INTRODUCTION
more bribes The government officials do not want to act quickly because they want to have more time and force the people or enterprises spend more bribes to them With this behavior the officials have tendency to give out their decisions basing on the price of corruption The enterprises with better quality but without corruption will have the disadvantaged decision from the authorized officials So a good project may come to an inability enterprise The benefit from this project can be destroyed by this enterprise So by corruption, effective allocation in economic has been made distortion
This will have the negative effects on economic growth
Moreover on the side of against the corruption, there are the ideas that corruption reduces the investment With corruption, the cost of project can become higher So this can drop out the good projects and reduce the investment Reduced investment will affect negatively to economic growth
So until now we really look corruption like the impediment to the economic growth
The report from World Bank in 1998 has seen corruption like the great obstacle to economic and social development However we does not still have enough the exactly theoretical framework to definitely confirm the impacts of corruption on economic growth We have the empirical researches to find out the effects of corruption in the specific cases with different methodologies Mauro (1995) showed that corruption reduced investment However investment is a main source of economic growth So corruption lowered economic growth through reducing investment As in Mauro
(1995) corruption and growth (also investment) had negative relationship and significant in aspect of statistic and “in an economic sense” Tanzi and Davoodi (1997) conducted the research about “corruption, public investment and growth” With cross- section data of countries and regression method they found that more corruption made more public investment and lower government revenues Also higher corruption made
“lower operation and maintenance expenditures” and “lower quality of public infrastructure” Also in this paper the authors showed that corruption lowered productivity of public investment (however increased public investment) So that led to negative impact of public investment on economic growth Finally corruption had negative impact on economic growth Kaufmann and Wei (1999) had a research on
“grease money” With data at firm level from worldwide, the authors found conclusion against “efficient grease” hypothesis They found that paying more bribes does not lead to reduce “management time wasted with bureaucrats” and cost of capital However paying more bribes would create more “management time wasted with bureaucrats” and more cost of capital This would affect investment projects and economic growth in general
Beside the direct impact of corruption on economic growth, recent researches have shown out the indirect impacts of corruption on growth In summary, we can list out five popular channels such as human capital, capital investment, government size, trade openness, and political instability through which corruption affect economic growth
About human capital channel, Murphy, Shleifer, and Vishny (1991) found that corruption affected how people invest in human capital If rent seeking rewards more than producing operation, people will devote most ability to become rent seeker and choose occupation that bring them more rent seeking, not for production Investment in human capital in this case will be reduced; production of nation will be lowered
Finally it will reduce growth
About capital investment, Mauro (1995) showed the negative relationship between corruption and private investment Corruption adds more cost for investment So it reduces private investment However investment is the main source of growth Lower investment will lower economic growth Mo (2000) also found corruption had negative impact on private investment channel And through impact on this channel it reduced economic growth
Tanzi and Davoodi (1997) examined the impact of corruption on public investment
Public expenditure had tendency to become bigger under corruption Corruption made public investment increase but its productivity decrease On net effect, it reduced economic growth However according to Hodge, Shankar, Rao, and Duhs (2009) corruption reduced government spending On total effect, corruption fosters growth through this channel by lowering government spending So we have mixed impact of corruption on government size Corruption can decrease or increase government spending
About trade openness, one of the ways that the corruption affects trade is quota of exporting and importing By that way corruption can restrict trade openness Pellegrini and Gerlagh (2004) found negative relationship between corruption and trade openness And final impact of corruption on growth through this channel was negative
Finally corruption affects growth through political instability channel Corruption can create the ideas about inequality and impropriety among citizens This is the root of political instability And political instability makes bad environment for investment and economy It will impede economic growth Mo (2000) examined the indirect impact of corruption on growth through political instability He found that corruption had positive relationship with political instability More corruption will be more instability And this will lead to lower growth Pellegrini and Gerlagh (2004) also came to the same result as Mo (2000) about the impact of corruption on political instability and economic growth
Looking closer on impact of corruption in developing countries, till now we have very few researches about it Almost researches here have used data of cross countries all over the world to find out the impact of corruption on economic growth (indirect and direct impact) According to these researches, corruption has mostly had negative relationship with growth That means the countries with higher corruption will suffer lower growth However this is still right if we look into group of developing countries?
