The mutual effects of shadow economy and financial development in ASEAN countries

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SCHOOL OF ECONOMICS
UNIVERSITY OF ECONOMICS
HO CHI MINH CITY
VIETNAM
INSTITUTE OF SOCIAL STUDIES
ERASMUS UNIVERSITY ROTTERDAM
THE HAGUE
THE NETHERLAND
VIETNAM - THE NETHERLANDS PROGRAMME FOR M.A.
IN DEVELOPMENT ECONOMICS
THE MUTUAL EFFECTS OF SHADOW ECONOMY AND
FINANCIAL DEVELOPMENT IN ASEAN COUNTRIES
by Nguyen Hoang Phu
A thesis submitted in partial fulfilment of the requirements for
the degree of
Master of Art in
Development Economics

VIETNAM - THE NETHERLANDS PROGRAMME FOR M.A. IN
DEVELOPMENT ECONOMICS
THE MUTUAL EFFECTS OF SHADOW ECONOMY AND
FINANCIAL DEVELOPMENT IN ASEAN COUNTRIES
by Nguyen Hoang Phu
A thesis submitted in partial fulfilment of the requirements for
the degree of
Master of Art in
Development Economics
Academic Supervisor:
Dr. Pham Thi Thu Tra

DECLARATION
I hereby declare that my dissertation entitled “THE MUTUAL EFFECTS OF
SHADOW ECONOMY AND FINANCIAL DEVELOPMENT IN ASEAN
COUNTRIES” is the result of my own work and includes nothing which is the outcome
of work done in collaboration except as declared in the Preface and specified in the text.
I also confirm that:
This thesis was done wholly while in candidature for a research degree at
VNP;
Where any part of this thesis has previously been submitted for a degree
or any other qualification at VNP or any other institution, this has been
clearly stated;
Where I have consulted the published work of others, this is always
clearly attributed;
Where I have quoted from the work of others, the source is always given.
With the exception of such quotations, this thesis is entirely my own work,
and I have acknowledged all main sources of help.
Date: January 02, 2018 Signature .....................................................
Full name: Nguyen Hoang Phu

ACKNOWLEDGEMENT
This thesis cannot complete without the support of my supervisor, Dr. Pham Thi
Thu Tra, who has spent the value time, efforts, and energy to guide me on the thesis
during the time of completing the thesis. Her dedication made me motivated when I
have a chance to discuss with her, her expertise is what makes me impressive when I
ask her questions about my thesis’s topic, and she also kept me in the “can – do”
attitude when I faced any difficulties in doing thesis. All of these leave me with the
most unforgettable memory and experience. My purpose of this acknowledgement is
to express my gratitude to my supervisor. Without her supports, I may not have a
chance to pursue my dream.
I would like to send my special thanks to Prof. Nguyen Trong Hoai, Dr. Pham
Khanh Nam, Dr. Truong Dang Thuy for their valuable command, guidance and
support during the program. Without your support and encouragement, I may not
complete the thesis as expected.
Additionally, my thanks are given to all of the lectures who have been my
knowledge guiders and the staff who have been my service supporters throughout the
master program at University of Economics and Erasmus University Rotterdam.
Without their help, never can I have an opportunity to proceed and complete my
master thesis.
Last but not least, I would like to thank Mr. Nguyen Cong Thanh, Truong Thi
Thu May and my family who have always been a pillar for me to rely on during the
hardships of attempting to achieve the master thesis. It is their unspoken sacrifice and
untiring work that bring me more spare time to be able to reach the final destination of
my progress.

ABSTRACT
This study focuses on examining the mutual relationship between financial
development and shadow economy by applying the theoretical and empirical
framework. Our research contributed to the way of calculating the size of shadow
economy applied the currency demand approach with updated data from 1997 to 2015
for 8 ASIAN countries. In particular, to have a robust result, we used 4 estimation
methods including POLS, FEM, REM and SGMM to calculate the value of the size of
shadow economy of each country. Then, we took each received results to examine the
mutual effect with the financial development using P – VAR approach. We found that
when the positive shock caused by the financial sector affects the shadow economy,
the shadow economy will immediately respond negatively to the shock. On the other
hand, when a positive shock caused by credit for private sector will lead to the
positive responses of the shadow economy. Interestingly, in this case, the response
tends to last longer with the estimated results from static model of shadow economy in
comparison with dynamic model of shadow economy.
Keywords: Shadow economy, financial development
JEL classifications: G32, H26

TABLE OF CONTENTS
Chapter 1: Introduction...............................................................................................................11
1.1. Problem statements....................................................................................................11
1.2. Research objectives ...................................................................................................13
1.3. Scope of the study .....................................................................................................14
1.4. Structure of the thesis................................................................................................15
Chapter 2: Literature review.......................................................................................................16
2.1. Review of theory .......................................................................................................16
2.1.1. The theory of shadow economy............................................................................16
2.1.2. The review on financial development theories.....................................................21
2.2. Review of empirical studies on the relationship between financial development
theory and shadow economy theory .................................................................................................27
2.3. Summary ...................................................................................................................31
Chapter 3: Research methodology..............................................................................................34
3.1. Analytical framework................................................................................................34
3.2. Econometric models..................................................................................................36
3.3. Data ...........................................................................................................................40
3.4. Variables and sampling .............................................................................................40
Chapter 4: Research results.........................................................................................................42
4.1. Overview of the research topic..................................................................................42
4.2. Descriptive statistics..................................................................................................44
4.3. Regression results and discussions............................................................................45
Chapter 5: Conclusions...............................................................................................................55
5.1. Conclusions ...............................................................................................................55
5.2. Limits of the study.....................................................................................................56
Reference ....................................................................................................................................58
Appendices .................................................................................................................................65

LIST OF TABLES
Table 1: Descriptive Statistics for the whole dataset......................................................44
Table 2: Matrix of correlation coefficients.....................................................................44
Table 3: Estimated results of currency demand model...................................................46
Table 4: Optimal model selection tests...........................................................................47
Table 5: Estimated value of Shadow economy over GDP .............................................48
Table 6: The results of Unit Root Test ...........................................................................49

LIST OF CHARTS
Figure 1: Conceptual framework of shadow economy and financial development.................31
Figure 2: The technical structure to deal with data..................................................................34
Figure 3: The analyzed results of impulse response function when the size of shadow
economic creates a shock with the estimated value of shadow economy from the
static models (POLS, FEM, REM) ...........................................................................51
Figure 4: The analyzed results of impulse response function when the size of shadow
economic creates a shock with the estimated value of shadow economy from the
dynamic models (SGMM) ........................................................................................52
Figure 5: The analyzed results of impulse response function when the financial development
creates a shock with the estimated value of shadow economy from the static models
(PLOS, FEM, REM) .................................................................................................53
Figure 6: The analyzed results of impulse response function when the financial development
creates a shock with the estimated value of shadow economy from the dynamic
models (SGMM))......................................................................................................54

LIST OF APPENDICES
Appendix 1: Shadow economy estimation using POLS..........................................................65
Appendix 2: Shadow economy estimation using FEM............................................................65
Appendix 3: Shadow economy estimation using SGMM........................................................66
Appendix 4: Shadow economy estimation using REM...........................................................67
Appendix 5: Hausman Test......................................................................................................67
Appendix 6: Breusch & Pagan Lagrangian multiplier test for random effects........................68
Appendix 7: Stationary test for shadow size estimated by POLS ...........................................68
Appendix 8: Stationary test for first difference of shadow size estimated by POLS ..............69
Appendix 9: Stationary test for shadow size estimated by FEM.............................................69
Appendix 10: Stationary test for first difference of shadow size estimated by FEM..............70
Appendix 11: Stationary test for shadow size estimated by REM...........................................71
Appendix 12: Stationary test for first difference of shadow size estimated by REM..............71
Appendix 13: Stationary test for shadow size estimated by SGMM.......................................72
Appendix 14: Stationary test for first difference of shadow size estimated by SGMM..........72
Appendix 15: Stationary test for financial development measured by Credit for private sectors
73
Appendix 16: Stationary test for first difference of financial development measured by Credit
for private sectors..............................................................................................73
Appendix 17: Stationary test for financial development measured by Credit from financial
sectors................................................................................................................74
Appendix 18: Stationary test for first difference of financial development measured by Credit
from financial sectors........................................................................................74
Appendix 19: Stationary test for money supply ratio ..............................................................75
Appendix 20: Stationary test for first difference of money supply ratio .................................75
Appendix 21: Stationary test for natural logarithm of GDP per capita ...................................76
Appendix 22: Stationary test for first difference of natural logarithm of GDP per capita ......76

ABBREVIATIONS
POLS: Pooled Ordinary Least Squared
FEM: Fixed Effects Model
REM: Random Effects Model

