BLS WORKING PAPERS

U.S. DEPARTMENT OF LABOR

Bureau of Labor Statistics

 

OFFICE OF PRICES AND LIVING

CONDITIONS

The Behavior of Intrafirm Trade Prices in

U.S. International Price Data

Kimberly A. Clausing, Reed College

Working Paper 333

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.
The Behavior of Intrafirm Trade Prices in U.S. International Price Data

June 2000

Kimberly A. Clausing

Asst. Professor of Economics

Reed College

3203 SE Woodstock Blvd.

Portland, OR 97202-8199

U.S.A.

(503) 771-1112, x7388

email: clausing@reed.edu

Abstract: This paper analyzes data from the Bureau of Labor Statistics on international

prices between 1997 and 1999 in order to investigate the pricing patterns of intrafirm

trade. The results indicate several important ways in which intrafirm trade prices differ

from non-intrafirm prices. First, intrafirm trade prices appear to be influenced by the taxminimization strategies of multinational firms. There is a strong and statistically

significant relationship between countriesí tax rates and the prices of intrafirm imports

and exports exchanged with those countries. Second, intrafirm trade prices are typically

more correlated with exchange rate variables. Third, price changes for intrafirm trade

products are less frequent. Still, the overall price patterns for intrafirm trade are quite

similar to those for non-intrafirm trade. The average magnitudes of price changes are

comparable, and the patterns of price changes over time are also similar.
2

I. Introduction

Since 1971, the Bureau of Labor Statistics (BLS) has been charged with the

collection of international price data, which is used to compile import and export price

indexes. To collect this data, BLS economists survey firms to determine the prices of

given imported and exported goods, and how these prices change over time. In contrast

to the collection of producer prices, the collection of international prices includes price

information from substantial amounts of intrafirm transactions, or transactions between

different affiliates of the same multinational firm. If the data is to be representative of the

overall prices of U.S. international transactions, the inclusion of intrafirm trade is

absolutely necessary; intrafirm trade accounts for a large share -- approximately 40% --

of all U.S. international trade. Still, the inclusion of intrafirm trade raises some important

concerns.

To the extent that intrafirm trade behaves differently from arms-length trade, the

inclusion of intrafirm trade is likely to affect intrafirm trade indexes. Previous research

has often emphasized ways in which intrafirm trade may differ from arms-length trade.

For example, intrafirm trade may be influenced by the tax minimization strategies of

multinational firms, as demonstrated by Clausing (1998) and others. Intrafirm trade may

respond differently to exchange rate changes, as hypothesized by Rangan and Lawrence

(1999). In addition, intrafirm trade may differ from arms-length trade in other respects as

well. Some have hypothesized that intrafirm trade is more likely to be based on cost

factors than on market-based demand considerations. Further, to the extent that

multinational firms are different from other firms, one might expect that their trade

patterns would also differ.
3

This paper utilizes data from the BLS on international prices in 1997, 1998, and

1999 to undertake an empirical investigation of the pricing patterns of intrafirm trade.

There are two basic aims. First, the paper considers how BLS price indexes are

influenced by the inclusion of intrafirm trade. Second, the paper investigates more

generally the pricing behavior of intrafirm trade, in order to achieve an improved

understanding of how intrafirm trade may differ from trade conducted at arms-length.

Results indicate that intrafirm trade prices do differ from arms-length trade prices

in several important ways: these prices are more sensitive to tax variables, these prices

are typically more sensitive to exchange rate variables, and price changes for intrafirm

trade products are less frequent. That said, the overall pattern of price changes for

intrafirm trade is quite similar to the pattern for arms-length trade. Price changes are

typically of similar magnitudes, and follow similar paths over time. Hence it appears that

the inclusion of intrafirm trade in international price indexes is unlikely to affect overall

inferences based on U.S. international price data. This is reassuring since the inclusion of

intrafirm trade in such indexes is warranted due to its quantitative importance in U.S.

international trade.

II. Background

The Behavior of Intrafirm Trade

Before addressing the BLS methodology of collecting international price

information, it is useful to first discuss how intrafirm trade is likely to differ from trade

conducted at arms-length. In particular, what are the theoretical reasons to suspect that

intrafirm trade might behave differently empirically?
4

In a previous paper (Clausing (1998)), I have demonstrated that U.S. intrafirm

trade flows appear to be affected by the tax minimization strategies of multinational

firms. In particular, the evidence suggests that the United States has less favorable

intrafirm trade balances with low tax countries. This result is anticipated if multinational

firms are manipulating transfer prices in order to shift income to low tax countries. For

example, there would be an incentive to underprice U.S. intrafirm exports to low tax

countries and overprice U.S. intrafirm imports from such countries, following the

opposite strategy with respect to transactions with high-tax countries.

Following Horst (1971) and Kant (1995), one can produce a simple model that

generates the prediction that intrafirm trade prices will be affected by the tax

minimization strategies of multinational firms. Consider a multinational firm with some

degree of market power that is operating in two countries. It produces and sells in each

country, and also exports part of its output from the home country (1) to the affiliate

abroad (2).1 For now, assume that the affiliate is fully owned.2

Profit functions for operations in the two countries are given by the following

equations:

 π1 = R1 (s1) ñ C1 (s1 + m) + pm (1)

 π2 = R2 (s2) - C2 (s2 - m) - pm (2)

π1 is profit in the home country, which depends on revenues R1 that are a function of

sales, s1, and costs C1 that are a function of production. Production includes both those

 

1

It is straightforward to extend this model to consider trade that originates in the affiliate country. One can

also consider this trade to be in intermediate products without affecting the basic insights developed here.

2

The implications of relaxing this assumption are considered in Kant (1995) and briefly discussed below.
5

goods sold at home, and those sent to the affiliate abroad, m. The output that is exported

to the affiliates abroad is given the transfer price p.

Consider the case where tax rates at home are greater than tax rates abroad (t1>t2)

and deferral is allowed. Let f represent the fraction of profits that are repatriated. The

effective tax rate on income earned in the affiliate country is then:

 t2

e

 = t2 + (t1 - t2) f (3)

The net profit function for the firm's global operations is:

π = (1-t1) π1 + (1-t2

e

) π2 (4)

To illustrate how the firm may choose a transfer price in order to maximize these net

profits, consider the derivative of (4) with respect to the transfer price, p.

 πp = (1-t1) m - (1-t2

e

) m (5)

Substituting for t2

e

 using (3) and rearranging,

 πp = -(t1-t2) (1-f) m (6)

So, if t1>t2, the above expression is negative, and the firm's net profits decrease with the

transfer price. Thus, firms have an incentive to underprice goods sold to low tax

countries in order to shift profits to low tax locations. Similarly, one can show that firms

have an incentive to overprice goods sold to high tax affiliates when t2 > t1.

3

 4

 

3

Note that these models implicitly assume that there is only one transfer price p; that is, firms keep just one

set of books. Firms in reality may keep more than one set of books, using one set of prices to minimize tax

liabilities and other sets of prices for other purposes such as determining the relative performance of

affiliates.

4

 As Kant (1990) reminds us, though, two considerations may interfere with this motivation. First of all,

firms may be subject to penalties if their manipulation of transfer prices is too flagrant. If the probability of

receiving a penalty increases as the transfer price is further from the arms-length price, firms will likely

choose a transfer price that balances the gain from profit shifting with the possibility of a penalty. This

consideration alters the degree of transfer price manipulation, but would not alter the desired direction of

underpricing or overpricing. Second, affiliates may not be wholly owned. This creates a second profit
6

This model suggests one dimension in which intrafirm trade may behave

differently from arms-length trade.5 Putting aside tax considerations, there is no reason

to assume that intrafirm trade will be similar in all other respects, given the literature on

multinational enterprises, which has emphasized several special characteristics of these

firms. For instance, the OLI paradigm (described in more detail in Caves (1996)) stresses

that multinational firms arise due to ownership, location, and internalization advantages.

