Economic Migration within Asia:
Transfer of Knowledge or Redistribution of Wealth

Shahanaz Parven1

1 PhD Candidate in Political Processes, Institutions, and Analysis, RUDN University, Moscow, Russia

グローバル化の進展によりアジア域内での出稼ぎ・移民労働者が増え、なかには現地で起業する人もいる。アジア域内の出稼ぎ・移民労働が技術移転や富の再分配につながるのかを検証した。

Abstract

A measurable feature of a globalising Asia is the flow of migrants who move between Asian countries in search of
employment. The theory on decentralised income redistribution and immigration suggests that it is possible to promote wealth inequality in a country by means of adopting policies, which favour the immigration of workers who
have a negative net contribution to the hosting fiscal system. The theory however fails to explain the positive externality that derive from the arrival of a migrant into the hosting country, with the subsequent transfer of knowledge
and skills that, even for low-skilled workers, is however still present. It has been noted that immigrants tend to beparticularly active entrepreneurs in certain contexts, which in turn suggests that migration can under certain conditions promote economic development. The question we study in our paper is whether the emigration of citizens
from South East Asian developing countries towards developed Asian countries favours the emergence of wealthinequalities. Or, instead, whether it is an engine of economic development by means of the transfer of knowledge
as embodied by the migrants, and by means of the entrepreneurship of the same migrants in the hosting communities. This research question is tackled by comparative analysis of the rate of entrepreneurship, in relation to
immigration from South East Asia into developed Asian economies such as China, Japan, and South Korea.
Keywords

Asian migration, globalisation, redistribution of wealth, wealth inequality.

Introduction

The literature on globalisation suggests that theincreased volume of international migration streams
that we observe recently is evidence for the emergenceof a larger, global society (Fertig & Schmidt, 2001;
Wickramasekara, 2008). In this sense, we can discussmigration as an observable phenomenon that corresponds to an unobservable, but nonetheless real, processof transformation that leads several disaggregated societies to merge into a single, unified, global system(Castles, 2010). Globalisation, however, does not exclusively comprise an increase in the streams of international migration. In addition to that, the literature in fact
identifies several other epiphenomenal characteristics ofglobalisation. These are, among others, an increased
diffusion of knowledge (Dale, 2005), a decrease role ofthe nation state in determining economic policies(Schulze & Ursprung, 1999), and also the convergenceor hybridisation of national cultures (Otočan, 2017).
Further, it was noted that human languages tend to converge over time (Auer, Auer, Hinskens, & Kerswill,2004); and because of the relationship between language
and knowledge, with the former providing the coding bywhich the latter is expressed verbally (Scardamalia &Bereiter, 2005), this suggests that human knowledge asa whole might also be undertaking some forms of convergence (Dale, 2005).
In parallel to this, and independently from this, it has

037Shahanaz Parvenalso been noted that globalisation leads to an increase in
wealth inequality (Siddiqui, 2018). This increase generally occurs both horizontally between nations (Alvaredo,
Chancel, Piketty, Saez, & Zucman, 2017; Hickel, 2017),
and vertically within the same national economy(Krieckhaus, Son, Bellinger, & Wells, 2014). It appears
therefore that globalisation does not provide a single,
clear-cut transformation of society according to one
exclusive migration. Instead, it is modifying it throughout a large span of its characteristics. It therefore makes
sense to study which ones among many characteristics
are affected by globalisation more than others.
Globalisation in Asia and its peculiar characteristics
Globalisation is taking place not only in the set ofcountries as a whole, and which therefore has “global”
characteristics; instead, it also presents some peculiarfeatures according to the region of study. Notably, forthis paper, we are interested in the specific characteristics that concern primarily Asian countries. In Asia,
globalisation is assuming the form of a transformationof the traditional role held by the state (Green, 2007),
which is not necessarily being replaced by a pan-continental political union as it is happening, instead, inEurope (Nousios, Overbeek, & Tsolakis, 2012). Of
course, one could argue that various forms of regional
integrations exist not only in Europe but also in Asia,and indeed the literature concurs on the idea that a kindof regional integration in Asia exists as well (Coleman& Underhill, 2012; Lee, Owen, & Van der Mensbrugghe,2009). Indeed, similarities between the European and
the Asian regional integration have been noted (Murray& Warleigh-Lack, 2013), as did fundamental differencesand even divergences (Fort & Webber, 2006). The mostimportant among the latter concerns the absence of anobservable and emerging political unity of the Asian
continent, which is instead present in Europe in theform of the European Union (Moon, 2017).
The transformation in Asia is multi-faceted, as we
will see shortly, but it affects transversally all typicalsectors of competence of a nation-state. These sectors
include the expanding welfare state (Ramesh, 2004), an
urban transformation that is characterised by an