Chapter 1: Introduction
1.1. Problem statements
According to World Economic Forum (2017), the shadow economy in some nations are
bigger than the official one. For instance, the shadow economy of Greece is about one – fifth of
its total GDP and right after is Italy (based on research by Germany’s Institute for Applied
Economic Research (IAW) at the University of Tübingen). Therefore, the activities related to
shadow economy may exist around the world. Many governments have tried to control shadow
economy by applying punishment, prosecution and even education. It is important for governor
of a nation to know about shadow economy’s activities and then they could make the economy
more efficient in terms of allocating resources. However, getting precise information about
shadow economy’s activities is hard, even with goods and labor working in the economy
because people tend to hide their activities’ in the market. Therefore, doing the research in this
area requires passion of the scientists and willing to explore “the unknown”. This is the first
motivation of author to research about this area.
Additionally, shadow economy is one of the main reasons that make the government
revenue for public goods reduce. Indeed, there are 75% of productions in developing countries
taken place underground while it is about 10% in developed countries (Enste & Schneider,
2000). Entering the shadow economy, it means that the businesses and institutions can be out of
the control of the government and it called “fly under the radar” by Enste and Schneider (2000).
Thus, the shadow economy will undermine the ability of the government in building up the
foundations as well as the capacity of governments to collect the taxes (government’s income)
for public goods and other trading promotion programs (Enste & Schneider, 2000; Gërxhani,
2004). As a result, the study about the shadow economy will touch many other areas and it will
lead to a broad research (Enste & Schneider, 2000; Gërxhani, 2004; Johnson, Kaufmann, &
Shleifer, 1997; Schneider, 2005, 2011; Tanzi, 1982). An intensive comprehension of the
determinants of “secret action” will help law - makers and governors in creating powerful
strategies which can fight back the uncontrollable exercises and encourage economic growth.
Thus, this is the second motivation for the author to study about this area.
To dig deeper in the field of this research, Enste and Schneider (2000); Gërxhani (2004);
Schneider (2005) stated that many other conducted studies found out that the difficulties in
accessing the credits, loans and the opportunity costs of these procedures are the main
determinants of shadow economy (Enste & Schneider, 2000; Gërxhani, 2004; Schneider, 2005).
Indeed, a country with strict assessments to have a loan or there are many barriers to open a new
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business will form a kind of foundations which is the origin of the initial shadow development
(Dreher, Kotsogiannis, & McCorriston, 2007; Friedman, Johnson, Kaufmann, & Zoido-Lobaton,
2000; Johnson et al., 1997; Teobaldelli, 2011; Torgler & Schneider, 2009). These organizations
(like commercial banks, financial institutions, insurance company, etc.) who will provide the
securities which can help the businesses to access the credit but they usually require the collateral
contract and in the case that a start – up business does not have assets, they have to deal with the
lack of credits and capital to operate their business in the early stage. As a result, they will seek a
new way to access the credit with lowest opportunity costs and it is the time for the development of
shadow economy. Furthermore, in the study of Vũ Việt Quảng and Lê Thị Phương Vy (2016), they
also showed that the ability of accessing to credit will contribute to the success of a business and
therefore this ability may affect the choice of a business to operate in the official economy or
shadow economy. The research of Nguyễn Thị Thùy Linh, Trần Huy Hoàng, and Nguyễn Hữu
Huân (2015) about the financial liberalization and the economic growth stated that the financial
development is the factor that fosters the financial liberalization and then economic growth, as a
result, it revealed that taking economic growth variable in the study should be considered.
As a result, the money related area is one specific kind of establishment that is probably
going to influence the spread of the shadow economy (Blackburn, Bose, & Capasso, 2012;
Bose, Capasso, & Andreas Wurm, 2012; Capasso & Jappelli, 2013; Dabla-Norris, Gradstein, &
Inchauste, 2008; Straub, 2005). In particular, the financial sectors serves numerous critical
capacities in an economy by giving business visionaries access to required credit, and allows
observing business exchanges for assessable purposes. Subsequently, money related
improvement raises the open-door cost of creating in the shadow economy by bringing down
the boundaries to acquiring credit, and along these lines, gives a motivation to casual business
people to move towards authenticity (Blackburn et al., 2012; Capasso & Jappelli, 2013).
Moreover, to the degree that the legislature can utilize the budgetary area to effectively screen
and duty exchanges, the advancement of the monetary segment brings down the events of
assessment avoidance, and accordingly, assist mitigates the spread of the shadow economy
(Blackburn et al., 2012; Capasso & Jappelli, 2013).
Recent researches about the topic done by Enste and Schneider (2000), and Schneider and
Enste (2013); Feld and Schneider (2010) are still controversial due to the disagreement of the
definition of shadow economy and the procedure of estimating as well as the uses of the estimates in
economic and policy analysis. In South East Asia, there were some researches on measuring the size
of shadow economies such as the study of Võ Hồng Đức, Lý Hưng Thịnh, and Tống Thị Hồng
Nhung (2015) researched on the field of shadow economy and also connected the concept
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of shadow economy with other factors such as the unemployment rate and economic growth which
is the motivation for the author to see another connection of shadow economy with other factors.
Indeed, in this research, the considered factor is the financial development which is closely related
to the economic growth (De Gregorio & Guidotti, 1995). However, the number of researches on
how shadow economy effects on other elements of the economy is still quite limited and scarce.
Thus, this thesis attempts to fulfil this gap by using updated data of 8 ASIAN countries and self –
estimating the value of shadow economy for each countries. Moreover, this research will apply the
same estimation technique with the research of Ardizzi, Petraglia, Piacenza, and Turati (2014) and
Enste and Schneider (2000) to estimate the value of shadow economy. Then, we will apply various
models such as POLS, FEM, REM and SGMM to test the relationship of shadow economy and
financial development to ensure the robustness of the results.
When we analyzed the relationship between shadow economy and financial development,
we found out that in the study of Straub (2005):
Increases in shadow economy
decreases in financial development and economic
growth.
On the other hand, the study of Capasso and Jappelli (2013) they claimed that:
Increases in financial development
increases opportunity cost of
producing in shadow economy
easier for Government to tax
decrease the shadow economy.
By applying the currency demand method, we will see how many percentage of
shadow economy over the total GDP of the overall researched countries?
What is the effect of the shock created by shadow economy on the financial
development and vice versa?
Does the shadow economy have larger effect on financial development?
1.2. Research objectives
Our research objective is quite simple.
1. First, we will see the size of shadow economy over the total GDP in each research country.
2. Then, we examine the relationship between the shadow economy and financial
development by observing the shock created by shadow economy on the financial
development and the shock created by financial development on the shadow economy.
We see that
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2.1.Increases in financial development
increases opportunity cost of producing
in shadow economy
easier for Government to tax
decrease the
shadow economy.
2.2.Increases in shadow economy
decreases in financial development and
economic growth.
Thus, we will examine the relationship based in the shock created by shadow economy
and financial development on each other.
Indeed, the shock created by shadow economy here in this research is considered as the
causes which will increase the size of the shadow economy such as the increase in taxation
(because this study focused on the shadow economy created by tax burden).
Moreover, the shock created by financial development in this research is considered as the
causes which will increase the financial development such as the increase in credit supply.
We do see the endogeneity in our model, but we will deal with it by using panel Vector
auto regression.
1.3. Scope of the study
This study focuses on the two main concepts which are shadow economy and the financial
development. Therefore, we will analyze each concepts separately. Then we will conduct a
review on the empirical works of the two concepts.
Firstly, the concept of shadow economy will be covered from the definition to the
indicators of shadow economy and in this research, we will observe the shadow economy
through the angel of tax burden mainly. Therefore, we will apply currency demand approach to
estimate the size of shadow economy. Then, the financial development concept is also
developed in the same way. There is a discussion on the origin of financial development and
how to measure the financial development. After all of these discussions, the study will review
some previous studies which connect the two concepts.
For the employed model in the study, we followed the model of Tanzi (1983) to measure
the size of shadow economy for 8 – ASEAN countries. We also use the latest data for this study
(from 1997 to 2015). We choose 8 – ASEAN countries because in the study of Carter (1984),
Johnson, Kaufmann, and Zoido-Lobaton (1998) , Berdiev and Saunoris (2016) , they found out
that there are a huge difference in the size of shadow economy in developed and developing
countries. Additionally, the countries in the same region tend to have similar tax burdens and
the behavior of the regulation enforcement toward the shadow economy. The limitation in
collecting data is also the constraint when we choose 8 countries to study.
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Finally, to test the relationship between the two concepts, we use P – VAR method to see
whether the effect of shadow economy on financial development is negative or positive and
vice versa.
1.4. Structure of the thesis
In chapter 1, we have a brief introduction about the topic shadow economy and financial
development. The importance of study in this field is discussed and the objectives of this research is
also mentions. Furthermore, to have a deep understand about the definition of shadow economy and
financial development, chapter 2 will have a very detailed discussion on these two concepts. The
authors reviewed all the relevant theories as well as the empirical works in chapter 2. After the
review on theories and empirical works, we come up with the methodology which we will apply for
this study in chapter 3. Moreover, chapter 3 will discuss about the analytical framework and the
econometric model which are used in our research. Data collection is also mentioned in chapter 3.
The results of this study is in chapter 4 which will show the regression results and the discussion of
the author. Finally, after receiving the research results, the author will come up with some
conclusions and also suggest the policy implications based on the author’s points of view in chapter
5. Furthermore, the limitation of this research is also discussed in this chapter.
The detail of each chapter is below:
Chapter 1: Introduction
Chapter 2: Literature review
Chapter 3: Research methodology
Chapter 4: Research results
Chapter 5: Conclusions and policy implications
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Chapter 2: Literature review
This chapter will go through the review of all related theories of shadow economy and
financial development. Then, there is a review of empirical works regarding to the relationship
between 2 concepts: shadow economy and financial development. Finally, summary section
will provide an overview about the previous studies related to this field.
2.1. Review of theory
This part will go through the concept of shadow economy and other theories related to
shadow economy which will help to see the main determinants of the shadow economy.
Furthermore, it also will have a little discussion about the causes of shadow economy in order to
have full understand of how shadow economy arises. After that a review on financial
development theories will be conducted to ensure the understanding of the origin of financial
development concept. Then, the determinants of financial development will be discussed.
2.1.1. The theory of shadow economy
The shadow economy is the general concepts which are to reflect economic activities in
an area that is contrary to the formal sector and is very important in the national economy.
Additionally, the definition of EU about shadow economy is that the economic activities that
are not recorded on statistical and quantitative network; furthermore, OECD states that activities
producing goods and services legally without declaring or producing unrelated goods and
services and intangible income are activities of shadow economy.
There are many studies on the existence of shadow economies such as Carter (1984),
Johnson, Kaufmann, and Zoido-Lobaton (1998) , Berdiev and Saunoris (2016) and many others.
These studies can be divided into two main groups: studies of shadow economics in developed
countries and studies in developing and underdeveloped countries. The fundamental difference
in approach of these two groups comes from the different chatter of underground activities. For
developed countries, the shadow economy is seen as an overlooked part of the national
economy. As for the developing and underdeveloped, the region is seen as an indispensable and
integral part of the national economy. This is also the reason why authors choose developing
countries for analysis in order to avoid mistakes about the nature of shadow economy in
different levels of national development.
According to Schneider (2011), the negative impacts of the shadow economy on the economy
are: tax-free, affecting government revenues, not counting on GDP, affecting statistics,
16

