Journal of Japanese Management Vol.1, No.2, May 2017

ISSN 2189-9592

Factor Analysis on Software Piracy
Lianfeng Yang

Nagoya City University, Japan
Japan Society for Information and Management
E-mail:yourenhou06@yahoo.co.jp
Abstract
Many empirical researches of software piracy have focused on the domestic factors, suchas corruption, democracy, economic freedom et al. However, this paper assesses the extent of
the international factors contributing to software piracy. It is founded that Patent
Cooperation Treaty (PCT) international applications have a significant impact on it. Thatmeans international intellectual protection is a good way to control the piracy. Additionally,
corruption is not a significant factor on piracy as previously believed.
Keywords
software piracy, corruption, PCT International application．
(1) Introduction

nonlinear the decrease in economic growth

It is well known that the issue of

diminishes with piracy (Andrés and Goel,software piracy has been growing more2012).

severe worldwide in recent years. “software

While numerous previous studies havepiracy” can be defined as the unauthorized use

looked at the issue of software piracy, sinceof computer software or the unauthorized

it is a complex issue (Goel and Nelson, 2009;

distribution of copies of software without

Lau, 2003; Reinig and Plice, 2011). It has not

permission being given by theowner 1 .”been

elucidated

fully.

Studiesthat

According to the Software Alliance’s Ninthempirically analyze factors in software

Annualpiracy from a macroeconomic approach do so

BSA

(The

Business

Alliance) Global Software

Software
Piracyusing models based on one or more of the five2011 damages caused by piracy

following factors: economic factors, cultural

totaled USD63.456 billion worldwide andfactors, technological factors, legal factors,

both piracy and the amount of related

and educational factors (Gomes, Cerqueira

damages were in an increasing trend.

and Almeida, 2014).

Study 2 , inSoftwarepiracy2011

affects

economic

Gross Domestic Product (GDP) per-growth. Greater piracy of computer software

capita often is used as an economic factor.

lowers economic growth. However, theHarbi, Grolleau and Bekir (2012) and Panas

relationship between piracy and growth is

and

1

2

See Lau (2003).

17

Ninni

(2011)

http://www.bsa.or.jp/

find

a

relationshipJournal of Japanese Management Vol.1, No.2, May 2017

resembling a Kuznets curve between the two.

ISSN 2189-9592

2011; Goel and Nelson, 2009).

If there is a Kuznets curve relationshipIn analysis of legal or systemic factors,

between piracy rate and GDP per-capita,

economic freedom and freedom of the press

then protection of intellectual property (IP)are used frequently. The concept is sociallyrights should be conducted in accordance

accepted that the higher the degrees ofwith the stage of economic development, but

economic freedom and freedom of the press

over the long term there would be a negative

the lower the piracy rate. In addition, many

correlation between piracy rate and GDP

empirical analyses use corruption as a

per-capita.

systemic factor (Andrés and Goel, 2011;

Other

as

Gomes,

Bagchi, Kirs and Cerveny, 2006; Banerjee and(2014)

have

Williams, 2013; Goel and Nelson, 2009;

developed toReinig and Plice, 2011). Analysis of data on

serve as an indicator of national character,the piracy rate and indices of corruption

as a cultural factor, indicating that nationalshows a very high correlation between thecharacter do affect the piracy rate. Such as

two.

Cerqueirastudiesandsuch

Almeidaemployed Hofstede’s

index 3 ,Rafee and Rouibah (2010) found that

Regarding

educational

factors,aawareness treatment was significant factor

negative correlation has been identified

in reducing intention toward digital piracy.

between the literacy rate of people aged 15

Of course, the level of technology is

and above and the piracy rate (Goel andlikely to impact the piracy rate. It is

Nelson, 2009). However, it also be argued

conceivablethat this result is unclear (Andrés and Goel,that

strongprotectionofauthorized software would increase the costs2011).

of piracy, and as the costs of piracy rise, theThus, each of the papers discussed

piracy rate would decrease. However, since

above focuses solely on domestic factors

protection of authorized software would

when examining piracy. Certainly, a strong

decrease the number of users of the software,correlation has been demonstrated between

in some cases it would not be desirable todomestic factors and the

producers of authorized software 4 . The

suggesting that improvement of domestic

number of Internet users is used as afactors would be an effective way to reduce

technological factor.

