Firm Outsourcing Decisions: Evidence from U.S. Foreign Trade Zones

Deborah L. Swenson

University of California, Davis and NBER

Abstract

This paper examines the operations of firms located in U.S. foreign trade subzones tostudy the responsiveness of outsourcing to international cost changes. I find that firms reducetheir reliance on foreign inputs when dollar depreciation increases the relative price of importedinputs. The effect is pervasive across industries and is economically significant. In addition,firms that rely more heavily on imported intermediate inputs reduce their overall shipments whendollar depreciation elevates their imported input costs. However, the magnitude of the shipmentseffect is economically small, suggesting that firms respond to exchange rate movements byadjusting their operations on other dimensions.

I. INTRODUCTION

During the NAFTA debates U.S. industry argued that it would be placed at a competitive

disadvantage if it failed to gain access to Mexican parts that benefitted from tariff reductions. In

the absence of such benefits it was argued that U.S. firms might even move their production off

shore. At the same time U.S. trade unions expressed great concern that jobs and high levels of

economic activity would be lost if NAFTA caused a rise in the outsourcing of intermediate

inputs. Although these countervailing concerns have attracted much attention, very little is

known about the responsiveness of firm outsourcing to relative price changes or about its

secondary effects on firm shipments, since outsourcing decisions are made at the firm level and

appropriate data is rarely available to researchers. This paper seeks to address this void by

analyzing a data set that provides information on these purchasing and shipment decisions.

Recent aggregate evidence indicates that firms are purchasing an increasing portion of

their intermediate inputs from their foreign affiliates, or unrelated parties located abroad.1 It is

argued that advances in transportation and communications have facilitated the trend towards the

dispersion of production activities. While the aggregate trends are striking, little research has

focused on individual firm decisions. One exception is Brainard and Riker's [1997] examination

of multinational firms' employment choices as they respond to international wage changes.

Brainard and Riker conclude that the degree of firm substitution among a firm's numerous

foreign affiliates is much higher than that between parent firms and their foreign affiliates, which

is relatively small. This labor market evidence suggests that foreign affiliate labor is not easily

substituted for home labor, and that the two may even be complements.2 In contrast a higher

degree of substitutability is implied by work including Feenstra and Hanson [1997 ] and Irwin

2

[1996] for the U.S., or Campa and Goldberg [1997] for the U.S., U.K., Japan, and Canada,

which documents that the usage of imported intermediate inputs has increased in almost all cases

since the 1970's.3

This paper studies the issue of input sourcing flexibility and its consequences by

examining individual firm decisions. The analysis is based on the activities of a set of firms

located in U.S. foreign trade subzones. I focus on this subset of firms, since the U.S. Foreign

Trade subzones program provides a unique opportunity to examine firm level decisions regarding

inputs and shipments. The reporting requirements of the Foreign Trade Zones program enable

us to view aspects of firm sourcing decisions that are usually unobservable.

I use two estimation methods to measure the general substitutability of inputs, and

outsourcing flexibility. First, I develop a CES model of input demand. I then use non-linear

least squares techniques to estimate the underlying demand parameters implied by the structural

equations. I then perform a tobit analysis of firm sourcing decisions. The benefit of the second

form of analysis is that it allows me to study additional determinants of outsourcing, and it does

not require strong assumptions about the functional form of the production function. Both

estimation methods indicate that U.S. manufacturing firms changed their sourcing patterns over

time as exchange rate changes alter relative production costs. In particular, the data indicate that

firms reduce their reliance on U.S. source inputs when dollar appreciation increases their cost

relative to imported foreign inputs. While Swenson [1997] showed that automobile industry

sourcing responds to changes in international costs, this paper demonstrates that the effect is

widespread. Though the economic magnitude of these responses varies substantially across

industries, it is significant in many. The fact that firms change input sourcing in response to

3

changes in relative production sourcing costs is interesting in itself. Most models of the

multinational firm postulate that firms incur fixed operation costs when they extend their

activities across borders.4 While these costs are no doubt real, their magnitude is not large

enough to deter frequent and large changes in sourcing over time.

Firm input sourcing flexibility has implications for other firm decisions. If a firm can

reduce its reliance on those inputs that become more expensive it can moderate cost increases

and presumably retain sales it might lose if it were forced to raise prices.5 If so the cost

repercussions of U.S. dollar depreciation are likely to be most detrimental for U.S. producers

who rely heavily on imported inputs. To investigate the economic importance of this effect, I

examine the sensitivity of firm shipments volumes to exchange rate changes. The evidence

indicates that a firm's exchange rate exposure is influenced by its reliance on imported

intermediate inputs.6 Nonetheless, I find that exchange rate exposure transmitted through prior

firm sourcing choices is very small when compared with the direct effects of exchange rate

movement on firm competitiveness. Here too, I find that the industry-specific responses to

shocks transmitted through intermediate inputs vary widely in magnitude across industries.

The paper is organized as follows. In the second section I model firm input demands to

develop a framework that relates sourcing decisions to relative international cost conditions.

Section three provides information on the firms in the sample. Here I use two estimation

techniques to evaluate how firms change their sourcing when exchange rate movements alter the

relative cost of U.S. inputs. The fourth section measures how prior firm sourcing decisions affect

firm shipment volumes. Final issues, and discussion are included in the fifth section.

4

II. A MODEL AND ESTIMATION OF FIRM INPUT DEMAND

To estimate the responsiveness of relative input demand to changes in relative

international production costs I begin with a stylized model of input demands. I consider a

representative firm that produces in the U.S. market for sales both in the U.S. and abroad. As the firm

produces total output Y, it chooses inputs to minimize its total production costs. The production

process is characterized by constant elasticity of substitution between inputs. There are Nus varieties

of U.S. inputs Xus and Nf varieties of imported inputs Xf. We assume that each input enters the

production function symmetrically and that the elasticity of substitution between any two inputs is

represented by σ, where σ> 1. As a result, the production function takes the form:

Each firm chooses its input mix of foreign and domestic parts to minimizes its costs in light of

input prices. The price of a typical U.S. part is Pus, while the price of a representative foreign part is

Pf. Cost minimization implies that the demands for each U.S. and foreign input take the following

forms respectively:

where the composite price of inputs PAGG is represented by:

The relative contribution of U.S.-origin content depends on the price and variety of U.S. and

foreign-origin inputs. Since a high portion of component purchases are transacted within the firm,

]X N + XN[ = Y 1/-11

)1/-(1ff

)1/-(1usus σσσ

,Y]P/P[ = X ; Y]P/P[ = X fAGGfusAGGusσσ

. ] ) P( + P [ = P -11)-(1

f)-(1

usAGG σσσ

5

whether the parts are produced in the U.S. or abroad, I assume that the parts are priced at marginal

cost. I assume further that intermediate inputs are produced by a constant returns to scale production

process. As long as we assume that the price of inputs is the same for all parts, the following formula

defines µ, the relative contribution of U.S.-origin inputs, or the value of US inputs relative to the

firm's total inputs.