additionally, it may be the place where the illegal activities occur that affect the economy, culture
and society of the country and are not controlled by the state. In addition, the shadow economy does
not provide sufficient and accurate information for the proper planning of macroeconomic policies,
the effectiveness of policies, the effectiveness of state management, and the effectiveness of the law
are dismissed and disabled (Scott Hacker & Hatemi-J, 2008). Furthermore, the shadow economy
also makes businesses and their products less competitive at the national level, and it is difficult to
integrate into international trade to take advantage of the opportunities offered by the associations
and easily out of the international economic movement, and become the periphery of development
cooperation (Teobaldelli, 2011; Torgler & Schneider, 2009). Such an economy may push the nation
backward in comparison with other nations or even the region. The shadow economy also creates an
unequal, untrustworthy and unfavorable business environment for honest businessmen who are
detrimental to the formal sector. Moreover, it creates unstable factors which may risk the investment
decision. The shadow economy also discourages and promotes creativity, discourages long-term
investment, large-scale investments or human resources development. The shadow economy also
limits the opportunities and the scale of business due to the fact of the contributed capital mainly
based on family relations, relatives, and inability to promote the advantages of scale (Schneider,
2005). In particular, it may create great public servants harassing, bribe and abuse power to serve
the interests of individuals. Obviously, the people working in the shadow economy do not have full
social security coverage (J. P. Choi & Thum, 2005). The shadow economy, however, is also the
place where many informal jobs are created, helping them earn a living and help the country survive
a recession.
About the causes and effects of the development of the shadow economy, there have been
many discussions and studies, including Gërxhani (2004); Johnson et al. (1997); Schneider (2005,
2011); Schneider and Enste (2000); Tanzi (1982). These research papers suggest that the severity of
administrative procedures and taxation are the main causes of the development of the shadow
market, according to Gërxhani (2004); Johnson et al. (1997); Schneider (2005, 2011); Schneider and
Enste (2000). Furthermore, the shadow economy is also permitting individuals and companies to
operate under the "fly under the radar" observation of state agencies due to internal weakness and
weak management capacity of governments to provide mechanisms for transparency of goods and
services (Schneider & Enste, 2000)(Gërxhani, 2004).
Studies of Dreher, Kotsogiannis, and McCorriston (2009); Friedman et al. (2000); Johnson et
al. (1998); Teobaldelli (2011); Torgler and Schneider (2009) found that in high taxed and strict
17

policies countries increased the sensitivity of informal sector operations. Some state
administrative organizations take advantage of the high tariffs and the huge administrative
burdens that underlie the development of shadow economy.
In this study, the observations of shadow economy will be based mainly on the tax
burdens. Furthermore, in the study of Straub (2005) also stated that the barriers to access to
public credit will promote the increase of shadow economy. On the other hand, the support
policies which reduce the tax burdens will shrink the size of shadow economy. According to
Elgin & Uras (2013b), the increase (decrease) of shadow economy will lead to the decrease
(increase) of financial development. The opposite view of Capasso & Jappelli (2013) claimed
that the increase in financial development will lead to the smaller size of shadow economy.
These two main theoretical frame works will be discussed further in the section 2.2.
2.1.1.1. Defining the Shadow Economy
Initially, it is difficult to define shadow economy concept until 1997, Smith (1997)
offered a new definition of shadow economy. He said that shadow economy was a kind of
market – based production of goods and services not in the estimation of official GDP
regardless its legitimation (legal or illegal). A broader definition is that all economic activities
avoiding regulation and taxation considered as shadow economy activities.
In this research, I follow the definition of shadow economy including all market – based
legal activities which are intentionally concealed by public departments or authorized
institutions due to any of these below reasons:
1. The payment of income and other taxes is evaded.
2. The payment of social insurances benefits is evaded.
3. To avoid committing labor legislation like minimum wages law, safety standards,
benefits for maternity, etc.
4. To not go through the complicated administrative procedures.
The concept of shadow economy in this research does not cope with illegal activities
which is also considered as shadow economy activities such as burglary, drug dealing, etc.
Thus, these points above are our very first assumptions about the shadow economy concept. In
this research, we just focused on the shadow economy created by the tax burdens. Thus, the
currency demand approach is the ideal choice for us to estimate the size of shadow economy
(Epaphra, M., & Jilenga, M. T., 2017).
18

2.1.1.2. What causes the Shadow Economy?
2.1.1.2.1. Tax and other social products burdens
The first cause of shadow economy is tax and social insurance burdens which are also the
concern of economists around the globe. Indeed, taxes will affect the income of the labors
incrementally and the social insurance will take out some proportion from the income of labor.
Thus, the larger gap between gross income (before taxes and expenses) and net income (after
taxes and expenses), the higher portion of the development of shadow economy. Due to this
effect, taxes and social insurance burdens should be taken into account when measuring the size
of shadow economy.
To prove the effect of tax on shadow economy, there are many studies on that such as of
Del’Anno and Schneider (2005); Enste and Schneider (2000); Schneider (1994) and Friedman
et al. (2000); Johnson et al. (1998). All of these studies empirically provided evidences of the
effect of taxes (direct and indirect) on shadow economy. Furthermore, these studies also found
evidence of the effect of social insurance burdens on shadow economy.
Due to the complexity of taxation system across countries, the study of Buehn and
Schneider (2009) suggested a comparable proxies for tax and social insurance burdens. In
details, the proxy was constructed by these variables:
1. The proportion of direct taxes on total taxes.
2. Size of government: this variable will be built based on government expenditures.
3. Fiscal freedom: the data from Heritage Foundation's economic freedom index.
2.1.1.2.2. The level of regulations enforcement
The second cause of shadow economy is the rigidity of government regulations. If the
government manages economic strictly and then creates the barriers for business operations, it will
discourage the engagement of business in the official economy. Indeed, the “regulations” comprises
the labor laws such as minimum wages law or the protection of labors regulations, etc., the trade
regulations such as quotas or tariffs. The empirical work of Johnson et al. (1998) found out the
effect of the regulations, especially the labor ones on the development of shadow economy.
Actually, if the government tightens the labor regulations, the labor costs will increase and then it is
the opportunity for the development of shadow economy because all the costs would be shifted to
the workers. Furthermore, this result also implies that the use of regulations or the enforcement is
the key elements for driving firms and also labor to shadow economy. In 2000, Friedman et al.
(2000) in their research, had the same result which stated that the relationship between regulations
and shadow economy was obviously positive. The research of Friedman et
al. (2000) also recommended that the government should improve the enforcement of
regulations. 19

