Globalization and Income Inequality: Comparative Analysis of 83

Countries

Yiming Li

1*,

Yue Xue

, Kaichen Song

and Silu Wang

business School, Jiangnan University, Wuxi 214122, China

Beijing-Dublin International College, Beijing University of Technology, Beijing, 100124, China

Milton International School, Qingdao, 266075, China

Seaview High School, Adelaide, SA5047, Australia

Keywords: Globalization, Income Inequality, Multiple Linear Regression.

Abstract:

The effect of globalization on income inequality is an issue of significant academic interest. On the one hand,

globalization is considered to promote global economic growth and social progress, while on the other, it is

blamed for growing income inequality and environmental degradation, causing social degeneration and

difficulty of competition. This paper aims to examine the impact of globalization on the inequality in rich/

middle/ poor economies. This study uses the least square method to establish a multiple linear regression

model, adding dummy variables. The results show that globalization indeed has varied impacts on the current

level of inequality around the world. The growth in the current globalization level will reduce the inequality

degree in rich/middle countries but rise the inequality degree in poor countries. We also find that there exists

an uneven impact of globalization on the inequality of rich countries and middle poor countries. For

middle/poor countries, this impact is even stronger.

1 INTRODUCTION

Globalization and its adverse effects are issuing that

human are commonly concern with. The regions of

the world are increasingly becoming a whole, with

unprecedented connection and dependence. No

country that wants to develop can ignore this trend of

globalization. However, Globalization is a global

trend and a state of gradual approach among all

countries, which is accompanied by a debate over

whether globalization is at the cost of inequality. An

obvious paradox of globalization is that the growing

global economic integration caused by globalization

leads more to social disintegration than social

integration. This article studies the relationship

between globalization and inequality through the

review of current research, using mathematical

modeling and data analysis.

2 LITERATURE REVIEW

This part will provide a brief overview of the debate

between inequality and globalization, which are two

main elements of this topic, namely the definitions of

inequality and globalization, the relationship and the

reasons why globalization causes inequality.

Although current studies on this issue cover a wide

variety of opinions, this paper will focus on three

major questions. To begin with, what are definitions

of globalization and inequality? Additionally, what is

the relationship between globalization and

inequality? Eventually, why globalization creates

inequality?

2.1 Definition of Globalization and

Inequality

Globalization refers to the global organic economic

whole of global economic activities beyond borders

through foreign trade, capital flow, technology

transfer, provision of services, interdependence and

interconnection, which is a political project that

operates under the increase of spatial connectivity,

driven by technological changes in transportation,

and produces new forms of national sovereignty that

promote more flexible and rapid rescheduling in

space (Ludden, 2012). It is explained that the reason

for globalization is dynamic and progressive vision of

capitalism’s worldwide expansion (Munck, 2011).

Economic globalization is an important trend of the

Li, Y., Xue, Y., Song, K. and Wang, S.

Globalization and Income Inequality: Comparative Analysis of 83 Countries.

DOI: 10.5220/0011186400003440

In Proceedings of the International Conference on Big Data Economy and Digital Management (BDEDM 2022), pages 471-482

ISBN: 978-989-758-593-7

471

world economic development in the contemporary

world.

In addition, because the concept of common

human beings is based on the acceptance of inherent

equality in mankind, inequality is a violation of

human rights and prevents billions of people from

realizing the comprehensive development of human

beings (Khondker, 2017).

It is depicted three kinds of inequalities that may

stand in our way of fully functioning human Being,

which interact with each other, namely vital

inequality, existential inequality and resource

inequality, including health, autonomy, income and

many items (Firebaugh, 2003). Khondker illustrates

that innequalities are socially generated and

maintained by systematic arrangements and

processes (Khondker, 2017). There appears to be a

consensus about the trends in inequality. According

to IMF in 2007, Income disparities increased mainly

in middle-to middle-income countries, while

decreased in low-income countries. This reflects the

growing differentiation between the countries out of

globalization, instead of growing integration

(Mills,

2009).