The equation demonstrates that the relative value of U.S. content is rising in the foreign price of

inputs and declining with the U.S. price of inputs. It is important to note that the foreign price

expressed in dollars Pf is generated by the nominal foreign currency price of foreign parts Pf* divided

by the exchange rate e, or that Pf = Pf*/e. Since e represents the number of foreign currency units per

U.S. dollar, dollar appreciation, which elevates e, is associated with an increase in the purchase of

foreign inputs, and a decline in the purchase of U.S. inputs.

III. ESTIMATION

In this section I use two techniques to measure the degree of substitution between foreign

and domestic parts used in production. First I first use non-linear least squares techniques to

estimate the specification that is implied by the theory of cost minimization under a CES

production function. The benefit of this specification is that it facilitates the direct identification

of the elasticity of demand for inputs. To verify the robustness of the results I next perform tobit

analysis on a more general specification that is augmented to include other industry and firm

])P/P)(N/N( + 1/[1 = fususf1-σ

) X N P +XNP)/(XNP( = fffususususususµ

6

regressors.

Data

The primary variable of interest is the relative contribution of U.S. input purchases to the

firm's overall sourcing plans. While it would be desirable to observe individual firm sourcing

decisions for a large set of firms, this information is generally unavailable. I examine a set of

firms located in U.S. foreign trade zones, since these firms provide a rare exception to this data

limitation. Firms located in U.S. foreign trade zones report the annual value of their domestic

and foreign input purchases. These inputs include both raw materials, and manufactured

intermediate inputs. Firms in the foreign trade zones program also report their subsequent

shipments.7

For each firm f the relative value of U.S. inputs in year t, is computed as µft = (U.S.

Source Inputsft)/(Total Inputsft,), where Total inputs = (U.S. Source Inputs + Foreign Source

Inputs). Since µft reports the value of each zone's input purchases, rather than the physical

quantities of inputs used, it is important to note that exchange-rate induced changes in input valuation

move the observed input sourcing variable in a direction that is contrary to the previous model

predictions.8 In other words, a dollar depreciation causes the reported value of U.S. sourcing to rise,

only if firms replace some of their foreign input purchases with U.S. source inputs.

Table 1 summarizes the Foreign Trade Zones data. The use of foreign trade zones grew

more than 10-fold over the 1984 to 1995 period I analyze. The growth of this program in the

1980's can be attributed to a U.S. Treasury ruling that limited tariffs assessed on foreign trade

zone products to the portion of the product originating from abroad. This facilitated the use of

foreign trade zones for manufactured products that relied on imported intermediate inputs, since

7

the finished products no longer faced tariff payment for the full value of the manufactured item.9

While most inputs were of U.S. origin, the volume of imported inputs grew from roughly $13

billion in 1984, to $132 billion by 1995.

The model in section 2 directly links the relative demand for U.S. source inputs to the

relative price of inputs, Pus/Pf, as shown in equation (4). Since foreign trade zone occupants

report the value of their foreign and domestic sourcing, but do not provide any details on the

product composition or country of origin of their input purchases, it is not possible to use price

indices related to actual products or country of origin. Because price movements differ

substantially across U.S. industries, I measure movements in the relative price of U.S. inputs by

using U.S. dollar industry real exchange rates.10 Increases in the real exchange rate variable

reflect dollar appreciation, and should be associated with reductions in U.S. sourcing.

The summary data indicate that the usage of U.S. source inputs fluctuated from year to

year in a manner that is consistent with the exchange rate predictions. The average Foreign

Trade Subzone use of U.S. inputs fell to its lowest point in 1984 - a time when the dollar was

especially strong. In contrast, the average use of U.S. source inputs peaked at 85.1 percent in

1992 - a time that followed the large depreciation of the dollar. Otherwise, the percentage U.S.

inputs used changes from year to year with no apparent trends.

On the shipments side, it should be noted that almost all Foreign Trade Zone occupants

export as well as selling to the U.S. market. Nonetheless, it is apparent that most zones are

designed with U.S. customers in mind, as roughly 90 percent of all zone shipments are

ultimately shipped to U.S. markets. Here too, there were year to year fluctuations in the relative

importance of the U.S. market, though exports never comprised more than twelve percent of total

8

subzone output.

Non-Linear Least Squares Estimation

I estimate equation (4) directly using non-linear least squares. If one assumes that the

elasticity is the same for all industries, the estimation yields an elasticity estimate of 1.872 with a

standard error of (0.270).11 The estimated value of Nf/Nus is 0.243 with a standard error of

(0.028). However, we can not interpret the estimated value of Nf/Nus too literally, as it also

captures any shifts in the relative demand between domestic and foreign inputs that are not

captured elsewhere. For example, suppose that firms differ in their efficiency in using foreign

and domestic inputs. Equation 1 could be rewritten with shift terms δus and δf multiplying the

foreign and domestic inputs respectively to reflect these differential efficiencies.12 If these shift

terms belong in the production function, the functional form of equation (4) remains valid.

However, the estimated Nf/Nus term now is a composite that captures the shift terms as well as

the relative diversity of inputs.

It may be overly restrictive to assume that the elasticity of demand for inputs is the same

for all industries. For this reason, I next estimate the specification implied by equation (4), but

allow the estimation to identify unique estimates of σi and γi for each industry. Each firm f is

assigned to an industry i, based on its primary zone output. The new specification is:

These results are displayed in the first column of table 2. Of the eleven primary industries in my

analysis, the highest implied elasticities of substitution are found in the Pharmaceutical and

Chemical, Oil and TV/Computer sectors - industries that are anecdotally known for their

])P/P( + /[11 = fusi1)-(

ftiγµ σ

9

outsourcing of inputs, or which have more homogenous inputs that we would expect to exhibit

greater price sensitivity. If there are no differential efficiencies in the use of foreign and

domestic inputs, γi provides industry estimates of Nf/Nus. However, since the estimate of γi is a

composite measure of input diversity and product demand shifters, it is not a pure measure that

we can interpret easily.