Corruption makes more cost for the economy and impedes economic growth If this is still right for developing countries, corruption will become the great obstacle for development in developing countries However we may have the argument when we look separately in some developing countries For example, Indonesia and Thailand have had fast pace of growth in spite of high corruption in these countries South East Asia has also experienced fast growth although corruption in most countries of this area is very popular So in this case corruption has promoted economic growth This is the reason why this paper would like to focus on developing countries We would like to examine more detail about the impact of corruption on this group of countries
Obviously, corruption has the impact on economic growth In scope of this research we would like to examine the effects of corruption on economic growth in developing countries and to find out that corruption has negative or positive effect on economic growth
LITERATURE REVIEWS
people’s trust in the political system It makes instability in society And with the existence of corruption, projects damaging environment can be licensed This will lead to destroy living environment and natural resources
In this paper we consider the impact of corruption on economic growth by direct and indirect way So corruption is also called the factor of growth Basically on the neoclassical growth theory, following the growth model of Solow, growth is a function of capital and labor Capital formation and labor force are the main factors of economic growth Moreover on researches about the determinants of growth, other factors have been found out Human capital is also the important factor of growth Mankiw, Romer, and Weil (1992), by cross-country data, found out human capital was the significant factor of economic growth beside labor and physical capital And Baro (1996) also showed that initial level of GDP, human capital, government consumption, term of trade, investment ratio were among the factors affecting growth Moreover Alesina, Ozler, Roubini, and Swagel (1992) found that political instability had negative effect on economic growth Generally economic growth is a complicated function of many independent variables In this paper we add one more determinant of growth This is corruption However beside the direct impact of corruption on growth, we also examine the indirect impact of corruption Corruption makes links with growth by just source factors of economic growth such as human capital, capital investment, government size, trade openness, and political instability Indirectly corruption affects growth through these channels In the following part we are going to represent some researches about how corruption affects growth and its transmission channels
Like in Introduction part, we have stated that corruption can be good or bad for economic growth So we will break down this section into two parts The first part is to review some papers that support for the positive effect of corruption on growth And the second part is of negative effect of corruption
2.2.1- Corruption greases the wheels of growth
As in Meon and Weill (2008), the authors tested whether corruption is “grease” or
“sand” of economic growth They examined the relationship among corruption, aggregate efficiency, and the dimensions of governance across 54 countries (including developed and developing countries) in period 1994-1997 With OLS method, the result showed that in the countries with effective institution, corruption would have negative effect; however in case of ineffective institution, corruption would have positive effect So, this paper came to conclusion of supporting for “grease the wheels” hypothesis According to this paper, with inefficient institutional countries, let corruption being free would bring back benefit However the authors also warned that
“country that would allow unfettered corruption may eventually find itself with an even worse global institutional framework, and thus be caught in a bad governance/low efficiency trap”
Or in Kaouthar Gazdar (2012), the author also would like to test the hypothesis “grease the wheels” of corruption This paper examined the relationship among the corruption, growth, and the quality of governance 19 MENA countries in period of 1984-2010 were used in this paper as the data for analyzing With the method of GMM, the author found that in case of weak institutional framework, the corruption is less detrimental for economic growth The corruption is positive effect on economic growth in case of low governance The hypothesis was again supported by this paper
2.2.2- Corruption is sand of the wheels of growth
Firstly Pak Hung Mo (2000) did a research about the relationship between corruption and economic growth He used data of 52 countries in period 1960-1985 He found that
“1% increase in the corruption level reduces the growth rate by about 0.72% or, expressed differently, a one-unit increase in the corruption index reduces the growth rate by 0.545 percentage points” And political instability is one of the top important channels beside human capital, and investment channels Political instability took 53% of total effect on economic growth