038

increasingly higher interconnectedness of Asian cities(Lo & Marcotullio, 2000), but also education and genderreforms (Ramirez & Chan-Tiberghein, 2003; Siegmann,2006). It also concerns security and defence (Till, Chew,& Ho, 2008), not only in terms of the traditional paradigm of state-centred security (Zhao, 2008), but also
because of the tight relationship between investments inthe defence sector and technological innovation (Raska,2014). A relationship between globalisation and military
expenditures has thus been noted (Solarin, 2018); though
in some Asian countries it seems that globalisation iscausing an increase in military expenditures, while inothers the reverse causality is true (Wu, 2017). It istherefore not clear whether the capacity for an Asian
economy to innovate derives from the traditional alliance between the industrial and the military sector(Smart, 2016), or whether other factors, such as the different levels of openness of Asian countries, may help
explain the different levels of human and economic
development achieved by them (Eusufzai, 1996). If
openness plays a role in the human development of anation, as we ask ourselves in this paper, then it should
be possible to produce policies that promote development by progressively increasing a country’s openness.
This has already been suggested by others (Chang,
Kaltani, & Loayza, 2009), and in this paper we canstudy whether the idea applies to Asian countries as they
undertake globalisation. The opposite idea, if this is nottrue, is that globalisation in Asia is promoting inequality
rather than development (Kanbur & Zhuang, 2013).

Fig. 1.
A globalising society receives increased flows of knowledge workers,
which promotes economic growth but generates inequality.

Openness of a society and its measurable observables: migration in Asia
Connected to the idea of a globalising world is the6th AFC Best Papers

concept of openness of a society (Popper, 2020). The
whole human social and political system, also called“global system”, can of course be considered as a closed
system. This is because, if we ignore for a second thatthe environment around humans also exists, then we canargue that the global system is closed because it includes
the whole set of humans. The sub-systems of the global
system, however, are open systems. This is because, if
we consider nation-states as subsystems of the global
system, then they do not include all humans that exist(Fulcher, 2000). If we consider the nation-state in its
dynamic evolution over time, however, we can imagine
that the degree of its “openness” may vary, as time
passes. We are going to give in a second a definition of
openness that we use in this paper; but for now, it issufficient to have the intuitive idea that societies canbecome more or less open as time passes. We can thenask ourselves the question, how can we determine
whether a society is becoming more or less open in thecourse of its evolutionary dynamic. Let us start by taking
two edge cases, that will clarify this concept further.
We can first consider as an improper subsystem of
the global system the global system itself. This subsystem is closed, because the global system is also closed.
A nation-state that were to become the sole politicalsystem on the planet would, by this definition, be classified as a closed system.
We can also consider a nation-state as a proper subsystem of the global system; this is because there aresome humans that are not part of it. If, in addition to that,the specific identity of the inhabitants of that subsystemdoes not change over time, we could then consider thatnation-state to be a closed system. Of course, the population may change due to the natural births and deaths thatcharacterise any human population. But for the purposesof this study, we can still think of a system whose population changes only according to deaths and genetic
births as a closed system. Another way to call this typeof society is “isolated society” (Lightman, 1977), whichis equivalent to this particular definition of closeness.
We can also consider an intermediate case between
these two extremes. This consists of a society that, while
being a proper subsystem of the global system, presents

however changes in the composition of its population
over time, if these changes are not reducible to naturalbirths and deaths. Of course, if the population does notchange because of births and deaths, then this meansthat there must be some kind of population exchangewith other systems. This exchange would take place
between the society we are considering and the global
system of which that society is a subsystem. If weassume that a political system is inseparable from its
territory, as we normally do in political geography(Mellor, 2015), we can then consider the process ofentering or leaving that territory as the observable phenomenon that corresponds to this population exchange.
Another word for that same process is, clearly, international migration. If we build our theoretical construction in this manner, we can then consider internationalmigration and its associated statistics as measures forthe degree of openness of a society.
Wealth inequalities and the measurement of
economic or human development
The theory however fails to explain the positive
externality that derive from the arrival of a migrant into
the hosting country, with the subsequent transfer ofknowledge and skills that, even for low-skilled workers,
is however still present (Williams & Baláž, 2014). It has
been noted that immigrants tend to be particularly active
entrepreneurs in certain contexts (Bhachu, 2017), which
in turn suggests that migration can under certain contexts promote economic development. The question we
study in our paper is whether the emigration of citizens
from South East Asian developing countries towards
developed Asian countries is a phenomenon the favours
the emergence of wealth inequalities in the hosting
countries.
The measurement of economic inequality can bedone with the usage of several different metrics (Cowell,2011). Some of these include the Gini coefficient of the
distribution of income (Zuguang, 2004), others consider
instead the share of national income that the top n earners in a society receive (Bakija, Cole, & Heim, 2012). In
this research we use both, in order to avoid the bias thatmight originate from the selection of a particular metric039

