Does software piracy affect economic growth? Evidence across countries

Journal of Policy Modeling 34 (2012) 284–295

Available online at www.sciencedirect.com

Does software piracy affect economic growth? Evidenceacross countries�

Antonio R. Andrés a,∗, Rajeev K. Goel b

a Institute of Public Health, Aarhus University, Bartholins Allé 1, 8000 Aarhus C, Denmarkb Department of Economics, Illinois State University, United States

Received 1 March 2011; received in revised form 1 June 2011; accepted 1 August 2011Available online 19 August 2011

Abstract

We examine the effect of software piracy on medium term growth using cross-country data over2000–2007. While the empirical literature has focused on identifying the causes of software piracy, ourcontribution is to examine its effects. Our findings suggest that software piracy reduces economic growthover the medium term but the relationship is non-linear – the rate of decrease in economic growth diminisheswith piracy increase. This growth-reducing effect is especially pronounced in low income countries. Policyimplications are discussed.© 2011 Society for Policy Modeling. Published by Elsevier Inc. All rights reserved.

JEL classification: O47; O57; K42

Keywords: Software piracy; Economic growth; Intellectual Property Rights; Low-income nations

1. Introduction

In the recent years, there is a wide consensus on the key role that Intellectual Property Rights(henceforth IPRs) protection plays in promoting innovation processes and economic growth.Thus, a large number of countries have reformed their copyright systems in order to strengthenthe IPRs protection. For example, in its 1998/99 World Development Report, the World Bank

� The authors’ names appear in alphabetical order and no seniority of authorship is implied. Helpful comments by theEditor and referees and research assistance by Michael Naretta are appreciated.

∗ Corresponding author. Tel.: +45 89423122.E-mail address: [email protected] (A.R. Andrés).

0161-8938/$ – see front matter © 2011 Society for Policy Modeling. Published by Elsevier Inc. All rights reserved.doi:10.1016/j.jpolmod.2011.08.014

dx.doi.org/10.1016/j.jpolmod.2011.08.014

mailto:[email protected]

dx.doi.org/10.1016/j.jpolmod.2011.08.014

A.R. Andrés, R.K. Goel / Journal of Policy Modeling 34 (2012) 284–295 285

emphasizes the importance of stronger IPRs protection as one of the main channels to acquireforeign knowledge, especially in developing countries. This is justified based on the grounds thatstronger IPRs protection should enhance economic growth by increasing the returns to innovation,and hence the incentives to innovate.

Intellectual property displays many of the features of public goods. That is, they are typicallynon-rival and non-excludable. Therefore, it becomes necessary to protect them from unauthorizeduse or access in order to ensure innovators profit from their innovations, which in turn would beexpected to impact innovation and economic growth.

At the aggregate level, a (broader) strand of the literature has investigated the relationshipbetween the intensity of IPRs protection and economic growth. The empirical literature on IPRsprotection has largely concluded that IPRs protection has a positive effect on economic growth,often using cross-section data (see for example, Falvey, Foster, & Greenway, 2006; Gould &Gruben, 1996; Park & Ginarte, 1997; Thompson & Rushing, 1996, 1999). However, the availablemeasures of IPRs protection are only rough measures of overall piracy activities in any particulareconomy and this research addresses the software piracy-growth linkage directly. The focus hereis software piracy because it is also the IT sector’s most serious problem (Anthes, 1993) and isone of the most notorious forms of IPRs violations.

A substantial recent empirical literature has focused on the socio-economic determinants ofpiracy rates in several copyright industries (Andrés, 2006; Banerjee, Khalid, & Sturm, 2005;Bezmen & Depken, 2006; Goel & Nelson, 2009; Peitz & Waelbroeck, 2006 for a review). Incontrast, there is scant empirical evidence to validate the basic premise that software piracymight impact economic growth. One of the main motivations of this paper is to empiricallytest the impact of software piracy on economic growth. There are numerous avenues throughwhich software piracy might impact economic growth. For instance, piracy rates might lowerproductivity, thereby affecting economic growth (negative effect). But pirated software might beuseful in raising productivity and increasing economic growth (positive effect). Further piracymight influence incentives to write software programs, to do software related R&D, and investin software capital. Piracy reduces the incentives to commercialize as well as innovate. Withoutadequate IPR protection, programmers will have little confidence in appropriating returns to theirefforts, nor will venture capitalists be willing to invest in programs that lack protection (and henceare too risky). Further, greater piracy rates might signal weaker formal institutions (regulations,rules), again affecting growth (see detailed discussion below). The linkage between piracy andeconomic growth is a key question that underscores the importance of piracy control efforts.