2.2 The Relationship between

Globalization and Inequality

Globalization is increasingly linked to inequality, but

with often divergent and polarized result.

Some researchers show that globalization

accentuates inequality both within and between

countries (Firebaugh, 2013), namely globalization

could lead to the decentralization of increased

personal income around the world, while others

arguing that globalization blurs the restrictions of

national boundaries, promotes economic integration,

improves the income level of the poor population, and

converges the wealth gap and narrowing the

inequality gap (Alderson, Nielsen, 2002). By

studying in a United Nations University study that

surveyed seventy-three countries in 2001, Munck

concludes that inequality among and within countries

has increased with globalization overall

(Munck,

2011)

. More importantly, Global polarization among

countries continues.

Globalization does not mean that every country

can benefit from it, it depends on international

institutions and rules (Alderson, Nielsen, 2002).

Under the current international system, the developed

and developing countries, as two different types of

countries, have the different impact of globalization.

Western developed countries are the dominant part of

economic globalization and can have more

advantages and gain more benefits in the process of

economic globalization

(Munck, 2011). Developed

countries have mastered the world's most advanced

productivity and new science and technology and are

in a dominant position in the global division of labor

system. Multinational corporations in developed

countries are an important promoter of economic

globalization and the main carrier to realize the flow

of global production factors and the optimal

allocation of resources (Firebaugh, 2003).

The internationally accepted system is dominated

by the developed countries. The international rules

largely reflect the characteristics of its domestic rules,

and there is no serious conflict with the foreign rules.

In short, globalization contributes to economic

growth in developed countries and reduces inequality.

In comparison, in terms of developing countries,

they are in a disadvantageous position in the current

process of economic globalization. As developed

countries are the leaders and promoters of economic

globalization and hold the initiative, most of the

existing international economic rules are formulated

and dominated by the developed countries (Wei,

2000). Meanwhile, Khondker emphasizes that due to

the unstable economic foundation of developing

countries, incomplete market development, relatively

weak economic structure, lack of funds and backward

technology, it is easy to suffer from the impact of

economic globalization and produce domestic

economic fluctuations (Khondker, 2017). In addition,

it is proposed that financial globalization brings

financial risks and economic impact that cannot be

ignored, while promoting the economic growth of

developing countries (Ludden, 2012).

2.3 The Reason Why Globalization

Causes Inequality

Mills and Blossfeld define Globalization as four

interrelated structural shifts that roughly occurred

since the 1980s of internationalization of markets and

declining importance of borders for economic

transactions, tougher tax competition between

countries, rising worldwide interconnectedness

through new Information and Communication

Technologies (ICTs), and the growing relevance and

volatility of markets, which may lead to inequality

(Mills, 2009, Wei, 2000).Furthermore, Mills et al. use

a flow chart to illustrate the process where

globalization affects inequality. That is, the impact of

globalization varies on the developed and developing

countries, which is consistent with Munck findings

(Munck, 2011, Mills, 2009).

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3 EXPLORATORY DATA

ANALYSIS

3.1 Globalization

Figure 1: Globalization in 2000.

Figure 2: Change in Globalization from 2000 to 2015.

Figure 1 shows the globalization in 2000, the darker

blue in the graph illustrates that country was more

globalized that year. The average globalization index

of these countries was 0.450. There are some outliers,

such as Belgium and Ireland, with globalization of

1.949 and 1.581 respectively. There are also some

countries that were basically not globalized, such as

Bhutan and Rwanda, both are quite small countries.

As shown in figure 2, orange indicates the level of

decreasing in globalization and blue indicates

Globalization and Income Inequality: Comparative Analysis of 83 Countries

473

increasing. Over this period, 68 out of 83 countries

had rising globalization. There are several outliers,

such as Malaysia, Yemen and Ireland. Some

significant decreasing trends could be seen in their

globalization level.

3.2 Income Inequality

Figure 3: Gini Index in 2000.

To explore income inequality, Gini coefficient was

adopted to indicates the inequality level. In figure 3,

the darker red illustrates the higher Gini index. In

2000, Gini index in the southern hemisphere is

generally higher than that in the northern hemisphere,

especially in South America, every country

researched had a Gini of over 50. Brazil with Gini of

58.41 at that time, Colombia was 58.68 and so forth.

