日本貿易学会研究論文第 7 号,2018（Haneda）

The Impact of the Madrid Protocol on*
International Trademark Transfers
Sho HANEDA†
Tokyo University of Social Welfare

Ⅰ Introduction
Innovation and Intellectual Property (herein IP) bundle have been one of the key issues in the field of multinational firms
in recent years. IP bundle is the combined use of patents and trademarks (hereinafter TMs), and employed by firms intheir branding strategies. Since the differentiation of goods in the competitive market is crucial for companies, they use
TMs as signaling tools. Furthermore, the governments of each country understand that innovation activities areimportant for economic growth and try to attract Foreign Direct Investment (FDI) in R&D sectors. In order for countries
to obtain large FDI flows, the protection of intellectual property rights is one of key factors (Dernis et al. 2015). In thesesituation, some firms face problems relating to patent and TMs.
In 2016, Yamazaki Biscuit, which is a Japanese firm that used to produce and sell “Bitz”, terminated a license
contract with Mondelez International. Because of the event, the firm needed to change the name of its product from“Bitz” to “Luvan”. Toyo Keizai Online estimates the reduction in Yamazaki Biscuit’s operating profits around 0.8 billion
Japanese yen in 2016, although the company can use a similar technology of “Bitz” to produce “Luvan” 1. Anotherexample is the case of Meiji. In March 2016, Meiji’s license contract with Indian company has finished and the company
no longer can use the name “Isojin” for its product. In order to maintain the power of their brand, Meiji decided toregister its character “Kaba-kun” as TMs. As a result, the Indian company was forced to change the design of its productbecause the firm did not file a trademark registration application of “Kaba-kun”. These examples imply that branding
strategies using TMs are important not only in domestic markets, but also in international markets.
Previous studies have investigated mainly three fields; economic intuition of TMs, the connection between firm’s
performance and TMs as well as the complementarity relationship between patent and TMs (Nakamura 2014). Firstly,
there is a discussion of the usage of TMs data as measure of innovation. Since the fact that economic impact of patents is
ambiguous because patent registrations only protect inventions, some studies try to employ TMs data for understanding
the degree of innovation (Millot 2009; Mendoça et al. 2004; Schmoch 2003). Secondly, the causal relationship between
firm’s performance and registration of TMs has been explored (Greenhalgh and Rogers 2012; Greenhalgh et al. 2011;
Helmers and Rogers 2011; Greenhalgh and Longland 2005). Main consensus is that having TMs or higher number of
TMs applications may improve outcomes such as productivity, sales, the number of employment, etc. Finally, acomplementary effect of TMs applications has been discussed by some studies (Dernis et al. 2015; Helmers andSchautschick 2013; Graham and Somaya 2006). The question here is whether or not TMs are complementary assets. The
main results from previous analyses suggest that the combination use of patent and TMs tends to be effective and boost
firm’s growth. Unfortunately, only a few studies focus on international applications of TMs and policies related to thembecause of data availability (Lybbert et al. 2014).
*

This work was supported by JSPS KAKENHI Grant Number JP16H03624. The views contained in this paper are those of
the author and not necessarily those of School of Social Welfare, Tokyo University of Social Welfare.
†
Email: shhaneda@ed.tokyo-fukushi.ac.jp

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JAFTAB Research Paper,Vol.7,2018（Haneda）

To fill the gap, this paper aims to investigate the determinants of international transfers as well as the effect of the
Madrid Protocol on TMs applications by using TMs data over the period of 2004-2014 and employing theDifference-in-Difference estimator (hereinafter DID). Section 1 introduces the definition of TMs and explains the systemof the Madrid Protocol. Section 2 is about data issues and section 3 focuses on methodologies of our empirical analysis.
Section 4 summarises the results from the DID estimation and the last section concludes.