The present research examines the (macro) effects of software piracy on economic growthusing a large cross-section of countries. Understanding of the piracy-growth nexus is importantfor the formulation of effective policy. We make the assumption that the rate of software piracycan be seen more generally to proxy for piracy of other goods (e.g., sound recordings, motionpictures, books, etc.).1 For that purpose, we use the neoclassical growth model (Solow, 1956) asthe main theoretical model to explain economic growth. In addition to providing evidence on theimpact of software piracy on medium term growth during the first decade of the new millennium,this study has a number of innovative elements: (i) the issue of possible nonlinearity betweenpiracy and growth is examined; and (ii) the potential endogeneity of the piracy in economicgrowth regressions is taken into account. We find that software piracy affects economic growth

1 Unauthorized use of computer software resulted in a vast majority of the over $31 billion loss to the US businesssoftware industry in 2009 (IIPA, 2010).

286 A.R. Andrés, R.K. Goel / Journal of Policy Modeling 34 (2012) 284–295

and the relation is nonlinear – greater piracy decreases growth and the rate of decrease diminisheswith piracy increase. Accounting for the reverse-causality between piracy and growth, the earlierfindings are reinforced.

2. Methodology and data

The scope of this paper is to determine if software piracy affects the level of economic growth.To test this, we begin with a basic neoclassical growth model (see Solow, 1956). To derive agrowth equation from a theoretical background, a simple aggregate production function with twofactors, capital (K) and labor (L), with GDP denoting the aggregate output of a country can beconsidered (see Goel & Ram, 1994; Goel, Payne, & Ram, 2008)

GDP = h(K, L) (1)

After totally differentiating (1) and rearranging, one can obtain the following basic growthequation:

dGDP

GDP= ∂GDP

∂K

K

GDP

dK

K+

[∂GDP

∂L

L

GDP

]dL

L(2)

In (2), (dGDP/GDP) and (dL/L) are, respectively, the rates of growth in (real) per capita GDPand labor (GDPgr and LABgr, respectively, in (3) below). Further, [(∂GDP/∂L)(L/GDP)] is theelasticity of GDP with respect to labor, dK is investment (GDI below) and (∂GDP/∂K) is themarginal product of capital (K).

Human capital (see Barro, 2001; Romer, 1990) or labor quality (LIT) and income (GDPpcand DEV) variables are added to (2) in different estimated versions to compare with the extantgrowth literature and to check the robustness of the base model. Other things being the same,greater literacy is likely to enhance growth. Initial per capita GDP in the base year, 2000, GDPpcis included to capture trends towards convergence (Sachs & Warner, 1995) and to be consistentwith endogenous growth theory (Aghion & Howitt, 1997; Barro & Sala-i-Martin, 2004; Mankiw,Romer, & Weill, 1992). As an alternate measure of income, a dichotomous variable DEV isincluded to identify low income nations in our sample.

The main focus, however, is on the impact of software piracy (PIRACY) on economic growth.There are numerous avenues, both direct and indirect, through which software piracy might impactgrowth. One, greater piracy lowers economic growth via unauthorized leakages of intellectualproperty. Pirated software fails to provide adequate returns to software developers resulting inlower investments (GDI) that retard growth. However, piracy might enhance growth in caseswhere efficiency gains outweigh any equity considerations from unauthorized software use. Forinstance, pirated software might result in additional investments that spur growth. These positiveeffects of piracy seem even more plausible when one thinks of positive network externalitiesgenerated. Second, greater piracy might lower productivity (i.e., ∂GDP/∂K above) (and hencegrowth) when the shadow economy operating with pirated software is significant.2 Third, broadlyspeaking, software piracy may be viewed in the context of the economics literature on illegalactivities (Becker, 1968). One illegal activity, corruption, has garnered considerable empiricalattention beginning with Mauro’s (1995) seminal work examining the corruption-growth nexus(see Lambsdorff (2006) for a review of the related literature). In this context, both corruption and