These advantages make it optimal to undertake activity within one multinational firm

rather than among separate, national firms. Depending on oneís perspective, such

advantages may enable multinational firms to respond more quickly or with greater

magnitudes to changes in economic variables. For instance, Rangan and Lawrence

(1999, p.14-15) argue that :

Multinationals with foreign facilities are likely to have an advantage. Even the

routine operation of those facilities generates a set of business relationships, a

continually replenished stock of information about actual prices, and detailed

knowledge about the existence, location, and precise needs and capabilities of

buyers and suppliers in that region. Hence, the multinational is conferred with

privileged access to valuable information and connectionsÖ6

 

shifting incentive, as firms may choose to overprice shipments to affiliates to transfer profits to sources that

are wholly owned and away from partially owned sources. While this consideration may influence the

desired direction of transfer price changes, it also assumes that firms are free to manipulate transfer prices

without the need to be responsive to the profits of their minority interests.

5

 However, it is important to note that such models have direct implications about the price of intrafirm

trade transactions, but have less direct implications about the volumes of intrafirm trade. For instance, such

models may lead one to expect that intrafirm exports to low tax countries would be under-priced.

However, this need not imply lower volumes of intrafirm trade, since quantities of such trade may increase

at the same time that prices are lower. In fact, this is what one would expect. Since intrafirm trade can

generate tax savings, it is optimal for firms to increase the volume of such trade relative to its level in the

absence of such considerations. See Eden (1998, p.298). In addition, a low tax country may attract more

foreign direct investment in general, and this in turn would act to increase volumes of intrafirm trade with

such a country in both directions.

6

 For arguments about the greater responsiveness of multinational firms, see also Knetter (1993), Lipsey

and Kravis (1986), and Little (1986).
7

Or, it is possible that the large size of multinational enterprises would generate more

ponderous decision making processes, and inhibit the firmsí responsiveness to changes in

economic conditions. As multinationals invest in different countries, they may become

increasingly integrated with the local economy, and less likely to respond to changes in

economic variables rapidly.7

 Finally, some have argued that there is little reason one

would expect any difference between the behavior of intrafirm trade and trade conducted

at arms-length.8 9

 In addition, authors have argued that intrafirm trade prices are more likely to be

based on cost considerations than on market value, and that intrafirm trade prices are

likely to change less frequently and/or more dramatically. (See, e.g., Alterman (1997b),

p.16.) One might also suspect that intrafirm trade would be different in other respects.

For example, it may be the case that intrafirm trade would be possible in situations of

imperfect information where arms-length markets fail. For instance, the internalization

advantages that are part of the OLI framework emphasize the difficulties associated with

licensing proprietary information. In an environment of imperfect information, it might

be easier to transact some products within the firm than at arms-length. In addition, the

 

7

 For similar arguments, see Goldsbrough (1981), Little (1986), and Encarnation (1992).

8

 See, for example, Caves (1996, p.33).

9

 Rangan and Lawrence (1999) have undertaken work examining whether intrafirm trade responds

differently to exchange rate changes. They find that the trade of U.S. multinational firms is indeed

sensitive to exchange rate changes, especially if one adjusts for the industry composition of U.S.

multinational firms and if one considers how sourcing decisions respond to exchange rate changes. They

also hypothesize that intrafirm trade may respond more quickly to exchange rate changes than does armslength trade due to the informational advantages associated with the superior international networks of

multinational firms. Their empirical work finds support for this view.
8

product composition of intrafirm trade is likely to be different from arms-length trade,

including more intermediate goods and fewer final products.10

In summary, intrafirm trade may behave differently for at least three reasons.

First, it may be more sensitive to tax influences. Second, it may be more or less

responsive to changes in economic variables such as exchange rates. Third, the

composition of intrafirm trade could differ from that of conventional trade in ways that

would affect its behavior.

Intrafirm Trade and BLS Methodology

The International Price Program (IPP) of the BLS is charged with producing data

on the prices of U.S. international trade. The IPP collects monthly information on prices

for approximately 22,000 items, and uses this information to generate import and export

price indexes. The program publishes over 700 detailed and aggregate trade price

indexes. These indexes are used for a variety of purposes, including deflating trade

volume statistics, measuring inflation, performing elasticity studies, deriving terms of

trade indexes and real exchange rates, and forming trade contracts.

In contrast to the trade price indexes, the producer price index (PPI) normally

does not include goods that are being sold from one part of a firm to another. As

Alterman (1997a) explains, ìUnder the definition of a net output index, these so-called

intra-company transfers are considered out-of-scope of the PPI when the different

branches of the same company are considered to be in the same industry.î However, the

 

10 In a recent paper (Clausing, 2000), I have demonstrated that the empirical behavior of intrafirm trade in a

gravity equation model differs substantially from that of arms-length trade. First, the gravity model, long

the most empirically successful model of international trade flows, has far less explanatory power with

respect to intrafirm trade than with respect to arms-length trade. Second, most of the individual

coefficients in the model are substantially different with respect to the two types of trade.
9

export and import price indexes are meant to represent the universe of goods that are

traded, and hence include substantial amounts of intrafirm trade transactions. Given the

large share of U.S. international trade that is conducted within the firm (approximately

40%), the inclusion of intrafirm trade in these price indexes is surely necessary.

Still, prior to 1998, the IPP only included intrafirm transactions that were deemed

to be ìmarket-basedî or ìmarket-influencedî. This policy changed in February 1998,

however, when the IPP began including all intrafirm transactions. In mid-1998, the IPP

also began collecting information on the pricing method used for intrafirm transactions.

Firms are asked whether they use market-based pricing, cost-based pricing, or ìother,

non-market basedî pricing, but all types of intrafirm trade prices are used.

This methodology raises several important sets of questions. First, what influence

does the inclusion of intrafirm trade have on U.S. import and export price indexes?

While it is likely appropriate to include intrafirm trade in trade price indexes, are there

issues that one should be aware of in terms of how such indexes are affected by intrafirm

trade? Second, how useful is the distinction between ìmarket-basedî intrafirm trade and

other types? Do the prices of these types of trade behave differently? Is it appropriate to

include all types of intrafirm trade in trade price indexes?

III. Data Analysis

This paper will undertake an empirical analysis of BLS data on export and import

prices with the aim of addressing how the inclusion of intrafirm trade is affecting trade

price indexes, as well as the aim of understanding how intrafirm trade behaves more

generally. The following questions will be central to this analysis.
10

• Is there evidence of tax-motivated transfer pricing for intrafirm trade? In particular, is

there evidence that the prices of intrafirm trade goods are sensitive to the tax rates of the

countries with whom the good is traded?

• Does intrafirm trade appear to be more or less sensitive to exchange rate changes,

compared to arms-length trade?

• More generally, does the pattern of price changes differ for intrafirm trade? Do price

changes differ in size? Are price changes more or less frequent?

• Does one find different patterns for market-based intrafirm trade compared with other

types of intrafirm trade?

The analysis employs monthly data on trade prices over three years: 1997, 1998,

and 1999. Table 1 describes some of the key features of this data. There are over

425,000 observations of monthly prices. 33% of these observations are for exports, and

38% of observations are intrafirm trade. A wide variety of countries are included.