Bagchi, Kirs andpiracy. However, since the issue of software

Cerveny (2006) show that Internet users had

piracy is complex, it is conceivable that itpartial influence on software piracy. Market

cannot be resolved fully through domestic

size is another technology factor often befactors alone. The global age is characterized

used in empirical analysis (Andrés and Goel,by all countries advancing in cooperation

3

Hofstede’s index was developed in 1980 by the Dutch
social scientist Geert Hofstede in order to measurequantitatively and index the national character ofmultiple countries. It consists of the following six
indices: (1) Power distance index, (2) Individualism,(3) Uncertainty avoidance index, (4) Masculinity, (5)Long-term orientation, and (6) Indulgence versus

piracy rate,

restraint.
4Since in general software involves network externalities,

the more the number of users increases the more thevalue of the software rises. For this reason, producersof authorized software aim to increase the number ofusers of their software.

18

Journal of Japanese Management Vol.1, No.2, May 2017

ISSN 2189-9592

with others. When advancing in cooperation

power. The reason this paper uses in its

with other countries, it is possible to protect

analysis the four factors other than cultural

one’s own country’s rights through mutual

factors is because such analysis has beenrecognition by countries of each others’common traditionally (Andrés and Goel,rights. In general, Patent Cooperation

2011; Goel and Nelson, 2009), and because it

Treaty (PCT ) international applications

is not easy to control the cultural factor ofplay an important role in getting othernationalcountries to protect one’s own country’s

through policy. The results show that ourscience and technology. A producer can

new variable of the number of applications

secure exclusive interests on a global basis

for PCT international applications does havethrough the exclusivity of PCT international

explanatory power with regard to the piracy

applications. For this reason, the increase in

rate. This can be considered to suggest the

the

PCT

possibility that countries’ recognition of eachinternational applications by producers in aothers’ PCT international applications could

country can be considered to relate to

be an effective way to reduce piracy.

numberofapplications

forstrengthening that country’s government’s

Thecharacter(Hofstede’s

paper employs theindex)

following

motivation to crack down on patent-related

structure. Section (2) presents a literaturepiracy. It is conceivable that recognizing

review. Section (3) illustrates research data

each other’s patents would have the effect ofon software piracy. Section (4) describes theprotecting IP rights. Accordingly, it can beanalytical method and models. Section (5)considered important and meaningful toillustrates the results of empirical analysis.

study the impact on the piracy rate ofSection (6) provides some considerations.

numbers

PCT

Section (7) concludes.

Based on the above perspective, this(2) Literature review

ofapplicationsforinternational applications.
paper analyzes the piracy rate through a

The issue of software piracy is aregression model in which the explanatorycomplex one to begin with, one impacted bypower of technological factors in particular isnumerous factors. Previous studies argue

strengthened, as one attempt at examiningthat it would not be possible to resolve piracy

factors such as those above. In addition toissues without improvements on all the

independent variables related to the four

factors of economic, systemic, social, andfactors used in Andrés and Goel (2011):

technological factors.

systemic, economic, social, and technological

The following is a description of thefactors, the model employs number of

specific indices impacting the piracy rateapplications

international

used as independent variables in theapplications as a new independent variable

following regression analysis, along with therelated to technological factors, developing areasons for using them, for each of the above

regression model to explain the piracy rate

four factors and in accordance with abased on these and using it with real-worldprevious study (Andrés and Goel, 2011).

data to seek out variables with explanatory

Differences from Andrés and Goel (2011) are

for

PCT

19

Journal of Japanese Management Vol.1, No.2, May 2017

ISSN 2189-9592

the facts that this study uses number ofstrategy of adding to authorized software

applications

international

high-quality value capable of differentiating

applications, which it did not use, and thatit from pirate software then consumers

this study does not use the size of thewould be likely to demand high-quality

software market, which had little impact on

authorized software as they enjoy greater

the piracy rate.

returns from its use. This is thought to be

for

PCT

As systemic factors, this study uses thethecorruption index, freedom of the press, andgrounds

for

the

above

negativecorrelation.

economic freedom. It is likely that in a

As a social factor, this study uses thecountry with a high corruption index pirates

national literacy rate. Gomes, Cerqueira andwould be able to secure a degree of toleration

Almeida (2013) show that more schoolingfor their acts or piracy through means such

years have the opposite effect to piracy. But

as bribery of government officials, increasing

Depken and Simmons (2004) have not

the piracy rate at a result. That is, it isidentified a significant relationship between

conceivable

literacy

that

there

is

a

positive

rate

and

piracy

rate.