2 Ding and Liu (2009) find different effects of software piracy on productivity across nations over 1994–2002.


SoftwarePirac y

Approp riab ility

Institution sRisk

EconomicGrowt h

⎫

⎬

⎪⎪

⎭

⎪⎪

⎫

⎬⎪⎪

⎭⎪⎪

Productivity

Fig. 1. Channels of influence of software piracy on economic growth.

software piracy can be viewed as measures of a nation’s institutional quality. However, relativelylittle attention has been paid to the effects of software piracy. Finally, presence of significantsoftware piracy might signal greater profit risk and this might hamper economic growth. A highdiffusion of piracy rates affects the riskiness of investments and the return on legal activities. IfIPRs are unsecure or investors run a high risk of being defrauded of their legitimate profits, theincentives to invest (write programs and applications) as well as the incentives to commercializeare hindered.

Fig. 1 provides a useful description of the possible channels of influence of software piracyon economic growth. Broadly speaking and summarizing the above discussion, piracy can affectgrowth via its impact on appropriability of intellectual property and related risks of loss of invest-ment, its effect on productivity (Ding & Liu, 2009) and its signal for low quality of institutions.The main hypothesized effect of all these influences is to lower economic growth, although thereis little hard evidence on the magnitude and nature (linear or nonlinear?) of such effect. Further,given possible network externalities associated with pirated software, the relationship betweenpiracy and growth might very well be non-linear.3

Software piracy is defined as the unauthorized copying of computer software which constitutescopyright infringement for either commercial or personal use (SIIA, 2000). Due to software piracypotentially taking place in many avenues – e.g., organized copiers, commercial or business piracyand piracy by individuals – obtaining an accurate measure of the prevalence of software piracyremains a challenge. There are many types of piracy. According to the Business Software Alliance(BSA), we can distinguish among: (1) end user copying; (2) counterfeiting; and (3) downloading.The extent of piracy is computed as the difference in demand for new software applications(estimated from PC shipments) and the legal supply of software. In our paper, the measure ofpiracy employed is the percentage of software (primarily business software) in a country thatis illegally installed (without a license) annually and is taken to capture the extent of softwarepiracy. This variable is reported in percentages, ranging from zero percent (no piracy) to 100percent (i.e., all software installed is pirated). Piracy rates are obtained from the Business SoftwareAlliance (BSA) (2007) (see Business Software Alliance (2009) for measurement details).4 BSAis an industry group; nevertheless its data on software piracy is the best cross-country measurecurrently available, albeit subject to some inherent upward bias.5 The data on software piracymay be seen more broadly as proxying for the extent of digital piracy. The average level of piracy

3 It should, however, be noted that in most countries the extent of computer software piracy is rather as small comparedto the size of the overall economy.

4 The BSA data primarily measure the piracy of commercial software. We are unaware of any publicly available cross-national data on end-user software piracy. See Png (2008) for a discussion about the reliability of piracy data. Also seeTraphagan and Griffith (1998).

5 Among the many researchers that have used this data are Andrés (2006), Banerjee et al. (2005), Goel and Nelson(2009) and Marron and Steel (2000).


rate in the sample was 60.5 percent, with the minimum piracy rate of 21 percent and a maximumpiracy rate of 94.3 percent.

Based on the above theoretical background in (2), the estimated growth relations take thefollowing general form:

GDPgri = f (GDIi, LABgri, LITi, PIRACYi, GDPpci , DEV ) i = 1, 2, 3, . . . (3)

These variables are detailed in Table 1. The focus on this paper will be on Eq. (3) which will beestimated using OLS and 2SLS. Results from different variations of (3) are presented in Table 2below.

Whereas the main channel of influence is hypothesized to be from software piracy to economicgrowth, there might be some reverse causality (simultaneity) between software piracy and eco-nomic growth (for a general background, see Chong & Calderón, 2000). In other words, greaterpiracy can affect economic growth on one hand; however, growth can also affect piracy – lowgrowth nations might engender greater piracy (see Holm, 2003). To address the simultaneityaspect, Table 3 reports instrumental variables regression results where software piracy is takenas an endogenous variable. Internet users per 1000 population (IntUsers) and an index of patentrights (IPP) are taken as additional instruments for piracy (see Banerjee et al., 2005; Ding & Liu,2009; Goel & Nelson, 2009; Gopal & Sanders, 1998; Marshall, 2007 for determinants of piracy;Peitz & Waelbroeck, 2006 for a literature review). The number of Internet users could be used asa proxy for the market for information technology – both legal and illegal. More internet users,ceteris paribus, would enable faster diffusion of software (both legal and illegal), while at the sametime capturing the legal machinery that is also empowered to access (and police) the internet. Theindex of patent rights (IPP) captures the strength of intellectual property protection in a country(Park, 2008). Other things being the same, greater intellectual property protection would checksoftware piracy (see Andrés, 2006; Banerjee, 2006; Besen & Raskind, 1991; Stolpe, 2000).

