Income Shifting from Transfer Pricing: 

Further Evidence from Tax Return Data 

by 

Michael McDonald* 

`Office of Tax Analysis 

U.S. Department of the Treasury
 

1500 Pennsylvania Avenue, NW 

Washington, D.C. 20220 

The views expressed in this paper are those of the author and do not necessarily represent those of 

the U.S. Treasury Department. 

* U.S. Department of the Treasury, Mike.McDonald@do.treas.gov 

OTA Technical Working Papers is an occasional series of reports on the research, 

models and datasets developed to inform and improve Treasury’s tax policy analysis. 

Views and opinions expressed are those of the authors and do not necessarily 

represent official Treasury positions or policy. 

be directed to the authors. 

and suggestions for revision and improvement. Comments are welcome and should 

distributed in order to document OTA analytic methods and data and invite discussion 

OTA Technical Working Papers are

OTA Technical Working Paper 2 

July 2008 
 

Income Shifting from Transfer Pricing: 

Further Evidence from Tax Return Data 

by 

Michael McDonald* 

OTA Technical Working Paper 2 

July 2008 

OTA Technical Working Papers is an occasional series of reports on the research, 

models and datasets developed to inform and improve Treasury’s tax policy analysis. 

Views and opinions expressed are those of the authors and do not necessarily 

represent official Treasury positions or policy. OTA Technical Working Papers are 

distributed in order to document OTA analytic methods and data and invite discussion 

and suggestions for revision and improvement. Comments are welcome and should 

be directed to the authors. 

Office of Tax Analysis 

U.S. Department of the Treasury
 

1500 Pennsylvania Avenue, NW 

Washington, D.C. 20220 

* U.S. Department of the Treasury, Mike.McDonald@do.treas.gov 

The views expressed in this paper are those of the author and do not necessarily represent those of 

the U.S. Treasury Department. 
Income shifting from Transfer Pricing: 

Further Evidence from Tax Return Data 

Abstract 

Abstract: The paper updates, modifies, and extends research by 

Grubert (2003) to investigate income shifting from intercompany 

transfer pricing. The analysis is based on theoretical and regression 

models developed in Grubert (2003). The models are modified slightly 

to capture the effects of “real” intercompany tangible, intangible, and 

services transactions (as opposed to interest ‘income stripping’ 

through intercompany or interbranch debt), and extended to 

incorporate data relating to cost sharing arrangements. Although 

some caution is required in interpreting the transfer pricing 

implications from the regression results, the empirical analysis 

generally supports concerns about potential non-arm’s length income 

shifting under current transfer pricing rules. 

1 
 

 

Introduction: Income Shifting Under the Arm’s Length Construct 

By definition, a multinational corporation conducts business and has an economic 

presence in more than one legal jurisdiction. Absent legal and tax considerations, 

territorial borders should not in themselves constitute barriers to the operations of the 

multinational group - notwithstanding that each of the associated enterprises of the 

multinational may be a legally distinct company in the jurisdictions in which it operates, 

the multinational maximizes worldwide profits by freely disseminating the sources of 

competitive advantage to members of the multinational group. In fact, any barriers to the 

effective exploitation of such competitive advantages would undermine the very rationale 

of the global operations of the multinational in the first place. “Transactions” between 

the associated enterprises involving tangible or intangible property, or the provision of 

services by one associated enterprise for another, are not market transactions, and 

therefore the pricing of such transactions – “transfer pricing” - is artificial and not in 

itself necessarily relevant to the maximization of global profits, since such internal 

transactions are zero-sum.1 

Of course, territorial borders imply different legal environments and dual or even 

multiple taxing rights over the income of the multinational group. Accordingly, 

intercompany transactions may have tax implications. When multi-jurisdictional taxation 

is introduced, the taxing jurisdictions should have at least two taxing objectives. First, 

double taxation, or the imposition of tax by more than one jurisdiction on the same 

1

 The artificiality of intercompany pricing of transactions is perhaps clearest in the case of a parent 

corporation with wholly-owned subsidiaries. However, even when ownership is less than total, if one 

corporation has effective control of associated enterprises, the transactions between the associated 

enterprises are still not market transactions; that is, transactions between independent entities. 

2 
 

 

 

income, should be avoided to the extent possible. Double taxation results in an 

impediment to cross border transactions and the movement of capital. Second, each 

taxing jurisdiction should tax an “appropriate” share of the profits of the multinational 

group. Determining such appropriate shares requires establishing prices on the 

transactions between the associated enterprises. 

Many countries have agreed to a standard for determining transfer prices for tax 

purposes: the arm’s-length principle. The arm’s length principle and its relevance to the 

taxing rights of the jurisdictions is established in the Organisation for Economic 

Cooperation and Development (OECD) Model Tax Convention: 

[Where] conditions are made or imposed between the two [associated] 

enterprises in their commercial or financial relations which differ from 

those which would be made between independent enterprises, then any 

profits which would, but for those conditions, have accrued to one of the 

enterprises, but, by reason of those conditions, have not so accrued, may 

be included in the profits of that enterprise and taxed accordingly.2 

(Bracketed words added for clarity). 

Fundamentally, the arm’s length counterfactual is itself a construct, although a useful one 

that facilitates achievement of the two taxing objectives. With respect to the first 

objective, economic double taxation is eliminated in theory, and hopefully minimized in 

practice, through a taxing principle that can provide the basis for mutual agreement 

between taxing jurisdictions on how the taxing rights on intercompany transactions 

2

 Article 9, paragraph 1 of the OECD Model Tax Convention on Income and on Capital. The United States 

uses identical language in the 2006 Model Income Tax Convention. 

3 
 

 

ultimately are determined or settled. For example, the OECD’s Working Party No. 6 

attempts to reach agreement on a myriad of technical transfer pricing issues in order to 

clarify the appropriate pricing of transactions. In doing so they also clarify (indirectly) 

the associated taxing rights in a way that minimizes double taxation relating to these 

intercompany transactions. The second objective – determining the “appropriate” taxing 

rights of each jurisdiction relating to the intercompany transactions – is inherently 

subjective. The arm’s length principle attempts to simulate the working of markets. 

Simulating a market-based pricing system is intuitively appealing to economists, because 

the market’s pricing mechanisms tend to result in an allocation of income commensurate 

with the economic contributions and competitive position of the respective participants. 

The United States implements the arm’s length principle through section 482 of the 

Internal Revenue Code and the associated regulations, which state in part: 

In determining the true taxable income of a controlled taxpayer, the 

standard to be applied in every case is that of a taxpayer dealing at arm’s 

length with an uncontrolled taxpayer. A controlled transaction meets the 

arm’s length standard if the results of the transaction are consistent with 

the results that would have been realized if uncontrolled taxpayers had 

engaged in the same transaction under the same circumstances (arm’s 

length result). However, because identical transactions can rarely be 

located, whether a transaction produces an arm’s length result generally 

will be determined by reference to the results of comparable transactions 

under comparable circumstances (see Treas. Reg. §1.482-1(d)(2) Standard 

of comparability). Evaluation of whether a controlled transaction 

4 
 

 

produces an arm’s length result is made pursuant to a method selected 

under the best method rule. 3 

Unfortunately, attempting to determine arm’s length pricing for transactions that are not 

arm’s length, and perhaps would not even take place at arm’s length, can be difficult in 

practice. The regulations recognize the difficult valuation issues involved, as reflected in 

the acceptance, in some circumstances, of a range of potential arm’s length results rather 

than a single point; in the detailed guidance on the functional analysis, analysis of 

contractual terms, analysis of risk, and the analysis of economic conditions as an 

analytical roadmap for determining the arm’s length counterfactual and its appropriate 

pricing; in the allowance of multiple year, rather than single year, analyses; and in the 

guidance on quantitative adjustments to enhance comparability and reliability. 