However, for the analysis that includes tax or exchange rate variables, data limitations

restrict the data set to observations from 54 countries;11 this restricted data set is the data

set described in Table 1.

Table 2 shows the first comparisons of intrafirm and non-intrafirm trade prices:

this table considers the average price changes for observations in the entire sample. For

intrafirm trade, the average year over year change in price of a good is -.013, or a fall in

price of 1.3%. This is quite similar to the average change in price for the sample of nonintrafirm goods, where the average fall in price is 1.1%. Considering instead the absolute

value of the change in price allows one to examine the average magnitudes of price

changes. Again, intrafirm trade is almost indistinguishable from non-intrafirm trade.

Goods traded intrafirm see an average year over year price change of 7.4%, compared
11

with an average price change of 7.5% for non-intrafirm trade. Somewhat larger

differences in price patterns stand out if we consider the frequency of monthly price

changes. For the sample of intrafirm goods, 40.8% of observations experience a monthly

price change. For non-intrafirm goods, price changes are more frequent; 45.1% of

observations indicate monthly price changes. When one divides the sample into exports

and imports, slightly larger differences are observed for the price change variables, and

intrafirm trade continues to exhibit less frequent monthly price changes.

The similarity in price patterns for intrafirm and non-intrafirm trade is also

demonstrated graphically in figures 1 and 2. Figure 1 shows the average monthly price

changes for all of the observations in the sample over the period January 1997 to

December 1999. Figure 1a shows both exports and imports, while figures 1b and 1c

show exports and imports separately. Several features of the data are of interest. First,

the price changes exhibit noticeable patterns over time. Second, price trends for intrafirm

and non-intrafirm trade are very similar, particularly for imports, but also for exports.

When these average trade price changes are used to create an index in Figure 2, the

overall similarities continue to stand out. The import indexes are quite similar, in

particular. Non-intrafirm export price changes appear to be slightly more volatile in the

first part of the sample, and appear to be greater during the last seven months of the

sample.

Table 3 shows the same information as Table 2, broken down by 2-digit SITC

industry. The sample-wide averages obscure a substantial amount of industry variation in

 11 In particular, there is data on tax information from the Bureau of Economic Analysis for this set of

countries; these are also the countries for which I have collected exchange rate data.
12

price patterns. While it is sometimes the case that price changes are similar for intrafirm

and non-intrafirm trade, this is not the case for all industries.12

Table 4 shows the share of observations that are intrafirm trade, by two-digit

SITC industry. For the entire sample, 38% of observations are intrafirm trade. However,

this figure masks important differences across industries. For example, for SITC industry

#54, or medicinal and pharmaceutical products, 65% of observations are intrafirm trade,

while 18% of the observations from the fruit and vegetable industry (SITC #05) are

intrafirm trade. Table 4 also shows the breakdown of observations by different types of

intrafirm trade: market-based, cost-based, ìotherî, and not classified. The later category

accounts for the majority of the intrafirm observations as this data was only collected for

items initiated into the BLS survey after mid-1998. Still, for those intrafirm goods that

are classified, one notices substantial differences in the percentage of intrafirm trade that

is market-based across industries.13

Table 5 also shows the same information as Table 2, but now breaks the data

down by type of trade to examine more carefully the differences in price behavior

between different types of intrafirm trade. We again find intrafirm price patterns that are

similar to non-intrafirm patterns. The average price change hovers just over zero for

market and cost-based intrafirm trade and near ñ1% for non-classified intrafirm trade and

non-intrafirm trade. The exception is intrafirm trade that is classified as something other

than market or cost based; this trade experiences larger price declines. In addition, these

ìotherî observations also experience larger average absolute changes in prices (13.3%)

 

12 Table 3 includes only those industries with more than 100 observations for all of the variables. Complete

tables of all industries are available upon request. However, one should be particularly wary of making
13

than the other categories of trade, where average price changes are between 7.3% and

8.6% for the entire sample.14

Larger differences stand out if one considers the frequency of price changes.

Intrafirm prices change less frequently, particularly when prices are cost-based or

something other than market or cost-based. 37% of cost-based observations indicate

monthly changes in price; 29% of ìotherî observations do. And even market based

intrafirm trade observations experience fewer price changes (41% of observations) than

non-intrafirm observations (45%).

Regression Analysis

After the above consideration of the data on intrafirm price changes, it appears

that (overall) intrafirm trade price behavior is not substantially different from nonintrafirm trade. In particular, price changes tend to be of similar magnitudes, and to

follow similar paths over time, even though prices do change somewhat less frequently

for intrafirm trade. However, we have not yet addressed the more subtle questions raised

above. For instance, even though the average price patterns may be similar, it is possible

that intrafirm trade reacts differently to changes in exchange rates or to tax influences.

In the following analysis, I have merged the BLS data on monthly product prices

together with data on monthly exchange rates, and data on tax rates across countries. The

monthly exchange rate data have been used to derive a monthly exchange rate index for

each country in order to see how exchange rates have influenced prices over this time

 

inferences regarding the differences in price patterns for the industries with few observations.

13 Industries with fewer than 300 (total) monthly observations are indicated with an asterix.

14 Dividing the sample into exports and imports, one observes similar price changes for intrafirm and nonintrafirm trade, the exception again being the ìotherî category. Again, average absolute changes in prices
14

period.15 In addition, I have included data on the effective tax rate of the

destination/origin countries gathered from the Bureau of Economic Analysis surveys on

U.S. direct investment abroad; this tax variable is generated using data from 1997 and

varies only across countries, not over time. The effective tax rate is calculated as the

foreign income taxes paid by U.S. affiliates in a given country divided to by their pre-tax

net income.16 17

Table 6 estimates regressions explaining the prices of products in the sample.

Separate regressions are estimated for intrafirm trade and non-intrafirm trade, and for

exports and imports.

ln (Priceit ) = α + β1 ln(Exchange Rate Indexit) + β2 ln(1-Effective Tax Rateit) + β3

Inputeit + β4 Linkit + β5 NoDollarit + βz Industry Dummies + υit

All variables except dummy variables are in natural logs; i indicates individual

products and t indicates months. Dummy variables are used for goods where the price

 

are near 7% for most categories, with the exceptions of market and cost based intrafirm exports and ìotherî

intrafirm imports, which experience larger absolute price changes.

15 I use monthly exchange rate data from the University of British Columbia web site

http://pacific.commerce.ubc.ca/xr/data.html. This page and the FX database software are © 1998-99 by

Prof. Werner Antweiler, University of British Columbia, Vancouver, Canada. Similar data on exchange

rates are also available from several other sources.

16 While using marginal tax rates is a theoretically superior alternative, using marginal tax rates in practice

is very difficult. First, it is harder to get comparable data for this sample of 54 countries. Second, the

published marginal tax rates are an imperfect proxy for the actual tax rates firms face since such rates do

not account for the many subtleties (tax holidays, ad hoc arrangements, special allowances, etc.) that

determine the true tax treatment of firms. In fact, several studies have shown that effective tax rates are

commonly quite different from statutory rates, often due to the provision of special tax incentives. See,

e.g., Buijink, et al, (1999).

17 I have checked the results of this analysis using two alternative tax variables. The first was an average

effective tax rate for the years 1993-1997, again calculated using BEA data. This average tax variable

should correct for any anomalies of 1997 that could be affecting the results. Second, I used a average

effective tax variable calculated by Altshuler et al. (1998) using data from U.S. corporate income tax

(5471) forms for 1992. In both cases, the results are quite similar using the alternative variables. This is

perhaps not surprising given the high correlation between these alternative variables (.93 and .79,

respectively) and the variable used here.
15

has been inputed, for goods where a ìlink priceî has been estimated18, and for goods

where the price is not expressed in dollars. In addition, dummy variables are included for

SITC 2-digit industries. Expectations regarding the coefficients are as follows.