Ⅱ Trademarks and the Madrid protocol
According to United States Patent and Trademark Office (herein USPTO), “A trademark is a word, phrase, symbol,
and/or design that identifies and distinguishes the source of the goods of one party from those of others. A service markis a word, phrase, symbol, and/or design that identifies and distinguishes the source of a service rather than goods”(USPTO’s webpage) 2. Similarly, European Union Intellectual Property Office (hereinafter EUIPO) uses the following
definitions:“An EU trade mark may consist of any signs, in particular words, including personal names, ordesigns, letters, numerals, colours, the shape of goods or of the packaging of goods, or sounds,
provided that such signs are capable of: distinguishing the goods or services of one undertaking
from those of other undertakings; and being represented on the Register of European Union trade
marks in a manner which enables the competent authorities and the public to determine the clear
and precise subject matter of the protection afforded to its proprietor.” (EUIPO’s webpage) 3.
As they define, there are two types of TMs, namely goods TMs and service TMs. However, this paper does not consider
the difference between them, although our data include both of them.
To smooth international TMs applications, World International Property Organization (hereinafter WIPO)
established the Madrid system for international TMs registration in 1981. In addition, for the purpose of the removal of
difficulties in terms of TMs applications via the Madrid system, the Madrid Protocol was adopted in 1989 4. The maindifference is that applicants can submit the document to the office in origin country and the registration will be in force inmember countries without any additional procedure (see figure 1 in appendix). However, there are mainly two issues
regarding the Madrid Protocol. Firstly, the fee of TMs registration may be higher than that of the Madrid system, though
it depends on the agreement that each country signs. This means that the Madrid protocol can decrease the transaction
costs through the reduction in the registration fee. Secondly, “an international registration which is cancelled, at therequest of the Office of origin, for example because the basic application has been refused or the basic registration has
been invalidated within five years from the date of the international registration, may be transformed into national (orregional) applications in the respective Contracting Parties in which the international registration had effect, eachbenefiting from the date of the international registration and, where applicable, its priority date. This possibility does notexist under the Madrid Agreement.” (WIPO 2016, p.A5).
As we mentioned in the last section, little empirical research has been conducted for testing the impact of the
Madrid protocol on international TMs application. To check the relationship, by conducting an empirical analysis withinternational TMs application data, we test the following hypothesis:
Hypothesis: The Madrid Protocol reduces the transaction costs and increases the number of TMs applications
among member countries.
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日本貿易学会研究論文第 7 号,2018（Haneda）

Ⅲ DataThe studies on innovation and TMs heavily depend on the data availability. Since there was no official concordance
between TMs and economic data, researchers could not combine them in their studies. Nevertheless, Lybbert et al.
(2014) develop a concordance between NICE and Standard International Trade Classification (hereinafter SITC) to
speak each other. The NICE classification system is employed by European Union (hereinafter EU) for TMs applicationsin including TMs both for goods and services. The NICE classification is organised by two parts, 1 – 35 for goods and
36 – 45 for services 5. SITC is used mainly for trade data and Comtrade Database, United Nations (UN) employs thesystem. SITC is divided into 5 levels, which are Section, Division, Group, Subgroup, Basic heading. In this paper, we
use the concordance between NICE 2-digit level and SITC 2-digit level in order to convert them. Additionally, Lybbertand Zolas (2012) create a mapping method which can connect SITC and International Patent Classification (herein IPC)
for patent data. By employing those concordances, we can connect trade, TMs and patent variables in order to conduct
an econometric analysis. For the number of international TMs application, we use the data of WIPO IP Statistics Data
Center. From the database, we extract variables in terms of TMs by origin, destination, NICE class and year.
Figure 2 explains the trend in the number of international TMs applications in our samples from 2004 to 2014. Its
number is 2,864,948 in 2004 and 5,188,337 in 2014, which indicates that TMs applications have been almost doubled
during the period. In our study, a patent variable is also important. As we mentioned, both TMs and patent are ofimportance in company’s strategy regarding intellectual property rights and branding. In Figure 3, the variation in thenumber of international patent application is summarised. International patent application in 2004 is 1,574,300, which islower than TMs applications in the same year. Although its number has been gradually increasing until 2014, that is
2,680,900, still international applications of TMs are greater than those of patents. So as to check the difference between
OECD and non-OECD countries, we calculate the number of TMs applications by country characteristic and sector.
Table 1 reports the number of international TMs applications by income level, sector and year. Firstly, the average
number of TMs application has been gradually increasing in totally, from 37.6 in 2004 to 54.3 in 2014. Secondly, overall,TMs applications from OECD countries seem fewer than that of non-OECD countries during the period. This may be
because that OECD countries already have finished a large number of applications before 2004. In other words, thenumber of the stock of TMs registrations may be higher in developed economies than in developing economies. Finally,
OECD countries tend to register their TMs more in service sector than in manufacturing sector whereas for non-OECD
countries have an inverse relationship. So as to check the determinants of increased number of TMs application and test
the hypothesis, we employ the DID estimator.

