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Trade and migration of foreign nationals in the globalized OECD

An analysis on the correlation between wealth accumulation through international trade and

migration flows of foreign nationals in OECD countries

Abstract: Developed countries around the world and especially in Europe have been trying to reduce

migration flows since the 90s. The question is if their increased migration is simply a symptom of

their success in the international markets. In this research 32 OECD countries are analysed with a

closed up look on six differing cases and their performance on three fields: economy, policy and

migration. Results show that economy and migration factors are the strongest correlating factors

while policy seems to affect economic factors and both directly and indirectly affect migration itself.

1st reader: Dr. P.W.A. Scholten 2nd reader: Dr. A. Pisarevskaya

Thesis Governance of Migration and Diversity Wassim Benali (374380) 15-01-2019

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Contents 1 Introduction .......................................................................................................................................... 4

2 Theoretical framework ......................................................................................................................... 5

2.1 Global inequality and power relations forming push and pull factors .......................................... 5

2.2 Globalization in economics............................................................................................................ 7

Capitalist imperialism ...................................................................................................................... 7

Centralization of capital and the increase in global investment flows ........................................... 7

Current situation: premature deindustrialization and the consequences for migration ................ 8

2.3 Policy context of migration in the first world: Social expenditure and world market integration 9

Migration policy indexes, data sets and the OECD ......................................................................... 9

Research on social expenditure and its impact on migration flows ............................................... 9

World market integration.............................................................................................................. 10

On indexing policy ......................................................................................................................... 10

2.4 Summary...................................................................................................................................... 11

3 Research design .................................................................................................................................. 12

3.1 Research question and hypothesis .............................................................................................. 12

3.2 Methods ...................................................................................................................................... 13

3.3 Case selection .............................................................................................................................. 13

3.4 Plan for implementation research and limitations ..................................................................... 14

3.5 Operationalization ....................................................................................................................... 15

3.5.1 First step analysis: Levels of wealth accumulation through global trade ............................ 15

3.5.2 Economic metrics ................................................................................................................. 15

3.5.3 Correlation analysis .............................................................................................................. 16

3.5.4 Migration data ...................................................................................................................... 16

3.5.5 Economic and policy context ................................................................................................ 16

3.6 Summary .................................................................................................................................. 18

4. Economic findings and case selection ............................................................................................... 19

4.1 Collected account balance and FDI income numbers ................................................................. 19

4.2 Rankings ...................................................................................................................................... 22

5. Findings .......................................................................................................................................... 24

5.1 General overview case countries ................................................................................................ 24

5.2 Migration ..................................................................................................................................... 26

5.3 Policy ........................................................................................................................................... 27

5.4 Subconclusion .............................................................................................................................. 29

6. Analysis .............................................................................................................................................. 30

6.1 SPSS analysis ................................................................................................................................ 30

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........................................................................................................................................................... 31

6.2 Policy analysis .............................................................................................................................. 35

6.3 Open economies, selective migration ......................................................................................... 36

7. Conclusion and discussion ................................................................................................................. 37

7.1 Conclusion ................................................................................................................................... 37

7.2 Discussion .................................................................................................................................... 38

8. Bibliography ....................................................................................................................................... 39

9. Appendix ............................................................................................................................................ 42

9.1 OECD Countries ........................................................................................................................... 42

9.2 Data sets ...................................................................................................................................... 43

Current Account balance as part of GDP ....................................................................................... 43

FDI income as percentage of GDP ................................................................................................. 44

FDI restrictiveness index................................................................................................................ 45

Social expenditure as part of GDP ................................................................................................. 46

Migration inflow of foreign nationals............................................................................................ 47

Migration outflow of foreign nationals ......................................................................................... 48

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1 Introduction Globalization is a contested word today and fierce discussion are still had about the question if it had

or has a positive impact on society and if that impact affects all or only a certain subset of people.

What is uncontested though is that the world has never been as connected as it is today, the internet

has seen widespread adoption in every country and so has international trade and increasingly also

international investments been slipping inside the creaks of protective legislations. Where foreign

direct investment (FDI) remained strongly restricted in certain countries, the shift began to FPI

(foreign portfolio investment) according to OECD data. FPI amounted for 81% of total general

investments in OECD countries when measured in 2007 (OECD, 2010). Profit from FDI for the national

economy is low (it is essentially people buying company stocks). It is mostly the national broker

benefitting in the form of a small transaction fee which will end up showing up in GDP anyway. A

good economic outlook stems from capital retention, where FPI falls short as a low influence

indicator. As such income from FDI still remains a strong indicator of success on a global scale in

combination with exports. Emerging economies proved themselves to be successful in seizing the

moment and grabbing on a piece of the success that central, rich economies have been having for

decades. With this success there are also losers that can’t keep up and it are those countries that are

facing the consequences. The world and its global economy is not a big monolith. It is structured in

richer and poorer factions that interact with each other. The richer countries have more economic

power, this not only makes them independent and prosperous in itself but also creates a dependency

in the third world (and poorer nations in general) that are not financially independent. They rely on

foreign capital to survive but also to progress and get out of their situation but what if the divide

proofs to be to great to overcome? If the generation educated to lift up the country can’t find proper

job opportunities? Will the gap in development in combination with the grand economic success of

developed countries cause the developing countries’ labour ‘elite’ to migrate to the developed

world? Does policy also play a role in shaping the migration flows or do they simply reflect the

economic realities? This research aims to discover if there is a correlation between the economic

success on the global market of developed economies and their migration flows. What role does

economy play and what role does policy play? Do they interact with each other and what decides if a

country has a high turnover rate when it comes to foreign national residents and do either economic

or policy factors play a role in this?

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2 Theoretical framework The beating heart of this theoretical framework shall be the analysis of migration flows, with

economic conditions as the leading theme. This framework mentions but not focus on cultural links,

diaspora networks and regional conditions such as war or climate change. This is for practical

reasons as will be explained in the next chapter. Split in three parts, the theoretical framework

begins with a selection of mainly sociological development and migration theories based on global

dependency and functionalist theory to set the stage of this research. In the second section the

theoretical tools for analysis will be expanded by explaining materialistic conditions through the eyes

of economists. Finally, the policy subchapter shall go through policies directly and indirectly affecting

migration and two concepts that link policy choices to migration and economic growth. The

conclusion will supply us with a summary before moving on to the research design.

2.1 Global inequality and power relations forming push and pull factors With the rise of media and modern communication and transportation technologies, the divide

between the poor and the rich on a global scale becomes more visible than ever before. We see

migration patterns from the developing world to the developed world. For academic researchers in

migration one of the main points of research revolves around the question how people choose their

country of choice. Within the realms of migration theory a distinction is made in between two camps,

the functionalist and historical-structuralism. While the first focuses on differences in demand for

labour or individual pursued with the aim of profit maximization, the latter is rather focused on the

effects of global capitalism and power relations around the globe (Castles, de Haas, Miller, 2013: pp.

27-28). Both believe that there are structural imbalances in the world that cause poverty and

eventually move people to migrate to places where there is a better economic outlook.

The historical structuralism method shall prove to not only be scalable like the functionalist but have

the added bonus of being an analysis of material conditions of systemic processes in the world

economy. Conditions that can be looked at form an economical and sociological perspective. One big

thinker within the realms of development and structuralist economy was Raúl Prebisch an Argentine

economist who, around the half of the 20th century, advocated for protectionism in underdeveloped

Latin American countries to promote domestic economic progress. This because the countries still

being too weak to compete with the richer nations. Prebisch with the German economist Hans Singer

(who developed similar ideas on global trade), formed the Prebisch-Singer hypothesis that would be

the fundament of the world dependency theory. The hypothesis argues that because of the lower

elasticity of primary goods (goods produced in less developed nations), a rise in incomes would not

affect that output or demand for those goods. This while demand for luxury goods would increase

when income rises, them being either secondary or tertiary. This means that they are much more

price elastic. A study by Harvey, Kellard, Madsen and Wohar (2010) had as conclusion from a

substantive analysis of 4 centuries that there is merit in the hypothesis. Many poor nations are now

producing simple secondary goods (T-shirts for example). The implications of this and lowered

development as explained by the hypothesis is something that will come back in contemporary form

in the economic part of this chapter.

For potential migrants the situation is akin to the glass ceiling analogy. Many of them see themselves

or friends and family working in companies from the richer countries creating products that they

themselves desire but cannot afford (economic side). They look at movies produced by the richer

countries which creates an even stronger dependency on a social level and even mentally. Accounts

from migrants (Nieswand, 2012) often state that they had to have someone in the family try and go

to the richer countries. Increasing status in sending countries but when they are being destined to

illegality or low paying jobs they are ashamed to tell their people at home about the situation or even

return at all. As we can see the dependency of whole countries on a world level impacts individuals

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within a society on various levels. The question is what makes certain countries more popular in one

countries compared to the other? Here we can go back to the previous examples of seeing foreign

companies in their home countries or foreign media better formulated as linguistic and cultural

distances. The connection often is because of colonialism in parts of for example Africa, South

America and Asia but a more general answer is being exposed to that country. If The Netherlands

have great profit from their companies trading in Ghana, tourists visiting their countries or even

development aid then the Dutch brand will grow in that country. This can be seen as one of the

benefits to looking at migration from the perspective of world dependency, because it is an

perspective that can zoom in towards to smallest of levels while being a macro analysis at heart.

More recently has been the popularization of the globalization theories. The dependency and world

system theories, respectively focusing on colonialism and first-third world trade relations are seen as

outdated by some scholars. It is argued that globalization is part of an advanced, late stage of global

capitalism while the previously mentioned theories are when capitalist was still evolving towards the

system as it is today in the 21st century. The modern relations in between nations today go beyond

trade disputes or imperial conquest: political alliances are made transcending thousands of

kilometres, communicational technologies allow for cultural exchanges to happen in an instant and

transportation technology allow for a record amount of flights (ATAG, 2014:p.5). Developing

countries have rich areas that seem to almost operate on a different speeds than the rest of the

nation with highly educated expat communities originating from all continents. A good example is

China where cities are differentiated in city tiers where the 1st tier of cities are metropoles and vastly

different compared to lower tier cities (PWC, 2018).

Yet migration has not seen a significant increase when it comes to quantity of regular (non-skilled,

capital holding) people moving around (Castles, de Haas, Miller, 2013: p.34). At the core of this

contradiction lies the highly developed phenomenon of globalized capital and growing importance of

foreign direct investment (FDI) in the global economy. Capital travels rather freely and with less

effort compared to migrants, the market moves towards the people instead of the people towards

the markets (Ibid). This especially after efforts of neoliberal scholars and leaders during the tail end

of the 20th century on opening up foreign markets for capital inflows. So migration has stayed a

privilege for those with the financial or social-human capital to move or special conditions. Think of

refugees, high skilled migration and other forms of wanted migration. The idea is: Why move humans

when you can hire a contractor in a foreign land, keeping the workers in their place or origin,

produce your goods for cheap with local (loose) regulatory context and ship those back? You can

choose any country you’d like to invest in, the most profitable will be chosen and in the end, the

profits can freely flow back ‘home’. Which in most likeliness be an highly advanced economy (Ibid).

The difference with traditional domestic production (done internally) is that local production does

not necessarily result in locally or nationally derived long term profits. For the latter to be achieved

more is needed than simply the opening up of one’s internal market such as structured

industrialization with domestic enterprises (OECD, 2002).