While “arm’s length” may be clear in concept, quantifying arm’s length is a challenge. 

Transfers of intangible property can be particularly difficult to value in practice. Some 

intangibles, such as rights relating to important patents, software, or proprietary expertise, 

may be the key source of competitive advantage to a multinational corporation, and 

accordingly not typically transferred between unrelated parties (i.e., there are no 

comparable uncontrolled transactions). One type of arrangement relating to intangible 

property is worth noting here: cost sharing arrangements (CSAs). A CSA is an 

agreement between related parties to share in the costs of developing an intangible in 

proportion to each participant’s share of anticipated benefits from the exploitation of the 

intangible to be developed. Under a CSA, each participant owns its appropriate share of 

3

 Treas. Reg. §1.482-1(b) (1) 

5 
 

 

 

the developed intangible property, and consequently no licensing payments or other 

remuneration are required once the intangible property is developed. Because one or 

more parties may contribute intangibles at the outset of the CSA arrangement, the other 

CSA participants must provide arm’s length remuneration for this contribution. This is 

called a “buy-in payment.” While a CSA ultimately results in dual or multiple ownership 

of intangible property without the need for cross-licensing or other intercompany 

remuneration, this does not mean that CSAs are meant to be a vehicle for non-arm’s 

length transfers of existing intangibles. In practice, it is the buy-in payment that ensures 

that CSAs are ultimately structured and priced at arm’s length. 

Particularly complex valuation issues arise under CSAs, in part from the structure of 

CSAs themselves. For example, the general section 482 guidance on valuing intangible 

property typically applies to existing (and thus currently exploitable) technology. In 

contrast, CSAs typically involve two different types of intangible property. The first type 

of intangible property is the envisioned (that is, not currently existing and therefore not 

currently exploitable) technology that is the very subject of the cost sharing arrangement. 

The second type of intangible property, the subject of the buy-in payment, is the existing 

intangible that is contributed by one or more of the cost sharing participants, whose value 

derives from the intangible’s contribution to the development of the envisioned 

intangible, rather than, for example, to the contributed intangible’s exploitation in its own 

right. Further, the second type of intangible property is often an “in-process” intangible 

that is not currently exploitable and therefore particularly difficult to value. 

6 
 

Thus, for intercompany transactions, and for transfers of intangible property in particular, 

valuation questions are often inherently difficult. This situation sometimes requires 

flexibility in determining appropriate valuation methods, which may invite broad ranges 

of “acceptable” arm’s length outcomes. In the real world, when significantly different 

tax regimes (e.g., tax rates) across taxing jurisdictions and the flexibility under U.S. rules 

in repatriating foreign profits to the U.S. are also considered, policy makers 

understandably are concerned about companies’ use of transfer pricing to shift income in 

order to achieve tax-advantaged results. 

The opportunity to manipulate intercompany prices is a function of both the relative 

value of the transferred property to the taxpayer’s business, and the difficulty in reliably 

pricing the transaction (which tends to support a wider range of practically “acceptable” 

arm’s length prices). At one end of the spectrum, the intercompany transfers of 

commodities that are a relatively minor input to the production process pose little risk of 

income shifting: the value of the transferred property is small relative to the operations 

of the business, and there tend to be readily available reliable comparable transactions 

that define the arm’s length price within a narrow, and not easily manipulable, range. 

On the other end of the spectrum, there is significant risk of income shifting from 

transfers of valuable intellectual property that are crucial to the core business of a 

taxpayer and that are difficult to value accurately. 

By this standard, CSAs may pose a risk of income shifting from non-arm’s length 

transfer pricing. In addition to the valuation and definitional problems discussed above, 

7 
 

CSAs often involve the key value-driving intangibles of a business. For example, it is 

not uncommon for CSAs to be for “future generations” of all products or licenses derived 

from the core technologies of a multinational group. With CSAs covering such a wide 

potential scope of activities, it is conceivable that multinational companies may 

effectively achieve the transfer of valuable intangibles to offshore locations for less than 

the full value required by U.S. law.4 

This paper investigates whether there is evidence from tax return data of such income 

shifting. The paper updates, modifies, and extends prior research in the economics 

literature to investigate income shifting from intercompany transfer pricing. The analysis 

is based on theoretical and regression models developed in Grubert (2003). The model is 

modified slightly to capture the effects of “real” intercompany tangible, intangible, and 

services transactions (as opposed to interest “income stripping” through intercompany or 

interbranch debt), and extended to incorporate data relating to CSAs. 

Caveat Lector 

Some caution is required in assessing income shifting from transfer pricing using 

company-level data. Transfer pricing is intrinsically fact-dependent. Whether and the 

extent to which there may be income shifting from non-arm’s length pricing of 

intercompany transactions sometimes can only be definitively determined at the very 

detailed level of the particular transactions under review, rather than at the level of a 

single company within a multinational group. There is some difficulty in drawing 

4

 Specifically, section 367(d) requires remuneration for transfers of intangible property from U.S. taxpayers 

to foreign corporations, and section 482 of the Internal Revenue Code, and the associated 482 regulations 

establish methods for valuing transfers of intangible property for arm’s length consideration. 

8 
 

 

inferences related strictly to transfer pricing solely from such aggregated data (that is, 

company-level data from hundreds or thousands of companies) for two reasons: 

First, apparent income shifting in the aggregate data may in fact be fully supportable 

when specific transactions are analyzed. For example, it might be observed that the 

controlled foreign corporations (CFCs) of U.S.-based multinational corporations (MNCs) 

operating in low-tax jurisdictions have significantly higher profitability (measured 

relative to sales)5 than the CFCs of these same U.S.-based MNCs operating in high-tax 

jurisdictions. For a particular multinational, however, this result may not necessarily be 

indicative of non-arm’s length pricing of intercompany transactions. For example, a CFC 

operating in a low-tax jurisdiction may have developed a particular technology itself (for 

example through the independent efforts of its R&D activities) from which it earns 

above-normal returns, while a CFC in a high-tax jurisdiction may undertake only lowvalue routine activities that warrant relatively low profitability at arm’s length (e.g., a 

similar level of profitability as that of unrelated companies undertaking similar functions 

and risks). Or MNCs may simply invest more in low-tax jurisdictions. The differential 

in profitability may be related to such differences in investment levels, as profitability 

tends to be related to capital intensity, all else being equal. As discussed below, the 

regression analysis used in this paper attempts to account for many of these factors. 

However, it would not be possible to isolate all of the factors other than transfer pricing 

that might explain the profitability patterns, so the implications of the regressions on 

income shifting from non-arm’s length pricing are necessarily indirect. 

