A Look at the Relationship Between Intellectual Property and Investment

Introduction:

Globalization is changing the legal and political landscape of intellectual property worldwide. Intellectual property encompasses intangible assets such as branding, patents, copyright, and design rights. Intellectual property is fairly recent and discussed topic. As globalization persists, talks advocating for the protection of ideas and inventions have increased. People not only want to protect their ideas domestically but globally as well. Strong intellectual property rights have been known to foster innovation globally. The interconnectedness of intellectual property and development is becoming an even more relevant topic due to the inclusion of Trade Related Aspects of Intellectual Property Rights (TRIPS) in agreements overseen by the World Trade Organization. The TRIPS agreement set the groundwork for the current international intellectual property law and was heavily supported by developed countries. Intellectual property is more popular in developed countries than developing countries because developed countries have the legal and political means to enforce intellectual property. Subsequently, there are also upcoming conferences and summits regarding the use of intellectual property in developing countries. In fact, from April 20-April 24 there is going to be a committee on Development and Intellectual Property that will take place in Geneva, Switzerland. Conferences like the one mentioned is the perfect forum for developing countries to express their concerns regarding intellectual property. The main concern of developing countries is whether or not the use of intellectual property would foster or hinder economic growth in their respective countries.

That being said a topic I would like to investigate further is the following: Does the use of intellectual property impact investment inflows in middle- income countries? Middle- income countries are essentially classified as developing countries. This study is important because it can be a reference point for developing countries that are questioning whether or not to strengthen intellectual property rights in their respective countries as a means of improving levels of investment inflows.

Theoretical Argument:

Based on the research I have read I want to expand on the existing arguments and implement my own variables into the project. I infered that intellectual property will have a positive causal relationship and impact investment. Applying intellectual property systems in middle- income countries generates a favorable environment for foreign investment. Enforcement of intellectual property in a country is highly valued by investors because it is an indicator of a nurturing business environment. Intellectual property drives economic growth thus encouraging investment. To delve deeper, the implementation of intellectual property is an indicator of stability and of an advanced business environment, therefore, increasing the amount of FDI in a country. Multinationals crave stability when they establish business in any environment because they want to make sure their investment is safe.

Data and Methods:

The unit of analysis is country year since this project is a time series cross sectional analysis looking at different units at different periods of time. Only upper and lower middle income countries were selected as cases for this project because low- income countries are unlikely to have the means to implement intellectual property rights in their respective countries. Upper income countries were also taken out of the study because I wanted to look at countries that would be considered developing. The World Bank defines upper middle- income countries as, “Upper-middle-income economies are those in which 2013 GNI per capita was between $4,126 and $12,745.” Furthermore, lower middle- income countries are defined as, “Lower-middle-income economies are those in which 2013 GNI per capita was between $1,046 and $4,125.”

Intellectual property, the independent variable, is operationalized as charges for the use of intellectual property. Investment, the dependent variable, is operationalized as foreign direct investment net inflows. In order to improve the validity of the study there will be several control variables as well. All of the data and variables can be found via World Bank World Development Indicators, this allows for a uniform data source.

The dependent variable is foreign direct investment; net (BoP, current US$) is defined as “foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor.” The independent variable is charges for the use of intellectual property, payments (BoP, current US$) which is defined as “charges for the use of intellectual property are payments and receipts between residents and nonresidents for the authorized use of proprietary rights (such as patents, trademarks, copyrights, industrial processes and designs including trade secrets, and franchises) and for the use, through licensing agreements, of produced originals or prototypes (such as copyrights on books and manuscripts, computer software, cinematographic works, and sound recordings) and related rights (such as for live performances and television, cable, or satellite broadcast).” This measure differs from the previous studies that have looked at intellectual property rights. This measure of intellectual property is different from measuring the strength of intellectual property rights because this measure looks at what is essentially the enforcement of those intellectual property rights. In other words, it is looking at how much money is in circulation as a result of the existing intellectual property rights. This is a more effective way to measure the success of intellectual property compared to other studies. The other variables are trademark applications, patent applications, and research and development expenditures. All of these variables fall into the category of intellectual property, thus there is validity that the measurement captures the concept. The variables are measures as the following: patent applications for nonresidents and residents(#) , trademark applications(#), and research and development expenditures (% of GDP). Patent applications are defined as, “Patent applications are worldwide patent applications filed through the Patent Cooperation Treaty procedure or with a national patent office for exclusive rights for an invention — a product or process that provides a new way of doing something or offers a new technical solution to a problem. A patent provides protection for the invention to the owner of the patent for a limited period, generally 20 years.” Trademark applications are defined as “Trademark applications filed are applications to register a trademark with a national or regional Intellectual Property (IP) office.” Research and development expenditure (% of GDP) is defined as “expenditures for research and development are current and capital expenditures (both public and private) on creative work undertaken systematically to increase knowledge, including knowledge of humanity, culture, and society, and the use of knowledge for new applications. R&D covers basic research, applied research, and experimental development.” These variables are expected to present similar results to the main independent variable of charges for the use of intellectual property. All my variables are continuous variables because they have equal unit differences. The use of all continuous variables means that a correlation test or regression test must be performed. Since there are limitations in a correlation test, I am conducting both a regression and correlation test.

