The effect of corruption on economic growth in southeast asia countries

LIST OF FIGURESFigure 1: The effect of Corruption on Economic growth……….21 Figure 2: Scatter graph between Economic growth GDP and Corruption CPI………...37 Figure 3: Scatter graph between

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

VIETNAM - NETHERLANDS

THE EFFECT OF CORRUPTION ON

ECONOMIC GROWTH IN ASIAN COUNTRIES

BY

LE KIM DUNG

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES

VIETNAM THE NETHERLANDS

VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

THE EFFECT OF CORRUPTION ON

ECONOMIC GROWTH IN ASIAN COUNTRIES

A thesis submitted in partial fulfillment of the requirements for the degree of

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

BY

LE KIM DUNG

Academic supervisor

Dr TRUONG DANG THUY

HO CHI MINH CITY, Dec 2016

I CERTIFICATION

I confirm that this paper, namely “The effect of corruption on economic growth in

Asian countries” is my own work Where material has been used from other sources

it has been properly acknowledged and referenced If this statement is untrue I understand that I will have committed an assessment offence

I have read the Regulations of Vietnam – Netherlands Programme for M.A In Development Economics and I am aware of the potential consequences of any breach of them

Signature:

Name: Le Kim Dung

Date: Ho Chi Minh City, Dec 2016

I would like to extend my special thanks to Dr Truong Dang Thuy, the academic supervisor who always read and correct my thesis carefully His valuable comments, guidances, and encouragement help me to improve the quality of my thesis and complete it timely

I also would like to take this opportunity to express my thanks to Dr Nguyen Trong Hoai, Dr Pham Khanh Nam, other professors, tutors and course co-instructors of Economics University who, through their valuable lectures and advices, help me during the course

Finally, many thanks and gratefulness are given to my dear family, my warm friends for their encouragement in many ways that strongly support me during my study stage

III CONTENTS

Certifications……… I Acknowledment II

List of tables……… IV List of figures V

Abstract……… 1

CHAPTER 1: INTRODUCTION 2

1.1 Research problem 2

1.2 Research objectives and research questions 5

1.2.1 Research objectives 5

1.2.2 Research questions 5

1.3 Thesis Structure 5

CHAPTER 2: LITERATURE REVIEW 7

2.1 Theoretical concepts related to economic growth and corruption 7

2.2 Effect of corruption on economic growth: theoretical literatures 9

2.3 Effect of corruption on economic growth: empirical studies 11

2.3.1 The single equation approach 11

2.3.2 The system of equations approach 13

CHAPTER 3: METHODOLOGY AND DATA 21

3.1 General methods 21

3.1.1 Conceptual framework for the study 21

3.2 Research models and econometric methodology 25

3.2.1 Research models 26

3.2.2 Econometric methodology: 29

CHAPTER 4: ESTIMATION RESULT ANALYSIS AND DISCUSSION 34

4.1 Descriptive statistics analysis on the dataset 34

4.2 Regression results and discussion 42

4.2.1 Effects of corruption on economic growth directly 42

4.2.2 Effects of corruption on economic growth indirectly through transmitions channels 44

CHAPTER 5: CONCLUSION, LIMITATION AND FUTURE RESEARCH 52

5.1 Conclusion 52

5.2 Limitations and future research 52

5.2.1 Limitations 52

5.2.2 Suggestion for future research 53

REFERENCES……….… 55

APPENDIX Appendix A : Summary of empirical studies……….…….63

Appendix B : Sample of countries.……….68

Appendix C : Regression results……….69

IV LIST OF TABLES

Table 1: Expected sign of selected variables……….………….……….25 Table 2: Model specification of growth and transmission channel equations……….……29 Table 3: Summary of Variables ……….…………32 Table 4: Descriptive statistics and correlations of selected variables………….………….36 Table 5: Correlations of selected variables……….………….37 Table 6: Results of Pooled OLS, Fixed effect model (FEM), and Random effect model (REM) in GDP regression model (Model 1)………42

Table 7: Results of 3SLS regression in a system of structural equations………46 Table 8: Consequence of Corruption on Economic growth through transmission

channels……… … 47

V LIST OF FIGURES

Figure 1: The effect of Corruption on Economic growth……….21 Figure 2: Scatter graph between Economic growth (GDP) and Corruption (CPI)……… 37 Figure 3: Scatter graph between Economic growth (GDP) and Political Instability (PI)………38 Figure 4: Scatter graph between Economic growth (GDP) and Investment (I)………… 38 Figure 5: Scatter graph between Economic growth (GDP) and Human Capital (HC)……39 Figure 6: Scatter graph between Economic growth (GDP) and Trade Openness (OPEN) 39 Figure 7: Scatter graph between Economic growth (GDP) and Government Expenditure (GOV)……… …39 Figure 8: Scatter graph between Corruption (CPI) and Investment (I)……… …40 Figure 9: Scatter graph between Corruption (CPI) and Human Capital (HC)………….…40 Figure 10: Scatter graph between Corruption (CPI) and Political Instability (PI)…… …41 Figure 11: Scatter graph between Corruption (CPI) and Government Expenditure (GOV)41 Figure 12: Scatter graph between Corruption (CPI) and Trade Openness (OPEN)……….41

ABSTRACT

Many theoretical and empirical studies suggest that economic growth depends on various factors such as physical capital, human capital, openness to trade, macroeconomic conditions, corruption perceptions, education, and population growth This study focuses on summarizing these studies and examining the total impact of corruption on economic growth Based on panel data included thirty Asian countries over the observation period 1996-2014, this paper applies both ordinary least square (OLS) technique and three-stages least square (3SLS) technique to determine how corruption impacts on economic growth directly and indirectly through five possible transmission channels: investment, human capital, political instability, government expenditure, and the openness of international trade In consistency with findings of the previous empirical researches, this paper concludes that the effect of corruption on the economic development of thirty Asian countries is significantly negative