2.1.1.2.3. Public services
The government income will decrease due to the development of shadow economy which
affects negatively on the quality of public goods and services. Thus, to maintain the quality of
public goods and services, the government will tend to raise their income by increasing the
taxes imposing on the institutions and businesses in the official sector. These actions of the
government will push the business toward the shadow economy. The results from research of
Johnson et al. (1998) indicated that the country with lower tax rate and higher tax revenue, less
regulations and corruptions will have shadow economy with smaller size. Moreover, the nations
with strong law system respected by their citizens will have a smaller size of shadow economy.
On the other hand, especially transition nations are likely to have higher size of shadow
economies because they tend to have higher taxes (rates and revenue) on official sectors. In that
research, they reached the conclusion that a country with lower tax rate, having strong financial
fundamentals and low regulation burdens as well as good control of corruptions will have
relatively smaller shadow economy than others with counter – conditions.
2.1.1.2.4. Official economy
It is quite irony that official economy – itself is one of the reasons causing the shadow
economy. In various studies of Bajada and Schneider (2005); Schneider and Enste (2013); Feld
and Schneider (2010), the official economy will affect the choice of working or not working in
shadow economy of people and institutions. Indeed, when the economy is in the expansionary
state, the official economy will help to raise the opportunity costs of working in shadow
economy by providing good working conditions and facilitating the access to credits. However,
when the economy is in the recession state, the official economy will make the opportunity
costs of operating in shadow economy lower and thus it encourage people to move to shadow
economy. In order to observe these events, these below variables will be taken into account:
1. GDP per capita
2. Unemployment rate
These variables were used in the research of Feld and Schneider
(2010). 2.1.1.3. What identifies the Shadow Economy?
It is hard to measure the shadow economy directly. Thus, in order to measure the shadow
economy, the author has to calculate it indirectly by using the various indicators. In fact, there
are 3 kinds of indicators which can be used to calculate shadow economy such as monetary
indicators, labor market indicators and the official economy indicators.
20

2.1.1.3.1. Monetary Indicators
The medium of exchange in shadow economy is mainly in cash, all the transactions in
shadow economy have to be in cash in order to make sure that they are out of the control of “the
radar” and hence people cannot impose taxes on them. Therefore, the variable M2 should be
considered to use and the taxation variable T should be taken into account also (Ahumada,
Alvaredo, & Canavese, 2008). Indeed, there is a method of estimating the value of shadow
economy using mainly the monetary indicators called currency demand methods. This method
has many advantages and was applied by Tanzi (1982), up to now, there are several research
applied this method to estimate the value of shadow economy such as Schneider (1986),
Ahumada, Alvaredo, and Canavese (2007) , etc. Indeed, Bajada and Schneider (2005) claimed
that the currency approach is the benchmark of estimating shadow economy.
2.1.1.3.2. Labor Market Indicators
As discussed above, the shadow economy will shift the labors from official economy into
shadow economy. Therefore, to observe the changes in this area, there are 2 variables used in
the study of Schneider, Buehn, and Montenegro (2010):
1. The labor participation rate
2. Growth rate of total labor force
These 2 variables will help to discover the moving of labors to shadow economy
indirectly. 2.1.1.3.3. State of the Official Economy
To see the effect of official economy on the development of shadow economy, some
authors used the GDP per capita variable (Schneider, 2011). This variable will provide the
information on the living standard of the nation as well as indicating the status of the economy
(booming or recession).
2.1.2. The review on financial development theories
The research about financial development usually related to economic growth. Furthermore,
financial development is an important input to the common goal of each country's growth (De
Gregorio & Guidotti, 1995). Therefore, to understand the financial development, an initial
understanding about economic growth is necessary. Indeed, definition of economic growth as an
integrated process that includes improvements in all areas of society and welfare of the entire
population maintained while minimizing extreme poverty and the economic deprivation of any part
of society. The concept of economic growth is defined as the growth rate of total economic output,
including the contribution of capital accumulation in this output (Khan, 2001). Growth is still a
necessary but not sufficient condition for economic growth. Among the most
21

important inputs to economic growth are financial resources and access to these resources in all
spheres of economic activity (Levine, 1997). This explains the reason why the government
should care about the shadow economy because the main goal of the government is the
economic growth but to achieve the goal, they should facilitate the financial development and
interestingly, the financial development has mutual relationship with the shadow economy
logically. Indeed, in the research of Straub (2005) and Elgin & Uras (2013b) showed the
negative effect of shadow economy on the financial development. They argued that the
government policies related to taxes will increase the size of shadow economy and then increase
in shadow economy will inhibit the financial development. Actually, when the taxes are lower,
it means that the costs of operating in official economy is lower or the opportunity of operating
in shadow economy is higher. Whereas there are empirical evidence from research of Capasso
& Jappelli (2013) stated that the financial development will shrink the size of shadow economy.
The government should intervene in developing policy process of financial development to
reach the goal of economic growth. The role of financial institutions and their policies in economic
growth is addressed in Stiglitz and Stiglitz (2000), showing that the design of financial institutions
and policies plays an important role to the point of economic growth. Furthermore, the changes in
the policy which affect positively the financial development will be considered as a shock created
by financial development and will affect in shadow economy. On the other hand, the shock created
by shadow economy here in this research is considered as the causes which will increase the size of
the shadow economy such as the increase in taxation (because this study focused on the shadow
economy created by tax burden). The additional point is that when the government has any actions
which affect the financial development will somehow create a shock on shadow economy and this
section will be discussed in section 4: results and discussion
Obviously, financial markets are the intermediaries of the economy, contributing to
capital accumulation and technological innovation, and are closely linked to economic growth.
The theories emphasize that the development of the financial system is an important factor of
the economy in the long-term. The developed financial system can facilitate economic growth
through multiple channels. According to Drake (1980); Fritz (1984); Garcia and Liu (1999);
Beck and Levine (2005), these channels include:
(i) Providing information on feasible investments, to effectively regulate the capital;
(ii) Monitoring the corporates and corporate governance in public sector;
22

(iii) Diversification of risk;
(iv) Mobilizing and aggregating savings;
(v) Facilitating the exchange of goods and services; and technology transfer.
The financial sector serves many of the important functions of the economy, as countries
with low levels of financial development will deal with capital deficits, lack of competitiveness,
and financial injustice as well as limited ability to gather information for lenders, (Bose et al.,
2012). It is the fundamental for the development of shadow economy and therefore again it
appears to a relationship between the financial development and shadow economy.
When Love and Zicchino (2006) did a research about financial development for business
experience on financial constraints, which is a criterion for distinguishing between low levels of
financial development and high levels of financial development countries. The countries with
high developed financial system are places where firms are more experienced in the financial
constraints of the business as well as the financial market’s products. Thus, it will raise the
opportunity cost of operating in shadow economy.
2.1.2.1. The origin of financial development
The concept of financial development is not new in literature. However, understanding the
concept clearly will help to measure and observe it precisely. This part will introduce the origin
of financial development and the determinants of financial development. Including institutions,
macroeconomic elements, geographic factors and others.
2.1.2.1.1. Institutions
Institutions are mentioned because it played an important role in creating the concept of
financial development. Obviously, the regulations affecting some major related variables such as
property rights, the enforcement of agreements, accounting standards, etc. which definitely affect
the financial development (Porta, Lopez-de-Silanes, Shleifer, & Vishny, 1998). According to Beck
and Levine (2005), a country with strong regulation in terms of efficiently enforcement of
agreements will have higher financial development. On the other hand, country with weak
enforcement of regulations will have lower financial development. Indeed, the disclosure of
information, accounting standards, operation of banking system regulation and financial insurance
are all defined in the regulations which have a strong effects on financial development (Mayer &
Sussman, 2001). A deeper analysis of this issue is the interest group and its influence on the
financial development, a recent study of political economy mentioned that the interest
23

