-97

Variable (1) (2) (3)

Constant 

USRDSALE U.S. industry R&D as a percentage 

of current output 

PMNEINT U.S. parents’ foreign employment 

as a percentage of their total employment 

IMPCOMP Imports as a percentage of apparent 

consumption in U.S. industry 

TECH Computing power per dollar [inverse of 

log(price/millions of instructions per second)] 

SCALE Plant scale in U.S. industry 

[log((employees/establishment)2)] 

TIME 

Industry dummies

Chemicals 

Primary metal 

Fabricated metal 

Machinery 

Electrical 

Motor vehicles and equipment 

Other transport (mainly aircraft) 

Other industry dummies 

No. of observations 

Adj. R2 

F-stat 

Durbin-Watson

n/s not shown but included in the model. ***, **, and * indicate significance at the 1%, 5%, and 10%

levels respectively. The dependent variable is PXUSX U.S. parents’ total exports as a percentage of total

U.S. exports. Observations are from seventeen 2-digit manufacturing industries (excluding tobacco) and

six time periods: 1966, 1977, 1982, 1994, 1989, and 1997. The reference industry is food.

-136.35 

(-2.07) 

-1.15 

(-0.78) 

1.18 

(3.22) 

0.03 

(0.05) 

18.85 

(2.47) 

-0.40

(-1.58)

16.53 

(1.50) 

-12.15 

(-0.72) 

13.85 

(1.23) 

25.21 

(1.93) 

11.71 

(0.63) 

8.00 

(0.35) 

38.95 

(1.63) 

n/s

101 

0.67 

10.78 

2.04

** 

***

**

*

*

***

-14.19 

(-0.71) 

2.41 

(4.48) 

1.31 

(6.33) 

-0.38 

(-1.35) 

-373.12 

(-2.38) 

7.37 

(4.12) 

101 

0.60 

30.84 

1.49

*** 

*** 

** 

*** 

***

-122.15 

(-1.87) 

-1.20 

(-0.82) 

1.24 

(3.39) 

0.19 

(0.35) 

-382.11 

(-2.08) 

19.82 

(2.62) 

15.74 

(1.45) 

-14.41 

(-0.86) 

14.74 

(1.33) 

24.22 

(1.90) 

8.41 

(0.45) 

2.91 

(0.13) 

38.52 

(1.63) 

n/s 

101 

0.68 

11.10 

2.04

** 

***

**

**

*

*

***
40

Table 7. Regressions explaining intrafirm shares in U.S. manufacturing parents’ total exports, 

1966-97

Variable (1) (2) (3)

Constant 

PRDSALE U.S. parents’ R&D as a percentage 

of sales 

PMNEINT U.S. parents’ foreign employment 

as a percentage of their total employment 

PMNEHSP Affiliate-affiliate trade share in U.S. 

majority-owned foreign affiliates’ sales 

IMPCOMP Imports as a percentage of apparent 

consumption in U.S. industry 

TECH Computing power per dollar [inverse of 

log(price/millions of instructions per second)] 

SCALE Plant scale in U.S. industry 

[log((employees/establishment) 2)] 

TIME 

Industry dummies

Chemicals 

Primary metal 

Fabricated metal 

Machinery 

Electrical 

Motor vehicles and equipment 

Other transport (mainly aircraft) 

Other industry dummies 

No. of observations 

Adj. R2 

F-stat 

Durbin-Watson

n/s not shown but included in the model. ***, **, and * indicate significance at the 1%, 5%, and 10%

levels respectively. The dependent variable is PIFXPX U.S. parents’ intrafirm exports as a percentage of

U.S. parents’ total exports. Observations are from seventeen 2-digit manufacturing industries (excluding

tobacco) and six time periods: 1966, 1977, 1982, 1994, 1989, and 1997. The reference industry is food.

14.70 

(0.50) 

1.83 

(1.95) 

0.36 

(2.02) 

0.40 

(1.32) 

0.53 

(2.02) 

-0.65 

(-0.20) 

-0.32 

(-2.68) 

9.54 

(1.50) 

-3.51 

(-0.47) 

7.90 

(1.52) 

12.80 

(1.72) 

-1.42 

(-0.17) 

29.57 

(2.80) 

-15.14 

(-1.73) 

n/s

102 

0.82 

22.34 

2.17

*

** 

**

***

*

***

*

***

58.78 

(4.23) 

1.78 

(2.60) 

0.72 

(4.68) 

0.77 

(2.40) 

0.47 

(2.03) 