Keywords: economic growth, corruption, investment, human resource, political

instability, government expenditure, openness to trade

CHAPTER 1: INTRODUCTION

1.1 Research problem

During the past few decades, various researchers have tried to identify what are the most important determinants of economic growth, and why some nations have experienced quick long-term income growth rates while others have not A fundamental cause for this study is the lack of a final agreement about the engine of growth because there are many factors that influence the development of the economy Indeed, two most popular growth theories, the neoclassical growth theory

by Solow (1956) with the cruciality of investment activities and the endogenous growth theory by Romer (1986) and Lucas (1988) focusing on labor and the capacity of innovation lead to various extensions and country developments later These developments raise a big discussion about the most important sources of growth While some researchers refer to factors such as labor, capital, investment, technological progress, government spending, and openness of trade economic freedom; the others are referring to institutions, democracy, rule of law, geography factors, and corruption

In searching for the important growth determinants, a lot of economists focus on corruption, for example, Left (1964), Becker (1968), Lui (1985), Manion (1996), Kaufmann and Wei (1999), Haque and Kneller (2009), Mohamed Dribi (2013), Diaby and Sylwester (2014), Pak Hung Mo (2014) Even then, their lituratures have not approached to the last concord about the effects of corruption on economic growth Some papers stated that with a suitable level of corruption, the correlation between corruption and economic development is positive In the country that has wordiness, sophisticated, unclear administrative procedures, corruption is needed for completing an economic operation quickly such as building a house, application for licenses, organizing a company It can shorten businessman wasting time for queuing in line and paperwork (Lui, 1985) The “efficient grease” hypothesis stated that corruption improve economic effiency, and firms give more bribes should have approach capital with lower cost easily Corruption is also a side effect of an

emerging country and a free open market economy Manion (1996) clarified that: to avoid costly delays, applicants make corrupt overpayments to officers for enterprise licenses to which they are fully entitled In making such payments, bureaucrats enhance their income base When administration staff have high income, they spend more for goods and services so the economy will grows In addition, undeveloped states can not deal with corruption without having achieved the high level of economic development necessary If not, the governmet will spend a lot of labor force, time, and money to reduce corruption

However, a numerous evidences on significant negative corellation between corruption and economic growth are showed in many empirical researches after managing the vital determinants of economic like government expenditure, human capital, trade openness, investment, political instability, including Mauro (1995), Mauro (1996), Pak Hung Mo (2001), Pellegrini and Gerlagh (2004), Lorentzen, Mc Milan and Wacziarg (2008), Pellegrini (2011), Marie Chene (2014) For instance, the causual association between corruption and growth has been investigated in the study of Mohamed Dridi (2013) by employing the Channel Methodology (method which was developed by Tavares and Wacziarg in 2011) Based on cross-country data including 82 developed and developing countries for a period of 1980-2002, the author found that corruption affects the economic growth negatively The empirical result indicated that one point increased in the corruption index will generate 0.9 percent decreased in the annual growth rate via human resources, government spending, investment, inflation, political condition, and openness The paper futher concluded that human resources and political situation are the most crucial transmission channel through which corruption transmits its negative impact

on economic growth Unlike Mohamed Dridi, Mo (2001) used the decomposition method and found that the political instability accounts for 53 percent of the total corruption effect on growth Furthermore, using cross-coutry regression, Mauro (1996) showed the strong negative effects of corruption on growth in 94 countries

corruption reduces investment, especially in private sector, and declines the government expenditures in developing education seen as the vitual element of growth With the data from Global Competiveness Report Serveys in the year 1996 and 1997, based on Stackelberg game theory, Kaufmann and Wei (1999) checked the relationship between bribe payment and effective bureaucratic molestation They found that no evidences support for the “speed money” hypothesis, expressed differently, they refuted “efficient grease” thesis, so corruption reduces economic growth

Besides, the correlation between corruption and economic growth is still uncertain

in some findings from previous papers (Andvig and Moene, 1990; Ehrlich and Lui, 1999; Aidt et al, 2008; Haque and Kneller, 2009; Leite and Weidmann, 1999) By employing Threshold model with 54 developed and developing countries data set observed from 1980 to 2003, Haque and Kneller (2009) stated about Threshold effects Firstly, there is existence of a strong mutual negative relationship between corruption and economic growth Secondly, corruption is changeable and this relationship depends on the culture of corruption, any changes in culture tends to the destruction of the threshold Thirly, because of almost resources belongs to the state, government principally concerns with corruption, so development traps move

up Ehrlich and Lui (1999) also showed the non-linear correlation between corruption and economic growth

Therefore, in contributing to the discussion, this thesis aims at providing a general look at the corruption and economic growth through revisiting the most popular theoretical and empirical studies This study also re-examines the impacts of corruption on economic growth in Asian countries by applying various econometric techniques A new data set is collected and analyzed by formulating some economic growth equations with possible transmition variables of corruption The results will support further evidences on the casual relationship between corruption and growth

1.2 Research objectives and research questions

1.3 Thesis Structure

This thesis is divided into five chapters

Chapter 1: Introduction presents numerous conclusions about the correlation

between corruption and economic growth from various theoretical and empirical researches Besides, it explains what vital objectives are, what research questions should be raised to answer in this paper

Chapter 2: Literature review provides a general review of economic theories

associated to the causal correlation between corruption and economic growth This part describes theoretical framework and empirical studies consistent with this issue In addition, the definitions of the variables used in the model are mentioned

in this chapter

Chapter 3: Methodology is concerned about the general methods and how to

check effects of corruption on economic growth directly and indirectly, which

- analytical framework for the problem to be investigated

- appropriate models with variables to be described for the issue

- data sources and sample to be used to estimate the existence the corruption – economic development relationship

- research methodology and technique for processing and analyzing data set

Chapter 4: Empirical Findings focuses on presenting the estimation results about

influences of corruption on growth

Chapter 5: Conclusions, Limitation and Future research comes to the main

findings achieved in the previous chapter Accordingly, this part points out the limitations and further studies concerning the relationship between corruption and economic growth

