Patent Regimes, Host Country Policies and the Nature of MNE Activities
Usha Nair-Reichert
Georgia Institute of Technology
and
Roderick Duncan
Charles Sturt University
Abstract
This paper provides useful insights in the debate regarding the relationship between
stronger patent rights, host country policies and multinational enterprise (MNE) activity
using panel data from US MNEs. It analyzes the impact of stronger patent protection on
the exports, local affiliate sales and licensing activities by explicitly modeling the joint
nature of the MNE’s decision making process in servicing a foreign market. The key
findings support the idea that the policy environment in the host country influences the
impact of stronger IPRs on US MNE activities during the period 1992 to 2000. A risky
environment in the host country appears on average to have a negative and significant
impact on unaffiliated exports and affiliate sales. Increased patent protection in high-risk
countries on average appears to reduce licensing, and increase unaffiliated exports,
suggesting a dominant monopoly effect of stronger IPRs in the former case and a
dominant market expansion effect in the latter case.
JEL Classification: Q10, Q17, F23, K33, O34.
Key words: patent protection, intellectual property rights, imitation, innovation, exports, affiliate
sales, licensing, R&D.
Address for correspondence: Usha Nair, School of Economics, Georgia Institute of Technology, Atlanta,
GA 30332-0615; Tel: (404) 894-4903; Fax: (404) 894-1890; E-mail: usha.nair@econ.gatech.edu
Roderick Duncan; School of Marketing and Management, Charles Sturt University, Bathurst, NSW 2795,
Australia; Phone: (02) 6338-4982; Fax: (02) 6338-4769; Email: rduncan@csu.edu.au
We would like to thank Janusz Mrozek, Amy Glass and the participants at the 2006 Western Economics
Association meetings, the 2006 EEFS conference, and the Emory Trade Workshop for their useful
feedback.
1. Introduction
In recent years, intellectual property rights (IPRs) have become increasingly significant in
many types of international transactions, and strengthening IPRs has become a key issue
in global trade negotiations.1 The goal of this paper is to address the following question:
to what extent does the host country policy environment matter when thinking about the
effects of stronger IPR protection? A review of the literature suggests that previous
empirical work on the impact of IPRs has focused largely on the monopoly and market
expansion effects of stronger IPRs and analyzed how the imitative capabilities of the
country influence the impact of stronger IPRs. The literature does not provide
unconditional arguments regarding the impact of stronger patent rights on trade, foreign
direct investment (FDI), and licensing. In particular, host-country specific collateral
factors, which often affect the impact and economic value of patent rights, have been not
been studied much in the empirical literature on IPRs.2 Maskus (1998) notes that it is
inadequate to analyze the implications of IPR systems without also considering their
position in the general regulatory structure.
There are a large number of theoretical models that assess the impact of
intellectual property protection on MNE activities in the host country, but the results of
these models vary a great deal depending upon the modeling assumptions (for example
Lai (1998) and Glass and Saggi (1999, 2002a, 2002b, 2002c), Yang and Maskus (2001),
Branstetter et al. (2007)). The theoretical models that consider the interactions between
the host country environment and intellectual property protection in assessing the impact
of stronger IPRs on MNE activities in the host country have largely focused on human
capital and openness. Vishwasrao (1994) uses a strategic partial equilibrium model to
argue that lack of patent protection may encourage FDI relative to licensing where there
are country-specific fixed costs of establishing a subsidiary in the host country. For
example, subsidiary production faces certain inherent disadvantages such as the fear of
expropriation and other political and economic risks. Branstetter et al. (2007) analyze
how the strengthening intellectual property rights in developing countries impacts the
level and composition of industrial development. They conclude that IPR reform in the
1
Total global high-tech trade in 2000 was US$998 billion, that is 20 per cent of manufactured goods and
services traded internationally (World Bank 2003). Global FDI inflows were US$651 billion in 2002;
$79.61billion was received in 2002 by way of technology and license fees; the number of patent application
filed by residents in 2001was 939,267 (Singh (2006)). The emergence of new technologies has also led to a
continuous evolution in the types of instruments used to protect IPRs. Examples of such advances are in
biotechnology and its applications to agriculture and pharmaceuticals, and in information technologies.
2
For example, a patent has greater monopoly power when there is an import quota on similar goods that
are close substitutes.
2
South leads to increased FDI from the North, as Northern firms shift production to
Southern affiliates.3 Rodrik (1991) suggests that “even moderate amounts of policy
uncertainty can act as a hefty tax on investment, and that otherwise sensible reform may
prove damaging if they induce doubts as to their permanence.”4
Empirical evidence on the impact of IPRs is also rather diverse.5 Despite the
importance of the host country policy environment in explaining the impact of patent
rights on trade, investment and technology flows, there is limited empirical evidence in
this regard. Most of the existing work has focused either on the interaction between IPRs
and human capital / technological capability or the openness of the economy to trade.
Among the papers analyzing the impact of IPRs the most relevant to the current work are
Maskus (1998) and Smith (2001). Maskus (1998) uses a simultaneous equation
framework to analyze the impact of IPRs on different types of commercial flows, namely
patent applications, sales, exports, and level of affiliate investment assets using data from
1989-1992. He finds that exports to affiliates are highly positively affected by patent
strength in developing economies. While the average patent strength has limited effect on
affiliate sales, the impact is significantly positive in developing countries. Smith (2001)
uses cross-sectional data for 1989 to analyze the impact of stronger IPRs on US
unaffiliated MNE exports, local subsidiary sales and licensing receipts of subsidiaries
from unaffiliated firms and indicates that strong patent rights increase US affiliate sales
and licensing, particularly in countries with strong imitative abilities. Related research
also suggests that the level of IP protection itself varies, depending on the technological
capabilities of the host countries. In short, there has been relatively little evaluation of
In this literature, “South” is an example of a developing country or technology importer, while “North” is
an example of a developed country or technology exporter.
4
Other interesting perspectives on this include Bhagwati et al. (1992) and Lall (1997). Bhagwati et al.
argue that the policy framework in the host country can be endogenous to FDI. “Quid pro quo FDI” may
occur in such a case, where FDI incurs a loss in period one to diffuse the threat of protection in period two;
this maximizes the two-period payoff from the inter-linked decisions on trade and investment. Lall (1997,
p.244) also offers an interesting perspective that a strong IPR regime may be interpreted as a signal
regarding the government’s overall attitude towards foreign investments and commercial activities.