The data include annual cross-country observations for sixty five countries for the years2000–2007 (some countries dropped out of the analysis due to missing data). To overcome anoma-lies with year-to-year swings in data, we estimate cross-sectional models with variables averaged(annually) over the 2000–2007 period. Thus, the study may be viewed as estimating medium-termgrowth. This sample period also makes sense because the time period studied is the one whereworldwide computer and internet usage seemed to entering the second, mature phase.

In our sample period, the average growth rate of per capita GDP was 3.7 percent, while theaverage software piracy rate was 60.5 percent. The correlation between the two primary variablesof interest, PIRACY and GDPgr was a modest 0.31. Details about the variable definitions, datasources and summary statistics are provided in Table 1. The Appendix provides a correlationmatrix showing the basic correlations between key variables used in this study. The results sectionfollows.

3. Results

Table 2 reports estimation results from different variations of the growth relation outlined in(3).6 Model 2.1 can be viewed as the baseline model, while Models 2.2 and 2.3, respectively, addinitial GDPpc (to allow for catch up in the growth process) and DEV as additional determinants.

6 All estimations were conducted using the STATA software program.


Table 1Variable definitions, summary statistics and data sources.

Variable Definition (mean; std. dev.) Source

PIRACY Software piracy rate, 2000–2007 average Business Software Alliance (BSA, 2007)(Percentage of software acquired illegally)Higher values, more piracy(60.48%; 20.74)

GDPgr Growth in GDP per capita, PPP, 2000–2007 average World Bank Development Indicators(3.73%; 2.63)

GDPpc GDP per capita, PPP, 2000 World Bank Development Indicators($14,084.62; 12,906.91)

GDI Gross domestic investment, 2000–2007 average (% of GDP) World Bank Development Indicators(6.60%; 4.78)

LABgr Growth rate in labor force, 2000–2007 average World Bank Development Indicators(1.44%; 1.95)

LIT Literacy rate World Bank Development Indicators(Percentage of literate population age 15 and over),2000–2007 average(87.86%; 13.67)

IntUsers Internet users per 1000 people, 2000–2007 average International Telecommunication Union(ITU) and World Bank DevelopmentIndicators

(24.58; 21.82)

IPP Patent rights index, 2005; higher values, greater protection Park (2008)(3.75; 0.71)

DEV Dummy variable identifying low income nations For operational and analytical purposes,economies are divided among incomegroups according to 2008 gross nationalincome (GNI) per capita, calculatedusing the World Bank Atlas method

Models 2.4–2.7 allow for nonlinearity in the relation between economic growth and piracy byincluding a quadratic piracy term.

The overall fit of all models in Table 2 is decent as evidenced by the statistically significant F-value and an R2 that is at least 0.68. As a general test of the specification of the estimated relation,a RESET test was conducted. The corresponding results (reported at the bottom of Table 2) revealthat Model 2.6, with DEV and PIRACY2, was the one where RESET test showed an absence ofany significant specification error; although Models 2.4 and 2.7 are also acceptable (since theF-value of RESET is only significant at the 10 percent level in these cases). Consequently, thefollowing results are discussed with regard to these models and reveal these noteworthy points:

• Consistent with intuition and with the extant literature, GDI leads to greater growth (Goel &Ram, 1994). In terms of magnitude, a one percent increase in the average GDI over 2000–2007led to about 0.4 percent increase in economic growth over the same period (Models 2.4, 2.6),with the effects of all other factors held constant. Over time, policymakers have used variousfiscal incentives to boost growth through greater investment.

• Human capital or labor quality (LIT) enhances economic growth, while the effect of labor growth(LABgr) was statistically insignificant. A ten percent increase in the literacy rate increaseseconomic growth by about 0.3 percent (Model 2.6), ceteris paribus. The returns to humancapital investments have been recognized by policymakers and international donors for quitesome time.


