RIJKSUNIVERSITEIT GRONINGEN Faculteit der Economische Wetenschappen Vakgroep International Economics and Business
The influence of Intellectual Property Rights
protection on inward Foreign Direct Investment
between 1975 and 1994
Author:
J. Jonker
Student number:
s1143263
Date:
June 11, 2007
Coordinator:
Ass. Prof. B. Los
Table of Content
Table of Content ... 2
1. Introduction ... 3
2. Theory and empirical evidence... 6
2.1 Background information on IPR and FDI ... 6
2.1.1 Intellectual Property Rights ... 6
2.1.2 Foreign Direct Investment ... 9
2.2 Empirical Evidence... 11
3. Methodology ... 17
4. Data description... 19
4.1 The dependent variable: Foreign Direct Investment... 19
4.2 The independent variables and their expected effects... 19
4.2.1 Intellectual Property Rights protection... 19
4.2.2. Market size... 20 4.2.4 Human Capital... 21 4.2.5 Infrastructure ... 22 4.2.6 Political stability... 23 4.2.7 Openness ... 23 4.2.8 Descriptive Statistics... 24
Table 2: descriptive statistics of all variables in the research ... 24
5. Results... 26
6. Conclusions and recommendations ... 34
Literature ... 36
Appendices... 41
Appendix A: Groups of Countries used in the regression analysis ... 41
Appendix B: Correlation Matrix ... 42
1.
Introduction
In 1851 the Economist published a rather harsh opinion on patents: “The granting of patents ‘inflames cupidity’, excites fraud, stimulates men to run after schemes that may enable them to levy a tax on the public, begets disputes and quarrels betwixt inventors, provokes endless lawsuits...The principle of the law from which such consequences flow cannot be just,” (the Economist, 22nd oct. 2005).
More than 150 years later, the same magazine (the Economist, 22nd oct. 2005) published a survey on patents and technology. Its opinion on the matter has changed substantially since it recognizes the importance of patents and other intellectual property rights such as copyrights and trademarks. The survey points out the increase of the worldwide revenue out of intellectual property protection from around $ 10 bln. in 1985 to around a $100 bln. in 2004.
Investigating this rapid increase in revenues from IPR protection leads to the discussion whether profound protection of IPR is either beneficial or a menace to the economic development in the world. From the perspective of the developed world it is a benefactor since it creates a way to reward creativity and stimulates others to innovate in order to reap the economic benefits of it. However, if protection on key inventions is too profound, the temporary monopoly that it creates can withhold further development. This is often seen in the pharmaceutical world, (Subramanian, 1991). The developing world claims to be held back by strong protection since it will have to pay higher prices to use ‘western’ knowledge for its own development. These restrictions hinder the efforts of the developing countries to modernize, thereby perpetuating and strengthening the split between them and the developed nations, (Feinberg & Rousslang, 1990).
management practices and organizational arrangements, (Feenstra & Markusen, 1994; De Mello, 1997).
The purpose of this paper is:
• To find out whether there is a positive or negative relationship, on a worldwide level, between the inflow of foreign direct investment in a country and its system of protection of intellectual property rights, and whether it is significant or not.
The discussion about IPR protection being either a benefactor or a menace raises an interesting situation. If a significant relationship is to be found, does that mean the same for all countries? Can the richest countries of the world be in the same analysis with the poorest countries? The view of the developing countries is that IPR protection holds them back in their development. It is interesting to find out whether this view is true or not. Is the effect of IPR protection on the attraction of FDI different in our developed world than it is in developing countries? Therefore, the second purpose of this paper is:
• To find out whether the outcome of an analysis on a continental level varies with the outcome of the worldwide analysis, while using the same variables.
To make it possible to answer these research questions, several sub-questions must be answered:
- What are Intellectual Property Rights and how is their protection to be measured?
- Which other determinants are of influence on the inflow of Foreign Direct Investment? What is their influence on the inflow of FDI?
- How are the continental regions determined?
Javorcik (2004) used the index to find the relation between FDI and IPR in transition economies, in this case former Soviet countries.
There has not been a study on the worldwide relationship between FDI and IPR protection. Every previous study has some sort of limitation. The objective of this study is to find out whether there is a worldwide significant relationship between foreign direct investment and intellectual property rights protection. As a variable for IPR protection the index created by Ginarte & Park will be used. To filter out the effects of other determinants of foreign direct investment, such as human capital, economic size, economic freedom and infrastructure, several control variables will be used in a multivariate regression analysis to find out the effect and significance of all the determinants.
After the relationship between FDI and IPR protection has been determined, the group of countries is divided in 5 separated groups based on the continents of the countries. A regression analysis per continent will be performed. It is interesting to see if there are differences between continental regions concerning their IPR protection policies and its effect of FDI inflow.
2. Theory and empirical evidence
2.1 Background information on IPR and FDI
Before it is possible to find a relationship between the level of protection of Intellectual Property Rights and Foreign Direct Investment, it must be made clear what these variables consist of. This chapter will present the two most important variables of this study.
2.1.1 Intellectual Property Rights
Intellectual property refers to creations of the mind: inventions, literary and artistic works, and symbols, names, images, and designs used in commerce (Idris, 2003). Intellectual property rights protection is used to reward inventors for their creativity and to protect the inventors from people and/or companies who want to steal ideas. At the same time, this protection serves as a stimulant for economic growth, since the possible benefits create an incentive for further developing of ideas.
Although every country has its own laws concerning Intellectual Property Rights (IPR) protection, there are several organizations that try to harmonize international legislation concerning IPR, the World Intellectual Property Organization (WIPO) being the most important of them. In 1967 the WIPO arose from the United International Bureaux for the Protection of Intellectual Property (BIRPI), which was an intellectual property office that sprung out of the cohesion of several international property conventions1 (www.wipo.org).