group may affect the regulations in order to maximize their benefits. Then, it obviously affects
the financial development (Pagano & Volpin, 2001). Additionally, the study of Rajan and
Zingales (2003) stated that the trade openness and financial openness are affected by the interest
groups who can interfere in the financial market and the financial development is only better
with both openness environment.
In short, institutions plays an important role on financial development. The financial
development will depend somehow on the development of institutions of that nation. However,
due to the limitation of time and data, this research did not take into account the institutions as a
variables in our model.
2.1.2.1.2. Policy
As discussed above, the institutions will affect the financial development through its
intervention. However, how they can intervene the financial development? Actually, the policy is
the key for the institutions to open the power of intervening the financial development. In fact,
macroeconomic policies can promote the openness of trade by maintaining the low inflation rate
which will encourage the capital inflow. As the trade is open, the financial development is definitely
improved. Indeed, the study of Huybens and Smith (1999) theoretically and Boyd, Levine, and
Smith (2001) claimed empirically that the nations with low inflation rate will have more efficient
banks and equity markets. Furthermore, the recent work of Do and Levchenko (2009) also has the
alignment with the view of policies which may encourage the openness to trade and then the
financial development. Moreover, Claessens (1998) in their study figured out that the function of
banking systems and the quality of financial market are improve with opening banking systems.
Claessens and Laeven (2003) found out that the opening banking systems may help to reduce the
costs of financial transactions and stimulate the financial development.
2.1.2.1.3. Geography
The concept of geography initially seem not relevant with financial development concept.
However, in some studies, researchers have pointed out the relationship between geography and
financial development. Indeed, in the research of Gallup, Sachs, and Mellinger (1999), they found
out that tropical climate countries which are near the equator will have poor production of crop and
then it will lead to institution issues. Moreover, the studies of Sachs, Warner, Åslund, and Fischer
(1995), Easterly and Levine (2003); Malik and Temple (2009) stated that the countries with
landlocked will have less chance to open their trade as well as the opportunity for building up the
comparative manufactured goods. Then, it will lead to less openness of trade and as a result, the
financial development will be counted on. The last area which researchers focuses on
is the resource endowment and economic development. In the study of Isham, Woolcock, 24

Pritchett, and Busby (2005) the developing countries with rich natural resources will develop
their countries through just identical channel and it may put the countries in risky situations and
then it affects the economic development as well as the financial development as a result.
In short, geography does affect the financial development in terms of demand side of
financial development or the quality of institutions.
2.1.2.1.4. Other considered variables
There are still some other variables affecting the financial development which are
economic growth, the income, population, etc. Greenwood and Jovanovic (1990) and Saint-Paul
(1992) concluded that when a country has a strong economic growth, they will have costs
advantages of financial intermediaries. Indeed, when the economic grows, there are more
money flow – in the markets via financial channels (intermediaries) such as banks, it will
reduce the costs of these transactions. Additionally, this conclusion leads the author to the belief
that there are the positive relationship between financial development and shadow economy.
In addition, the relationship between income and financial development empirically tested
through the study of Levine (1997), Easterly and Levine (2003) and Beck and Levine (2005).
The research of Jaffee and Levonian (2001) also found out a specific evidence of the
relationship in banking development by using the data of bank assets, numbers, and employees.
The result shows the positive relationship between income and banking system development.
Last but not least, the financial development is also affected by the culture (especially
religion and language). In fact, culture helps to foresee the differences in the enforcement of
creditor rights as well as investor rights and from that it may affect the trade openness (Stulz &
Williamson, 2003). Furthermore, the study of Djankov, Glaeser, La Porta, Lopez-de-Silanes,
and Shleifer (2003) opened a new variable which may affect financial development is the state
ownership.
2.1.2.2. General determinants of measuring financial development
A direct result from McKinnon and Shaw (1973) and Shaw (1973) showed that interest rate
regime, reserve requirements and credit programs were the main causes on the financial
development. Indeed, they found out the negative result when a country having high interest rate,
high required reserves and direct credit programs tends to have lower financial development level.
In the study, the problem of financial development is the allocation of credits. Obviously, if the
government interfered to the process of credit allocation, it would be likely a corruption because the
money will go to the “interest sectors”. Therefore, a policy which can eliminate the interest
rate ceilings, set the required reserve lower and liberate the financial systems form government
25

intervention is crucial for the financial development. This review also motivate the author to
pick the credit for private sectors and credit from financial sectors to represent the financial
development because it is suitable for the current research condition of the author in terms of
time and data constraint.
2.1.2.3. The potential determinants
There are potential determinants which can represent the financial development. After
reviewing many selected sources, there are some variables which can help to be the “face” of
financial development. These variables which may cause the endogeneity problems are not
taken in to account.
The financial variables
The easiest way to measure the financial development is to take the direct variables which
directly affect the financial development. According to McKinnon and Shaw (1973), the
financial development will be changed by the change in interest rate regime, reserve
requirements and credit programs. Therefore, taking financial variables to represent the
financial development is reasonable. Moreover, Aghion, Howitt, and Mayer-Foulkes (2005)
took the credit multiplier as the main parameter to measure the financial development. Thus, it
confirmed our point of view on the representative of financial development.
Institutional variables
An institutional variable may be considered in the research to measure the financial
development. According to Porta et al. (1998), the legal variables will be a potential
determinant for financial development. In his study, he suggested a dummy variable to identify
the financial development. However, the use of institutional determinants will be considered
based on the characteristics of the data.
Policy variables
On of other potential determinants for financial development is policy variables which
will examine the macroeconomics policy variables and its effects on the variance of financial
development (Demetriades & Luintel, 1996). The elements of financial policies and trade
openness will be taken into account when using these variables. It will be great if we have the
data covering all these variables.
26

2.2. Review of empirical studies on the relationship between financial
development theory and shadow economy theory
Theoretically, the study of the relationship between financial development and the shadow
economy was founded by Becker (1968) study, which was the economic impact of criminal
acts. Becker (1968) argues that firms in the market will face the option of benefiting from one
side of the benefits of shadow economy operations over paying for detection and fines. In the
shadow economy, entrepreneurs in particular measure the benefits of informal sector operations,
such as evading heavy taxes or avoiding the cost of doing business with compliance in
comparing with the costs of legally operating and other opportunity costs, e.g., and utilities for
official beneficiaries of government policies. When the benefits of operating in the shadow
economy are more than the cost of paying for it when discovered by law, businesses tend to
increase their activities in the shadow economy.
The theories discussing the financial system are one of the special agencies that affect the
costs and benefits of the informal sector, thus affecting the shadow economy in the overall
economics (Straub, 2005); (Dabla-Norris et al., 2008); (Blackburn et al., 2012); (Bose et al.,
2012); (Capasso & Jappelli, 2013). For example, the impact of financial development is an
increase of the opportunity cost of operating the shadow economy, which is to reduce the
barriers to capital gains with lower costs, incentive policies, and increased government
investment driving the companies into the formal sector (Capasso & Jappelli, 2013).
First, Straub (2005) develops a theoretical model in which firms measure the benefits and
costs of operating in the formal sector and the shadow economy. In particular, the benefits from the
formal sector are: the use of public resources such as working with state financial institutions. These
state agencies allow and advise businesses and companies to access financed resources effectively,
including funds from government for areas or products promoted by the government. However,
experienced entrepreneurs may also be able to measure the cost they have to pay when they choose
to enter the formal sector, which are fees and taxes. Therefore, this model suggests that enterprises
must provide the smallest initial registered asset level and contemporaneously participate in the
formal sector with capital requirements for investment and production. However, these
entrepreneurs are even not able to afford this low initial capital because of the cost of registration
and credit limits for businesses, which keep them operating in shadow economy (Straub, 2005).
Business people will borrow capital from the shadow economy despite the higher cost of capital.
Finally, Straub (2005) concludes that the lowest initial capital level of
27

enterprises is the major benefit of operating in the official (formal) economy deriving from
support packages from government financial institutions which cover small and medium
enterprises with low interest rates on the comparison between the formal and informal sector.
The reduction of binding legal obligations on the creditor's rights is obvious and it also reduced
level of ambiguity and tax obligation clause. While the disadvantages of taking part in the
formal economy cause the increase in participation costs, which may include costs of business
creation, fees and taxes. After 8 years, in the study of Elgin and Uras (2013b), they claimed that
an increase in size of shadow economy will lead to a decrease in financial development. Indeed,
Elgin and Uras (2013b) employing the data from 152 countries in the period 1999 – 2007
conducted a research on how financial development affects the shadow economy and vice
versa. His research showed that financial development and shadow economy have mutual
effect. In fact, the financial development will be constrained if the shadow economy gains the
advantages. On the other hand, the shadow economy will be narrowed down if the level of
financial development improves. This findings is obviously the evidence of the mutual
relationship of shadow economy and the financial development.
The formal economy vs. shadow economy by Straub (2005)
The arguments based on “low initial registered capital of enterprises”
Advantages Disadvantages
Lower interest rates, incentives in government
Creation fees
incentives when registering low initial funding.
Reduce legal obligations on the rights of
Other fees and taxes.
creditors when initial low initial capital.
Clearance of tax obligations and duties Credit limit.
Moreover, Gobbi and Zizza (2007) found out that the financial development does not
significantly affect the size of shadow economy but the reverse is statistically significant. Indeed,
the shadow economy affected the financial development. In this study, Gobbi and Zizza (2007) used
the data from 1997 to 2003 for Italian debt market. The recent research of Berdiev and Saunoris
(2016) argued that an underdeveloped financial sector is likely to be abused by subjects in the
shadow economy (securing loans or hiding funds), while the developed financial sector is being
innovated and providing better financial services (e.g., the emergence of more optimal services from
mutual funds and debt securities such as collateralized debt obligations), so the opportunity cost to
produce in the shadow economy is higher. In addition, advances in the formal
financial market bring more alternatives than those of the shadow economy, such as the 28