Expected Sign Justification

β1 - As the dollar is stronger, export and import prices should both be

lower.

β2 IF<NIF for exports;

IF>NIF for imports

Prices of intrafirm exports should be lower than non-intrafirm

exports for low-tax countries (when (1-Effective Tax Rate) is high).

Prices of intrafirm imports should be higher than non-intrafirm

imports for low-tax countries.

β3 ? Inputed prices may be higher or lower than normal.

β4 + ? When link prices are estimated, prices may be higher or lower than

normal. An improvement in quality would generally raise prices.19

β5 ? When prices are not quoted in dollars, prices may be higher or

lower than usual.

βz + or - Prices are likely to vary by industry.

Results are in Table 6. For both exports and imports, intrafirm trade appears to be

more sensitive to variations in exchange rates. A dollar index that is one percent stronger

is associated with 1.5 percent lower intrafirm export prices and .73 percent lower

intrafirm import prices; for non-intrafirm trade, export prices are .56 percent lower and

import prices are .4 percent lower. Lower prices are consistently associated with

countries with low effective tax rates. (I have no good explanation for this finding.) For

exports, however, this association is larger (by a factor of 6) for intrafirm exports than for

 

18 Link prices are used by the BLS in the place of reported prices when survey items have changed. The

aim is to calculate a price at which the old item would have traded in the new time period. In the analysis

here, I use the non-link prices rather than the link prices, noting that the presence of link prices may lead to
16

non-intrafirm exports. This would be expected if multinational firms are more likely to

underprice goods sold to low tax countries in order to shift profit away from such

locations. For imports, the negative association is much larger for non-intrafirm goods

than for intrafirm goods. This could also support tax minimization incentives since

multinational firms would prefer higher prices on intrafirm goods purchased from low tax

countries.

In terms of other variables, results indicate that goods with inputed prices are

likely to have higher prices in the three cases where this variable is statistically

significant. Goods where a link price is available are likely to have higher prices.

Finally, goods that are not priced in dollars are also likely to have higher prices. All

specifications include industry dummies for industries at the SITC 2-digit level of

aggregation. These dummies are typically highly statistically significant, and they also

much improve the explanatory power of the regression as a whole.20

Table 7 shows regressions similar to those in Table 6, but now intrafirm trade is

estimated together with non-intrafirm trade. This approach leads to similar overall

conclusions but allows a clearer investigation of how intrafirm trade is different form

non-intrafirm trade. A dummy variable is included to indicate when trade is intrafirm. In

 

expected changes in the non-link prices. For example, if the quality of the good has improved, using the

normal price rather than a link price would lead to a higher observed price.

19 However, there are many other reasons for a link price including unit changes, discounts, or others.

20 Regressions is tables 6,7, and 8 all include industry dummies for industries at the SITC 2-digit level of

aggregation. It is also useful to consider industry dummies at an even more disaggregate level, such as 4

digit. This enables a comparison of prices, controlling for the (more finely classified) industry of the

product. One can then ask whether intrafirm trade within such industries behaves differently. With this

data, however, one runs into computer memory problems with such a large regression matrix and so many

observations. Therefore, I limited the analysis to one month of data at a time. Running the same baseline

regressions as reported in the text, I typically found quite similar results with the more disaggregate

industry dummy variables. This may ameliorate concerns that it is the industry composition of intrafirm

trade, rather than the intrafirm nature of such trade, that is driving these results.
17

addition, interaction terms are included to indicate whether, when trade is intrafirm, its

responsiveness to exchange rates or tax rates differs substantially. The equation

estimated is:

ln (Priceit ) = α + β1 Intrafirm Dummyit + β2 ln(Exchange Rate Indexit)+ β3 ln(1-

Effective Tax Rateit) + β4 ln(Exchange Rate Indexit)*Intrafirm Dummyit+ β5 ln(1-

Effective Tax Rateit)*Intrafirm Dummyit + β6 Inputeit + β7 Linkit + β8 NoDollarit +

βz Industry Dummies + υit

The coefficient β4 is expected to be negative if intrafirm trade is more responsive to

exchange rates, and positive if intrafirm trade is less responsive to exchange rates. If taxmotivated transfer pricing is important, the coefficient β5 is expected to be negative for

exports and positive for imports. In particular, intrafirm exports to low-tax countries

should have lower prices as multinational firms attempt to shift profits to such locations

whereas intrafirm imports from such low-tax countries should have higher prices.

Turning to the results, the coefficient on the intrafirm dummy variable indicates

that intrafirm prices are typically larger, controlling for the other variables in the

regression. All trade is associated with the exchange rate index variable in the

hypothesized direction: when the dollar is one percent more appreciated, this is

associated with export prices .62 % lower and import prices .42% lower. Intrafirm trade

is even more strongly associated with the exchange rate variable, particularly intrafirm

exports. A dollar exchange rate index that is 1% more appreciated is associated with a

further 1% reduction in intrafirm export prices and a further .34% reduction in intrafirm

import prices.
18

Lower prices again tend to be associated with countries with low effective tax

rates. However, for trade that is intrafirm, export prices are lower, while import prices

are higher. Both of these tax interaction terms are highly statistically significant. The

estimates indicate that a tax rate one percent lower is associated with intrafirm export

prices that are 1.3% lower and intrafirm import prices that are .60% higher, relative to the

tax effects for non-intrafirm goods.21 This is consistent with tax minimization incentives.

Other variables are similar to those in the previous specification: prices are higher when

the price is inputed, when a link price is present, and when the transaction is not

denominated in dollars.22

Table 8 shows regressions similar to those in Table 7. The only difference is that

the intrafirm trade variables are now separated into the different types of intrafirm trade:

market-based, cost-based, ìotherî, and non-specified. Controlling for other variables, the

intrafirm dummies indicate that these goods have higher prices than non-intrafirm goods,

with the exception of ìotherî intrafirm trade.

Again, intrafirm prices also appear to be more sensitive to exchange rate

differences. All of the coefficients on the exchange rate interaction terms are negative

and statistically significant, again with the notable exception of ìotherî. In terms of tax

sensitivity, the results again indicate that intrafirm exports to low tax countries tend to

have lower prices, and intrafirm imports from such countries tend to have higher prices,

with only one exception (ìotherî intrafirm imports). The tax interaction coefficients are

largest for cost-based intrafirm trade. For such goods, a tax rate one percent lower is

 

21 The tables show elasticities with respect to (1-Effective Tax Rate). In the text, I discuss the implied

elasticities with respect to the tax rate, which are calculated at the mean effective tax rate for the sample.
19

associated with intrafirm export prices that are 2.6% lower and intrafirm import prices

that are 1.3% higher, again relative to the tax effects for non-intrafirm goods.23 Other

results are similar to those reported in Tables 6 and 7.

Table 9 turns to an analysis of the frequency of price changes observed in the data

set. The probability of a monthly change in price is hypothesized to depend on whether

the item is traded intrafirm, how much the exchange rate has changed in the last month

and over the last six months, an interaction term that considers the effect of such changes

in the exchange rate when trade is intrafirm, and dummy variables that indicate if a price

is inputed during the months considered, if there is a link price present in the months

considered, or if the price of the item in question is not denominated in dollars. It is

expected that price changes will be more likely when trade is non-intrafirm, when

exchange rate changes are larger, when there is an inputed price, when there is a link

price, or when the price is not denominated in dollars. (If a good is denominated in

foreign currency, the dollar price will automatically change even if the foreign currency

price is constant since the exchange rate will typically change.)