Ⅳ Methodology
Main part of our specifications is to use the DID method in order to check the causal relationship between participationin the Madrid Protocol and firm’s TMs application. To do so, we can conduct the DID analysis with the pooled OLS
regression using interaction terms. In this case, the analysis needs more than two time periods and two groups in our
samples, which are treatment and control groups. The treatment group is samples, for instance people, firms andindustries, which experience the event we are interested in. The control group is individuals who are not affected by theincident. To quantify the average effect of treatments, we can use the following equation:𝑦 = 𝛽0 + 𝛽1 𝐷𝑃 + 𝛿0 𝐷2 + 𝛿1 𝐷𝑃 × 𝐷2 + 𝑢31(1)JAFTAB Research Paper,Vol.7,2018（Haneda）

where y is the outcome variable of main interest. In the two-period model, 𝐷𝑃=1 if a sample is in treatment group in the
period two and 0 otherwise. 𝛽1 𝐷𝑃 captures the difference between the treatment and control group before the event.
𝐷2=1 in the second period and 0 in the first period. 𝛿0 𝐷2 captures the aggregate year effects even the incident does notoccur. 𝑢 is the error term, Let us suppose that 𝑦̅ is the average value of the outcome and T, C, 1 and 2 denote treatmentgroup, control group, period 1 and period 2 respectively. Now, 𝛿̂1 from OLS estimation can be written as:𝛿̂1 = (𝑦̅𝑇,2 − 𝑦̅𝑇,1 ) − (𝑦̅𝐶,2 − 𝑦̅𝐶,1 )(2)where the first term in the right-hand side of equation (2) is the difference in the mean of outcome values between the
period 1 and 2 for the treatment group and the second term is that for the control group. We can interpret 𝛿̂1 as theaverage effect of the event or policy that we are interested in. In addition, we can add other covariates in the equation (1)but the interpretation of 𝛿̂1 is unchanged (Wooldridge 2010: 146-148).
However, there has been a concern about a serial correlation in the DID estimation (Bertrand et al. 2004).
According to Greene (2011), whether serial correlation causes serious bias in t-statistics and significance levels in the
DID empirical works depends on three issues. The first one is the length of the time series used in the papers and thesecond one is the fact that the most commonly used dependent variables tend to be serially correlated. The last one iswhether studies include any solutions (Greene 2011: 249-259)6.
In order to quantify the effect of the Madrid Protocol on international transfers of TMs, we use the DID estimation 7.
We estimate the following equations with Ordinary Least Squares (OLS) in our empirical analysis:
𝑌𝑖𝑗𝑘𝑡 − 𝑌𝑖𝑗𝑘𝑡−1 = 𝛽1 𝑀𝑎𝑑𝑟𝑖𝑑𝑖𝑡 + 𝛽2 𝑋𝑖𝑗𝑘𝑡−1 + 𝜀𝑖𝑗𝑘𝑡(3)where i, j, k and t are origin country, destination country, industry and year respectively. 𝑌 is the number of TMs
applications and 𝑀𝑎𝑑𝑟𝑖𝑑𝑖𝑡 is a dummy variable that takes a value of one if country i signs the Madrid Protocol in year
t. X is a vector of variables controlling for decisions of TMs applications. Following Lybbert, Zolas and Bhattachayya(2014), we include variables such as change in the number of patent applications, value of exports, FDI and R&D
investment 8. The definitions of each variables as well as descriptive statistics are reported in table 3 and 4 respectively.
In the equation (3), we investigate the impact of the Madrid Protocol on the trade in TMs. In other words, its effecton the change in TMs transfers between year t and year t-1 is explored. All coefficients are expected to be positive.

