Shadow economy in the relationship with FDI, institutional quality, and income inequality, empirical evidence from asian countries

MINISTRY OF EDUCATION AND TRAINING
UNIVERSITY OF ECONOMICS HO CHI MINH CITY

HUYNH CONG MINH

SHADOW ECONOMY IN THE RELATIONSHIP WITH FDI,
INSTITUTIONAL QUALITY, AND INCOME INEQUALITY:
EMPIRICAL EVIDENCE FROM ASIAN COUNTRIES

PhD THESIS

Ho Chi Minh City – 2018


MINISTRY OF EDUCATION AND TRAINING
UNIVERSITY OF ECONOMICS HO CHI MINH CITY

HUYNH CONG MINH

SHADOW ECONOMY IN THE RELATIONSHIP WITH FDI,
INSTITUTIONAL QUALITY, AND INCOME INEQUALITY:
EMPIRICAL EVIDENCE FROM ASIAN COUNTRIES
Major:

Development Economics

Code:

9310105

PhD THESIS

Advisors:
1.

Dr. Nguyen Hoang Bao

2.

Dr. Nguyen Vu Hong Thai

Ho Chi Minh City – 2018


i

This thesis submitted to the School of Economics, University of Economics Ho Chi
Minh City, in partial fulfillment of the requirements for the degree of Doctor of
Philosophy in development economics.


ii

DECLARATION

I hereby declare that this thesis is my own research. Data and results are reliable,
clearly originated, and have never been published in any other study.

The author


iii

ACKNOWLEDGEMENTS

First of all, I would like to express my great gratitude to Dr. Nguyen Hoang Bao
and Dr. Nguyen Vu Hong Thai for their invaluable supervision and inspirations. Thank
you so much for keeping me on track throughout the research process, giving wise
comments, advices and encouragement during such a long academic journey.
Then I am honestly grateful to Dr. Pham Khanh Nam, Dr. Truong Dang Thuy,
Dr. Le Van Chon, Dr. Vo Tat Thang, Dr. Vo Hong Duc, Associate Pro. Dr. Nguyen Huu
Dung, Dr. Nguyen Luu Bao Doan, Dr. Pham Thi Thu Tra, Dr. Pham Thi Bich Ngoc,
Associate Pro. Dr. Vuong Duc Hoang Quan and the two independent Reviewers for
their valuable comments and encouragements so that I can improve the quality of my
thesis.
I cannot forget showing my special thanks to lecturers at school of economics as
well as those at University of Economics HCMC such as Professor Dr. Nguyen Trong
Hoai, Dr. Pham Khanh Nam, Dr. Truong Dang Thuy, Associate Pro. Dr.Nguyen Manh
Hung, Dr. Tran Thi Tuan Anh, Associate Pro. Dr. Tran Tien Khai… for their academic
and practical instructions during my time of study and research at the university.
Last but not least, I am deeply grateful to my beloved family, including my
deceased father, my 83-year-old mother as well as my sisters and brothers who always
support and encourage me in time for completing the thesis.


iv

TABLE OF CONTENTS

Declaration
Acknowledgements
Table of contents

List of Abbreviations
List of Tables
List of Figures
Pages
Chapter 1: Introduction................................................................................................................................ 1
1.1. Research context and gaps................................................................................................... 1
1.2. Research objectives................................................................................................................ 13
1.3. Research questions………………………………………………............................. 13
1.4. Research subjects and scope................................................................................................ 14
1.5. Research methodology and data …………………………………............................ 14
1.6. Contributions........................................................................................................................... 15
1.7. Limitations............................................................................................................................... 18
1.8. Thesis outline.......................................................................................................................... 18
Chapter 2: Literature review and hypotheses......................................................................................... 19
2.1. Shadow economy................................................................................................................... 20
2.1.1. Theories on shadow economy.................................................................................... 20
2.1.1.1. Definition............................................................................................................... 20
2.1.1.2. Schools of thought............................................................................................... 21
2.1.2. Empirical studies on shadow economy.................................................................... 31
2.1.2.1. Methods to estimate the size of the shadow economy................................ 31


v

2.1.2.2. Determinants (causes)
2.1.2.3. The impacts of shadow economy (effects)
2.2. Shadow economy, FDI and Institutional quality