legalization of business operations. Berdiev and Saunoris (2016) also pointed out that the
transparency of government agencies provides protection against corruption and manipulation
of public property to private property as well as unfair access to capital and contract execution,
such as economic contracts or tenders. However, the existence of the shadow economy also
contributes to the weakening of government agencies, the inadequacy of budgets for
government operations leads to a decline in both quantity and quality of public goods. If there
are no effective government intervention, it would be possibly by legislation as the alternative
solution. Additionally, Habibullah, Din, Yusof-Saari, and Baharom (2016) also did a same
research to analyze the relationship between the financial development and shadow economy
for Malaysia in the period 1971 – 2013. The received result revealed that there was a negative
relationship between shadow economy and financial development.
Next, Capasso and Jappelli (2013) formulated the theoretical model where the firm
chooses between receiving high assistance when requiring collateral for credit from financial
institutions and getting low subsidies from production using internal capital sources. This model
assumes that entrepreneurs can get a lower cost of capital by providing collateral to financial
institutions, as collateral is secured, the risk must be lower and business could negotiate at the
low interest rate (costs of capital). However, the provision of collateral in parallel with the need
to point out the economic activities of the business, the income, as a result, it leads to higher
duties. This understanding is so great that government representatives can use these financial
intermediaries to monitor the operations of debt-financed companies, the financial system
reduces barriers to access to funds and credit through which prevent the act of tax evasion,
thereby reducing the spread of the shadow economy. Capasso and Jappelli (2013) continue to
discuss their views on the choice between participating in these two highs or lows, the choice
between the cost reduction benefits of participating in the receiving support area with highly
supportive of formal sector and the benefit of hiding revenue when using internal capital. In a
nutshell, the decision of whether an enterprise receives low cost capital from an intermediary
financial institution or uses an internal capital source; it also comes along with the need to prove
collateral for income and economic activity, and to bear higher costs and taxes, or to hide
activities and revenues for less premiums and taxes. Capasso and Jappelli (2013) also argued
that the development of financial sector will increase the opportunity cost of evading taxes, or
underground operations, or the opportunity cost of decreasing credit limit and the opportunity
cost of not receiving new technology investment.
29

The formal economy vs. shadow economy by Capasso and Jappelli (2013)
The arguments based on “choosing the credit technology of the business”
Advantages Disadvantages
Lower interest rates, incentives in government Disclosure of collateral resources,
incentives packages. business operations, revenue sources.
Higher credit limits given by the business to
Do not evade fees and taxes with
collateral assets and disclosure revenue sources.
publicity activities.
Get access to new technologies.
Previously, Amaral and Quintin (2006) argued that in developing countries, formal
workers tend to gain more experience, be more educated, and earn more than informal workers.
Research indicates that low-skilled workers face barriers to entry into the formal sector. In
equilibrium, the author finds the characteristics of informal and informal workers differ
systematically, although the labor market is perfectly competitive. The informal sector is
characterized by lower skill traits, because informal sector enterprises have less access to
finance than the formal sector, and therefore firms in informal sector choose low-skilled
workers to reduce capital use. Furthermore, a research of Bose et al. (2012) for 137 countries
with the data from 1995 to 2007 applied panel regression model examined the relationship
between banking sectors and shadow economy. This research concluded that banking sector
development has negative relationship with shadow economy. It means that the more developed
banking sector, the smaller size of shadow economy. In the same year 2012, Blackburn et al.
(2012) found out that a country with lower level of financial development tends to higher size
of shadow economy. Moreover, a study of Bittencourt, Gupta, and Stander (2014) also found
the evidence of the negative relationship of financial development over the shadow economy.
This study was conducted by collecting the data of 150 countries in the period 1980 – 2009.
Indeed, they observed that the financial development caused the decrease for shadow economy.
Recently, Bayar and Ozturk (2016) conducted a research about the same topic with the data
from European transition economies from 2003 to 2014. The author of this research also found
the negative relationship between the financial development and shadow economy.
30

2.3. Summary
Figure 1: Conceptual framework of shadow economy and financial development
To sum up, the shadow economy, according to Smith (1997), was a kind of market –
based production of goods and services not in the estimation of official GDP regardless its
legitimation (legal or illegal). A broader definition is that all economic activities avoiding
regulation and taxation considered as shadow economy activities. The concept of shadow
economy in this research does not cope with illegal activities which is also considered as
shadow economy activities such as burglary, drug dealing, etc.
The first view point of Straub (2005) and Elgin & Uras (2013b) is about the effect of
shadow economy on the financial development. In fact, Straub (2005) pointed out the causes
which may create a shock for shadow economy. For instance, an announcement of government
which will limit the access to public credit will encourage business to operate in shadow
economy and then the size of shadow economy will be larger (Elgin & Uras, 2013b).
Furthermore, the causes of shadow economy are taxes and other social security’s burdens, the
level of regulations enforcement, public services and the official economy. First of all, to prove the
effect of tax and social security’s burdens on shadow economy, there are many studies on that such
as of Del’Anno and Schneider (2005); Enste and Schneider (2000); Schneider (1994) and Friedman
et al. (2000); Johnson et al. (1998). Secondly, the empirical work of Johnson et al. (1998) found out
the effect of the regulations on the development of shadow economy, it stated that the more sticky
regulation, the greater size of shadow economy. Thirdly, to maintain the quality of public goods and
services, the government will tend to raise their income by increasing
31

the taxes imposing on the institutions and businesses in the official sector. These actions of the
government will push the business toward the shadow economy. Last but not least, in various
studies of Bajada and Schneider (2005); Schneider and Enste (2013); Feld and Schneider
(2010), the official economy will affect the choice of working or not working in shadow
economy of people and institutions. Indeed, when the economy is in the expansionary state, the
official economy will help to raise the opportunity costs of working in shadow economy by
providing good working conditions and facilitating the access to credits. Finally, to measure the
shadow economy, there are some suggested potential factors such as the monetary indicators
(M2, taxation), labor market indicators (The labor participation rate, Growth rate of total labor
force) and the status of official economy (GDP per capita). With these factors, it is quite easy to
identify the potential variables for the research.
The second view point of Capasso & Jappelli (2013) stated the effect of a change in
financial development will negatively impact in the shadow economy. It means that an increase
in financial development will lead to a decrease in size of shadow economy. There are many
causes of increasing or decreasing the financial development. According to Drake (1980); Fritz
(1984); Garcia and Liu (1999); Beck and Levine (2005), the developed financial system can
facilitate economic growth through multiple channels. The concept of financial development is
usually gone with the economic growth. Indeed, there are some other variables affecting the
financial development which are economic growth, the income, population, etc. Moreover,
Greenwood and Jovanovic (1990) and Saint-Paul (1992) concluded that when a country has a
strong economic growth, they will have costs advantages of financial intermediaries. Thus, to
understand deeper about the change in financial development, the causes of financial
development were shown in a direct result from McKinnon and Shaw (1973) and Shaw (1973).
It showed that interest rate regime, reserve requirements and credit programs were the main
causes on the financial development. Indeed, they found out the negative result when a country
having high interest rate, high required reserves and direct credit programs tends to have lower
financial development level. In the study, the problem of financial development is the allocation
of credits. Thus, the potential determinants of financial development are financial variables,
institutional variables and policy variables. Logically, the easiest way to measure the financial
development is to take the direct variables which directly affect the financial development.
Therefore, taking financial variables to represent the financial development is reasonable.
Moreover, Aghion et al. (2005) took the credit multiplier as the main parameter to measure the
financial development. Thus, it confirmed our point of view on the representative of financial
development. Additionally, in our research, we acknowledged that the shock created by shadow
32

economy is considered as the causes which will increase the size of the shadow economy such
as the increase in taxation (because this study focused on the shadow economy created by tax
burden). Moreover, the shock created by financial development in this research is considered as
the causes which will increase the financial development such as the increase in credit supply.
Finally, the recent studies about the relationship between shadow economics and financial
development of Straub (2005); Dabla-Norris et al. (2008); Blackburn et al. (2012); Bose et al.
(2012); Capasso and Jappelli (2013) show the negative relationship between financial
development and shadow economy. Interestingly, there are some research show the mutual
relationship of the two concepts such as the study of Elgin and Uras (2013b). In short, we see
there may be a mutual relationship between shadow economy and financial development.
33