Table 2Software piracy and economic growth (dependent variable: GDPgr).

(2.1) (2.2) (2.3) (2.4) (2.5) (2.6) (2.7)

GDPpc 0.00002 −0.00003(0.6) (0.6)

DEV −1.84** −2.16**

(2.4) (3.4)GDI 0.37** 0.37** 0.39** 0.36** 0.35** 0.37** 0.38**

(6.1) (6.2) (6.4) (6.5) (6.5) (6.9) (6.4)LABgr −0.07 −0.08 −0.08 −0.09 −0.08 −0.11 −0.08

(0.6) (0.6) (0.7) (0.8) (0.8) (0.8) (0.7)LIT 0.06** 0.06** 0.04** 0.06** 0.06** 0.03** 0.04**

(3.4) (3.2) (2.6) (3.3) (3.4) (2.2) (2.6)PIRACY 0.04** 0.05* 0.04** −0.24* −0.28* −0.26**

(2.1) (1.9) (2.1) (1.9) (1.7) (2.1)

PIRACY2 0.002** 0.002** 0.002** 0.0003**

(2.2) (2.0) (2.3) (2.3)PIRACY*DEV −0.02**

(2.2)F-value 18.1** 14.1** 14.2** 15.7** 13.2** 13.6** 14.5**

R2 0.68 0.68 0.70 0.71 0.71 0.73 0.70N 65 65 65 65 65 65 65RESET test(p-value of F)

3.5** 3.3** 2.9** 2.6* 2.8** 1.4 2.6*

(0.02) (0.03) (0.04) (0.06) (0.05) (0.26) (0.06)

Notes: Variable definitions are provided in Table 1. All equations included a constant term. However, corresponding resultsare not reported to conserve space. The figures in parentheses are robust t-statistics from OLS regressions.

* Statistical significance at the 10% level.** Statistical significance at the 5% level.

• Other things being the same, growth was lower in low income countries. The coefficient onDEV is negative and statistically significant. One plausible explanation for this negative effectcould be that developing nations lack the frameworks for taking advantages of any positivespillovers from pirated software.

• Turning to the effect on software piracy, greater piracy retards economic growth, although therelation between piracy and growth seems nonlinear. The negative growth-effect of softwarepiracy is especially noteworthy in light of the fact that in terms of magnitude the extent ofsoftware piracy in most nations is quite small as compared to the size of the overall economy.7

This negative effect of piracy on economic development has been found elsewhere (Bezmen& Depken, 2004); however, the nonlinear relation has not been examined. The positive, andstatistically significant, coefficient on PIRACY2 implies that the relation between piracy andeconomic growth might be convex – i.e., greater piracy lowers economic growth, albeit at adiminishing rate. A plausible explanation for this convex relation is that modest levels of piracylower growth by reducing investment, but as piracy rates increase beyond some threshold level,the rate of decline in growth goes down (likely due to some positive spillovers or networkexternalities from piracy).

• To examine possible differential growth effects across nations with different income levels,Model 2.7 introduces an interaction term between PIRACY and DEV to see if the effects of

7 We thank a referee for bringing this to our attention.


GDPgr

PIRACY

Fig. 2. Effect of software piracy on economic growth.

piracy on growth were different on low income nations. The coefficient on PIRACY*DEV isnegative and statistically significant, implying that greater software piracy lowered growth inlow income nations. Government policies in low income nations should be especially gearedtowards checking software piracy.

Fig. 2 shows the relation between piracy and economic growth. Given the positive coefficienton the quadratic piracy term, the relation between piracy and growth is convex. This finding isnovel in the literature and has implications for public policy. For instance, controlling softwarepiracy should boost economic growth. However, the (negative) effect of piracy on growth dimin-ishes as piracy becomes more prevalent. Also, growth is lower in low income nations, ceterisparibus.

3.1. Simultaneity between software piracy and economic growth

There is likely to be a two-way relation between software piracy and economic growth. On theone hand, high growth nations are empowered to spend greater resources in combating piracy; onthe other hand, potential pirates in nations with high growth countries might have more resources toundertake illegal activities. Table 3 allows for simultaneity between software piracy and economicgrowth by estimating two-stage least squares (2SLS) models of versions 2.1–2.3, 2.7 from Table 2,where PIRACY is taken to be endogenous.8 Banerjee et al. (2005) and Goel and Nelson (2009)provide guidance regarding the choice of determinants affecting software piracy.