Tobit Estimation

While the first set of results directly measure the implied elasticity of demand, the

estimating framework is not easily modified to capture all the firm level and industry level

factors that may influence the relative demand for U.S. inputs. I now move to a specification that

incorporates firm level and industry factors, as well as the relative cost of inputs. As before, the

variable of interest is degree of U.S. sourcing, µft, chosen by the firms in the sample. The new

specification takes the following form.

(5) µft = 3iθi + ω*Rt + λXft + εft

The first set of terms θi are industry indicator variables designed to capture industry-level

sourcing differences, the second component measures the sensitivity of US sourcing decisions to

changes in relative production costs as measured by the industry real exchange rate Rt, and the

third set of terms captures changes in firm characteristics Xft over time. The regression error

term is represented by εft. Since the dependent variable is bounded between zero and one, I

perform a tobit analysis. The benefit of the tobit specification is that it allows one to easily add

characteristics, such as subzone age or firm fixed effects, which presumably influence the

relative demand for U.S. source inputs, and that can not be added naturally to the non-linear least

squares specification in (4) without further assumptions about the structure of firm input

10

demands.

The results of the tobit specification are presented in Table 3, which describes U.S.

sourcing responsiveness for the full sample, as well as for different subsets of producers. Row

(1) of Table 3 displays the baseline regression of US sourcing on relative costs. The general

message is that firms economize on their use of U.S.-source inputs when dollar appreciation

causes their relative price to rise.

A basic question is whether one should use the current exchange rate, or its lagged value

in capturing the effect of relative price changes. If firms require time to adjust to cost changes,

then one would use lagged values of the exchange rate. When the first regression is repeated

with the lagged value of the exchange rate, the estimated exchange rate coefficient is -0.3172

with a standard error of (0.829). The fit of the regression is slightly worse, as indicated by an

increase in the log likelihood to (-474.7). If the current and lagged exchange rates are both

included in the same regression, the current exchange rate enters with a value of -.3759(.1804),

while the coefficient on the lagged exchange rate is- 0.0695(.1446). In these equations, and the

later tests, it appears that the current exchange rate has greater explanatory power than do lagged

exchange rates. This implies that the sourcing decisions of the firms in my sample respond

quickly to exchange rate changes, and for this reason the remaining results presented do not

include lagged values of the exchange rate.

The age and industry variables included in specification (1) deserve some comment.

Age may affect firm sourcing decisions if firms learn more about U.S. sources of supply after

they establish their US facilities. In particular, sourcing of U.S. inputs will rise over time as

firms shift their purchases towards recently identified U.S. suppliers. In addition, if suppliers

11

follow assemblers, we would expect the use of U.S. inputs will increase over time as suppliers

set up new facilities that are located near the subzone occupants.13 These potential changes over

time are captured by Age, which is measured as the number of years the subzone has operated.14

Age2 is simply the square of the age term, and is entered to capture any non-linearities in the age

effect.

I include industry dummy variables to capture industry differences in U.S. comparative

advantage in supplying inputs. The industry variables can also be justified by a growing

literature based on industrial organization theories regarding profit-maximizing multinationals,

which imply that the presence of multinational firms may alter the composition and magnitude of

trade flows. Multinational firms have to decide whether to export their outputs from a

centralized location, or to produce outputs in a number of widely dispersed subsidiaries. The

benefits of dispersion include the ability to avoid transport costs, and linkage benefits created

when the multinational's local presence stimulates demand in host markets. At the same time,

the trend towards dispersed subsidiary production is inhibited by the fixed costs associated with

the opening of new plants and facilities.15

I assume that the production techniques chosen within an industry are similar, which

implies that industry comparative advantage will determine a firm's baseline sourcing decisions.

If so, I can capture the effects of comparative advantage through a set of industry dummy

variables θi. Each firm f is again assigned to one of eleven industries based on the primary

industry activity it conducts in the foreign trade subzone. The possibility that θi changes over

time is addressed later. I take no position on the source of comparative advantage, and whether it

arises from inherent cross country differences in factor endowments or technological abilities, or

12

whether the comparative advantage arises from economies typified by increasing returns to scale

production.16

I next examine whether U.S. firms respond differently than foreign firms. The

Armington Assumption is usually used to justify consumer preferences for home products, but it

can be applied to producers as well.17 For example, it is likely that the typical supplier tailors

its production with the needs of home country firms foremost in mind. If so, downstream firms

will purchase more inputs from suppliers located in their own country, since these firms have

created parts that are most closely customized to their specific needs and preferences. Also,

human networks may cause firms to be better informed about the quality of products from their

own markets, than about the quality of products from other countries. This would reinforce any

firm tendencies to rely more heavily on home produced inputs.

In light of these arguments, I apply the general regression specification to foreign and

U.S.-owned Foreign Trade Subzones separately, and report the results in rows (2) and (3) of

Table 3.18 I find that the estimated responsiveness is greater for the U.S.-owned than for the

foreign-owned facilities. However, the difference in the estimated exchange rate response is not

statistically significant. This suggests that while the operation of domestic and foreign firms is

somewhat different, it is not overwhelmingly so. For this reason, I treat production by domestic

and foreign-owned subsidiaries as comparable for the remaining estimation, and retain the pooled

sample.19

To this point I have assumed a common exchange rate response for all industries.

However, it is possible that the relative availability of foreign and domestic inputs differ across

industries and that these differences condition industry responses to exchange rate levels. Since

13

auto assemblers represent a large portion of the sample, I exclude them from the specification

tested in row (4) of Table 3 to see whether the exchange rate effects differ for the non-auto

sectors. I find that industries outside the automobile sector respond more vigorously to

exchange rate movements. The estimated coefficient of -.49 for the non-auto subsample exceeds

the coefficient of -.38 for the full sample by almost 30 percent. While these two estimates are

not statistically distinct, they reinforce the conclusion that cross-industry heterogeneity is

important, and that it may operate on more than one dimension.

I next expand the specification to allow the exchange rate variable to vary uniquely by

industry. This involves the inclusion of eleven exchange rate coefficients ωi which correspond

to the eleven industries in the sample. The regression now takes the form:

(6) µft = 3iθi + 3iωi*Rt + λXft + εft

Though I am observing data on firms f, located in foreign trade zones, the exchange response is

now classified by the industry i, to which the firm belongs.