Ⅴ

The impact of the Madrid Protocol on international TMs transfers

Table 5 summarises the results from the DID estimation for all sectors. After controlling for variables that affect the
number of TMs applications, the coefficient of Madrid is statistically significant and positive. This means that the
Madrid Protocol may increase TMs applications among member countries. For Patent and Exports variable, theircoefficients are statistically significant and positive. These are consistent with the results of Lybbert, Zolas andBhattachayya (2014). As Dernis et al. (2015) and Nakamura (2014) emphasise, there may be the complementary effectof TMs on patents. In other words, the combination usage of patent and TMs registrations may be important in order forcompanies to protect their invention and technology. The coefficient of FDI is not statistically significant and that of
R&D is even negative. To check the robustness of these results, we divide our sample into two parts, namely
manufacturing sectors and service sectors.
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日本貿易学会研究論文第 7 号,2018（Haneda）

Table 6 and 7 show the results from estimations for manufacturing and service industries respectively. The maindifferences between them are twofold. Firstly, there might be heterogeneous impacts of the Madrid Protocol oninternational TMs registrations between manufacturing and service fields. Its coefficient is statistically significant andpositive for the results of manufacturing sector while its sign is not significant in the estimation of service industries. Oneof the reasons could be that new entry countries of the Madrid Protocol are mainly non-OECD countries and theirstrategies focus on manufacturing sector rather than service sectors, although we need additional estimations in order todiscuss the different impacts of the Madrid Protocol. The fact also can be seen in the table1. As we stated, the average
number of TMs applications in manufacturing sectors from developing economies is higher than that in service industry.
Secondly, the coefficient on FDI is positive and statistically significant for the estimation of service sector, which is not
the case for manufacturing firms. This might be explained by the fact that service activities may enter the foreign
markets through FDI than trade because of its characteristics. For instance, on the one hand, when a firm opens a
restaurant in another country, they may carefully care about logo or name of their shop rather than those of exported
ingredients or foods because they are cooked by chefs immediately. On the other hands, exported manufactured products
can be easily copied by foreign companies if exporting firm does not register its patent and TMs9. As a policy
implication, it can be stated that the Madrid Protocol may have positive impact on international TMs applications andmight be important for the branding, though its effect seems to be limited to manufacturing sectors.
It needs to be mentioned that this paper only uses industry-level data and cannot discuss firms’ branding strategies
overseas precisely. To conduct further studies, more detailed data of TMs among countries and firm-level TMs data
should be developed.

Ⅵ Concluding remarks
This paper sheds light on the effect of the Madrid Protocol on international transfers of TMs using industry-level datasets
over the period of 2004-2014. In firms’ branding strategies, combination usage of patent and TMs registrations has
become crucial in recent years. Additionally, for some companies, IP bundle is much more important in international
markets.
The main findings from the DID estimation are threefold. Firstly, our result suggests that the Madrid Protocol may
reduce the transaction cost of TMs applications and increase the number of TMs submissions. This result supports our
hypothesis, which is positive relationship between the participation in the Madrid Protocol and international TMs
applications. Secondly, the results from estimations for each sector show that the effect is limited to manufacturingindustries. However, this paper cannot discuss the issues more deeply because we only use aggregated industry-level
data and focus on the difference between two sectors. Finally, the result shows that inventors may use trademarks
complementary as a protection of their patents. This finding is consistent with results of previous analyses andemphasises the importance of IP bundle mentioned by Dernis et al. (2015).
As a policy implication, the Madrid Protocol should be accepted by more countries, especially non-OECD
economies, so as to reduce transaction costs, even though target may be mainly manufacturing industries.
It should be noted that there are several things to do relating to this paper. Firstly, further studies need to develop
more disaggregated concordance in terms of patents and TMs since each NICE 2-digit code includes too many sectors.
For instance, NICE classification has codes beyond 2-digit level. The mapping of product-level codes between different
classifications may be helpful for future works. Secondly, empirical analyses on the topic using firm-level dataset should
be conducted if it is possible. Finally, mode suitable estimation method needs to be considered in order to control for the33

JAFTAB Research Paper,Vol.7,2018（Haneda）

endogeneity and investigate causal relationship between the Madrid Protocol and TMs applications.