It

is

correlation between the corruption index

conceivable that the national literacy rate

and the piracy rate. On the other hand, there

could have some impact on the piracy rate

is likely to be a negative correlation between

since as literacy increases the number of

freedom of the press (Andrés and Goel, 2011;users of software (both pirate and authorized

Salahodjaev Odilova and Andrés, 2016) andsoftware) would increase. However, it is not

economic freedom (Bezmen and Depken,

necessarily possible to determine clearly

2006; Fraj, 2015) on one hand and the piracy

whether this correlation would be positive or

rate on the other. It is conceivable thatnegative.

improving

determine the sign of the correlation based

these

would

increasesocialtransparency, making it easier to uncover

Accordingly,

this

paper

will

on the results of individual data analysis.

illegal acts by government and pirates andAs a technological factor, this study

increasing the risks of piracy as a result, souses number of Internet users. Goel andthat the piracy rate would decrease.

Nelson (2009) showed that internet users

This study, like numerous previous

will mitigate the software piracy. It is

studies, uses GDP per-capita as an indicator

conceivable that as this number increasesof economic factors. This is considered tothe piracy rate would decrease because it

have a negative correlation to piracy (Andrés

would become easier to detect acts of piracy.

and Goel, 2011; Chen, Chen and Yeh, 2010;

In other words, there could be a negative

Goel and Nelson, 2009). In fact, piracy iscorrelation between the number of Internet

unlikely to decrease if authorized software

users and the piracy rate.

and pirate software are identical in value

The independent variables used in theand consumers expect the same benefits

regression model, reflecting consideration of

from both authorized software and piracy.

previous studies, are as described above.

On

This paper also uses the number of

the

other

hand,

if

producersofauthorized software were to adopt theapplications
20

for

PCT

international

Journal of Japanese Management Vol.1, No.2, May 2017

ISSN 2189-9592

applications as an independent variableapplications

related to technological factors. By taking

applications would serve to make them moreoutaconscious of the need to demand an

producer can secure exclusive interests on aenvironment in which protection of IP rights

global basis through the exclusivity secured

strengthens, improving the piracy rate as aby patents. For this reason, an increase in

result. Accordingly, in the following analysis

the

as

PCT

international

numberofapplications,applications

for

PCT

international applications by producers in a

well

for

this

PCT

paper

international

focuseson

thisindependent variable in particular.

country can be considered to relate to astrengthening

of

that

country’s(3) Research data

government’s motivation to crack down on

As described above, the regression

patent-related piracy. At the same time, it

analysis used in this paper employs thealso can be considered to raise awarenesspiracy rate as the dependent variable andconcerning elimination of piracy as thevariables included in four categories as seen

producers

in

who

apply

for

the

PCT

AndrésandGoel(2011)

theinternational applications attempt to protect

independent

the value of the technologies that they have(indicators of corruption, freedom of thedeveloped themselves. For the above reasons,press, and economic freedom), economic

the

PCT

factors (GDP per-capita), social factors

international applications is expected to(national literacy rate), and technologicalhave a negative correlation to the piracy rate.

factors (number of Internet users, number of

numberofapplicationsforvariables: systemicasThis paper considers the final variableapplications

numberPCT

applications). The sources and meanings ofinternational applications to be of particular

the data used in this analysis are outlined

importance. This is because since thebelow.

ofnumberofofapplications

applications

for

for

PCT

technological progress, an increase in theofinternational

applications
applications

for
also

innovation.

In

fact,

PCT

organization is considered highly credible,

involvesitand the results of its studies on piracy andprotection of IP rights have been cited inisnumerous

conceivable that if this independent variable
does

affectproducers5

topiracyincreasethenthepapers.

Thepiracyrate

iscalculated as shown below:

encouraging
numberinternational

Software Alliance (BSA) 5 is used. This

aspects that make it possible to maintainsustained

PCT

1. Piracy rate (Piracy, abbreviated pir)
For piracy rate, data published by theinternational applications is related tonumberforfactorsof

http://www.bsa.or.jp/index.html. The BSA measures

Andrés and Goel, 2011; Goel and Nelson, 2009; Harbi,

the piracy of commercial software. These estimates are

Grolleau and Bekir, 2012; Lau, 2003; Reinig and Plice,some of the most reliable ones and have been used2011),

largely in empirical papers (for instance Andrés, 2006;

unreliable.