The presence of control variables eliminates omitted variable bias and spuriousness. My control variable is GDP per capita. This variable is defined as, “GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.” These variables are measured as either percent of GDP or current USD. GDP per capita will control for the differences in income between upper and lower middle income countries. Another control variable is total tax rate which “measures the amount of taxes and mandatory contributions payable by businesses after accounting for allowable deductions and exemptions as a share of commercial profits. Taxes withheld (such as personal income tax) or collected and remitted to tax authorities (such as value added taxes, sales taxes or goods and service taxes) are excluded.” Tax rate is a good control variable because a tax rate placed on corporations is a large deciding factor for whether or not multinationals invest in a country. This is to ensure that any increase in investment is from an increase or decrease in charges for the use of intellectual property rather than the tax rate or income level.

Hypotheses:

I will be assessing the relationship between continuous variables, therefore, as aforementioned I will be conducting a correlation and a regression test. The correlation and regression test has a corresponding set of hypotheses. The hypothesis for the correlation test is as follows:

HO: There is no relationship between charges for the use of intellectual property and foreign direct investment net inflows.

HA: There is a relationship between charges for the use of intellectual property and foreign direct investment net inflows.

The corresponding hypothesis for the regression test is as follows:

HO: β=0, there is no relationship between charges for the use of intellectual property and foreign direct investment inflows.

HA: β > 0 (β is positive, indicating a positive relationship between the independent and dependent variable.)

For the regression test I will be running two models. The first model will simply look at relationship between charges for the use of intellectual property and foreign direct investment net inflows. The second model will run those two variables along with the control variables and the other variables. The second model is designed to look at how the other values impact the results for the main independent variable. Essentially this will account for potential confounding variables.

Findings/Results:

The first test conducted was the correlation test. Correlations closest to 1 or -1 are ideal and are considered almost positively associated.

Although correlation tests have many limitations, they are a good indicator of an association between variables. The correlation test indicates a 0.9465 almost perfect positive association between the dependent variable FDI and the independent variable charges for the use of intellectual property. The p- value suggests a zero percent chance of observing this correlation by chance. With this p- value we can reject the null hypothesis that there is no relationship between the independent and dependent variable, at all critical levels. We accept the alternative hypothesis that there is a relationship between FDI and charges for the use of intellectual property.

Next, I looked at the correlation between the dependent variable (FDI) and the two control variables (GDP per capita and total tax rate). I anticipated a stronger association between FDI and these control variables. Surprisingly, as depicted in the table, both control variables have a weak positive association with the dependent variable.

Finally, the table above depicts the correlation between all the variables in the study. Unfortunately, correlation tests cannot account for control variables, thus the correlation for charges for the use of intellectual property remains unchanged in the table above compared to the initial correlation test. All of the variables are positively associated with one another; however, some variables have a stronger association than others. The p-values are also statistically significant at the 0.01 level, except for the relationship between tax and GDPPC. For instance, trademark applications are strongly associated with not only foreign direct investment, but also charges for the use of intellectual property. I anticipated this because trademark applications falls under the category of intellectual property. Since correlation does not indicate causation, a regression test must be performed. The regression test will assess the statistical and substantive significance. The purpose of the regression test is to understand the extent to which the independent variable has an effect upon the dependent variable.

The beta value for Model 1, which looked at the dependent variable and the main independent variable, is 15.77586. Given this positive beta value and the p- value of 0.000 we can reject the null hypothesis at all critical values indicating that there is a statistically significant relationship between the two variables. We accept the hypothesis that an increase in charges for the use of intellectual property will result in an increase in foreign direct investment inflows.

The beta value decreases from Model 1 to Model 2 when taking into account the other variables. However, the beta value is still positive and statistically significant at all critical values. The beta value for the first Model signifies that for each one unit increase in charges for the use of intellectual property there is an estimated 15.76 increase unit increase in FDI. The suggested equation for this relationship is FDI = -1.79e+08 + 15.76*IPcharges.

The R2 value is the variance in the dependent variables that can be explained by the independent variable. In Model 1 89.58% of the variance in the dependent variable FDI can be explained by the independent variable, charges for the use of intellectual property. In Model 2 the r-squared value increases meaning that 94.52% of the variance in the dependent variable FDI can be explained by the independent variable when controlling for other variables.Thus, this model for the regression test becomes much more accurate in accounting for the change in the dependent variable which is explained by the independent variable.

This scatter plot depicts the line of best fit between charges for the use of intellectual property which is on the x axis and foreign direct investment which is on the y axis. This line of best fit describes expected outcomes of FDI based on the values for the IP charges. The upward slope indicates a slight positive association between charges for the use of intellectual property and foreign direct investment net inflows. The results above were statistically significant; however, that does not imply substantive significance. Substantive significance measures the degree of variation between the two variables. A change in 1 standard deviation in charges for the use of intellectual property predicts a change in approximately 1.2433498 standard deviations in FDI.

Implications and Conclusions:

Based on the results it is safe to assume that an increase in intellectual property charges will result in higher investment inflows. The results supported the original theoretical expectations. The study implicates that the presence of intellectual property increases investment in middle-income countries. Although, the study had control variable there is still a possibility of omitted variable bias because there are many factors that can dictate the level of investment inflows a country receives. A potential control variable that should have been used in the study is interest rates because they are a huge factor is deciding investment in countries. There is also a possibility that there are biases in the method of data collection, however, it is difficult to asses this because the data collection was from the World Bank. Further studies should look at various industries and consider how intellectual property impacts investment in each of them. For example, the manufacturing and pharmaceutical industry relies heavily on intellectual property rights in the form of patents compared to other industries. These are also heavily pirated industries, thus adding to the potential benefit of the study. In terms of policy recommendations based on the study, developing countries simply need to enforce their existing intellectual property laws and draft more patents for their citizens in order to ensure more investment inflows.

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