1. TEAM 1
Economic Inequality and Differing
Educational Opportunities
Impacts of Educational Structures
Anisha Anil Damani
Ian Fang Shengyu
James Bazakos
Kim Dong-hun
Paul Gouvard
Shin Jung-min
08 May 2015
This final report is the product of our learning experience within the Global Integrative Module
(GIM) project, which is formed by students from business schools around the world. The aim is to
engage studentswithcurrentissuesandexplore aswell asdeveloppotential solutions.This year the
question centered on "Why and how can companies contribute to the reduction of economic
inequality in the world?" Our team has approached this issue from a perspective of educational
structures by grouping countries’ education system according to its similarity to the Finnish and
South Korean model. This is unlike studies done in the past, which mainly emphasizes family
background as a key factor in differing educational opportunities. We hope that our collaboration
will hopefully assist in solving some of the challenges faced by these societies.
2. 1
Contents
1) Definitions and Preliminary Studies........................................................................................ 2
1.1) Economic inequality: our definition..................................................................................... 3
2) Research Question.................................................................................................................... 5
3) Methodology............................................................................................................................ 7
4) Results................................................................................................................................... 11
Table 4.1................................................................................................................................ 11
Table 4.2................................................................................................................................ 12
Table 4.3................................................................................................................................ 13
Table 4.4................................................................................................................................ 14
Table 4.5................................................................................................................................ 15
5) Your Recommendations to the Company/ies Selected .............................................................. 16
5.1) What can for-profit companies do?................................................................................... 18
5.2) What can Government do?............................................................................................... 21
5.3) What can Schools do?....................................................................................................... 24
6) What Should Business Schools’ Contribution Be?...................................................................... 27
References................................................................................................................................. 29
Bibiliography.............................................................................................................................. 30
Appendix A................................................................................................................................. 32
Appendix B................................................................................................................................. 33
3. 2
1) Definitions and Preliminary Studies
A quick benchmarking of how “economic inequality” is usually defined on the web
gives us the following results:
“Economic inequality is the unequal distribution of household or individual income
across the various participants in an economy.” – Investopedia
http://www.investopedia.com/terms/i/income-inequality.asp
“Income inequality refers to how evenly or unevenly income is distributed in a
society.” – John D. Sutter, CNN
http://www.cnn.com/2013/10/29/opinion/sutter-explainer-income-inequality/
“Income inequality refers to the extent to which income is distributed in an uneven
manner among a population.” – Inequality.org
http://inequality.org/income-inequality/
It appears, not that surprisingly, that for popular scientific literature or, more broadly,
for the general public, “economic inequality” is first a matter of income inequality, that is to
say a matter of an “inappropriate” distribution of income between the actors of the economy.
But to define “economic inequality” by “income inequality” is in fact substituting a
measure – “income” – for a concept – “economic”. In fact there are many other ways than
income to measure what could be appropriately called “economic inequality”: the amount of
capital owned, the time spent in unemployment for a given category of population, the
number of people working as factory workers or office workers vs the number of top-
managers, etc.
In academic research we can distinguish at least two main differing bodies of research
that address the umbrella term “economic inequality”, namely the aforementioned ‘income
inequality’, and the slightly less popular ‘wealth inequality’. To most, the difference between
income and wealth inequality is not readily discernable by the titles afforded to them,
however to economists and people seasoned on the topic, the difference between these two
terms can lead to a very different discussion.
The main difference between income and wealth inequality is that income inequality
measures the share of total income going to a particular percentile whereas wealth inequality
shows the share of total wealth going to a particular percentile. Both of these concepts tend to
end up discussing the disproportionate share of either income or wealth accruing amongst the
4. 3
top 10%, 5%, 1% and .01% of the population. Regardless, the concept that one chooses to
discuss can greatly dictate how nuanced this argument can become. For example, wealth
inequality is in fact a much more disconcerting picture than income inequality. That’s not to
say that income inequality is an irrelevant discussion, but it would seem that the
‘blasphemous’ discrepancies people have been sounding in more recent times are
significantly more prominent amongst the distribution of wealth. The different degrees to
which income and wealth inequality have been increasing is illustrated by the following
graph:
1.1) Economic inequality: our definition
Now that we have clearly highlighted the fact that defining “economic inequality” as
“income inequality” is not neutral and that it strongly dictates the type of results obtained, we
can try to provide a more complete definition of “economic inequality” which will also be the
starting point of explaining how we got to define the problem we are tackling.
Our group is in favor of Alvaredo et al. (2013) and their study on economic
inequality, which talks about discrepancies in the repartition of the total income generated by
the market. However, we are also supportive of the view of inequalities in the repartition of
5. 4
capital between households (NEF, 2013). The interest of this broader definition is that it takes
into account both the existing inequalities before the repartition of the income – namely
inequalities in the ownership of capital – and the way through which inequalities are
perpetuated through the actual repartition of the income. Thus economic inequality is a both a
state of the economy (discrepancies in the repartition of capital) and an economical process
(capitation of the bigger part of incomes by a certain proportion of the population).
Starting from this definition of economic inequality, we have tried to find how
companies could contribute to reduce it. To this purpose we have tried to identify on which
factors of economic inequality companies could concretely act. Two main observations led us
to define our problem.
First, the rise of economic inequality is linked to the demand of high-skilled worker in
the economy (Alvaredo et al., 2013). It has been observed that cutting taxes could entail
higher incomes for the top 1% of the population. One of the possible factors for this is the
increase of marginal gain per supplementary income : if higher incomes are less taxed, people
in the top 1% of the population have more incentive to bargain for their salary ; meanwhile,
the demand of high-skilled workers being high in developed economies where technology is
well-developed and high-skills provide important gains in productivity, the bargaining power
of companies shrinks if top-skilled workers can expect a significant gain in their income by
bargaining for their salary as taxes are lower ; thus the level of higher incomes rises.