CHAPTER 2: LITERATURE REVIEW

2.1 Theoretical concepts related to economic growth and corruption

Definition of economic growth

Economic growth is an expansion in productive capacity of commodities and services, and average national income level in a period of time, compared with an another period (Perkins et al., 2006, p 12)

In comparison of economic growth from two countries, Gross Domestic Product (GDP) or Gross National Product (GNP) are in common use GDP and GNP can be caculated in nominal denomination, which includes inflation, or in real denomination, which is adjusted inflation

Theories of economic growth

Despite the absence of a dominant theory, almost all economic growth researches argue that differences in level of income across the countries around the world are due to differences in factor endowment, factor productivity, technology, the combination of any two factors, or all the above

In the first growth theory, and perhaps the most popular theory, Solow (1956) found that capital has less contribution to economic growth than expected, leaving a large residual unexplained, even after taking account for effective labor

Besides the research of Solow, growth theory moved into two separate directions In

one direction, some economists raised concerns on the correctness of the aggregate

production function employed by Solow As one of the most notably researches within this direction, Lewis (1954) introduced his dual sector model which explained the economic growth by the transition of labor force between two sectors,

from the traditional agriculture section to the modern industry section In the other

direction, many economists turned their attention to seeking an explanation of why

the effect of exogenous technical change (Solow residual) being so large in reality, quite different from the theoretical prediction In explaining why growth rates differ, they focused on the interactions of political and economic factors The most

notable works in this trend included the literature by Lucas (1988), Romer (1989), Mankiw, Romer, and Weil (1992) These efforts mainly tried to adjust labor for quality and led to various endogenous growth theories Endogenous growth theories included some additional variables into the neoclassical production function of Solow such as human capital, R&D By including human capital into the neoclassical production function, the cross section study by Mankiw, Romer and Weil (1992) has explained about eighty percent of the variation in the growth rate Although endogenous growth theory has pointed some vitual elements of the Solow residual, Robert J Barro (1991), Barro and his colleague (1995) has identified some another factors and used as a benchmark for subsequent empirical works In details, these economists checked the significance of human resouces, government policies, quality of institution, trade openness, freedom, development aid, reforms of finance.

Concept of corruption

In term of definition, corruption is a complex phenomenon Generally, corruption is

the misuse of entrusted authority for extra positive personal benefit (Transparency International website)

In term of typology, corruption divided into three categories as grand corruption,

bureaucratic corruption and political corruption determined by the sector where it happens and how much money paid off

-Grand corruption (nearly the same meaning as political corruption) comprises about activities involving high level of public area that falsify government policies or the central operating of the nation This kind of corruption is centralized and can affect all citizens in the country

-Bureaucratic corruption (or petty corruption) refers to the small amount of money which ordinary citizens pay for public bureaucrats to access basic commodities or sevices in places like public hospitals, schools, police departments, licensing authorities, taxing authorities, and other agencies This type of corruption has also been called “low-level” or “street-level” corruption It is decentralized that

the exact bribes taken are not arranged It just makes bureaucrats speed up the procedure or skip legal penalties

-Political corruption is defined as the situation in which political decision makers abuse their position to influence policies, organizations and processes in the allocation of public resources and investment in order to strengthen their jurisdiction, position and wealth This type of corruption is also considered as having impact on the result of election voted by legislators

In term of measurement, the most popular corruption measures used in most

empirical researches are the Corruption Perception Index (CPI), Bribe Payers Index (BPI), Global Corruption Barometer (GCB), and National Intergrity System assessments (NIS) recored by Transparency International institution; the Control of Corruption Index(CC) caculated by the Worldwide Governance Indicator group; the Corruption Index (CI) produced by the International country risk guide CPI will be also employed in this study This indicator has a limitation in scope It just indicated perceptions of the extent of public sections corruption, such as administrative category, political category

2.2 Effect of corruption on economic growth: theoretical literatures

Owning to rent-seeking, queue model, and transaction cost theory, corruption has an effect on output through capital, labor, and other economic factors It reduces productive work so declines actual wealth creation, losts government revenue, lowers income equality through inefficient allocation of resources includes capital and labor

- Rent Seeking:

“Rent Seeking” is one of the most important concept involves in corruption Gordon Tullock originated this concept in 1967, and it was introduced in 1974 by Anne Krueger Klostad and Soreide (2009) stated that individuals and groups are said to seek rents when they try to get extra profits for themselves through the political arena instead of allocation their time and skills at the right way

Bade, R and Parkin, M (2013) supported that rent seeking activities as bribery, lobbying, and other political activities aiming to collect the benefits from international trading and get the profits during the process Because of rent seeking culture (tariff on a good, restrictions on import, quota on import), the misallocation

of resources makes a deadweight loss in which no-one can obtain surplus and social benefits decrease Higher price leads to lower output It means economic growth reduces

- Queue Model:

Queueing theory was developed by Agner Krarup Erlang in 1909 This model is constructed to predict queue lengths and waiting time for a good or service This model applied for companies, shops, offices, and hospitals Lui (1985) developed this model to illustrate the circumstance in which bureaucrats issue business licenses to firms and grant privileged treatment to people who suborn the relevant administrators in order to expedite the proceduces For example, if business entity would like to establish a company or set up a factory, there paperwork would be reduced and a license will be granted quickly and easily through bribery It can express differently, corruption has a positive relationship with the growth rate

- Transaction Cost Theory:

Lambsdorff (2002) metioned that transaction cost of legal contract include seeking partners and information costs, bargaining and determining appropriate contract condition costs, policing and enforcement of contract term costs These costs of corruption agreements needs to be concealed So, most corrupt contracts are discussed through broker

Lambsdorff (2002) also mentioned that if parochial corruption exists in a market to trade goods and services, the total transaction cost will rise because there need to be more expenses to find potential contractors The accelerating costs come from searching potential partners, quality appraisal, product and individual ability evaluation as well as eagerness to abide by corrupted products The search for partners will stop when the costs reaching marginal transaction cost of searching

one additional partner, which is equal to the estimated profit generated from a potentially superior dealing with another competitor