35
40

44

2.2.1. FDI and institutional quality 44
2.2.1.1. Theories on FDI (Definition, Theories, Determinants)

44

2.2.1.2. Theories of institutional quality (Definition, Theories, Determinants)

47

2.2.1.3. The relationship between institutional quality and FDI

48

2.2.2. Institutional quality and shadow economy

54

2.2.2.1 The effect of institutional quality on shadow economy

55

2.2.2.2 The effect of shadow economy on institutional quality

57

2.2.3. Shadow economy and FDI

59

2.2.3.1 The effects of FDI and FDI-institutional quality interaction on shadow
economy

59

2.2.3.2 The effects of shadow economy on FDI

59

2.3. Shadow economy and income inequality

61

2.3.1. Income inequality

61

2.3.1.1. Definition

61

2.3.1.2. Theories

62

2.3.1.3. Measurements

65

2.3.1.4. Determinants 66
2.3.2. The impact of shadow economy on income inequality 67
Chapter 3: Methodology, model specifications, and data.................................................................. 73
3.1. Analytical framework

74

3.2. Empirical models and data

77

3.3. Econometric methodology

88

3.4. The sample selection of 19 Asian countries and their backgrounds on research
problems

93


vi

Chapter 4: Shadow economy, FDI and Institutional quality: empirical evidence from Asian
countries.......................................................................................................................................... 96
4.1. Introduction.............................................................................................................................. 96
4.2. Data analysis............................................................................................................................ 97
4.2.1. Data descriptive statistics............................................................................................ 97
4.2.2. Unit-root test.................................................................................................................. 99
4.2.3. Correlation analysis...................................................................................................... 101

4.3. Estimation results and discussions..................................................................................... 102
Chapter 5: The impacts of shadow economy on income inequality in developing Asia
113
5.1. Introduction.............................................................................................................................. 113
5.2. Data descriptive statistics..................................................................................................... 116
5.3. Empirical results and discussions....................................................................................... 119
Chapter 6: Conclusions and policy implications.................................................................................... 125
6.1. Conclusions.............................................................................................................................. 125
6.2. Policy implications................................................................................................................. 128
6.3. Limitations and further research implications................................................................. 129
List of publications........................................................................................................................................... 131
References............................................................................................................................................................ 132
Appendices.......................................................................................................................................................... 159


vii

LIST OF ABBREVIATIONS

2SLS:

Two-stage Least Squares

3SLS:

Three-stage Least Squares

ARDL
:

Autoregressive-distributed lag model

AR1:

Second-order Autocorrelation

AR2:

Error correction model

ECM:

Economic Freedom Report

EFR:

Foreign direct investment

FDI:

Fixed Effects

FE:

The Freedom House

First-order Autocorrelation

FH:
GCI:

Global Competitiveness Index

GDP:

Gross Domestic Products

GLS:

Generalized Least Squares

GNI:

Gross National Income

MENA:

Middle East and North Africa

MIMIC:

Multiple Indicators Multiple Causes

MNCs:

Multinational Corporations

HDR:

Human Development Report

HF:

The Heritage Foundation

ICRG:

The International Country Risk Guide

IEF:

Index of Economic Freedom


viii

ILO:

International Labor Organization

IMF:

International Monetary Fund

IQ:

Institutional quality

JGLS:

Joint Generalized Least Squares

OLI:

Ownership, Location, and Internalization

OLS:

Ordinary Least Squares

POLS:

Pooled Ordinary Least Squares

PRS:

Political Risk Services Group

RE:

Random Effects

SEM:

Simultaneous equation model

SGMM:

Two Steps System Generalized Method of Moments

SURE:

Seemingly Unrelated Regression

UNESCO:

United Nations Educational Scientific and Cultural Organization

UNCTAD:

United Nations Conference on Trade and Development

UNDP:

United Nations Development Programme

WB:

World Bank

WDI:

World Development Indicators

WEF:

World Economic Forum

WGIs:

Worldwide Governance Indicators


ix

LIST OF TABLES

Table 2.1. Labor market classification........................................................................................... 23
Table 2.2. Structure of informal work typology......................................................................... 29
Table 4.1. Summary statistics........................................................................................................... 98
Table 4.2. Unit root tests for all variables..................................................................................... 100
Table 4.3. The estimation results of the SEM by 3SLS and Two Steps System GMM
...................................................................................................................................................................... 103
Table 4.4. The effect of FDI on shadow economy..................................................................... 110
Table 5.1. Definition and summary statistics............................................................................... 118
Table 5.2. Final estimation results for the impact of shadow economy on income
inequality by FE and RE...................................................................................................................... 120
Table 5.3. Estimation results for the impact of shadow economy on income inequality
by 2 Steps SGMM.................................................................................................................................. 121


x

LIST OF FIGURES

Figure 1.1. Institutional quality by 5 components in Asian countries on average from
2002-2015 ................................................................................................................... 3
Figure 1.2. The size of shadow economy as a share of official GDP and FDI as the
percentage of GDP in Asian countries on average from 1999-2015 ..........................
Figure 1.3. Recent trends of income inequality in Asian developing countries .........

Figure 2.1. The place of institutions in the FDI determinants pattern ........................
Figure 2.2. The theoretical framework for the link between shadow economy and
income inequality ........................................................................................................
Figure 3.1. The analytical framework for the relationship among FDI, institutional
quality, shadow economy and income inequality .......................................................
Figure 5. The shadow economy and income inequality in Asian countries (1990-2015)
………………………………………………………………………………..

115


1

CHAPTER 1
INTRODUCTION
Chapter Outline

1.1.

Research context and gap

1.2.

Research objectives

1.3.

Research questions Research

1.4.

subjects and scope Research

1.5.

methodology and data

1.6.

Contributions Limitations

1.7.
1.8.

Thesis outline

1.1 Research context and gaps
1.1.1 Practical background
For recent decades, shadow economy, investment from abroad, institutional quality
and income inequality have attracted a great deal of attention in development
economics because all of them relate to economic growth. Both of foreign direct
investment (FDI) and institutional quality (IQ) are considered important determinants
of economic growth and development (Borensztein, Gregorio, & Lee, 1998; NairReichert & Weinhold, 2001; Rodrik, Subramanian, & Trebbi, 2004; Acemoglu,


2

Johnson, & Robinson, 2005; Hansen & Rand, 2006; Varsakelis, 2006; and Kandil,
2009); while the official economy is closely related to the shadow economy (Schneider
& Bajada, 2003; Vo & Pham, 2014). Moreover, economic growth is associated with

income inequality (Kuznets, 1955; Barro, 2000). Especially, these variables and their
relationships become worth studying in the context of Asia for its rising thorny
features, such as high flow of FDI but low institutional quality, large shadow economy
and rising income inequality.
First, global foreign direct investment has significantly grown since the 1970s,
reached $1.76 trillion in 2015, fell 13% in 2016 ($1.52 trillion) and recovered in 2017;
especially, developing Asia is now the largest recipient and accounts for almost onethird of total FDI inflows (UNCTAD, 2017). It is seen as the result of Asian countries
in effort to attract FDI for economic development by adopting an open door policy,
governance changes & institutional innovation (Haggard, 2004; Lee, 2002). However,
the positive impact of FDI on economic growth depends on the institutional quality in
the host countries (Brahim & Rachdi, 2014; Jude & Levieuge, 2017). It is also Asia’s
specific concern, especially when there are many countries might be stuck in middle
income trap in the region and deficient institutional quality is one of the main causes
(Dollar, 2015). Figure 1.1 describes the institutional quality by 5 components
(including Voice and Accountability, Political Stability and Absence of Violence,
Government Effectiveness, Regulatory Quality, and Rule of Law) in 19 Asian
1

countries on average from 2002-2015. The scale of measurement ranks from -2.5
(lowest quality) to 2.5 (highest quality). In general, the institutional quality in Asian
countries is low. The improvement has been seen but it is a slow progress. FDI has
flowed into Asian countries in great amounts, but institutional quality is still
1 Including Bangladesh, Bhutan, Cambodia, China, India, Indonesia, Kazakhstan, Kyrgyzstan, Laos,

Malaysia, Maldives, Mongolia, Myanmar, Nepal, Pakistan, Philippines, Sri Lanka, Thailand, and Vietnam.