21

in spite ofcriticism that the data areJournal of Japanese Management Vol.1, No.2, May 2017

points, with a higher figure indicating apiracy rate=

lower degree of media freedom. For this

Quanitity of pirated PC software
Total quanitity of PC software installedreason, this figure can be described as anindicator of lack of freedom of the press. This

The denominator above is derived by

figure is made up of three elements: (i)multiplying the number of PCs on which

influence of laws and regulations on thesoftware is installed by the quantity of PC

media (ranging from 0 to 30 points), (ii)software per computer, while the numerator

political pressure and media internal control

is derived by subtracting the quantity of(ranging from 0 to 40 points), and (iii)

authentic PC software from the denominator,

economic impact of media (ranging from 0 toor the denominator minus total units of PC

30 points). A total score in the range of 0-30

software sold divided by the average price ofis considered to indicate a state of freedom,

PC software.
2.

while one in the range 31–60 indicates the

Corruption

index

presence of freedom to some degree and one(Corruption,adbreviated cor)in the range 61–100 indicates a lack ofAs an index of corruption, this study

freedom.

uses the estimated value of Control of

4. Economic freedom (Freedom of Economic,

Corruption 6 published on the Web by theabbreviated ef)

World Bank. This is an indicator of theDatagovernance ability of government, ranging

corruption),

corruption. These data are collected fromfree markets (freedom of trade, freedom ofinvestment, financial freedom). Each oforganizations,these elements is graded as a score in theinternational agencies, and private-sector

range 0–100, and the average of these scoresorganizations, among other sources.
the

press

is used as the value of economic freedom.
The higher this value, the higher the(Democracy,

assessed degree of economic freedom.

abbreviated dec)
This study uses data published by

5.

Freedom House7 concerning freedom of the7GDP

Per-capita(GDP

Per-capita,

abbreviated gdp)

press. The data range in value from 0 to 100
6politics

labor freedom, currency freedom), and (iv)through research organizations, think tanks,ofconstitutional(iii) regulatory efficiency (business freedom,on governance, based on data collected

Freedom(ii)(political freedom, government expenditure),companies,

citizens, and experts concerning their views

nongovernmental

Heritage(i) politics (property rights, freedom fromhigher the score the lower the degree ofnumeroustheelements from the following four categories:

the trustworthiness of government, and the

with

by

freedom. Economic freedom is made up of 10

corresponds to a 90% confidence interval forinterviews

published

Foundation 8 are used to indicate economic

in value from −2.5 to 2.5 points. This range

3.

ISSN 2189-9592

http://www.worldbank.org/
http://www.freedomhouse.org/report-types/freedom-

8

22

press
http://www.heritage.org/index/download

Journal of Japanese Management Vol.1, No.2, May 2017

ISSN 2189-9592

For GDP per-capita, this study uses theof R&D in each country the higher thisdata published on the Web by the Center for

number the greater the incentive to protect

Internationalthe

its own IP rights is likely to be. For this

University of Pennsylvania9. These data arereason, this paper focuses on the number ofconsidered the most trusted and most widely

applications

usedapplications. Furthermore, to eliminate thedataComparisons

on

GDP

at

per-capita

inmacroeconomic analysis.
6.

National

literacyratenumber(Literacy,

for

PCT

for PCT international applications is theWorld Intellectual Property Organization12,

follows their precedent. The data used arewhile data published by the World Healththe latest data published on Wikipedia 10 .

Organization (WHO) were referred to for

While for most countries these data covereach nation’s population13.

ages 15 and older, for a few countries
different ages are used.

Data adjustments
Actually, the countries for which data

7. Number of Internet users (Interneton the above dependent variable (piracy

user, abbreviated net)rate) and seven independent variables are

For number of Internet users, data

published vary by variable. For this reason,

published on the Web by the International
Telecommunication Union11 are used. These

Table 1. Meaning of each variable
Variable
pir
cor
dec
ef
gdp
lit

data indicate the number of Internet users
in a country per 100 citizens.
ofapplications

international

applications

for

PCT

(Patent,

abbreviated pat)
Another independent variable used inthis model is the number of applications fornet