This means that the higher the marginal transation cost is, the fewer potential collaborator to be sought As a result, entrepreneur can save the capital and invest

in another project When the project continues, this will allow to hire more workers for system operations and enhance the productivity of goods and services It enhances economic growth as well

2.3 Effect of corruption on economic growth: empirical studies

There are two approaches analyzing the impacts of corruption on growth One is a single equation approach The other is a system of equations approach The former

is done by introducing corruption variable into the growth function, which allow to estimate the total impacts The latter uses a system of inter-related equations, which allow for separating the direct and indirect correlation of corruption on growth

2.3.1 The single equation approach

Corruption is a debatable issue that occurs all over the world regardless the nations are rich or poor, developed or undeveloped, democracy or dictatorship, socialistic or capitalistic Many economists have tried to identify the correlation between corruption and economic growth, but their lituratures have not come to the final agreement yet Some reseachers demonstrated that the suitable level of corruption has a positive effect on country development Leff (1964) with “grease the wheel” hypothesis proved that corruption might raise economic growth because of removing government-imposed rigidities and interfering with other economic decisions favourable to growth Lien (1986) with Competitive bribery game and Lui (1985) with Equiblirium queuing model also suggested that corruption may be enhance economic growth

In contrast, the concern about the bad impacts of corruption on economic growth

has increased rapidly in both developing and developed countries Various empirical studies have shown up on this issue, including Mauro (1995), Tanzi

suggested that private firms who win government’s contracts by high paying are not necessarily economically competitive firm and such un-optimal use of human resource will destroy economic growth Moreover, private companies were often forced to make side-payments to corrupted government officials and that cost was often huge for small-scaled but emerging firms, which can be the driving force for growth of the economy.

With the dataset of 21 Africa countries covering the period 1993-1999, Kwabena Gyimah-Brempong (2002) modified the growth equation in a linear form include corruption as an independent variable:

g = α o + α 1 k + α 2 edu + α 3 x + α 4 corrupt+α 5 y 0 +α 6 govcon + ε i

where: g: rate of economic growth of real income (dependent variable)

εi : stochastic error term

αi: coefficients to be estimated

k (investment rate), edu (educational ettainment of the adult population), x (growth rate of real export), corrupt (corruption), govcon (government consumption), yo (initial level of income) are explanatory variables

Employing OLS regression method, Kwabena Gyumah-Brempong (2002) concluded that corruption affects economic growth negatively and significantly

Using growth rates of GDP per capita for the period 1960-1985 (from Summers and Heston – 1988 dataset source) and Business International’s 1984 corruption index, Mauro (1995) applied a simple regression with instrumental variables (ethno-linguistic fractionalization) and also showed that the standard deviation of corruption index has negative correlation with the annual growth rate of GDP per capita significantly But without control variables, this result is not robust After controlling for other variables, including secondary education in 1960, government expenditure, assassinations, investment, political instability index, the effect of corruption on growth becomes insignificant

Nwankwo (2014) also employed Johansen co-integration test, granger-causality test, Unit root test, Error correction mechanism and OLS method to check only the simple econometric model below:

Linear function: GDP = b0 + b1 * COR + Ut

and Log function: Log (GDP) = b0 + b1log(COR) + Ut

Where: GDP is gross domestic product, COR is corruption index Using dataset gathered in Nigeria for the period 1997-2010, Nwankwo (2014) found that there is a long-run relationship between corruption level and economic development The author also concluded that corruption influences Nigeria’s growth negatively (b1 = -4.680)

In conclusion, there are not many researches finding out the direct impact of

corruption on economic growth is significant The reason is that corruption aslo through many possible transmission channels such as investment, education, international trade, political conditions, government expenditure, transmits its impact on growth So the system of equation approach used to calculate the overall effect of corruption on development

2.3.2 The system of equations approach

Applying the system of equations approach to check the direct and indirect effect of corruption on the economy, a numerous papers stated that corruption has a negative impact on economic growth such as Pak Hung Mo (2001), Pellegrini and Gerlagh (2004), Lorentzen, Mc Milan and Wacziarg (2008), Pellegrini (2011), Marie Chene (2014), Campos et al., (1999), Mohamed Dribi (2013) The typical system of equations is specified as below:

Direct effect: GDP = f(CPI, TV) (named as equation 1a, 1b)

Indirect effects: TV = f(CPI, GDP) (named as equation 2a, 2b)

where TV presents other determinants of economic growth

2.3.2.1 Direct effects of corruption on economic growth

Pellegrini and Gerlagh (2004) modeled the direct relationship between economic growth and corruption as follows:

G i = α o + α 1 ln(Y o i ) + α 2 C i + α 3 Z i + ε i (equation 1a)

Where:

Gi : dependent variable, represented by GDP growth rate per year

covering the period from 1975 to 1996, Gi = (1/T)ln(YTi/ Yoi) ln(Yoi) : independent variable, represented by the logarithm of the degree

of initial income with negative coefficient, α1 < 0

Ci : explanatory variable, represented by corruption which measures

the extent of bribes and bribes asking in one country from 1980

to 1985 Data are from the Corruption Perception Index by Transperancy International

Zi : vector of other independent variables: investment, schooling,

trade openness, political instability (Levine and Renelt, 1992; Sachs and Warner, 1995)

Investment: The percentage of gross public investment and private investment

on GDP Then they calculated an average for the whole period 1975-1996 Data are from Penn World table 6.0

Schooling: The average years of schooling of all residents over 25 years old

in 1975 Data are taken from the International Data on Education Attainment by Barro and Lee

Trade Openness: The number of years opened for trade of each country over the

εi : denoted as Error term

i, t : Country i and time t respectively

With above model, Pellegrini and Gerlagh (2004) regressed the data set of 48 countries covering the period 1965-1996 and got the results The coefficient for corruption is negative and equal to 0.07 (decrease almost to zero) It means the direct effect of corruption on economic development is negative, insignificant, and insubstantial Pak Hung Mo (2001) examined the correlation between corruption and growth via the model below:

GR = F (CORRUPT, y70, PRIGHT, PRIGHT2, HUMAN, INSTAB, IY, POPG)

(equation 1b)

Where

GR : Growth rate of real GDP in percentage

CORRUPT : Corruption index

y70 : The initial per capita of national income

PRIGHT : The Gastil index of political rights

HUMAN : Average years of schooling in the total residents over the age of

twenty five from 1970 to 1985 INSTAB : Measure of political instability

IY : Ratio of private investment to GDP

POPG : Rate of population of one country growth

With panel dataset collected by Robert Barro and Jong-Wha Lee covering the period 1960-1985, the OLS regresstion results of Mo (2001) showed that corruption has an insignificant negative effect on the volume of output The coefficient for corruption is negative and equal to just 0.06459

2.3.2.2 Indirect effects of corruption on economic growth – Channel of Transmission

Based on the previous empirical studies relating indirect impact of corruption on economic growth, this research focus on five transmission channels: political instability, investment, human capital, government expenditure, and trade openness

Mo (2001) suggested the below formula to compute the influence of corruption on growth via plausible elements

Zi : represented the impact of corruption on the vector of dependent

variables: investment, schooling, openness of international trade, political instability

ln(Yoi) : represented by the logarithm of the degree of initial income

Ci : described by corruption

βo, β1, β2 : four-dimensional vectors of coefficients

µi : denoted as the vector of residuals

To control endogeneity of the corruption variable through 2SLS regression, Mo (2001) used continental dummies (dummy for East Asian countries, dummy for Latin-American countries, dummy for OECD countries, dummy for Sub-Saharan African countries) and ethnolinguistic fractionalization while Pellegrini and Gerlagh (2004) used legal origins as instrumental variables Legal origins in this research is defined as a set of dummy variables that characterize the countries as Scandinavian, French, English or German Furthermore, to test robustness, Pellergrini and Gerlagh also added some other independent elements such as regional dummies, democracy indexes, OECD dummy to OLS regression

2.3.2.2.1 Investment

Mello (1997), Bengoa and Robles (2003) stated that investment boosts up the economic growth However, corruption discourages domestic and foreign direct investment (FDI) because of additional transaction costs in conducting targeted project Most studies proved that corruption has a negative relationship with investment significantly, and hence it reduces the volume of output Sarkar and H (2001) mentioned that corruption will increase the price of goods or services, lower the quantity demanded, and the quantity of output Bardhan (1997) reported that speed money is an requirement for entrepreneurs to commence their business in a country with high level of corruption But, if business profit is lower than amount of bribe, they may be choose a shutdown of production As a consequence, Mauro (1995) expressed that corruption decreases the incentives to investment because profit of productive investment will decline when the amount of bribes is higher In the corruption-growth correlation, Mo (2001) quantified that investment mechanism accounts for 28.4 percent of the impact of corruption on growth Pellegrini and Gerlagh (2004) also proved that one degree in corruption level enhances 2.46 percentage point in investment, which in turn increases 0.34 percentage point in economic growth

2.3.2.2.2 Human Capital

Investment in education for creating high skilled labour force will promote other factors’ productivity, and hence contribute to economic growth In the other words, schooling is positively correlated with GDP per capita across countries as stated by Barro and Martin (1995) However, Rumyantseva (2005) found that the existence of corruption in educational organizations leads to low quality of labour force Besides, Murphy et al (1991) also proved that the presence of bribes will cause the suboptimal use of human capital In the other words, people without skill and knowledge have many opportunities to obtain high positions easily by offering bribes to the educators in order to get value educational degree Latova and Latov

(2008) supported that fraudulent educational system may lower the quality of human capital through no actual knowledge learned by student Furthermore, Mo (2001) indicated that corruption has a negative effect on growth via human capital Based on panel dataset collected by Robert Barro and Jong-Wha Lee covering sample period from 1960 to 1985, he proved that due to human capital channel, one percent decrease in corruption leads to 9.7 percent increase in productivity In the research of Pellegrini and Gerlagh (2004), this number is 0.06 percent per year in growth (in which human capital represented by half a year of schooling of the people above 25 years)

2.3.2.2.3 Political Instability

Pak Hung Mo (2001) stated that corruption increases inequality in income through depressing level of ouput, biasing systems of taxation preferring the rich, diminishing effectiveness of social spending, and accumulating unequal approach to public services of residents Hence, the poor make more violent reaction to protest against corruption activities It increases political instability, which in turn decrease

in investment operation, job opportunities, and productivity growth He proved that corruption has a strong positive correlation with political instability Then, in the corruption-growth linkage, he calculated that political instability accounts for 64 percent of the effect of corruption on national growth Pellegrini and Gerlagh (2004) also mentioned that one-standard deviation decrease in corruption leads to decrease 0.06 point in political instability index, in turn associated with 0.14 percent per year increase in growth

2.3.2.2.4 Government Expenditure

Government expenditure is an effective tool to stimulate economic growth Easterly and Rebele (1993) pointed out a productive government spending on transportation infrastructure brings lower production cost, higher productivity Chude and Chude (2013) mentioned that effective government expending on education and health creates high skilled labor force It means higher quality human capital, higher level

of country output However, many researches showed that the existence of

corruption affects the structure of public spending and reduces economic growth Mauro (1995) discovered that high level of corruption associated with inefficient government investment on education Gupta, Mello, and Sharan (2001) also reported that corruption increases misallocation of government spending on healthcare and public works In opposite, Daniel J Mitchell (2005) claimed that the expansion of government expenditure can bolster economic development by putting more money into people’s pockets Mohamed Dribi (2013) with data covering 82 both developed and developing countries from 1980 to 2002, regressed many econometric model and proved that corruption has positive effect on growth via government expenditure channel