3

problematic in the region. Whether institutional quality really helps attracting FDI and

FDI in its turn helps improving institutional quality. Does this bidirectional relationship
exist in Asian countries?
0
2002
-0.1
-0.2
-0.3
-0.4
-0.5
-0.6
-0.7
-0.8
-0.9

Figure 1.1. Institutional quality by 5 components in Asian countries on
average from 2002-2015.
(Source: Worldwide Governance Indicators, World Bank, 2017b)
Second, the shadow economy problematizes policy-makers in Asia, because the
size of the shadow economies in Asian countries has grown considerably since 1989,
suggesting that national accounts data is on average significantly underestimated as
national accounts are not supposed to capture shadow economies (Bajada and
Schneider, 2005). The estimated average size of shadow economy in Asian countries
over 1999 to 2015 is 30.94 % of official gross domestic products (GDP), and this
period experiences an increase of 10.24% in the shadow economy size (Medina &


Schneider, 2018). The lowest and the highest sizes are 29.04% and 33.41% in 2006 and
2009 respectively. The size of shadow economy in Asian countries is empirically

4

attributed to the money demand, tax burden, private consumption, interest rate and
Gross National Income (GNI) per capita (Bajada & Schneider, 2005; Vo et al., 2015).
The presence of shadow economy distorts the allocation of resources, alters income
distribution and reduces governments’ tax revenue (Alm & Embaye, 2013). If we
ignore this sector, it is biased to evaluate the consequences of various economic
policies. Thus, it is imperative to comprehensively understand about the shadow
economy in Asia in relation with other variables such as FDI and institutional quality.
Whether FDI is a channel to improve institutional quality and the improvement in
institutional quality helps reduce shadow economy when institutional quality is a driver
of shadow economy? The figure 1.2 shows the shadow economy and FDI in Asian
countries on average from 1999-2015.
35.06
34.0
economy(%ofGDP)

33.0

5

32.04
31.0

Shado
w

30.0

3

29.02
27.0
28.0

1

26.00
1999200020012002200320042005200620072008200920102011201220

Figure 1.2. The size of shadow economy as a share of official GDP and FDI as
the percentage of GDP in Asian countries on average from 1999-2015.
(Source: World Bank, 2017a; and Medina & Schneider, 2018)


5

Third, recent rapid economic growth in Asia has reduced poverty but widened
income gap in many countries. To Zhuang, Kanbur, and Maligalig (2014), the Asiawide Gini index rose at an annual rate of 1.4% from 0.39 in the mid-1990s to 0.46 in
the late 2000s; 14 of 37 Asian economies now have a Gini coefficient of 0.40 or
greater, widely considered the threshold for “high inequality”. However, the
comparison between the two periods of mid-1990s and around-2012 shows that the
average Gini index for 19 developing Asian countries decreases by 5.22%. This
improvement in income inequality mostly came from Central Asian countries such as
Kyrgyz Republic, Kazakhstan, and Maldives. Gini indexes were also seen falling in
Cambodia, Thailand, Nepal, Malaysia and Mongolia. On the contrary, China, Indonesia
and India - covering 82% of the population in the region- experienced a rapid rising
income inequality with their increases in Gini indexes by 18.8%, 14.9% and 14.1%
respectively. The income inequality was also found rising in Sri Lanka, Laos, Pakistan,
Vietnam and Tajikistan. The figure 1.3 provides the recent trends of income inequality