The research we read focused on tax-cuttings, but we decided to investigate further
the link that the paper identified between the demand for high-skill workers and the increase
in economic inequalities. In fact we were wondering if this dimension of the problem still had
an impact independent of the presence of tax cuts in the economy. If yes, it meant that the
increase in demand for high-skilled workers was one of the factors of economic inequality as
it gave more bargaining power to the high-skilled workers to negotiate their salary.
To assess the relevancy of our analysis we looked at a complementary study held in
France for the period 2002-2007; it showed that when the average salary rose of 0.5% on this
period, the salary of high-skilled workers rose by nearly 6% (Amaar, 2010). No significant
tax cuts had taken place, unemployment was around 9%, and growth around 2%. This tended,
if not to directly support our view, to show that something was going on here.
In developed economies, the demand for high-skilled workers is the result of the
existence of high productivity gains due to technology. The presence of high-skilled workers
in the economy as well as the development of technology is due to the existence of high
6. 5
quality educational institutions that produce knowledge, top of the art technology and the
elite workers capable of using (and eventually understanding) them.
Thus, if the demand for high-skilled workers really entails income inequality,
education quality, as one of the condition of production of both productivity gain and elite
workers, can have a negative impact on economic inequalities.
And here we reached a paradox. Generally, education inequality is considered as part
of the inequality problem, along with economic inequality: the Inequality-adjusted Human
Development Index measures the losses in human development due to health, education an
income inequality (UNDP, 2010). The general public tend to consider that the higher the
level of education, the lower the economic inequality; as if the existence of educated people
in the economy entails that it would naturally become just.
But if education quality has an impact on the development of the economy, it is not
necessarily true, given what we had found, that it helped reducing economic inequality.
In the end we had identified a tension between two opposite conceptions : on the one
end we had the feeling that if the quality of education was high, the more developed was the
economy and thus the demand for high-skill workers was higher and ultimately the
bargaining power of elite workers insured them the ability to negotiate higher salaries that
would, in the long run, increase their capital, allow them to afford high quality studies for
their children, and durably perpetuate economic inequality; on the other end we had the
generally admitted idea that education is both a factor of economic development and a way to
reduce economic inequalities by introducing opportunities for individuals to rise in the
society.
Our idea was to determine the real contribution of education quality to the increase or
the decrease of economic inequalities, and then to evaluate the opportunities the answer could
represent for companies.
Hence our problem: do varying degrees of educational quality have an impact on
economic inequality, and if so, what are the implications of this?
2) ResearchQuestion
Our group has decided to research on economic inequality due to differing
educational opportunities as we believe that education is the fundamental building block of
society, without which, order and democracy would not have existed. Moreover, much debate
and research has been made of it throughout the times, with studies being conducted to posit
7. 6
both the positive and negative effects of differing educational opportunities on economic
inequality. Contrary to what our group is going to try and establish; Hendel, Shapiro and
Willen have written a discussion paper that established a positive correlation between
affordable education and the widening inequality in income (2004). By approaching the topic
based on job market signalling, they have concluded that lowering the cost of borrowing for
education has resulted in a steady increase in the number of the poor who become educated,
which has in turn resulted in poor people but of high ability leaving the uneducated group.
Consequently, this simultaneously increases the disparity between skilled workers and
unskilled, low productivity workers; and the skill premium required to move into skilled
labour jobs, thus, increasing income inequality.
This effect is further compounded by the rapid evolution of technology of the 21st
century. In their book ‘The Race between Education and Technology’, Goldin and Katz
(2008) posited that technological advances have resulted in companies demanding for more
skilled labour, causing the wage gap between skilled and unskilled labour to drift further
apart. This wage gap is prevented from widening further by increasing the supply of skilled
labour, which essentially turns this into an economics play of supply and demand.
However, it is important to note that Hendel, Shapiro and Willen were focused solely
on the educational policies of the United States, and that differing regions might see differing
results depending on the macro-environmental factors of that country involved. For example,
countries heavily reliant on manufacturing or textile industries for revenues might require a
higher unskilled to skilled labour ratio compared to a country that is focused on
pharmaceuticals and bio-chem.
Okun (1975) has summed it up pretty simply in what he describes as the “big
tradeoff”. In his book, both efficiency and equality are opposing polarities and that there is
the opportunity cost of one when seeking another. Okun also talked about transferring income
from the rich to the poor through the government’s system of taxes as a solution to the
inequality problem. However, this is highly inefficient due to the difference in utility of every
dollar between the rich and the poor, assuming that the rich are people of high productivity.
Returning to this scenario, we too, are faced with the question if it is more efficient to adopt
an education-for-all mentality and provide equal education to the majority of the people in the
name of equality rather than focus on the highly talented minority and nurture them for future
prosperity and growth of a country.
8. 7
Taking all of this into account, it seems that several studies have linked differing
educational opportunities with the family environment that the child is brought up in. While
this is not incorrect, it might also prove that the family environment factor is in itself, an
effect of the economic inequality from previous generations rather than a cause. In fact, a
study conducted by Sacerdote (2007), has shown that the outcomes of educational attainment
and income are often least affected by the differences in family environment. In his table 5,
Sacerdote estimated that 56% of the variance in family income is derived from external
environmental factors unrelated to family. Out of the remaining 44%, 33% was attributed to
genetic heritability. Only 11% of the outcome was attributed to the family environment,
which in a larger sense, does not actually make for a convincing argument that educational
opportunities between different income groups are vastly different.