It became an entity of the United Nations in 1974 and it started working with the WTO in 1996. During the Uruguay Round of the WTO/GATT negotiations the TRIPS agreement was negotiated. The TRIPS agreement establishes minimum standards for protection. Countries are free to adopt stronger laws if they wish and are free to decide on how to implement the agreement using their own system of law and practice. TRIPS also provide for enforcement mechanisms and it provides for transitional arrangements for countries at different stages of economic development. For example, developed countries were given one year to ensure that their laws conformed to TRIPS. Developing countries were given five years and the
least developed countries were given eleven years (OECD Working Paper, 2002). The expected effect of this increased harmonization of intellectual property protection is a higher overall level of protection worldwide.
There are four types of Intellectual Property Rights: Patents, Copyrights, Trademarks and Trade Secrets.
- Patents:
- Copyrights:
A copyright is the exclusive right for the creator or author of a literary or artistic work. The owner of a copyright has the right to prohibit publication, translation, broadcasting or public performance of their creation by others. Such a right is owned by the creator during his entire life and after his/her death by his/her heirs for a period of 50 years (Sherwood, 1990). Music and computer programs for example are important products that are protected by copyrights, although in the last years software patents are more and more granted.
- Trademarks:
A trademark is commonly a word or mark which serves to identify exclusively the source of a product or service (Sherwood, 1990). More often than not, these marks are associated with a certain amount of quality. A trademark protects a producer from competitors who make the same sort of product and try to take advantage by using a similar mark. What companies should be careful of is the fact that a trademark can be registered by anyone anytime. A company has to make sure that they have registered their trademark in every country they want to sell the product, otherwise the chance might exist they would have to change their product name in certain countries because someone else has registered the mark (Jain, 2001).
- Trade Secret:
2.1.2 Foreign Direct Investment
This variable is measured because it is expected that FDI is growth enhancing. It provides the possibility for integration of new inputs and technologies in the recipient economy through technological spillovers and knowledge transfers, and can thus be used as measurement for economic development (Sherwood, 1990; Feenstra & Markusen, 1994; de Mello, 1997). Foreign Direct Investment is determined by many factors. The best known theory to explain Foreign Direct Investment behavior by multinational enterprises is called the eclectic paradigm or ownership-location-internalization (OLI) theory by John. H. Dunning. The theory asserts that the FDI behavior by MNEs will be determined by the configuration of three sets of forces2:
1) The ownership advantages.
Multinational companies enjoy advantages over local enterprises through their ownership of intangible assets. These advantages arise from their ability to coordinate these assets with other assets across national boundaries in a way that benefits them relative to their competitors, or potential competitors. Examples of these ownership advantages are: new technologies, informal know-how shared among employees, reputation for quality, etc.
2) The location advantages
The advantages of a location that makes multinational companies decide to move value-adding activities outside their national boundaries. A foreign country must offer advantages that make it more profitable to locate business abroad instead of exporting it out of the company’s home country. Examples of locational advantages are low production costs, the extended market, access to distribution networks, the availability of natural resources, etc.
3) Internalization advantages
The extent to which firms perceive it to be in their best interests to internalize the markets for the generation and/or the use of these assets; and by doing so add value to them. This means that it must be more profitable to internalize production
2
than to sell or license their intellectual assets to independent firms in the foreign country.
Once a firm has decided that it wants to extend its business over the boundaries of its home country, how does it decide which country it will expand to? As described in Dunning's eclectic paradigm, this is where the locational variables come into play. In a study on the determinants of Foreign Direct Investment in Latin American, Asian and African countries by Schneider and Frey (1985), two types of variables are distinguished: economic variables and political variables.
Economic location variables:
The OLI theory states that once a company has decided it wants to expand to other countries because of their internalization advantages and competitive advantages, the location advantages come into play. The location variables eventually determine where a company will expand. This is fed by the knowledge that multinational enterprises will seek markets where the profit possibilities are the highest
Political location variables:
Political instability may affect the attracted Foreign Direct Investment in a negative way. A country in which there is political unrest or in which there is a great threat of having the investment nationalized (without adequate compensation) is more of a risk than a country offering political stability and a guarantee of property rights (Schneider & Frey, 1985). Multinational companies will think twice before investing in a country where they run the risk of their investment being seized by the local authorities, especially when they have invested in technological novelties that require solid protection to make a profit. Furthermore religious instability or even the lack of religious freedom is a negative component in the attraction of FDI (Tuman & Emmert, 2004; Asiedu, 2006), mostly because it creates an easy opportunity for massive riots.
Unstable political situations are more common in developing countries. With this knowledge it will be fascinating to see the effect of political location variables in the developing countries compared with to the effect in the developed countries.
ownership advantage, the location advantage and the internalization advantage. Owning IPR covers the ownership advantage; the level of protection varies for each country (L); the effect of the level of IPR protection influences the internalization (I) decision of a company. It influences their decision whether they need to invest in a country or that it might be more profitable to penetrate a country through licensing. Once an investment decision has been made, it influences the level of investment. Can a company build a research center, or can they only build a production center since new inventions would be jeopardized because of a low level of protection.
2.2 Empirical Evidence
The following section will give an overview of the empirical evidence on the topics of Intellectual Property Rights and Foreign Direct Investment.
One of the first empirical studies on the effect of Intellectual Property Rights on Foreign Direct Investment was conducted by Lee and Mansfield in 1996. They tested whether the legal protection system of Intellectual Property Rights had an influence on the investment of U.S. firms. A random selection of 100 U.S. enterprises in 6 different industries were questioned whether the protection system in 14 countries3 was too weak to either transfer new technologies to, invest in joint ventures or even too weak to license their technologies to local unrelated companies. They found a significant inverted relationship between the volume of U.S. direct investment in manufacturing in a country and the weakness of protection there. Furthermore, they stress that developing countries are not likely to accomplish anything if they implement laws regarding the protection of Intellectual property, but can not convince firms that these laws will be fairly executed.