It is because of these materialistic conditions around the world that the separation between

structural-historic and functionalist thinking, where one looks at systems and historic relations while

the other side focuses on individual push and pull factors is a dated separation. Materialistic analysis

is scalable between macro-socioeconomic movements and micro-level considerations by individual

migrants. It is true that macro-analysis struggles with the detailed explanations that micro-level

analysis has however both of base themselves for a significant amount on the same core materialistic

assumptions.

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2.2 Globalization in economics To start a look in the economics of globalization one first has to go back before even the Prebisch-

Singer hypothesis to the time of the Bolshevik revolution in Tsarist Russia. After discussing the theory

of imperialism, the resulting centralization of capital will be discussed. Technology helped increase

the flows of capital. Finally these modern dynamics of capital will be linked with the contemporary

situation in non-dominant capital markets and with that migration.

Capitalist imperialism Materialism has historically been the basis of Marxist analysis and takes the materialist (economic)

conditions as the most important cause behind societal issues and the driver behind societal change.

Revolutionary socialists and Marxists in general were not only active in the analysis of the national

situation of their own country but also participated in the creation of theory based on the worldwide

system of capitalism and its effects for development. Paul Krugman (1980) schematized the ideas of

global economic imbalances as they were originally theorized by Lenin in 1917. The notion in his

article is that for capital intensive manufacturing to develop, capital is needed. Economies that

acquire a head start in wealth accumulation shall be able to expand on it and increase the efficiency

of their manufacturing. Creating a benefit on the global market, this while those that are behind will

see their capital intensive good manufacturing continuously decrease and be left to do mostly labour

intensive production. So while the capital rich economies specialize in capital intensive goods, the

other economies have to specialize in labour intensive goods to at least compete on some level with

the capital rich economies. The result of this model is the creation of advanced, emerging and

peripheral economies that interact with each other on the global stage (Krugman, 1980). From this

we derive a simple model explaining that differing amount of capital stocks can move on to create

long term and even continually increasing imbalances.

Centralization of capital and the increase in global investment flows Researchers such as Castells have expanded on the workings of modern information structures and

globalization in books that saw many re-releases (2010). What is seen is that the power of nation

states or even places in defining economic activity has lowered. Capital is more fluid than ever and

can travel throughout the world in a blink of an eye. Foreign direct investment (FDI) is a big part of

this increased capital fluidity. The importance of FDI on a macro level comes from its ability to

provide for much needed jobs in poor and rich countries alike but also nets foreign currency for

central banks and import of foreign goods. There is the case of FDI inflow (country receiving

investment) and that of FDI outflow (country investing outside of its borders). Around 2000 over 90%

of the world’s outflows originated from developed countries (OECD, 2002: p.7). What is shown in the

research of the IMF is that emerging markets see an increase in FDI outflow and with that an increase

in external assets (assets outside the own borders) (Bems et al. 2016: p.72). These could be anything

from foreign currencies to property in foreign nations. The surge of external assets is an indicator for

both economic development as well as further integration into the world market. The more income a

country has, the more it will start to invest outside of its own borders. The investments furthermore

get institutionalized in the form of for example pension funds (Bems et al., 2016). Taking the

globalization theory into account: The increase in FDI outflow and external assets made possible by

increased income, will mean that other countries on the receiving end will become more dependent

on the emerging market and thus affect the economic hierarchy. Furthermore, the wealth

accumulation decreases the effects of a reduction of FDI inflow from developed countries by creating

a buffer of sorts (Ibid). Countries without a developed economy or a strong emerging one with

capital buffers shall increasingly be marginalized because of the competitive nature of these global

economic workings.).

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So, while capital flows fluidly, the ownership of it seems less and less so fluid, especially when also

looking at the evolution of multinationals.

Liodakis (2005) showed that globalization has made the concentration of capital a much bigger

metric on the global scale.

‘It signals that stage at which quantitative changes in some factors turn into qualitative ones. In what concerns competition and the exploitation and accumulation potential, the impressive increase in concentration and monopolisation of capital leads to a complex and extensive development of large conglomerates, while the exhaustion of extensive limits shifts focus on the sphere of production and on intensive methods of development’ (Ibid: p.11).

Current situation: premature deindustrialization and the consequences for migration Migration is partly influenced by labour market conditions and it is in the developing countries that it

may be hard to get a job even when highly educated (Pedersen, Pytlikova and Smith, 2008). Though

classically the high skilled workers are attracted to developed countries because that is where the

jobs are including higher wages. This was believed to be reversed by industrialization, requiring

relatively low amount of high skilled workers initially compared to low skilled workers. Funding for

factories and such was provided by the increased global investment flows. The profit made from

industrialization and commodity production could then be used to increase wages, deindustrialize

and move onto becoming an advanced service economy. In his article, Rodrik (2016) explains the

concept of premature deindustrialization.

‘The hump-shaped relationship between industrialization (measured by employment or output shares) and incomes has shifted downwards and moved closer to the origin. This means countries are running out of industrialization opportunities sooner and at much lower levels of income compared to the experience of early industrializers’ (Ibid:p.2). This concept shows that while quite some countries in the east managed to go through the stages of peripheral, emerging and advanced, this progression has been halted because of poor economies being sucked into low-paying service level jobs provided by multinationals. Lack of perspective for low skilled workers and the high skilled is the reality in many lagging economies of today (Rodrik, 2016). Which would explain the phenomenon as discovered by de Haas, in which the weak economies see a surge of emigration after people earned enough to be able to leave: ‘People need a certain minimum of social and economic resources in order to be able to migrate. It is therefore no coincidence that wealthy people and societies tend to be generally more mobile than relatively poor people and societies. This challenges common views that poverty is the main driver of migration occurring within and from developing countries’ (de Haas & Rodríguez, 2010:p.2). De Haas researched the migration patterns in emerging economies and discovered that the common idea that economic progress will slow emigration down in third world countries is not fully correct. The emigration graphs show a curve in which early economic developed actually increased migration. This because of the earlier mentioned acquired ability to move with spare money but also because of increased aspirations within a richer and better educated society. It is only after economic progress continues in the middle and later stages that emigration slows down again (Ibid). The early deindustrialization theory explains that economic growth is slowing down in certain third world countries. Which in combination with de Haas’s theory should mean a continuation of patterns of emigration. “The real losers from globalization are those developing countries that have not been able to seize the opportunities to participate in this process“(Dollar and Kraay, 2001: p.73). Simply put: While economic improvement has happened in poorer nations, a wall has been put up in certain countries with stagnation and continued high emigration numbers as a result. In the next subchapter

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about policy we can see the capitalization on this situation by developed countries in the form of selection of migrants based on skill.

2.3 Policy context of migration in the first world: Social expenditure and world

market integration In this subchapter the overall impact of public policies on migration flows is discussed including the

relevant policy areas that either directly or indirectly affect migration. After which the impact of

social expenditure and world market integration get elaborated before ending with literature on

indexing migration policies.

Migration policy indexes, data sets and the OECD

Research from the OECD on policy and the effect on migration patterns in countries around the

world has shown that high income countries rarely engage in intervention to curb emigration (OECD,

2016: p.133). This while immigration policies have opened up to encourage migration between 1996

and 2016, albeit being more selective in who gets to enter. With the two most influential policy areas

being selection on basis of skills and policies regarding family reunification. This appears to be the

case in both high income as well as middle income countries, though only the former has seen

migration rise with a faster pace. Overall the OECD discovered that policies encouraging migration

had a more immediate impact on immigration than policies aimed at reducing immigration, which

had a gradual impact. The research suggests that this might be because of the fear of a possible

short-term nations of the regulatory relief (Ibid: p.138).

Besides policies directly affecting migration, there also are policies that can indirectly act as pull or

push factors for migration such as the ability of migrants to integrate in their new host country. One

of these are labour market policies. National job programs creating formal job contracts for citizens

can further the connection that citizens have with a country and with that discourage emigration as

well as the perspective on higher payed jobs through labour market mobility. On the other side

having a more open and liberal job market attracts migrants because of the low obstacles to

achieving employment as a migrant. Another policy area that showed effective is education, policy

on education can help countries both with retaining current inhabitants as well as attracting new

ones (OECD, 2016). Rainier Bauböck, researched the connection between naturalization and migrants

and has discovered that migrants self-report to experience better socio-economic positions, job

opportunities and a higher rate of political participation and engagement thanks to their

naturalization into the host country (Bauböck, 2006:p.63). Two policy areas that have a relatively

weak effect on migration according to the OECD publication were social protection and health

policies (OECD, 2016). Typically two areas that are also part of the social expenditure of a country

through its public institutions, a topic that will be further discussed in the next paragraph.

Research on social expenditure and its impact on migration flows

Social expenditure and migration have quite an history in public debate but is ‘welfare migration’

even a thing? In 2008 Pedersen, Pytlikova and Smith published a research on the migration flows

during the 1990-2000 period in OECD countries. It looked with a special focus on the possible

connection between social expenditure and migration flows. Herein it concluded that a strong

relation between the two has not been found.

‘In the short to intermediate run, however, job-related movers are only in incomplete ways entitled to social benefits in destination countries, the flows of tied movers are by nature strongly influenced by the stock of immigrants in a destination country, i.e. the network effect, and finally the flow of refugees consists of convention refugees, where entry depends on political decisions, and spontaneous individual asylum seekers, where the conditions for granting a residence permit depend on national immigration policies’ (Ibid:p.1181).

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According to the researchers this might have been because of tightened migration regulations,

especially in countries with large social expenditures, limiting the amount of choice people had in the

countries they wanted to migrate towards (Pedersen et al, 2008). This should logically mean that

voluntary migration/regular migration follows this result since that form of migration is falls fully

under the sovereignty of nation states. This while irregular migration (not directly bound by

migration regulation) or humanitarian migration (locked down in bilateral treaties) might be able to

show such an effect. Especially if the person is able to choose the country to take refuge in.

World market integration

To economically benefit from your top position in the world as discussed previously, one does need

to have a certain amount of openness to the world market policy wise.

Integration to the world market, inward FDI, migration and economic growth are often part of the

same bundled package in the leading first world countries. Claudia Buch and Farid Toubal (2009) did

a research on the connection between international market integration and growth where they

compared different West and East German states. What they discovered is that for developed

economies like Germany factors like international trade, migration and FDI helped in making use of

their position on the global scale by integrating oneself in the world market. On the other hand

having closed off policies like was the case in East Germany impacts those three factors and with

them also the potential for economic growth (Ibid).

‘There are not only few parents of multinational firms located in East Germany, but also the share of East Germany in inward FDI is particularly low. In a second step, we have used predicted values for bilateral openness and a trend term that is specific to the East German states to obtain instruments for the overall openness of each state. We find that trade openness has a positive and significant impact on per capita GDP’ (Ibid: pp. 420-421).

This does not only re-affirm global dependency theories as is the red herring of this theoretical

chapter but also shows us that FDI and migration themselves are also connected. Economy is leading

for the effects on the GDP though and migration seems to be only a by-effect, this conclusion can be

made on the fact that the researchers did not find a correlation between the share of immigrants

and the GDP when analysing those two factors alone (Ibid: p.421). Openness to trade and investment

is thus positive for GDP and as a by-effect migration occurs.