To that, our group has decided to approach things from another perspective; that
differing educational opportunities resulting in income inequality is not something that is
caused due to differing family background or lack of access to education but rather, because
of something external and more culture oriented. Intuitively, this would make perfect sense,
given that the family environment is only being assigned a minor role in changing outcomes
as per according to Sacerdote’s study; it would require an intervention from the environment
that also makes up for a huge part of a child’s development for extended periods of time, in
order for beliefs and values to take root. Our group did not consider the other 33% that is
derived from genetic heritability as a possible cause due to its fixed nature from birth. Thus,
our group has decided to explore differing educational opportunities from the perspective of
educational structures, due to schools forming a huge part of a child’s life during pre-school
and elementary school. Through personal experience and asking friends about it, there was a
consensus that the way others perceived a person in primary school had an effect on that
particular person’s behaviour throughout secondary school, which would then snowball into
college and so on and so forth.
3) Methodology
To delve into educational structures, its effects on differing educational opportunities
and economic inequality. We started off by first establishing that there is indeed a positive
correlation between literacy rates and the wealth of a country; and that differing educational
opportunities have an impact on economic inequality amongst countries. This is done by
9. 8
simply accessing UNESCO Institute of Statistics to obtain the latest available GDP per capita
and literacy rates.
After establishing a relationship, we then decided to look at two country’s highly
different, yet highly successful education systems in the world: Finland and South Korea. On
average, both are highly ranked in the annual PISA tests and both countries usually take turns
to secure first and second place. Finland’s education system only has one exam, which is
taken when students are 16 years old. Another distinct difference is that there are no inter-
school rankings and no comparisons or competition made between schools. As stated in the
Smithsonian (2011) magazine, every school has the same goal and draws from the same pool
of educators, who are in turn placed in a very selective process that only sees the top 10% of
graduates with a Master’s degree in education being appointed as teachers. In sum, every
child has the same opportunity as the next in getting a good education regardless of where he
or she lives. More importantly, they receive extra help if they are weaker in certain areas of
academia.
Then we have the South Korean education system, which emphasizes 16 to 20 hour
study days until the day of the university entrance exam or ‘examination hell’ as it is known
(BBC, 2013). Exams are in a multiple-choice format which leaves no room for error.
Students that score well are able to enter one of the top 3 universities in Korea, which would
subsequently guarantee them a lucrative, lifelong job at a Korean conglomerate or high
ranking government position. On the other hand, students that tick a few boxes incorrectly are
destined to attend a lesser university and be locked out of the upper tiers of Korean society
(The Economist, 2011).
To determine if a positive relationship exists between the difference in two education
systems and economic inequality, we had to first define and identify other countries
following or having similar elements to each education system. While South Korea’s
education system is markedly easier to identify with other countries (e.g. Singapore, Hong
Kong, USA), Finland’s education system posed a much larger problem as it was undeniably
unique. We considered using geographical proximity to Finland and the ripple effect to
include other countries that would have adopted Finland’s education system but there was no
solid evidence present to say with certainty that those countries (e.g. Belarus, Estonia,
Norway) adopted elements of Finnish education. As a result, we placed Finland in a group of
its own.
10. 9
To conduct sufficient testing however, we have decided to include countries whose
education system contradicts the South Korean education system (i.e. encourages equality
and participation of the majority). However, this does not imply that they are similar to the
Finnish education system as most have exams. For example, we have selected Sweden as one
of the countries due to its ongoing attempt at widening participation in higher education by
abolishing fees, having simple rules of admission and acceptance of ethnic minorities and
low-income groups. Another example would be Denmark, as it has statistics similar to
Finland; well-paid teachers, high GDP allocation, high participation rates in education and
little to no private entities being operated within the state (OECD 2015). More importantly, it
is also an advocate of equality among students regardless of social status and gender.
The second component of this would be economic inequality and for this measure, we
used the GINI index to compare and contrast inequality in the selected countries. One
challenge that stood in the way was the figures itself that were provided in databases. Several
countries’ GINI index for certain years was missing and others had entire periods blank. To
overcome this obstacle, our team has decided to take the average GINI index from year 2000
to 2014, and utilize both the CIA database and the World Bank database for accuracy
purposes. One concern we had at first was related to the objectivity of the average figure,
given that having huge time skips might result in larger than imagined deviations in figures.
However, after looking through the selected countries GINI index, we have concluded that
most deviations were negligible.
Should a positive relationship be found, we then looked into the school rankings of
countries with high GINI to see if there are any variances in elementary and secondary school
rankings in the past few years. Intuitively, a low variance in rankings would indicate that
there might be existing differing educational opportunities (or career opportunities).
On the other hand, a high variance in rankings might indicate that schools are ranked
differently and that other aspects of school life have been taken into account; or there might
not even be a ranking at all and that all schools before university are deemed to be equal
amongst their peers, such as in the case of Finland. For this part, most of the research is based
on information from the local government’s website, as well as personal experiences; given
that our group has members from Singapore and South Korea (grades-oriented culture). Thus,
research in this aspect, while objectively based on information from a government source, is
still debatable as there is the human aspect of it. However, most of the information derived
11. 10
from personal experience can also be found and sourced from interviews provided online,
thus, it is safe to say that our local perspectives of academia in our respective countries are
well within general expectations.
Moving on, we also started to look at the number of notable alumni each of these
schools had. In this case, we decided to focus and elaborate on Singapore as the data provided
was comprehensive enough to draw conclusions from. With regards to this, the term
“notable” seems to incorporate people that are well-known; locally or globally, regardless of
their impact in society. For that matter, we only counted people who presently hold, or held
governmental positions in the past; or are integral to Singapore's development or well-known
globally. We excluded winners of beauty contests, singing contests, scholarships and local
actors and actresses. Scholarship winners, while debatable, had no positive contribution in
society until they graduated and came from various and very diverse aspects (sports, music,
drama, military, academics etc.) and thus, we refrained from including them. However, even
if included, it would not vary statistically as each school had around 4-6 of these alumni on
average.