5
Papers in this literature include Ferrantino (1993), Maskus and Eby-Konan (1994), Maskus and Penubarti
(1995), Gould and Gruben (1996), Lee and Mansfield (1996), Maskus (1998), Smith (1999, 2001), Yang
and Maskus (1999b) and Park (2002).
3
3
patent rights in conjunction with other international and domestic policies to assess their
full impact on a multinational’s mode of servicing a host country market.6
Saggi (2002) has pointed out that most of the literature discussed suffers from another
fundamental problem; either FDI or licensing is the only channel through which the
Northern firm can produce in the South. A more sophisticated analysis of the
consequences of strengthening patent rights in the South requires that we consider all of
the MNE’s options (trade, FDI and licensing) jointly. Most of the existing empirical
studies, with the exception of Maskus (1998), have not adequately captured the joint
effects of MNE activities over time, as they are based on single equation studies, cross
sectional analysis, or time-averaged data.
This paper builds on the Maskus (1998) and Smith (2001) papers. It develops a
theoretical framework and empirically evaluates the interactive effects of multiple
institutions and polices, including IPRs on MNE activities. It differs from the earlier
papers in that it focuses on the role of the host country policy environment and its impact
on the influence of stronger IPRs in facilitating the process of internationalization of
technology transfer, investment, and trade. The analysis also uses panel data for the years
1992-2000 and a simultaneous equation framework to account for the fact that the
decision by a firm to export a patentable product is jointly determined with decisions to
service the market through licensing or FDI, as was done in Horstmann and Markusen
(1987) and also Maskus (1998). The key findings indicate that the policy environment in
the host country influences the impact of stronger IPRs on US MNE activities during the
period 1992 to 2000.
The rest of this paper proceeds as follows. Section 2 presents the basic model and the
propositions that are being tested. Section 3 presents the empirical analysis and section 4
summarizes the key conclusions and policy implications.
2. Theoretical Framework
This section develops a framework to examine how the host country policy
environment and patent protection jointly affect the MNE’s mode of entry into a foreign
Our focus here is only on empirical papers that address the issue of how a multinational’s mode of
servicing a market is influenced by IPRs in the host country.
6
4
market through exports, FDI or technology licensing to the host country. 7
The
assumptions of the model are similar to those in a standard North-South framework. An
MNE in the North invents a new technology or good and patents it. Production for the
Southern market can take place in the North or the South. The Northern firm has three
choices or modes of production: it can produce at home and export to the South, it can
form an affiliate in the South to service that market, or it can license its technology to a
Southern firm. Although firms typically produce for both their domestic and export
markets, we assume in this model that all production in the North is for export and that all
production in the South is for the local market.8 This is a static one-period model and
does not take into account the post-imitation rivalry between firms and the strategic
interactions among the rival firms.9
The decision of a Northern firm about the mode of production will depend on several
factors in the host country. A unit of production, x, requires one unit of labor, at a cost of
w in the North and ws in the South. Southern labor is assumed low cost, w > ws, and
production in the South avoids the per unit tariff, t.10 However production in the South
will incur either a given fixed cost, f, for setting up a local affiliate or must share profits
with a Southern licensor at some rate, 1-.
We assume technological sophistication of local firms and labor is related to the level
of research and development conducted by local firms, R. Technological sophistication
is assumed to improve productivity of Southern labor and so lower the per unit cost of
production, ws(R)/R < 0. Technological sophistication is also assumed to increase the
imitative ability for new technologies by local firms. As in Fosfuri (2000) an increase in
the imitative ability of local firms raises the bargaining power for Southern firms in a
licensing agreement with Northern firms. This increase in bargaining position will lower
7
This is similar to the approach in Vishwasrao (1994), but the strategic elements are not considered.
We also note that this model does not consider the existence of a competing industry in the host country
since the North is inventing a new technology/product. In the empirical analysis, we also do not have the
relevant data to examine this issue.
9
Our theoretical model helps us to develop a framework to motivate our empirical analysis, and since we
do not have the data to adequately capture firm rivalry, we have not explored this aspect in the theoretical
model.
8
10
The factor t can also be considered as a composite of all country-specific import costs such as tariffs and
transport costs.
5
the share of profits in the licensing agreement which can be captured by the Northern
firm, /R <0.
The Northern firms face an inverse demand function for their output in the Southern
market, p = a-bx, where p is the price and x represents quantity. x e, xf and xl represent the
quantities under each of the three modes of servicing the market: exports, FDI, or
licensing. The Northern firm makes a profit of e by exporting, a profit of f from
opening an affiliate in the host country, and l by licensing its technology to the foreign
firm. We assume that the Northern firm will choose the mode that produces the highest
profit.11
In the case of exports, the Northern firm’s profits will be:
 e  (a  bxe ) xe  wxe  txe
(1)
Differentiating with respect xe, and solving for the equilibrium profits from exports,
we get,
(a  w  t ) 2
4b
In the case of FDI, the Northern firm’s profit function is:
 e* 
 f  (a  bx f ) x f  ws ( R) x f  f
(2)
(3)
The equilibrium profits from FDI are
(a  ws ( R)) 2  4 fb
(4)
4b
The third approach to servicing the Southern market is by licensing the technology to
 *f 
local firms in the host country. The division of rents between the Northern firm and the
Southern firm depends on several factors such as the relative bargaining powers of the
contracting parties, degree of market competition and government intervention
(Contractor and Sagafi-Nejad, 1981). Several papers (Yang and Maskus (2001b) and
Taylor (1994) and Markusen (2001)) indicate that stronger IPRs lead to a reduction in the
licensors’ monitoring and contacting costs and raise the return on transferring technology.
11
We do not consider the rate of return due to data limitations, since we lack the data to calculate the rate
of return on investment for each type of MNE activity.
6
There is also evidence in the literature that stronger IPRs increase the licensor’s share of
rents. Gallini and Wright (1990) show that where information is asymmetric and
imitation is possible, the licensor sacrifices some of the rent, although the licensor’s share
increases with the increase in imitation costs.