5

 This measure of profitability is used throughout the paper. The rationale for using this measure is further 

discussed below. 

9 
 

 

 

 

 

Second, transfer pricing transactional detail may be “buried” within the broader financial 

data that are typically used for empirical analyses. There may be significant non-transfer 

pricing “noise” that hinders the ability to isolate transfer pricing effects, or to compare 

reliably the effects over time. For example, the “check-the-box” regulations issued in 

1997 resulted in greater use of hybrid entities. One type of hybrid entity is an entity 

disregarded as separate from its owners according to U.S. tax rules, even though it may 

be a corporation under foreign law. Under tax consolidation rules, the hybrid 

“disappears” as its profit and loss results are rolled up into the consolidated return of the 

parent/affiliate. Importantly, what disappear are “zero sum” intercompany (which 

become interbranch) transactions. The years examined in this report are 1996 (prior to 

the 1997 check-the-box rules), 2000, and 2002.6

 Although the impact of the check-thebox rules bear most notably on intercompany interest payments (which this analysis 

explicitly eliminates from consideration in order to isolate, to the extent possible, other 

transfer pricing effects), the use of disregarded entities may itself further encourage nonarm’s length pricing between foreign affiliates controlled by U.S. parents (see Altshuler 

and Grubert (2006) and Mutti and Grubert (2006)). Therefore, some caution is required 

in comparing 1996 and earlier years to 1997 and subsequent years. One reason is that 

under the filing rules of Form 5471, a CFC that checks the box to become a branch of 

other CFCs disappears from the tax file.7

 The “remaining” CFC may be in either a lowtax or high-tax jurisdiction. Another reason is that important transfer pricing regulatory 

6

 2002 and 2000 are the two most recent years of available data (components of the database are only 

compiled every other year). In addition, 1996 is included in order to benchmark the updated data to a prior 

analysis discussed below (Grubert(2003)). 

7

 This issue would be particularly troublesome if the empirical analysis employed a “panel” data analysis; 

that is, an analysis that tracked particular CFCs over time. 

10 
developments also affected years subsequent to 1996, for example the §1.482-7 cost 

sharing regulations. Attempting to disentangle the transfer pricing effects that may be 

due to the check-the-box regulations from those that may be due specifically to the new 

cost sharing rules is difficult. 

Notwithstanding the caveats discussed above, an examination of tax return data is useful 

in detecting and understanding patterns or relationships in the data that may point toward 

non-arm’s length pricing or income shifting among related companies. 

A Brief Review of Recent Literature 

A number of studies have undertaken empirical investigations of income shifting. These 

can be categorized based on the data sources used: 1) aggregated, country-specific data; 

2) firm-level data based on public (non-tax) filings of publicly traded companies, and 3) 

firm-level data based on tax and non-tax filings of U.S. multinationals and their CFCs. 

In the first category, Grubert and Mutti (1991) use aggregated country-level BEA data on 

U.S. multinationals’ affiliates to regress profit rates on local country statutory tax rates, 

while controlling for GDP growth, and conclude that the pattern of profitability in highand low-tax jurisdictions is consistent with income shifting behavior. Hines and Rice 

(1994) use country-level aggregated data of non-bank CFCs (i.e., treating all foreign 

affiliates in a country as if owned by representative U.S. parent firms), and find evidence 

of sensitivity of profitability to local country effective tax rates, adjusting for financial 

structure and capital employed. Clausing (2001) uses aggregated country-level BEA data 

11 
 

on intrafirm trade flows and shows that the intrafirm trade balance between the U.S. and 

its foreign affiliates, as well as intrafirm sales between foreign affiliates of U.S. MNCs, 

are related to effective tax rates in a manner consistent with, although not necessarily 

entirely explained by, income shifting.8 

In the second category, Harris et al. (1993) use cross-sectional firm-level panel data from 

the public filings of 200 U.S. manufacturing corporations to investigate how differences 

in U.S. taxes as a percentage of U.S. sales or assets relate to subsidiary operations in 

foreign tax jurisdictions. Taking into account company characteristics (e.g., R&D and 

advertising as proxies for intangible assets, interest expense, and number of employees), 

and using indicators on the presence of an affiliate in a particular low-or high-tax 

jurisdiction, they show evidence of income shifting out of or into the United States 

consistent with (that is, negatively correlated with) tax rate differentials between the 

United States and foreign jurisdictions. Harris (1993) uses firm-level data from public 

filings of U.S. and foreign corporations to investigate the effects from major capital cost 

provisions in the Tax Reform Act of 1986 whose theoretical effect would unambiguously 

increase the incentive to shift income and/or capital to the United States from foreign 

affiliates independent of relative tax rates. Taking into account company characteristics 

pertaining to the level of “flexible” expenses (e.g., R&D, advertising, interest expense), 

and investigated separately from the U.S. and foreign perspective, he shows evidence that 

multinational companies shifted more income into the United States after the Tax Reform 

Act of 1986, and that they did so quickly. Jacob (1996) uses similar data to extend Harris 

(1993) by accounting for the volume of intercompany transactions between firms. His 

8

 See also Keemsley “Comment” (2001). 

12 
 

analysis provides evidence that transfer pricing, rather than other factors, may explain the 

income shifting. 

In the third category, Grubert and Slemrod (1998) use firm-level tax panel data of U.S. 

multinationals with subsidiaries in a particular low-tax jurisdiction (Puerto Rico), 

supplemented by data from public filings of the U.S. multinationals. They investigate, 

through probability regression models (probit, tobit) the joint investment and income 

shifting choices available to multinational firms, and find evidence that a large fraction of 

U.S. investment in Puerto Rico is due to the income shifting opportunities (uniquely) 

available there. Grubert (2003), of which this paper is an extension, seeks, in part, to 

address the somewhat limited applicability of Grubert and Slemrod (1998) by extending 

the analysis across a more comprehensive spectrum of low-tax and high-tax foreign 

jurisdictions. He uses firm-level tax data of U.S. CFCs, each matched to U.S. parentlevel tax return data, and further supplemented with data from public filings of the U.S. 

parent. (A more detailed description of the data is provided below). The paper evaluates 

the correlation between pre-tax profitability and local country statutory tax rates, 

controlling for parent and CFC characteristics (e.g., CFC asset intensity, parent size, 

start-ups, and in particular the presence of intangible assets), and finds evidence of 

income shifting, primarily associated with industrial (rather than marketing) intangibles. 

The analysis is further extended to investigate and quantify the extent to which tax 

incentives to shift income increase the volume of related party transactions. 

Data 

13 
 

The data used in this analysis are derived from the corporate tax return (Form 1120) file 

for each of the years, merged with information from Form 5471 (an information return 

filed for each of the U.S. parent’s CFCs), and Form 1118 (by which a U.S. parent 

calculates its foreign tax credit for foreign taxes paid by its CFCs and branches). These 

tax return data were further matched, where possible, to financial data reported in public 

filings (e.g., SEC filings) of the U.S. parent. The sample is derived from the data for the 

7,500 largest CFCs because detailed information is only available for them. The sample 

is further restricted by excluding financial CFCs and loss-making CFCs, and by applying 

other financial screens to eliminate significantly outlying observations. 

