FDI and The Middle-Income Trap
Foreign Direct Investment’s Effect on Research & Development Spending in Middle-Income Countries
Note: This is an earlier draft of this work. An updated version can be found here: https://ccsenet.org/journal/index.php/jpl/article/view/0/49797
This paper attempts to explain the relationship between FDI inflows and R&D spending within middle-income countries. R&D spending is a key input for innovating, which helps middle-income countries escape or avoid the middle-income trap and advance towards high-income status. This paper uses OLS regressions to find that R&D spending is negatively correlated with FDI inflows. This paper then suggests exercising caution on the part of middle-income countries when accepting FDI. The findings of this paper should provide clarity for policymakers in middle-income countries when making policies regarding FDI.
We now live in the age of globalized capitalism. Companies increasingly do not have ‘home countries,’ as they now do not solely operate in a single country. These Multinational Corporations (MNCs) have arms all over the globe. A single iPhone needs parts produced in 43 countries and six different continents. MNCs use Foreign Direct Investment (FDI) in order to set up businesses outside of their ‘home country’ in order to serve their supply chain needs. According to Kaname Akamatsu’s Flying geese paradigm, capital will find where ever wages are the cheapest to perform low-value adding economic activities. So capital will enter relatively poor countries for the purpose of setting up enterprises that specialize in relatively low-value adding economic activities. This creates questions on the impact of FDI on developing countries’ ability to develop, namely middle-income (MI) countries.
From 1960 until 2008, there have only been 13 MI economies that have been able to advance towards high-income (HI) status. Except for these cases, most MI countries have been unable to transform into a fully ‘developed country.’ The term the ‘Middle-Income Trap’ (MIT) has been created to describe this phenomenon. The consensus to explain the MIT is that after advancing towards high MI status, countries lose their competitive advantage in low-value added economic activities, since their wages have grown relatively high, yet are unable to compete in higher-value added activities, since they lack the ability to innovate. Scholars have thus stressed the importance of investments, such as research and development (R&D) and other ways to improve levels of human capital, when suggesting policy responses to the MIT.
There are debates about whether FDI hurts a country's ability to innovate, upgrade industries, and advance to the next stage of development. This paper does not seek to fully answer this question, yet it seeks to explain the effect FDI has on R&D spending within MI countries. R&D spending is a critical input for creating indigenous innovation capacity. Some have theorized that too much FDI could impact a country's ability to innovate (Zeng and Fang, 2014) (Doner and Schneider, 2017). Through FDI, MNCs, and by extension the rich world, could just be profiting from the host country’s cheap labor, and move those profits back to the MNC’s home country, ensuring they can not be invested in R&D inside of the host country. Through a multivariable OSL regression, this paper seeks to see if this is true, but first, we will review what the current literature has to say about FDI’s effect on R&D spending in MI countries.
FDI’s Effect on R&D Spending
There are debates among Economists about whether FDI hurts or aids the development of new technology. On the pro-FDI side, some argue that the spillover effects and tighten competition will increase innovation in developing countries. Erdal and Gocer (2015) argue FDI spending in developing countries should have a positive effect on R&D spending and other ‘innovation activities.’ This is because of spillover effects, as local staff internalize the knowledge and technology of these foreign enterprises after working for them. They look at 10 ‘developing’ countries solely in Asia (China, India, Iran, Pakistan, Malaysia, Thailand, Saudi Arabia, Turkey, South Korea, and Singapore) from the years of 1996–2013. Though it should be noted that both South Korea and Singapore were HI, developed countries for most of the years they looked at. The model they constructed shows that FDI inflows are expected to increase developing countries’ level of R&D spending and increase the frequency of other innovation activities. They conclude that developing countries that suffer from capital deficiency and technology gaps, when compared to the developed world, should construct public policy to increase the level of FDI in their country. Erdal and Gocer (2015) fall short since they solely look at Asian countries, added two developed countries, and looked at a shorter time period when compared to the model constructed in this paper.
One argument that comes from the anti-FDI side, FDI inflow could create a situation in which foreign R&D spending acts as a substitute for domestic R&D spending. In this case, domestic firms will just try to imitate foreign products rather than trying to create indigenous technology. That is precisely what Azman-Saini et al (2018) argue. Their data set consists of 48 developing countries over the years of 1996 to 2013. Their model shows that FDI inflows depress R&D spending in these developing countries. While FDI does depress R&D spending, it is positively correlated with “imports of machinery and equipment, stronger legal protections, better human capital, and higher economic growth.” Their paper does a better job than Erdal and Gocer (2015), yet Azman-Saini et al (2018) fail to take advance of all the data that is currently available.