12. 11
4) Results
To begin, let us start by looking at the global perspective and relationship between a
country’s wealth and literacy rates. As stated before, this is not meant to be conclusive in the
sense that higher literacy rates would significantly improve a country’s GDP. Rather, it is just
presented as a starting point for our group; to check if there is indeed, a positive relationship
between GDP per capita and literacy rates amongst countries.
As seen in Table 4.1, which was provided in the International Literacy Data report by
the UNESCO Institute for Statistics (2013), there is an existing positive correlation between
adult literacy rates and GDP per capita:
Table 4.1
While this might seem too broad a conclusion due to the number of components found
within GDP, this acts as a fundamental step forward for us; showing that there is indeed,
economic inequality amongst countries on average and that literacy rates have an impact on
it, whether significant or not. Moving forward, we then plotted a chart based off the economic
inequality in each country using the GINI index and countries with similar education systems
to South Korea and Finland. This is shown in Table 4.2:
13. 12
0.0
10.0
20.0
30.0
40.0
50.0
60.0
Countries with similar education
systems to Finland
Countries with
similar
education
systems to
Finland
Table 4.2
From Table 4.2, it seems that there is a positive correlation between education
systems and economic inequality. On the left, countries that displayed similar elements of
education to South Korea can be seen to have a higher GINI figure than compared with those
on the right. One interesting point to note would be that South Korea’s GINI figure is actually
comparatively lower than other countries with a similar education system. Our group has
theorized that it could possibly be due to the ‘globalization’ factor involved. Logically
speaking, countries that are more connected with other countries; possess strategic locations
and capabilities; have a rapidly growing economy should result in a higher GINI index in
relation to other countries as they become the focal point of investment from overseas
companies wanting to invest within the region. Demand for skilled local labour would then
cause income inequality to rise as talented, ‘global’ employees (people who know multiple
languages, widely travelled etc.) become highly sought after. As such, as a country becomes
more globalized, academic curriculums are also modified to adapt to changing circumstances,
which often results in harder tests and higher standards (as seen in countries with South
Korea’s education system) to promote investment inflows into the country for its highly
skilled workforce. In sum, education is key for these countries, where the nurturing of the
brightest talents is crucial for the country’s growth.
0.0
10.0
20.0
30.0
40.0
50.0
60.0
Singapore
China
India
UnitedStates
Korea,Rep.
HongKongSAR
Countries with similar education
systems to Korea
Countries with
similar
education
systems to
Korea
14. 13
Now that we have established that economic inequality is related to the education
structure, we also probed deeper and investigated if there were any repercussions in following
either structure. As stated previously, we decided to look into Singapore due to its heavy
emphasis on meritocracy. Do note however, that the data obtained was from year 1999 to
2002, as specific rankings for schools were then abolished in 2004 and replaced by banding;
the grouping of schools with certain grade requirements together.
Table 4.3
SecondarySchools Ranking Average GCE O Level Grades
1999 2000 2001 2002 1999 2000 2001 2002
Top 20 in1999
RafflesInstitution 1 1 1 1 7.9 7.9 7.8 7.8
RafflesGirlsSecondary 2 2 2 2 8.2 8.3 8.6 8.3
The Chinese High 3 4 3 4 8.9 9 8.6 8.5
NanyangGirlsHigh 4 3 4 3 9 8.6 9.1 8.4
DunmanHigh 5 5 5 5 9.2 9.6 9.4 10.1
CHIJ St.NicholasHigh 6 7 8 7 10.4 10.1 10.9 10.9
RiverValleyHigh 7 6 6 6 10.6 10 10.6 10.2
Singapore ChineseGirls 8 8 10 8 10.9 10.9 11.4 11.4
Anderson Secondary 9 11 13 13 11.5 12 11.6 12.4
Anglo-Chinese
(Independent) 10 10 9 9 11.5 11.5 11 11.5
MethodistGirls'Secondary 11 8 7 11 11.7 10.9 10.7 11.8
ZhonghuaSec 12 19 15 23 11.8 13.2 11.9 14.4
Victoria 13 12 19 17 12 12.2 13 13.2
AnglicanHigh 14 21 20 18 12.4 13.3 13.1 13.4
St. Joseph'sInstitution 15 16 16 14 12.7 12.8 12.3 12.6
ChungChengHigh(Main) 16 23 21 21 12.8 13.8 13.2 13.8
TemasekSec 17 24 23 30 12.8 13.9 13.5 15.6
CedarGirls' Sec 18 12 12 10 12.9 12.2 11.5 11.7
TanjongKatongGirls' 19 14 10 12 13 12.4 11.4 12.2
CrescentGirls' 20 17 18 16 13.1 13.1 12.8 13.1
As seen in Table 4.3 above, there has been little to no change among the top 8 schools
in Singapore from year 1999 to 2002. Based on the following figures, it seems safe to assume
that there is some existing form of differing educational opportunities, given that rankings
have differed much more when we look at the other 12 schools while students from the other
top 8 schools have consistently produced excellent grades. Moreover, as seen in Appendix 3,
grades, there has been little to no fluctuation in terms of admission grades amongst the
schools that have seen little variation in the rankings. Not only does this highlight the
importance and significance of the rankings for parents and students, it also implies differing
educational opportunities as students with excellent grades are always aiming for the same
15. 14
schools. However, Singapore is not the only exception in this respect; as seen in Table 4.4
below:
Table 4.4
Seoul National University
Years To be admitted Number of
applicants
2015 2,531 19,046
2014 2,816 19,990
2013 1,744 17,738
2012 2,496 20,137
2011 1,884 12,468
Korea University
Years To be admitted Number of
applicants
2015 2,986 68,783
2014 2,961 63,280
2013 2,881 71,743
2012 2,666 83,906
2011 2,646 78,645
Yonsei University
Years To be admitted Number of
applicants
2015 2,585 45,156
2014 2,637 45,685
2013 1,154 30,669
2012 1,154 32,392
2011 1,150 31,863
The table above displays the admission results for “SKY”, an abbreviation for the top
3 Korean universities, made up of the first letter of each university. As seen from the table,
acceptance rates are very low; and admission numbers vary depending on the demand for
each university. On the whole, however, SKY universities have experienced an increase in
number of applicants over the past few years, which also resulted in an increase in admission
numbers. However, the average grade for admission has largely remained unchanged;
students entering SKY have an average grade of 1.x, the equivalent of being within the top
10% in the National University Entrance Examination. Moreover, an interesting point to note
is that SKY universities have increased their admissions rate rather than reducing it further as
16. 15
demand increases. One plausible explanation for this might be that students within the top
10% category have scored very similar grades to one another, which forces the universities to
admit all of them due to the lack of other aspects of differentiation.