In our model, we follow Yang and Maskus (2001b) and Fosfuri (2000) and assume
that the licensor’s rent share is a positive function of Southern IPRs. Stronger IPRs make
it more difficult to imitate, and hence the licensee commits not to imitate at a lower rent
share, thus increasing the licensor’s share.
Let  be the Northern firm’s share of rents, such that 0<<1, =(k, R), and /k >0,
where k measures the strength of the Southern IPR regime and R the level of domestic
research and development. Hence the Northern firm makes a profit of (k, R)sl by
licensing technology to the Southern firm, where sl is the profits of the Southern firm.
The Southern firm’s profit function can be written as follows:
 sl  (a  bxl ) xl  ws ( R) xl
(5)
The equilibrium profits of the Southern firm are:
(a  ws ( R)) 2
 
4b
Hence, the equilibrium profits of the Northern firms from licensing its technology to
*
sl
(6)
the Southern firm is
 
*
l
 (k , R)( a  ws ( R)) 2
4b
The profitability of each mode of operation for the Northern firm is not observable.
However we can observe indicators of the level of operation of each mode by all
Northern firms in a host country. The relative profitability of the three modes of MNE
operation given by Equations 2, 4 and 7 will determine the aggregate level of operation of
each mode in a host country. Holding all else constant, an increase in the profitability of
one mode should raise the level of operation of that mode and lower the level of
operation of the other two modes. For a higher level of tariffs for example, we would
expect to see a lower level of exports and higher levels of FDI and licensing.
7
(7)
Applying the logic from the previous paragraph to Equations 2, 4 and 7, we derive the
expected signs of the changes in the aggregate level of operation of exports, FDI and
licensing for the parameters of interest from our model: k, ws, t, f and R. These expected
signs are reported in Table 1. We can find expected signs for all of the coefficients of
the parameters for all three modes of operation, except in the cases of ws and R for
licensing. In these cases the coefficients are ambiguously signed due to the interactions
between , R and ws, as well as the substitution away or towards that mode of operation
from other modes. In the case of a rise in ws the profitability of FDI falls, while the
profitability of licensing also falls, but not by as much. Some firms will switch away
from licensing to exports, but other firms will switch to licensing from FDI. The net
impact in ambiguous.
3. Empirical Analysis
In this section we develop an empirical framework based on the gravity model to test
the propositions on the impact of patent protection and country specific fixed costs on the
MNC’s mode of entry that we derived from theory.
i) Data Considerations
The data for this study covers the activities of majority-owned US MNEs from
1992 to 2000, and includes aggregate bilateral data for each type of MNE activity:
unaffiliated exports, local affiliate sales and unaffiliated licensing receipts (lMNA in
equation 12 below represents real values of three different types of US MNE activity in
logs). This data is different from that used in earlier work in that it covers a later time
period, and has both time series and cross-sectional dimensions. Before we proceed with
the analysis it is useful to discuss the main characteristics and limitations of the data.
Data on exports by US parents to unaffiliated firms is not available for the nonbenchmark survey years. So, we use data on exports from the US to unaffiliated firms,
which is calculated as the difference between bilateral exports from the US to the host
country, and the exports of US parents to their affiliates in the host country. We also use
local sales by affiliates in the host country obtained from the BEA, instead of FDI flows,
since our analysis focuses on the outputs of MNE activity rather than inputs. Licensing
8
receipts of US parents from unaffiliated firms are from the Survey of Current Business. 12
While interpreting these variables it is worth noting that in the case of local affiliate sales,
US MNEs may already have assets in the host country and may vary the degree of
utilization of these assets to service the local market.13
The host country policy environment variables in our theoretical model include the
wage rate, ws, patent protection, k, tariffs, t, the fixed costs of doing business in the host
country, f, and the host country’s level of research and development, R. Data availability
considerations compel us to be parsimonious with the use of variables included in our
regressions. The home country’s wage rate, ws, is proxied by the compensation (Wages),
the patent protection, k, by the Ginarte and Parks index of patent protection (PR), tariffs,
t, by the Sachs-Werner openness index and trade to GDP ratio (Open), and the fixed costs
of doing business in the host country, f, by the Euromoney country risk index and the
ICRG risk indices (Risk).14 The ICRG Country Risk Index is a composite of political,
economic and financial risk indices. Our measure of country risk is defined as (100Country Risk Index).15 Our transformation allows higher index values to be associated
with higher levels of risk, and hence higher fixed costs, and facilitates interpretation of
the results.
The real wages in the host country are calculated from the total compensation and the
number of employees of MNE subsidiaries available from the BEA deflated by the
12
As in Smith (2001) we assign a value of one cent where there are no exports, local sales or licensing
receipts. This enables us to retain zero observations in the log linear treatment, and use the information on
countries that have at least one form of MNE activity. This is consistent with our focus on the MNC’s
decision regarding how to service the foreign market rather than whether to service the foreign markets.
13
These assets may exist prior to the year in which the local sale occurred. The subsidiary local sales
include all sales, using both new and existing assets.
14
The correlation coefficient between the two indices is 0.8682.
15
The Euromoney and ICRG country risk indices are 100 point indices, with 100 denoting the lowest level
of risk. The Euromoney index and is based on political risk, economic performance, debt indicators, debt in
default or rescheduled, credit ratings, access to bank finance, access to short-term finance, and access to
capital markets. The ICRG composite risk Index is incorporates economic, political and financial risks,
and we also have data for its individual components. The Political Risk Index has as its main components
government stability, socioeconomic conditions, investment profile, internal conflict, external conflict,
corruption, military in politics, religion in politics, law and order, ethnic tensions, democratic
accountability, and bureaucracy quality. The Economic Risk Index is comprised of GDP per capita, real
GDP growth, annual inflation rate, budget balance as a percent of GDP and current account as a percent of
GDP. The components of the Financial Risk Index are foreign debt as a percent of GDP, Foreign Debt
Service as a % of Exports of Goods and Services, Current Account as a % of Exports of Goods and
Services, Net International Liquidity as Months of Import Cover and Exchange Rate Stability. In
calculating the composite ICRG Country Risk Index, political risk rating contributes 50% of the composite
rating, while the financial and economic risk ratings each contribute 25%.