With the research “Does corruption grease or sand the wheels of growth?”, Pierre and Khalid (2003) assessed the corruption’s effect on growth and investment Panel data from 71 countries in period time 1970-1998 was used in this research The corruption would have more and more negative impact on investment in case of inefficient government and political instability Same as investment, corruption also affected negatively on economic growth This result supported for the hypothesis of “corruption sands the wheels of growth”
Beside the impact of corruption on growth, Lorenzo Pellegrini and Reyer Gerlagh
(2004) also did the research about the transmission channels of corruption They examined four channels such as schooling, political instability, openness of trading, and investment Corruption had all negative effects on schooling, trade openness, and investment However corruption and political instability had positive relationship The final result confirmed that corruption had negative impact on economic growth
Moreover Mina Baliamoune-Lutz and Léonce Ndikumana (2008) also examined the impact of corruption on investment in African countries Firstly they analyzed the effect of investment on economic growth After that they would research the impact of corruption on investment By that way they could have a better view about the effect of corruption on growth through investment The paper used the GMM method to examine 33 African countries from 1982 to 2001 The result once again concluded that investment had significant effect on economic growth More important thing was that corruption also had negative impact on domestic investment However corruption had different effects on private investment and public investment In aspect of private investment, corruption had negative effect on it But in view of public investment, corruption had positive relationship with it
And Aliyu and Elijah (2008) also did the research in Nigeria about the relationship between corruption and economic growth The authors used ECM method along with time series data in period 1986-2007 to conduct research The study showed that corruption had negative impact on economic growth Moreover it also explored that corruption had negative relationship with human capital development However corruption went the same way with government capital expenditure
Sriram Shankar (2009) conducted the paper to “model the transmission channels through which corruption indirectly affects growth” Five main transmission channels he used in this research were investment, human capital, government size, openness, and political instability Data of 81 countries from 1984 to 2005 was chosen to examine in this paper Using system of equations methods he found that corruption had negative effects on investment, human capital, and political instability Through these channels corruption hindered economic growth However “corruption is found to foster growth by reducing government consumption and, less robustly, increasing trade openness” In total, corruption had negative effect on economic growth
And Ugur and Dasgupta (2011) have conducted the research about the impact of corruption on economic growth in low income countries The author has used meta- analysis method to analyze the findings of 72 empirical researches The authors also have examined the transmission channels of corruption to economic growth The result of this research showed that corruption put the significant effect on economic growth
And another important thing was that corruption had negative impact on growth This result also extended to non-low income countries The corruption also had negative and significant effect on growth in non-low income countries Without transmission channels, the paper found out that the direct effect of corruption on non-low income countries was higher than low income countries So the authors concluded that
“corruption should be considered as an international problem with negative economic consequences rather than as a problem specific to LICs only”
All the above studies can be summarized like the following:
Pierre Guillaume Meon and Laurent Weill
1997 corruption has positive effect on growth in case of inefficient institutional framework
This paper supports for "grease the wheels" of growth of corruption
Corruption had negative effect on growth political instability is one of the top important channels beside human capital, and investment channels
OLS Panel data from 71 countries in period
The corruption would have more and more negative impact on investment in case of inefficient government and time 1970-1998 political instability corruption also affected negatively on economic growth
Lorenzo Pellegrini and Reyer Gerlagh
OLS, 2SLS Cross countries Corruption had all negative effects on schooling, trade openness, and investment But corruption and political instability had positive relationship The final result confirmed that corruption had negative impact on economic growth
Mina Baliamoune-Lutz and Léonce Ndikumana
1982 to 2001 corruption also had negative impact on domestic investment and growth
ECM Time series data in period 1986-2007 in Nigeria
Corruption had negative relationship with human capital development However corruption went the same way with government capital expenditure and growth
Corruption had negative effects on investment, human capital, and political instability "corruption is found to foster growth by reducing government consumption and, less robustly, increasing trade openness"
Corruption had negative and significant impact on growth And without transmission channels, the paper found out that the direct effect of corruption on non-low income countries was higher than low income countries
Table 2.1: Summary of literature reviews