The research of Bayla Seyoum (1996) was done in a different way. He also examined the relationship between the level of protection of IPR and the Foreign Direct Investment in a country. The data, concerning IPR protection, he used was gathered by sending questionnaires to intellectual property attorneys and consultants in the countries involved in the research. The FDI data he used was found by World Investment reports by the UN. In his analysis of 27 countries, he found a positive effect for copyrights, trademarks and trade-secrets. This analysis did not contain an effect for patents since there were too many LDC’s in which there was no patent
legislation. Once he divided the 27 countries he was investigating in three groups: the least developed countries, the newly industrializing countries and the developed countries only the copyrights were positive and significant for all the countries. Trademarks were positive related to FDI in the NIC’s, but negative in the developed and the least developed countries. Trade-secrets though, were found to have a positive effect in the NIC’s whereas there effect is negative in the LDC’s and developed countries. The protection of patents was found to have a negative effect in developed countries but positive in the case of NIC’s and the LDC’s for which there was patent legislation.
In 1997 Juan Carlos Ginarte and Walter Park developed an index on the protection of Intellectual Property Rights that would be used repeatedly by other researchers (Oxley, 1999; Smarzynska Javorcik, 2004; Hagedoorn et al, 2005). This research will also use their index as one of its variables.
Countries show considerable differences with regard to important aspects of intellectual property rights protection, such as the efficiency with which property rights can be established by those seeking legal protection. Other major differences refer to the broadness of the interpretation of property rights and the actual enforcement of property rights protection by authorities. These international differences in Intellectual Property Rights protection are most clearly demonstrated for patents (Hagedoorn et al., 2005). In the past researchers developed their own way of comparing countries to one another, but now a standardized index was available. Ginarte and Park (1997) have constructed an index to compare the regimes of IPR protection by using a coding scheme based on five categories of patent laws:
1) Extent of coverage
The value of this category indicates the fraction of seven elements (pharmaceuticals, chemicals, food, plant and animal varieties, surgical products, micro-organisms, and utility models) being specified as patentable. Every element accounts for 1/7 of the value for a country.
2) Membership in international patent agreements
3) Provisions for loss of protection
Patent holders may also face risks of forfeiting their patent rights. This category measures protection against losses arising from three sources:
• ‘Working’ requirements. This refers to the exploitation of inventions. For example, when the authorities require that a good based on the patent is manufactured in the country or, if the patent is granted to a foreigner, that the good is to be imported into the country to enjoy patent protection. In the absence of such requirements, the patentee does not have to put the invention into practice in order to enjoy patent protection.
• Compulsory licensing. Patentees are required to share their knowledge with a third party. This reduces the future profits of the patentee.
• Revocation of patents. Countries that do not revoke patents that are not working receive a value of 1/3.
A country that protects against all three sources receives a value of 1 in this category.
4) Enforcement mechanisms
In this category, the applicable conditions are the availability of:
• Preliminary injunctions, this protects a patentee from infringement until a final decision is made in a trial
• Contributory infringement, actions that do not in themselves infringe a patent right but cause infringement by others. Examples include the supplying of materials or machinery parts that are essential to the use of a patented invention.
• Burden-of-proof reversals are procedures that shift the burden of proof in process patent infringement cases from the patentee to the alleged infringer. Under a burden-of-proof reversal, if a certain product is produced by another party, it is assumed that it was produced with the patented process. It is on the infringer to prove otherwise and thereby reveal the underlying process. This can be a very powerful mechanism.
5) Duration of protection
Two scales were designed to measure the duration of protection. It depends whether a patent starts on the date of application or the date of the grant of the patent. In the cases that a patent starts on the date of application, it is granted for 20 years, in general. It takes about 3 years before the patent is granted. Those that provide shorter terms receive a value equal of the fraction of the 20 years that are provided. Those patents that start on the date of granting will last for 17 years, thus receiving a value of 17/20.
Ginarte and Park use the index to examine what factors of characteristics of economies determine how strongly patent right will be protected. First they point out that the level of patent protection, or IPR protection, depends on its costs and benefits. The benefits are that it stimulates innovation. Increasing patent protection also enhances productivity growth and the quality and variety of goods increases. Better protection also provides better trade relations with other countries. The costs are that if protection is excessive, innovators with market power have a smaller incentive to introduce new technologies. Other costs are that patents create higher costs in the development of new products, which leads to more patents etc.
An important finding is that there needs to be a critical size of the innovating sector before countries implement a system of higher Intellectual Property Rights protection. This has to do with the fact that a profound system of protection has large fixed costs, as well as high operating costs. Countries are not willing to implement such a system if the innovating sector is small and there are not enough innovations produced to make the system worthwhile.
benefits unless adequate resources are committed to the administration and enforcement of IPR and entrepreneurs become convinced of the sustainability of the regime.
Joanna Oxley (1999) used the index by Ginarte and Park (1997) to find the impact of intellectual property protection on the structure of inter-firm alliances. The result of her research led to an affirmation of her hypothesis that companies tend to choose more hierarchical alliances, equity joint ventures instead of contract-based alliances, in countries where protection is weak.
John Hagedoorn et al. (2005) confirm the findings of Oxley. In their analysis of 2005 partnerships between 1956 companies in 53 countries, they argue that the preference of companies for hierarchical control, through a joint venture mode for international R&D partnering, is inversely related to the strength of intellectual property rights protection in the home country of their partner. Important in their research is their variable for sectored technological change, in which the R&D expenditures as a percentage of output is measured. The larger the differential between the innovative capabilities of partners, the more the ‘leading’ company will search for protection of these capabilities by means of equity joint ventures. International contractual R&D agreements, characterized by organizational flexibility, are preferred in R&D-intensive and innovative studies. However, they recommend that further research needs to be conducted using a wider range of sectored characteristics than they have been using.
The results of Oxley and Hagedoorn are put in an extra interesting daylight in combination with the research of Beata Smarzynska Javorcik (2004). She addresses her interest to the composition of the foreign direct investment. She finds that a weak protection mechanism has significant impact on the composition of FDI inflows, especially for the technology-intensive sectors. What she detected for every industry was that weak protection encourages foreign investors to set up distribution facilities rather than to engage in local production. This is especially interesting as she quotes Lee & Mansfield (1996): The concern about the IPR regime also depends on the purpose of an investment project, being the highest in the case of R&D facilities and the lowest for projects focusing exclusively on sales and distribution.
determined by other variables. The most common determinants and their effects are published in a schedule in Asiedu (2002 & 2006).