Finding good instruments for potentially endogenous regressors in growth studies is a challengebecause economic growth is potentially affected by a multitude of influences (see Levine & Renelt,1992). As discussed above, internet users (IntUser) and an index of patent protection (IPP) aretaken as additional instruments for piracy. The index of patent protection is arguably superior to adummy variable that would identify countries with strong Intellectual Property Rights protection(Andrés, 2006). Internet users capture ease of access to the underlying technology of softwarepiracy – i.e., computers – by producers, consumers and monitors of piracy.

8 Note that the number of observations declines in Table 3 due to missing data.


Table 3Simultaneity between software piracy and economic growth: 2SLS regressions (dependent variable: GDPgr).

(3.1) (3.2) (3.3) (3.4)

GDPpc −0.00006(0.9)

DEV −1.78**

(2.2)GDI 0.22** 0.21** 0.24** 0.24**

(4.5) (4.0) (5.0) (5.4)LABgr −0.57** −0.56** −0.61** −0.61**

(3.9) (3.6) (4.3) (4.6)LIT 0.02 0.02 0.002 0.002

(1.2) (1.3) (0.1) (0.1)PIRACY 0.02 −0.01 0.02

(0.9) (0.3) (1.1)

PIRACY2 0.0002(1.1)

PIRACY*DEV −0.02**

(2.3)F-value 15.4** 10.7** 14.5** 14.5**

N 52 52 52 52First-stage F-value 13.3** 11.5** 10.9** 10.3**

Sargan overidentificationtest (p-value of χ2)

0.12 0.68 1.08 1.15(0.73) (0.41) (0.30) (0.28)

Notes: Variable definitions are provided in Table 1. Constant included but not reported. The results shown are second stageresults for 2SLS regression. PIRACY was instrumented by IntUser and IPP. The figures in parentheses are z-statistics.Statistical significance at the 10% level.** Statistical significance at the 5% level.

The statistically significant, first-stage F-values and the results of the Sargan overidentificationtest point to the validity of our instrument choice. The instruments are not weak in the sense ofrecent econometric literature (Staiger & Stock, 1997). The overall fit of Models 3.1–3.4 is good.The findings across the four models are mostly similar.

• GDI again consistently enhances economic growth in Models 3.1–3.4. General investmentremains a key determinant of economic growth. Again, policies strengthening incentives forinvestment are recommended.

• Unlike Table 2, labor growth (LABgr) in Table 3 lowers economic growth, while the effect ofliteracy (LIT) is positive, but statistically insignificant. The negative effect of LABgr is plausible,given that economic growth is being measured in per capita terms.

• Initial GDPpc fails to show any significant trend towards convergence (Model 3.2). This findingis consistent with Models 2.2 and 2.5.

• The coefficient on PIRACY in Table 3 is statistically insignificant in Models 3.1–3.3. Theexogeneity of software piracy in these models where piracy enters linearly is confirmed by theendogeneity test reported at the bottom of Table 3. However, in Model 3.4 the coefficient onPIRACY*DEV is negative and statistically significant – a result that was also found in Model2.7. The nonlinear relationship between economic growth and software piracy holds. Thus, thenegative efect of piracy on growth in low income countries holds even after controlling forpossible endogeneity between piracy and growth. Greater piracy rates in low income nations


are likely sending (adverse) signals for the presence of weak institutions that retard investmentand growth in these nations. Policies that check the piracy of computer software would boosteconomic growth.

The main finding from our empirical analysis of cross-country medium-term growth is thatsoftware piracy hinders economic growth, but the relation between piracy and growth is nonlinearand convex. Efforts to check software piracy must take special importance in low income nationsand policymakers should take account of inherent nonlinearities.

4. Concluding remarks

Using data from a large sample of countries and employing a fairly standard growth model,this research examines the effect of software piracy on medium term growth. There are various,direct and indirect, means through which software piracy can affect economic growth (Fig. 1).The extant literature has primarily devoted attention to estimating the causes of software piracy(Banerjee et al., 2005; Bezmen & Depken, 2006; Goel & Nelson, 2009). The present researchcontributes to the literature by examining the effects of piracy.