The results which include the industry exchange rate interaction terms are displayed in

rows (5), (6) and (7) of Table 3. Row (5) includes no industry dummy variables. Industry

dummy variables are added in rows (6) and (7), and row (7) also includes industry trend

variables. It should be noted that an F-tests for the joint significance of the industry-exchange

rate variables are significant at better than the 1 percent level in all three specifications. The

improvement in the log-likelihood of these equations also supports the inclusion of these more

detailed variables. Consider specification (6) presented in Table 3. The exchange rate

coefficient is negative in every industry but one, indicating that a dollar appreciation causes firm

reliance on U.S.-source inputs to decline. For the 10 industries that respond as predicted, I find

14

that the exchange rate coefficient ranges from a low of -.07 to a high of -4.2 in the

Chemical/Pharmaceutical industry.

In principle, we might expect that overall economic changes cause the optimal value of

θi to change over the 12 years of estimation. While it would be possible to estimate unique

values of θit for each industry-year, this would use a large number of degrees of freedom.

Instead, I capture changes in comparative advantage through a more compact measure: θit = θi0 +

ρit. Baseline industry differences in comparative advantage are represented by the term θi0,

while changes over the period of estimation are assumed to evolve on an industry basis, and are

measured by unique industry-trend terms ρi. We expect ρi to be negative if comparative

advantage for a range of inputs used in the industry shifts away from the U.S. Two likely

scenarios that would cause in this shift would include technology transfer from the U.S. that

increased the diversity of available foreign inputs, or U.S. trade liberalization which created the

same effect.20 Industry-year trends are also important if there were secular trends during the

period of estimation that changed the relative diversity of foreign and domestic inputs.

The new specification that includes industry-specific time trends is presented in column

(7) of table 3. While the magnitude of the exchange rate coefficients changes some, this is to be

expected, as the industry time trends absorb all industry trend movements, including those

attributable to the general decline of the dollar from its peak in 1985. Nonetheless, the same

qualitative results remain.21

Another firm characteristic that is likely to influence a firm's sourcing opportunities is

whether the firm has facilities in other countries. Presumably, a firm that establishes worldwide

operations should be able to change its international sourcing to a greater extent than a pure U.S.-

15

based firm. First, since the firm has already sunk fixed costs which accompany the decision to

locate some operations abroad, it should be less costly for these firms to increase their foreign

sourcing. A second reason relates to the firm's ability to identify relevant new sources of supply.

Exposure to information about purchasing opportunities should be especially marked for firms

with widely dispersed subsidiaries.22 To capture these effects, I used corporate directories to

identify the firms in my sample which had operations in Europe, South East Asia, Japan, South

America or non-U.S. North America, and tested whether the presence of these facilities affected

the responsiveness of the firms to changes in relative costs. I do not report these results, since I

identified no significant effects. While this channel may be important generally, there is

insufficient variation in my sample to identify the effect.23

In order to check for robustness of the exchange rate results, I ran a final specification

which included firm fixed effects γf. If the exchange rate effect is assumed to be constant across

industries, the estimated exchange rate coefficient of -.2366 (.0452) is not much smaller than

the coefficient for the comparable specification presented in row (1) of Table 3. When the firm

dummy variables are used along with a full set of industry exchange rate terms, 9 of the 11

estimated industry-exchange rate coefficients are negative. Five of the 9 remain significant at

better than the 5% level.

Implied Sourcing Responsiveness

To quantify the economic implications of the exchange rate coefficients for firm input-

sourcing decisions, I performed calculations which compare actual industry sourcing decisions,

with the predicted level of sourcing that would have occurred had the U.S. dollar been 10 percent

stronger in 1995. These calculations are contained in Table 4.

16

As a reference point, the first column of Table 4, lists the actual 1995 reliance on U.S.

inputs for the 11 industries in the sample. The second column shows the fitted values for input

use, which are based on regression (1) in Table 3, which posits a common response to exchange

rate changes. However, since the later regression analyses indicate that there was substantial

heterogeneity in industry sourcing responses it is best to account for these differences directly.

The last two columns of Table 4 report the predicted U.S. input usage for 1995 based on

regression specification (6). This specification allows heterogeneous industry response, and is

again used to see how U.S. input usage would have changed if the dollar had appreciated to a

level 10 percent higher than its actual 1995 value. In this setting, the changes in the two auto

sectors are relatively small. With the exception of the pharmaceutical sector, the implied

percentage changes are less than 10 percent in the remaining manufacturing sectors. In thinking

about the implied effects of these results for the U.S. as a whole, caution is advised. Since firms

self select into the foreign trade zones program for its tariff reduction benefits, I expect that the

firms in my sample rely somewhat more heavily on imported intermediate inputs than do the

universe of U.S. firms more generally. Nonetheless, these results show that the responsiveness

of input sourcing decisions is not only statistically significant, but economically meaningful in

most industries.

One possible explanation for my differential industry exchange rate findings is input

specificity. Even though firms located in Foreign Trade Subzone firms do not report their import

of foreign inputs at the product level, we know that some industries rely on specifically designed

inputs, while other firms can purchase homogenous inputs from any supplier. At the one

extreme, we think of many car parts, such as car bodies, or even car engines, as specifically

17

designed with the end user in mind. In contrast, though there are differences in grades of

unrefined oil, it is likely that the inputs to oil refining or the pharmaceutical/chemical sector are

far less differentiated, and not often tailored for particular purchasers. In the absence of other

rigidities, such as long-term contracts, sourcing in these industries should respond more

vigorously to cost shocks, than sourcing in industries characterized by input specificity.

While I measure firm responses to exchange rate induced changes in relative production

costs, there is no reason to believe that firms would respond any differently if cost shocks were

caused by other factors such as changes in tariff and trade policy. As a result, I expect that firms

will change their sourcing patterns as trade liberalization such as NAFTA, reduce the relative

cost of imported inputs. More generally, the ongoing decline of trade barriers should influence

the mix of foreign and U.S. inputs used in U.S. production.

IV. LINKAGES BETWEEN INPUT FLEXIBILITY AND FIRM SHIPMENTS

The previous section indicates that firms purchase a higher percentage of their inputs in

the U.S. when the relative cost of U.S. inputs declines. However, while firms plan their

production optimally in light of exchange rate expectations, they are often surprised by actual

exchange rate realizations. In addition, even within industries exchange rate changes are likely

to influence firms' competitive positions since prior firm sourcing choices lead to differential

firm exchange rate exposure. As a result, I analyze whether firm exchange rate exposure

transmitted by intermediate input sourcing helps explain changes in firm shipment levels. Since

most of the products in the sample are differentiated manufactured products, the analysis

assumes that final goods markets are imperfectly competitive.