9
appropriate GDP deflator.16 The Sachs and Werner (1995) openness index, Open, which
takes values of either 0 or 1, measures the trade distortions in the host country. 17 If Open
has a value of 1, it is comparable to having low tariffs in the theoretical model. The
expected sign of Open from our model in Section 2 is the opposite of the expected sign of
tariff in Table 1. The index of patent protection (PR) is based on Ginarte and Parks
(1998), and Park (2002) work analyzing national patent law. The overall composite
index ranges between zero and five with higher values signifying greater patent
protection.18 The literature also suggests that the impact of increased patent protection in
a country depends on its ability to imitate. Hence we include the host country’s R&D as
a proportion of GNP to proxy for the host country’s ability to imitate (R&D), and the
interaction between the patent index and R&D is a measure of the threat of imitation. The
classification of countries according to regions,19 the real GDP per capita (gdppc),
population (pop), are from the World Development Indicators (2004); the other gravity
variables such as distance (dist) proxied by the geographical distance between the US and
its trading partners and language (langdum) a dummy variable that equals 1 if the official
language of the country is English, and zero otherwise are from Jon Haveman’s
website.20 The GDP per capita, distance, population, and wages are all expressed in logs.
We note that MNEs can typically choose both the country in which to invest in as well as
the mode of entry, and if some country specific factors change, in addition to shifting the
mode of entry, they can also chose to invest in another country. Our data however does
not provide information for this type of analysis, and hence we focus only on the mode of
entry into a given market.
16
This is the best approximation that was available for all the countries that were in the dataset. This
variable does not distinguish between part-time and full-time employees.
17
Open has a value of 1 if a country meets all of the following four criteria: i) not a socialist country, ii)
low black market exchange premium, iii) low quota coverage on intermediate and capital goods, and iv)
export marketing boards do not create extreme trade distortions. Harrison and Hanson (1999) have shown
in their analysis that the Sachs-Werner index can be weak as a measure of trade orientation. In our data,
the correlation between this index and the ratio of exports to GDP is 0.24, and it is significant at the 1%
level.
18
It is obtained by aggregating across five categories reflecting country specific characteristics of PRs, each
of which takes values between zero and one. The five categories are: coverage; membership in international
patent agreements; provisions regarding loss of protection; enforcement mechanisms; and duration of
protection. Their analysis indicates that the ranking of countries by this index is not sensitive to the
weighting scheme used. The value of this index for countries in our sample varies from 0.51 to 4.52. We
thank Walter Park for the data.
19
Africa=1; Asia=2; Oceania=3; Europe=4; North America=5; South America=6.
20
www.haveman.org.
10
ii) Methodology
The decision by a firm to export a patentable product is jointly determined with
decisions to service the market through licensing or FDI. The impact of patent rights on
unaffiliated exports, local affiliate sales, and licensing are tested empirically in a
simultaneous equation framework to capture the idea that the MNE’s choice of the mode
of entry is a joint decision making process. The system of equations is specified using an
adaptation of the gravity model that is common in the literature. Bergstrand (1989)
expresses bilateral trade by commodity as:
X ijk   0i (Q j / N j )1i ( N j ) 2i (Qk / N k ) 3i ( N k ) 4i ( D jk ) 5i ( Aijk )
(11)
This equation states that bilateral trade depends on per capita incomes in regions j and
k (Q/N), population in regions j and k (N), the distance between the trading partners (D)
and distortionary factors that impede or augment trade (A). We use the same type of
framework to specify equations for host country sales of US affiliates (henceforth
referred to as local affiliate sales) and licensing receipts. The distortionary factors in our
model include measures of intellectual property protection, trade distortions and other
government policies. We consider only characteristics of the importing country, since we
have just one exporter, namely the US. The estimating equations are obtained by taking
the natural logs of a modified version of equation (1) for each type of US MNE activity:
lMNAijt   0it  1it lgdppc jt   2i ldist j   3i lpop jt   4i langdum j   5i PR jt
  6i Open jt   7iWages jt   8i Risk j t   9i R & D jt  10 i Open jt * PR jt
 11iWages jt * PR jt  12 i Risk jt * PR jt  13i R & D jt * PR jt
  jt
(12)
where j indexes countries with which the US has trade, investment, or licensing
agreements, and t indexes time. We use the above methodology to test the following
propositions derived from our theoretical model:
Proposition 1: Our model suggests that higher levels of patent protection will be
associated with lower levels of exports and FDI and higher levels of licensing.
11
The literature also suggests that there may be additional effects of stronger patent
protection (other than those predicted by our theoretical model) on exports, local affiliate
sales and licensing which may offset each other and make the impact of patent protection
on MNE activities ambiguous. Stronger patent rights create a trade off between enhanced
market power and the resultant lower MNE output (monopoly power effect), and larger
effective market size in the host country that results from tighter constraints on the local
firms’ abilities to imitate (market expansion effect).21 Hence, the overall effect of patent
rights on trade and local affiliate sales is ambiguous and depends on the relative strengths
of these effects. Yang and Maskus (2001b) argue that the overall effect of stronger IPRs
on licensing and innovation is also indeterminate because of two opposing effects of
patent rights: the economic returns effect that results from an increase in the share of the
licensor’s rents and lowers enforcement costs, and the monopoly power effect.
Proposition 2: Greater country risk will be associated with higher levels of exports
and licensing and lower levels of FDI.
In addition, we are also interested in analyzing how country specific fixed costs
modify the relationship between IPRs and the MNCs mode of entry and so we derive
some second order results.22 Taking f and δ as our parameters of interest and holding all
other parameters fixed (and dropping the function notation for simplicity), we can
implicitly solve for the values of f and δ that equalize profits for the MNE under exports,
Equation 2, and profits under FDI, Equation 4. As δ does not appear in either expression,
this equation reduces to a critical value for f, f*:
( a  ws ) 2  ( a  w  t ) 2
(8)
4b
For fixed costs above f*, it is more profitable for the MNE to export than it is to engage
f*
in FDI. For fixed costs below f*, the reverse is true. Likewise, we can obtain the critical
level of f with regard to the trade off between FDI and licensing.