The answer to the question posted in the title of the paper is yes – software piracy affectseconomic growth. As expected, greater piracy of computer software lowers economic growth.However, the relationship between piracy and growth is nonlinear – the decrease in economicgrowth diminishes with piracy (Fig. 2). An explanation for this is that low piracy rates retardgrowth by reducing investment, but as piracy rates increase, piracy has some positive spilloversvia network externalities that dampen the rate of decline in growth. There is thus some thresh-old piracy level after which increases in software piracy benefit growth by exploiting spilloverexternalities. This implies that the level of piracy matters in piracy control – the gains from low-ering piracy are not uniform across different piracy levels. Further, the negative growth effectsof piracy are found to be especially pronounced in the case of low income nations. The resultsfrom Table 2 generally hold when allowance is made for potential endogeneity of piracy inTable 3.

Investment and education increase growth, while there was little support for the convergencehypothesis. Other things being the same, growth was lower in low income countries – suggestingthe presence of some minimum income threshold in order for nations to get on a growth trajectory.

From a policy angle, initiatives to boost investment and/or literacy are shown to provide growthdividends. Examples of such initiatives include investment tax credits and education subsidies.However, these growth dividends seem undermined by the prevalence of software piracy. Yet,relatively large piracy rates do seem to have some positive growth dividends. Stronger propertyrights protection that checks software piracy would boost economic growth; however, the growthdividends are likely to be nonlinear. Policymakers should take account of these nonlinearities indesigning effective piracy-control policies. The payoffs from piracy control efforts seem especiallystrong for developing nations.

This line of inquiry may be fine tuned by including additional determinants of economicgrowth and examining their sensitivity to software piracy (see Levine & Renelt, 1992) and viathe availability of data at a finer level of detail. Finally, it would be interesting to compare andcontrast the growth effects of piracy and pirates (e.g., some nations might have many piratesbut the magnitude of software piracy might be low and vice versa), if corresponding data wereavailable.


Appendix A. Correlation matrix of key variables

PIRACY GDPgr GDPpc GDI LABgr LIT

PIRACY 1.00GDPgr 0.31 1.00GDPpc −0.73 −0.19 1.00GDI 0.31 0.77 −0.26 1.00LABgr −0.04 −0.23 0.06 −0.10 1.00LIT −0.26 0.36 0.33 0.16 −0.34 1.00

N = 65.

References

Aghion, P., & Howitt, P. (1997). Endogenous growth theory. Cambridge: MIT Press.Andrés, A. R. (2006). The relationship between copyright software protection and piracy: Evidence from Europe. European

Journal of Law and Economics, 21, 29–51.Anthes, G. H. (1993). Study cites software industry growth, piracy problems. Computer World, 27, 119.Banerjee, D. S. (2006). Enforcement sharing and commercial piracy. Review of Economic Research on Copyright Issues,

3, 83–97.Banerjee, D., Khalid, A. M., & Sturm, J.-E. (2005). Socio-economic development and software piracy. An empirical

assessment. Applied Economics, 37, 2091–2097.Barro, R. J. (2001). Human capital and growth. American Economic Review, 91, 12–17.Barro, R. J., & Sala-i-Martin, X. (2004). Economic growth (2nd ed.). Cambridge: MIT Press.Becker, G. S. (1968). Crime and punishment: An economic approach. Journal of Political Economy, 76, 169–217.Besen, S. M., & Raskind, L. J. (1991). An introduction to the law and economics of intellectual property. Journal of

Economics Perspectives, 5, 3–27.Bezmen, T. L., & Depken, C. A. (2006). Influences on software piracy: Evidence from the various United States. Economics

Letters, 90, 356–361.Bezmen, T. L., & Depken, C.A. (2004). The impact of software piracy on economic development, working paper. Francis

Marion University.Business Software Alliance (BSA) (2007). Piracy study, Fifth Annual BSA and IDC Global Software.Business Software Alliance (BSA) (2009). What is software piracy? http://www.bsa.org/Piracy%20Portal.aspx (accessed

May 2009).Chong, A., & Calderón, C. (2000). Causality and feedback between institutional measures and economic growth. Eco-

nomics and Politics, 12, 69–81.Ding, C. G., & Liu, N.-T. (2009). Productivity changes of Asian economies by taking into account software piracy.