18

Exchange rate movements influence firm profits, and consequently firm shipments in at

least two ways. First, exchange rate changes alter the relative price of foreign and domestic

products. This exerts a direct effect on the competitiveness of domestic firm output, and we

expect that the adverse competitive consequences of dollar appreciation will reduce domestic

firm shipments. Even if there is incomplete pass through of price changes by competing foreign

firms, dollar appreciation will generally depress the shipments of domestic firms.

Second, exchange rate movements have a unique effect on each firm which arises from

the firm's sourcing choices.24 In this context, we can predict that dollar depreciation, since it

raises the price of imported intermediate inputs, will have the most negative consequences for

those firms that purchase a greater percentage of their inputs abroad.

To capture the effects mentioned, I examine the yearly shipments of individual subzones,

Total Shipments, according to the following specification:

(7) Total Shipmentsft = α + δ*Exposeft-1 + β*Exchange Rateft-1 + 3γi + εft

In addition to the constant term and industry-specific γi's that capture industry differences in firm

shipment size, there are two coefficients which are designed to reflect the exchange rate effects

described above. The exchange rate measures the foreign currency price of the U.S. dollar,

which means that an decline in the variable Exchange Rate, represents a dollar depreciation.

Dollar depreciation enhances the relative competitiveness of U.S. products (in both U.S. and

foreign markets), and should cause U.S. shipments to rise. The competitiveness effect predicts a

negative coefficient β on the pure exchange rate term.

19

At the same time, a dollar depreciation harms those U.S. producers who rely heavily on

imported intermediate inputs. I capture the effect of exchange rate exposure with the term,

Expose = (1-µft-1)*(1/Exchange Rate). As before, µft-1 measures the percentage of U.S. origin

inputs purchased by the individual zone user. Consequently, (1-µft-1) measures a particular zone's

reliance on foreign inputs, and their relative price is indicated by (1/Exchange Rate). I expect

the coefficient δ to be non-positive, since this term reflects the effect of a rise in the cost of

intermediate inputs on firm shipments.25

I experiment with various partial specifications before moving to the full specification

which is displayed in Row (5) of Table 5. The coefficient on the interaction term Expose

implies that dollar depreciation translates to reduced shipments for firms that rely more heavily

on imported intermediate inputs. Highly significant industry dummies indicate that variation in

shipment size is influenced by industry characteristics. The negative coefficient on the pure

exchange rate term shows that dollar depreciation, because it causes the relative price of U.S.

produced goods to fall, elevates the level of shipments from firms located in U.S. foreign trade

zones.

To see whether the potency of the intermediate inputs channel differs significantly across

industries, I change the specification slightly to allow exchange rate sourcing exposure to exert to

exert unique effects on the industries in the sample. The modified specification is:

(8) Total Shipmentsft = α + 3δi*Exposeft-1+ β*Exchange Rateft-1 + 3γi + εft

I now estimate a unique δi, coefficient for each industry in the sample to capture the effects of

exchange rate sourcing exposure for individual industries.

The results which include the industry exposure interaction terms are displayed in row (6)

20

of Table 5. Ten of the eleven exchange rate exposure terms enter with the predicted negative

sign. Though many of the individual terms are not significant at conventional levels, an F-test

for the joint significance of the exchange rate terms is significant at better than the 1 percent

level. Some of the terms are not surprising. For example, the term for the oil industry, is not

statistically different from zero. However, since the demand for oil is not thought to be elastic in

the short run, it would be surprising to find a negative coefficient in this industry, as this would

imply that adverse production cost shocks exert a strong inhibiting effect on oil shipments.

To quantify the economic implications of the shipping results, I can ask how much

shipment volumes would have changed if the dollar appreciated 10 percent. I find that a 10

percent dollar appreciation would reduce the representative firm's shipments by 4.1 percent.26

While the transmission of cost shocks to shipments through the channel of imported intermediate

inputs is statistically significant, it is not economically large. Direct demand effects strongly

dominate instead.

V. CONCLUSION

In studying the international composition of input purchases by firms in the U.S. Foreign

Trade Subzones program, two findings emerge. First, this paper documents that a firm's relative

reliance on U.S. inputs is affected by the relative price of U.S. inputs; when the relative cost of

U.S. inputs is elevated by U.S. dollar appreciation, the relative use of U.S. inputs declines.

While the strength of this effect differs from industry to industry, the effect appears to be

pervasive and it is economically significant. Second, the data in this paper allow one to measure

individual firm exposure to exchange rate movements that are transmitted by cost shocks to

imported intermediate inputs. The results indicate that those firms that rely more heavily on

21

imported intermediate inputs reduce their overall shipments when adverse exchange rate

movements elevate their cost of imported inputs. However the magnitude of this effect is quite

small, especially when it is compared with the direct effect of exchange rates on the relative

competitiveness of U.S. products.

In explaining why firm input cost shocks do not have a larger effect on firm shipments, it

is important to remember that firms have many other decisions they may alter instead. Campa

and Goldberg [1995] show that U.S. firms reduce their investment when adverse exchange rate

shocks hit U.S. industries. Alternatively, firms may instead adjust employment, as is considered

by Burgess and Knetter [1996] . Finally, firms may find that sourcing and pricing to market are

substitutable channels for adjusting to exchange rate changes as is suggested by Rangan and

Lawrence [1993] and Gron and Swenson [1996; 1998].

In any case, it is clear that firms in some industries change their sourcing of inputs

significantly when relative prices change. While I present evidence that describes the effects of

exchange rate induced cost shocks, there is no reason to believe that other changes that affect the

relative price of imported inputs, including transportation cost reductions, or the effects of trade

reforms on tariff costs, would not have a comparable effect on the relative demand for imported

intermediate inputs. The fact that exposure transmitted through firm differences in sourcing does

not translate into large shipment effects may simply mean that firms maintain shipment levels in

the short run, while adjusting their long run operations along other dimensions including the

sourcing of their input purchases.

References

Bergsten, C. Fred and Marcus Noland. (1993), "Reconcilable Differences? United States-Japan Economic Conflict." Washington, D.C.: Institute for International Economics.

Blonigen, Bruce A. and Wesley W. Wilson. (1996) "Explaining Armington: What Determines Substitutability Between Home and Foreign Goods?" University of Oregon Working Paper.