It can be seen in table 1 that there is one variable for which certain researchers found significant positive results, while others found significant negative results. In the case of real GDP per capita Schneider & Frey in 1985 find that it has a positive effect on FDI. The higher GDP per capita, the better is the national economic health, and the better are the prospects that direct investment will be profitable (Schneider and Frey, 1985). Lipsey in 1999 found that high per capita real income proved to be the most consistent favorable influence in all the categories of industry.
The researches published in the schedule are similar to this research since they try to find out the effect of certain determinants on the attraction of FDI. Most of these researches use about 60 low developed countries in the time span between 1975 and 1980. The findings of the authors of the schedule answer the first part of the sub-question: Which other determinants are of influence on the inflow of Foreign Direct Investment? In the data section the expected influence of these determinants on the inflow of FDI for this study will be discussed.
Table 1: Results of research on the most common determinants of FDI
Source: Asiedu, E; On the determinants of Foreign Direct Investment to developing countries: is Africa different? World Development, vol. 30, no. 1, 2002
Determinants Positive Negative Insignificant
of FDI
Real GDP per Schneider & Frey (1985) Edwards (1990) Loree and Guisinger (1995) capita Tsai (1994)
Lipsey (1999) Hausmann and
Fernandez-Arias (2000)
Infrastructure Wheeler & Mody (1992)
quality
Loree and Guisinger (1995) Labor Cost Schneider & Frey (1985) Tsai (1994)
Loree and Guisinger (1995)
Lipsey (1999)
Openness Edwards (1990) Gastanga et al. (1998)
Hausmann and
Fernandez-Arias (2000) Taxes and Loree and Guisinger (1995) Wheeler & Mody (1992) Tariffs Gastanga et al. (1998) Lipsey (1999)
Political Instability Schneider & Frey (1985) Loree and Guisinger (1995) Edwards (1990) Hausmann and
3. Methodology
This research will try to find out the impact of the protection of Intellectual Property Rights on the inflow of Foreign Direct Investment. Based on the studies on FDI determinants in Table 1, I will use independent variables controlling for economic size, economic stability, trade, human capital, political freedom and infrastructure. This was also described in the OLI-theorem by Dunning. Dunning’s paradigm explains that when multinational companies decide to move their activities to another country, locational variables of the country start to make a difference. Market size, natural resources, Human Capital, infrastructure and political stability are being regarded as the most common determinants of the amount of FDI that flows into a country. This research tries to find out whether the amount of IPR protection can be added to that list. All other determinants must be included in the research to see what the role of IPR protection is.
To find out what the influence of an independent variable is on the dependent variable a multivariate regression analysis will be used.
The equation to be estimated is:
(FDI in US $/inhabitants) = K + β(IPR) + γ(M) + ζ(E) + δ(H) + η (I) + θ(O) + ρ(P) + ε IPR = IPR protection, M = Market Size, E = Economic Stability, H = Human Capital, I = Infrastructure, O = Openness and P = Political Risk
Once is determined whether location has a positive or negative influence, it is time to focus on the different continental regions. It is interesting to find out whether, in groups of countries of the same geographic region, there is a stronger and more significant effect of their IPR protection policy on their FDI inflow than on a worldwide level, hence the second part of the research. In the second analysis the sample of 82 countries has been divided in continental groups. This analysis uses the same data, which is annual data in the period from 1975 until 1994. The continental groups are the same groups as employed by the World Bank. The groups are:
- High income OECD countries
- Latin American and Caribbean countries - North African and Middle East countries - Sub-Saharan African countries
- South-East Asian countries
The same regression analysis is applied to each one of them to see whether there is a difference in the regional effects of IPR protection policy compared to the worldwide trend. This is to answer the second part of the research question whether the level of economic strength of countries is of importance in determining the policy concerning the IPR protection.
4. Data description
If not mentioned otherwise, the data were found in the World Development Index 2005 by the World Bank, and were used for the time span of 20 years from 1975 until 1994. To avoid having to adjust the data for exchange rates and inflation, the data have been gathered in the dollar 2000 mode provided by the WDI 2005. This option supplies all the data concerning amounts of money in dollars of the year 2000. All amounts have been adjusted to that dollar value. Assumed here is that the World Bank has used correct exchange rates and inflation number in calculating the amounts in US dollars of the year 2000.
4.1 The dependent variable: Foreign Direct Investment
The dependent variable in this research is the inflow of Foreign Direct Investment of a country. To be able to compare countries with a large population to countries with a smaller population, the amount of FDI per capita has been chosen. This amount was found by dividing the absolute amount of inflow of FDI in dollars through the population of the country in the same year.
4.2 The independent variables and their expected effects
The chapter concerning the background information on foreign direct investment already briefly discussed the possible effects of the most common determinants of foreign direct investment. In this chapter the determinants used in this research will be discussed, as well as their expected effects on the amount of FDI inflow to a country.4.2.1 Intellectual Property Rights protection
equal weights. This way the minimum level of protection is 0 and the maximum level is 5.4 To find out whether the value was sensitive to unequal weighting of the categories Ginarte and Park (1997) conducted a sensitivity test in which one condition accounted for 40%, the rest being divided equally over the other conditions, being 15% per condition. This was repeated by the same sort test but then the weights were divided in 60% for one condition and 10% for the other four conditions. The results were that the correlation between the original patent index and each of the ten new patent indices never fell below 0.85. Therefore the original patent index was declared not sensitive to the application of equal weighting of the categories.
The last year to be valued in their research was 1990. Walter Park extended his research on patent protection with another partner. Park & Smita Wagh (2002) contains an extended version of the patent index for 53 countries covering the index numbers of 1995 and 2000.
This research will use the index of Ginarte and Park patent index as an indicator for the IPR protection in a country. The values of the years in the period between 1974 and 1994 will be used, since not all the countries in the sample of 82 have an extended index until 2004. The complete patent index containing all the 5-year values for the 110 countries can be found in the Appendix.
4.2.2. Market size
Market size is accepted to be the determinant which has the most significant effect on the inflow of FDI in previous studies (see Table 1).