Table 9 shows the results from probit regressions that estimate the probability of a

monthly change in price. The coefficients that are reported indicate the change in the

probability of the dependent variable (a change in price) given a change in the

independent variable. Consider first the export equation. The intrafirm coefficient

indicates that intrafirm exports are 8% less likely to experience a monthly change in price

 22 An alternative specification would be to include only those data that are not inputed in this analysis. This

produces coefficients on the other variables that are quite similar to those found here.

23Again, note that the tables show elasticities with respect to (1-Effective Tax Rate). In the text, I discuss

the implied elasticities with respect to the tax rate, which are calculated at the mean effective tax rate for

the sample.
20

relative to non-intrafirm exports. A greater change in the exchange rate, either in the

previous month, or in the previous six months, is associated with an increased probability

of a change in price. For intrafirm exports, the interaction terms indicate that a change in

price is even more likely given a change in the exchange rate. Goods with inputed prices

are 26% more likely to experience changes in price. Goods where a link price is reported

are also more likely to experience a price change, and goods reported in currencies other

than the dollar are 59% more likely to see a monthly change in their (dollar) price.

For the import equation, most results are quite similar. The one important

difference is that intrafirm imports are less likely to experience a monthly price change

in response to changes in the exchange rate than non-intrafirm imports. The final column

estimates imports and export together, and indicates that exports are less likely to see

monthly price changes than are imports, controlling for changes in the other variables.

A Case Study

Most of the above results indicate that intrafirm trade appears to be more sensitive

to exchange rates, with the exception of the import results for the above probit equations,

where it appeared that import price changes were less likely in response to changes in

exchange rates. In order to examine these relationships in a different light, I examined a

case study of price changes for goods traded with Japan during this time period, 1997 to

1999.

Figure 3 shows the price movements for trade with Japan, as well as the yen/$

exchange rate during this period. Price indexes are created from the average monthly

price changes for intrafirm and non-intrafirm trade. As shown, the yen/$ exchange rate

exhibited substantial changes during this period. From June 1997 to August 1998, the
21

dollar experienced a substantial appreciation, from a value of 114 yen to a value of 144

yen. From August 1998 until December 1999, the dollar depreciated steadily, although

not monotonically, from 144 yen to 102 yen.

Considering first Figure 3a, it appears that intrafirm trade responds with less

magnitude to these exchange rate shifts. During the dollar appreciation, prices fell more

sluggishly and did not fall as far; during the dollar depreciation, prices rose more slowly

and did not increase as much. Examining figures 3b and 3c, one ascertains quickly that

this pattern is more in evidence for imports than for exports. For imports, intrafirm prices

clearly respond to a lesser degree to exchange rate changes than do non-intrafirm prices.

For exports, however, no clear pattern emerges. During the initial dollar appreciation,

intrafirm price changes are quite similar to non-intrafirm price changes. During the

dollar depreciation, intrafirm prices appear to increase more rapidly than do non-intrafirm

prices.

Implications for BLS Methodology

As discussed above, the BLS currently includes intrafirm trade prices in the

construction of international trade price indexes by the IPP. While it is the current

practice of the IPP to include all types of intrafirm trade prices, prior to 1998, only those

intrafirm trade prices that were deemed to be market-based were included. The above

analysis is instructive for considering how these practices are affecting trade price

indexes.

Perhaps one should begin by stating that intrafirm trade should be included in

international trade price indexes, if for no other reason than the fact that intrafirm trade

accounts for a large fraction (currently about 40%) of all U.S. international trade. In
22

addition, it appears from the above analysis that the price patterns of this trade are quite

similar to those of non-intrafirm trade. In particular, year over year price changes are

quite similar for both types of trade, regardless of whether one considers average price

changes or the average absolute value of price changes. While intrafirm trade is

somewhat less likely to experience monthly changes in price (41% of observations

relative to 45% for non-intrafirm trade), the overall patterns of monthly price changes

illustrated in figures one and two indicate that differences between the pricing behavior

of intrafirm and non-intrafirm trade are neither large nor particularly systematic.

Nonetheless, the above generalizations are based on the entire sample of price

observations. When one considers more narrowly trade in particular industries or with

particular countries, larger differences may be evident. For instance, figure 3 illustrates

that price patterns for intrafirm and non-intrafirm trade with Japan differed during this

time period. Further, Table 3 indicates that there are some industries where price patterns

may be more different for these two types of trade. Thus, when considering more

detailed price indexes, it remains possible that intrafirm prices may experience different

patterns.

Turning to the types of intrafirm trade, it is clear from the above analysis that

ìother, non-market basedî intrafirm trade prices behave differently from the marketbased or cost-based intrafirm trade prices. Monthly changes in prices are less likely, and

the year over year price changes themselves are quite different. Further, in the regression

analysis, prices for this type of intrafirm trade behaved atypically.

The prices of market, cost-based, and unclassified intrafirm trade also displayed

differences from non-intrafirm trade. In particular, intrafirm trade prices were typically
23

more correlated with exchange rate levels, and were also shown to be consistent with taxminimizing behavior. Still, while these observations are interesting and important, and

may be particularly important for some countries or industries, the percent of the

variation in trade prices accounted for by these variables is quite small. In particular, if

one considers regressions similar to those in Tables 7 or 8 that only include intrafirm

variables (i.e., dummies and interaction terms), exchange rates, and tax rates, one finds

that these variables account for only between one and five percent of the total variation in

the dependent variable. In contrast, industry dummies and the other variables account for

substantially more variation.24

My summary recommendations for the IPP are as follows.

• Continue to collect and utilize price data from intrafirm trade transactions.

• Continue to collect information on whether transactions are intrafirm. This will

provide useful information for future study of these and other questions.

• Consider excluding those intrafirm prices where prices are neither market-based nor

cost-based. (This accounts for only approximately one quarter of one percent of trade

prices.)

• Particularly with respect to more detailed trade price indexes, be aware that intrafirm

trade may behave differently from arms-length trade. This may be particularly

important with respect to some stimuli, such as tax rate differences or exchange rate

changes.

 

24 Detailed results are available from the author upon request.
24

IV. Conclusions

This paper has analyzed data from the BLS on international prices between 1997

and 1999 in order to investigate the behavior of intrafirm trade prices. This research has

illuminated several important ways in which intrafirm trade prices differ from armslength prices. In addition, there are implications for the construction of international

price indexes by the BLS.

First, intrafirm trade appears to be influenced by the tax-minimization strategies

of multinational firms. In particular, there is a strong and statistically significant

relationship between a countryís tax rate and the prices of intrafirm imports and exports

transacted with that country. The estimates in Table 7 indicate that a tax rate one percent

lower is associated with intrafirm export prices that are 1.3% lower and intrafirm import

prices that are .60% higher, relative to non-intrafirm goods. As Table 8 indicates, these

tax effects are strongest for the intrafirm trade which is cost-based. For such goods, a tax

rate one percent lower is associated with intrafirm export prices that are 2.6% lower and

intrafirm import prices that are 1.3% higher, again relative to non-intrafirm goods.