in 19 Asian developing countries.
60
50
40
30
20
10
0

Gini index


6

Figure 1.3. Recent trends of income inequality in Asian developing countries
(Source: World Bank, 2017a)
The rising inequality matters for many reasons. First, highly unequal societies
with the concentration of wealth on the rich are less likely to consolidate democracy,
and may end up with social unrest or even coups (Acemoglu & Robinson, 2001).
Second, it hampers the pace at which growth enables poverty reduction (Ravallion,
2004). Third, the inequality undermines the growth process through many channels of
economic, social, and political mechanisms; it negatively affects growth and its
sustainability (Ostry, Berg, & Tsangarides, 2014). Fourth, income inequality causes low
quality of institutions- one of key factors for development (Chong & Gradstein, 2007b;
and Zhuang et al., 2010); and excessively high levels of inequality erode institutional
quality even in democracies (Kotschy & Sunde, 2016).
From the practical background above, there is a need to study the relationships
amongst these variables so that policy makers can be provided with empirical studies
for their decision-making in dealing with these aggregate variables simultaneously.
However, the motivation for carrying out this study is arisen not only from the practical

background but also from the theoretical background.
1.1.2 Theoretical background
FDI, institutional quality and shadow economy
The failure in explaining economic phenomenon by one theory has led to the
tendency of using an integrative approach to bring insights in recent decades (Torgler
& Schneider, 2009). In fact, FDI is long documented as the main driver of host
countries’ economic growth (Borensztein et al., 1998; Nair-Reichert & Weinhold,
2001; and Hansen & Rand, 2006), while the emerge of the new institutional economics
in recent decades gets a great deal of attention from economists (Kotschy &


7

Sunde, 2016; Neyapti & Arasil, 2016). On the other hand, a vast literature has
attempted to study the shadow economy, especially from the transformation of the
socialist economies such as China, Russia, and Vietnam in 1990s where institutional
weaknesses and corruption are major obstacles to their market reforms (Gupta & Abed,
2002; Torgler & Schneider, 2009). Knowing the unknown and estimating the shadow
economy are still a difficult task that has posed notable challenges in statistical studies
in the past decades (Torgler & Schneider, 2009). Fortunately, the availability of shadow
economy’s dataset re-highlighted the interests of economists into the relationships
between shadow economy and other factors from both sides of economics and
institutions (Gupta & Abed, 2002).
The nexuses between FDI, institutional quality and shadow economy can be
divided into three strands with ambiguous relationships. In the first strand, the
relationships between FDI and institutional quality are concentrated, following
theories of international trade and institutions. In particular, Dunning (1980) uses the
eclectic paradigm, also known as the OLI-Model or OLI-Framework, to explain the
various reasons why a multinational corporation (MNC) enters into a host country. To
him, an MNC decides to invest in the host country when advantages of OLI

(Ownership, Location, and Internalization) are met. In this context, governance and
institutions can be seen as a location factor that may encourage or deter the investment
inflows. Similarly, North (1990) with the institutionalization theory shows that
institutions set “the rule of the games” which organizations and MNCs must follow in
pursuit of their own learning and goals for resource allocation. To him, institutions
affect uncertainty level and allow individuals and firms interact effectively. To attract
investments, governments improve their governance to lower transaction costs in
which investors might get higher profitability. In addition, Westney (1993), by using a
framework of MNCs theory, explores the potential significant role of MNCs in


8

improving the organizational patterns in host countries through subsidiaries. Thus, to
the above theories, institutional quality is a key determinant of FDI and FDI in its turn
helps improve institutional quality in the host country. However, He (2006) with the
Pollution Haven Hypothesis suggests that the motives of some FDI firms are to find a
place to hide pollution, and developing countries with lax environmental regulations is
the destination for these businesses. By this view, low institutional quality will attract
polluting FDI firms.
Most of studies argued the role of institutional quality in determining FDI inflows
with three categories: i) FDI is positively affected by institutional quality represented
by single indicators such as transparency (Zhao et al, 2003), democratic accountability
(Busse & Hefeker, 2007), intellectual property rights and contract enforcement (Du et
al, 2008), political rights and civil liberties (Tintin, 2013); ii) There is no impact of
institutional quality on attracting FDI (Kandil, 2009; Bellos & Subasat, 2011; Farla et
al., 2014; and Iloie, 2015); and iii) the new argument, especially in the case of China’s
outward FDI, is found that the low institutional quality attracts higher FDI inflow (Fan,
Morck, Xu, & Yeung, 2009). Meanwhile, the feedback effect of FDI on institutional
quality of host countries has received less attention from researchers. Larrain &