Similarly from Equations 2 and 7 we can obtain the critical value for δ, δ*, which
influences the choice between exporting and licensing:
21
22
Stern, 1987 and Maskus and Penubarti,1995.
The mathematical derivations are available from the authors on request.
12
(a  w  t )2
( a  ws ) 2
For MNE shares of rents below δ*, the MNE prefers exporting to licensing, while for
* 
shares above δ*, the reverse is true. Using similar reasoning we can arrive at the
following propositions:
Proposition 3: Licensing is preferred to FDI when fixed costs are high and is also
preferred over a larger range of fixed costs as patent protection in the South increases.
Proposition 4: FDI and licensing are preferred to exports where tariffs are high.
Licensing is preferred to exports over a larger range of tariffs as the patent protection in
the South increases.
Proposition 5: Licensing is preferred to FDI over a larger range of patent protection
levels as the wage rate in the South increases. Licensing is preferred to exports over a
smaller range of patent protection levels as the wage rate in the South increases.
The net impact of patent protection and Southern wages is indeterminate and remains
an empirical question.
Ideally, we want to test how increased patent protection influences the firm
preferences regarding each mode of entry into the foreign market in comparison to the
other modes of entry, in the presence of fixed costs (representing the host country policy
environment) of doing business in the country. Our empirical analysis does not permit us
to directly test how the range of fixed costs over which one mode of servicing the market
is preferred to another change, as patent protection changes.
This would require
expressing earnings from unaffiliated export, local sales and licensing as a ratio of the
total earnings that the MNE parent receives from servicing the foreign market. However,
in the case of local sales, the figures pertain to the revenues of the local subsidiary and we
do not have comparable figures for the earnings of the parent from local sales. As an
approximation, instead, we can test how stronger patent protection in the host country
influences the firm’s choice regarding each mode of entry (exports, local subsidiary sales
and licensing) into that market, taking into account the simultaneous nature of these
choices.
13
(9)
Our model of exports, licensing and FDI is based on the decision of one MNE. In
our data, we observe the results of the choices of many MNEs in different industries and
facing different cost structures. Factors such as fixed costs and wages will vary across
MNEs even within a country. The willingness of domestic governments to enforce patent
protection may differ across industries, so that patent protection may not be the same for
all MNEs within a country. We envisage then that the values facing individual firms are
clustered around some average level for each country. The observed decision by one
MNE may be different from others within the same country due to this variability. Our
model is then a probabilistic one predicting the average results of multiple MNE
decisions within a country. We estimate two variants of the basic equation system
(equation 12) to capture the different effects suggested by the theory in propositions 1-5
above, and to test for robustness. The system of equations was estimated using the
seemingly unrelated regression model to account for the MNEs joint decision making
process and corrected for heteroskedasticity.23
iii) Results
Tables 2 to 5 present our regression results.24 Table 2 presents the baseline model, while
Tables 3, 4, and 5 presents the results obtained by the inclusion of host country policy
variables interactions in the analysis of the impact of IPRs on US MNE activities.
The estimated coefficients in the baseline model Table 2 provide mixed results. The
market size as proxied by the GDP per capita and population has a positive and
significant influence on all three modes of entry, as does the openness variable. The
patent index is insignificant in all cases. The country risk index offers partial support for
Proposition 2: it is negative and significant in the case of affiliate sales and licensing,
suggesting a greater reliance on a more arms length mode of servicing the market
(exports). Our baseline model is clearly inadequate in capturing the complex relationship
23
Even though the Hausman Test did not indicate that the dependent variables were endogenous, we also
estimated the model using Instrumental variables, the results of which are not reported. Lagged dependant
variables, real values of FDI stock and assets were used as instruments. The first stage R 2 in all cases was
between 0.53 and 0.75. The results were qualitatively similar to the SUR models; our discussion is based
on the SUR model, which is the more conservative model.
24
Year dummies and regional dummies have been included in all regressions, but have not been reported.
Standard errors are reported within parenthesis. Significance is indicated by one asterisk (10-percent
level), two asterisks (5-percent level), three asterisks (1-percent level).
14
between an MNE’s behavior and patent rights. Hence we focus on the results in Tables
3, 4 and 5 for a more detailed understanding on the relationships between IPRs and the
policy variables.
A comparison of the results from the baseline model in Table 2 and the full models in
Tables 3, 4 and 5 that include the policy variables indicates that the inclusion of the
variables that proxy for the policy environment has a strong influence on the results. The
patent index variable in Table 2 is insignificant in all cases. However, with the inclusion
of the other policy variables, the coefficient on the patent variable is now negative and
significant in the case of unaffiliated exports (Table 3) and positive in the case of the
licensing, and significant when we use the EM risk index (Table 5). This suggests that in
general, the monopoly power effect dominates the market expansion effect of stronger
patent rights in the case of unaffiliated exports while the market expansion effect is the
dominant effect in the case of licensing. Our results regarding licensing are similar to
Smith (2001) who finds that patent protection has a net positive market expansion effect
on licensing. The patent index variable is insignificant in the case of affiliate sales. An
insignificant coefficient in this regression does not imply that the patent variable has no
impact on affiliate sales; this result could be caused by the fact that the market expansion
and monopoly affects of IPRs offset each other causing the net impact to be insignificant.
Thus our results on average offer support for Proposition 1.
An important policy variable suggested by our theoretical model is the country risk
index. The fixed costs (proxied by country risk index) are hypothesized to have a
negative impact on FDI in our theoretical model.