CFC Profitability in High- and Low-Tax Jurisdictions 

A CFC is defined in the Code as a foreign company, more than 50 percent of which is 

owned by “U.S. shareholders” (defined as U.S. persons, including entities, that own at 

least ten percent of the voting power of the company). If a multinational group is 

systematically engaging in non-arm’s length pricing of intercompany transactions in 

order to facilitate purely tax-advantaged outcomes, we would expect to observe higher 

CFC profitability in low-tax jurisdictions and lower CFC profitability in high-tax 

jurisdictions, assuming other factors that affect profitability are equal. This section 

undertakes an investigation of CFC profitability based on tax return data for the years 

1996, 2000, and 2002. 

The incentives and mechanisms to shift income are available to U.S. corporations and 

their foreign affiliates, regardless of whether the transactions are between U.S. parents 

14 
 

 

and their CFCs, or between foreign-controlled U.S. corporations and their parents, or 

between foreign affiliates of U.S. corporations. The tax data used in this paper happen to 

relate to U.S. corporations and their CFCs, but the results can be interpreted more 

broadly. 

Figure 1 depicts the relationship between CFC profitability, measured by the ratio of 

operating profits to sales (or operating margin), and the statutory tax rate of the CFC 

jurisdiction.9 Operating profits are defined as pre-tax earnings excluding interest income 

and interest expense, but including royalty income and royalty expense. The measure is 

based on “earnings and profits” (E&P), which are intended to approximate “book” 

operating profits. This measure of pre-tax operating profits has the advantage of being 

defined consistently across the taxing jurisdictions in which the CFCs operate. By 

excluding interest flows, the measure captures real (“above the line”) activity, related to, 

for example, the flows of tangible, intangible, and services transactions between related 

and unrelated parties. Grubert (2003) discusses the rationale for using pre-tax, rather 

than post-tax, earnings to analyze potential income shifting. This operating margin 

measure has the further advantage of being a common “profit level indicator” when 

applying the comparable profits method under Treas. Reg. §1.482-5. Statutory tax rates 

are used rather than other measures (for example effective tax rates) because the shift of 

9

 An alternative measure could be return on investment. For example, one measure of profitability could be 

operating profits divided by operating assets. However, assets are valued for book purposes based on 

historical value rather than at current market value. In addition, the reporting of asset data on tax forms is 

historically not as reliable as income data reported on tax forms. Notwithstanding these shortcomings, the 

analyses undertaken in this paper do incorporate by proxy a return to the contribution of assets by including 

asset intensity as a regressor. The approach therefore allows this important economic contributor to CFC 

profitability to be taken into account, albeit imperfectly, so that ultimately the tax effects can be more 

reliably measured. 

15 
 

an additional dollar of income from one taxing jurisdiction to another would result in a 

change in tax equal to the difference in the marginal tax rates of the jurisdictions. The 

marginal tax rate is best captured by the jurisdiction’s statutory tax rate. 

Figure 1 depicts the relationship between operating margin and tax rates for all nonfinancial CFCs for each of the tax years analyzed. In general, the curves slope downward 

(although certainly not monotonically, notably in 1996), indicating an inverse 

relationship between pre-tax profitability and tax rates. For example, in 2002 the 

weighted average pre-tax operating margins were over 20 percent for CFCs operating in 

tax jurisdictions with a zero percent statutory tax rate, while the pre-tax operating 

margins were under 8 percent for CFCs operating in tax jurisdictions with statutory tax 

rates over 35 percent. 

Figure 1: CFC Profitability by Statutory Tax Rates: Non-financial CFCs 

0

5

10

15

20

25

0 10 20 30 40 50 60

Local country statutory tax rate (%) 

Operating Margin (%) 

1996 2000 2002

16 
 

 

In order to more carefully examine the relationship between CFC profitability and local 

country tax rates - in particular to capture as many of the non-transfer pricing factors as 

possible – a regression analysis is undertaken. 

Regression Analysis 

The regression analyses presented in Tables 1 through 4 are based on the model presented 

in Grubert (2003), updated through 2002 and supplemented to incorporate new transfer 

pricing-specific data. The dependent variable in the Table 1 regressions is the ratio of 

CFC pre-tax operating profits to CFC sales (that is, the dependent variable is the 

operating margin depicted in Figure 1). As discussed above, the dependent variable in 

these regressions is slightly different than the dependent variable in Grubert (2003), as 

Grubert’s income measure includes interest income and interest expense, and the analysis 

here excludes interest flows. As in Grubert (2003), a negative correlation between 

operating margins and the statutory tax rate, controlling for the other non-tax factors 

(which should have an independent effect on profitability), can be interpreted as 

providing evidence of possible income shifting through transfer pricing. 

Table 1: Non-Financial CFC Profitability 

Dependent Variable: Ratio of CFC operating profit to sales 

(T-statistics in parentheses) 

1996 2000 2002 

Independent 

Variables: 

Intercept .083 

(2.69) 

.115 

(5.22) 

.129 

(5.76) 

CFC Age < 5 years .024 

(2.74) 

.02 

(1.82) 

-.01 

(-1.21) 

CFC Age 5-15 years .015 

(2.42) 

.029 

(3.99) 

.02 

(2.89) 

17 
 

 

 

 

Parent R&D / Sales .224 

(1.28) 

.406 

(3.48) 

.219 

(1.86) 

Parent Advertising / 

Sales 

.112 

(1.28) 

.093 

(0.8) 

.06 

(0.44) 

Parent domestic 

profits / sales 

-.01 

(-1.7) 

.0001 

(1.09) 

-.0001 

(-.69) 

Local statutory tax 

rate 

-.109 

(-4.6) 

-.17 

(-6.23) 

-.216 

(-6.98) 

Log of parent sales .002 

(1.02) 

.001 

(0.39) 

.003 

(1.49) 

CFC assets / sales .045 

(20.93) 

.045 

(22.96) 

.033 

(16.92) 

Adjusted R2 .1779 .2354 .1574 

Mean of dependent 

variable .1445 .1645 .1585 

Number of 

observations 

2,290 2,047 1,953 

Turning to the non-tax factors in table 1, asset intensity (the regressor CFC assets / sales) 

not surprisingly had a positive and statistically very significant effect on profitability for 

all years. CFCs that were between five and fifteen years old also were statistically more 

profitable than older CFCs in all three years. Start-up CFCs (that is, CFCs under 5 years) 

were also more profitable than older CFCs in 1996 and 2000. Although this would be a 

surprising result for pure start-up CFCs, the data would also reflect mergers. Parent R&D 

intensity, a proxy for CFCs in intellectual property-intensive industries, not surprisingly 

had a positive and generally significant effect on profitability for all three years.10 The 

proxies for parent size (log of parent sales), parent advertising intensity, and parent 

profitability (parent domestic profits / sales) had an effect on CFC profitability that was 

generally not statistically significant, although generally with the expected sign. 

10 The coefficient was positive and significant at the 1 percent level and 7 percent level in 2000 and 2002, 

respectively and was positive, but only significant at the 20 percent level in 1996. 