Now we will turn towards what Political Economy and Political Science have to say about the relationship between FDI inflows and R&D spending has on MI countries. While all of their research is more extensive than just the relationship between FDI inflows and R&D spending, we can infer how they believe the relationship would be. Doner and Schneider’s (2017) research looks at the political economy of the MIT. They state that the economic impediments leading to the MIT mostly come from productivity slowdowns as they ‘exhaust the gains from moving into MI status,’ (or at least the current economic literature says so). MI countries, on the aggregate, grow slower than low-income (LI) and HI ones, as they can no longer compete with LI countries in low-value added industries (since their wages are too high) and HI countries in high-value added industries (as they are not technologically advanced enough yet). To upgrade industries and make improvements in human capital, a country needs more and better education (especially higher and technical), greater savings and better investment, better infrastructure, more innovation, more R&D spending, and industrial policy. To pursue these policies, a state needs better institutions, yet there are social cleavages that exist in MI countries that make coalition building for these institutional upgrades very difficult. These cleavages include economic inequality, informal workers vs. formal workers, and home-grown businesses vs. multinational corporations (MNCs).
They warn against too much FDI. MNCs do not have vested interests in upgrading the host country's institutions or industries and most of their R&D spending is in their home country. MNCs could just be profiting from the developing countries’ resources, such as cheap labor, and taking benefits back to their home country, trapping the host country in their place in the global supply chain. From their argument, we can assume that MNCs do not have much interest in R&D spending in host countries. Because of this the larger the share of FDI in a country, the lower the R&D spending. Also, there are political problems that derive themselves from the cleavages between local businesses and MNCs. This could make the political system unable to invest in R&D.
Zeng and Fang (2014) use World-Systems Theory to explain the MIT, which works nicely as,“during the last two decades of the 20th century there appears to have been less upward mobility than occurred in the 1960s and 1970s, which suggests that ‘globalization’, rather than spreading wealth and facilitating development, may create barriers for nations on the lower rungs of the global economy to move upwards.” Because of the global division of labor that global capitalism brings, countries far down the supply chain cannot advance from the periphery (and semi-periphery) to the core. The industries in the periphery are much more competitive when compared to industries in the core, since there is a much smaller amount of countries to compete in core industries, which the authors label as “quasi-monopolised.” So when exchange happens between core and periphery countries, competitive products are in a much weaker position, so “there is a constant flow of surplus value from the producers in the periphery to the producers in the core.” Periphery and semi-periphery countries usually do not have the power to change the system and are almost forced to go along with the nature of global capitalism as they are dependent on the core. To break this and develop, developing countries must be selective about what FDI they allow in, and the state must invest in industrial upgrading and R&D to move towards knowledge-based, high value-added economic activities.
They pay special attention to China, labeling its development as ‘dependent.’ They state that FDI has contributed to China’s development thus far, yet will create hurdles to creating indigenous innovation capacity. The reason being is that foreign investors use China as a production base for economic activities with thin profit margins. Due to this, China cannot produce enough profit to reinvest in its productive capacity. Thus R&D will be ignored. FDI also creates insecurity. As capital will go to wherever wages are the lowest, this might incentivize keeping wages low and sticking with current industries. Again, the industries that foreign investors use China for do not produce a large amount of profit, so this could suppress R&D spending for the short- and long-term. From their argument, we can make the assumption that due to the low profit-generating nature of the industries that FDI inflows set up, it would be difficult for MI countries, that take in a large among of FDI, to devote enough money to R&D.
There seems to be no consensus as to what FDI means for R&D spending in MI countries. Some studies just look at developing countries as a whole. This is a mistake, as R&D spending is not as crucial to low-income (LI) countries when compared to MI countries. Much of the quantitative research also does not take full advantage of the available data, narrowing down the number of countries and the number of years used when constructing a model. Most of the qualitative research is bearish on FDI’s impact on developing countries' R&D spending and their ability to innovate more generally, yet has yet to provide empirical evidence to support these claims. Due to the gaps in the current literature, research that looks at all MI countries over the longest amount of time would be welcomed.
Hypothesis and Data
The hypothesis of this research is that if a greater share of the economy is dominated by FDI, there should be less profit directed towards R&D spending. This is for three reasons; 1) MNCs’ R&D spending is concentrated in their home country, so the profits generated by FDI should contribute to the already developed world’s R&D spending (Doner and Schneider, 2017). 2) Due to the nature of the economic activities that FDI usually creates in MI countries, very little profit is left within the host country. There would not be enough profit left to reinvest in R&D spending within the host country, as more basic investments would take priority over R&D investments (Zeng and Fang, 2014). 3) Lastly, FDI would incentivize copying foreign technology rather than making the investments needed to create indigenous innovative capacity (Azman-Saini et al, 2018).