The country with highest Gini was Haiti, with Gini of

59.48.

Figure 4: Change in Gini from 2000 to 2015.

During the period of 15 years, as shown in figure 4, the shade of the color represents the level of change

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in globalization over the period from 2000 to 2015,

green represents decreasing in Gini and red represents

increasing. Overall, the average Gini decreased by

1.49 and 50 out of 83 countries had falling inequality.

It is worth mentioning that Gini of countries in South

America all decreased and there are some outliers:

Burkina Faso -14.64, Gambia -12.60, Indonesia

+10.00, Benin +9.18, Ethiopia +9.09.

Figure 5: Gini index in 2015 of countries in each continent.

Figure 5 shows countries (country code) in

different continents, with their Gini coefficient in

2015. Overall, European countries have the lowest

Gini coefficient. Some countries in southern Africa

had very high Gini coefficients, such as South Africa,

Zambia. Despite the decreasing trends, countries in

South America still had relatively high Gini

coefficients.

3.3 Effects of Globalization

To explore the effects of globalization on countries

with different levels of development. Countries

selected are divided into three groups, rich, middling

and poor, based on their Human Development Index.

3.3.1 Effects of Globalization on Average

GDP

Figure 6: Rich Countries.

Globalization and Income Inequality: Comparative Analysis of 83 Countries

475

Figure 7: Middling Countries.

Figure 8: Poor Countries.

For rich countries (figure 6), the trend line shows

a negative slope, that indicates a rise in globalization

may lead to a smaller rise in average GDP for these

rich countries. There are some outliers, for example,

globalization in Luxembourg slightly decreased, but

its average GDP increased quite a lot. This illustrates

there are many other factors affecting average GDP

that need to be considered. For middling countries

(figure 7), the trend line also shows a negative slope

with an even lower R-Squared value. For poor

countries (figure 8), the trend line shows a negative

slope as well.

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3.3.2 Effects of Globalization on Inequality

Figure 9: Rich Countries.

Figure 10: Middling Countries.

Globalization and Income Inequality: Comparative Analysis of 83 Countries

477

Figure 11: Poor Countries.

For rich countries (figure 9), the Gini coefficient

of 16 out of 26 countries increased. The trend line

shows a slightly negative slope, that indicates a rise

in globalization may lead to a fall in inequality for

these rich countries. There are some outliers, for

example, as discussed previously, globalization in

Ireland decreased a lot, but the Gini coefficient also

decreased. For middling countries (figure 10), the

Gini coefficient of 34 out of 46 countries decreased.

The trend line also shows a negative slope. For poor

countries (figure 11), the Gini coefficient of 5

countries increased and the other 6 countries

decreased. The trend line shows a positive slope, that

indicates a rise in globalization may lead to a rise in

inequality for these poor countries. It is worth

mentioning that the R-squared values in all three

cases are small, that means change in globalization is

not explaining that much in the variation of change in

Gini and this will be discussed in later part.

4 MODEL BUILDING

4.1 Data Analysis

4.1.1 Modeling and Research Methods

In order to study the impact of the degree of

globalization on the degree of inequality in different

countries, we selected 83 countries which spread

across all continents. The variable globalization is

measured by adding import and export as a

percentage of GDP. We use the Gini coefficient to

measure the variable of inequality. And we add

income and inflation as control variables in our

model. We select the data of different indicators in

2000 and 2015 and get the change value of different

indicators between 2000-2015 as variables. Table 1

gives an insight into the definitions and sources of all

variables.

In order to better study the situation of countries

with different levels of development, we divided the

83 sample countries into three categories: rich

countries, middle countries and poor countries

according to their HDI index.