18 
Turning to the tax related factor, Table 1 shows that, even when important non-tax factors 

are accounted for, higher local country statutory tax rates had a negative and statistically 

significant effect on the operating margin of CFCs. In fact, the coefficient increases 

significantly between 1996 and 2002, indicating a widening of the profitability disparities 

between high- and low-tax jurisdictions over that time. As discussed above, some 

caution is required in comparing 1996 to subsequent years. While the results nominally 

support income shifting that is increasing over time, this may not necessarily be the case. 

For example, to the extent that “surviving” CFCs after checking-the-box reside in low-tax 

jurisdictions, the income could be higher between 1996 and 2000 for reasons other than 

pricing manipulation. Of course, surviving CFCs could also be in high-tax jurisdictions, 

so the net effect is ambiguous. Also, note that the statutory tax rate parameter does 

become more negative between 2000 and 2002. The check-the-box rules were obviously 

applicable for both of these years, and so is not a differentiating factor. 

It is important to recall again that these results do not in themselves necessarily point to 

transfer pricing abuse as the underlying cause of the inverse relationship between tax 

rates and profitability. The data are aggregated beyond the transactional level necessary 

for such a determination, and in addition there were no transfer pricing specific regressors 

to evaluate. Nevertheless, because the analysis takes into account many non-transfer 

pricing economic factors that could affect profitability, the hypothesis that multinationals 

engage in non arm’s length pricing of intercompany transactions in order to facilitate 

purely tax-advantaged outcomes clearly cannot be rejected by the available data – in both 

19 
the pre- and post- check-the-box years. This result is consistent with the existing 

economics literature. 

As discussed above, information directly relevant to transfer pricing is not typically 

contained in the aggregated financial accounts of multinational corporations, nor is a 

clear trail of evidence relating to transfer pricing found on tax return information filed by 

multinationals, including Form 5471. In view of the limitations of the available data, it is 

only possible to draw transfer pricing inferences by ruling out as many non-transfer 

pricing factors as possible, as illustrated in Table 1. 

In order to address these data limitations, the IRS was asked in 2006 to undertake a 

survey of its International Examiners and economists in order to identify the 

multinational corporations that have in the past engaged in cost sharing arrangements 

(CSAs) or are currently engaged in CSAs with any of their CFCs. The survey 

information included the names of U.S. parent companies that have at least one CSA, the 

starting year of the CSAs identified, the names of the CFCs participating in the CSAs, 

and some information on audit activity of the CSAs. The survey does not include any 

detailed information on the CSAs themselves, such as the type of cost shared intangibles, 

the buy-in payments, or any financial information specifically associated with the CSAs. 

The survey cannot be considered comprehensive (that is, as capturing all CSAs) and, 

given the methodology, should be considered more reliable for more recent, rather than 

more distant, years. Nevertheless, such information might be useful in broadly assessing 

profitability across taxing jurisdictions comparing the CFCs of U.S. multinationals 

20 
 

 

engaging in CSAs with one or more of their CFCs with CFCs of U.S. multinationals not 

engaging in CSAs. 

Although these data allow the analysis to move a step closer towards the investigation of 

income shifting through specific transfer pricing transactions, the results of this analysis 

are not determinative, and should again be interpreted with some caution. The data 

identify U.S. parents that undertake CSAs, but the data do not provide the level of 

transactional detail necessary to make a more targeted assessment of CSAs under the 

Treas. Reg. §1.482-7 regulations, or to determine the extent to which the results are 

driven by the CSAs themselves. More work is needed to refine the analysis further. 

The regression model presented in Table 2 contains the same explanatory variables as in 

Table 1, but adds two explanatory variables related to CSAs. The first is a dummy 

variable that identifies all CFCs whose U.S. parent has been identified as engaging in 

CSAs.11 Note that this definition captures CFCs that may not themselves be explicit 

participants with their parent company in the CSAs. Including these non-participating 

CFCs is appropriate, since the effects of CSAs would typically impact the financial 

results of CFCs beyond those that are engaged in the legal arrangement. For example, a 

CFC that is a CSA participant may license the developed intangible to affiliated CFCs 

that are not themselves participants in the CSA, but whose financial results are 

11 For a given year, the dummy variable is ‘1’ only if the U.S. parent has been identified as having CSAs 

whose starting date predates the end of that tax year. For example, a parent whose CSA commences in 

1999 will be assigned a dummy of ‘0’ for 1996, and ‘1’ for 2000 and 2002. As discussed above, the ”nonCSA” control group is not a perfect measure, as it is theoretically possible that some parents involved in 

CSAs were not identified in the survey. However, given the fact that the data are comprised of only the 

largest CFCs, the potential under-identification is not likely to be significant. 

21 
nevertheless impacted by the CSA through the licensing or other payments they make. 

The second explanatory variable is the product of the local country statutory rate and the 

CSA dummy variable. This variable captures the incremental effect of the relationship 

between pre-tax profitability and tax rates for those CFCs whose parents engage in CSAs. 

The relationship between pre-tax operating profit and local country tax rates for CFCs of 

parents engaged in CSAs can be determined by summing the coefficient for “local 

statutory tax rate” and the coefficient for “local statutory tax rate times parent cost 

sharing status”. 

22 
 

 

 

 

Table 2: Non-Financial CFC Profitability Including Cost Sharing 

Effects 

Dependent Variable: Ratio of CFC operating profit to sales 

T-statistic in parentheses 

1996 2000 2002 

Independent 

Variables: 

Intercept .08 

(2.49) 

.12 

(5.42) 

.127 

(5.52) 

Parent cost sharing 

status 

.09 

(3.01) 

.02 

(0.56) 

.045 

(1.79) 

CFC Age < 5 years .02 

(2.66) 

.016 

(1.84) 

-.011 

(-1.22) 

CFC Age 5-15 years .015 

(2.49) 

.029 

(3.95) 

.022 

(2.97) 

Parent R&D / Sales .232 

(1.33) 

.39 

(3.36) 

.201 

(1.68) 

Parent Advertising / 

Sales 

.106 

(1.21) 

.08 

(0.72) 

.063 

(0.49) 

Parent domestic 

profits / sales 

-.005 

(-1.73) 

.0001 

(1.15) 

-.0001 

(-.6) 

Local statutory tax 

rate 

-.086 

(-3.44) 

-.17 

(-5.82) 

-.193 

(-5.59) 

LS tax rate * 

parent cost sharing 

status 

-.223 

(-2.88) 

.008 

(0.1) 

-.116 

(-1.5) 

Log of parent sales .002 

(0.82) 

-.0001 

(-0.06) 

.002 

(1.1) 

CFC assets / sales .045 

(20.98) 

.046 

(22.8) 

.033 

(16.8) 

Adjusted R2 .1840 .236 .1623 

Mean of dependent 

variable .1445 .1645 .1585 

Number of 

observations 

associated w/ CSAs 

201 263 343 

Number of 

observations 

2,290 2,047 1,953 

Turning first to the most recent year, 2002, CFCs whose parents engage in CSAs tend to 

be more profitable in general than other CFCs, with significance at the 7 percent level. In 

23 
 

 

 

 

 

 

 

 

 

addition, the coefficient on the CSA-tax rate variable has the expected sign (that is, these 

CFCs have higher profitability in low-tax jurisdictions and lower profitability in high-tax 

jurisdictions than their non-CSA cohorts), but the coefficient is not statistically different 

from zero at traditional confidence levels.12 

In the year 2000 analysis, the CSA-related tax coefficient is not statistically different 

from zero, indicating that multinationals engaging in CSAs do not exhibit more 

pronounced income shifting than the non-CSA cohort in that year. 