Brainard, Lael. (1997) "An Empirical Assessment of the Proximity-Concentration Tradeoff between Trade and Multinational Sales." American Economic Review, 87(4):520-544.

Brainard, S. Lael and David A. Riker, (1997), "U.S. Multinationals and Competition from Low

Wage Countries," NBER Working Paper 5959, March.

Burgess, Simon and Michael M. Knetter (1996), "An International Comparison of Employment

Adjustment to Exchange Rate Fluctuations." NBER Working Paper 5861, December.

Campa, Jose and Linda S. Goldberg. (1995) "Investment in Manufacturing, Exchange Rates and External Exposure," Journal of International Economics, 38:297-320.

Campa, Jose and Linda S. Goldberg, (1997) "The Evolving External Orientation of Manufacturing Industries: Evidence from Four Countries," NBER Working Paper 5919, February.

Casella, Alessandra and James E. Rauch, (1997), "Anonymous Market and Coethnic Ties in International Trade," March Working Paper.

Caves, Richard E. (1996), Multinational Enterprise and Economic Analysis, Second Edition, Cambridge: Cambridge University Press.

Dornbusch, Rudiger, (1987), "Exchange Rates and Prices," American Economic Review, 77:93- 106.

Feenstra, Robert C, (1989). "Symmetric Pass-Through of Tariffs and Exchange Rates Under Imperfect Competition: An Empirical Test", Journal of International Economics, 27:25-45.

Feenstra, Robert C. (1998), "Integration of Trade and Disintegration of Production in the Global Economy," Journal of Economic Perspectives, 12(4):31-50.

Feenstra, Robert C., Joseph E. Gagnon, and Michael M. Knetter, (1996), "Market Share and

23

Exchange Rate Pass-Through in World Automobile Trade," Journal of International Economics, 40:187-207.

Feenstra, Robert C. and Gordon H. Hanson (1996) "Foreign Investment, Outsourcing and Relative Wages," in R.C. Feenstra, S.M. Grossman and D.A. Irwin, eds., The Political Economy of Trade Policy: Papers in Honor of Jagdish Bhagawati, MIT Press, 89-127.

Goldberg, Linda S. (1993)"Exchange Rates and Investment in United States Industry." Review of Economics and Statistics, 75(4):575-588.

Gron, Anne and Deborah L. Swenson (1996), "Incomplete Exchange-Rate Pass-Through and Imperfect Competition: The Effect of Local Production," American Economic Review, 86(2):71-76.

Gron, Anne and Deborah L. Swenson (1998), "Cost Pass-Through in the U.S. Automobile Market," manuscript.Irwin, Douglas A. (1996), "The United States in a New Global Economy? A Century's Perspective," American Economic Review, 86(2):41-46.

Markusen, James R. (1995) "The Boundaries of the Multinational Enterprises and the Theory of International Trade." Journal of Economic Perspectives, 9(2):169-189.

Markusen, James R. and Anthony J. Venables, (1998), "Multinational Firms and the New Trade Theory," December, 46(2):183-203.

Rangan, Subramanian and Robert Z. Lawrence. (1993). "The Responses of U.S. Firms to exchange Rate Fluctuations: Piercing the Corporate Veil," Brookings Papers on Economic Activity, (2):341-72.

Roberts, Mark J., Theresa A. Sullivan and James R. Tybout, (1995) "Micro Foundations of Export Booms: Evidence from Colombia, Mexico, and Morocco." Pennsylvania State University Working Paper, December.

Slaughter, Matthew J., (1995), "Multinational Corporations, Outsourcing, and American Wage Divergence," National Bureau of Economic Research Working Paper # 5253.

Swenson, Deborah L. (1997) "Explaining Domestic Content: Evidence from Japanese and U.S. Auto Production in the U.S.," in Robert C. Feenstra (editor), The Effects of U.S. Trade Protection and Promotion Policies. Chicago: University of Chicago Press.

Zeile, William J. (1997), "U.S. Intrafirm Trade in Goods," Survey of Current Business, February, 23-38.

Table 1: Trends in Foreign Trade Subzone Usage, 1984-1995

Year No. of Value of Inputs %U.S. Inputs %U.S.

Subzones $Million Shipments

1984 26 13,098 76.4 89.3

1985 41 22,778 81.8 89.7

1986 51 37,548 81.7 91.3

1987 56 45,777 82.8 91.6

1988 59 54,382 81.1 90.5

1989 68 71,188 79.8 88.5

1990 82 85,298 83.1 89.7

1991 86 79,475 83.7 90.3

1992 105 85,897 85.1 88.6

1993 117 91,086 82.8 90.3

1994 131 111,435 83.5 88.4

1995 152 132,740 83.7 90.0Notes: Data based on Foreign Trade Zones Board Annual Reports and Author's Calculations. Datainclude Foreign Trade Subzone data, but exclude General Zone users. %US Inputs = [USInputs]/[Total Inputs]. %US Shipments = [US Shipments]/[Total Shipments]. Total Shipments = USShipments + Exports. The percentage calculations are weighted by zone input size.

25

___________________________________________________________________________

Table 2: NLS - Estimated Elasticity of Demand for Inputs___________________________________________________________________________

σi γi__________________

Auto Assemblers 2.732 0.252(.701) (.028)

Auto Parts 1.501 1.062(1.296) (.211)

Oil Refineries 6.341 1.931(2.460) (.684)

Food 3.725 0.703(2.635) (.260)

Shipbuilding 2.771 0.503(1.613) (.134)

Pharmaceutical/Chemicals 12.777 8.835(4.921) (7.049)

Appliances/Electronics 0.197 1.079(3.588) (.555)

Apparel 3.972 1.858(1.863) (.509)

TV's/Computers/Microwaves 4.003 0.910(1.285) (.179)

Heavy Machinery, Tractors, etc 2.584 1.874(1.461) (.431)

Other Manufacturing -1.015 1.043(1.594) (.239)

R2 0.81___________________________________________________________________________Notes: 974 observations. Estimation is based on equation (4'). Standard errors in ( ).