Footnote
1. See the following article: http://toyokeizai.net/articles/-/131079.
2. Please see the following;
webpage:http://www.uspto.gov/trademarks-getting-started/trademark-basics/trademark-patent-or-copyright
3. Please see the following webpage; https://euipo.europa.eu/ohimportal/en/trade-mark-definition.
4. Member countries are reported in the table 2 in appendix.
5. See the following file for more details:
http://www.wipo.int/export/sites/www/classifications/nice/en/pdf/text_ncl_10_part_2.pdf
6. This paper uses -cluster- option in the econometric analysis to avoid the problem.
7. Many studies employ the combination of the DID and Propensity Score Matching (PSM) methods for their empiricalanalyses to control for endogenous selections. However, we only use the DID method because of data issues.
8. According to Lybbert, Zolas and Bhattachayya (2014), a higher protection level of intellectual property rights
positively affects TMs transfers and it should be considered in the empirical analysis. Nevertheless, we exclude theprotection variable since it tends not to change over time, which means that its effect is controlled by country fixed
effects.
9. Exports variable for service sectors does not mean the trade in service. It is the export value in service related sectors,
thus, interpretation can be the same as the results of manufacturing sectors.

References
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Dernis H., Dosso M., Hervás F., Millot V., Squicciarini M. and Vezzani A. (2015), World Corporate Top R&D Investors:
Innovation and IP bundles, A JRC and OECD common report. Luxembourg: Publications Office of the European
Union.
EUIPO’s webpage (https://euipo.europa.eu/ohimportal/en/trade-mark-definition: accessed in 10/9/2016).
Graham, S.J.H. and Somaya, D. (2006), “Vermeers and Rembrandts in the Same Attic: Complementary between
Copyright and Trademark Leveraging strategies in Software,” Georgia Institute of Technology TIGER Working
Paper.
Greene, W. H. (2011), Econometric Analysis, 7th edition, Upper Saddle: Prentice Hall.
Greenhalgh, C. and Longland, M. (2005), “Running to Stand Still? – The Value of R&D, Patents and Trade Mark in
Innovating Manufacturing Firms,” International Journal of the Economics of Business, 12 (3), 307-328.
Greenhalgh, C. and Rogers, M. (2012), “Trade Marks and Performance in Services and Manufacturing Firms: Evidenceof Schumpeterian Competition through Innovation,” Australian Economic Review, 45 (1), 50-76.
Greenhalgh, C. and Rogers, M, Schautschick, P. and Sena, V. (2011), “Trade Mark Incentives,” Intellectual Property
Rights Office, Report 2011/1.
Helmers, C. and Rogers, M. (2011), “Does Patenting Help High-Tech Start-Ups?,” Research Policy, 40 (7), 1016-1027.
Helmers, C. and Schautschick, P. (2013), “The Use of Intellectual Property Right Bundles by Firms in the UK,”
Intellectual Property Rights Office, Report 2013/28.
Lybbert, T. J., Zolas N. J. and Bhattachayya, P. (2014), “An “Algorithmic Links with Probabilities” Concordance for34

日本貿易学会研究論文第 7 号,2018（Haneda）

Trademarks for Disaggregated Analysis of Trademark and Economic Data,” WIPO Economics & Statistics Series,
No.14, 1-30.
Lybbert, T. J. and Zolas, N. J. (2014), “Getting patents and economic data to speak to each other: An “Algorithmic linkwith Probabilities” approach for analyses of patenting and economic activity,” Research Policy, 43(3), 530-542.
Mendoça, S., Pereira, T. S. and Godinho, M. M. (2004), “Trademarks as an indicator of Innovation and Industrial
Change,” Research Policy, 33 (9), 1385-1404.
Millot, V. (2009), “Trademarks as an Indicator of Product and Marketing Innovations,” OECD Science, Technology andIndustry Working Papers, 2009/06, OECD Publishing.
Nakamura, K. (2014). “Economic Analysis of Trademarks: Trends and Prospects,” Kokumin-Keizai-Zasshi, 210 (2),85-103.
Schmoch, U. (2003) “Service Marks as Novel Innovation Indicator,” Research Evaluation, 12 (2), 149-156.
USPTO’s webpage (http://www.uspto.gov/trademarks-getting-started/trademark-basics/trademark-patent-or-copyright:
accessed in 10/9/2016).
WIPO (2016), GUIDE TO THE INTERNATIONAL REGISTRATION OF MARKS UNDER THE MADRIDAGREEMENT AND THE MADRID PROTOCOL, Genova.
Wooldridge, J. M. (2010), Econometric Analysis of Cross Section and Panel Data, Second revisited edition, Cambridge:
The MIT Press.