It is important to note that our
empirical model analyzes local sales of affiliates instead of FDI flows. Our empirical
analysis confirms that increased risk reduces affiliate sales in the host country. The
theoretical model suggests that an increase in patent protection would reduce the range of
fixed costs over which FDI is preferred to licensing, and cause a substitution from FDI to
licensing (Proposition 2). The coefficient on the patent-risk interaction term is positive
but insignificant possibly because even in a high-risk country, increased patent protection
leads to an increase in affiliate sales as a result of a strong market expansion effect of
patent protection. US MNEs, when evaluating their strategy in a high-risk country that
15
has increased its patent protection, may also decide to utilize assets already existing in the
host country and increase affiliate production to service the local market.25
Our theoretical model suggests that those higher fixed costs also result in a greater
preference for arms length arrangements like licensing and unaffiliated exports. Our
results offer mixed support this hypothesis in Proposition 2: while there is a reduction in
affiliate sales as expected, higher fixed costs also have a negative impact on exports and
for the ICRG index it is also significant. The coefficient on the risk variable in the
licensing equation is negative but insignificant. The theoretical model (Proposition 3)
also suggests that risk-patent index interaction term in the licensing equation should be
positive, as increased patent protection increases the range of fixed costs over which
licensing is preferred to FDI. The negative and significant coefficient on the risk-patent
index interaction term in the licensing equation suggests that when patent protection is
strengthened in high-risk countries, it decreases licensing, possibly due to a dominant
monopoly effect. In high-risk countries, increase in the economic returns to licensing
may be dominated by the monopoly power effect of patent rights. In the unaffiliated US
exports equation, the patent-risk interaction term is positive and significant.
This
suggests that in high-risk countries, strengthening patent protection increases unaffiliated
exports.
We also used the individual political, economic and financial risk indices from ICRG
to ascertain the impact of these different types of risks on MNE activity. Our analysis
indicates that political risk has the most impact. The coefficient on the political risk
index is negative and highly significant, both in the case of affiliate sales and licensing.
This finding is consistent with the literature on expropriation of FDI and non-fulfillment
of licensing contracts as deterrents to FDI and licensing. However, strengthening patent
protection in countries that are politically high risk appears to increase both affiliate sales
and licensing.
Proposition 5 states that while licensing is preferred to FDI over a larger range of
fixed costs as ws, the wage rate in the South increases; higher wages in the host country
may also lead to a substitution from licensing to exports. Hence our theory predicts that
25
These assets may exist prior to the year in which the local sale occurred. The subsidiary local sales
include all sales, using both new and existing assets.
16
wages will have a negative coefficient in the local sales equation, and a positive
coefficient in the exports equation and while the effect is indeterminate in the case of
licensing. The wage rate has a negative effect in both the exports and licensing equations
and is significant in the exports equation; while the wages-patent index interaction terms
in both equations are positive but significant only for the ICRG risk model in the
licensing equation. The negative coefficient on wages in the licensing equation is not
surprising: at higher level of wages, the substitution effect from licensing to exports
dominates the substitution from local subsidiary sales into licensing. However, the
positive and significant interaction term suggests that at higher levels of patent
protection, the substitution effect from FDI into licensing is stronger than the substitution
from licensing to exports as a result of high wages.
The results from the exports equation, where wages have a negative and significant
impact on unaffiliated exports, and from the affiliate sales equation where the wages are
positive in the affiliate sales equation (and significant only in then case of the EM Risk
index model), is counterintuitive to the predictions of our theoretical model. One
explanation is that the host country wage rate is probably highly correlated with the GDP
per capita variable. However, the GDP per capita may also be capturing the demand side
effects, and it is difficult to separate the two. The positive coefficient on GDP per capita
in the exports equation also lends support to this notion. In the affiliate sales equation the
wages-patent index interaction term is negative and significant suggesting that as patent
protection increases in high wage countries, there is less need for internalization of
production through affiliates.
In Table 2, the openness variable is significant and positive with respect to all three
modes of entry into the foreign market. In the full model, the coefficient on the openness
variable in Table 5 indicates that licensing is larger in more open economies; the
openness-patent index interaction in this equation is negative and highly significant
suggesting that for a given degree of openness, as patent protection increases, licensing
decreases possibly because of a dominant monopoly effect on licensing. Hence our
results lend support to Proposition 4. Openness and its interaction with the patent index
are insignificant in the other cases.
17
The literature also suggests that the ability to imitate, as proxied by the R&D variable
may influence the impact of IPRs on the MNEs mode of entry into a foreign market. In
the case of licensing, the ability to imitate could have an ambiguous effect. A country
with greater R&D can imitate more efficiently at a lower cost which could discourage US
licensing. On the other hand US firms may view higher local R&D as a signal that
workers can learn and adapt new technology more efficiently, reducing the cost of
technology transfer. This is turn could stimulate US licensing activity. 26 In Table 5, we
find that in the case of licensing, R&D has a positive and highly significant effect: this
suggests that the savings in costs by licensing to a highly skilled country outweighs the
negative effect of the fear of imitation. The patent index-R&D interaction term in the
licensing equation has a negative and significant coefficient suggesting that the negative
monopoly effect of stronger patent rights dominates the positive effect of the increase in
economic returns to licensing where there is a low threat of imitation.
R&D has a negative and significant coefficient in the affiliate sales equation
indicating that high ability to imitate leads to lower affiliate sales, while it is insignificant
in the unaffiliated exports equation. The positive and significant R&D-patent index
interaction term in both the unaffiliated exports and affiliate sales equations suggest that
when patent protection is strengthened in countries with a high ability to imitate (so that
they pose a low threat of imitation) the positive market expansion effect dominates the
negative monopoly power effect.27 This finding lends support to Manfield’s (1995)
argument regarding the incentives for MNEs to internalize their activities.28 However it
is useful to note that Smith (2001) using a cross-section from 1989 found that
strengthening patent rights in countries with strong imitative abilities increases both
affiliate sales and licensing. While our panel data analysis finds similar results with
respect to affiliate sales, we find a dominant monopoly effect in the case of licensing. The
marginal effect of intellectual property rights on each form of MNE activity, which
26
Yang and Maskus (2001b) have termed these as the imitation cost effect and the licensing cost effect
respectively.
27
Even if a country has high R&D and hence high ability to imitate, strong patent protection implies that it
poses a low threat of imitation.
28
Mansfield (1995, pp. 290) suggests that “many firms prefer direct investment in wholly owned
subsidiaries as a channel by which to transfer technology to other countries, particularly if they believe that
licensing will give away valuable know-how to foreign producers who are likely to be competitors in the
future.”