Shahanaz Parvenas opposed to another.
The theory on economic inequality however emphasises the point that, while the distribution of income might
be an important point to target by economic policies, it
may be a poor representation of the actual capacity by
citizens to conduct economic actions (Sen & Foster,1997). In fact, the income is a representation of the relative purchasing power by the population of an economy,
but does not account for the actual capability to perform
economic transactions by the same population (Sen,1980). Notably, the measurement of inequality in a country based on the income may not detect particularly
extraordinary phenomena such as famine, which are
believed to have an institutional origin. This institutional
origin has been studied in the cases of Finland (Voutilainen,2016), Russia (Johnson, 2015), and China (Meng, Qian,& Yared, 2015), among others. This is because, thetheory suggests (Sen, 2001), the measurement of theeconomic capability of the population on the basis of asingle metric such as income inequality is a gross projection of a much more complex economic system.
Instead, one could use the so-called “positive freedom”,
which is believed to be a better indicator of economic
and human development (Prados De La Escosura, 2015),
with comparison to economic inequality.
So what is positive freedom? Positive freedom is aterm that comes from the literature on sociology(Bowring, 2015), and in particular from Isaiah Berlin’s
notion of “types of freedom” (Berlin, 1969). A simple
way to describe the notion of positive freedom is toframe it as the antithesis to the concept of “negative
freedom”. The latter is the answer to the question “freedom from what?” (Van Hees, 1998), and can assume
various forms according to the discipline that studies it.
In political theory, where the concept originated, negative freedom is often associated with freedom from
oppression (Grant, 2013), against a tyrant or a totalitarian government for example. In the context of economy
and, in particular, of economic development, a typicalexample of negative freedom is the freedom from thesystematic confiscation of private property by the state,that a government might use as a form of economic
policy (Epstein, 1982). In contrast to negative freedom,

040

positive freedom can be conceptualised as the answer tothe question “freedom to do what?”. An example of positive freedom could be by the freedom to choose andpurchase some among many possible products (Schwartz,
Markus, & Snibbe, 2006), as opposed to a limited selection of them that has been approved by the state. It has
also been suggested that positive freedom relates not
only to purchase of goods, but also to the acquisition of
immaterial objects such as values and culture that originate from the personal preferences of individuals(Friedman & Friedman, 1990). These, in turn, arereflected in the macroeconomic indices that we use toassess the measure of economic freedom in nations(Kaun, 2002). Another way to reformulate the previous
sentence is to say that there is a high degree of humanbias in conducting comparisons on the level of economic
freedom across states. If this is true, this means thatinter-state comparisons of openness may not be possible, without some kind of prejudice on the part of theanalyst that conducts the research. While we cannot
solve this problem here, we can however acknowledge
that the variation in wealth inequality is not necessary agood indicator of the way in which an economy is developing, and that some other measures could be used inaddition or complement to it.
Comparative analysis of the rate of entrepreneurship
The discussion we made above introduces us to the
problem of measuring the impact that migration has onknowledge generation in a country. There is an idea that
if migration, and notably immigration, causes a country
to generate innovation, this should be observable basedon the number of companies that open in that country.
This is because, if we follow the Schumpeterian
approach (Schumpeter, 2000), the innovation is theaction of the entrepreneur that embodies the change in asociety (Hébert & Link, 2006). Therefore, the existenceof a link between the openness of a society and knowledge generation should also pass through the existenceof a relationship between immigration and the rate ofentrepreneurship. As we discussed earlier, the theoretical expectation we hold is that, the more open a society
is, the more frequently its population generates

6th AFC Best Papers

knowledge and innovation, or at least this is what one
could expect. The measurable characteristics of thisrelationship is the expected dependency of the rate ofentrepreneurship in a country to the volume of immigrants in the same country, short of a time delay if necessary. The figure below sums us the first hypothesisthat we test in this paper.