On indexing policy Creating or picking a good index when it comes to migration policies can be difficult because not only

does migration gets impacted by a wide variety of policy fields, migration itself has proven to be in

itself a diverse subject. In the research of Helbing et al. (2016) all these concerns are taken into

account with the extra vision on the importance of taking the measured years into account. The

biggest takeaway from the article is that conceptualization and definitions are important including

consciousness for the time range of the dataset. Especially when it involves multiple countries the

choice of policy and policy definitions used can impact the reliability of the data (Helbing et al, 2016).

Countries often use different definition and thus an index on the basis of migration policy has to

clearly define what it is measuring. Taking standardized data from countries with relatively similar

conditions such as the European Union or the OECD for example helps in this (Ibid). Since the current

research is only spanning a handful of years and focusing on economics and policy, other influencing

factors that cover the social factors of migration such as cultural ties will be excluded. More on this in

the following chapter but before that a summary of that which is discussed in this theoretical

framework.

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2.4 Summary Globalization and a more interconnected world is possible thanks to technological innovation and as

a result international relations are more impactful than ever before. Sociological theories followed

and grew together with globalization itself. Economy but also culture and regional events have a

global impact when it comes to migrant flows, this research chooses to focus on the economy and

the materialist conditions. The phenomena that resulted from the aforementioned globalization can

best be explained by the use of a combination of historical structuralism and functionalist views

where a world system of power relations is the main engine creating push and pull factors that drive

individual decisions to migrate. The ever adapting capitalist economic system took the form of

imperialism in the early twentieth century. Capital was concentrated by the method of conquest and

unequal trade relations. Today, technological improvements resulted in capital moving through

countries more often and faster than ever. The privilege to migrate to another country is still in the

hands of a select few in relative terms and while the rate of migration is increasing, it is a far reach

from the transformation that capital experienced. FDI and external assets can be indicators of

advanced development, emerging markets or economic stagnation. These metrics differ between

countries and can create a hierarchy of some sort between advanced economies with lots of spare

capital, emerging economies with profit potential and the left out peripheral economies. In modern

times, the categorization can be based on capital accumulation and retention. The countries further

along in their development have a big advantage to those that are lagging behind and are able to

invest more in foreign countries but also attract more capital themselves. The downside is for the

countries that industrialized last, which seem to be increasingly stuck in economic stagnation. At the

same time first world countries are trying to balance big social expenditure with openness to trade

and migration in order to benefit from their position in the world market without overstressing the

public sector with the use of various direct and indirect policy measures. The theoretical chapter was

concluded with a paragraph stressing the importance of taking conceptualization and definitions into

account when setting up a policy index or data set within the field of migration research.

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3 Research design

3.1 Research question and hypothesis The main research question: To what extent does the process of wealth accumulation from

international trade and investment correlate with the migration flows of foreign nationals in and out

of OECD countries?

Migration has seen a steady rise in numbers, especially to the developed OECD nations. The cause of

this can be found in numerous phenomena: economic upturns, war situations, but also international

trade relations causing issues that push migrants out of the origin country like premature

deindustrialization. The quantity in which the foreign national migrants migrate towards and

outward of OECD countries is the dependent variable of this research. It seeks to find a correlation

between migration flows of foreign nationals towards and outward of OECD countries and wealth

accumulation through trade and investment in addition to the existing thesis explaining policy

influence on the migration flows. The choice of to be researched countries fell on the OECD not only

because of this theoretical relevance but also practical considerations as will be discussed in the Plan

for implementation research and limitations (3.5). The conceptual model is as follows:

The independent variable are the push and pull factors affecting migration flows. From the theory we

know that policy affecting migration can be split in two sides, policy that directly regulates migration

flows and policy that indirectly affects migration flows. The addition this research will give to the

existing theory is seen in the scheme above in the box ‘Wealth accumulation through trade’. This is

hypothesized to be an additional factor in the shaping of migration flows. With the economic

relations a country has with the rest of the world economy being a potential pull or push factor in

itself, affecting the considerations of potential migrants. Wealth accumulation through trade and

investment is in itself affected by policies that also indirectly affect migration and the other way

around, which is why those two factors are linked together in the conceptual model. At the end of

the model we have the migration flows of foreign nationals as dependent variable.

This model does not take in account cultural links, humanitarian migration, climate change and

possible other factors influencing migration because of a combination of practical and theoretical

reasons, which will be explained in the rest of this chapter.

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3.2 Methods

An answer to the research question will be developed by the way of desk research and a mix of

quantitative and qualitative analysis. The three main research fields that are central in this research

are economy, policy and migration. A case selection will be done using quantitative methods. After

that the correlation between the three fields shall also be analysed by a mix of quantitative and

qualitative methods. Collection of data shall be done through desk research. For the economical and

other development related numbers the OECD shall be the main source. This is an organization with

huge and generally standardized and trusted datasets. The findings of the desk research shall be laid

out and statistically tested. A qualitative look into migration policy of selected case countries will

provide further insight into nation specific context.

3.3 Case selection The OECD, with its European background consists of relatively wealthy and more importantly

economically developed countries (OECD, 2018b). The possible case countries will thus all be from

the higher stages of capitalist development. There is a lack of OECD countries selling only primary

goods such as raw oil or metals, instead many rely on a diversified stock of capital intensive goods.

Big OECD oil exporters like in the case of the USA and Norway see a cut of less than 50% for crude oil

or gas exports (OEC, 2018). Making them distinct from classic high GDP but lowly developed

economies such as Qatar and Saudi-Arabia who, while recently announcing change, do still have

more than 50% of their GDP in primary goods. This distinction is very important to make since we are

talking about the capitalist development which in its higher stages relies on profit form added value.

Emerging economies mostly by creating clothes from cotton (secondary goods) and the advanced

economies from the copyrighted design or distribution of said secondary goods (Liodakis, 2005). For

the case selection six OECD countries will be ranked by level of wealth accumulation through global

trade. From this list the two top and two bottom performers will be selected to be analysed in a

qualitative way, on the basis of selecting the most distinct cases. This gives a broad enough view

different countries that perform exceptionally well and those at the bottom within the OECD. The

reason to select four dissimilar countries is because of the similarity between OECD countries

possibly being in conflict with the theory that focuses on global relations between countries that are

in different stages of development. The analysis based on two high and low performing countries

should help give more meaning to the earlier quantitative analysis. Finally addition to the 4 dissimilar

cases, two average performers shall also be taken into consideration and compared to the dissimilar

ones. This to account for anomalies.

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3.4 Plan for implementation research and limitations Starting with some clear limitations, broad nature of migration research forced a choice between

different causes for migration. The choice has fell on a combination of materialistic conditions and

influential policy areas. This means that the research will not cover cultural links or regional events

but rather try to prove a link between migration flows and economic trade next to the existing policy

context. Furthermore the migration data that will be discussed will solely cover foreign nationals

immigrating and emigrating to and from OECD countries. This because of the difficulty in measuring

emigration of non-foreign nationals and the need to demarcate the research topic and prevent it

from becoming too broad. The analysis will be based on a triangle of variables (economy, policy and

migration) and executed in two steps. The first step will start with collecting all necessary data from

the OECD database. OECD countries will be ranked by level of wealth accumulation through trade,

after which a case selection will be done to create a group of dissimilar cases. Case selection will

result in three groups for analysis, two high performing, two average and two bottom performers

when it comes to accumulation of wealth through international trade. The theory partly focuses on

global relations between developed, emerging and developing countries. These are countries with

infrastructures and economies that differ significantly from each other. Sadly a research based on

such a diverse selection of world countries wasn’t possible due to missing and inconsistent data.

With the use of the OECD as source higher level of guarantee can be had on the consistency of the

collected data (standardization). Classically the OECD has been a collection of rather developed and

similar countries, making the extra step of ranking and selecting six countries for a parallel analysis a

necessary one. OECD countries have been chosen because of their wide range of universalized data,

unfortunately third world countries have either unreliable or very much outdated and sparingly

available statistics. The core of the analysis will be the search of the existence of any correlation

between trade and migration within the OECD. Logically this would mean correlation between a

highly developed OECD country and developing third world country would be even stronger in case

of correlation. This is however something that can only be speculated on and falls beyond the scope

of this research. Another caveat is the significant amount of missing data when it comes to three

OECD countries. These ones are Canada, Israel and Mexico and will thus fall outside of this research.

To be specific it is their FDI income data that cannot be retrieved from OECD resources.

Furthermore the OECD (OECD Statline database) mentions that migration data in particular is a very

hard statistic to universalize. Every country has its own definition of who is and who is not a migrant

and in which category they fall. Such conditions should be taken into consideration with this

research. However overall economic data while also having differences in certain metrics, is quite

standardized and can be used without much care. Humanitarian migration will not be a distinct part

in the analysis. This because of the amount of complexity this would add to the research. Migration

data will be collected for the final analysis, in which the combined data will be used to do statistical

analysis. Certain data not available in OECD databases will be collected from the United Nations such

as national population numbers (OECD stopped supplying the data and refers to the UN). These

choices increase the confidence in a research result that is specific and replicable.

15

3.5 Operationalization The operationalization will serve the function of translating the theory in clear concepts that will be

the instruments of the researcher during analysis.

3.5.1 First step analysis: Levels of wealth accumulation through global trade The first step is to rank all the OECD countries in level of wealth accumulation from global trade and

investment after which we move on to look at migration data to see if higher levels of wealth

accumulation through trade coincide with higher levels of migration. By looking at all data from a

relative perspective which means relatively to the size of the national economic production in a

whole year within a country’s borders (GDP).

The operationalization of the performance when it comes to wealth accumulation shall rely on the

following economic metrics:

➔ Current account balance as percentage of GDP

➔ FDI income as percentage of GDP

Account balance measures the left over income from trade in goods and services (exports minus

imports), this in combination with the FDI income will cover most net income a country will

experience from international trade and relations. The metrics shall then be collected per year

starting from 2013 up until the year 2016. The mean of both metrics shall then be used to rank the

countries.

3.5.2 Economic metrics To analyse how much an advanced or emerging economy in reality relies on their position on the

global ladder of trade, certain key metrics need to be discussed that when combined show this in

numbers.

Current account balance as percentage of GDP

This metric measures the incoming money from selling domestic goods and services minus the

imports. Important is to note that if for example Apple assembles an iPhone in China, brings it to the

US at $300 total cost and sells it for $800, the 500$ profit counts for the US GDP but the exports do

not. However, if the iPhone gets sold in China for $500 profit then Apple USA and with that the US

exports increase by $500. This profit is called a service export and adds up with the general export

and trade balance calculations. This example is of course excluding any tax trickery in reality and

serves as an example of how this economic metric is calculated.

FDI income as percentage of GDP

FDI income is calculated on the asset/liability principle as is the new international standard since

2013 (OECD, 2014). Since this is a complex matter the explanation shall be simplified. The assets are

your companies lending to foreign companies, of which the debts are needed to be paid good

performance or bad performance. Liabilities are what your companies lend from foreign creditors,

which your companies have to pay no matter their performance.

To further illustrate this with a known situation: Greece in the Euro crisis of post-2008 had a lot

liabilities towards foreign companies, this while the northern of Europe had a lot of assets in Greece.