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JAFTAB Research Paper,Vol.7,2018（Haneda）

Appendix
Figure 1. The difference between The Madrid System and the Madrid Protocol

Note: The figure is drawn by the author.

Figure 2. The number of international TMs applications
6,000,000
5,000,000
4,000,000
3,000,000
2,000,000
1,000,000
0

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

Total 2,864,948 3,120,634 3,337,682 3,421,078 3,406,662 3,352,034 3,798,116 4,283,578 4,548,055 4,852,703 5,188,377

Source: WIPO statistics database.

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日本貿易学会研究論文第 7 号,2018（Haneda）

Figure 3. The number of international patent applications
3,000,000
2,500,000
2,000,000
1,500,000
1,000,000
500,000
0

2004

Total 1,574,300

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

1,702,900

1,791,100

1,874,400

1,929,400

1,855,600

1,997,400

2,158,000

2,356,600

2,564,800

2,680,900

2009
38.1
37.4
40.3
39.7
37.4
47.7
35.5
37.4
28.9

2010
41.8
41.0
45.0
40.7
38.4
49.6
43.3
44.6
38.0

2011
46.5
45.6
49.9
40.1
38.0
51.2
54.5
56.1
48.1

Source: WIPO statistics database.

Table 1. The average number of industry-level TMs applications
Country
Total

Industry
Total
Manufacturing
ServiceOECD
Total
Manufacturing
Service
NonOECD Total
Manufacturing
Service

2004
37.6
37.2
38.9
36.8
35.8
40.6
39.4
40.5
34.6

2005
38.1
37.9
39.2
37.4
36.6
40.7
39.5
40.4
36.1

2006
35.6
34.7
38.8
35.7
34.2
41.1
35.4
35.6
34.5

2007
37.0
35.8
41.5
39.3
37.3
46.7
33.4
33.6
32.9

Source: WIPO statistics database.
Note: Author’s calculation.

37

2008
37.0
35.6
42.3
41.7
39.2
51.0
30.4
30.5
29.9

2012
49.9
49.0
53.1
42.2
39.4
52.5
60.2
61.9
54.0

2013
51.6
50.3
56.4
45.4
42.0
58.0
59.5
60.9
54.1

2014
54.3
52.5
61.3
44.6
41.1
58.2
66.6
67.0
65.3

JAFTAB Research Paper,Vol.7,2018（Haneda）

Table 2. Member countries of the Madrid Protocol
Entry year Country
1995
United Kingdom, Sweden, Spain, China, Cuba
1996
Denmark, Germany, Norway, Finland, Czech Republic,
Monaco, Democratic People's Republic of Korea
1997

Poland, Portugal, Iceland, Switzerland, Russian Federation,
Slovakia, Hungary, France, Lithuania, Republic of Moldova

1998

Serbia, Slovenia, Liechtenstein, Netherlands, Curacao, Sint
Maarten, Bonaire, Saint Eustatius and Saba, Belgium,
Luxembourg, Kenya, Romania, Georgia, Mozambique, Estonia,
Swaziland

1999

Turkey, Lesotho, Austria, Turkmenistan, Morocco, Sierra
Leone

2000

Latvia, Japan, Antigua and Barbuda, Italy, Bhutan, Greece,
Armenia, Singapore, Ukraine

2001
2002
2003

Mongolia, Australia, Bulgaria, Ireland, Zambia
Belarus, The former Yugoslav Republic of Macedonia
Republic of Korea, Albania, United States of America, Cyprus,
Islamic Republic of Iran2004