Economic Inquiry, 47, 135–145.Falvey, R., Foster, N., & Greenway, D. (2006). Intellectual property rights and economic growth. Review of Development

Economics, 10, 700–719.Goel, R. K., Payne, J. E., & Ram, R. (2008). R&D expenditures and U.S. economic growth: A disaggregated approach.

Journal of Policy Modeling, 30, 237–250.Goel, R. K., & Ram, R. (1994). Research and development expenditures and economic growth: A cross-country study.

Economic Development and Cultural Change, 42, 403–411.Goel, R. K., & Nelson, M. A. (2009). Determinants of software piracy: Economics, institutions, and technology. Journal

of Technology Transfer, 34, 637–658.Gopal, R. D., & Sanders, G. L. (1998). International software piracy: Analysis of key issues and impacts. Information

Systems Research, 9, 380–397.Gould, D. M., & Gruben, W. C. (1996). The role of intellectual property rights in economic growth. Journal of Development

Economics, 48, 323–350.Holm, H. J. (2003). Can economic theory explain piracy behavior? The B.E. Journal of Economic Analysis & Policy, 3,

1–15.

http://www.bsa.org/Piracy%2520Portal.aspx


Copyright industries’ global challenges and solutions for 2010. International Intellectual Property Alliance. WashingtonD.C. Available at http://www.iipa.com/pdf/2010Special301Challenges.pdf.

Lambsdorff, J. G. (2006). Causes and consequences of corruption: What do we know from a cross-section of countries?In S. Rose-Ackerman (Ed.), International handbook on the economics of corruption (pp. 3–51). Cheltenham, UK:Edward Elgar.

Levine, R., & Renelt, D. (1992). A sensitivity analysis of cross-country growth regressions. American Economic Review,82, 942–963.

Mankiw, N. G., Romer, D., & Weill, D. N. (1992). A contribution to the empirics of economic growth. Quarterly Journalof Economics, 107, 407–437.

Marshall, A. (2007). Causes, effects and solutions of piracy in the computer software market. Review of Economic Researchon Copyright Issues, 4, 63–86.

Marron, D. B., & Steel, D. G. (2000). Which countries protect intellectual property? The case of software piracy. EconomicInquiry, 38, 159–174.

Mauro, P. (1995). Corruption and growth. Quarterly Journal of Economics, 110, 681–712.Park, W. G. (2008). International patent protection: 1960–2005. Research Policy, 37, 761–766.Park, W. G., & Ginarte, J. C. (1997). Intellectual property rights and economic growth. Contemporary Economic Policy,

15, 51–61.Peitz, M., & Waelbroeck, P. (2006). Piracy of digital products: A critical review of the theoretical literature. Information

Economics and Policy, 18, 449–476.Png, I. (2008). On the reliability of software piracy statistics. Mimeo: National University of Singapore.Romer, P. M. (1990). Human capital and growth: Theory and evidence. Carnegie-Rochester Conference Series on Public

Policy, 32, 251–286.Sachs, J. D., & Warner, A. M. (1995). Economic convergence and economic policies. Harvard Institute of Economic

Research Working Papers 1715.SIIA. (2000). SIIA report on global software piracy 2000. Washington, DC: Software and Information Industry Association.Solow, R. M. (1956). A contribution to the theory of economic growth. Quarterly Journal of Economics, 70, 65–94.Staiger, D., & Stock, J. H. (1997). Instrumental variables regressions with weak instruments. Econometrica, 65, 557–586.Stolpe, M. (2000). Protection against software piracy: A study of technology adoption for the enforcement of intellectual

property rights. Economics of Innovation and New Technology, 9, 25–52.Thompson, M. A., & Rushing, W. A. (1996). An empirical analysis of the impact of patent protection on economic growth.

Journal of Economic Development, 21, 61–79.Thompson, M. A., & Rushing, W. A. (1999). An empirical analysis of the impact of patent protection on economic growth:

An extension. Journal of Economic Development, 24, 67–76, 1999Traphagan, M., & Griffith, A. (1998). Software piracy and global competitiveness: Report on global software piracy.

International Review of Law, Computers & Technology, 12, 431–451.

http://www.iipa.com/pdf/2010Special301Challenges.pdf

Documents

Does software piracy affect economic growth? Evidence across countries