The results for 1996 are notable for two reasons. First, the CFCs associated with these 

multinational parents were significantly more profitable and had a significantly more 

negative correlation between pre-tax profits and local country tax rates than the non-CSA 

cohort, even when the non-tax factors affecting profitability are taken into account. 

Second, cost sharing arrangements prior to 1996 would correspond to CSA rules that predate the current Treas. Reg. §1.482-7 regulations.13 

12 The coefficient is significant at the 13 percent level. One factor not explicitly accounted for in this 

analysis is the possible influence of CSAs that are in early, unprofitable stages. This is addressed below. 13 The guidance provided in the regulations, effective for years 1968 through 1995, consisted of a single 

paragraph, which read, “Where a member of a group of controlled entities acquires an interest in intangible 

property as a participating party in a bona fide cost sharing arrangement with respect to the development of 

such intangible property, the district director shall not make allocations with respect to such acquisition 

except as may be appropriate to reflect each participant’s arm’s length share of the costs and risks of 

developing the property. A bona fide cost sharing arrangement is an agreement, in writing, between two or 

more members of a group of controlled entities providing for the sharing of the costs and risks of 

developing intangible property in return for a specified interest in the intangible property that may be 

produced. In order for the arrangement to qualify as a bona fide arrangement, it must reflect an effort in 

good faith by the participating members to bear their respective shares of all the costs and risks of 

development on an arm’s length basis. In order for the sharing of costs and risks to be considered on an 

arm’s length basis, the terms and conditions must be comparable to those which would have been adopted 

by unrelated parties similarly situated had they entered into such an arrangement. If an oral cost sharing 

arrangement, entered into prior to April 16, 1968, and continued in effect after that date, is otherwise in 

compliance with the standards prescribed in this subparagraph, it shall constitute a bona fide cost sharing 

arrangement if it is reduced to writing prior to January 1, 1969.” See Treas. Reg. §1.482-2A(d)(4). 

24 
To summarize, based on the results presented in Table 2, the evidence that CSAs have 

provided a possible means for more pronounced income shifting is somewhat mixed. 

However, the analysis above does not account for what might be called post-1996 “CSA 

vintaging” effects: Because the CSA regulations were substantially revised in 1996, it is 

possible that the data for a number of years after 1996 (possibly even as late as 2002) 

incorporate CSAs in their early stages. Since a CSA is an agreement to share costs – 

typically early-year research costs and buy-in payments – in order to exploit future 

envisioned intangibles, it would not be surprising for a CSA to experience operating 

losses in early years and operating gains (to the extent that the CSA is ultimately 

successful) only in later years. Accordingly, in those early years, the relationship 

between CFC profitability and statutory tax rates would tend to be positive, rather than 

negative, even for those CSAs that ultimately produce non-arm’s length income shifting. 

Thus, in order to more carefully assess the effects of the current Treas. Reg. §1.482-7 

cost sharing regulations on the data, some adjustment for this CSA vintaging effect is 

warranted. 

Tables 3 and 4 summarize the results from adjusting for CSA vintaging for 2002 and 

2000, respectively. In Table 3, the first column of results reproduces the results in Table 

2 for 2002, that is, a CFC is considered to be associated with CSAs if its parent has CSAs 

with starting dates in any year prior to the end of 2002. In the second column of results, a 

CFC is considered to be associated with CSAs only if its parent has CSAs with starting 

dates prior to the end of 1999. Thus, only CSAs that are at least three years old are 

25 
 

incorporated into the CSA dummy variables. In the third column of results, a CFC is 

considered to be associated with a CSA only if its parent has CSAs with starting dates 

prior to the end of 1996. Thus, only CSAs that are at least six years old are incorporated 

into the CSA dummy variables. 

26 
 

 

 

 

 

Table 3: 2002 Non-Financial CFC Profitability Including Cost 

Sharing Effects 

Dependent Variable: Ratio of 2002 CFC operating profit to sales 

T-statistic in parentheses 

CSAs prior 

to 2003 

CSA’s prior 

to 2000 

CSAs prior 

to 1997 

Independent 

Variables: 

Intercept .127 

(5.52) 

.126 

(5.46) 

.133 

(5.78) 

Parent cost sharing 

status 

.045 

(1.8) 

.051 

(1.81) 

.087 

(2.63) 

CFC Age < 5 years -.011 

(-1.22) 

-.01 

(-1.18) 

-.01 

(-1.17) 

CFC Age 5-15 years .022 

(2.97) 

.022 

(2.96) 

.022 

(2.94) 

Parent R&D / Sales .201 

(1.68) 

.216 

(1.82) 

.231 

(1.95) 

Parent Advertising / 

Sales 

.063 

(0.49) 

.062 

(0.48) 

.051 

(.40) 

Parent domestic 

profits / sales 

-.0001 

(-.6) 

-.0001 

(-.6) 

-.0001 

(-.55) 

Local statutory tax 

rate 

-.193 

(-5.59) 

-.193 

(-5.77) 

-.193 

(-5.92) 

LS tax rate * 

parent cost sharing 

status 

-.116 

(-1.5) 

-.147 

(-1.71) 

-.213 

(-2.11) 

Log of parent sales .002 

(1.1) 

.002 

(1.2) 

.002 

(0.78) 

CFC assets / sales .033 

(16.8) 

.033 

(16.8) 

.033 

(16.9) 

Adjusted R2 .1623 .158 .16 

Mean of dependent 

variable .1585 .1585 .1585 

Number of 

observations 

associated w/ CSAs 

343 292 203 

Number of 

observations 1953 1953 1953 

The results in Table 3 indicate that, when CSA vintaging is taken into account, CFCs 

associated with CSAs have higher profitability in low-tax jurisdictions and lower 

profitability in high-tax jurisdictions than their non-CSA cohorts, at statistically 

significant levels. The older the ”vintage” of the CSAs, the more pronounced are the 

27 
 

 

 

 

 

 

 

effects, both in magnitude and in significance. Thus, the data provide more evidence of 

incremental income shifting associated with CSAs than the model presented in Table 2. 

