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 .....................................................................
13
1.5. Research methodology and data ………………………………… ...........
14
1.6. Contributions .............................................................................................
15
1.7. Limitations ................................................................................................
17
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) ...............................................................
35
2.1.2.3. The impacts of shadow economy (effects) ................................
40
2.2. Shadow economy, FDI and Institutional quality ....................................
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 ............................................................................................................
130
References ...........................................................................................................................
131
Appendices ..........................................................................................................................
158
vii
LIST OF ABBREVIATIONS
2SLS:
Two-stage Least Squares
3SLS:
Three-stage Least Squares
ARDL:
Autoregressive-distributed lag model
AR1:
First-order Autocorrelation
AR2:
Second-order Autocorrelation
ECM:
Error correction model
EFR:
Economic Freedom Report
FDI:
Foreign direct investment
FE:
Fixed Effects
FH:
The Freedom House
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 .......................... 4
Figure 1.3. Recent trends of income inequality in Asian developing countries ......... 5
Figure 2.1. The place of institutions in the FDI determinants pattern ........................ 49
Figure 2.2. The theoretical framework for the link between shadow economy and
income inequality ........................................................................................................ 70
Figure 3.1. The analytical framework for the relationship among FDI, institutional
quality, shadow economy and income inequality ....................................................... 74
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
1.4.
Research subjects and scope
1.5.
Research methodology and data
1.6.
Contributions
1.7.
Limitations
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
countries1 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
-0.1
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Government Effectiveness
-0.2
-0.3
-0.4
Political Stability
Regulatory Quality
-0.5
-0.6
-0.7
Rule of Law
Voice and Accountability
-0.8
-0.9
Government…
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.
35.0
6
34.0
5
32.0
4
31.0
3
30.0
29.0
2
FDI (% of GDP)
Shadow economy (% of GDP)
33.0
28.0
1
Shadow
economy
27.0
FDI
26.0
0
19992000200120022003200420052006200720082009201020112012201320142015
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
Gini index
50
40
30
Gini
1990s
20
10
0
Gini
around
2012
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
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