-370.79 

(-3.38) 

-3.65 

(-3.25) 

102 

0.51 

18.62 

0.72

*** 

** 

*** 

**

** 

*** 

***

***

22.36

(0.78) 

1.94 

(2.05) 

0.37 

(2.07) 

0.36 

(1.19) 

0.51 

(1.91) 

-220.25

(-2.49)

-0.19 

(-0.06) 

9.24 

(1.46) 

-3.85 

(-0.51) 

8.35 

(1.59) 

13.46 

(1.80) 

-1.80 

(-0.21) 

28.98 

(2.69) 

-16.31 

(-1.85) 

n/s 

102 

0.82 

22.05 

2.13

**

** 

**

** 

*

***

*

***
Table 8. U.S. exports to U.S. majority-owned foreign affiliates as a percentage of total U.S. manufacturing exports, and percentage of the former 

that is shipped intrafirm by U.S. parents, 1966-97

 U.S. exports to manufacturing MOFAs U.S. exports received intrafirm from U.S. parents

Industry as a % of total U.S. manufacturing exports* as a % of total U.S. exports received by U.S. MOFAs**

1966 1977 1982 1989 1994 1997 1966 1977 1982 1989 1994 1997

Manufacturing 24.1 26.9 21.5 23.3 23.0 22.6 82.6 81.6 83.1 86.8 83.3 84.5

Food and kindred products 10.3 13.4 16.8 13.7 10.5 9.1 53.1 46.6 50.8 70.5 80.1 77.2

Chemicals and allied products 27.2 28.2 20.2 20.5 22.2 24.3 84.5 88.3 81.7 88.5 84.7 90.7

Primary metals products 7.4 11.2 6.0 6.2 4.0 3.3 97.3 84.9 64.7 83.4 73.5 71.2

Fabricated metal products 26.1 11.5 8.0 11.0 12.2 10.2 71.0 68.7 83.6 77.9 67.0 77.5

Industrial machinery and equipment 15.9 14.2 12.4 21.0 17.9 17.3 98.5 92.6 94.4 92.8 88.6 88.7

Electronic and other electric equipment 25.6 26.3 25.5 24.8 23.8 23.8 72.1 85.8 89.5 89.7 94.6 92.1

Motor vehicles and equipment 56.6 89.8 87.1 99.1 85.4 89.8 112.2 80.7 81.4 86.1 78.9 79.1

Other transport (including aircraft) 48.0 2.6 2.3 1.4 3.1 2.8 20.1 48.7 50.8 49.2 34.8 32.5

Tobacco products 82.4 32.3 n/a 5.0 2.0 10.0 17.2 n/a n/a 68.0 76.4 100.0

Textile products and apparel 6.2 13.1 14.8 8.1 4.5 3.6 53.9 63.6 86.7 73.8 73.6 76.7

Lumber, wood, furniture, and fixtures 3.4 2.6 1.8 3.2 5.7 4.9 75.1 n/a 78.7 82.1 58.9 83.2

Paper and allied products 32.1 23.8 14.3 13.0 16.4 13.5 57.5 60.9 72.0 63.9 77.5 84.0

Printing and publishing 15.1 9.5 5.3 4.1 7.1 6.8 60.7 89.2 88.9 87.9 79.2 96.0

Rubber products 111.5 45.1 34.8 29.1 26.8 25.8 117.5 81.6 77.1 85.4 85.0 81.3

Miscellaneous plastics products 21.3 8.6 19.2 20.0 17.5 14.1 116.2 80.6 79.1 87.6 91.2 86.5

Glass products 16.8 16.1 13.0 24.4 4.7 18.2 106.7 80.9 88.5 82.6 61.7 73.1

Stone, clay, and nonmetallic mineral products 25.4 24.2 19.6 20.1 18.1 16.5 95.0 71.9 79.0 75.0 81.9 87.4

Instruments and related products 31.7 24.4 22.8 20.7 17.0 16.4 80.3 94.9 97.4 90.0 92.9 92.6

Source: U.S. export figures are from U.S. Department of Commerce, Statistical Abstract of the United States, various issues; 

multinational export figures are from U.S. Department of Commerce, U.S. Direct Investment Abroad, various issues.

*The U.S. Commerce Department classifies multinational export data by industry of U.S. parent and U.S. export figures by product. This, in some cases,

leads to estimates of intrafirm shares that are greater than 100 percent of the total. 

**Author's estimates, in some cases, lead to shares that are greater than 100 percent. 

n/a not available; figures in italics are author's estimates.