Table 4: 2000 Non-Financial CFC Profitability Including Cost 

Sharing Effects 

Dependent Variable: Ratio of 2000 CFC operating profit to sales 

T-statistic in parentheses 

CSAs prior 

to 2001 

CSA’s prior 

to 1996 

CSAs prior 

to 1994 

Independent 

Variables: 

Intercept .12 

(5.42) 

.12 

(5.51) 

.12 

(5.49) 

Parent cost sharing 

status 

.02 

(0.56) 

.03 

(0.9) 

.06 

(1.81) 

CFC Age < 5 years .016 

(1.84) 

.016 

(1.86) 

.016 

(1.8) 

CFC Age 5-15 years .029 

(3.95) 

.029 

(3.94) 

.029 

(3.95) 

Parent R&D / Sales .39 

(3.36) 

.40 

(3.45) 

.40 

(3.43) 

Parent Advertising / 

Sales 

.08 

(0.72) 

.08 

(0.65) 

.08 

(0.71) 

Parent domestic 

profits / sales 

.0001 

(1.15) 

.0001 

(1.17) 

.0001 

(1.19) 

Local statutory tax 

rate 

-.17 

(-5.82) 

-.17 

(-5.86) 

-.16 

(-5.64) 

LS tax rate * 

parent cost sharing 

status 

.008 

(0.1) 

-.002 

(-.03) 

-.08 

(-.89) 

Log of parent sales -.0001 

(-0.06) 

-.0001 

(-.19) 

-.0001 

(-.29) 

CFC assets / sales .046 

(22.8) 

.045 

(22.8) 

.045 

(22.72) 

Adjusted R2 .236 .237 .237 

Mean of dependent 

variable .1645 .1645 .1645 

Number of 

observations 

associated w/ CSAs 

263 187 164 

Number of 

observations 2,047 2,047 2,047 

28 
The results in Table 4 similarly show that, as in Table 2, the coefficients have the 

expected sign, but the results are not statistically different than zero. 

The regression analyses summarized in Tables 1 through 4 were also run on a CFC salesweighted basis, as shown in Tables 5 through 8. The sales-weighted regressions provide 

further insights into the more aggregated effects of potential CFC income shifting, as well 

as further adjustment for CFC size compared with the unweighted regressions. 

As in the unweighted regressions, the weighted regressions show significantly higher 

profitability in low-tax jurisdictions and lower profitability in high-tax jurisdictions, 

providing evidence of possible income shifting. The tax coefficients in Table 5 are 

similar in magnitude and significance to the tax coefficients in Table 1. 

With respect to the effects of cost sharing arrangements, the evidence from the weighted 

analysis– similar to the unweighted analysis – is somewhat mixed. As shown in Table 6, 

the CSA-related tax coefficient is not as pronounced or as significant in 1996 as in the 

unweighted regression (Table 2) - the CSA tax coefficient is significant at the eight 

percent level. For 2000, CFCs whose parents engage in CSAs were not statistically 

different than other CFCs. However, for 2002 the CSA-related tax coefficient shown in 

Table 6 is both more pronounced and more significant (at the one percent level) than in 

the unweighted regression. 

29 
With respect to accounting for CSA vintaging effects, Table 7 shows even more 

pronounced and significant results in 2002 for CSAs undertaken prior to 2000 than in the 

unweighted analysis. However, for CSAs undertaken prior to 1996 – corresponding to 

CSAs undertaken prior to the revised 1996 cost sharing regulations – the CSA tax 

coefficient is not statistically significant. With respect to 2000, Table 8 shows no 

evidence of incremental potential income shifting effects for CFCs associated with CSAs 

when vintaging is taken into account. 

Taken altogether, the results from the weighted and unweighted analyses show that the 

data are not inconsistent with the existence of possible income shifting. In addition, the 

analyses provide evidence – although not indisputable evidence – that CFCs whose 

parents participate in CSAs may engage in more aggressive income shifting. 

30 
 

 

 

 

 

Table 5: Non-Financial CFC Profitability 

Dependent Variable: Ratio of CFC operating profit to sales 

(T-statistics in parentheses) 

Weighted by CFC Sales 

1996 2000 2002 

Independent 

Variables: 

Intercept .121 

(3.92) 

.111 

(5.32) 

.097 

(4.44) 

CFC Age < 5 years .002 

(0.2) 

.008 

(1.08) 

-.01 

(-2.12) 

CFC Age 5-15 years -.003 

(-.48) 

-.002 

(-0.04) 

.02 

(2.67) 

Parent R&D / Sales .067 

(0.41) 

.551 

(5.52) 

.474 

(4.6) 

Parent Advertising / 

Sales 

.205 

(2.35) 

.198 

(1.81) 

.905 

(7.54) 

Parent domestic 

profits / sales 

.001 

(0.1) 

.0001 

(1.15) 

-.0001 

(-.86) 

Local statutory tax 

rate 

-.110 

(-5.27) 

-.202 

(-8.33) 

-.206 

(-7.2) 

Log of parent sales -.002 

(-1.29) 

.001 

(0.25) 

.002 

(0.11) 

CFC assets / sales .072 

(23.62) 

.055 

(24.25) 

.043 

(19.27) 

Adjusted R2 .2091 .2714 .2496 

Mean of dependent 

variable .1175 .1318 .1246 

Number of 

observations 

2,290 2,047 1,953 

31 
 

 

 

 

 

Table 6: Non-Financial CFC Profitability Including Cost Sharing 

Effects 

Dependent Variable: Ratio of CFC operating profit to sales 

T-statistic in parentheses 

Weighted by CFC Sales 

1996 2000 2002 

Independent 

Variables: 

Intercept .123 

(3.86) 

.115 

(5.31) 

.08 

(3.59) 

Parent cost sharing 

status 

.047 

(1.85) 

-.017 

(-0.83) 

.062 

(3.05) 

CFC Age < 5 years .002 

(0.18) 

.009 

(1.11) 

-.02 

(-2.62) 

CFC Age 5-15 years -.002 

(-0.42) 

-.0003 

(-.06) 

.020 

(2.79) 

Parent R&D / Sales .072 

(0.44) 

.544 

(5.44) 

.476 

(4.56) 

Parent Advertising / 

Sales 

.198 

(2.26) 

.195 

(1.75) 

.89 

(7.43) 

Parent domestic 

profits / sales 

.005 

(0.1) 

.0001 

(1.15) 

-.0001 

(-.9) 

Local statutory tax 

rate 

-.097 

(-4.45) 

-.22 

(-7.97) 

-.149 

(-4.49) 

LS tax rate * 

parent cost sharing 

status 

-.123 

(-1.75) 

.05 

(0.94) 

-.206 

(-3.31) 

Log of parent sales -.002 

(-1.44) 

.0004 

(0.21) 

.002 

(0.12) 

CFC assets / sales .073 

(23.55) 

.056 

(24.15) 

.043 

(19.49) 

Adjusted R2 .2096 .271 .2531 

Mean of dependent 

variable .1175 .1318 .1246 

Number of 

observations 

associated w/ CSAs 

201 263 343 

Number of 

observations 

2,290 2,047 1,953 

32 
 

 

 

 

 

 

Table 7: 2002 Non-Financial CFC Profitability Including Cost 

Sharing Effects 

Dependent Variable: Ratio of 2002 CFC operating profit to sales 

T-statistic in parentheses 

Weighted by CFC Sales 

CSAs prior 

to 2003 

CSA’s prior 

to 2000 

CSAs prior 

to 1997 

Independent 

Variables: 

Intercept .08 

(3.59) 

.08 

(3.45) 

.09 

(4.23) 

Parent cost sharing 

status 

.062 

(3.05) 

.077 

(3.58) 

.021 

(0.82) 

CFC Age < 5 years -.02 

(-2.62) 

-.02 

(-2.48) 

-.01 

(-2.15) 

CFC Age 5-15 years .020 

(2.79) 

.02 

(2.81) 

.02 

(2.69) 

Parent R&D / Sales .476 

(4.56) 

.491 

(4.73) 

.481 

(4.65) 

Parent Advertising / 

Sales 

.89 

(7.43) 