So, the regression model in algebraic form is as

follows:

()

()()

()

01 0 0 0

INQ GL Y INF DUM RICH

DUM MIDDLE DUM RICH GL

UM MIDDLE GL DUM RICH Y

UM MIDDLE Y DUM RICH INF

DUM MIDDLE INF

ββ β β β

ββ

βε

=+Δ+Δ+Δ + =

+= + =Δ

+= Δ+ =Δ

+= Δ+

The dataset studied in this project consists of 83

observations and 9 variables as follows:

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Table 1. Data dictionary.

Variable Notation Measurement Data source

Income inequality INQ Gini coefficient WDI,World Bank

Globalization GL |Share of import|+Share of export www.ggdc.net/pwt

Income Y Ln(GDP per capita) www.ggdc.net/pwt

Inflation INF GDP deflator: linked series (annual %) WDI,World Bank

Three categories

Divides all countries into three categories (rich; middle; poor) depend on HDI index.

Rich countries: HDI＞0.826

Median countries: HDI ≥ 0.5

Poo

countries: HDI < 0.5

4.1.2 Result Analysis

Table 2. Estimation Results.

Model without DUM Model with DUM

All countries Rich countries Middle countries Poor countries

constant

-4.34

(4.53)

2.55

(24.07).

13.17

(19.82)**

-39.41

(17.80)*

△GL

-0.36

(3.11)

-1.56

(13.39)*

-5.9162

(13.77)*

25.72

(12.66)*

△Y

0.34

(0.52)

-0.25

(3.06).

-1.80

(2.74)*

4.98

(2.54).

△INF

0.001

(0.03)

-0.22

(0.36)*

-0.02

(0.32).

0.52

(0.32)

R-Squared 0.006 0.18

Countries 83 26 46 11

Note: The standard error of each coefficient is in

brackets; the number above the brackets is the

coefficienof the independent variable.

Significant codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05

‘.’ 0.1 ‘ ’ 1.

By comparing the second and last three columns

of the table2, after adding dummy variable and

intersection, the significance of the variables have

been greatly improved, and our model fit better.

It is interesting to observe that the coefficient of

GL index, indicator for change in globalization, is

negative in all countries model, and in rich countries

and middle countries, but positive in poor countries.

The GL index is significant in each country. This

result shows that the impact of the degree of

globalization on the degree of inequality varies

among countries with different development levels.

The increase of globalization will cause the inequality

of poor countries to increase, but it will also cause the

inequality of rich countries and middle countries to

decrease.

Another interesting result to observe is the same

trends of the impact of change in capita GDP and

change in inflation on the change in inequality. For

poor countries, per capita GDP and inflation are in the

same direction as inequality. For rich countries and

middle countries, per capita GDP and inflation and

inequality change in the opposite direction.

4.2 Model Check

4.2.1 Regression Diagnostics

In model building we have chosen linear regression

model to estimate the relationship between change in

gini index which interprets the change in inequality (

△INQ) and other variables, in the model of linear

regression, checking whether it conforms to the

GaussMarkov assumptions is the preference.

In the early stage of building the model, we use

the summary function to repeatedly filter out three

explanatory variables which are change in

Globalization and Income Inequality: Comparative Analysis of 83 Countries

479

globalization (GL), change in income (Y) and change

in inflation (INF). And we decided to add dummy

variables in order to divide rich, middle and poor

countries and interaction transformations. From

checking the standardized residual plot, Obviously,

the Residuals vs Fitted plot (Figure.12) are basically

independent of the predicted values, this shows that

the linear hypothesis is rational. For checking the

normal distribution of errors, by looking through the

Q-Q plot (Figure.13) and histogram (Figure.14), we

can easily find that, most of observations are landed

close to the straight line except #53 and #80. Even

more clear in the histogram of Distribution of Errors,

the Normal Curve is almost coincided with the

standard normality curve - Kernel Density Curve.

Therefore, the assumption of normality is proved.

Figure 12: Residuals vs Fitted plot.

Figure 13: Q-Q plot

Figure 14: Histogram of Distribution of Errors.

Because of each data point is one unique country

in the world, the assumption of independence of

errors is reasonable. From observation of Scale -

Location plot (Figure.15) in order to check the

homoscedasticity assumption, the points are not

distributed around the horizontal line smoothly

concentrated in the middle to the left, this indicates

mild heteroskedasticity.