On the other hand, South Koreans who do manage to get in are guaranteed a bright
future; 38% of CEO's of top 100 Korean companies, 93% of judges in Supreme Court, 60%
of government ministers and about half of the members in National Assembly were Seoul
National University alumni in 2012 (Times Higher Education, 2013). This would adequately
explain the demand seen by these universities.
With that in mind, we conducted a search into the alumni list of Singapore’s top
schools and took note of the number of notable alumni each school had as shown in Table 4.4
below:
Table 4.5
School
Rankingin
2002
Notable
Alumni
RafflesInstitution 1 40+
RafflesGirlsSecondary 2 11
NanyangGirlsHigh 3 10
The Chinese High 4 30+
DunmanHigh 5 6
RiverValleyHigh 6 5
CHIJ St.NicholasHigh 7 2
Singapore ChineseGirls 8 7
Anglo-Chinese (Independent) 9 30+
CedarGirls' Sec 10 1
MethodistGirls'Secondary 11 5
TanjongKatongGirls' 12 3
AndersonSecondary 13 1
St. Joseph'sInstitution 14 20+
CrescentGirls' 16 1
Victoria 17 20+
AnglicanHigh 18 0
ChungChengHigh(Main) 21 1
ZhonghuaSec 23 0
TemasekSec 30 0
As seen from the table, one might say that with the exception of a couple of schools,
many notable alumni; including government officials, founders and CEOs of internationally
known corporations and government organizations are seen to be heavily weighted within the
17. 16
top 10 schools of Singapore. This all the more lends weight to the argument that differing
educational opportunities exist, given that parents are attracted by the “star-power” of such
individuals and are more than willing to send their kids to these schools. One good example
would be Anglo-Chinese (Independent), which was ranked ninth in year 2002. Due to its
huge number of notable alumni; the majority of which being in the active political scene of
Singapore, average admission grades have been steadily rising from year 2000 to 2003,
signifying the influence notable alumni have on parents’ and students’ decisions
Additionally, while South Korea has only gated education in the universal National
University Entrance Examination, Singapore has 3 such exams; the Primary Six Leaving
Examination, the GCE O-Levels, and the GCE A-Levels, with the PSLE usually defining a
child’s future as an exceptional grade would send the child on a through-train to university in
one of the best schools. This is not to say that students from other schools are unable to get
admitted at any of the top schools if they are not affiliated, however, it is extremely difficult,
given the different environment the student is in and the elitism culture within the top schools
that causes affiliated students to look down on students from non-affiliated ones.
In sum, it seems that countries having similar education systems to that of South
Korea have a tendency to reserve the best educational opportunities for the social and
meritocratic elite, while barely maintaining a minimum standard of competency for the
majority that satisfies global standards. On the other hand, Finland’s education system is
meant to target and support weaker and underprivileged students, providing them with the
assistance needed to interact with their peers.
While this marks the conclusion of our research, we would like to add that differing
educational opportunities come from other sources as well. One of which would was
mentioned here, but was not the focal point of our research, would be the globalization factor.
5) Your Recommendations to the Company/ies Selected
Thus far, we’ve concluded that advances in technology increase the need and
therefore demand for high-skilled workers. We’ve also recognized that the “creation” of
high-skilled workers and advances in technology are both fueled by educational institutions.
Having identified educational institutions as a stimulus to both of these factors, and
having observed that economic inequality is in part a play of the supply and demand of high-
18. 17
skill workers, we realized that by increasing the supply of skilled workers, the bargaining
power of said workers to negotiate higher wages could be in part mitigated.
In our efforts to identify how educational institutions affect the supply of high-skilled
workers, we turned the focus of this paper on educational systems and their emphasis on
either equality, or efficiency (meritocracy). What we found is that countries with schooling
focused on a highly productive yet smaller group of individuals experienced higher average
GINI coefficients; meanwhile, countries with schooling focused on equal educational
opportunities among students of differing educational capabilities experienced lower average
GINI coefficients. As a result, it’s safe to say that countries with schooling focused on
providing more students with a higher level of education versus countries focusing a
disproportionate amount of resources on educating a lesser, more “capable” group of
students, experience lower economic inequality.
As is such, we now turn to ask ourselves what, if anything, can organizations do to
reduce economic inequality?
Although this paper focuses on educational institutions, we believe we can broaden
the definition of “organizations” for the purpose of this paper to not just schools, but also
government, as well as non-governmental organizations including for-profits companies. In
other words, schools are not the only actor that can play a role in enhancing external
environmental factors, which as Sacerdote identified; contribute to 56% of the variance in
family incomes.