PCT international applications. While there
are various methods of totaling patentpat

applications by companies, since the number
forapplications

source for data on numbers of applications

an independent variable, and this paper

applicationsofthe number per million population. The

analysis have used national literacy rate asofinternational

international applications are converted toMany previous papers on empirical

NumberPCT

effects of population, for all countries theabbreviated lit)

8.

for

PCT

international

applications is considered to reflect the level912

https://pwt.sas.upenn.edu/
http://en.wikipedia.org/wiki/List_of_countries_by_literacy_rate
11 http://www.itu.int/en/Pages/default.aspx
10

Meaning
Piracy rate
Corruption index
Freedom of the press
Economic freedom
GDP Per-capita
Literacy rate of population
aged 15 and older
Number of Internet users
per 100 population
Number of PCTinternational applications
applied for per million
population

http://www.wipo.int/pressroom/en/articles/2012/article_0001.html

13http://memorva.jp/ranking/unfpa/who_2010_

population_total.php

23

Journal of Japanese Management Vol.1, No.2, May 2017

ISSN 2189-9592

the analysis in this paper is limited to the 86

of independent variable to piracy is as shown

countries for which data are available for all

in Table 4.

eight variables (see Appendix). Lastly, theTable 3. The result of simplest model
Variables
Estimated result
0.897
constant(13.19)-0.090cor(-4.67*)0.002
dec(2.62*)-0.003net(-4.41*)
̅2
R
0.770

table below reviews the variables used:(4) Analytical method and models
This section will use the independent
variables described at the end of theprevious section in a regression analysis
with piracy rate as the dependent variable.
Table 2 shows the variation in size and otherinformation for each variable.

Note: t-values are in parentheses. t- values aligned to
the right* above are those for which estimates are
statistically significant at the 1% significance level.

Table 2. Range of variation in size of eachvariable
Variable Mean
Max.
Min.
pir

0.58

0.93

0.20

Table 4. The correlation coefficient of

cor

0.30

2.38

−1.27

independent variable and logarithmic value

dec

43.56

94.00

10.00

of independent variable to piracy

gdp

19250

136248

1247

ef

64.42

86.10

37.10

cor

-0.836lcor-0.836

net

49.71

93.39

3.70

dec

0.708

ldec

0.761

lit

0.92

1.00

0.56

ef

-0.711lef-0.697pat

53.17

521.830.01

gdp-0.639lgdp-0.788lit-0.425llit-0.412net-0.792

lnet-0.698pat-0.663lpat-0.885pir

Notes: net is Number of Internet users per 100
population, pat is number of applications for PCTinternational applications per million population.

pir

Note: Variables with l at the beginning denote thelogarithmic value of variable.

Regression analysis with the simplest
model (All the coefficients in this paper are

The table indicate that the logarithmic

non-standardized coefficients).

value especially GDP and patent has apir = c1 + b1 cor + b2 dec + b3 ef + b4 gdp

higher+ b5 lit + b6 net + b7 pat + u1

correlation

than

originaldata.

The result will be as shown in Table 3

Regression analysis with changing variable

when remove the no significant independent
variable by t-test (the absolute value of t test

and logarithmic value of variable, three
result of model with the best 𝑅̅ 2 value is theis less than 1.96).

following.
𝑝𝑖𝑟 = 𝑎1 + 𝑎2 𝑙𝑐𝑜𝑟 + 𝑎3 𝑑𝑒𝑐 + 𝑎4 𝑙𝑔𝑑𝑝

The result shows that corruption is+𝑎5 𝑒𝑓 + 𝑎6 𝑙𝑖𝑡 + 𝑎7 𝑛𝑒𝑡 + 𝑎8 𝑙𝑝𝑎𝑡 + 𝑢1

significant to piracy as many previously(1a)studies. But the correlation coefficient of
𝑝𝑖𝑟 = 𝑏1 + 𝑏2 𝑙𝑐𝑜𝑟 + 𝑏3 𝑑𝑒𝑐 + 𝑏4 𝑙𝑔𝑑𝑝

independent variable and logarithmic value+𝑏5 𝑒𝑓 + 𝑏6 𝑙𝑖𝑡 + 𝑏7 𝑙𝑛𝑒𝑡 + 𝑏8 𝑙𝑝𝑎𝑡 + 𝑢2
24

Journal of Japanese Management Vol.1, No.2, May 2017

ISSN 2189-9592(5) Results of empirical analysis(1b)