Chapter 3: Research methodology
3.1. Analytical framework
The financial sectors are the fundamental which effects the development of shadow
economy (Capasso & Jappelli, 2013). The development of financial sectors supports investors
to approach the credits easier, and through this channel the governments as well as the
governors will supervise all the transaction’s activities. Additionally, it will facilitate the work
of imposing taxes on transactions within the economy as well as encourage the businesses to
switch from shadow economy to the official economy due to higher opportunity costs of
operating in shadow economy (Capasso & Jappelli, 2013; Martimort & Straub, 2005). On the
other hands, the development of shadow economy may prevent the financial development
(Elgin & Uras, 2013b). Therefore, it is crucial to control the 2 – ways relationships between
financial development and shadow economy in the study. We do apply the p – VAR method to
see the impact of shadow economy on financial development and vice versa. The detail will be
discussed in section 4: Research results.
POLS
FEM
Data
Shadow Financial
Economy Development
REM P-VAR
SGMM
Figure 2: The technical structure to deal with data
There are some concerns about the financial development and shadow economy except the 2
– way relationship issue. Firstly, there are many variables should be taken into account when we
measure the financial development as we discussed in section 2.1.2. Thus, if we only use 1 variable,
it cannot represent the financial development. However, with the limitation of time and
34

data, in this study, the author used 2 variables to represent the financial development aligned
with the study of Elgin and Uras (2013b), Berdiev and Saunoris (2016), Mai and Schneider
(2016) and Medina and Schneider (2017) which are:
1. Credit for private sectors: Credit provided by domestic credit institutions to the private
sector (creditprivate).
2. Credit from financial sectors: Domestic credit from the financial sector includes total
credit for other sectors and net credit to the government (creditfinancial).
These measurements are calculated based on GDP, data for the measurement is from
World Bank Development Indicators, ADB and Euro monitor.
The measurement of shadow economy size is also the challenging part when doing this study.
The shadow economy is known as the economic activities and the incomes avoiding the control of
governments and taxation system (Del’Anno & Schneider, 2005). The estimation of the size of
shadow economy is therefore difficult because individuals and organizations operating in shadow
economy tend to hide their activities. Thus, there are some academics who try to find out the way of
measuring the shadow economy. Indeed, there are generally 3 ways of measuring shadow economy
and Đức, Thịnh, and Nhung (2015) listed 3 main methods of measuring shadow economy including
applied dynamic models with multiple indicators, direct and indirect methods. The first method
based on the dynamic multiple indicators – multiple causes model to measure the shadow economy.
Indeed, the size shadow economy variable is considered as the variable affected by the group of
observed macroeconomic variables. Additionally, the direct method is based on the micro – survey
(surveying and auditing). The accuracy of this method depends much on the way of building and
developing the questionnaires and the quality of interviewees who are paid for the survey and other
aspects. The final method is indirect method which will exploit the economic variables and other
variables such as the differences between the national (current) accounts and national expenses, the
differences between the official number of labors and the actual number, the money demand
approach, etc. to calculate the size of shadow economy.
This study will estimate volume of shadow economy based on money demand which is
developed by Tanzi (1983) , Cagan (1958) and recently Epaphra, M., & Jilenga, M. T., (2017).
Indeed, Tanzi (1983) estimated the demand for currency and employed the results to
measure the size shadow economy established by the relationship between the demand for
money and the pressure in the US tax in period of 1919-1955. Besides, Tanzi (1983)
demonstrated that most transactions in the shadow sector, which is generated so as to prevent
oversight from the government, are primarily performed by cash. Therefore, the increase in
demand for cash somehow reveals the increase in shadow sector.
35

The money demand method has been used many authors in order to measure the size of
shadow economy involving Bhattacharyya (1999), Klovland (1984), Bajada (1999), Schneider
(2002), Alm and Embaye (2013), Đức et al. (2015). Hence, this study is going to apply the
money demand method following Tanzi (1983) and also inherit some adjustments from Alm
and Embaye (2013), Đức et al. (2015) in order to archive more appropriate estimation for
developing countries. This study employed tax burden factor ( ), private expenditure ( ), gross
national income ( ), deposit interest rates ( ), GDP per Capita ( ), thereby estimating an equation
below with money in circulation over total money supply M2 ratio ( / ) as dependent variable:
( ) = + ( + ) + ( / ) + + + (1)
, , , , , ,
To estimate the equation, this study will utilize various techniques for panel data
including pooled ordinary least squared (POLS), fixed effects model (FEM) and random effects
model (REM). In which, POLS technique does not take into account the specific characteristics
of each country in the model, FEM considers the specific characteristics of each country in the
model, but it comes with a very strict assumption that the individual characteristics have to be
fixed and does not change over time, meanwhile, REM allows the random countries
characteristics which are treated as another error-term in the model. Moreover, this study will
also employ System Generalized Method of Moments (SGMM) so as to deal with endogeneity
due to including order one lag dependent variable.
3.2. Econometric models
According to Đức et al. (2015), the most prominent methods are money demand method and
dynamic model method. Both methods are applied in many recent research in order to estimate the
size of shadow economy of many countries for 50 years. The money demand approach is developed
by Tanzi (1983) based on the previous study of Cagan (1958) about the relationship between the
money demand and the tax burden in United States in the period 1919 – 1955. Tanzi (1983)
estimated the demand of money and used this results to measure the size of shadow economy of US
in the period 1929 – 1980. The assumptions in the study of Tanzi (1983) is that almost transactions
in shadow economy using cash to avoid the supervising activities from the government; as a result,
it will lead to the increase in size of shadow economy and then the demand for money. Applying
money demand approach, Tanzi (1983) used the regression model to analyze the effect of different
factors such as income of people, payments, deposit interest rates and tax burden on money demand.
The residuals in the estimated model is considered as the increase in the money in circulation.
Additionally, Tanzi (1983) also assumed that the money in circulation in official economy and
shadow economy is similar and hence, the size of shadow
36

economy is identified by taking the differences in the money in circulation with 2 different tax
rates.
The currency (money) demand approach was used by many authors such as Bhattacharyya
(1999), Klovland (1984), Bajada (1999), Schneider (2002), Alm and Embaye (2013) and Đức et al.
(2015) to estimate the size of shadow economy in several countries. In this research, we apply the
currency (money) demand approach method in order to estimate the size of shadow economy. In
comparison with the study of Elgin and Oztunali (2012) , we update the data for the research
because the previous data of Elgin and Oztunali (2012) is just updated up to the year 2009. Indeed,
we would like to update the latest data from the input of international organizations such as World
Bank, ADB and Euro Monitor. Additionally, in the study of Elgin and Oztunali (2012) , they used a
different method to estimate shadow economy called two-sector dynamic general equilibrium
models. However, as discussed above, there are extremely many previous researches using currency
(money) demand method, thus it proved the value of this method.
To estimate the size of shadow economy, the research will follow these steps below:
1. Inheriting from the model of Tanzi (1983), the author collect data about tax burdens,
household consumptions, interest rate, GDP per capita, unemployment rates to estimate
the value of CM/MS following the below model:
( ) = + ( + ) + ( / ) + + + (1)
, , , , , ,
Where:

The ratio of money supply CM/MS: is the ratio of money in circulation over the money
supply. CM is the amount of cash using in buy – sell transactions, it is not the cash
reserved in commercial bank, financial institutions and central bank. Additionally, MS
is the money supply and we took the data of M2 as the representative.



Tax T: the total income from tax over GNI. Income from taxes comprises all taxes
payables to the state.



Personal consumptions C/I: it includes the actual consumptions and estimated
consumptions of individuals for goods and services.



The deposit interest rate R: the opportunity cost of holding money.



GDP per capita Y: GDP per capita calculated by Purchasing Power Parity method.