This research uses two variables to assess the role of market size in the decision whether or not to invest in a foreign country: Real GDP per capita and GDP Growth of the country. The annual data for all the 82 countries were found in the World Development Index 2005 created by the World Bank for the period between 1975 until 1994.
- Real GDP per Capita. Measures the amount of income per head of the population. It is expected to have a positive effect on the amount of inflow of FDI. The more money inhabitants of a country have to spend, the more attractive the market of that country becomes. To avoid the huge amounts in the research, the natural logarithm has been used to make the numbers more manageable.
- GDP Growth measures the growth of the total nominal GDP of a country in percentages per year in relation to the previous year. This variable is also expected to have a positive relationship to FDI inflow of a country, due to the same reason as Real GDP per Capita. The higher this value is the more attractive an economy becomes. On the other hand, GDP growth must not be too high and fast in danger of overheating the economy, and then a fear rises for a correction.
4.2.3 Economic Stability
The economic stability in the countries is measured by the inflation. This number used is the percentage per year. Inflation is a rise in the general level of prices in a country. The higher the inflation in a country, the more the prices rise and the less the money becomes worth. This means that the population of the country loses purchasing power if their income does not rise with the same percentage as the inflation. Stable economies, such as in the European Union, are expected to have an inflation between 0% and 3%. Very high inflation percentages suggest economic instability, for example when governments try to solve their economic problem by printing extra money. In such situations prices can go up by the hour and money in the bank becomes worthless. The possibility of these scenarios will scare away (potential) foreign investors in a country. Inflation therefore is expected to have a negative effect on FDI.
4.2.4 Human Capital
enrollment in a country. This variable has been found in the work of Barro and Lee (2001) and is a better variable than the literacy rate, a variable that also has been used in several studies. The difference between the two variables is that learning how to read is taught in primary school. The literacy rate therefore includes a high number of students that have not gone any further than primary school, whereas in secondary school the human capital is increased substantially. Tertiary school enrollment is not used because the numbers used are from the age category that starts at the age of 15 and tertiary schooling starts at higher age. The over-15 age group corresponds better to the labor force for many developing countries (Barro & Lee, 2001).
The variable for the wages has been too difficult to find. There are no data on average wages before the year 1990. Second option was to use the unemployment rate; a higher rate of unemployment would suggest lower wages. Although the International Labor Organization has data until 1975 for some countries, there were too many gaps in their data to include it in this research. This means the assumption is to be made that the human capital of the local population is of a bigger importance than the cost of labor, therefore in this research we will use only the human capital variable of secondary school enrollment.
4.2.5 Infrastructure
In figure 1 can be seen that infrastructure is recognized as an important determinant of FDI. All the studies have found a significant positive effect between FDI and infrastructure. A good measure of infrastructure development should take into account both the availability and reliability of infrastructure, since available infrastructure that does not work, is almost the same as non-existing infrastructure (Asiedu, 2002).
Infrastructure has proven itself as such an important determinant it can not be left out of the research, although in recognition of the shortcomings of the variable. The amount of telephones per 1000 inhabitants is expected to have a positive effect on the amount of FDI inflow.
4.2.6 Political stability
The political situation in a potential new market is of importance for a multinational company. Several researches (Schneider & Frey, 1985; Edwards 1990) found that political instability had a negative impact on the attraction of FDI. Companies are reluctant to invest in a country in which there is a great chance of change of government, or where they risk that their assets are being seized by the government (Edwards, 1990). Furthermore, although not proven significantly by Edwards, it is assumed that political violence has a negative effect on FDI as well.
This research starts too long ago for the World Development Indicator to have any data on riots or political crises in the first years of the research, therefore another database will be used. It is constructed by the non-profit organization called Freedom House. Every year it publishes their annual Freedom in the World report, which is an evaluation of the political rights and civil liberties in the world (www.freetheworld.com). Every country receives a value for their ‘freedom’ with 1 being the value for complete free and democratic countries and 7 being the value for the least free countries. Political freedom is enjoyed in a country when it is possible for everybody in a country to start a political party and when the leaders of every political party have the possibility to be elected to a position of power within the government. Civil liberties are enjoyed in a country when there is freedom of religious, ethnic, economic, linguistic and other rights, including gender and family rights, personnel freedoms and freedoms of the press, belief and association (www.freedomhouse.org).
In this research it will be assumed that political freedom brings political stability. The expected effect of this variable is a negative one, which means the lower value a country has (which means it is ‘free’) the more FDI will be attracted by the country. 4.2.7 Openness
trade area without extra cost for the export. Membership of a free trade area creates a bigger market for such companies. This research will use the six largest free trade areas: The European Union, The European Free Trade Association (EFTA), the North American Free Trade Association (NAFTA), the Southern Common Market (MERCOSUR), the Association of Southeast Asian Nation Free Trade Area (AFTA) and the Common Market of Eastern an Southern Africa (COMESA). If a country is a member of one of the free-trade areas it receives a value 1, if not it receives a value 0. If a certain trade area did not yet exist or if a country was not yet part of the trade area, the countries involved receive the value 0. The expected effect of being a member of a free-trade area is to be positive.
4.2.8 Descriptive Statistics
Although the Ginarte and Park patent index covers 110 different countries, this research only uses the data of 82 countries. This has to do with the fact that for a number of countries, both developing as well as developed countries, it was not possible to find all the necessary data. If one of the variables could not be found, the country was left out of the research. Therefore, only 82 countries were found for which all the data were available. Table 2 shows the descriptive statistics for the 82 analyzed countries.