Table 5 shows the results of estimation𝑝𝑖𝑟 = 𝑐1 + 𝑐2 𝑙𝑐𝑜𝑟 + 𝑐3 𝑑𝑒𝑐 + 𝑐4 𝑙𝑔𝑑𝑝

using regression model (1a), model (1b) and+𝑐5 𝑙𝑒𝑓 + 𝑐6 𝑙𝑖𝑡 + 𝑐7 𝑙𝑛𝑒𝑡 + 𝑐8 𝑙𝑝𝑎𝑡 + 𝑢3
(1c)model (1c). A look at the results of VIF for

Each of the coefficients 𝑎1 ~𝑎8 , b1 ~b8 ,each independent variable in Table 5 shows

𝑐1 ~𝑐8 will be estimated using this model. The

that each is substantially below 10, so thatterms 𝑙𝑐𝑜𝑟 , 𝑙𝑔𝑑𝑝 etc are abbreviations forthere is nothing similar to multicollinearity

the logarithms of the variables defined at the

between any of the independent variables,

end of the preceding section, ln(𝑐𝑜𝑟) ,and for this reason the results for theln(𝑔𝑑𝑝) etc, while 𝑢1 , 𝑢2 and 𝑢3 are error

regression coefficients can be surmised to beterms. Estimation is conducted using therelatively robust to variations in data values.

ordinary least squares (OLS) method. Since

Next, judgment of the statistical significancethe values of the corruption index rangeof the explanatory power of each regression

from −2.5 to 2.5, this paper uses a revisedcoefficient and each independent variable

corruption index in which 2.55 has beenusing t values shows that even at a

added to that value. All of the data used are

significance level of 10% the explanatory po-

for the year 2011.
Table 5. Results of estimation using regression model (1a), model (1b) and model (1c)Variable
Model (1a)Model (1b)Model (1c)constant
dec
ef
net
lit
lcor
lgdp

Result0.752(4.284)0.002(3.983*)-0.001(-0.601)-2.87 E-04(-0.417)0.520(4.755*)-0.007(-0.110)-0.065(-3.385*)

VIF

2.433
3.189

Result0.754(4.422)
0.002(4.123*)4.123(-0.543)

VIF

2.381

2.385

3.915
1.790
6.764
4.593

lnet

𝑅̅ 2

VIF

3.181

0.543
(4.855*)-0.009(-0.152)-0.062(-3.329*)

1.882
6.766
4.426

lef

lpat

Result0.883(2.084)0.002(4.113*)-0.0435.627(-5.788*)0.865-0.0182.898(-0.904)-0.042
5.237(-5.946*)
0.866

0.542
1.882
(4.843*)-0.0136.707(-0.220)-0.062
4.481(-3.322*)-0.0433.056(-0.431)-0.0182.922(-0.903)-0.042
5.234(-5.935*)
0.866

Notes: t-values are in parentheses, and t-values aligned to the right* above are those forwhich estimates are statistically significant at the 1% significance level.

25

Journal of Japanese Management Vol.1, No.2, May 2017

wer of the three variables corruption,

ISSN 2189-9592

at the same time).

economic freedom, and Internet users could

A look at the results in Table 6 shows

not be considered statistically significant.

that the values of all regression coefficients

By eliminating the lowest t value ofare statistically significant at the 1%

variables, the result is as the following insignificance level and that the corresponding

Table

independent variables have explanatory

6

(the

result is thesame byeliminating a variable at a time).

power vis-à-vis the dependent variable.
̅ 𝟐 hasComparing with the results ahead, 𝑹

Table 6. Results of regression analysis after
eliminating the lowest t values frommodel (1a), model (1b) and model (1c)
Estimated
Variables
VIF
result0.710
Constant(4.748)
0.003
1.727
dec
(5.354*)−0.071
3.344
lgdp(−4.518*)
0.536
1.675
lit
(5.226*)−0.0454.505
lpat(−7.050*)
𝑅̅ 2
0.869

been greatly improved, so the latter model isa superior model. Additionally, the common
explanatory variable is democracy only.
Other variable will be shuffled all. Notably,
corruption is not remained as independence
variable. As a result, this model combines
the original data and replaced logarithmic
data. In this model, corruption index will bedeleted by using 𝑙𝑔𝑑𝑝 and 𝑙𝑝𝑎𝑡 . That
means