Table 3: The Effects of the Exchange Rate on Percent U.S. Input Usage - 1984-1995.Tobit Estimates: Dependent Variable, Percent U.S. Input Usage

Reale Age Age-Sq Industry Constant Obs Log-L

(1) -.3816a .0146 -.0026a Yes .7234a 974 -458.3 (.0913) (.0121) (.0010) *** (.0991)

(2) US-Owned -.3088a .0168 -.0036a Yes .6273a 644 -186.7(.0997) (.0126) (.0011) *** (.1044)

(3) Foreign-Owned -.3568b .0487c -.0039c Yes .9987a 138 -9.61(.1696) (.0247) (.0020) *** (.2172)

(4) No Auto -.4932a .0216 -.0038a Yes .8111a 603 -391.7 Assemblers (.1382) (.0176) (.0014) *** (.1411)

(5) EI .0221c -.0032a No .8646a 974 -461.5*** (.0121) (.0010) (.0819)

(6) EI .0148 -.0027a Yes .1951 974 -450.8*** (.0122) (.0010) *** (.2886)

(7) Including Industry- EI .0099 -.0025b Yes -2.5575 974 -429.0 Year Terms *** (.0121) (.0010) *** (2.4361) Notes: Standard Errors in Parenthesis. EI Indicates that the specification has interaction terms for the industry dummies with the exchangerate variable. EI results are contained in the following table which provides the remaining Table 3 results . *** Indicates that the set ofvariables is jointly significant at the 1% level. The letters a, b, and c denote statistical significance at the 1%, 5% and 10% levels,respectively.

27

Table 3 (Continued): The Effects of the Exchange Rate on Percent U.S. Input Usage - 1984-1995.

Tobit Estimates: Dependent Variable, Percent U.S. Input Usage

Exchange Rate Coefficients

Sector Specification (5) Specification (6) Specification (7)Auto Assemblers -.0679 -.3359a -.0246

(.0782) (.1279) (.1940)

Auto Parts -.5012a -.0697 -1.0159c

(.1036) (.2604) (.5335)

Oil Refineries -.9395a - .7079a .1834(.1861) (.2678) (.3839)

Food -.2760b -.3510 -2.9595a

(.1336) (.5679) (1.099)

Shipbuilding -.2124b -.4526 -.5204(.1022) (.3483) (.6319)

Pharmaceutical/Chemicals -.6877a -4.2003a .2142(.1242) (1.6243) (3.1544)

Appliances/Electronics -.5887a -.5941 1.6729(.1162) (.6302) (1.4938)

Apparel -.6039a -.7941a -.4962(.1009) (.3118) (.5703)

TV's/Computers/Microwaves -.3324a -.5318b -1.5759a

(.0925) (.2247) (.4624)

Heavy Machinery, Tractors, etc -.5516a -.4354 -.8930b

(.0908) (.2739) (.4195) Other Manufacturing -.5549a .2775 .7421

(.0973) (.3472) (.5501) Notes: Standard Errors in ( ). The letters a, b, and c denote statistical significance at the 1%, 5% and10% levels, respectively.

Table 4Actual and Predicted Values of US Input Usage, 1995

Industry % USInputs1995

µ-prd(1) µ-prd(1)10% $apprec

µ-prd(6) µ-prd(6)10% $apprec

Auto Assemblers .873 .802 .774 .791 .766

Auto Parts .363 .476 .452 .437 .432

Food .421 .611 .585 .602 .578

Shipbuilding .602 .722 .694 .729 .695

Pharmaceutical/Chemical .590 .344 .320 .445 .179

Appliances/Electronics .482 .361 .336 .377 .337

Apparel .541 .310 .285 .373 .312

TV's/Computers/Microwaves .551 .561 .536 .577 .541

Heavy Machinery .348 .308 .279 .308 .274

Oil Refineries .612 .474 .463 .502 .483

Other Manufacturing .410 .361 .334 .279 .299%-US Inputs 1995 is the actual percentage US inputs by industry for 1995. µ-prd(1) is the percentageUS inputs predicted for 1995, using the row(1) specification from Table 3. µ-prd(1) 10 % $ apprec predicts 1995 usage of US inputs if the dollar had been 10 % stronger. µ-prd(6) is the percentage US inputs predicted for 1995, using the row (6) specification ofTable 3. µ-prd(6) 10% $ apprec predicts 1995 usages of US inputs if the dollar had been 10%stronger.

Table 5: The Effects of Exchange Rate Exposure on Shipment VolumeDependent Variable: Total Shipments

Exposet-1 Real Excht-1 Industry Industry* Constant Obs Adj-R2

Dummies Exposet-1(1) .3774c --- -- 0.5991a 940 .003

(.1942) (.1577)(2) -.8561a 1.5209 940 .140

(.0760) (.0603)(3) -.9516a -.6427b --- --- 2.0664a 940 .146

(.0862) (.2763) (.2421)(4) -.3919a Yes --- 0.5477a 940 .452

(.0816) *** (.1482)(5) -.4022a -.5646c Yes --- 0.9985a 940 .454

(.0816) (.2970) *** (.2795)

(6) -.5362c Yes Yes 940 .458(.2971) *** ***

Exchange Rate Exposure Interaction Terms3 Indi*Exposet-1

Ind1 Ind2 Ind3 Ind4 Ind5 Ind6 Ind7 Ind8 Ind9 Ind10 Ind11-.8028a -.5013b -.0720 -.0624 .1142 -.0796 -.4336 -.0163 -.9033a -.3361 -.4643c

(.1879) (.2471) (.1717) (.4777) (.4893) (.3454) (.3087) (.3778) (.2761) (.3188) (.2524) Note: Standard errors in ( ). Ind1 = Auto Assembly, Ind2 = Auto Parts, Ind3 = Oil Refining, Ind4 = Food, Ind5 = Shipbuilding, Ind6 =Pharmaceutical/ Chemical, Ind7 = Appliances/Electronics, Ind8 = Apparel, Ind9 = TV's/Computers/Microwaves, Ind10 = HeavyMachinery/Tractors, Ind 11 = Unclassified Mfg. *** Indicates that the set of variables is jointly significant at the 1% level. The letters a, b,and c denote statistical significance at the 1%, 5% and 10% levels, respectively.

Footnotes

* I thank the IGCC and the Institute for Governmental Affairs at UC Davis for research support. Katherine Guthrie provided excellent research assistance. Bruce Blonigen, Rob Feenstra, DavidRiker and two anonymous referees provided helpful comments. All remaining errors are myown.Author: Assistant Professor, University of California Davis and National Bureau of EconomicResearch. Phone (530) 752-1569. Fax (530) 752-9382. Email deswenson@ucdavis.edu

1. Feenstra [1998] provides a survey and description of trends in international sourcing.

2. Slaughter [1995] examines this same data in aggregated form, and comes to a similarconclusion.

3. These papers use input-output tables and information on the relative size of import flowscompared with industry outputs to impute usage of imported intermediate inputs.