Tavares (2004) find that FDI significantly reduces corruption levels. Long, Yang, &
Zhang (2015) find the same results on the effects of FDI inflows on institutional
quality. However, the bidirectional relationship between FDI and institutional quality is
largely ignored except by a few including Fukumi & Nishijima (2010) for Latin
America & the Caribbean, and Shah et al. (2015) for Pakistan. Then what is the
bidirectional relationship between FDI and institutional quality in Asian countries and
is it illustrated by the Eclectic paradigm (Dunning, 1980), the Institutionalization
theory (North, 1990), the MNCs theory (Westney, 1993), or He (2006) with the
Pollution haven hypothesis? It is an empirical gap needed to fill, giving policy-makers


9

with evidences to consolidate their decision on FDI attraction and institutional
innovation. If FDI inflows and institutional quality have a positive nexus (as supported
by Dunning, 1980; North, 1990; and Westney, 1993), governments can combine the
policies to deal with FDI and institutional quality at the same time to take the
advantage of this causal relationship. Otherwise, environmental regulations should be
adjusted to limit polluting FDI firms if Asian countries confirm the Pollution haven
hypothesis (proposed by He, 2006).
The second strand focuses on institutional quality as a driver of shadow economy,
basing on Legalism school of thought on the informal economy. Following this view,
better institutional quality reduces the shadow economy because of two reasons: i)
better institutional quality lessens the burden of regulations and procedures - the main
cause that explain why people participate in informal activities - and thus lowers
shadow economy (Demsetz, 1974; ii) better institutional quality reveals informal
transactions which consequently turn official and hence reduces shadow economy (De
Soto, 1989, 2000). The negative impact of institutional quality on shadow economy is
empirically confirmed by Johnson et al. (1998); Friedman et al. (2000); Fugazza &
Jacques (2003), Torgler & Schneider (2009), Dreher et al. (2009), Dreher & Schneider

(2010), Singh et al. (2012), Razmi et al. (2013), and Hassan & Schneider (2016). There
is no study on the feedback effect of shadow economy on institutional quality.
However, this theoretical and empirical gap needs to be filled for 2 reasons: i) if the
feedback effect of shadow economy on institutional quality is found, Legalism theory
may be modified in the view that institutional quality is not only the cause but also the
consequence of shadow economy; and ii) studies on this relationship should take the
endogeneity problems into consideration. To fill this gap, I argue that shadow economy
reduces the tax revenue and falling tax revenue diminishes government income which
leads to less capacity to provide public goods with high quality.


10

The third strand examines the linkage of FDI and shadow economy. To the best of
my review, this strand is represented by three studies by Nikopour et al. (2009),
Davidescu & Strat (2015) and Ali & Bohara (2017). The result from Nikopour et al
(2009) indicates that higher FDI reduces shadow economy. However, Nikopour et al.
(2009) do not explain through which channels that FDI can negatively affect shadow
economy. Similarly, Davidescu & Strat (2015) find a negative unidirectional short-run
causality that runs only from FDI to the shadow economy in the case of Romania.
Meanwhile, Ali & Bohara (2017) confirm that higher shadow economy increases FDI
inflows since MNCs take advantages of tax evasion in host countries with higher size
of shadow economy. However, this bidirectional nexus needs to be further re-examined
for both theoretical and empirical aspects for 2 reasons. First, it is imperative to
research through which channels that FDI can affect shadow economy as well as
shadow economy can affect FDI. Second, policy makers in Asia will be provided by
empirical results to deal with FDI and shadow economy simultaneously whereas FDI
inflows contribute to economic growth (Borensztein et al., 1998; Nair-Reichert &
Weinhold, 2001; and Hansen & Rand, 2006), but shadow economy is regarded as one
of the major threats of development (Friedman et al., 2000; Ihrig & Moe, 2004; Alm &