Republic of Croatia, Kyrgyzstan, Namibia, Syrian Arab
Republic, European Union

2005
2006
2007
2008
2009
2010

Bahrain
Viet Nam, Botswana, Uzbekistan, Montenegro
Azerbaijan, San Marino, Oman
Madagascar, Ghana, Sao Tome and Principe
Bosnia and Herzegovina, Egypt, Liberia
Sudan, Israel, Kazakhstan, Curacao, Sint Maarten,
Bonaire, Saint Eustatius and Saba

2011
2012
2013
2014
2015

Tajikistan
Philippines , Colombia, New Zealand
Mexico, India, Rwanda, Tunisia

2016

Lao People's Democratic Republic

African Intellectual Property Organization
Zimbabwe, Cambodia, Algeria, Gambia

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Table 3.

The definition of variables

Variables
TMs applications
PatentExports
FDI
R&D
MadridTable 4.

Definition
Log of the number of international TMs applications
Log of the number of international patent applications
Log of export value
Log of FDI value
Log of R&D value
Take value of 1 if a country joins the Madrid Protocol in theyear, 0 otherwise

Classification
NICE 2 digit
IPC 4 digit
SITC 2 digit

SourceWIPOWIPO
UN Comtrade
WDI
WDI
METI

Descriptive statistics

Variable

Mean

Std. Dev.

Min

Max

TMs application-0.0250.759-4.682

4.963

Madrid

0.005

0.072

0

1

Patent

0.079

0.212

-2.398

2.197

Exports

0.074

0.722

-15.797

15.644FDI

0.182

18.499-354.250

332.064

R&D

0.035

0.100

-0.462

0.493

Table 5.

Estimation results for all sectors

VARIABLES
MadridPatentExports
FDI
R&D
Constant

Observations
R-squared(1)
TMs application
0.079**(0.021)0.037**(0.008)0.025**(0.002)0.000(0.000)-0.037*(0.018)-0.029**(0.002)(2)
TMs application
0.029(0.020)0.074**(0.006)0.027**(0.002)(3)
TMs application
0.101**(0.017)0.022**(0.007)-0.110**(0.016)-0.006**(0.002)0.000(0.000)-0.017(0.016)-0.020**(0.002)

212,205
0.001

311,6130.001

265,4540.000

Note: The values of Patent, Exports, FDI, R&D are defined as the difference of the log of those variables. Robust
standard errors in parentheses. ** p<0.01, * p<0.05, † p<0.1.

39

JAFTAB Research Paper,Vol.7,2018（Haneda）

Table 6. Estimation results for manufacturing sectors

VARIABLES
MadridPatentExports
FDI
R&D
Constant

Observations
R-squared

Manufacturing(1)
TMs application
0.092**(0.024)0.024*(0.009)0.030**(0.003)-0.000(0.000)-0.052**(0.020)-0.032**(0.002)
174,705
0.001(2)
TMs application
0.039†(0.023)0.066**(0.007)0.031**(0.002)(3)
TMs application
0.111**(0.019)0.011(0.008)-0.119**(0.017)-0.008**(0.002)-0.000(0.000)-0.036*(0.018)-0.023**(0.002)

256,5470.001

217,6420.000

Note: The values of Patent, Exports, FDI, R&D are defined as the difference of the log of those variables. Robust
standard errors in parentheses. ** p<0.01, * p<0.05, † p<0.1.
Table 7. Estimation results for service sectors

VARIABLES
MadridPatentExports
FDI
R&D
Constant

Observations
R-squared

Service(1)
TMs application
0.021(0.044)0.095**(0.020)0.014**(0.005)0.001*(0.000)0.044(0.043)-0.014**(0.004)37,5000.001(2)
TMs application-0.018(0.042)0.106**(0.015)0.015**(0.004)(3)
TMs application
0.064†(0.036)
0.068**(0.016)-0.060(0.037)0.002(0.004)0.001**(0.000)0.079*(0.038)-0.006(0.004)55,0660.001

47,8120.001

Note: The values of Patent, Exports, FDI, R&D are defined as the difference of the log of those variables. Robust
standard errors in parentheses. ** p<0.01, * p<0.05, † p<0.1.
40