𝑙𝑔𝑑𝑝

and

𝑙𝑝𝑎𝑡

are

betterindependence variables than corruption.
Incidentally, it is known that in thecase of regression analysis using cross sectional data as used in this study, the tNote: t-values are in parentheses, and t valuesaligned to the right* above are those for which
estimates are statistically significant at the 1%
significance level.

value often does not necessarily function
correctly as an indicator of statisticalsignificance due to a lack of uniformity in

Comparison of Table 5 and Table 6

distribution (Matsuura and McKenzie, 2012).

shows that the adjusted coefficient ofdetermination ( 𝑅̅ 2 ) remains largely

Accordingly, a check for such lack of
uniformity in distribution in this case wasunchanged and there was no difference in

conducted.

the fact that the explanatory power ofA White χ2 test with a null hypothesis

corruption, economic freedom and Internetof uniformity of distribution yields a χ2

users. These variables are not statisticallystatistic of 11.352, for which the p value issignificant. Accordingly, a regression model

0.658, so that the null hypothesis ofanalysis was conducted after eliminating theuniformity of distribution is not rejected.

variables corruption, economic freedom andInternet users as well. The results are shown(6) Consideration of resultsin Table 6 (There was no change in the

The results above can be summarized

results of the F test and the χ2 test between

as follows: First, the statistical significancethe case of eliminating economic freedomof each independent variable’s explanatory

alone and that of eliminating both variables

power will be verified. A look a Table 6 shows26

Journal of Japanese Management Vol.1, No.2, May 2017

ISSN 2189-9592

that all four of the independent variables ofcontrol piracy through improving theseindex of freedom of the press, GDP per-variables, since they involve large-scale

capita, national literacy rate, and number ofissues.

applications

for

PCT

international

This paper showed that the number ofapplications had statistically significant

applications

explanatory power with regard to the piracy

applications, which was not addressed inrate, indicating that all did affect piracy.

previous

While this finding is consistent with those of

explanatory factor with regard to the piracy

previous studies, it should be noted that

rate. What’s more, controlling this variableconsideration based on t value in particulardoes not involve unnatural issues with social

shows that the independent variable ofethics like those above and is effectively

numberPCT

correlated with social innovation, so that itinternational applications, introduced forcan be considered extremely significant. In

the first time in this paper, had the highest

fact, it is conceivable that as economic

degree of statistical significance.

globalization advances incentives will act onofapplications

for

for

studies,

PCT
isinternationalanimportantFirst of all, with regard to the nationalcountries and companies that have few

literacy rate, it should be clear that reducing

patents, encouraging them to obtain PCT

this rate even below its current level in orderinternational applications, and the resulting

to reduce the piracy rate would not be

increase in awareness of protection of

appropriate from economic considerations,patents (and copyright) could lead tobecause it would lead to a decrease in thestronger crackdowns on piracy. Accordingly,

number of users of software—not to mention

progress on creating an environment that

ethical reasons. It is conceivable that thewould encourage companies to apply for PCT

reason the piracy rate increases with aninternational applications can be considered

increase in the literacy rate is because of theas an effective means of decreasing theresultingincreaseinpiracy rate.

consumersusingpiratethenumberofsoftware,as

On the other hand, this study showed

individuals gain access to methods ofthat corruption, economic freedom, andevading the regulatory net. Realistically, thenumber of Internet users had little influencenational literacy rate is high in moston the piracy rate. While there is no problem

countries, so that the national literacy rate’swith this finding with regard to the latter

impact is not likely to be very pronounced.

two because previous studies also showed

The index of freedom of the press andthat they had no influence, it does conflict

GDP per-capita used in this paper both havewith the results of most previous studies

been used as variables explaining the piracy

that showed that corruption had a strong

rate in previous studies as well, and suchinfluence.

studies have identified them as having

corruption itself show that it can bestatistically significant explanatory power.

explained by factors such as freedom of the

However, it must be said that realisticallypress,

speaking it would in fact be difficult tofreedom (with coefficients of determination
27

Some

GDP

previous

per-capita,

studiesandon

economicJournal of Japanese Management Vol.1, No.2, May 2017

ISSN 2189-9592

of 82% or above). While correlation between

consumers

indices of corruption and the piracy rate areindividuals gain access to methods ofvery high, and as a result an index ofevading the regulatory net.