2. The coefficients γ of the model (1) after the estimation is substituted for the model (1),
then we have the model (2) (with fixed coefficients).
3. Assume tax T = 0 and the coefficients of independent variables are unchanged, we will
calculate the amount of money when there is no effect of the shadow economy (when tax
37

T = 0) and the amount of money when existing the shadow economy (when tax T ≠ 0).
The official money in circulation is identified by the ratio of Gross National Income
(NI) and money supply. In the consistent with Đức et al. (2015), we assume that the
money in circulation in official economy and shadow economy is equivalent. Hence, the
size of shadow economy may be calculated by multiplying the money in circulation with
the amount of money.
4. Applying the above calculation for each country respectively, we will receive the result
for the size of shadow economy in the research sample.
Furthermore, according to Berdiev and Saunoris (2016), the level of economic growth have a
significant effect on the size of shadow economy and as well as the financial development. On the
other hand, the more prosperous nation will have higher level of financial development and smaller
size of shadow economy. Contemporaneously, the larger size of shadow economy together with
lower level of financial development will keep the economic growth in low level. Therefore, to
control these aspects, author added a logarithm variable of GDP per capita in the P
– VAR equation when we examine the relationship between financial development and shadow
economy.
After identifying all the related variables and the estimation methodology, the author
chose the panel vector auto – regression model in order to control the 2 – way relationship
between financial development and shadow economy (P – VAR). This is the technique to
estimate contemporaneously as system of equations which considered the financial
development variables and shadow economy variables as endogeneity (Berdiev & Saunoris,
2016; Holtz-Eakin, Newey, & Rosen, 1988; Love & Zicchino, 2006). Because of the two – way
relationship between financial development and shadow economy, it leads to the deviation of
the estimation. Additionally, the relationship between the two variables is observed by a time
series data with identical lag, thus a dynamic model will work better than static model in this
case. Contemporaneously, the result of p –VAR model will allow us to build impulse - response
function to illustrate the development on time basis of 1 variable (such as shadow economy
variable) right after a shock on another variable (such as financial development variable)
(Berdiev & Saunoris, 2016). Therefore, we could observe the whole dynamic process from very
first shock to the long – term stable status of a variable.
Before taking the panel vecto autoregression (P – VAR), we conducted the unit root test
to avoid the spurious regression. Moreover, the optimal latency test is also applied to ensure the
efficiency of the model.
38

The panel vector autoregression (VAR) analysis of (Love and Zicchino, 2006; Holtz-
Eakin et al., 1988) was applied to investigate the dynamic relationship between financial
development and the shadow economy. The equation of panel VAR is described:
, = + ∑ , − + , (3)
=1
In the equation above, Yit is a matrix represented by 1 × 4 vector containing the
endogenous variables log of GDP per capita, financial development (creditfinancial, or
creditprivate), M2/GDP and shadow economy. Following we limit our system to four variables
and include the log of real GDP per capita (lgdp), which is one of the main determinants of both
shadow economy and financial development, as discussed in the previous section.
In order to interpret the panel VAR (3) with the predicted existing endogenous relationship
between 4 variables, the p – VAR model stays freethinker with regards to the right fundamental
hypothetical relationship among the factors and rather regards every one of the factors as
endogenous in the framework. Furthermore, the yield of the p – VAR model incorporates impulse
– response functions, which indicate the period way for every variable accompanying a stun of
the different variables in the framework. Accordingly, we analyze those reactions of the shadow
economy after a shock created by financial development, the magnitude of this shock, and
whether this effect is statistically significant over time. Moreover, we see the opposite side of
the effect by observing the response of financial development following a shock created by
shadow economy. Therefore, those entirety dynamic process could be observed.
To ensure the stationary of variables in the VAR equation system, the author uses Fisher
Unit Tests for panel data. Furthermore, due to the limitations of collected data, the author can
only select one latency level for all variables in the system. One weakness of the VAR method
for panel data is the loss of several degrees of freedom for each additional variable put into the
system. That is the explanation for the reason why the authors just put 4 variables into the
system including GDP per capita, MS, shadow economy, and financial development).
The most important point in the study was the impulse - response function received after
estimating the P-VAR model, which shows the development over time of each variable
following a shock to other variables in the system. For example, we can analyze responses of
the size of shadow economy after a shock happened with financial development, the magnitude
of this shock and whether the effect of this shock on the variable is statistically significant over
time or not. Thus, the whole process from the initial shocks to the stable state in the long term
of the variables is observed.
39

3.3. Data
Recently, in the research of Berdiev and Saunoris (2016), they used the data of shadow
economy from the study of Elgin and Oztunali (2012) to examine the relationship between the
shadow economy and financial development but the point is that they do not calculate the size
of shadow economy and employed the result from other study to conduct their research. Thus,
the robust of their study may be affected. However, this research will calculate the shadow
economy caused by tax burdens and then examine the relationship between the shadow
economy and financial development.
Currently, we apply the macroeconomics and some microeconomics data from IMF,
World Bank and Euro-monitor to build the dataset. For the data, we collected macroeconomic
data such as Private Expenditure, Money supply M2, Government Tax, GNI, Deposit Interest
Rate, GDP per Capita, GDP, Credit Private, Credit Financial as the ingredients for calculating
the target variables.
3.4. Variables and sampling
Our study uses annual data table for the period 1990 - 2015 in developing countries. We
consider 8 countries: Brunei, Cambodia, Indonesia, Malaysia, Myanmar, Philippines, Thailand,
and Vietnam.
When studying the shadow economy, the researcher faces the difficulty of estimating this
economy by its defining nature as unpredictable parameters of the statistics department, and
also by the shadow economy subjects which are individuals and businesses that try to hide their
involvement. However, this study is supported by recent measurement studies, Schneider et al.
(2010); Elgin and Oztunali (2012); Alm and Embaye (2013) have developed methods of
estimating the shadow economy. The author denotes the name of the sequence of data that
measures the fluctuation of the shadow economy in terms of size is “shadow”.
Data of the shadow economy measured by Elgin and Oztunali (2012), the author has used two
general equilibrium areas corrected by macro variables to estimate the shadow economy. The Elgin
and Oztunali (2012) estimation model calibrates the model used from the previous estimation
method presented by Schneider et al. (2010). The correlation of these estimation methods is up to
0.99 and considered to be the same as estimated results. In this paper, the author uses the
measurement data from the Elgin and Oztunali (2012) studies because this dataset provides a longer
measurement period. It can be imagined that the relationship between financial development and the
shadow economy is a process developed over decades and therefore the
longer the data, the more fully it can be captured the developments and changes of this topic. 40

According to the estimation of Elgin and Oztunali (2012), the average size of shadow economy
is about 36% of GDP, with the smallest shadow economy (8% of GDP) being Swissland and the
biggest shadow economy (80% of GDP) is Georgia. Within the scope of the paper, the author
focuses only on developing countries.
For financial development measurement, the dimension is multidimensional, the Elgin and
Uras (2013a) research paper uses three methods of measuring change in financial development:
• M2 money supply on GDP, unit of percentage (m2gdp)
• Domestic credit provided by financial institutions for private sector on GDP, percentage
unit (credit private symbol)
• Domestic credit from the financial sector includes total credit for different sectors and
net credit to the government on GDP, percentage unit (credit symbolical)
Regarding control variables, the study by Enste and Schneider (2000) shows the different
levels of economic development that affect the shadow economy. Additionally, the different
levels of development of the economy also affect the level of financial development, according
to Levine, R. (1997). Economically, the rich countries have a higher level of experience and
understanding of the financial products as well as their financial limits. Conversely, countries
with large shadow economy have a low level of financial development that inhibits the
prosperity of the economy. Thus, economic development with GDP per capita data (lgdp
symbol) is used as a control variable, as economic development has evidence that impacts both
the shadow economy and financial development.
41

Chapter 4: Research results
4.1. Overview of the research topic
Initially, the study of the relationship between financial development and the shadow
economy was founded in the study of Becker (1968), which was the economic impact of
criminal acts. Becker (1968) argued that firms in the market will face the option of benefiting
from one side of the benefits of shadow economy operations over paying for detection and
fines. Indeed, the businesses have to tradeoff between operating in shadow economy which can
help them enjoy big profits as well as the benefits of tax evasion but a big penalty if catch and
operating in official economy which will avoid the big penalties, more transparent and be
protected but they have to pay taxes and less competitive. When the benefits of operating in
the shadow economy are more than the cost of paying for it when discovered by law,
businesses tend to increase their activities in the shadow economy.
First, Straub (2005) develops a theoretical model in which firms measure the benefits and
costs of operating in the formal sector and the shadow economy. In particular, the benefits from
the formal sector are: the use of public resources such as working with state financial
institutions. Straub (2005) concludes that the lowest initial capital level of enterprises is the
major benefit of operating in the official (formal) economy deriving from support packages
from government financial institutions which cover small and medium enterprises with low
interest rates on the comparison between the formal and informal sector. The reduction of
binding legal obligations on the creditor's rights is obvious and it also reduced level of
ambiguity and tax obligation clause. While the disadvantages of taking part in the formal
economy cause the increase in participation costs, which may include costs of business
creation, fees and taxes.
Secondly, Capasso and Jappelli (2013) formulated the theoretical model where the firm
chooses between receiving high assistance when requiring collateral for credit from financial
institutions and getting low subsidies from production using internal capital sources. Capasso
and Jappelli (2013) also argued that the development of financial sector will increase the
opportunity cost of evading taxes, or underground operations, or the opportunity cost of
decreasing credit limit and the opportunity cost of not receiving new technology investment.
Moreover, Amaral and Quintin (2006) argued that in developing countries, formal workers tend
to gain more experience, be more educated, and earn more than informal workers. Research
indicates that low-skilled workers face barriers to entry into the formal sector. In equilibrium,
the author finds the characteristics of informal and informal workers differ systematically,
42

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