Table 2: descriptive statistics of all variables in the research
Mean Maximum Minimum Std. Dev. FDI per Capita (in 2000 $) 41.32 1123.52 -258.34 104.53 GDP growth in annual % 2.69% 35.62% -51.03% 5.61% Inflation in annual % 54.36% 13611.63% -29.17% 525.62%
Political freedom 3.69 7.00 1.00 1.92
Sec. School enrollment in annual % 13.58% 43.10% 2.30% 10.60% Real GDP per Capita (ln value) in 2000 $ 7.51 10.46 3.87 1.59
Protection of IPR 2.52 4.52 0.33 0.80
No. of telephones/1000 inhabitants 112.50 689.14 0.00 168.40
Member of trade area 0.136 1.00 0.00 0.34
The descriptive statistics show some remarkable results that need to be explained. The first interesting number is the minimum value of the dependent variable, FDI per Capita, which has a negative value. This means that in a certain country in a certain year, more foreign capital has been withdrawn from the country than has been attracted. In this case it was Panama in the year 1988.
there was a crisis in South-America which resulted in hyperinflation. Other very large percentages are found in countries such as Argentina and Brazil. Those high percentages of hyperinflation have “colored” the descriptive statistics of the
inflation. The mean of inflation is very sensitive to the highest values of inflation found. For example, if the 10 highest values of inflation are left out, the average inflation in percentages drops with more that the half to 21.43%. The negative value for the inflation is called deflation, which means that people can buy more with the same amount of money.
5. Results
The first analysis is the worldwide analysis. The data, described in the data chapter, of the 82 countries has been used in the OLS regression equation, which was explained in the methodology chapter. The results of this regression analysis are given in Table 3.
Table 3: The Results of the regression analysis with FDI/Capita as dependent variable on an annual basis between 1975 and 1994 for 82 countries.
*, **, *** means significant at the 0.10, 0.05, 0.01 level respectively
Even though the results give a satisfying high R-squared value of 0.317, which means that model explains 31,7% of the variation of FDI in the world, and a couple of the most important variables have significant effects, the outcomes in table 3 can not be used. There is one statistic in the outcome that makes it impossible to use these outcomes as definitive. The Durban-Watson statistic of the model has a value of 0.685. The Durban-Watson statistic is used to test for the presence of first-order autocorrelation in the residuals of a regression equation. The minimal value of 0 indicates positive correlation; the maximum value of 4 indicates negative auto-correlation. Values surrounding the mid-value 2 indicate that there is no autocorrelation (Hill, Griffiths & Judge, 2001; Brooks, 2002). The value of 0.685 is too far from the mid-value to be able to say that there is no autocorrelation. In this
Dependent Variable: FDI/CAPITA
Variable Coefficient Prob. GDP growth** 86.60824 0.0350 Inflation -0.191689 0.6516 Political stability*** -9.080899 0.0000 Sec. School *** 545.6435 0.0000 Trade area -13.51089 0.1097 IPR*** 21.08026 0.0000 Telephones/1000 inh.*** -124.4499 0.0000 LN Real GDP -2.994327 0.1293 DUM_Sub Saharan 2.023008 0.8785 DUM East Asia*** -55.63692 0.0000 DUM Latin America** -26.10896 0.0143 DUM Middle East** -28.30117 0.0280 R-squared 0.317191
situation the coefficients of the variables are regarded as impure and therefore of no use.
This problem can be solved by switching to a model with differences. (Hill, Griffiths & Judge, 2001; Brooks, 2002). In this model the original variables are substituted by dummies of the variables. These dummies are created in the following way: the average value of each variable was calculated for every country in the analysis for the period between 1975 and 1994. This average value was subtracted from the annual values. As a result for every country the difference from the average value for each variable in the period from 1975 to 1994 was measured. For example: the average value of IPR was 3 for country A. If in the 1989 the value was 3.19, the measured value for 1989 is 0.19. If the value in 1990 is 2.78 then the measured value for 1990 is -0.22. This is done for all the variables on both sides of the equation, creating a dataset that consists of adjusted data. An OLS regression analysis was used as on this adjusted dataset. The following results were found for the worldwide adjusted database containing 82 countries:
Table 4: The Results of the regression on the adjusted database with FDI/Capita as dependent variable on an annual basis between 1975 and 1994 for 82 countries.
Dependent Variable: FDI/CAPITA
Variable Coefficient Prob.
GDP growth 38.36752 0.2653 Inflation -0.223080 0.5708 IPR protection*** 47.84558 0.0000 Political Stability 1.220973 0.5732 LN Real GDP*** 29.82473 0.0061 Secondary school*** 765.8835 0.0000
LN (telephones per 1000 inh.)*** -24.60420 0.0000 Trade area*** 35.71463 0.0018 DUM South-East Asia 0.245222 0.9569 DUM Latin America 0.425132 0.8949 DUM Middle East 3.024087 0.5576 DUM Sub-Saharan Africa -0.052306 0.9860
R-squared 0.264861
Adjusted R-squared 0.258767 Durbin-Watson stat 1.256651
Most important outcome for this research is the coefficient of the Intellectual Property Rights protection. The coefficient is positive and significant at the highest level. This proves that in a worldwide view a better protection of intellectual property rights does have an influence on the investment decisions of companies whether or not to invest in a country or not. This outcome confirms the expectations that were created by the empirical work by Mansfield & Lee (1994), Seyoum (1996), Oxley (1999) and Smarzynska Javorcik (2004).
Other significant results which were expected are: the positive effects of real GDP, Secondary school enrollment and membership of a free-trade area. Once the real GDP increases per capita increases, the inhabitants of a country have more money to spend, which makes it more attractive for foreign companies to invest in the country. The level of education seems to be more important to companies than the fact that better educated employees cost are more expensive. Entering a free-trade area also has a positive effect, especially since fellow members do not have to endure anymore barriers to enter the market. This is the expected result, which had a negative coefficient in the original analysis. Unexpected, but significant, is the negative coefficient of the amount of telephones per 1000 inhabitants, which is the variable covering infrastructure. It will be interesting to see whether this remains the same for every continent in the continental analysis, mainly as previous studies have always found that infrastructure has a positive effect on FDI. A possible explanation for this effect might be near multicollinearity. If near multicollinearity between two variables exists, this can result in a regression that looks good as a whole, but the coefficients values might give inappropriate conclusions (Brooks, 2004). The correlation matrix in the Appendix suggest that the only two variables for which this could be possible are secondary school enrollment and the number of phones per 1000 inhabitants (infrastructure), with a correlation value of 0.538. Although this negative effect might be caused by near multicollinearity, and for the continental analyses the infrastructure will continue to give some unexpected outcomes, the correlation value is not so high in such a way that the analyses or the data need to be changed. This would be necessary with value around 0.8 or 0.9. Therefore this study continues to use these variables as intended, with the unexpected results. In the conclusion the matter of multicollinearity will be further discussed.