Second, intrafirm trade prices are more correlated with exchange rate index levels

than are non-intrafirm trade prices. In particular, a stronger dollar is associated with

lower export and import prices, but particularly so for intrafirm exports and imports. The

estimates in Table 7 indicate that a 1% stronger exchange rate index (indicating a

stronger dollar) is associated with export prices that are .6% lower in general, but 1.6%

lower for intrafirm goods. Similarly, a 1% stronger dollar is associated with import

prices that are .4% lower in general, but .7% lower for intrafirm goods. Still, all evidence
25

does not indicate that intrafirm goods are more responsive to exchange rate changes.

When one considers the probability of a change in price, one finds that intrafirm export

prices are more likely to change in response to changes in exchange rates than are nonintrafirm export prices. Still, the opposite is true for import prices, where intrafirm

import prices are less likely to change in response to changes in exchange rates. This

same pattern is also in evidence when one considers a case study of price changes for

trade with Japan during 1997-1999, a period where the dollar first appreciated strongly,

and then depreciated, vis a vis the yen.

Still, when one examines the extent of variation in trade prices that is explained

by these variables (intrafirm dummies or interaction terms, exchange rates, and tax rates),

one finds that the overall explanatory power of these variables is relatively low. Further,

the overall price patterns for intrafirm trade are not very different from those for nonintrafirm trade. The average magnitudes of price changes are comparable, and the

patterns of such changes over time are also similar. Therefore, one should not

overemphasize the differences between intrafirm trade and non-intrafirm trade. While

there may be important differences at a detailed level, or with respect to some stimuli, the

overall behavior of intrafirm trade prices is quite similar to that of non-intrafirm trade

prices.

Therefore, the IPP should certainly continue to sample prices from intrafirm trade

transactions, and to include such prices in the subsequent construction of price indexes.

The one exception to be considered would be ìother, non-market basedî trade, where

prices appear to be substantially out of line with those of other goods.
26

References

Alterman, William. 1997a. ìAre producer prices good proxies for export prices?î

Monthly Labor Review. October. 18-32.

Alterman, William. 1997b. ìA Comparison of the Export and Producer Price Indexes

for Semiconductors.î Photocopy. July.

Buijink, Willem, et al. 1999. ìFinal Report of a Study on Corporate Effective Tax Rates

in the European Union.î April. photocopy.

Bureau of Economic Analysis. U.S. Direct Investment Abroad: Operations of U.S.

Parent Companies and Their Foreign Affiliates. 1997.

Bureau of Labor Statistics. 1999. International Trade Price Indexes and Seasonal

Commodities. Washington: U.S. Department of Labor.

Caves, Richard E. 1996. Multinational Enterprise and Economic Analysis. 2nd edition.

New York: Cambridge U P.

Clausing, Kimberly A. 1998. ìThe Impact of Transfer Pricing on Intrafirm Trade.î

NBER Working Paper no.6688 , forthcoming within U of Chicago Press volume.

Clausing, Kimberly A. 2000. ìThe Empirical Behavior of Intrafirm Trade in a Gravity

Equation Model.î Draft. March.

Eden, Lorraine. 1998. Taxing Multinationals: Transfer Pricing and Corporate Income

Taxation in North America. Toronto: U of Toronto Press.

Encarnation, Dennis. 1992. Rivals Beyond Trade: American versus Japan in Global

Competition. Ithaca: Cornell U Press.

Goldsbrough, David J. 1981. ìInternational Trade of Multinational Corporations and Its

Responsiveness to Changes in Aggregate Demand and Relative Prices.î International

Monetary Fund Staff Papers. 28(3). 573-99.

Horst, Thomas. 1971. The Theory of the Multinational Firm: Optimal Behavior Under

Different Tariff and Tax Rates.î Journal of Political Economy. 79(5). 1059-72.

Kant, Chander. 1995. ìMinority Ownership, Deferral, Perverse Intrafirm Trade and

Tariffs.î International Economic Journal. 9(1). 19-37.

Kant, Chander. 1990. ìMultinational Firms and Government Revenue.î Journal of

Public Economics. 42(2). 135-147.
27

Knetter, Michael M. 1993. ìInternational Comparisons of Pricing-to-Market Behavior.î

American Economic Review. 83(3). 473-86.

Lipsey, Robert E. and Kravis, Irving B. 1986. ìThe Competitiveness and Comparative

Advantage of U.S. Multinationals, 1957-1983.î National Bureau of Economic Research

Working Paper no. 3051. October.

Little, Jane Sneddon. 1986. ìIntra-firm Trade and U.S. Protectionism: Thoughts Based

on a Small Survey.î New England Economic Review. Jan/Feb. 46-51.

Rangan, Subramanian, and Robert Z. Lawrence. 1999. A Prism on Globalization:

Corporate Responses to the Dollar. Washington: Brookings Institution Press.

Rauch, James E. 1996. ìNetworks versus Markets in International Trade.î NBER

Working Paper no. 5617. June.

Zeile, William J. 1997. ìU.S. Intrafirm Trade in Goods.î Survey of Current Business.

February. 23-38.
28

Figure 1b: Average Monthly Price Changes, exports

-0.015

-0.01

-0.005

0

0.005

0.01

0.015

intrafirm non-intrafir

Figure 1c: Average Monthly Price Changes, imports

-0.01

-0.008

-0.006

-0.004

-0.002

0

0.002

0.004

0.006

intrafirm non-intrafir

Figure 1a: Average Monthly Price Changes, all trade

-0.01

-0.008

-0.006

-0.004

-0.002

0

0.002

0.004

0.006

intrafirm non-intrafir
29

Figure 2a: Monthly Price Movements, all trade, indexed

91

92

93

94

95

96

97

98

99

100

101

intrafirm non-intrafir

Figure 2b: Monthly Price Movements, exports, indexed

93

94

95

96

97

98

99

100

101

102

intrafirm non-intrafir

Figure 2c: Monthly Price Movements, imports, indexed

88

90

92

94

96

98

100

102

intrafirm non-intrafir
30

Figure 3a: Trade with Japan, monthly prices 

86

88

90

92

94

96

98

100

102

90

100

110

120

130

140

150

Non Intrafirm Intrafirm Exchange Rate, Yen/$

Figure 3b: Exports to Japan, monthly prices

84

86

88

90

92

94

96

98

100

102

90

100

110

120

130

140

150

Non Intrafirm Intrafirm Exchange Rate, Yen/$

Figure 3c: Imports from Japan, monthly prices 

86

88

90

92

94

96

98

100

102

90

100

110

120

130

140

150

Non Intrafirm Intrafirm Exchange Rate, Yen/$
31

Table 1: Descriptive Statistics

Number of Monthly Observations 426,670

% of Observations that are Exports 33.1

% of Observations that are

Intrafirm Transactions

 38.2

 Of which: MarketBased

11.1%

CostBased

5.6%

ìOtherî

0.7%

Not

Classified

82.6%

% Of Observations that are

Inputed

 42.0

% Of Observations where a link

price is available

 0.3

Mean Effective Tax Rate for

Observations in the Sample *

 32.1%

 (Standard Deviation = 14.2)