Fig. 2.
The argument that supports the first hypothesis. Opennes of a society
favours immigration, which supports the local knowledge production. This
results in a measurable increase in the entrepreneurial activities in thatsociety.

The opposite idea, and its corresponding hypothesis,
consists in the consideration that migration does not help
generate new knowledge and innovation, but instead
contributes to the accumulation of wealth in the handsof the wealthiest few. This is because, as we discussed,
at least part of the migration workforce weighs upon thelocal welfare system, and is thus unable to contributeproductively to the economy. Therefore, if this second
hypothesis is correct, one should observe that as thenumber of immigrants into a country increase, the wealthinequality also increases. The image below sums up thesecond research hypothesis that we test in this paper.

Fig. 3.
The argument that supports the second hypothesis. A stream of
immigrants arrive into the country. Over the course of the next years, anincreasingly larger portion of the state budget is used to support themfinancially. This leaves less resources for investments and reducescompetitiveness.

Methodology

We selected a group of Asian countries in order totest these two hypotheses. The independent variable that
we use is the same for all countries, and corresponds tothe number of immigrants arriving in a host country ina given year.
Because we are interested in studying the flow of
migrants as a whole, and not the flow of skilled migrants
in particular, we selected as countries of emigration
those that are characterised by particularly high levelsof unskilled emigration. Notably, we chose those countries whose emigrants move abroad to join the labour
force in construction sites, housekeeping duties, or analogous unqualified jobs. These countries are: Bangladesh(Moses, 2009), the Philippines (Asis, Huang, & Yeoh,2004), and Nepal (Yamanaka, 2000). We consider as anindependent variable the time series that relates to thearrival of migrants from those countries into each of thethree destination countries that we are studying. The
destination countries are selected among the most developed nations in Asia, and comprise China, Japan, andSouth Korea. The table below show in a more convenient format the variables that we used for our analysis
and their associated labels (Table 1).
Table 1. Independent variables – time series
Description
Emigration from Bangladesh to China
Emigration from Bangladesh to Japan
Emigration from Bangladesh to South Korea
Emigration from the Philippines to China
Emigration from the Philippines to Japan
Emigration from the Philippines to South Korea
Emigration from Nepal to China
Emigration from Nepal to Japan
Emigration from Nepal to South Korea

Label
BC
BJ
BK
PC
PJ
PK
NC
NJ
NK

The dependent variables are two. The first dependent
variable corresponds to the rate of entrepreneurship,
which is measured as the number of listed companies ina country in a given year, as a fraction of the populationof that country. The idea is that the number of companies represents the entrepreneurship of the population,
as a quote of the latter. While it is possible for more than
one company to be opened by a single individual, we041

Shahanaz Parvenassume that this phenomenon is rare and that it does not
significantly affect the aggregate ratio. The dataset that
we use indicates the number of listed companies, not the
number of companies in general; therefore we assume
either representativeness of the listed companies over
the total number of companies, or the listed companies
as being those that comprise the highest proportion ofknowledge generation.
The second dependent variable is the wealth inequality, which we measure as it is common in the literatureby using the Gini coefficient for the income distributionof the population in a given year (Wolff, 1992). We alsouse, as an alternative representative measurement ofwealth inequality, the percentage of the income that isheld by the top 10% earners, as the literature also does
(Roine, Vlachos, & Waldenström, 2009). This second
measurement is used as a control for the first, and wedeem that results that are reflected on both variables are
more likely to be accurate.
The table below shows the dependent variables we
use for this study and the associated labels (Table 2).
Table 2. Dependent variables – time series
Description
Time difference of listed companies - China
Time difference of listed companies - Japan
Time difference of listed companies – S. Korea
Gini coefficient - China
Gini coefficient - Japan
Gini coefficient - Korea
Income share of top 10% earners - China
Income share of top 10% earners - Japan
Income share of top 10% earners - South Korea

Label
LC
LJ
LK
GC
GJ
GK
IC
IJ
IK

The time period that we consider relates to the mostrecent 50 years, for both the dependent and the independent variables. This is the longest period of time that iscovered by the dataset we used. The resolution for the
dependent variables is yearly, the resolution for the
independent variables is by decade; this implied thenecessity to conduct data aggregation, as we discuss inthe next section. All the data that we use for this researchoriginates from the databank of the World Bank; and,042

namely, from the Global Bilateral Migration dataset1
and from the World Development Indicators2.