Figure 15 Scale-Location plot.

Figure 16: Cook’s distance.

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Figure 17: Index Plot of Hat Values.

4.2.2 Outlier Analysis

And Cook’s distance plot (Figure.16) and Index Plot

of Hat Values plot (Figure.17) show #75 data

observation which is Yemen (poor countries) has the

largest cook’s distance and hat values, there is a big

rise in Yemen’s inflation rate from 2000 to 2015

(22.924), it has the highest inflation rate among Arab

countries. According to common sense, inflation is

mostly caused by economic development, but

Yemen's economic development is so backward that

even food can not meet national needs. According to

the statistics, the Yemen’s government faced deficit

valued about 10 billion dollars. Since inflation will

lead to changes in income inequality to a great extent,

we may overestimate the impact of globalization on

income inequality.

From Q-Q plot (Figure.13) and the Scale-

Location plot (Figure.15), #80 which is Burkina Faso,

one of the least developed countries in the world and

a major exporter of migrant workers from

neighboring African countries. Economically, the

country is based on agriculture and animal husbandry,

accounting for nearly 80% of the country's labor

force. The country is short of resources and is located

on the edge of the desert with less arable land, we can

easily see the change of income inequality is the

highest among all the countries. Additionally, the

education in Burkina Faso is very weak, the literacy

rate is only 36%, as a result, the gap between the

skilled and unskilled labor is wide, this might be a

reason why income inequality is such serious.

Furthermore, the neonatal mortality rate is 60.9%,

and the poor with a daily income of less than US $1.9

account for 47.3% of the national population. This

may possibly cause overestimation the impact of

globalization on inequality.

However, we chose to keep the outliers. Firstly,

we are exploring the influence of globalization on

income inequality globally, each country is one

unique part in the globe. Moreover, the model after

deleting outliers, some explanatory variables are not

significant. The model with all the countries can

better reflect the objective situation.

5 DISCUSSION

5.1 Key Findings

We find out that globalization indeed has varied

impacts on the current level of inequality around the

world. But these impacts vary from different

countries: the growth in the current globalization

level will reduce the inequality degree in rich and

middle countries and rise the inequality degree in

poor countries. For poor countries, rise in per capita

GDP and inflation will causes increasing in

inequality. For rich countries and middle countries,

rise in per capita GDP and inflation will lead to

decreasing in inequality.

5.2 Theoretical and Empirical

Implications

Our research provides some useful findings for those

curious about the relationship between globalization

and inequality and allows people to make in-depth

research on this basis. It also reveals the limitations

of some indicators, such as GINI index.

And by studying the relationship between

globalization and inequality, a more powerful,

accurate and scientific basis for the government's

macro decision-making could be provided. The

government may be able to formulate policies based

on national conditions. This would be one of the

empirical implications.

5.3 Limitation

The obvious one would be the insufficient data size,

in other words, only 87 countries were selected due

to the incomplete data and limited time, but there are

totally 197 countries in the world. Another would be,

there are some missing values in data set, for

example, it’s hard to find all the type of data in all

countries such as HDI in small poor countries.

Also, Gini index shortcoming is one of the

limitations, they do not consider, for example,

whether income inequality changes because of the

rich becoming richer, the poor becoming poorer (or

Globalization and Income Inequality: Comparative Analysis of 83 Countries

481

both).

Some other limitations could be that it might be

necessary to explore non-linear relationships between

globalization and income inequality; and there could

be other measures for income inequality. As well as

we might try other ways of grouping, such as ‘divided

countries by continent’.

6 CONCLUSIONS

In conclusion, this study has evaluated how

globalization has contributed to inequality changes in

83 countries from 2000 to 2015. The results show that

globalization indeed has varied impacts on the current

level of inequality around the world. The growth in

the current globalization level will reduce the

inequality degree in rich/middle countries but rise the

inequality degree in poor countries. We also find that

there exists uneven impact of globalization on the

inequality of rich countries and middle/poor

countries. For middle/poor countries, this impact is

even stronger.

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