.916 

(7.64) 

.91 

(7.44) 

Parent domestic 

profits / sales 

-.0001 

(-.9) 

-.0001 

(-.94) 

-.0001 

(-.86) 

Local statutory tax 

rate 

-.149 

(-4.49) 

-.146 

(-4.5) 

-.196 

(-6.33) 

LS tax rate * 

parent cost sharing 

status 

-.206 

(-3.31) 

-.256 

(-3.86) 

-.07 

(-0.86) 

Log of parent sales .002 

(0.12) 

.002 

(0.17) 

.002 

(0.08) 

CFC assets / sales .043 

(19.49) 

.043 

(19.58) 

.043 

(19.27) 

Adjusted R2 .2531 .2546 .2491 

Mean of dependent 

variable .1246 .1246 .1246 

Number of 

observations 

associated w/ CSAs 

343 292 203 

Number of 

observations 1,953 1,953 1,953 

33 
 

 

 

 

 

 

Table 8: 2000 Non-Financial CFC Profitability Including Cost 

Sharing Effects 

Dependent Variable: Ratio of 2000 CFC operating profit to sales 

T-statistic in parentheses 

Weighted by CFC Sales 

CSAs prior 

to 2001 

CSA’s prior 

to 1996 

CSAs prior 

to 1994 

Independent 

Variables: 

Intercept .115 

(5.31) 

.122 

(5.69) 

.118 

(5.48) 

Parent cost sharing 

status 

-.017 

(-0.83) 

-.01 

(-.37) 

.003 

(0.13) 

CFC Age < 5 years .009 

(1.11) 

.009 

(1.17) 

.008 

(1.1) 

CFC Age 5-15 years -.0003 

(-.06) 

-.0003 

(-.08) 

-.0002 

(-.03) 

Parent R&D / Sales .544 

(5.44) 

.547 

(5.48) 

.547 

(5.48) 

Parent Advertising / 

Sales 

.195 

(1.75) 

.15 

(1.32) 

.167 

(1.49) 

Parent domestic 

profits / sales 

.0001 

(1.15) 

.0001 

(1.20) 

.0001 

(1.19) 

Local statutory tax 

rate 

-.22 

(-7.97) 

-.21 

(-8.16) 

-.204 

(-7.94) 

LS tax rate * 

parent cost sharing 

status 

.05 

(0.94) 

.08 

(1.15) 

0.2 

(0.39) 

Log of parent sales .0004 

(0.21) 

-.0004 

(-.21) 

-.0002 

(-.11) 

CFC assets / sales .056 

(24.15) 

.055 

(23.84) 

.055 

(23.87) 

Adjusted R2 .271 .272 .2711 

Mean of dependent 

variable .1318 .1318 .1318 

Number of 

observations 

associated w/ CSAs 

263 187 164 

Number of 

observations 2,047 2,047 2,047 

34 
Conclusion 

The arm’s length principle has proven its value as an effective tool in minimizing 

economic double taxation and in ultimately clarifying taxing rights associated with 

intercompany transfers. Nevertheless, the “arm’s length construct” can be difficult to 

evaluate, especially for transfers of valuable intangible property. The transfer of 

intangible property associated with cost sharing arrangements, especially buy-in 

payments, has proven particularly difficult to price appropriately. For these reasons, and 

based on the experience of the IRS in administering the transfer pricing rules, 

policymakers have expressed some concern that transfer pricing can be a tool to shift 

income inappropriately. This paper extends prior economic research to investigate 

whether tax return data of CFCs are consistent with income shifting. The paper modifies 

and updates Grubert (2003), and extends the empirical work to incorporate information 

on CSAs. While the ability to draw transactional transfer pricing inferences from tax 

return and CSA data is to some extent limited, the analysis demonstrates that the tax data 

are consistent with (although do not conclusively prove) the existence of potential income 

shifting from non-arm’s length transfer pricing. 

35 
References 

Altshuler, Rosanne, and Harry Grubert (2006), “The Three Parties in the Race to the 

Bottom: Host Countries, Home Countries, and Multinational Companies,” Tax Notes, 

February 27, 2006, pp. 979-992. 

Clausing, Kimberly A. (2001), “The impact of Transfer Pricing on Intrafirm Trade,” in 

International Taxation and Multinational Activity, edited by James R. Hines, Jr., 173-

194. 

Clausing, Kimberly A. (2006), “International Tax Avoidance and U.S. International 

Trade,” National Tax Journal 59(2), June 2006, pp. 269-287. 

Grubert, Harry and John Mutti (1991), “Taxes, Tariffs and Transfer pricing in 

Multinational Corporation Decision Making,” Review of Economics and Statistics 33: 

285-293. 

Grubert, Harry and John Mutti (2006), “New Developments in the Effect of Taxes on 

Royalties and the Migration of Intangible Assets Abroad,” NBER Working Paper. 

Grubert, Harry (2003), “Intangible Income, Intercompany Transactions, Income Shifting 

and the Choice of Location,” National Tax Journal 56(1) part 2, March 2003, pp. 221-

242. 

Grubert, Harry and Joel Slemrod (1998), “The Effect of Taxes on Investment and Income 

Shifting to Puerto Rico,” Review of Economics and Statistics 80: 365-373. 

Harris, David, Randall Morck, Joel Slemrod, and Bernard Yeung (1993), “Income 

Shifting in U.S. Multinational Corporations,” in Alberto Giovannini, R. Glenn Hubbard, 

and Joel Slemrod (eds.), Studies in International Taxation (Chicago: University of 

Chicago Press). 

Harris, David G. (1993), “The Impact of U.S. Tax Law Revision on Multinational 

Corporations’ Capital Location and Income-Shifting Decisions,” Journal of Accounting 

Research 31: pp. 111-140. 

Hines, James R., Jr., and Eric Rice (1994), “Fiscal Paradise: Foreign Tax Havens and 

American Business,” Quarterly Journal of Economics, 109: (February) pp. 149-182. 

Jacob, John (1996), “Taxes and Transfer Pricing: Income Shifting and the Volume of 

Intrafirm Transfers,” Journal of Accounting Research 34, pp. 301-312. 

Kemsley, Deen (2001) “Comment on ‘The impact of Transfer Pricing on Intrafirm 

Trade’,” in International Taxation and Multinational Activity, edited by James R. Hines, 

Jr., 194-199. 

36 
Mintz and Smart (2001), “Income Shifting, Investment and Tax Competition: Theory and 

Evidence from Business Taxation in Canada,” Journal of Public Economics, 88(6), pp 

1149-1168. 

Organisation for Economic Cooperation and Development (2005), Model Tax 

Convention on Income and on Capital. July. 

Slemrod, Joel (1990). “The Impact of the Tax Reform Act of 1986 on Foreign Direct 

Investment to and from the United States,” in Joel Slemrod (ed.) Do Taxes Matter? The 

Impact of the Tax Reform Act of 1986, pp. 168-197. 

US Department of the Treasury, Office of Tax Analysis (2002), “Corporate Inversion 

Transactions: Tax Policy Implications,” May. 

US Department of the Treasury, Office of Tax Policy (2000), “The Deferral of Income 

Earned Through U.S. Controlled Foreign Corporations,” December. 

37