CONCEPTUAL FRAMEWORK
In this section we would like to find out how corruption affects economic growth by the transmission channels So first in this section we will list out and describe these channels
According to Sriram Shankar and co-authors (2009), corruption will affect growth by five transmission channels such as government size, capital investment, openness, human capital, and political instability
As in Sriram Shankar and co-authors (2009), there are two different ideas about the impact of corruption on government size On one way, corruption makes government size increase On the other way, corruption reduces government size
To some officials, they can corruption by the way of extending the government expenditure By that way they have more opportunities to make the corruption They also allocate the budget inefficiently because of their corruption For these officials expending more and more governmental budget is an opportunity to take more corruption
However for some other officials, narrowing public expenditure is the way to take more corruption They report lower budget that is available for consumption in order to using more part of this budget or take corruption under various forms Under this way, limiting government size creates opportunities for take corruption
So here it is up to every specific case to have a negative or positive effect of corruption on government expenditure This effect will result from empirical examination
There are some ideas to explain the impact of corruption on investment As in Sriram Shankar and co-authors (2009), Lorenzo Pellegrini and Reyer Gerlagh (2004), and Pak Hung Mo (2000) corruption adds more cost to projects when the corruption exists
Corruption can make feasible projects become infeasible projects And when corruption exists, enterprises can be uncertainty about the return on investment activities Enterprises must pay bribes in corrupting officials to go ahead the business operation So corruption is another cost of business operation of enterprises As a result corruption will make less incentive to proceeds to investment activity As in growth theory, investment is a very important factor of economic growth Less investment may lead to less growth
However according to idea of “grease the wheels” of corruption, it may go positively with investment In case of complicated administration existing in some countries, without corruption, administrative procedure of business operation can be more time, more money, and more labor So in this case corruption can make support for business and investment operation
However in reality, until now more practical studies found that corruption has negative impact on capital investment More corruption will lead to less investment So we can expect that in this paper we also come to the result that corruption also has negative impact on capital investment However we aware that corruption can still have positive impact on capital investment in the hypothesis of “grease the wheels”
Lorenzo Pellegrini and Reyer Gerlagh (2004) showed that corruption have a negative effect on trade openness The corruption activities happen on the process of quota of export and import With the incentive to free trade, rent-seeking activities through quota will stop down So the intervention into the trade to have more opportunities to corrupt will remain This will limit the openness of trading According to this, corruption is expected to have negative relationship with openness of trade
In some recent empirical research such as Pak Hung Mo (2000) and Sriram Shankar
(2009), corruption showed a negative effect on human capital This impact can be explained by some ideas Firstly, corruption is the cause for reducing government revenue Because of corruption, tax evasion activity and wrong tax exemption cases can happen This will lead to reduce government tax revenue Education and health are usually in the categories of budget spending of government So when government revenue is reduced, the government expenditure to develop human capital will be reduced too As a result corruption has made negative impact on human capital
Another idea to examine the effect of corruption on human capital is in budget of enterprises to develop human capital Existing of corruption can acts as another cost for enterprises When the cost increases, the budget for investment may be reduced It also means that budget for developing human capital may be reduced as well So through some these ideas about the relationship between corruption and human capital, this give us the thinking about negative impact of corruption on human capital investment
Moreover on the paper of Murphy, Shleifer, and Vishny (1991) about “The allocation of talent: Implications for growth” showed that people choose occupation due to the return of that occupation When people see that rent seeking rewarding more, they will become rent seeker However rent seeker does not support growth They just
“redistribute wealth and reduce growth” This behavior affects the different types of investment in human capital People can devote all in how to have power and become a rent seeker Or they can devote to the occupation such as engineering, science, manufacturing to promote productivity and support for growth In the paper of