The data collected comes from the World Bank’s DataBank (https://databank.worldbank.org/source/world-development-indicators). The data includes all 110 countries listed under the World Bank’s middle-income country category and spans over the years of 1960 to 2020. The variables collected were:
R&D expenditure (% of GDP)
Foreign direct investment, net inflows (% of GDP)
GDP per capita (current US$)
Gross domestic savings (% of GDP)
Current account balance (% of GDP)
Imports of goods and services (% of GDP)
Exports of goods and services (% of GDP)
The first OLS regression just has the independent variable, R&D expenditure (% of GDP), and the dependent variable, Foreign direct investment, net inflow (% of GDP). After removing the years with missing data, 886 observations were recorded in the first regression. Due to the large amount of observations of this project, to visualize the data, only observations in the year 2017 were chosen for Figures 1 through 3. Figure 1 shows the amount of R&D spending relative to GDP in MI countries for 2017, Figure 2 shows the amount of FDI relative to GDP in MI countries for 2017, and Figure 3 is a scatter plot chart of both variables.
As for the second OLS regression, five control variables were added; GDP per capita (current US$), Gross domestic savings (% of GDP), Current account balance (% of GDP), Imports of goods and services (% of GDP), and Exports of goods and services (% of GDP). The countries and the years remained the same as the first regression, but after removing the years with missing data, 835 observations were recorded. Both the first and second regression results are shown in Table 1.
Discussion of Results
In the first OLS regression, we can see that the two variables have a significant negative relationship. From this model, we can assume that one standard deviation increase of FDI should result in a decrease of .00647 of a standard deviation of R&D spending in MI countries. This is not a very large effect, as the standard deviation of FDI is quite large and the standard deviation of R&D spending is rather small. Yet we can claim that increases in FDI in MI countries should result in decreases of R&D spending.
In the second OLS regression, we can see that the relationship is still significant and still negative. Yet not as strong as in the first OLS regression. The P value of FDI’s variable dropped from .004, in the first model, to .017, in the second. The coefficient rose from -.0064683, in the first model to -.0061336, in the second model. Again, much like the first model, the effect is not very large, due to the size of the variables' respective standard deviations. Again, we can claim that increases in FDI in MI countries should result in decreases of R&D spending.
From both of these models, we can reject the null hypothesis that FDI and R&D spending move together in the same direction and assume that Erdal and Gocer (2015) are misguided. It would be irresponsible on their part to argue, as they did, of “the need of FDI for (developing) countries who want to increase (the) level of R&D and innovation.” While the findings of this model, does not confirm the findings of Erdal and Gocer (2015), it does confirm the empirical findings of Azman-Saini et al (2018). This model also provides some empirical evidence for both Doner and Schneider (2017) and Zeng and Fang (2014).
As for the reason why the relationship between FDI inflows and R&D spending within MI countries is negative, this paper cannot give a definite answer. It could be one, two, or all of the three reasons given in the hypothesis, or it could be something entirely different. What we can conclude is that we can reject that FDI inflows in MI countries does encourage R&D sending.
Conclusion
The scholarship regarding the relationship between FDI inflows and R&D spending in developing country seems somewhat undeveloped. A few did not take full advantage of the existing, available data. When using all the data available, much like what this paper did, we can see that increases of FDI inflows in MI countries discourages R&D spending. This research should provide policymakers in MI countries with some clarity when forming policies governing FDI. Most of the scholarship surrounding the MIT focuses on some MI countries' inability to innovate and compete with the developed world in high-tech industries. One of the key inputs for innovation is R&D spending. This is why MI countries looking to develop and advance towards HI status, should be cautious about letting in large amounts of FDI. Though a more nuanced approach would be to look at the nature of the FDI. Javorcik (2004), studying Lithuania (a recent graduate to HI status), finds that when FDI is used to set up a fully foreign-owned enterprise, there is no evidence of productivity spillovers to domestic firms. This story changes a bit when he looks at joint ventures. His findings show that positive productivity spillovers exist through contacts between the joint venture and local firms in upstream sectors. So it seems as though the nature of FDI is quite important if it is used for local industrial upgrading. It is unclear if joint ventures would increase R&D sending when compared to fully foreign-owned enterprises, but this seems like a good place for the literature to head into. What is clear is that generally speaking, larger FDI inflows would discourage more R&D spending in MI countries.
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