Expected here was that political instability due to a dictatorial regime, military coups, riots or the risk of private property being seized by the government would have a negative effect on the amount of FDI attracted by a country. It will be fascinating to see if this outcome holds for every continent, even though insignificant. GDP growth and inflation show their expected signs but without significance. Maybe in a more homogeneous group of countries these variables will become more significant. The dummy variables for the continents have lost their significance due to the differences model.
In addition to the differences model, an analysis is made out of the average values for every variable from every country, a “between-estimation.” This analysis shows the effect of the country averages of the variables on the average FDI per capita over the last 20 years. In general, the results show the expected results. GDP Growth, Secondary school enrollment, IPR protection, Real GDP per capita and the Political stability have a positive effect on the attraction of Foreign Direct Investment in a country, although only the variable for Real GDP per capita shows significance. More significant are the negative coefficients of the dummies for the continental regions of Latin America, East-Asia, the Middle East and Sub-Saharan Africa. The negative effects of the No. of telephones per 1000 inhabitants and whether or not being a member of a trade area are unexpected.
Table 5: The Results of the regression analysis performed on the country averages over the period from 1975 to 1994 of each variable, for 82 countries.
Dependent Variable: FDI/CAPITA
Variable Coefficient Prob. GDP Growth 59.25012 0.8317 Inflation 0.290566 0.9224 Sec. school enrollment 289.5670 0.1682 IPR Protection** 14.32531 0.0295 LN Real GDP per capita*** 31.50790 0.0001 Trade Area -32.70351 0.1778 Political Stability -4.803890 0.4642 LN(phones per 1000 inh.)*** -0.319558 0.0002 Dum Sub-Saharan Africa*** -182.3950 0.0012 Dum Middle East*** -185.5160 0.0002 Dum Latin America*** -184.8676 0.0000 Dum South East Asia*** -148.9032 0.0000
R-squared 0.639296
The first part of the research question has been answered by the results of the analyses above. IPR protection can be considered as a determinant of FDI according to the Dunning eclectic paradigm. It has a significant positive effect on the attraction of FDI in a country, on the base of a worldwide analysis. However, there are still the results by Ferrantino (1993) and Primo Braga & Fink (1998), which say that in certain economies a lower level of IPR protection would be preferable. Therefore the big database of 82 countries has been divided in continental regions. The same regression analysis has been run, of which the results will be presented per continental region.
In table 6 the results for the analysis of the high income countries5 are presented. The theory that IPR protection has a positive effect on FDI is confirmed for this group of countries since the result is positive and highly significant.
Table 6: The Results of the regression on the adjusted database with FDI/Capita as dependent variable on an annual basis between 1975 and 1994 for the high income countries.
Dependent Variable: FDI/CAPITA
Variable Coefficient Prob. GDP Growth** 751.9269 0.0353 Inflation** -638.5784 0.0168 IPR Protection*** 107.2070 0.0038 Political stability -11.35276 0.5859 LN Real GDP per capita -127.8727 0.5002 Sec. school enrollment*** 730.2610 0.0000 LN (phones per 1000 inh.) -25.34411 0.7437 Trade area 13.62063 0.7541
R-squared 0.346286
Adjusted R-squared 0.329943 Durbin-Watson stat 1.319776
This result was expected. Most of the world technological improvements are produced in these countries, thus their need for proper protection is very high. Other important variables for these countries are the variables that show economic size and stability. The positive coefficient of GDP growth and the negative coefficient of inflation are significant. These countries all endure great freedom, well maintained infrastructure and education; therefore the variables that suggest economic stability and/or growth have a greater impact on the attraction of Foreign Direct Investment. Although the coefficients are insignificant the variables for
political stability and secondary school enrollment do show the expected positive signs. The insignificant negative signs for Real GDP per Capita and telephones per 1000 inhabitants were unexpected.
The results of the analysis on Latin American countries in table 7 show different outcomes. In this continental region the effect of Intellectual Property Rights protection has a negative coefficient, even though insignificant. This can be explained by the studies of Ferrantino (1993) and Primo Braga & Fink (1998), that for less developed countries it might be better to have a lower protection level. Significant positive results are found for the growth of GDP, Real GDP per capita and the secondary school enrollment. Infrastructure in the form of telephones per 1000 inhabitants has a negative coefficient which was not expected. The variable for political freedom here is positive, which means that less freedom attracts more Foreign Direct Investment. This outcome is unforeseen, since political stability was thought of as a positive determinant.
Table 7: The Results of the regression on the adjusted database with FDI/Capita as dependent variable on an annual basis between 1975 and 1994 for the Latin American countries.
Dependent Variable: FDI/CAPITA
Variable Coefficient Prob. GDP Growth*** 89.16094 0.0091
Inflation -0.005016 0.9788
IPR protection -0.659812 0.9608 Political Freedom 2.729975 0.1189 LN Real GDP per Capita** 33.35980 0.0142 Sec. School enrollment*** 478.3252 0.0002 LN(phones per 1000 inh.) -10.07942 0.2894
Trade area 7.549834 0.4120
R-squared 0.165810
Adjusted R-squared 0.148431 Durbin-Watson stat 1.237424
protection. Interesting fact here is that in the period between 1975 and 1994 the countries in this area that had a high economic growth have rapidly increased their level of protection, while the low protection level they had is one of the triggers of their economic success since it made copying of existing products possible. The other variables show their expected signs with political freedom, secondary school and no. of telephones being significant on the highest level.
The analysis for the countries in the Northern part of Africa and the Middle East is a particular strange one. When the data were adjusted for the fixed effects model, the statistical program gave a failure notice of a singular matrix. It seemed that all the countries of this continental region did not adjust their level of IPR protection in the period between 1975 and 1994. This can be double checked in the patent index by Ginarte and Park (1997) in the Appendix.