When Greece was hit with the crisis, they were very much hurt because of this while northern

European countries had leverage over Greece because they lent money to her companies

(Moravcsik, 2012). Assets will be subtracted from the liabilities to assess if the country’s FDI income

has been more or less risky in the respective period, which as percentages of GDP shows the risk or

safety of the FDI income relative to the total domestic production of a country. If this metric is

negative such as minus 4 percent, then that means you have a four percent (of GDP) risk when a

16

crisis occurs. Your country’s GDP may then drop in full percentages simply because of loss of assets

due to bankruptcies for example.

3.5.3 Correlation analysis

The collected data will be checked for correlations by the method of the Pearson’s correlation test.

The Pearson method shows how significant the variables relate to each other, a rather simple

statistic that doesn’t supply us with much information beyond this. Variables correlate to each other

if the measurement of significance is under 0.05 (two sided). This because in the context of this

research the question is if there is any correlation between economic factors and migration, so not

necessarily a positive or negative correlation. The choice didn’t fell on doing an additional linear

regression analysis due to the limited number of cases that are analysed in this research.

3.5.4 Migration data

As for migration the inflow and outflow of permanent migration shall be collected. Next to the total

in and outflow numbers there is also a distinction possible between humanitarian numbers (asylum

seekers) and other types migration. This shall prove especially useful in this research because of the

data being collected from 2013 onwards and the context of not only the Syrian civil war but also

political unrest in Africa causing an increased amount of humanitarian migration. However taking

that distinction into account would ask for the inclusion of many other factors that also impact the

inflow of asylum seekers and migrants in general such as geographical location. The decision has thus

been made to not make such a distinction in order to limit the size of the research. This limitation is

needed because of the limited scope and the resources available for the conduction of this research.

3.5.5 Economic and policy context

Premature deindustrialization

The concept of premature deindustrialization is the logical result of inequal global trade, with certain

countries taking the lead and preventing less developed economies from industrializing properly. The

developing countries experience a lack in highly skilled jobs, causing the highly skilled layer of their

labour supply to search for work elsewhere. Result is a stream of highly skilled labour to the

developed countries while the developing nations are forced to focus on low level heavy industry or

service sector dealings.

FDI Regulatory Restrictiveness index

The theory showed that areas that opened themselves up for investment also were more receptive

to migration which ended up showing in actual migration flow statistics in Germany (Buch & Toubal,

2009). The FDI regulatory restrictiveness index serves the purpose of indicating the openness of a

country when it comes to inward foreign investment.

For example: Countries in Asia have liberalized their investment regulation, increasing FDI (OECD,

2017). The regulatory index shall be collected from OECD sources and contain data from 2013 up

until the most recently available data. From the four or three years of data the mean will be

extracted and used to rank the countries based on openness for investment. For this index one

means fully restricted while zero means there are nearly no restrictions when it comes to FDI.

Social expenditure

Social expenditure shall be measured as percentage of GDP. This is a conceptualization of social

spending and thus the welfare system in a country but also other supportive spending that is relevant

to migrants trying to build up a new life or for existing residents that are trying to overcome a

difficult stretch in their life (such as unemployment or sickness).

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Migrant Integration Policy Index (MIPEX)

The Migrant Integration Policy Index incorporates more than one hundred policy indicators across all

EU members states and select non-EU OECD countries. It was created to give better insight into

migration and integration policies and to find areas for improvement. The index is used by both

governmental as well as non-governmental actors around the world and sources its information from

trusted sources (MIPEX, 2018b). The index is especially relevant because it measures data of foreign

nationals, covering the same subjects as the collected migration data. The MIPEX data that will be

used in this research covers the following migrant-related policy areas:

Labour market mobility

This area covers the ability of migrants to climb up the social ladder through education, training to

get better job opportunities. It also looks into the support unemployed get through social spending,

support that can help them survive and get out of unemployment. This policy area is relevant

because of the relative high amount of migrants in low paying jobs, being able to grow to higher

paying jobs is thus an important financially but is also seen as an indicator of integration (MIPEX,

2018c).

Education

Education covers the performance of migrants within the education system. This area impact the

labour market mobility of migrants but also their participation rate. Education, naturally, is a gateway

to labour market participation but also integration into the target country’s customs and institutional

systems (Ibid.)

Political participation

This is measured by looking at the share of migrants that is eligible for political participation (voting)

and at the share of those that are not eligible. Political participation is one of the main pillars of

integration next to labour market participation (Ibid.)

Access to nationality

This is defined as the amount of naturalizations per year and the amount of migrants eligible for

naturalization. Naturalizations may be one of the most straightforward ways of ‘integrating’ migrants

into your country by the way of policy by making them full citizens (Ibid.).

Family reunion

This concerns the successful applications aimed at reuniting family and also the amount of migrants

that are married abroad but are not currently living together with their spouse. A high rate of family

reunion can promote integration by making the target country the main focus of family life (Ibid.).

Permanent residence

The permanent residence is measured by taking the share of the migrant stock that has or is able to

get a long term or permanent residence permit. A permanent or long term residence permit can help

in making migrants focus on the target country in a similar manner like family reunion does. An

example of this is a higher rate of active participation as a citizen or otherwise (Ibid.).

Anti-discrimination

The final policy area is measured by the amount of official reports of discrimination on the basis of

ethnicity or religion and the self-reported experiences of discrimination. Discrimination can be a

hindrance to labour market participation and political participation for migrants and slows or even

limits the ability to integrate (Ibid.).

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With this index we cover all of the left over migrant related policy factors that impact migration flows

according to the previously gathered theory. The policy areas in the MIPEX overlap those mentioned

in OECD research on migration policies (2016). The MIPEX will be used to look at the final case

countries in order to have a way of insight into data that goes beyond the scope of the more

quantitative data as collected by the OECD.

3.6 Summary

The central research question is: To what extent does the process of wealth accumulation from

international trade and investment correlate with the migration flows of foreign nationals in and out

of OECD countries?

The hypothesis is that there is some correlation between income from international trade and

investment and the migration statistics of OECD countries. This shall be researched by the way of

quantitative methods combined with desk research to collect all the necessary data. First a case

selection will be done on wealth accumulation through global trade and investment after which a

correlation test will be performed based on the data collected for the case selection. The six case

countries will be the subject of qualitative analysis. This by gathering information around the policy

context and applying the knowledge from the theoretical framework.

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4. Economic findings and case selection In this part of the analysis the concepts of capital accumulated from international trade of good and financial assets (investments) will be used to determine the performance of OECD countries relative to each other. All the economic and migration numbers are collected from OECD’s database (OECD, 2018a) unless stated otherwise. The source years of the data are 2013 up until 2016 and shall be presented in a quick overview of the collected data. After discussing these, ranking lists will be put up for the individual economic factors and a combined one will help us choose six case countries that will be the basis of the second part and the meat of the research.

4.1 Collected account balance and FDI income numbers

The account balance shows the results of trade of goods and services between a country and international trade partners. Exports create an income stream and the imports are then subtracted to end up in the account balance. A positive account balance is thus an indicator of the accumulation of capital within a country.

20

Let’s take a look at the collected numbers:

Country 2013 2014 2015 2016 Average

OECD 32 average 1.70 1.65 2.11 2.18 1.91

Australia -3.39 -3.07 -4.65 -3.30 -3.60

Austria 1.94 2.47 1.73 2.48 2.15

Belgium -0.33 -0.87 -1.03 -0.60 -0.71

Chile -4.04 -1.65 -2.26 -1.40 -2.34

Czech Republic -0.54 0.19 0.24 1.57 0.37

Denmark 7.76 8.92 8.78 7.32 8.19

Estonia 0.53 0.79 1.85 1.97 1.28

Finland -1.95 -1.54 -0.73 -0.74 -1.24

France -0.51 -0.96 -0.37 -0.75 -0.65

Germany 6.71 7.44 8.91 8.52 7.90

Greece -2.04 -1.63 -0.23 -1.26 -1.29

Hungary 3.77 1.47 2.71 6.17 3.53

Iceland 5.72 3.83 5.17 7.42 5.54

Ireland 2.14 1.64 10.90 3.96 4.66

Italy 0.99 1.91 1.48 2.54 1.73

Japan 0.90 0.79 3.10 3.82 2.15

Korea 6.21 5.98 7.66 7.05 6.73

Latvia -2.76 -1.82 -0.44 1.51 -0.88

Luxembourg 5.27 5.16 5.08 5.09 5.15

Netherlands 9.76 8.49 6.32 8.05 8.15

New Zealand -3.08 -3.10 -2.83 -2.15 -2.79

Norway 10.22 11.00 7.98 3.99 8.30

Poland -1.27 -2.08 -0.57 -0.53 -1.11

Portugal 1.58 0.08 0.12 0.59 0.59

Slovak Republic 1.87 1.15 -1.76 -2.16 -0.23

Slovenia 4.38 5.79 4.54 5.53 5.06

Spain 1.52 1.08 1.16 2.26 1.50

Sweden 5.23 4.54 4.53 4.27 4.64

Switzerland 11.61 8.53 11.11 9.85 10.28

Turkey -6.69 -4.67 -3.73 -3.84 -4.73

United Kingdom -5.15 -4.93 -4.91 -5.22 -5.05

United States -2.08 -2.08 -2.24 -2.31 -2.18

The OECD average shows an overall two percent growth in capital with exports as origin, so as a

whole the OECD subtracted quite some capital from international trade. This happened increasingly

as the recovery from the 2008 financial crisis got more and more momentum.

The results for individual countries do not always show that positive outlook and great varieties exist.

Important is to keep in mind that income from financial assets is not taking in account here, some

countries may focus on getting more income from the trade of goods while others specialize in

financial assets. Some conclusions can be made when the data is put next to economic complexity

data (Economic Complexity Index) showing the built up of different world economies (OECD, 2018).

The top performing countries such as Denmark, Germany and Switzerland trade in capital intensive

goods. Norway is an exception where the raw products they sell still result in a positive account

balance compared to Chile, which is big in mining. This can be explained by the diversification of the

economy that happened in Norway compared to Chile. Norway sells capital intensive goods next to

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their raw products while Chile only has simple agricultural products next to their more valuable raw

material exports. A good account balance in this case can thus be a safe indicator of a mature

industrial and services sector, an important thing to keep in mind when we start to take migration

and policy into the calculation. High level industry and services require a good inflow of highly

educated talent or cheap labour to compliment the increased demand for labour. FDI income

presents us the result (net income) of the international exchange in financial assets while excluding

goods. This means that this indicator is essential to have next to that of the account balance (goods

and services) when wanting to summarize all capital accumulation happening within an economy

from international markets.