2.3.2.2.5 Trade Openness

Most of papers completed by the conclusion of significant positive relationship between openness to trade and economic growth Yanikkaya (2003) indicated that trading allows developing countries get more benefit through exchanging in technology advancement and sharing of technical knowledgement However, corruption increases the transaction cost of trade openness, not only bribes payment for the allocation of quota, tariff and trade licenses, custom bureaucracy, but also the uncertainty of signing illegal agreement and the competition by the international rivals (Lambsdoff, 2002) Pellegrini and Gerlagh (2004) carried out a 2SLS regression and found that one standard deviation increase in corruption, 0.19 decrease in trade openness, which in turn 0.30 percent decrease per year in growth

To sum up, Mo (2001) suggested that the overall impact of corruption on economic

growth can be separated into two parts: direct impacts (equation 1b) and a set of indirect impacts through the channel variables (equation 2b) With regression

results, he proved that corruption has a negative impact on growth The contribution

of direct effect and the transmission mechanisms described are: direct effect (-11.8), human capital (-14.8), political instability (-52), investment (-21.4) in percentage point

Pellegrini and Gerlagh (2004) also stated that corruption and growth has a negative relationship, expressed in detail, a one point increase in corruption index reduces the output growth per capita by 0.38 percentage point The vitual channel via which corruption affects growth is investment The contribution of fixed investment, trade openness, political instability, human capital to the total negative effect is 32%, 28%, 16%, 5% respectively This total effect is also calculated by Pellegrini and Gerlagh’s equation below:

G i = (α o + α 3 β o )+ (α1 + α 3 β 1 ) ln(Y o i ) + (α 2 + α 3 β 2 )C i + α 3 µ i + ε i

in which α2 is the direct effect, and α 3 β 2 is the sum of the indirect effects of corruption on economic growth (value of α2 , α 3 got from equation 1a, and value of

β 2 got from equation 2a)

To test the corruption-growth correlation, beside five endogenous variables (namely human capital, investment, government expenditure, inflation, political instability), Mohamed Diribi (2013) also added some exogenous variables such as public expenditure on education (PSE), rate of urban population, ethnolinguistic fractionalization, total population of the country, share of total residents under 15 and over 65, landlocked dummy, trade openness, uninterrupted democracy dummy

By using 2SLS, 3SLS method, he showed that the contribution of human capital, investment, inflation, political instability to negative impact of corruption on growth

is 36.6%, 22.9%, 6.6%, and 33.8% respectively Corruption has positive effect on growth via government expenditure channel

CHAPTER 3: METHODOLOGY AND DATA

3.1 General methods

3.1.1 Conceptual framework for the study

Figure 1: The effect of corruption on economic growth

Corruption perceptions index (CPI) (-) (DIRECT EFFECT)

Political Instability Human Capital

Governmet Expenditure

Economic Growth (GDP)

Gross investment (I)(-)

The secondary school

enrollment rate (-)

Political Stability (PI) Absence of Violence(-)

Ratio of Ex plus Im to GDP (OPEN)(-)

Government final Consumption Expenditure (GOV) (+)

Analytical framework

The basic framework for this study is the Solow growth model Behind this growth model is the production function In this function, the level of output depends on the level of capital (K), human capital or labour force (L), and the Solow residual (A) Many empirical researches have shown that using production function to estimate the growth rates, factor accumulation only explains about half of the variation in output growth and the rest is given by the Solow residual, which is actually the measure of ignorance of the possible determinants of the economic growth So, besides using the traditional variables such as capital or labor level, this study will also pick up and verify the most significant determinants proposed by previous empirical researches (corruption, political condition, government expenditure, and trade openness) This paper tries to find out how much of the variation in economic development can be explained by the factor accumulation or some key potential determinants of the Solow residual Especially, this thesis focuses on the effect of corruption on economic growth directly and indirectly

While Mauro (1995), Acemoglu and Verdier (1998), Mo (2001), Blackburn et al (2008), Aidt (2009) investigated that growth in wealth per capita and corruption has negative correlation, Lui (1985), Lien (1986), Leff (1964) emphasized that corruption may be efficient with growth The others cited the non-linear relationship between corruption and growth (Ehrlich and Lui, 1999) So, the above conceptual framework is employed to clarify how corruption affects economic development in Asian countries directly: positive, negative, or uncertain

Beside the direct correlation between corruption and country development, the impact of corruption can be transmited to economic growth indirectly via five possible channels: investment, human capital, political instability, government expenditure, and openness to trade

In terms of the first channel – investment, corruption increases transaction costs and

asymmetric information so reduces the motivation to invest The decrease in the

capital accumulation has a negative impact on national income From the literature review, this paper synthetized that reduction in investment leads to shrinking in growth and benefit of both entrepreneur and individuals The Solow growth model emphasized the importance of investment with production factors (capital and labor) and technology residual This study will use the level of capital to investigate the impact of corruption on growth through investment Due to the deficiency of reliable data on capital stock in many countries, the gross domestic fixed investment

is used to measure the level of capital However, Bosworth and Collins (2003) showed that investment ratio, as a proxy for capital, gave poor results Therefore, this research will use another method proposed by Rodney Smith (2010) to generate

a capital stock series based on the gross fixed capital formation indicator by World Bank:

In terms of the second channel – human capital Labour is the fundamental source

of economic growth Human capital refers to labor’s accumulation of skills through education, training, experience, and is a major factor that affects technology level and the productivity of other production factors Various findings such as Robert J.Barro (1991), Mankiw and his colleagues (1992), Barro and Sala-i-Matin (1995) have evaluated the quality of human resource using proxies coordinated to education (examples, rate of schooling enrolment, average years of schooling) and found evidences suggesting that skilled labor is the vital factor of economic development The more skilled workers in the economy, the more goods and services produce, and it makes the country develops quickly However, corruption reduces productivity in the economy due to own benefit seeking and external force Moreover, corruption is the reason of decrease in budget for education investment

In the other words, corruption has a negative consequence on growth transferred via

human capital As the data of average years of schooling is only collected each five years, this study will use the secondary school enrollment rate as the proxy for human capital instead