Table 8: The Results of the regression on the adjusted database with FDI/Capita as dependent variable on an annual basis between 1975 and 1994 for the South-East Asian countries.
Dependent Variable: FDI/CAPITA
Variable Coefficient Prob.
GDP Growth 52.13448 0.3160
Inflation -4.265278 0.8192
IPR protection -14.46485 0.2144 Political Freedom*** -6.079675 0.0013 LN Real GDP per Capita 8.879081 0.4230 Sec. School enrollment*** 207.9010 0.0039 LN(phones per 1000 inh.)*** 1.757714 0.0000
Trade area 3.364057 0.6576
R-squared 0.623352
Adjusted R-squared 0.607373 Durbin-Watson stat 1.457618
This means that it is not possible to see the effect of altering or lowering their protection level on the attraction of IPR. What is known is that in the original analysis there was a negative significant relationship, indicating that the countries in that area that had a lower protection level attracted less Foreign Direct Investments.
It still remains interesting to see whether the other determinants show their
Table 9: The Results of the regression on the adjusted performed database with FDI/Capita as dependent variable on an annual basis between 1975 and 1994 for the North African and Middle Eastern countries.
Dependent Variable: FDI/Capita
Variable Coefficient Prob. GDP Growth -36.87378 0.1045
Inflation -15.27879 0.2589
Political Freedom 1.035887 0.5487 LN Real GDP per capita*** 43.99694 0.0000 Sec. School enrolment*** 374.3171 0.0000 LN(phones per 1000 inh.)*** -20.79895 0.0003
R-squared 0.937859
Adjusted R-squared 0.934924 Durbin-Watson stat 0.946916
Table 10: The Results of the regression on the adjusted database with FDI/Capita as dependent variable on an annual basis between 1975 and 1994 for 82 the Sub-Saharan African countries.
Dependent Variable: FDI/CAPITA
Variable Coefficient Prob. GDP Growth 2.045669 0.9088 Inflation -0.710010 0.9196 IPR Protection -0.746451 0.9213 Political Freedom 1.052740 0.4722 LN Real GDP per capita*** 2.595388 0.6639 Sec. School enrolment*** 242.5131 0.1404 LN(phones per 1000 inh.)*** -19.36598 0.0002
R-squared 0.041604
Adjusted R-squared 0.026972 Durbin-Watson stat 1.988771
The results for the sub-Saharan countries show support for the theory for
Ferrantino (1993) and Primo Braga & Fink (1998) although the negative effect of IPR protection is insignificant. Actually, all the results of this analysis are insignificant, except the no. telephones per 1000 inhabitants which have a negative coefficient. Overall, this model has a very low value of R-squared, 0.04, which means this model explains a mere 4% of the variation of FDI per Capita is this region. This might be caused by omitted variables in that area. The extreme weather conditions for instance create very specific problems that might not be included in this
6. Conclusions and recommendations
In this research I have tried to examine the effect of Intellectual Property Rights protection as a determinant of the inflow of Foreign Direct Investment. This study used data from 82 countries in the period between 1975 and 1994 on determinants of FDI. The first objective was to find out whether there exists a positive or negative relationship, and whether that relationship is significant or not. Second objective was to find out whether there is a difference in the relationship in different parts of the world, which was divided in continental regions.
In order to assess this objective properly an extensive research in the existing literature was conducted. The determinants of FDI to be measured were determined and their expected effects on the inflow of FDI were mentioned. This led to a multivariate regression analysis which was first conducted on the complete database of 82 countries, and later on the geographical regions in which the database was divided.
The first result of the regression analysis was that IPR protection does have a significant positive effect on the inflow of FDI and thus can be added to the list of location advantages by Dunning is his paradigm. Unfortunately the model, which explained more than 31% of the variation of FDI inflow, had a very low value of the Durban Watson statistic. This low value of the Durban-Watson statistic of the analysis suggested autocorrelation. To correct for this autocorrelation a differences model needed to be created. The national average was subtracted from every value of every variable, which generated an adjusted database. The results of the regression of this adjusted analysis show that IPR protection indeed has a positive significant effect on the attraction of Foreign Direct Investment. This was confirmed by the analysis of the national averages over the period of 20 years.
In the analyses per region it became clear that the relationship differs greatly. In high income countries, IPR protection is positive and significant. It is important for these countries to protect their inventions. In the other continental regions the variable for IPR protection loses its positive coefficient. In the poorest regions of the world, a higher IPR protection rate has an insignificant negative effect on the Foreign Direct Investments.
countries to invest in their IPR protection, to be able to further develop their economies. Once the protection is high enough for companies to work through license agreements, local companies can welcome production assignments for Multinational enterprises. The results of the continental analyses in this research as well as the results by Ferrantino (1993) and Primo Braga & Fink (1998) suggest that the protection of IPR is of the biggest importance for the internalization advantages described by Dunnings OLI-paradigm, although the level of protection varies by location.
I hope that this result will make this thesis to a contribution to the field of Intellectual Property Rights protection. However, what I failed to achieve was to prove this result together with the expected effects of the other FDI determinants. Infrastructure was expected to have a positive effect on the FDI inflow, but it proved to be negative in this research. This is in contrast to the researches of Wheeler & Mody (1992) and Loree & Guisinger (1995), in which this variable was either insignificant or positive. Near multicollinearity with secondary school enrollment might offer an explanation for the negative results. A sensitive regression due to ignored near multicollinearity might produce coefficients for variables that are unreliable. This leaves an opportunity for further research. It is clear that with other infrastructure numbers than the number of phones per 1000 inhabitants, the results will change. The variable for openness also leaves room for improvement. This study uses the fact whether a country is a member of a free-trade area or not. All free-trade areas are assumed to have the same economic value, whereas in reality this is not the case. Some of the free-trade areas have an economic force that much higher and has more influence than others of the considered free-trade areas. Alternatively, the import and/or export numbers could be used to measure openness. The import and export percentages give a better view on how dependent a country is of other countries. Using this variable would probably give other results for the openness of countries.
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