Country 2013 2014 2015 2016 Average

OECD 32 average -0.20 -0.49 0.14 0.23 -0.14

Australia -0.93 -0.73 -0.85 -0.90 -0.85

Austria 1.20 1.27 0.29 0.61 0.84

Belgium -1.23 -1.27 -1.50 -0.40 -1.10

Chile -4.50 -3.52 -2.78 -2.68 -3.37

Czech Republic -6.74 -6.98 -6.75 -6.82 -6.82

Denmark 1.96 2.35 2.52 2.11 2.23

Estonia -4.64 -4.82 -4.38 -4.45 -4.57

Finland 0.86 1.70 1.41 1.69 1.42

France 1.84 1.88 1.78 1.72 1.81

Germany 1.49 1.21 1.60 1.29 1.40

Greece 1.09 0.33 -0.09 0.44

Hungary -3.85 -5.44 -6.30 -4.60 -5.05

Iceland 2.25 1.26 1.50 2.30 1.83

Ireland -13.21 -12.19 -18.22 -14.01 -14.41

Italy 0.60 0.71 0.03 0.20 0.39

Japan 1.31 1.52 1.65 1.48 1.49

Korea 0.25 0.13 0.01 -0.01 0.09

Latvia -3.25 -3.16 -3.69 -3.82 -3.48

Luxembourg 13.59 15.42 47.93 45.01 30.49

Netherlands 4.84 -3.63 -3.66 -3.99 -1.61

New Zealand -3.25 -3.30 -3.06 -2.54 -3.04

Norway -1.21 1.05 0.52 1.19 0.39

Poland -3.63 -3.66 -3.99 -3.76

Portugal -0.17 -1.06 -1.54 -1.55 -1.08

Slovak Republic -3.07 -3.11 -4.65 -3.96 -3.70

Slovenia -2.38 -2.47 -2.43

Spain 0.80 0.81 0.74 0.69 0.76

Sweden 2.39 2.19 1.44 1.25 1.82

Switzerland 3.99 2.44 4.47 3.01 3.48

Turkey -0.36 -0.22 -0.39 -0.34 -0.33

United Kingdom 1.59 1.12 0.48 -0.08 0.78

United States 1.70 1.59 1.47 1.39 1.54

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In these results it is instantly visible that financial investment in the OECD is lagging, this while the

OECD had a positive net income from the trade of goods and services. This might be due to the fact

that the OECD is a collection of relatively developed economies with less growth potential compared

to the rest of the world market, like the booming markets in China and India. The case of economic

specialization can still make specific OECD economies rather attractive for direct investment of

financial assets such as Luxembourg and Switzerland who both are known to be big destinations of

wealthy individuals. It is however important to not equate these results with that stereotype. The

third in place, Denmark is also doing very well and that country is not exactly known for its low taxes.

The high FDI income results of these countries is to be linked with the value of corporate assets that

firms in those countries hold (Isakse, Kramp and Klausen, 2016). Luxembourg, Swiss and Danish

companies hold assets in firms that deal with highly capital intensive goods elsewhere in the world. It

is thus more likely that these countries hold a lot of expensive patents, R&D companies and

international relations on the high end of the scale when it comes to internationally attractive

industries.

4.2 Rankings On the following page there is an overview of the overall results and the final place that countries ranked when adding up the results from the account balance and FDI income data that was collected. The majority of the results have already been discussed in the previous pages and also in the overall ranking a similar story seems to present itself. There isn’t a case of a country that has an exemplary score in one factor without being at least decent in the other factor. This is because successful trade in goods and services will eventually result in the increase of FDI income due to the attractive nature of the investment opportunities in that result from profitable trade endeavours in the export market.

As final part of this part of the research the following case countries have been decided:

Top performers: Switzerland, Denmark

Middle of the bunch: Finland, United States of America

Bottom performers: Chile, New Zealand

The decided cases are a collection of vastly differing economies in a diverse collection of state

structures and context. There are countries small in numbers and size like Finland and more dense

ones like Chile and the politics go from social democratic to free market liberalism. Economically we

have countries that focus on raw materials, financial assets but it was also essential to not leave out

the world’s biggest single country economy: The United States of America. Especially with its position

as holder of the world’s leading trade currency. This gives us a robust fundament for the qualitative

part of the study where we dive more in depth in the build-up of migrant flows and policies in the

selected countries.

23

Country Overall ranking Account balance ranking

FDI income ranking

Switzerland 1 1 2

Denmark 2 3 3

Luxembourg 3 8 1

Iceland 4 7 4

Germany 5 5 10

Sweden 6 11 5

Norway 7 2 15

Japan 8 14 8

Korea 9 6 17

Austria 10 13 11

Netherlands 11 4 22

France 12 21 6

Spain 13 16 13

Italy 14 15 16

Slovenia 15 9 23

Finland 16 25 9

United States 17 27 7

Portugal 18 18 20

Greece 19 26 14

Hungary 20 12 30

Ireland 21 10 32

Belgium 22 22 21

United Kingdom 23 32 12

Estonia 24 17 29

Slovak Republic 25 20 27

Australia 26 30 19

Latvia 26 23 26

Turkey 28 31 18

Czech Republic 29 19 31

Poland 30 24 28

Chile 31 28 25

New Zealand 32 29 24

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5. Findings With the case selection based on capital accumulation through international trade we have

discovered the performance of countries when it comes to this part of the equation. Two other

important components that flowed from out of the research question and theoretical framework are

migration and policy. In the following chapter we are going to discuss each of these respectively to

finally end up with a full triangle of trade performance, migration and policy that will help us shape

an answer to the research question and reach a conclusion. In the Appendix (9.2) for the part of the

dataset that could not be included in the findings.

5.1 General overview case countries Before jumping into the migration numbers we are going to start with a general overview of the

countries at hand to supply us with a backdrop to the coming analysis and discussion. All numerical

data is taken from the base year 2013 and it sourced from the OECD database while the additional

info is sourced from the database of the Massachusetts Institute of Technology’s database for the

Economic Complexity Index that in itself will also proof useful further on in the analysis of these

countries.

Let’s first start with the average population size, GDP per capita and percentage of foreign born

population in the OECD:

Population: 37.74 million

GDP per capita: $39008.86

Percentage foreign born population: 12.69 million

Top performers: Switzerland, Denmark

Switzerland Denmark

Population (million) 8.14 5.61

Percentage foreign born population

28.30% 8.48%

GDP per capita $60108.54 $46742.94

Switzerland and Denmark are both relatively small population countries that are quite well off. The

percentage of foreign born population is remarkably high in Switzerland with its 28.30%, Denmark

sits on the half of the OECD average. When it comes to GDP per capita both sitting comfortably in the

top ten of the OECD. Switzerland’s biggest export products are chemical products like medicine and

Gold, both totalling to 50% of their exports. Danish exports mostly consist of medicine and electrical

appliances. Both countries have big specific industries that are supported with a diversified variety of

other smaller exports. This makes them quite tolerant to dips in individual export markets.

25

Middle of the bunch: Finland, United States of America

Finland United States of America

Population (million) 5.4 316.5

Percentage foreign born population

5.59% 13.08%

GDP per capita $41293.29 $53016.29

With Finland and the United States of America not a more distinct duo of countries could have been

chosen as the ‘middle of the bunch’ performers when it comes to capital accumulation from

international trade. Finland with its tiny 5 million residents doesn’t even come close to the US’s

biggest cities, last mentioned has well above 300 million residents. This is also reflected in the

percentage of foreign born where the United States more than doubles that of Finland. Finally GDP

per capita numbers show them both to perform above average compared to their OECD peers.

Finland’s exports consist mostly from electrical appliances, paper and raw earth materials while the

US combines heavy industry products like cars and aircrafts with chemical produce. These two

countries do show something than can be called a trend where big industries are supplemented with

smaller, more varied industries.

Bottom performers: Chile, New Zealand

Chile New Zealand

Population (million) 17.63 4.44

Percentage foreign born population

2.52% 22.41%

GDP per capita (2013) $22352.53 $36074.21

The last two case countries are Chile and New Zealand, both under the OECD average when it comes

to population numbers but with Chile having significantly more than New Zealand. What is the other

way around are the foreign born population numbers that show almost a quarter of New-Zealand to

be foreign born. With these two countries we also have two representatives of the below-average

GDP crowd within the OECD.

With Chile and New Zealand we see quite a difference when it comes to exporting industries

compared to the other four countries. Both of these bottom performers deal in either simple

secondary produce (Cheese, Wine) and primary produce like wood or raw earth materials. The

supplementing export industries are also far less varied with these two countries, making them more

vulnerable than the others for economic downturns in their specific export markets.

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5.2 Migration

The migration numbers are sourced from the OECD database and include the average inflow and

outflow of the selected case countries from 2013 up until 2016. The numbers are shown in absolute

numbers and relative to the respective country’s population in 2013. The choice for 2013 as a base

number to divide the migration data is based on the availability of the population statistic. The years

2014 up until 2016 had too many countries missing data and using different base years per country

has been deemed unfavourable due to the inconsistent nature of the prospective analysis that would

result from this. Another note is for the probability that the inflow numbers have been inflated by

inflow of asylum seekers, something to keep in mind. Due to the realities of such asylum inflows in

the current age, it was decided not to split the numbers in separate asylum and non-asylum

migration parts.

Switzerland Denmark Finland USA Chile New Zealand

Inflow average

145319.25 (1.79%)

53520.19 (0.95%)

24052 (0.44%)

1060451.75 (0.34%)

106983.33 (0.61%)

78191.375 (1.76%)

Outflow average

72571 (0.89%)

30082.50(0.54%) 5965.50 (0.11%)

- - 22559 (0.51%)

The numbers show not many surprising results with the previously discussed percentage of foreign

born population in mind, with Switzerland and New Zealand leading the inflow of migrants.

Interesting is the low inflow into the United States of America, relative to their number of foreign

born residents. Putting these numbers next to the economic numbers alone will not be sufficient to

explain what we are seeing here, for that a look into the policy context is needed.

27

5.3 Policy

This part of the findings chapter revolves around the third and last point of the triangle namely

policy. For this part we have three variables that show the openness for investment (FDI index), the

government support for the vulnerable in society (social expenditure) and finally the level of

integration supporting policies (MIPEX).

Switzerland Denmark Finland USA Chile New Zealand

FDI restrictiveness index average

0.08 0.05 0.02 0.16 0.13 0.30

Social expenditure in percentage of GDP average

19.45 28.88 30.25 18.98 13.99 19.44

MIPEX (2013) 46 55 71 62 - 70

The findings of the FDI restrictiveness index scores teach us that Finland and Denmark are relatively

open for investment. Part of the reason behind their score might also be their participation within

the European Union’s internal market. The fact that New Zealand is an Island nation does also affect

its possibilities to open up for investment as well as other countries that have direct neighbours

through land. Denmark and Finland lead in social expenditure while Chile stands far behind even the

second lowest expenditure of the USA. The MIPEX scores of Finland and New Zealand are the highest

while Switzerland has the lowest. Chile’s MIPEX was not available.

Family reunification and skilled migration

The theory stressed the fact that family reunification and skilled migration are getting more and

more important as gates for migration inside OECD countries. In the following pages the found

examples of regulation on these migration areas are laid down per case country

28

Switzerland

Family reunification for third country nationals in Switzerland is restricted to only spouses and

children. The law does allow for a more long term settlement permit after a residency in Switzerland

for an uninterrupted time of at least five years (CH, 2018b). Switzerland’s close connection to the

European union means that labour migrants coming from the EU/EFTA experience very lenient

regulations ‘merely’ requiring one to have multiple scientific qualifications or when one comes for

seasonal work. This is very different from those that are from third-countries (outside of EU/EFTA)

who have to adhere to strict rules and quotas. The prospective employer has to apply for the

employees’ visa and can only be accepted when ones arrival is in the general economic interest and

no Swiss or EU/EFTA candidate with comparable qualifications is available. Even the migrant has to

have multiple scientific degrees and/or professional experience (CH, 2018a).

Denmark

Danish government publication on migration and integration reflect their MIPEX score when it comes

to family reunification. Only spouses of 24 years or older and minor children qualify for most cases.