In terms of third channel – political instability An important feature of the

institutional framework that influences the relationship between corruption and growth is the level of political stability (evaluated by equity, gap between rich and poor, number of violences) In the period of high degree of political instability, corruption makes bad environment for economic performance easily It means corruption has a positive correlation with political instability

In terms of four channel – government expenditure Corruption affects to growth

via government spending in infrastructure, education, healthcare With supreme power, government take any opportunities to expand state budget and get more money in the pocket by corruption So that, they allocate the fund inefficiently Unproductive using of government budget in public works leads to negative impacts on country development In opposite, Daniel J Mitchell (2005) claimed that government spending expansion can bolster economic growth by putting more money into the market This paper will take government final consumption expenditure in the model as the proxy for transmission channel to check the impact

of corruption on economic growth

Finally, in term of fifth channel - trade openness A popular determinant for

economic growth, especially for developing countries, is trade openness Various literatures have found that countries which are more open to international trade often have higher GDP per capita and grew faster, such as Karras (2003), Robert and David (1999), Dollar (1992) Openness to trade affects growth through technology and knowledge transfer, increasing scale of economies And through trade openness, corruption conveys impacts to economic development based on quota, tax, and restriction on exporting and importing Pellegrini and Gerlagh (2004) illustrated that corruption and trade openness has a negative relationship

Following the approach employed by previous researches, this study will use the

ratio of exports plus imports to output as the proxy for openness to trade

3.1.2 Research hypotheses:

The hypotheses are intended to test in this research are follows:

- Hypothesis 1: Corruption has a negative impact on economic growth

- Hypothesis 2: Corruption has a negative correlation with economic growth

indirectly via investment channel

- Hypothesis 3: Human capital is the vital channel through which corruption

is likely to decrease economic development

- Hypothesis 4: Political instability is an important channel via which

corruption operates to reduce growth

- Hypothesis 5: Government expenditure is one of the channels that

involves a positive contribution of corruption on national income

- Hypothesis 6: Corruption negatively contribute to economic growth via

transmission channel – Openness to trade The expected signs of variables are described in Table 1

Table 1: Expected sign of selected variables:

Independent

variables

(Impact of…)

Dependent variable

(on EconomicGrowth)

Expected effect

Expected sign of coefficient

Source

Corruption (CPI)

GDP

Negative (Direct effect)

Positive (+)

Blackburn et al (2008) Paulo Mauro (1996) Pak Hung Mo (2001) Rock and Bonnet (2004) Corruption

Mohamed Dribi (2013) Paulo Mauro (1996)

Investment (I) Tanzi and Davoodi (1997)

Pellegrini and Gerlagh(2004) Corruption

through Human

Capital (HC)

Negative Positive (+)

Mohamed Dribi (2013) Pak Hung Mo (2001) Pellegrini and Gerlagh(2004)

de Vaal (2009) Pak Hung Mo (2001) Pellegrini and Gerlagh(2004) Corruption

through

Government

Expenditure

(GOV)

Positive Negative (-) Mohamed Dribi (2013)

Ugur and Dasgupta (2011)

3.2 Research models and econometric methodology

3.2.1 Research models

Based on the theoretical arguments summarised as aboved, this research mainly

investigates the impacts of corruption on economic growth directly and indirectly

via five possible transmission channels: investment, human capital, political instability, government expenditure, and openness to trade

With the objectives as presented in this paper, the system of estimated regression equations on examining the corruption – economic correlation are suggested as follows:

- First regression function: Examining the effect of corruption(CPI) on

economic growth (GDP ) directly:

GDP it = α o + α 1 CPI it + α 2 I it + α 3 HC it + α 4 PI it + α 5 GOV it + α 6 OPEN it + ε it (1)

- Second regression function:Investigating the impacts of corruption (CPI) on

economic development (GDP)indirectly through five transmission channels:

I it = β o + β 1 LnGDP it + β 2 CPI it + β 3 HC it + β 4 OPEN it +β 5 DLI i + β 6 DLMI i + β 7 DUMI i + β 8 DHIO i

+ β 9 DHINO i +σ it (2)

HC it = δ o + δ 1 LnGDP it + δ 2 CPI it + δ 3 PSE it + δ 4 LnPOP it + δ 5 URBAN it +δ 6 DLI i + δ 7 DLMI i +

δ 8 DUMI i + δ 9 DHIO i + δ 10 DHINO i +µ it (3)

PI it = i o + i 1 LnGDP it + i 2 CPI it + i 3 GOV it + i 4 LnPOP it + i 5 URBAN it + i 6 DLI i + i 7 DLMI i +

i 8 DUMI i + i 9 DHIO i + i 10 DHINO i + π it (4)

GOV it = j o + j 1 LnGDP it + j 2 CPI it + j 3 HC it + j 4 URBAN it +j 5 DLI i + j 6 DLMI i + j 7 DUMI i +

j 8 DHIO i + j 9 DHINO i +Ω it (5)

OPEN it = x o + x 1 LnGDP it + x 2 CPI it + x 3 GOV it + x 4 HC it +x 5 DLI i + x 6 DLMI i + x 7 DUMI i +

x 8 DHIO i + x 9 DHINO i + £ it (6)

The explanatory variables and dependent variables are defined as follow:

 GDP: Growth rate of real GDP (annual percent growth) This indicator measured by the annual percentage growth rate of gross domestic product (GDP) based on constant local currency

 CPI: Corruption Perception Index (a unit) This index ranges from zero to ten whereby lower point indicates higher level of corruption and vice versa

 I: Gross domestic fixed investment (annual percent growth) This indicator measures how much capital is invested in infrastructure such as land improvements (fences for defence, drains, ditches, water delivery, sewage treatment and so on); plant, machinery, equipment purchases; the

schools, offices, hospitals, private residential apartments, commercial buildings, and industrial factories (World Bank Indicator definitions)

 HC: (Human Capital) Gross enrolment ratio, secondary, both sexes (percent)