Murphy, the authors used two proxy variables to represent for two cases of occupational choices They used the variable college enrollment in law to stand out for the talent towards rent seeking And enrollment in engineering to represent for talent allocated to productivity And the result showed that the country with more engineering grow faster Through that we can think about whether corruption can affect investment in types of human capital So beside the effect of reducing the investment in human capital, corruption can affect types of investment in human capital
In this paper we intend to examine the effect of corruption on types of human capital
More detail we will see how corruption affects engineering type of human capital
Because of having more benefit from corruption, people have tendency to become rent seeker This choice will make people go away from devoting to the occupation such as engineering, science, manufacturing Because of that, we expect corruption will have negative effect on human capital (in aspect of investment in engineering area of human capital)
METHODOLOGY AND DATA SOURCE
However if we just notice about the impacts of corruption and transmission channels in this model, we can accept the shortcoming of a perfect growth model like this
Model (4.1) will be examined by OLS method to see how the relationship among corruption, transmission channels and growth And from this we can estimate direct effect of corruption on growth by using coefficient a2
4.2- INDIRECT EFFECTS OF CORRUPTION ON GROWTH THROUGH TRANSMISSION CHANNELS
Second, we will examine the effect of corruption on each channel Like in Lorenzo Pellegrini and Reyer Gerlagh (2004) we have:
Where T is the vector of transmission channel variables such as gFC, gGX, gTT, PI, EEPC And b 0 , b 1 , b 2 are five-dimensional coefficients vector, CI is corruption perception index, LY0 is the log of GDP per capital in the base year 1990
Through model (4.2) we can see the effect of corruption on each channel And by the model (4.1) we can estimate the indirect effect of corruption on growth by each channel The indirect effect of corruption on growth through each channel will be achieved by b 2 x a (a 3 to a 7 ) For example the indirect effect of corruption on growth through capital investment channel will be the product of corresponding coefficient b2 and a 3
Because the capability of having endogenous problem transmission channels in model (4.2), so 2SLS method with instrument variable LO (legal origin) also intends to use to solve this problem
According to Conceptual Framework part, we expect that corruption will have negative relationship with human capital in type of engineering, investment, and openness And corruption will have positive relationship with government size, and political instability Finally, total effect of corruption on economic growth will be negative
4.3- TOTAL EFFECT OF CORRUPTION ON GROWTH
With 4.1 we have direct effect of corruption on growth And with 4.2 the indirect effects of corruption on growth through each channel has been achieved Total indirect effect of corruption on growth will be the sum of all indirect effects of corruption on growth through each transmission channel And finally total effect of corruption on growth will be the sum of direct effect and total indirect effect of corruption on growth
This paper intends to use cross section data in developing countries in 2008 However for enough data of each variable, we just have around 35 observations cross developing countries in 2008 to do the research
The economic crisis has happened from the end of 2008 up to now If we choose time point at 2009, 2010 or 2011 to collect data, the abnormal changes rooted in crisis can effect negatively to our estimation So the reason of choosing year 2008 is to avoid the turbulence of economic crisis in the recent years
Most of data are taken from World Bank except Corruption Perceptions Index (CI) is taken from Transparency International CI ranges from 1 to 10 The country with higher score will be cleaner from corruption
Moreover, We will express the definition of some main independent variables like following:
- Fixed capital formation growth rate (gFC): According to definition from World Bank,
“Gross fixed capital formation (formerly gross domestic fixed investment) includes land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, offices, hospitals, private residential dwellings, and commercial and industrial buildings According to the 1993 SNA, net acquisitions of valuables are also considered capital formation” And the growth rate of fixed capital formation is the increasement in percentage compared with the previous year
- Government expenditure growth rate (gGX): This is the increasement in percentage year to year of general government final consumption expenditure According to World Bank, it is defined as “all government current expenditures for purchases of goods and services (including compensation of employees) It also includes most expenditures on national defense and security, but excludes government military expenditures that are part of government capital formation”
- Political stability index (PI): This index is taken from the project “Worldwide Governance Indicators” from World Bank This index “reflects perceptions of the likelihood that the government will be destabilized or overthrown by unconstitutional or violent means, including politically-motivated violence and terrorism” It ranges from -2.5 to 2.5 Higher score reflects stronger in political stability
- Enrolment in engineering per capita: This data is taken from database from World Bank It represents the human capital in engineering area