Overall Denmark allows for family reunification of spouses, children. Parents only granted in cases of

a minor that has been granted asylum and in that case only if the parent migrating would serve as

beneficial to the child (The Danish Immigration Service, 2018a). Visas based on being ‘other family’,

which means falling outside of the previously mentioned categories, is technically possible but rarely

granted. Skilled migration to Denmark is fully based on having exceptional qualities that the country

is in need of having. This is characterized by sector specific requirements, minimum salaries (low

payed jobs are a no-go) or exceptional educational performance (The Danish Immigration Service,

2018b).

Finland

The MIPEX data suggests that Finland’s family reunification regulation is lenient. This is reflected in

government sources where both Finnish citizens as well as non-citizens are eligible for certain family

reunification schemes. Though parents are not included, the biggest requirement set by the Finnish

government is the fact that the applicant him or herself (the person migrating) should apply for

family reunification and that the Finland resident has enough financial capacities to support their

family member (Ministry of the Interior of Finland, 2018a). Finnish labour migration for non-EU

citizens allows for students that have completed a degree in Finland to search for employment. For

non-students the residence permit regulations are relative to the type of work, with rare and

exceptional skills being valued more (Finnish Immigration Service, 2018b).

USA

Family reunification in the United States of America is relatively expansive with spouses, children,

parents and siblings being eligible for a green card. Certain age requirements apply for the US citizen

that is applying for reunification, with most set at 21 years old (USCIS, 2018). The US has to ways for

skilled based migration, one is based on educational performances for students and the other is

employment based. The educational visa for students has as biggest obstacle is getting a

confirmation of a place in a US based educational institution and proof of strong ties with your home

country (Workpermit.com, 2018a). This to ensure your return at the end of your studies. The

employment based visas base themselves on either extraordinary abilities or capital holdings (such as

rich investors). Exceptions for those without exceptional abilities, capital holdings or connections to

important institutions are available in the case of permanent US employment offers

(Workpermit.com, 2018b).

29

Chile: Chile does allow for family reunification but the administrative capabilities of the government

are quite lacking in this regard (Economist, 2018). An example is the fact that the IOM had to

negotiate proper channels for Haitian migrants to be able to supply applications for reunification of

close family (spouses, children) (IOM, 2018). There are special requirements based on criminal

records and health concerns such as infectious diseases (Ibid). In the time period of this research

(2013-2016) it was possible to travel to Chile on the basis of a tourist visa and find work inside the

country before applying for a longer term work visa (Economist, 2018). When it comes to labour

migration the government of Chile changed its policy to be more selective. It was made impossible to

apply for a work visa while residing inside the country on the basis of a tourist visa. Currently people

have to apply for work visas outside of the country, with more lenient distribution of visas to highly

skilled workers or students (Ibid).

New Zealand

While long term visas are not possible for extended family such as parents or grandparent, New

Zealand does offer long term visas for partners and children. These rules apply for both New Zealand

citizens as well as those residing inside the country on the basis of a long term visa (Ministry of

Business, Innovation & Employment, 2018a). New Zealand adopted a point based system when it

comes to skilled migration. With points given for simply being younger than 55 years old, speaking

English to having recognized qualifications and experience in skilled employment. Comparable to

other discussed case countries, having an offer from an employer greatly eases the migration process

(Ministry of Business, Innovation & Employment, 2018b).

5.4 Sub conclusion The migration numbers show that the country with the highest GDP per capita, Switzerland and the

one with the lowest GDP per capita, New Zealand both lead when it comes to inflow and outflow of

migration. This almost rules out a correlation between GDP per capita and migration flows when we

simply look at the six case countries. The policy data has both Denmark and Finland performing really

well while New Zealand mostly thrives when it comes to the migration-related policy that is collected

in the MIPEX. Examples of family reunification and skilled migration regulation in the case countries

showed a mix of very strict and lenient systems depending on the country. The findings ask for

further analysis based on the collected theory in order to find patterns that may not be recognized

from the collected data alone.

30

6. Analysis The analysis will start with SPSS statistical look on the 32 OECD countries and the collected data

which will be analysed by means of a Pearson’s correlation analysis. After this a look will be done on

the six case countries and the collected MIPEX data (MIPEX, 2018a) which will be done with the rest

of the findings and the results of the correlation analysis in mind. This will end with a sub conclusion

before moving on to the final chapter of this research.

6.1 SPSS analysis Before judging all the findings based on the collected theory it is very important to first test the

collected data for their statistical relevance, which would then help either support possible outcomes

from the analysis or add nuance to taken conclusions. For this it is not possible to simply focus on the

six case countries. As such data for all thirty two base OECD countries will be analysed over four

years. This supplies us with enough cases to have reliable results from the calculation.

First the task is to see if the collected data is normally distributed. A selection of the normal Q plots

shown below give a more optimistic view than the detruded plots which have quite some

irregularities and lead to the conclusion that the numbers are not normally distributed. Part of the

reason for this might be that the selected variables come from the OECD, which might already be a

selection of countries with certain specific features or simply because the amount of cases is not high

enough. This means that ANOVA tests are out of the question. Luckily the Pearson’s correlation test

does not assume normality and may be used to see if there is any correlation between the collected

numbers. For the Pearson’s test the assumption that the relations between the variables is linear has

been confirmed, the plots for this and the results from the Pearson’s test are shown on the following

pages.

31

32

33

Correlations

MigrationInflow MigrationOutflow AccountBalance FDIincomeGDP FDIindex SocialExpenditure MIPEX

MigrationInflow Pearson Correlation 1 .361** .262** .539** .228** .093 .307

Sig. (2-tailed) .000 .003 .000 .010 .315 .093

N 128 128 126 125 128 120 31

MigrationOutflow Pearson Correlation .361** 1 .360** .266** .088 -.072 .122

Sig. (2-tailed) .000 .000 .003 .325 .435 .513

N 128 129 126 125 128 120 31

AccountBalance Pearson Correlation .262** .360** 1 .167 .035 -.023 .151

Sig. (2-tailed) .003 .000 .065 .699 .802 .418

N 126 126 126 123 126 118 31

FDIincomeGDP Pearson Correlation .539** .266** .167 1 -.085 -.034 .172

Sig. (2-tailed) .000 .003 .065 .344 .716 .382

N 125 125 123 125 125 117 28

FDIindex Pearson Correlation .228** .088 .035 -.085 1 -.187* -.082

Sig. (2-tailed) .010 .325 .699 .344 .041 .661

N 128 128 126 125 128 120 31

SocialExpenditure Pearson Correlation .093 -.072 -.023 -.034 -.187* 1 .403*

Sig. (2-tailed) .315 .435 .802 .716 .041 .030

N 120 120 118 117 120 120 29

MIPEX Pearson Correlation .307 .122 .151 .172 -.082 .403* 1

Sig. (2-tailed) .093 .513 .418 .382 .661 .030

N 31 31 31 28 31 29 31

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

34

The SPSS results from the Pearson’s correlation test show firstly that the economic factors all have a positive

correlation with both migration inflow as well as outflow. The strongest correlation is between the inflow of

migrants and the income a country experiences from foreign direct investment. This is in line with the theory where

the highest tier countries are those that attract the most investment while at the same keeping significant portions

of the profits that resulted from the invested foreign money. What is also in line with the theory is how that the

increase in trade of goods and services in between countries increases the migration. We can’t measure the specific

effects that trade one the internal flows of migration two pairs of countries had, though we can see that both the

inflow and outflow of migration increases when the account balance of a country is high. Especially interesting is the

increased inflow of migration when a country shows itself to be relatively open for investment (FDI restrictiveness

index), this is an effect that is not significantly present when it comes to the outflow of migration. While it is rather

easy to conclude that migration towards a country increases the opener a country shows itself to be, it is harder to

explain why such an effect is not present when it comes to the outflow of migration. This while a dual-sided effect is

to be seen in the other economic factors. One explaining is best done with an example:

Country A (open for investment)

Country B (closed for investment)

Country C (closed for investment)

In this example the open country might see an increase in the investment towards them and with that an increase in

the positive account balance and FDI income. Since a return investment by country A towards countries B and C is

not possible, migration towards those countries will stay the same. This might explain why the outflow for country A

will not see a significant effect due to opening up the markets while it will see an inflow of migration.

When it comes to the other policy variables next to the openness to investment we can see that there is no direct

significant correlation with the migration variables. However one of the things that can be observed is the indirect

effect on the significant variable FDI restrictiveness index, namely that of social expenditure and even more indirectly

that of MIPEX. MIPEX positively affects social expenditure, logically following from the fact that good integration

policies require some form of public investment. This by a sort of chain reaction also negatively affects the openness

for investment. A reason for this could be that countries that invest more in social expenditure have higher taxes to

accommodate for that. Higher taxes means being less ‘open’ to foreign investment in economic terms since the

taxes form a barrier for capital investors. This concludes the SPSS analysis where we can see that the main focus for

the correlation lies in the economic variables. In the next part of the analysis we are going to discuss the six case

countries to give a more close up insight beyond statistical correlations.

35

6.2 Policy analysis The benefit of being able to zoom in six case countries is that we can have an extra look on the individual scores of the migration integration index and see how individual countries score on individual metrics. The MIPEX overall score as shown in the findings chapter consists of eight different policy fields that all affect both migration as well as integration. They will be shown first (source year 2013) and then and elaborated on by taking the other findings and theoretical knowledge that has been discussed in the previous chapters.

Country Labour market mobility

Family reunion

Education Political participation

Permanent residence

Access to nationality

Anti-discrimination

Switzerland 59 48 42 58 51 32 31

Denmark 79 42 47 58 74 42 46

Finland 80 68 60 79 70 63 74

USA 64 66 60 36 54 61 90

Chile

New Zealand

67 68 66 74 64 71 79

Interesting are the metrics concerning anything that facilitates long term stay like labour market mobility,

permanent residence, political participation and access to nationality. Finland has good scores there and also sees a

low amount of migration outflow however another country like Denmark that also scores high on these points does

not experience the same low amount of migration outflow of foreign nationals. This is where the theory comes in

handy, from the theory we know that the two most impactful regulation areas are family reunification and labour

mobility. On both levels Denmark has shown to have rather restrictive regulations, with skilled based migration

aimed at highly skilled and high earners while family reunification is relatively restrictive. Finland is relatively lenient

when it comes to family reunification but very selective on labour migration, same applies for Switzerland. One of

the reasons for this might be that both Denmark, Finland and Switzerland are either in the EU or have close ties with

the EU. This means that they enjoy a labour supply that is already quite substantive based on EU’s openness when it

comes to intra-EU labour migration. The United States and New Zealand respectively have many Visa options or a

forgiving point system that in no circumstance becomes as strict as the European cases. This is explained by both

their lack of an alternative method of supplying their economies with labour as well as their existing experience with

migration flows. This while Chile did not have a streamlined immigration system in place, where theoretical rights on

migration where blocked by an administrative reality where little resources were put into creating a more

streamlined system. Something that has changed recently where they have shown to have implemented a more

selective labour migration system comparable to the other case countries. Overall the conclusion the OECD made in

their 2016 report ring true in the findings here. OECD countries are more and more moving towards creating

selective immigration system that focus on supplying the country with specific types of skilled workers that the

economy lacks, with countries like Denmark even having sectoral policies in place. With certain sectors in the

national industry having different requirements than others. A concept that was previously suggested as a good

policy option by the OECD themselves (OECD, 2016).