Before delving into the myriad of things organizations as defined above can do, there
is a very important, eye opening characteristic of economic inequality that must first be
addressed. Joseph Stiglitz argues in The Price of Inequality that, “‘market democracy is
incompatible with extreme inequality’. He contends that, ‘the market is at risk because
extreme differences of power make a mockery of the voluntary nature of market
transactions’.” (Allen Lane, 2012) Likewise, the International Monetary Fund (IMF) found
that inequality reduces overall economy growth as well as challenges basic democratic
principles and fairness. (David, Berg, Tsangarides, 2014) While the preceding observation
concerns a slightly more daunting outcome, both point to the same thing; economic inequality
when drastic enough results in mockeries of the voluntary nature of labor transactions until
one day the disadvantaged refuse to transact. Put more simply, economic inequality if not
curbed could be the impetus for a revolution, and at the least extreme market inefficiencies
19. 18
bad for both laborers and companies. Fortunately, the market has not – yet – reached such a
mockery, which could look something like the overthrowing of wealthy capitalists that Karl
Marx theorized in his “March of History”. (A Failed Vision of History, 2003) In order to
maintain the voluntary nature of market transactions, we’ve compiled a list of
recommendations for different organizations, or “Actors”, that we believe can help to
mitigate economic inequality as a result of Skill-Biased Technological Change (SBTC).
(Violante, NYU)
5.1) What can for-profit companies do?
Why do for-profits have a role in reducing economic inequality? Well, for-profits tend
to comprise the largest organizations in the world. These would be the Coca-Cola’s of the
world, the McDonald’s, Johnson & Johnson, Virgin, etc. The rising size of firms has been
identified as a causal factor of economic inequality. Studies show that, “In America, for
instance, the number of workers employed by the country’s 100 biggest firms rose by 53%
between 1986 and 2010; in Britain the equivalent figure is 43.5%” (The Bigger the Less Fair,
2015), therefore this section will focus on what large for-profits, that are typically also
Multinational Corporations (MNCs), can do.
We believe that for the majority of these global firms, recommending they implement
an operational change could be far-fetched. These companies have achieved the size and
economies of scale they possess thus far without drastic changes to their operational model
from third-party sources such as ourselves; therefore we propose something more familiar to
global companies, namely Corporate Social Responsibility (CSR) initiatives. CSR is defined
as a, “Corporate initiative to assess and take responsibility for the company's effects on the
environment and impact on social welfare. The term generally applies to company efforts that
go beyond what may be required by regulators or environmental protection groups.”
(Investopedia, 2007) This approach to socially conscionable actions on behalf of companies
has actually proven to increase shareholder value, more specifically the value of stocks,
especially in the three days following the publishing of a CSR initiative as seen in the
following table:
20. 19
Considering that companies can increase their stock value on average by 1.46% and
thus shareholder value with a CSR initiative, we believe this shared-value proposition makes
for a feasible attempt at getting a program going despite the typical bureaucratic nature of
these companies.
In light of wage-premiums for the skilled labor force as a result of favorable
educational opportunities during youth, we propose a company such as Apple or Microsoft
adopts a school or multiple schools. This could work as follows:
1) Apple/Microsoft identifies low-income underprivileged schools with a lack of
adequate computer technology.
2) Donate (for example sake) 20 computers to these schools. For the sake of this
example we’ll assume 10 schools. (200 computers in total)
For the students at these beneficiary schools, these computers will help to catalyze
their skill-based technical adequacy, making them more competitive in the marketplace and
21. 20
over-time increasing the supply of high-skilled workers, in-turn reducing the wage premium
high-skilled workers can negotiate. Not only does this reduce economic inequality as defined
earlier, but it also adds value to the firm both immediately (through stock-price increase) and
in the future (through an increase in profit). The example continues as follows…
Let’s assume that at each of the 10 high schools it donates a lab to, the company
estimates there is a 50% probability of generating additional sales of 100 computers (at the
average price) and a 50% chance of generating no additional sales from the school. For this
example, we will use the following financial assumptions of the company:
Given the above data and the probabilities aforementioned, we can calculate the effect
of this proposal on Apple/Microsoft’s pre-tax profits with 3 steps.
1) We first calculate the relevant cost.
200 𝑥 𝑈𝑛𝑖𝑡 𝑉𝑎𝑟𝑖𝑎𝑏𝑙𝑒 𝐶𝑜𝑠𝑡 = 200 𝑥 (50+ 50 + 36) = $27,200
; Where 50 is Direct Materials, 50 is Direct Labor, 36 is Variable Mfg. Overhead
22. 21
2) We then calculate the expected increase in revenue.
50% 𝑥 220 𝑥 100 𝑥 10 = $110,000
; Where 220 is Price Per Unit, 100 is Donated Computers, 10 is Number of Schools
3) We then calculate the cost of producing the computers.
50% 𝑥 100 𝑥 10 𝑥 136 = $68,000
; Where 100 is Donated Computers, 10 is Number of Schools, 136 is Total Variable Cost
4) We then observe the change in Net Income (profit).
$110,000 − $27,200 − $68,000 = $14,800
In conclusion, we see that donating computers to schools lacking in such technology
can not only serve to bridge the wage-premium gap of high-skilled workers to unskilled
workers, but it can also increase the firm’s pre-tax profit by $14,800 (assuming such
numbers) in the long-run and generate an increase in share price in the short-run. This
example was taken from NYU Professor Hao Xue’s Managerial Accounting course and
adapted for the following recommendation.
5.2) What can Government do?
Governments play a large role in the creation, facilitation and implementation of laws
and programs alike. As is such, we’ve identified some proposed legislations and ideas
governments can put forth to reduce the educational opportunity gaps, specifically related to
disparities amongst students’ access to technology that enable them to gain technological
competency.