Embaye, 2013; and Porta & Shleifer, 2014). Taking institutional quality into the
bidirectional relationship between FDI and shadow economy is the contribution to the
third strand by combining the three theories including international trade,
institutionalization and Legalism. It is argued that FDI can reduce shadow economy
through the channel of institutional quality improvements resulted from FDI inflows;
and higher shadow associated with lower institutional quality which may discourage
FDI inflows. Besides, FDI inflows may have potential impacts on shadow economy by
other channels such as creating jobs and increasing the official economic growth.


11

As argued above, though FDI, institutional quality and shadow economy are intercorrelated and even inter-dependently, their mutual relationships remain the gap in the
literature. This gap is imperative to be filled in because of two reasons. First, studying
on this mutual relationship formulates the mechanism in which these variables interact
to foster economic growth, by using an integrative approach of combining three
relevant theories. Second, FDI, institutional quality and shadow economy attract great
attention from policies makers because all of them are closely associated with
economic growth and development. The demonstrated results of their mutual
relationships indicate that policies to tackle any one of them can affect the other two at
the same time, and governments need empirical evidences to consolidate their policymaking on dealing with these aggregate variables simultaneously.
Shadow economy and income inequality
The shadow economy attracts researchers on studying not only its causes but also
its effects. The shadow economy has an impact on many variables such as the labour
market (Voinea and Liviu-Albu, 2011; Castells & Portes, 1989; Portes & Benton,
1984); the productivity (Friedman et al., 2000; Ihrig & Moe, 2004; La Porta & Shleifer,
2014); economic growth (De Soto, 1989; Johnson et al., 1997; and Loayza, 1997); and
poverty (Kim, 2005; Nikopour & Habibullah, 2010; and De Martiis, 2014). However,
attempts to investigate the impact of shadow economy on income inequality are still
scarce. Rosser et al. (2000, 2003), by macroeconomic approach of using empirical data

for 16 transition economies between 1987 to 1989 and 1993 to 1994, conclude with
caution that there is a positive relationship between the degree of income inequality
and the size of the informal economy. An increase in inequality causes more informal
activities due to the decline in social solidarity and trust, and expanding informal
activities lead to more inequality because of falling tax revenues and weakened
redistributive policies.


12

However, I propose new arguments in this thesis that shadow economy has a
negative impact on income inequality by combining three schools of thought on
shadow economy, including Dualism, Legalism and Voluntarism, with two theoretical
points as follows. First, Dualists with the residue theory depict the shadow economy as
a set of survival activities performed in a marginal society, generating income for the
poor (Hart, 1973; Sethuraman, 1976; and Tokman, 1978). Although the classical theory
of distribution concludes that income inequality increases in the process of economic
growth because the expanding industrial sector absorbs the labor force surplus from the
agriculture without increasing wages; classical economists did not forecast that
marginal people who cannot be absorbed in the industrial sector may work
underground, and increase their income by this way. Thus by taking point into account,
the shadow economy is expected to increase the income share of the poor. Second,
Legalists and Voluntarists with the alternative theory of shadow economy contend that
the rising shadow economy creates unfair competition for businesses and employees
between the formal and informal sectors (Chen, 2012). Nevertheless, this unfair
competition between the two sectors eventually turns out to be a channel to help reduce
income inequality because to dual approach, shadow economy attracts most of the poor
and small businesses, but not the rich and big businesses. Therefore, the unfair
competition from shadow economy may reduce the income share of the rich as the poor
get more benefit from working underground. As a result, the shadow economy may

lessen the income inequality. This new argument needs to be empirically confirmed in
the context of Asia for two reasons. First, if this negative affect is demonstrated, the
research will extend theories in the context of Asian developing countries on the
positive effects of shadow economy in the literature. Second, the result may provide
policy-makers with empirical evidences that policies to deal with the shadow economy
should take the poor into close consideration with other simultaneous solutions for
poverty eradication and income inequality reduction.