*This variable is defined and discussed on p.14 of the text.
32

Table 2: Price Changes for Intrafirm and Non-intrafirm Trade

Intrafirm Non Intrafirm

All Trade

% Change in Price,

Year over Year,

sample average

 -1.3 -1.1

Absolute Value of % Change in Price,

Year over Year,

 sample average

7.4 7.5

% of Observations with a Change in Observed Price,

month to month

 40.8 45.1

Exports

% Change in Price,

Year over Year,

sample average

 -0.2 -0.6

Absolute Value of % Change in Price,

Year over Year,

 sample average

 8.0 6.9

% of Observations with a Change in Observed Price,

month to month

 36.9 40.3

Imports

% Change in Price,

Year over Year,

sample average

-1.7 -1.4

Absolute Value of % Change in Price,

Year over Year,

 Sample average

 7.2 7.8

% of Observations with a Change in Observed Price,

month to month

 42.3 47.7

These figures indicate the average values for intrafirm and non-intrafirm trade, over the

entire sample. Data are from the Bureau of Labor Statistics.
33

Table 3: Price Changes for Intrafirm and Non-Intrafirm Trade,

by SITC industry

Imports

SITC

2 digit

industry

Change in Price,

year/year

Absolute Change in Price, year/year Observations with a Monthly

Change in Price

Intrafirm Non-Intrafirm Intrafirm Non-Intrafirm Intrafirm Non-Intrafirm

03 1% 0% 14% 14% 74% 77%

05 -6% -1% 15% 19% 56% 70%

11 1% 2% 1% 4% 34% 31%

23 -3% -17% 4% 18% 81% 82%

24 10% 10% 13% 13% 60% 78%

27 -3% -2% 6% 3% 30% 31%

42 0% 5% 9% 11% 89% 74%

51 -3% -2% 10% 11% 48% 44%

52 -4% -5% 13% 9% 39% 43%

54 -2% 3% 9% 7% 46% 50%

55 -3% -3% 8% 6% 64% 41%

57 5% 2% 12% 7% 40% 45%

58 -8% -2% 16% 6% 51% 49%

59 -7% -4% 13% 8% 33% 24%

62 0% -1% 4% 3% 34% 30%

64 -3% -5% 7% 8% 61% 48%

65 -1% -3% 3% 5% 40% 49%

66 0% 0% 4% 4% 49% 33%

67 -5% -8% 8% 10% 55% 58%

68 1% 1% 10% 14% 58% 84%

69 -3% -1% 8% 7% 43% 52%

71 -1% 0% 5% 5% 32% 40%

72 0% 2% 5% 6% 47% 45%

73 -1% 0% 4% 4% 37% 45%

74 1% -1% 7% 7% 39% 42%

75 -6% -8% 11% 12% 46% 54%

76 -2% -4% 5% 6% 29% 38%

77 -3% -2% 8% 9% 42% 48%

78 1% 2% 5% 6% 35% 42%

79 3% 1% 8% 3% 21% 24%

81 -7% 0% 8% 4% 49% 38%

82 -11% -3% 12% 4% 31% 46%

83 5% 1% 7% 5% 36% 44%

84 0% -1% 5% 4% 38% 35%

85 -1% -1% 3% 3% 65% 44%

87 -1% -1% 5% 5% 37% 38%

88 0% 0% 5% 4% 41% 41%

89 -2% -1% 5% 5% 40% 41%
34

Table 3: Price Changes for Intrafirm and Non-Intrafirm Trade,

by SITC industry (Continued)

Exports

SITC

2 digit

industry

Change in Price,

year/year

Absolute Change in Price, year/year Observations with a Monthly

Change in Price

Intrafirm Non-Intrafirm Intrafirm Non-Intrafirm Intrafirm Non-Intrafirm

01 15% 0% 23% 18% 85% 85%

03 14% 12% 26% 22% 78% 74%

04 -2% -5% 7% 9% 55% 42%

05 8% 3% 12% 23% 39% 69%

11 -4% 1% 4% 8% 35% 27%

23 -9% -5% 10% 6% 45% 42%

24 1% 1% 9% 10% 59% 63%

51 -2% -3% 9% 10% 36% 43%

52 2% -1% 8% 4% 31% 28%

54 -2% -3% 8% 9% 15% 18%

55 2% 2% 5% 4% 26% 29%

57 -1% -1% 5% 10% 35% 47%

58 -2% 0% 4% 4% 36% 48%

59 -2% -1% 7% 8% 33% 29%

62 19% -3% 23% 7% 77% 28%

64 -2% 0% 11% 7% 53% 47%

66 -3% 0% 9% 2% 27% 25%

67 -2% -7% 4% 7% 30% 42%

68 1% -1% 6% 12% 78% 78%

69 0% 0% 5% 6% 38% 37%

71 1% 1% 4% 4% 25% 18%

72 -2% 1% 7% 2% 41% 28%

74 0% 1% 3% 4% 25% 26%

75 -8% -3% 12% 6% 46% 47%

76 -2% -2% 7% 4% 29% 29%

77 -1% -2% 7% 8% 37% 37%

78 1% 0% 3% 2% 31% 35%

79 -2% -2% 8% 4% 37% 26%

84 -9% -4% 14% 9% 37% 26%

87 2% 1% 7% 3% 41% 27%

89 -1% 0% 7% 3% 30% 41%

(Note: These tables include only those industries with more than 100 observations for all

of the variables. Complete tables of all industries are available upon request. However,

comparisons of price patterns for the other industries are particularly difficult.)
35

Table 4: Share of Observations that are Intrafirm by SITC Industry

SITC IntraFirm

Market Cost Other n.a. SITC IntraFirmMarket Cost Other n.a.