18
shows the percentage change in each form of MNA activity for a unit change in patent
protection, was calculated.29 We find that there are considerable differences between
closed and open economies when we consider the impact of a unit change in patent
protection on MNE activities, indicating that there may be some trade-off involved in the
case of less open economies. For example in these economies, MNEs may be able to
extract greater licensing rents. 30
4. Concluding Remarks
This paper provides useful insights in the debate regarding the relationship between
stronger patent rights, host country policies and MNE activity using panel data from US
MNEs. The results support the idea that the policy environment in the host country
influences the impact of stronger IPRs. First, we find that on average, patent protection
reduces exports and increases licensing. Second, higher R&D in the foreign markets, our
proxy for the ability to imitate, is positively associated with US licensing, and negatively
associated with US affiliate sales. However, in countries that pose a weak threat of
imitation (high R&D accompanied by stronger patent protection) there is a reduction in
licensing and an increase in affiliate sales and unaffiliated exports. This offers a possible
explanation for the reluctance of developing countries with a skilled and scientifically
trained workforce such as China and India to strengthen patent protection, since
unaffiliated licensing is seen as a valuable channel for technology transfer. Third, a risky
environment in the host country appears on average to have a negative and significant
impact on unaffiliated exports and affiliate sales; the impact on licensing is insignificant.
Increased patent protection in high-risk countries on average appears to reduce licensing,
and increase unaffiliated exports suggesting a dominant monopoly effect of stronger IPRs
in the former case and a dominant market expansion effect in the latter case. We find no
support in our data for the hypothesis that strengthening patent rights in countries that
29
The coefficients from Tables 3-5 and the mean values of the variables are used to derive the marginal
effects.
30
The marginal effect of intellectual property rights on each form of MNE activity, which shows the
percentage change in each form of MNA activity for a unit change in patent protection, was calculated. The
coefficients from Tables 3-5 and the mean values of the variables are used to derive the marginal effects.
We found differences between closed and open economies. For example, a unit increase in patent
protection has an overall impact of 1.31% on local affiliate sales in an open economy as compared to
0.44% in a closed economy. The corresponding numbers for unaffiliated licensing receipts was -3.19% and
1.33% respectively.
19
have a strong ability to imitate reduces the desire for internalization through affiliate
production. The study also indicates that the marginal effect of stronger patent rights on
US unaffiliated exports, local affiliate and licensing varies considerably in magnitude and
direction, depending on whether the economy is open or closed. Our results lend support
to the argument that changes in patent rights policies should be evaluated in conjunction
with other international and domestic policies to assess their full impact on the host
country.
The direction of the impact of the policy variables also differs with the type of MNE
activity: unaffiliated exports, local sales or licensing. For example, in high-risk countries,
strengthening patent rights leads to less licensing and more unaffiliated exports. One
interesting policy implication for host countries is that while strengthening patent rights,
they should consider how policy distortions can sometimes influence outcomes with
regard to the impact of patent right policies, and affect an MNE’s choice between
exports, FDI, and licensing. This is especially relevant to policy makers who consider
one form of MNE activity to be superior to another in promoting knowledge spillovers
and growth in the host country.31 An important contribution of this paper is that it
highlights and validates the need to evaluate the overall impact of stronger patent
protection in conjunction with other domestic and international policies in the host
country, rather than as a stand-alone policy.
Given the current data limitations, this work uses aggregate country-level data to
analyze the impact of patent protection on a US MNE’s mode of entry into foreign
markets. The key data limitation is the lack on industry level data on unaffiliated
licensing receipts by US MNEs. We are also in the process of examining how IPRs
impact affiliates’ R&D activities in the host country.
Further research on the effects of
patent protection is needed at a much more disaggregated level, especially in R&D
intensive industries that face high threat of imitation. This may also facilitate our
understanding of the channels through which the market expansion and market power
effects of patent protection impact the different modes of MNE entry into foreign
markets.
31
Saggi (2002) indicates that Japan, in contrast to its restrictive stance towards FDI, actively encouraged
licensing of foreign technology. Saggi (1999, 2002) suggests that countries may prefer technology
licensing to FDI as a method of encouraging technological development of indigenous firms.
20
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22
Table 1: Patent Rights and Host Country Policies: Predictions of the Theoretical Model*
Independent Variables
Southern IPR
Southern wages
Southern tariffs
Fixed costs of FDI
Southern R&D
Exports
+
+
-
FDI
+
+
Licensing Receipts
+
?
+
+
?
* - Negative; + Positive; ? Indeterminate
Table 2: Patent Rights and Mode of Servicing the Host Country Market - Baseline Model
Variables
Unaffiliated Exports
Local Sales of Affiliates
distance
EuroMoney
(EM) Risk
Index
1.78*
EuroMoney
(EM) Risk
Index
0.34
ICRG
Index:
composite
0.28
ICRG
Index:
composite
1.74*
Unaffiliated Licensing
Receipts of Parents
EuroMoney ICRG
(EM) Risk
Index:
Index
composite
-0.13
-0.23
(1.02)
(1.04)
(0.29)
(0.30)
(0.44)
(0.45)
language
dummy
1.29**
1.16*
1.23***
1.29***
0.55**
0.61**
(0.64)
(0.63)
(0.19)
(0.18)
(0.28)
(0.27)
GDP per
capita
1.59***
1.44**
1.43***
1.50***
0.43
0.50*
(0.64)
(0.62)
(0.18)
(0.18)
(0.27)
(0.27)
1.46***
1.44***
1.02***
1.04***
0.92***
0.96***
(0.25)
(0.25)
(0.07)
(0.07)
(0.11)
(0.11)
0.51
0.56
0.20
0.17
-0.20
-0.24
(0.51)
(0.51)
(0.15)
(0.15)
(0.22)
(0.22)
-1.14
-1.23
-0.33
-0.27
1.14**
1.21***
(1.12)
(1.11)
(0.32)
(0.32)
(0.48)
(0.48)
1.92*
1.71*
1.00***
1.12***
1.19***
1.32 ***
(1.06)
(1.04)
(0.31)
(0.30)
(0.46)
(0.45)
1.29
1.16
-1.14***
-1.13***
-0.67
-0.68
(1.18)
(1.18)
(0.34)
(0.34)
(0.51)
(0.51)
population
patent index
compensation
openness
ratio of R&D
to GNP
EuroMoney
risk index
0.03
-0.02***
-0.03**
(0.03)
(0.01)
(0.01)
ICRG index
Number of
observations
0.01
289
(0.04)
289
-0.03***
289
(0.01)
289
-0.04**
289
(0.02)
289
Significance is indicated by one asterisk (10-percent level), two asterisks (5-percent level) and three
asterisks (1-percent level).