corruption alone can show a high degree ofusing

piratesoftware,as

4. The number of PCT international

explanatory power regarding piracy rate, theapplications

appliedaddition of numerous independent variables

population also affects piracy. An increase in

as in this study results in the elimination of

the number of patent applications leads to a

the explanatory power of the index ofdecrease in the piracy rate. It is conceivablecorruption. In light of these considerations,that this is because governments andindices of corruption, considered important

producers

in many previous studies, like piracy rate, be

protecting IP rights and more strongly

dependent variables explained by variables

motivated to protect their own property.

such as freedom of the press and GDP per-Results of each of the analyses in this study

capita rather than causes of piracy rate.

showed that the number of applications forbecome

for

more

per

millionconsciousof

PCT international applications had a strong(7) Conclusion

degree of explanatory power vis-à-vis the

The main purpose of this paper is toverifytheeffectapplications

for

of

increasing the number of applications forinternational

PCT international applications would beapplications on the piracy rate. Using data

meaningful in both economic and policy

from 2011, it analyzed the factors impacting

terms because it enables a country to carrypiracyout sustainable innovation.

while

applications

of

PCT

adding
for

the

the

PCT

numberpiracy rate, and it is conceivable that

numberofinternational

5. This paper showed clearly thatapplications as a variable for the first time.

corruption, considered an important factor

The results showed that GDP per-capita,in many previous studies, is not a factor.

index of freedom of the press, national

Considerationofofapplications

PCT international applications affect theapplications, introduced for the first time inpiracy rate. These findings are summarized

this study, showed that if countries with low

below:

numbersof

PCT

numberliteracy rate, and number of applications for

1. The piracy rate decreases with an

for

the

applications

international

for

PCT

international applications put effort into

increase in GDP per-capita.

suchfactors

relatedtotechnological

2. The piracy rate decreases with aprogress they would be able to address

decrease in the index of lack of freedom ofpiracy more efficiently, and such efforts also

the press (i.e., an increase in freedom of thewould facilitate the long-term technologicalpress).

progress of such countries. Accordingly,

3. The piracy rate increases with an

puttingeffortinto

PCT

numberofincrease in the national literacy rate. It isapplications

conceivable that this is because an increase

applications would be recommended for suchin the literacy rate increases the number ofcountries. It is hoped that these findings will
28

for

the

international

Journal of Japanese Management Vol.1, No.2, May 2017

Bezmen, T. L. and Depken, C. A. (2006).
Influences on software piracy:
Evidence from the various UnitedStates, Economics Letters, 90, pp.
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prove useful in policymaking.
Acknowledgements
The author would like to thank threeanonymousreferees

for

their

ISSN 2189-9592

usefulcomments. Also, thanks Prof. Shinichi
Kamiyama, Prof. Tetsuya Misawa and Dr.

Journal of International and global
Economic Studies, 3(2), pp.53-62.

Nianzhi Guo for their helpful comments andsuggestions at early stage of the paper.

Cox, J. A., Collins and Drinkwater, S. (2010).
Seeders, leechers and social norms:
Evidence from the market. Information
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Depken, C. A. and Simmons, L. C. (2004).
Social construct and the propensity forsoftware piracy. Applied Economics
Letters, 11(2), pp.97-100.
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An

Appendix: Countries for which data were used in this paper
Albania
Austria
Belgium
Cameroon
Croatia
EcuadorGeorgia
Iceland
Italy

Algeria
Azerbaijan
BosniaChile
CyprusEgypt
GermanyIndia
J apanArgentina
Bahrain
Botswana
China
Czech Republic
Estonia
GreeceIndonesia
Kazakhstan

Armenia
Bangladesh
BrazilColombia
Denmark
Finland
GuatemalaIreland
Kenya

Australia
Belarus
Bulgaria
Costa Rica
Dominican
FranceHungary
IsraelKorea

LatviaLebanon

Libya

Lithuania

Luxembourg

Malaysia
Nigeria
Peru
RussiaSlovenia
S witzerland
United Kingdom
ZambiaMalta
NorwayPolandSaudi Arabia
South Africa
Thailand
United States

Mauritius
Oman
Portugal
SerbiaSpain
Tunisia
Uruguay

MoroccoPakistan
Qatar
Singapore
Sri Lanka
TurkeyVenezuela

Nicaragua
PanamaRomania
Slovakia
SwedenUAE
Vietnam(Received: November 23, 2016)(Accepted: May 8, 2017)30