4. Markusen [1995] reviews this literature.

5. The level of sales lost by the firm will depend on changes to competitors costs as well, as inRoberts Sullivan and Tybout [1995]. Dornbusch [1987] and Feenstra, Gagnon, and Knetter[1996] discuss how similarity in cost structure influences the degree of pass-through ofexchange rate shocks.

6. In a related fashion, Campa and Goldberg [1995] find that the level of investment in U.S.industries is affected by external exposure to exchange rates changes both through exports andimported intermediate inputs. This paper differs from their analysis in two fundamental ways. First, since this paper is based on firm level data, I can directly observe firm decisions. Second,rather than assuming that all firms within an industry are similarly exposed to exchange rateshocks, I am able to measure individual firm exposure.

7. The Foreign Trade Zones program was created in 1934, and has been expanded in later years. Its primary benefit is the reduction of tariffs on imported intermediate goods. See Swenson[1997] for details. Those firms who successfully apply for and receive foreign trade subzonestatus are obligated to report the foreign and domestic composition of their inputs and shipments.

8. For example, suppose that firms purchase a fixed physical quantity of inputs from domesticand foreign sources. If U.S. dollar depreciation causes the dollar price of foreign inputs to rise,the reported value of foreign sourcing rises. In this context, the value of µft falls rather thanrising, as is predicted by the model in section 2.

9. Swenson [1997] describes the changes in Foreign Trade Zone operations. Because the foreigntrade zone program allows firms to choose whether to pay the tariff assessed on imported

intermediate inputs, or the final product tariff, on the product value that is attributable to foreigninputs, the program is especially favorable in situations of inverted tariffs. Ie: situations wherethe tariff applied to the final good is lower than the tariff that applies to the intermediate inputscontained in the final product.

10. Industry real exchange rates were constructed by taking Bureau of Labor Statistics data onindustry producer prices.

11. The regression R2 is 0.81.

12. Bergsten and Noland [1993] document differential efficiency effects of this type in theJapanese auto industry, while Swenson [1997] observes a similar effect in Japanese automobiletransplant production.

13. For the purposes of this paper, I adopt a geographical rather than ownership definition of"domestic" sourcing. Parts produced in the U.S., whether by U.S. or foreign-owned firms, areclassified as "domestic".

14. Since existing plants may apply for subzone status, it is possible that the physical age of theplant is greater than the number of years for which the plant has utilized subzone status.

15. A number of possible equilibria may emerge in this context. Work by Markusen andVenables [1998] shows that the resulting equilibrium is influenced not only by issues of industrystructure, such as the magnitude of transportation costs relative to fixed costs of additionalfacilities, but is also affected by factors that determine country comparative advantage, such asfactor endowments, and country size. Markusen [1995] describes the theoretical work in thisarea, and displays some instructive simulations. Brainard [1997] performs empirical analysis ofU.S. multinationals which describe the countervailing effects towards proximity orconcentration, and suggests that incentives operate on both dimensions. Caves [1996] provides acomprehensive survey of multinational firm decisions.

16. If the differences in input usage across industries are driven by increasing returns to scalemodel effects, the variables that are important at the industry level include the level oftransportation costs or the degree to which products in a particular industry are heavy, delicate, oreasily perishable. Since the data on foreign input usage does not report the product compositionof foreign purchases, I can not measure these effects directly or speculate on the particularsources of comparative advantage.

17. See Blonigen and Wilson [1996] for a discussion of industry factors which influenceArmington elasticities.

18. The sample includes a few international joint ventures. I do not include these observationsin rows (2) or (3), since they are not purely "domestic" or "foreign".

19. Domestic and Foreign subzone users differ in some respects. Foreign firms are present in

only 6 of the 11 industries (1,2,3, 7,9, and 10) and over half of the foreign observations are fromthe auto assembly and auto parts industries. The shipments profiles of foreign and domesticfirms are almost identical. In both cases, roughly 90% of shipments are sent to U.S. locations. However, foreign and domestic firms differ in their sourcing choices. The average domestic firmpurchases about 90% of its inputs in the U.S., while the typical foreign firm purchases only 59%of its inputs in the U.S. Because the sample of foreign firms is thin, I am not able to exploreforeign-domestic distinctions in more detail.

20. Whether either of these influences causes a shift in comparative advantage depends on thesize of the U.S. comparative advantage prior to the technology transfer or trade liberalization.

21. This specification provides a lower bound on the value of the exchange rate coefficients. Because the dollar generally depreciated over the interval of estimation, part of the exchange rateeffect will now be captured in the industry-trend terms.

22. Models, such as Casella and Rauch [1997], demonstrate the importance of information. Human flows including migration may inform buyers about potential purchasing opportunitiesthat would otherwise remain unknown.

23. Five indicator variables were added to denote whether the firm had a presence in each of thefollowing five markets: 1. North America, not including the U.S., 2. Europe, 3. South East Asia,4. Japan, and 5. South America. For each region the firm was classified as having a "presence" ifit had at least one affiliate in the region. Determination of affiliate activities was based onMoody's Corporate directories. Though most firms had more than one subsidiary in theselocations, the percentages which had at least 1 subsidiary in each of the following regions were,respectively, 96.5 for North America, 96.5 for Europe, 70.4 percent in South East Asia, 86.9percent for Japan, and 92.2 percent for South America.

24. Roberts, Sullivan and Tybout [1995], find that a firm's output or exports decline when itfaces cost shocks that are adverse relative to its competitors.

25. If input suppliers engage in pricing to market, this behavior will attenuate some of the costincreases induced by exchange rate shocks. Nonetheless, the prediction of a non-positiveresponse remains as long as dollar depreciation results in at least some increase in the cost ofimported inputs. Such an increase is likely because a substantial portion of trade is intra-firm innature, as documented by Zeile[1997]. In this context it is not sensible for firms to cut profitmargins on intra-firm input shipments to maintain market share, since the sales are conductedbetween related arms of the firm located in the U.S. and overseas.

26. The representative manufacturing firm imports 20 percent of its inputs. The direct of effectof the 10 percent dollar appreciation, due demand effects, is a 4.13 percent reduction in firmshipments, while dollar appreciation's cheapening of imported intermediate inputs increases firmshipments by 0.03 percent.