In the context of economic inequality, the Occupy movement swept the U.S. media
shedding light on the 99% and 1% disparities. One of their proposed solutions to economic
inequality is to increase the minimum wage. Contrary to popular belief, increasing the
minimum wage makes a mockery of the voluntary nature of market transactions because at a
point, companies will stop employing young people that normally take low-paying jobs
because to the company, these employees are no longer worth the new minimum wage cost of
labor. As U.S. News describes it, “The harm done by minimum wage increases gets
compounded for young workers because it prevents them from gaining experience, thus
23. 22
increasing their chances of being unemployed in the future.” The chart below shows how an
increase in minimum wage policy causes a reduction in youth employment.
As is so, we recommend that governments do not impose a more stringent minimum
wage policy as this can lead to a decrease in the amount of youth employed, resulting in less
skills-training and a larger group of unskilled labor leaving the demand for high-skilled labor
high. (Slavov & Aspen, U.S. News) Looking forward we’ve identified two possible actions
the government can take to increase the amount of skilled labor in the workforce.
One such proposal is for the U.S. government to utilize the “National Report Card” as
a benchmark with which it can measure its level of spending on a per-student basis by state.
“The National Report Card (NRC) examines each state's level of commitment to equal
educational opportunity, regardless of a student's background, family income, or where she or
he attends school. Providing fair school funding -- at a sufficient level with additional funds
to meet needs generated by poverty -- is crucial if all students are to be afforded the
opportunity to learn and be successful. The NRC evaluates all 50 states and the District of
Columbia on four separate, but interrelated, funding "fairness indicators" -- funding level,
distribution, state fiscal effort, and coverage.” From here the government can work to
equalize its spending per-student across all 50 states and the District of Columbia to ensure
that each student is receiving similar educational opportunities, in-turn reducing the GINI
coefficient of the U.S. by acting more equitably. An example of a nation with a low GINI
24. 23
coefficient as a result of such an equitable system would be the aforementioned Finland.
Another such proposal is to impose, and in some cases increase inheritance tax.
Inheritance tax is defined as, “a percentage of the value of a decedent's estate transferred to
beneficiaries by will, heirs by intestacy and transferees by operation of law. The tax rate
varies depending on the relationship of the heir to the decedent.” (PA.gov) By imposing an
inheritance tax, or increasing it in societies where one is already in place, wealth captured in
the top-percentiles can be de-cumulated and redistributed to educational institutions, in
particular to early education where most economic inequality can be mitigated early on.
(Powell, Haas Institute)
As seen from the above info-graphic, the success of investments in early childhood
education can be measured be observing reductions in dropouts, and higher mean test scores.
25. 24
We believe that there are other metrics with which we can measure the effectiveness
of investments in early childhood education, however these are most appropriately looked at
in the context of what schools can do to help mitigate economic inequality. First though, it’s
important to identify how earnings from inheritance tax should be used. The Haas Institute
has identified two successful organizations that invest in early childhood education, namely
Head Start and Universal Pre-K. In lieu of the credibility of the Haas Institute, we too
recommend that proceeds from the increased/imposed inheritance tax be funneled into these
two organizations working to support youth educational opportunities.
5.3) What can Schools do?
It should come as no surprise that the very schools, in which economic inequality is
exacerbated due to a lack of proper resources, could play some form of an active role in
reducing this trend. Thus, we only saw it appropriate to advise schools on some methods
through which they could play an active role; methods that do not need additional resources;
and methods that are cognoscente of the fact that educators in low-income/underprivileged
schools are not necessarily top-notch instructors with great expertise. These
recommendations will be provided with data metrics with which they can be measured as
well as used to measure the effectiveness of the distribution of inheritance tax proceeds and
its effect on subject schools.
Johannes Haushofer describes his findings of the existing relationship between
poverty, time-discounting and risk-taking in the article “On the psychology of poverty”. What
he finds is that “Poorer households were more likely to choose smaller and earlier monetary
rewards over larger, delayed ones.” (Hausofer, E. 2014) To sum up Haushofer’s findings, the
state of poverty is enough to reduce the body’s production of the hormone cortisol, which is
essential to maintaining a state of mental homeostasis or in other words managing stress-
levels. Because the state of poverty is enough to cause a mental predisposition to stress, this
in turn leads to time-discounting and reduced risk-taking actions inherent to entrepreneurial
activity.
We can see the numerous ways in which this permeates the trials of the impoverished
teenager working to finish high school. The National Center for Education Statistics found in
a recent study that, “Low-income students fail to graduate at five times the rate of middle-
income families and six times that of higher-income youth.” (U.S. Department of Education)
Similarly, 12% of students in a recent report by Harris Interactive and Everest College
26. 25
indicated students dropped out of school to work and support their families. (Sheehy, U.S.
News) You may be wondering, ‘well how does this contribute to economic inequality?’
According to a recent earnings report by the Bureau of Labor Statistics, “Students without a
high school diploma also earn about 30 percent less than their peers who stayed in school.”
(U.S. BLS, 2015) From these eye opening statistics, it’s evident that the stress of being
impoverished causes risk-averse actions such as dropping out to support immediate family
needs. This makes perfect sense. The risk of defaulting on the mortgage and thus losing their
home and ending up in a homeless shelter or even worse on the street is more imminent a
threat than that of not having the wherewithal to sustain themselves in the future (i.e.
obtaining a college degree). This is the discouraging, perpetual effect of time-discounting
actions.
To mitigate these disheartening factors, we propose that schools introduce a number
of life-skill programs to provide students with the wherewithal to combat becoming a dismal
statistic. The life-skills we propose teaching are as follows:
1) Teach interview skills.