23
Table 3: Patent Rights, Host Country Policies and US Unaffiliated Exports
Dependant Variable: Unaffiliated Exports
Variables
EuroMoney (EM)
Risk Index
ICRG Index:
composite
0.70
(1.14)
2.31***
(0.75)
2.01***
(0.70)
1.29***
(0.28)
-8.43*
(4.58)
-5.66*
(3.25)
1.44
(0.93)
-4.20
(7.36)
2.72
(3.77)
-6.77
(5.97)
2.22
(1.68)
-0.12
(0.08)
0.06*
(0.03)
0.69
(1.14)
2.28***
(0.75)
1.54**
(0.64)
1.16***
(0.27)
-7.79*
(4.28)
-4.98
(3.10)
1.18
(0.87)
-3.43
(7.26)
2.04
(3.72)
-8.19
(5.78)
2.72*
(1.63)
Distance
language dummy
GDP per capita
Population
patent index
Compensation
patent index interacted with compensation
Openness
patent index interacted with openness
ratio of R&D to GNP
patent index interacted with R&D ratio
EuroMoney risk index
patent index interacted with EuroMoney risk index
ICRG index
ICRG Index:
disaggregated
0.60
(1.15)
2.43***
(0.78)
1.42**
(0.64)
1.16***
(0.28)
-9.00
(6.40)
-5.68*
(3.12)
1.31
(0.87)
-0.92
(7.47)
0.56
(3.86)
-8.23
(5.92)
2.83*
(1.68)
-0.22**
(0.11)
0.08**
(0.04)
patent index interacted with ICRG index
economic risk
0.06
(0.18)
-0.01
(0.07)
-0.16
(0.13)
0.06
(0.04)
-0.25
(0.16)
0.06
(0.05)
patent index interacted with economic risk
political risk
patent index interacted with political risk
financial risk
patent index interacted with financial risk
Number of observations
289
289
289
Significance is indicated by one asterisk (10-percent level), two asterisks (5-percent level) and three
asterisks (1-percent level).
24
Variables
Table 4: Patent Rights, Host Country Policies and Local Affiliate Sales
Dependant Variable: Local Affiliate Sales
ICRG Index:
EuroMoney (EM) ICRG Index:
disaggregated
Risk Index
composite
Distance
0.10
(0.33)
1.17***
(0.22)
1.31***
(0.20)
1.04***
(0.08)
0.23
(1.33)
1.61*
(0.94)
-0.58**
(0.27)
-0.76
(2.13)
0.88
(1.09)
-4.06**
(1.73)
0.90*
(0.49)
-0.04*
(0.02)
0.004
(0.01)
language dummy
GDP per capita
Population
patent index
Compensation
patent index interacted with compensation
Openness
patent index interacted with openness
ratio of R&D to GNP
patent index interacted with R&D ratio
EuroMoney risk index
patent index interacted with EuroMoney risk index
ICRG index
0.12
(0.33)
1.24***
(0.22)
1.42***
(0.19)
1.07***
(0.08)
-0.40
(1.25)
1.20
(0.90)
-0.42*
(0.25)
-0.58
(2.12)
0.87
(1.08)
-3.33**
(1.69)
0.69
(0.47)
0.05
(0.33)
1.25***
(0.23)
1.33***
(0.19)
1.05***
(0.08)
-0.17
(1.85)
1.02
(0.90)
-0.34
(0.25)
-0.47
(2.16)
0.83
(1.11)
-3.51**
(1.71)
0.74
(0.49)
-0.07**
(0.03)
0.01
(0.01)
patent index interacted with ICRG index
economic risk
0.10
(0.15)
-0.03
(0.02)
-0.11***
(0.04)
0.03**
(0.01)
-0.06
(0.05)
0.01
(0.01)
patent index interacted with economic risk
political risk
patent index interacted with political risk
financial risk
patent index interacted with financial risk
Number of observations
289
289
289
Significance is indicated by one asterisk (10-percent level), two asterisks (5-percent level) and three
asterisks (1-percent level).
25
Table 5: Patent Rights, Host Country Policies and Licensing Receipts from Unaffiliated Firms
Dependant Variable: Licensing Receipts from Unaffiliated Firms
Variables
ICRG Index:
EuroMoney ICRG
disaggregated
(EM) Risk
Index:
Index
composite
Distance
0.36
(0.49)
0.43
(0.32)
0.30
(0.30)
0.94***
(0.12)
5.55***
(1.96)
-0.42
(1.39)
0.36
(0.40)
11.02***
(3.15)
-5.04***
(1.61)
6.00**
(2.56)
-1.82**
(0.72)
0.04
(0.03)
-0.03**
(0.01)
language dummy
GDP per capita
Population
patent index
Compensation
patent index interacted with compensation
Openness
patent index interacted with openness
ratio of R&D to GNP
patent index interacted with R&D ratio
EuroMoney risk index
patent index interacted with EuroMoney risk index
ICRG index
0.07
(0.49)
0.58*
(0.32)
0.58**
(0.27)
1.00***
(0.12)
2.54
(1.85)
-1.92
(1.34)
0.87**
(0.37)
9.91***
(3.14)
-4.43***
(1.61)
5.61**
(2.49)
-1.71**
(0.70)
-0.10
(0.49)
0.55*
(0.33)
0.47*
(0.28)
0.95***
(0.12)
2.59
(2.73)
-1.84
(1.33)
0.94***
(0.37)
8.10***
(3.19)
-3.36**
(1.65)
4.73*
(2.53)
-1.51**
(0.72)
-0.04
(0.05)
0.004
(0.02)
patent index interacted with ICRG index
economic risk
0.06
(0.08)
-0.01
(0.03)
-0.15***
(0.06)
0.03*
(0.02)
0.10
(0.07)
-0.03
(0.02)
patent index interacted with economic risk
political risk
patent index interacted with political risk
financial risk
patent index interacted with financial risk
Number of observations
289
289
289
Significance is indicated by one asterisk (10-percent level), two asterisks (5-percent level) and three
asterisks (1-percent level).
26