It means the total enrollments for secondary education, regardless of age In the other words, this figure expressed as a percentage of the official secondary education age population

 PI: Political stability and absence of violence (a unit) This indicator ranges from approximately -2.5 to 2.5 (weak to strong) governance performance Higher PI index reflects lower instability in political situation

 GOV: General government final consumption expenditure (percent of GDP) This determinant includes all current government spendings to purchase commodities and services (including benefits for laborers) It is also inclusive of most spendings on defense and security of the country, but exclusive of military spendings which are parts of national capital formation (World Bank Indicator definitions)

 OPEN: Openness to trade of GDP (percent of GDP) This indicator equals the ratio of sum of exports and imports of commodities and services to GDP

 LnGDP: Logarithm of GDP (current USD)

 PSE: Government expenditure on education, total (percent of GDP)

 POP: Total population (person)

 URBAN: Urban popupation (percent of total population)

 DLI (dummy variable) = 1 for low income countries

 DLMI (dummy variable) = 1 for lower middle income countries

 DUMI (dummy variable) = 1 for upper middle income countries

 DHIO (dummy variable) = 1 for high income countries in OECD group

 DHINO (dummy variable) = 1 for high income countries not in OECD group

Through equations from (2) to (6), this paper check the effect of corruption to each transmission channel Combine with equation (1), this study calculates the indirect

effect of corruption on economic growth via each channel by equation: (coefficient

of corruption in equations 2 to 6) x α, in which α from α2 toα6 in equation 1

Table 2: Model specification for Growth and Transmission channel equations:

model in Aidt et al (2008), Haque and Kneller (2009); Dynamic general equilibrium model in Blackburn et al (2006, 2008), Blackburn and Forgues-Puccio (2009); model based on a Stackelberg game in Kaufmann and Wei (2009); Equilibrium queuing model in Lui (1985) Besides, Channel methodology is employed to investigate the contribution of each transmission channel to the impact

of corruption to economic development (Mauro, 1995; Tavares and Wacziarg, 2001) These empirical studies also stated that most variables used are considered

as endogenous So the two stage least square (2SLS) (L Hansen, 1982) with instrument variable can adjust bias problems caused by inconsistent coefficient estimates because the simple ordinary least square (OLS) can not solve the presence of endogenous variables No correlations between instrument regressor and the error term in the equation is the most important condition to use this method

Following above empirical studies, firsly this study uses the results of descriptive statistics, correlation matrix, scatter diagram and graph to understand partly the correlation between corruption and economic growth and predict slightly the regression results Besides, to investigate the effects of corruption on growth indirectly through possible transmission channels (investment, human capital, political instability, government expenditure, and openness to trade), this research will employ the Channel methodology Furthermore, this paper also applies both the three stage least square (3SLS), the pooled ordinary least squares (OLS), fixed effects method (FEM), random effects method (REM) technique to analyze the corruption-growth relationship in thirty seleted countries

The two stage least square (2SLS) is the simplest and the most common estimation method for the simultaneous equations model It is an equation-by-equation technique, where the endogenous regressors on the right hand side of each equation are being instrumented with the regressors X from all other equations This method was developed by Theil (1953) and Busmann (1957) The three stage least square estimator (3SLS) was introduced by Zellner and Theil (1962) It can be seen as a

special case of multi-equation GMM where the set of instrumental variables is common to all equations If all regressors are in fact predetermined, then 3SLS reduces to seemingly unrelated regressions (SUR) Thus it may also be seen as a combination of 2SLS with SUR 3SLS estimator uses more information (include all equations at the same time) and estimate parameters precisely than 2SLS Because

of this reason, this paper carried out 3SLS regression

Diagnostic Checking for the equations:

Regression diagnostics are used to check on how well our data meet the assumption

of pooled OLS regression There are some diagnostic checks below:

 Normality of residuals: Shapiro-Wilk W test

 Homoskedasticity of residuals (the error variance should be constant): White’s test, Breusch-Pagan test

 Multicollinearity (two variables are near perfect linear combinations of one another): VIF test

 Model specification: Ramsey Reset test

3.3 Data

In accordance with the objectives mentioned in this research, we use panel data which covers thirty Asian countries, namely Armenia, Azerbaijan, Bangladesh, Brunei Danissalam, Cambodia, China, India, Iran Islamic Republic, Indonesia, Israel, Jajikistan, Japan, Jordan, Kazakhstan, Korea Republic, Kyrgyz Republic, Lao PDR, Lebanon, Malaysia, Mongolia, Myanmar, Nepal, Oman Pakistan, Philippines, Singapore, Srilanka, Thailand, Timor – Leste, Viet Nam The panel data brings two advantages First, the panel data allows to control for elements can not observe or evaluate, and elements changing overtime but not across entities Second, the panel data is more informative, efficient, and gives less collinearity among elements, and more degree of freedom through combining time series data and cross sectional data

The data is described briefly as follows:

- The number of observations: 558

- Variables: GDP (economic growth), CPI (corruption perception index), I (gross domestic fixed investment), Human Capital (total of labor force), PI (political stability and absence of violence), GOV (general government final consumption expenditure), OPEN (openness to trade of GDP), PSE (public spending education), POP (population), URBAN (urban population), and five dummy variables (DLI, DLMI, DUMI, DHIO, DHINO)

- Sources of the data: The data of corruption (Corruption Perception Index – CPI)

is taken from Transperancy International (TI) The secondary data of other variables

is collected from World Bank’ s World Development Indicators and Global

http://data.worldbank.org/indicators In detail, the Political Instability Index (PI) is gathered from the Worldwide Governance Indicators (WGI) project developed by Daniel K., Aart K., and Massimo M.(2010)

The summary of the variables, Abbreviation of Data and Source of Data are briefly reported in Table 3:

Table 3: Summary of variables:

World Bank Indicators

Corruption CPI

Corruption Perception Index (higher index, lower corruption level)

World Bank Indicators

Human Capital HC Total enrollment in

secondary education

Percent of population of secondary

World Bank Indicators