By teaching students interview skills, this can help them secure part-time jobs around
school that enable them to produce income for family needs without dropping out of
school to do so.
2) Teach time management skills.
Because working a part-time job around school is time consuming, it’s pivotal that
teachers arm their students with the proper knowledge of how to prioritize their
school work and outside work to make the most of their situations. A renowned time-
management tool is Stephen Covey’s Time-Management Matrix as seen below:
27. 26
(U.S. Geological Survey)
3) Teach personal finance skills.
Working a part-time job is great if the necessary money for family needs is actually
making it to the family. Because students will be in part supporting themselves and
the unmet financial needs of their households, it’s crucial they have a basic
understanding of personal-finances so they can make a disciplinary budget. A
renowned program for personal-finance is Dave Ramsey’s Foundations in Personal
Finance: High School Edition. (Daveramsey.com) This curriculum in personal-
finance needs no administrator, rather it is a series of educational yet entertaining
videos that can be watched on a computer, played in an auditorium or physically
distributed.
Through the culmination of these efforts, there should be an observed impact on the
reduction of the status-quo time-discounting and risk-averse tendencies plaguing low-income
schools. This impact should be measure and we anticipate it can be measured through the use
of the following metrics:
1) Reduced drop out rate.
2) Higher class attendance.
3) Higher levels of cortisol (if test subjects agree to testing for some monetary gain).
4) Higher average test scores.
28. 27
These tactics can be used in a pilot school and if there is an observed impact as we
anticipate there should be, it can be implemented in low-income schools anywhere in the
world, including Singapore.
6) What ShouldBusiness Schools’ContributionBe?
Business students at top universities will go on to fill pivotal roles in society such as
leading some of the largest, most influential companies in the world and directing
government policy that affects whole nations. The reach top-business students can and tend to
have is tremendous and as such they should be educated with the capability to make informed
decisions that can either reduce or increase economic inequality in our increasingly
interconnected global community. Together, we’ve indentified some recommendations we
believe business school administrators would be wise to consider. Namely, they are to
provide:
1) Good grounding in ethics.
“The proper role of ethical reasoning is to highlight acts of two kinds: those that
enhance the well being of others—that warrant our praise—and those that harm or diminish
the well-being of others—and thus warrant our criticism.” (Elder & Paul, 2011) Having such
a grounding provides business students with a formal lense through which they can evaluate
the social implications of the big decisions they will often go on to make for years to come.
2) Socially grounded missions.
We believe it is the responsibility of business schools to appropriate some of the
monetary resources students provide the school through large tuition payments to socially
grounded missions. This can include but is not limited to charitable events, volunteering time
at underpriveleged schools to either teach or provide necessary physical labor, or even
volunteering with social entrepreneurs.
3) Analytical skills on how to measure social impact using data metrics.
As business students are dispersed amongst companies heavily focused on their
bottom lines (i.e. profit), it’s important that just as students learn analytical skills in
operations, finance, personnel management and the likes, they also learn how to analyze and
measure the social implications of their executive decisions. This provides a data-driven
29. 28
framework with which to develop concrete evidence of social impact to complement the
ethical framework through which to perceive the implications of decisions.
4) Policy Classes.
Not every business student ends up working at a financial firm, in fact a considerable
number of students study economics and end up on the policy side of things. Taking this into
consideration, we feel its appropriate for business schools to provide some sort of
understanding of the process of policy making. This process can often be slow and
bureaucratic, therefore it would be especially useful for students to understand the lense of
policy-makers when proposing legislation or reform in order to help expedite the process of
benefical social policies.
5) Balancing Equity and Efficiency.
The observation of equitable wage distribution and the efficiency of workers in the
workplace have often been viewed as polarities. We understand the implications of this, and
believe that it is thus necessary to observe companies and/or case studies thereof highlighting
how striking a balance between equitable wages and efficient production of labor can be
more rewarding than either end of the spectrum.
Ultimately, we believe that by following the aforementioned recommendations for
governments, companies, schools and business schools, there is a fighting chance at reducing
some of the factors that lead to the wage premium for high-skilled workers in the labor
market. In doing so, we can see the slow return of capital to the demand side of the economy,
and the equitable dispersion of wages that should in turn reduce the perpetual effects of
income discrepencies compouding wealth accumulation in the top percentiles of the working
population. We hope that this paper has helped you grasp a clear, if not enhanced
understanding of economic inequality, the dynamic nature of the term, contributing factors,
and how they can be in-part mitigated through a careful, multi-faceted approach involving
multiple “actors” and their duties to societal equity.
30. 29
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Appendix A
Data Source
WORLD BANK GINI INDEX (%)
Country Name 2000 2002 2004 2005 2007 2008 2009 2010 2011
Countrieswith
similareducation
systemsto Korea
Singapore
China 42.6 42.48 42.63 42.06 37.0
India 33.38 33.9 33.6
UnitedStates 40.2 40.57 41.64 41.12
Korea,Rep.
Hong KongSAR
Countrieswith
similareducation
systemsto Finland
Norway 27.6 30.17 26.48 26.83
Sweden 27.5 26.08
Finland 27.2 28.27 28.2 27.79
Denmark 24.1 24.6 25.98 26.88
Data Source
CIA
GINI AVERAGE GINI
CountryName % Year %
Countrieswith
similareducation
systemsto Korea
Singapore 46.3 2013 46.3
China 47.3 2013 42.4
India 36.8 2004 34.4
UnitedStates 45 2007 41.7
Korea,Rep. 31.3 2011 31.3
Hong KongSAR 53.7 2011 53.7
Countrieswith
similareducation
systemsto Finland
Norway 25 2008 27.2
Sweden 23 2005 25.5
Finland 26.8 2008 27.7
Denmark 24.8 2011 24.9