36

6.3 Open economies, selective migration The conclusion on the analysis can be that the economic factors Current Account Balance and FDI income are the

strongest when it comes to correlating with the migration in and out flow from the selected OECD countries. Of the

three policy variables it was only the FDI restrictiveness index that also correlated significantly. A policy factor rather

closely connected to international trade relations and even then it only was significantly correlating with the

migration inflow. Something that could be logically explained. It would seem that policy facilitates economy, which in

itself is the biggest predictor of migration flows. While causation has not been proven, the combination of open

economies being successful and the importance and further development of selective migration policies do show a

certain pattern. Globalized economies on the world market are unequal in their level of development which the

theory has shown to limit the ability of developing nations to industrialize. Highly skilled workers from developing

nations have better job opportunities in the developed nations and aspire to migrate. At the same time developed

nations develop more open but selective migration policies that are focused on attracting and accepting those same

highly skilled workers. The increasing selectivity of migration policy in means that the ability of migrants to stay for

the long term are becoming more and more in the interest of the target countries themselves. The move away from

low skilled migration, as is the case in a globalized world where that level of work can be outsourced, removes the

need to dispose of workers when the national economic conjecture asks for it. Migrants that entered based on

sectored, skilled migration regulations will have more stable employment in rather diversified and specialized

industries. Industries that produce products and services that do not only serve the national economy but also

internationals clients and attract international investors. Sectored skilled migration also serves the ideal of

specialized economies in a way that it allows for migration policy to shape the labour market in a way that internal

educational or labour market policy cannot. Subsidies and promotional campaigns can be used to push home-grown

students and workers to educate and move themselves towards the needy sectoral industries. It is hard to force

people into a specific industry however, which either means that persons become unemployed or emigrate to a

country with better employment opportunities on that front. From the theory it is known that the OECD countries’

emigration policies are based on a ‘hands-off’ approach. With a more streamlined inflow of highly skilled and needed

workers into future specialized economies gives countries the ability to evolve emigration policy into being more

encouraging for resident that do not fit the current economic needs. On the other side keeping your economy more

diversified is also eased when the inflow of highly skilled migrants becomes more commonplace. Such a steered way

of policy can be far away for some when we take the lacking political participation, access to nationality and anti-

discrimination laws. The question if scoring lacklustre on these areas can impact long term stay of foreign nationals.

With that we steer almost into the discussion, something that will be continued in subchapter 7.2. This is a sign that

enough has been discussed to answer the research question in the conclusion.

37

7. Conclusion and discussion With the conclusion and discussion we have arrived at the final part of the research. We shall first start with a recap

of the research question:

To what extent does the process of wealth accumulation from international trade and investment correlate with the

migration flows of foreign nationals in and out of OECD countries?

7.1 Conclusion

From the observed 32 OECD countries it were Switzerland and Denmark which topped the ranking when it comes to

the accumulation of wealth through international trade. The worst performers were Chile and New Zealand while

Finland and the United States of America were selected as the two medians. The case selection was a healthy mix of

big and small countries (population wise) that performed above and below average when it comes to GDP per

capita. Also the migration and policy numbers showed that we were dealing with a diverse selection of countries and

the findings alone didn’t help to show a discernible pattern of set up a clear conclusion. Only after analysis was it

clear that the triangular relation between Economy, Migration and Policy seemed to heavily focus on the first two.

Policy ended up being merely a facilitating factor in this thesis. With the strongest variable being the openness to

investment, this directly affects the position of a country in the global economic markets but with that also the

global migration markets.

The findings broadly reflect what has been theorized with the hypothesis. There is a positive correlation between

wealth accumulation through international trade and migration of foreign nationals. For there to be wealth the

needs to be income from trade or investment and as a by-effect migration occurs. Policy context can indirectly affect

these economic factors and thus only correlate with migration in a very indirect manner. At the same time policy

directly focused on migration or policy that indirectly affects migration has also shown to be impactful in their own

way. Looking at specific examples of family reunification and skilled migration showed that both Switzerland and

Denmark, the countries which ranked highest in the case selection, have very strict regulations when it comes to

these two areas. Though they lag behind the others when it comes to political participation, access to nationality and

anti-discrimination. Something that can cause problems if their economies become more and more reliant on

foreign high skilled labour. This research did not look at trade deals, it could be that open and a more inclusive

migration policy is a factor in making proper trade deals that then result in good economic performance. Overall the

biggest take from this research seems to be

• Wealth accumulation correlates with migration flows of foreign nationals in and out of OECD countries. In

other words materialistic realities on the world stage correlates with migration.

• Policy measures can realistically be seen as impactful when it comes to these migration flows and especially

the ability of countries to hold on to the inflow of selected, highly skilled migrants.

Especially international trade happened to have such a heavy correlation with migration flows. It has to be said that

the research was limited in scope and that having the exactly right combination of variables and reliable data has

38

proven to be difficult. Not only because of the fact that proper and extensive data gathering can take years (as

shown in the research of Helbing and Kalkum, 2018) but also because of the nature of migration data. Most data is

based on foreign nationals. Aside to that every country has their own way of collecting data and definitions can differ

per state, not only within the OECD but even within the European Union. With that we move onto the discussion.

7.2 Discussion A big regret from this research is the lack of incorporation of a full analysis of the dependency between highly

performing and worse performing countries when it comes to wealth accumulation. It could be simply that the lack

of success from some third world countries also impacts the migration towards them, which would be an interesting

discovery. Especially in combination with the theory of de Haas where there seem to be an increase in migration

flows (emigration) when a country reaches the first stages of economic development. Another factor that has been

missed in this research is that of regional performance. The high migration numbers when it comes to Switzerland

and New Zealand might also be because of them having a relatively high GDP per capita compared to their

neighbours. One might mention that also South-Korea and Japan have high GDP per capita numbers but both policy

and cultural factors can explain why they are generally known to have a lower amount of incoming migration. Having

a more robust inflow of highly skilled migrants or keeping them residing inside the country for the long term might

also be of interest of these kind of technological powerhouses as will be clear at the end of this paragraph. The goal

of this research was to take a step into discovering the link between success in trade and migration in order to

influence the debate going on where highly developed countries have been increasingly trying to dampen migration

flows. The question is and stays if this is a realistic goal if they also wish to be economically successful on the

international markets. Having to swallow my own pride, there seems to be nuances to this initial impression. Firstly

it is not that current migration policies are more restrictive per se. It is more that they are becoming more and more

selective and streamlined which actually opens up new economic possibilities. Due to premature deindustrialization

in developing nations, highly skilled labourers from developing nations will desire to move to developed nations with

more opportunities. Steered economic policy becomes possible without forcing the native population to choose a

specific educational direction or career path with this increasing impulse of highly skilled labour. Developed

economies, as we now know, are more diversified than developing economies and deal in capital intensive goods

and services (asking for highly skilled workers). Diversification has been a long economic strategy in order to make

one’s economy more robust for economic downturns in specific sectors. Other countries have more specialized

economies, for example when it comes to the technological sector such as the previously mentioned countries of

South-Korea and Japan. Streamlined selective migration might make the continuations of the economic success

more easier to achieve for both kind of economies. Attracting migrants is only half the work though and the

retention of foreign nationals relies on other factors such as labour mobility, political participation or levels of

discrimination. It is here that the challenge lies, not only when it comes to policy technicalities but also when it

comes to cultural mind-set. Low skilled migration traditionally is highly conjectural in its nature and labourers are

expected to be there when they are in need and leave when they are not needed. Highly skilled migrants staying in

dire times can serve the long term ambitions of policy makers in the shaping of a more designed economic landscape

but cause friction with the native population. Being outcompeted by highly skilled migrants can cause backlash from

native ‘losers’ on the labour market, on the other side discrimination causing an overrepresented amount of

migrants to become unemployed will also lead to problems. One thing is certain though and that is that migration is

a reality that cannot be escaped if one desires to be successful on the international stage. Materialistic realities have

consequences and policy is slowly adapting to that reality, the question is if cultural mind-set will see the same

change?

39

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9. Appendix

9.1 OECD Countries All 32 used OECD countries and their official OECD abbreviations

OECD countries

Australia (AUS) Austria (AUT) Belgium (BEL) Chile (CHL)

Czech Republic (CZE) Denmark (DNK) Estonia (EST) Finland (FIN)

France (FRA) Germany (DEU) Greece (GRC) Hungary (HUN)

Iceland (ISL) Ireland (IRL) Italy (ITA) Japan (JPN)

Korea (KOR) Latvia (LVA) Luxembourg (LUX) Netherlands (NLD)

New Zealand (NZL) Norway (NOR) Poland (POL) Portugal (PRT)

Slovak Republic (SVK) Slovenia (SVN) Spain (ESP) Sweden (SWE)

Switzerland (CHE) Turkey (TUR) United Kingdom (GBR) United States (USA)

Canada, Lithuania, Mexico and Israel are missing due to missing usable FDI income data.

43

9.2 Data sets

Current Account balance as part of GDP

Country 2013 2014 2015 2016 Average Ranking

Australia -3.39 -3.07 -4.65 -3.30 -3.60 30

Austria 1.94 2.47 1.73 2.48 2.15 13

Belgium -0.33 -0.87 -1.03 -0.60 -0.71 22

Chile -4.04 -1.65 -2.26 -1.40 -2.34 28

Czech Republic

-0.54 0.19 0.24 1.57 0.37 19

Denmark 7.76 8.92 8.78 7.32 8.19 3

Estonia 0.53 0.79 1.85 1.97 1.28 17

Finland -1.95 -1.54 -0.73 -0.74 -1.24 25

France -0.51 -0.96 -0.37 -0.75 -0.65 21

Germany 6.71 7.44 8.91 8.52 7.90 5

Greece -2.04 -1.63 -0.23 -1.26 -1.29 26

Hungary 3.77 1.47 2.71 6.17 3.53 12

Iceland 5.72 3.83 5.17 7.42 5.54 7

Ireland 2.14 1.64 10.90 3.96 4.66 10

Italy 0.99 1.91 1.48 2.54 1.73 15

Japan 0.90 0.79 3.10 3.82 2.15 14

Korea 6.21 5.98 7.66 7.05 6.73 6

Latvia -2.76 -1.82 -0.44 1.51 -0.88 23

Luxembourg 5.27 5.16 5.08 5.09 5.15 8

Netherlands 9.76 8.49 6.32 8.05 8.15 4

New Zealand -3.08 -3.10 -2.83 -2.15 -2.79 29

Norway 10.22 11.00 7.98 3.99 8.30 2

Poland -1.27 -2.08 -0.57 -0.53 -1.11 24

Portugal 1.58 0.08 0.12 0.59 0.59 18

Slovak Republic

1.87 1.15 -1.76 -2.16 -0.23 20

Slovenia 4.38 5.79 4.54 5.53 5.06 9

Spain 1.52 1.08 1.16 2.26 1.50 16

Sweden 5.23 4.54 4.53 4.27 4.64 11

Switzerland 11.61 8.53 11.11 9.85 10.28 1

Turkey -6.69 -4.67 -3.73 -3.84 -4.73 31

United Kingdom

-5.15 -4.93 -4.91 -5.22 -5.05 32

United States -2.08 -2.08 -2.24 -2.31 -2.18 27

OECD average

1.70 1.65 2.11 2.18 1.91

(Sourced from OECD)