Results

We set to perform correlation analysis on each pairsof independent and dependent variables. Because this isa requirement for correlation analysis, we had to selecttime series of equivalent length. This implied the necessity to conduct data aggregation and the cutting of thetime series at some more or less arbitrarily points. We
conducted data aggregation on the time series related tomacroeconomic data (the variables starting with the letters G, I, and L) by rolling over each decade, and by thenaveraging the values corresponding to the valid observations for that decade. The time delta we used for correlating the time series corresponds to 20 years (2decades), with the independent variable preceding thedependent variables.
In doing so, the variable LC resulted in only two
observations corresponding to the years 2000s and2010s, so we had to discard it from the analysis. Similarly,
the variables GK, IK, GJ, IJ also resulted in only twovalues, so we had to discard them from the analysis. Thisis a limitation to the results of the research we conducted,
which will need to be filled by studies that use data at ahigher resolution and/or longer time series.
The table below shows the correlation measures foreach pair of variables that were not discarded following
the considerations we made above (Table 3).
Table 3. Pearson’s correlations between variables
BC
PC
NC
BJ
PJ
NJ

GC
0.999167888
0.8197964-0.65847558
LJ
0.76519859
0.89372873
0.95358019

IC
0.999886601
0.8342622-0.63888932
BK
PK
NK

LK
0.98713595
0.883994
N/A

1 https://databank.worldbank.org/source/global-bilateral-migration
2 https://databank.worldbank.org/source/world-developmentindicators

6th AFC Best Papers

The correlation value for the pair (NK, LK) is missing because the dataset we use reports zero immigrants
from Nepal to South Korea up to the 2000s, when that
number suddenly becomes 1450. The rest of the values
were deemed to be accurate.

Discussion

For two of the three countries that we consider,namely Bangladesh and the Philippines, immigration to
China correlates positively with the future Gini index
and also with the quota of national income that is heldby the top 10% earners. By “future” we hereby mean
“twenty years later”, since that is the time delta that weuse between the two time series, as discussed earlier.
This observation seems to support the thesis that immigration leads to higher income inequality in the country
where it takes place; and that namely, this is true for
China. The third country that we consider, however,shows a strongly negative correlation between immigration and wealth inequality. Because Nepal however
holds less than 100 immigrants to China up to 2000s,
this may however simply mean that the inflow of migrants
is insufficient to affect macroeconomic statistics.
Regarding the impact of immigration onto entrepreneurship, both countries that we included, Japan andSouth Korea, show a positive correlation. The immigration from Nepal to South Korea has been null up until
the 2000s, which is why we did not include it in the final
results. With this exception, the positive correlation isvalid for all countries of origin that we considered, andfor both countries of destination. This is an argument infavour of the hypothesis that immigration support entrepreneurship, and the generation of knowledge into thehost country of the immigrants.
As mentioned earlier, the most significant limitationof this research consists in the very coarse-grained resolution of the data concerning the bilateral immigration,that depends upon the usage of this particular dataset.
Further research might compensate for it by including
observations from the national statistical publications of
the host countries, provided that these have a higher resolution than the one we used.

Conclusions

In this paper, we studied the relationship between
openness of a society, as represented by the streams ofimmigration, and innovation and knowledge generation,
as represented by the entrepreneurship. We have defined
two research hypotheses, that comprised the role that
migration has as a promotor of knowledge generationand innovation or, instead, as a promotor of wealthinequality in the hosting country. We have further provided empirical testing of these two hypotheses, on thebasis of macroeconomic data associated with the variables of immigration, on one hand, and of entrepreneurship and income inequality on the other. The analysis
that we have conducted shows that there is some support
to the hypothesis that immigration produces wealthinequality; and, at the same time, that immigration also
generates knowledge and promotes entrepreneurship in
the hosting country. This research and its conclusions
were developed upon a subset of the Asian country that
we consider representative of the dynamics of migrationand development that are taking place in the continent.
If this is true, then the implication is that the two hypotheses we consider are both validated. That is to say, thatas migration increases between Asian countries, thisleads to simultaneously an increased generation ofknowledge by the local enterprises, and an increased
concentration of wealth among the top earners. The consequence for globalisation as it takes place in Asia isthat, if the current migration trend continues, then the
future Asia will see both a higher incidence of private
entrepreneurship, and a higher concentration of wealthamong the few.

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