All 38% 4% 2% 0.3% 32% 55 38% 2% 1% 0% 36%

00 30% 0% 0% 0% 30% 56 26% 1% 3% 0% 23%

01 20% 8% 1% 0% 10% 57 42% 2% 2% 0% 39%

02 37% 2% 0% 0% 36% 58 39% 2% 1% 0% 36%

03 19% 2% 0% 0% 17% 59 62% 6% 3% 0% 53%

04 20% 1% 9% 0% 11% 61 16% 1% 6% 0% 10%

05 18% 4% 4% 0% 11% 62 52% 2% 1% 0% 49%

06 39% 1% 3% 0% 35% 63 14% 2% 0% 0% 11%

07 18% 3% 2% 0% 14% 64 28% 5% 1% 0% 21%

08 18% 5% 6% 0% 8% 65 19% 3% 3% 0% 13%

09 70% 7% 9% 0% 54% 66 25% 5% 2% 0% 19%

11 17% 3% 1% 0% 14% 67 41% 7% 1% 0% 33%

12 19% 1% 0% 1% 17% 68 33% 6% 0% 0% 27%

21 33% 2% 0% 0% 32% 69 28% 4% 3% 0% 21%

*22 43% 0% 19% 0% 24% 71 41% 3% 3% 0% 35%

23 28% 1% 0% 1% 27% 72 50% 4% 3% 0% 44%

24 39% 2% 1% 0% 37% 73 51% 4% 1% 0% 47%

25 8% 2% 0% 1% 5% 74 39% 3% 1% 1% 34%

26 5% 2% 2% 0% 1% 75 58% 6% 3% 0% 50%

27 47% 10% 0% 0% 37% 76 52% 2% 1% 0% 49%

28 17% 5% 4% 0% 9% 77 50% 4% 2% 0% 43%

29 23% 6% 8% 0% 10% 78 41% 7% 4% 1% 30%

32 2% 0% 0% 0% 2% 79 54% 6% 11% 4% 34%

33 11% 0% 0% 0% 11% 81 24% 4% 0% 0% 20%

34 6% 0% 0% 0% 6% 82 21% 3% 2% 0% 16%

41 0% 0% 0% 0% 0% 83 26% 3% 0% 0% 23%

42 61% 27% 2% 0% 31% 84 16% 1% 2% 0% 13%

*43 88% 0% 0% 0% 88% 85 11% 2% 0% 0% 9%

51 39% 3% 1% 0% 34% 87 59% 7% 3% 1% 49%

52 44% 2% 0% 0% 42% 88 59% 12% 2% 0% 46%

53 61% 1% 8% 0% 52% 89 28% 5% 2% 0% 21%

54 65% 7% 3% 0% 56% *97 58% 22% 0% 0% 36%
36

Table 5: Price Patterns by Type of Trade

Market

Based

Cost Based Other Intrafirm

Not

Classified

NonIntrafirm

Trade

All Trade

% Change in Price,

Year over Year,

sample average

 0.4 0.4 -11.4 -1.4 -1.1

Absolute Value of % Change

in Price,

Year over Year,

 sample average

8.1 8.6 13.3 7.3 7.5

% of Observations with a

Change in Observed Price,

month to month

41.2 37.2 28.7 41.0 45.1

Exports

% Change in Price,

Year over Year,

sample average

 1.2 0.8 -3.5 -0.4 -0.6

Absolute Value of % Change

in Price,

Year over Year,

 sample average

11.9 9.5 6.9 7.7 6.9

% of Observations with a

Change in Observed Price,

month to month

40.1 36.3 25.5 36.7 40.3

Imports

% Change in Price,

Year over Year,

sample average

 0.1 -0.2 -13.5 -1.9 -1.4

Absolute Value of % Change

in Price,

Year over Year,

 sample average

6.8 7.6 15.0 7.2 7.8

% of Observations with a

Change in Observed Price,

month to month

41.7 38.0 30.5 42.7 47.7

This table shows the average value of the price variables for different categories of intrafirm trade

(market-based, cost-based, other, and not classified) as well as for non-intrafirm trade.
37

Table 6: Price Regressions, Separating Intrafirm and Non-Intrafirm Trade

Exports Imports

Independent

Variables

Intrafirm Non-Intrafirm Intrafirm Non-Intrafirm

Exchange Rate -1.544

 (.1114)

 -.5583

 (.0593)

 -.7303

 (.0596)

 -.4035

 (.0263)

1- Effective

Tax Rate

 -3.196

 (.1218)

 -.5086

 (.0801)

 -.7990

 (.0655)

 -1.971

 (.0394)

Inpute .1202

 (.0267)

 .1723

 (.0192)

 -.0279

 (.0180)

 .0356

 (.0118)

Link .6859

 (.1757)

 .6046

 (.1607)

 .3604

 (.1510)

 .2924

 (.1128)

No Dollar .4821

 (.0622)

 .0683

 (.0628)

 .0514

 (.0301)

 .2815

 (.0208)

Industry

Dummies

Yes Yes Yes Yes

# of obs. 44,646 90,575 113,711 162,175

Adjusted R2 .410 .399 .316 .379

F

Prob > F

470.3

0.000

863.5

0.000

835.4

0.000

1522.6

0.000

Note: All variables except dummy variables are in natural logs. Standard errors are in

parentheses.
38

Table 7: Price Regressions,

Intrafirm and Non-Intrafirm Trade Estimated Together

Independent Variables Exports Imports

Intrafirm Dummy 3.494

 (.6140)

 2.576

 (.2821)

Exchange Rate -.6170

 (.0590)

 -.4216

 (.0293)

1- Effective Tax Rate -.5201

 (.0792)

-2.080

 (.0440)

Intrafirm Dummy

*Exchange Rate

-1.020

 (.1275)

 -.3446

 (.0600)

Intrafirm Dummy

*(1-Effective Tax Rate)

 -2.737

 (.1402)

 1.261

 (.0717)

Inpute .1579

 (.0156)

 .0190

 (.0102)

Link .6286

 (.1206)

 .3534

 (.0925)

No Dollar .3364

 (.0442)

 .1759

 (.0175)

Industry Dummies Yes Yes

# of obs. 135,221 275,886

Adjusted R2 .381 .353

F

Prob > F

1188

0.000

2185

0.000

Note: All variables except dummy variables are in natural logs. Standard errors are in

parentheses.
39

Table 8: Price Regressions,

Including Different Types of Intrafirm Trade

Independent Variables Exports Imports

Market Intrafirm Dummy 9.453

(1.653)

 3.069

 (.6240)

Cost Intrafirm Dummy 3.174

(1.932)

11.85

(1.121)

ìOtherî Intrafirm Dummy -17.44

(10.15)

-1.035

(2.777)

Non-spec. Intrafirm

Dummy

 2.427

 (.6733)

 1.971

 (.3121)

Exchange Rate -.6167

 (.0590)

 -.4202

 (.0293)

1- Effective Tax Rate -.5175

 (.0792)

-2.077

 (.0440)

Mkt. Intrafirm Dummy

*Exchange Rate

-2.065

 (.3407)

 -.3807

 (.1302)

Cost Intrafirm Dummy

*Exchange Rate

-1.153

 (.3935)

-2.247

 (.2326)

ìOtherî Intrafirm Dummy

*Exchange Rate

 3.400

(2.133)

 -.0967

 (.5728)

Non-spec. Intrafirm

Dummy *Exchange Rate

-0.800

 (.1401)

 -.2232

 (.0652)

Mkt.Intrafirm Dummy

*(1-Effective Tax Rate)

 -.4611

 (.3573)

 1.411

 (.1613)

Cost Intrafirm Dummy

*(1-Effective Tax Rate)

-5.423

 (.4446)

 2.719

 (.2999)

Other Intrafirm Dummy

*(1-Effective Tax Rate)

-2.135

(1.201)

-6.425

 (.7869)

N-sp. Intrafirm Dummy

*(1-Effective Tax Rate)

-2.752

 (.1515)

 .2232

 (.0652)

Inpute .1629

 (.0156)

 .0209

 (.0102)

Link .6197

 (.1205)

 .3448

 (.0925)

No Dollar .3437

 (.0442)

 .1789

 (.0175)

Industry Dummies Yes Yes

# of obs. 135,221 275,886

Adjusted R2 .381 .354

F

Prob > F

1056

0.000

1940

0.000

Note: All variables except dummy variables are in natural logs. Standard errors are in

parentheses.
40

Table 9: Probit Regressions

Estimating the Probability of a Monthly Change in Price

Independent Variables Exports Imports All Trade

Intrafirm Dummy -.0886

 (.0047)

 -.0608

 (.0033)

 -.0673

 (.0027)

Absolute Value of Change in

Exchange Rate, last month

 .1978

 (.0896)

 .4313

 (.0667)

 .3448

 (.0531)

Absolute Value of Change in

Exchange Rate, last 6 months

 .1086

 (.0296)

 .2234

 (.0196)

 .1915

 (.0162)

Intrafirm Dummy

*Exchange Rate Variable

 .2880

 (.1525)

 -.4212

 (.0699)

 -.3203

 (.0576)

Intrafirm Dummy

*6 month Exchange Rate Variable

 .2666

 (.0546)

 -.3185

 (.0340)

 -.1391

 (.0279)

Inpute .2610

 (.0031)

 .2811

 (.0024)

 .2753

 (.0019)

Link .2713

 (.0217)

 .2823

 (.0160)

 .2798

 (.0129)

No Dollar .5872

 (.0054)

 .5678

 (.0024)

 .5751

 (.0022)

Export -.0414

 (.0021)

# of obs. 86,317 173,792 260,109

Psuedo R2 .094 .140 .127

χ2

Prob > χ2

10,410

0.000

32,829

0.000

44,170

0.000

Note: Coefficients reported are the change in the probability of the dependent variable (a

change in price) given a change in the independent variables, or dF/dx where F is the

probability function and x is the independent variable. However, for the dummy

variables, dF/dx is for a discrete change of the dummy variable from 0 to 1. Standard

errors are in parentheses.