44

FDI income as percentage of GDP

Country 2013 2014 2015 2016 Average

OECD 32 average

-0.20 -0.49 0.14 0.23 -0.14

Australia -0.93 -0.73 -0.85 -0.90 -0.85

Austria 1.20 1.27 0.29 0.61 0.84

Belgium -1.23 -1.27 -1.50 -0.40 -1.10

Chile -4.50 -3.52 -2.78 -2.68 -3.37

Czech Republic -6.74 -6.98 -6.75 -6.82 -6.82

Denmark 1.96 2.35 2.52 2.11 2.23

Estonia -4.64 -4.82 -4.38 -4.45 -4.57

Finland 0.86 1.70 1.41 1.69 1.42

France 1.84 1.88 1.78 1.72 1.81

Germany 1.49 1.21 1.60 1.29 1.40

Greece

1.09 0.33 -0.09 0.44

Hungary -3.85 -5.44 -6.30 -4.60 -5.05

Iceland 2.25 1.26 1.50 2.30 1.83

Ireland -13.21 -12.19 -18.22 -14.01 -14.41

Italy 0.60 0.71 0.03 0.20 0.39

Japan 1.31 1.52 1.65 1.48 1.49

Korea 0.25 0.13 0.01 -0.01 0.09

Latvia -3.25 -3.16 -3.69 -3.82 -3.48

Luxembourg 13.59 15.42 47.93 45.01 30.49

Netherlands 4.84 -3.63 -3.66 -3.99 -1.61

New Zealand -3.25 -3.30 -3.06 -2.54 -3.04

Norway -1.21 1.05 0.52 1.19 0.39

Poland

-3.63 -3.66 -3.99 -3.76

Portugal -0.17 -1.06 -1.54 -1.55 -1.08

Slovak Republic

-3.07 -3.11 -4.65 -3.96 -3.70

Slovenia

-2.38 -2.47 -2.43

Spain 0.80 0.81 0.74 0.69 0.76

Sweden 2.39 2.19 1.44 1.25 1.82

Switzerland 3.99 2.44 4.47 3.01 3.48

Turkey -0.36 -0.22 -0.39 -0.34 -0.33

United Kingdom

1.59 1.12 0.48 -0.08 0.78

United States 1.70 1.59 1.47 1.39 1.54

(Sourced from OECD)

45

FDI restrictiveness index

Country 2013 2014 2015 2016 Average Ranking

Australia 0.128 0.078 0.141 0.141 0.122 9

Austria 0.106 0.15 0.15 0.15 0.139 5

Belgium 0.040 0.035 0.035 0.035 0.036 21

Chile 0.057 0.15 0.15 0.15 0.127 8

Czech Republic

0.010 0.025 0.025 0.025 0.021 24

Denmark 0.033 0.056 0.056 0.056 0.050 20

Estonia 0.018 0.023 0.023 0.023 0.022 23

Finland 0.019 0.015 0.015 0.015 0.016 25

France 0.045 0.155 0.155 0.155 0.128 7

Germany 0.023 0.069 0.069 0.069 0.058 17

Greece 0.032 0.079 0.079 0.079 0.067 15

Hungary 0.029 0 0 0 0.007 29

Iceland 0.167 0.241 0.241 0.241 0.223 2

Ireland 0.043 0.135 0.135 0.135 0.112 12

Italy 0.052 0.13 0.13 0.13 0.111 13

Japan 0.052 0.069 0.069 0.069 0.065 16

Korea 0.135 0.25 0.25 0.25 0.221 3

Latvia 0.022 0.014 0.014 0.014 0.016 25

Luxembourg 0.004 0 0 0 0.001 32

Netherlands 0.015 0.062 0.062 0.062 0.050 19

New Zealand 0.240 0.325 0.325 0.325 0.304 1

Norway 0.085 0.156 0.156 0.156 0.138 6

Poland 0.072 0.05 0.05 0.05 0.056 18

Portugal 0.007 0.006 0.006 0.006 0.006 30

Slovak Republic

0.049 0 0 0 0.012 28

Slovenia 0.007 0 0 0 0.002 31

Spain 0.021 0.011 0.011 0.011 0.014 27

Sweden 0.059 0.138 0.138 0.138 0.118 10

Switzerland 0.083 0.083 0.083 0.083 0.083 14

Turkey 0.059 0.013 0.013 0.013 0.025 22

United Kingdom

0.040 0.138 0.138 0.138 0.114 11

United States 0.089 0.181 0.181 0.181 0.158 4

(Sourced from OECD)

46

Social expenditure as part of GDP

Country 2013 2014 2015 2016 Average Ranking

Australia 18.109 18.697 18.794 19.146 18.6865 25

Austria 27.559 27.854 28.03 27.786 27.80725 6

Belgium 29.324 29.174 29.17 29.005 29.16825 3

Chile 20.261 10.52 11.18 .. 13.987 30

Czech Republic

20.261 19.897 19.475 19.437 19.7675 19

Denmark 29.017 29.001 28.814 28.677 28.87725 4

Estonia

15.977 17.037 17.427 16.81367 27

Finland 29.482 30.177 30.575 30.783 30.25425 2

France 31.493 31.938 31.685 31.548 31.666 1

Germany 24.758 24.851 24.964 25.289 24.9655 10

Greece 26.04 26.077 26.387 27.026 26.3825 8

Hungary 22.108 21.373 20.672 20.604 21.18925 18

Iceland 16.603 16.677 15.674 15.214 16.042 28

Ireland 20.229 19.161 16.971 16.105 18.1165 26

Italy 28.619 28.972 28.917 28.871 28.84475 5

Japan 23.06 23.06

23.06 14

Korea 9.332 9.718 10.108 10.359 9.87925 32

Latvia 14.377 14.227 14.415 14.46 14.36975 29

Luxembourg 23.233 23.004 22.184 21.8 22.55525 15

Netherlands 22.879 22.661 22.313 22.006 22.46475 16

New Zealand 19.275 19.371 19.667 .. 19.43767 22

Norway 21.765 22.448 23.909 25.075 23.29925 12

Poland 19.57 19.489 19.419 20.214 19.673 20

Portugal 25.497 24.523 24.1 24.113 24.55825 11

Slovak Republic

18.103 19.318 19.408 18.598 18.85675 24

Slovenia 23.978 23.081 22.362 22.834 23.06375 13

Spain 26.28 26.069 25.371 24.61 25.5825 9

Sweden 27.386 27.136 26.677 27.057 27.064 7

Switzerland 19.195 19.275 19.608 19.727 19.45125 21

Turkey 13.359 13.507 .. .. 13.433 31

United Kingdom

21.874 21.58 21.502 21.493 21.61225 17

United States 18.816 18.813 18.954 19.321 18.976 23

(Sourced from OECD)

47

Migration inflow of foreign nationals

(Sourced from UN Migration database)

Country 2013 2014 2015 2016 Average Ranking

Australia 1.09892 1.010358 0.966066 0.943752 1.00 10

Austria 0.824819 1.798321 2.315901 1.850618 1.70 7

Belgium 0.857398 0.953596 1.154609 0.925278 0.97 11

Chile

0.478434 0.583582 0.775869 0.61 18

Czech Republic 0.363319 0.298178 0.328563 0.33 25

Denmark 0.845189 0.869794 1.041061 1.041061 0.95 12

Estonia

0.101891 0.557489 0.581921 0.41 22

Finland 0.439084 0.434927 0.393857 0.501637 0.44 20

France 3.980719 4.000782 3.952487 3.768586 3.93 1

Germany 0.576906 1.652038 2.481069 2.116766 1.71 6

Greece

#N/B

Hungary

0.264215 0.26201 0.241851 0.26 26

Iceland

1.329664 1.517737 2.403364 1.75 4

Ireland 0.601311 0.933362 1.052969 1.151217 0.93 14

Italy 0.467061 0.416237 0.419764 0.440653 0.44 21

Japan 0.04467 0.262269 0.304848 0.333236 0.24 27

Korea 0.121491 0.811384 0.743357 0.801696 0.62 17

Latvia 0 0.220529 0.220725 0.168937 0.15 29

Luxembourg 3.308991 3.857615 4.148257 3.955413 3.82 2

Netherlands 0.624957 0.827482 0.947049 1.08171 0.87 15

New Zealand 0.99772 1.777092 2.031142 2.116733 1.73 5

Norway 1.187971 1.209947 1.163443 1.152413 1.18 9

Poland

0.083471 0.224717 0.279407 0.20 28

Portugal 0.250679 0.334964 0.359527 0.445678 0.35 23

Slovak Republic 0.044571 0.069567 0.066544 0.06 30

Slovenia

0.889351 0.964569 0.969409 0.94 13

Spain 0.386303 0.566373 0.621022 0.75905 0.58 19

Sweden 0.947031 1.103484 1.184275 1.487114 1.18 8

Switzerland 1.667761 1.870232 1.84965 1.759498 1.79 3

Turkey

#N/B

United Kingdom

0.456589 0.779691 0.74411 0.702341 0.67 16

United States 0.313989 0.322155 0.333093 0.375076 0.34 24

48

Migration outflow of foreign nationals

(Sourced from UN Migration database)

Country 2013 2014 2015 2016 Average Ranking

Australia 0.13694 0.140974 0.148158

0.14 18

Austria 0.868594 0.892014 0.934262 1.037841 0.93 3

Belgium 0.706331 0.582075 0.53663 0.436298 0.57 9

Chile

#N/B

Czech Republic

0.256296 0.151539 0.141816 0.126874 0.17 17

Denmark 0.527457 0.539677

0.53 10

Estonia 0.02466 0.024433 0.248865 0.257337 0.14 19

Finland 0.077892 0.100625 0.122807 0.137557 0.11 22

France

#N/B

Germany 0.809209 0.942109 1.057379 1.335609 1.04 2

Greece

#N/B

Hungary 0.133215 0.110018 0.105395 0.10632 0.11 21

Iceland 0.702752 0.756881 0.687156 1.114373 0.82 5

Ireland 0.704827 0.640752 0.587356 0.621529 0.64 7

Italy 0.073138 0.080368 0.074908

0.08 23

Japan 0.166284 0.165952 0.174216 0.181983 0.17 16

Korea 0.534366 0.539223 0.599992 0.647731 0.58 8

Latvia 0.167124 0.068153 0.125576

0.12 20

Luxembourg 1.639083 1.741101 1.916514 2.08 1.84 1

Netherlands 0.493171 0.495505 0.505879 0.533967 0.51 12

New Zealand 0.514143 0.479571 0.48942 0.514121 0.50 13

Norway 0.493126 0.459326 0.539374 0.605279 0.52 11

Poland

#N/B

Portugal

#N/B

Slovak Republic

0.05106 0.001272 0.000645

0.02 25

Slovenia 0.034802 0.048161 0.082091

0.06 24

Spain 0.982856 0.685231 0.533706 0.517784 0.68 6

Sweden 0.255881 0.274321 0.325876 0.243921 0.28 14

Switzerland 0.860974 0.851187 0.903037 0.954015 0.89 4

Turkey

#N/B

United Kingdom

0.262991 0.264538 0.253709 0.301666 0.27 15

United States

#N/B