- Total trade growth rate (gTT): it is the increasement in percentage of total trade year to year And the total trade is the sum of total export of goods and services and total import of goods and services This variable represents the openness of economy
In this section we will consider the relationship between each pair of variables under descriptive statistic situation such as between corruption and every transmission channel and between every transmission channel and growth
5.1- RELATIONSHIP BETWEEN TRANSMISSION CHANNELS AND GROWTH
Firstly we are going to consider the relationship between every main transmission channel and growth As be stated in previous section there are five transmission channel examined in this paper such as investment, government size, openness, political instability, human capital Here we use growth rate of gross fix capital formation (gFC) to represent for investment variable, growth rate of general government final consumption expenditure (gGX) to stand for government size, growth rate of total trade (gTT) for openness variable, percent of number of enrolment in engineering over total population (EEPC) for human capital variable, and political instability index (PI) for political instability And growth rate of GDP (g) is chosen to stand for economic growth All these data are collected in 2008
In descriptive statistic approach we are going to use graph and correlation coefficient to show the relationship between every pair of variables, beginning with the relationship between economic growth and investment.
RESEARCH FINDINGS IN DESCRIPTIVE STATISTIC
RELATIONSHIP BETWEEN CORRUPTION AND TRANSMISSION
Until now we have represented how the five transmission channels affect economic growth Now we move to next part representing how corruption affects these channels
Then we will link two parts together and see how corruption affects growth through these channels
Firstly we are going to make a graph to consider how corruption affects government size channel
Figure 5.6: Scatter graph between CI and gGX
According to this graph, corruption has negative effect on government size (here is represented by growth rate of general government final consumption expenditure That means when a country is less corrupted, government expenditure will be less Or we can say more corruption will make more government expenditure Also with this graph, although through the trend line we can say corruption affects negatively on government expenditure, however this effect is small (downward slopping of this trend line is so small) The correlation coefficient in this case is -0.114 This shows the weak linear relationship between them The minus sign in this correlation presents negative relationship
So until now corruption has negative effect on government size Because corruption is presented by corruption index with higher corruption index presenting less corruption, negative effect in this case means that the government expenditure will be more in the more corrupted country However with the above consideration between government size and growth we say that more government expenditure will create more growth So with the link between corruption, government size and growth, the corruption will support growth through government size channel
Now the relationship between corruption and capital investment will be examined
Figure 5.7: Scatter graph between CI and gFC
Following this graph, there is not much explanation between corruption and capital investment (presented by growth rate of gross fix capital formation) The points scatter randomly There is not clear trend between corruption and capital investment The correlation is 0.021, a very small number This also indirectly presents very weak linear relationship in this case With the above consideration between capital investment and growth, they have a good positive relationship However in the case of corruption and capital investment we cannot draw conclusion from them So we also cannot draw conclusion between corruption and growth through capital investment channel under approach of descriptive statistics
The relationship among corruption-capital investment-growth will be examined again under approach of inferential statistics in next part
Now we move to relationship between corruption and openness under the following graph
Figure 5.8: Scatter graph between CI and gTT
According to this graph, there is a clear downward slopping trend line However on the graph, there are two special outliner points that can make negative influence on our examining So we are going to drop out these two points The graph now is following:
Figure 5.9: Scatter graph between CI and gTT (dropping out two outliner points)
Now the trend line is more fitments The downward slopping shows that less corruption will make less openness Another speaking is more corruption will create more openness The correlation is -0.594 This shows negative and a strong linear relationship between them So there is the clear effect of corruption on openness in this case
Also with the above examining, openness has a positive effect on growth More openness will create more growth So through the link among corruption, openness, and growth the inference is that more corruption will make more growth through openness channel
The scatter graph between corruption and political instability is following:
Figure 5.10: Scatter graph between CI and PI
Again an upward slopping of trend line is clear The corruption index has positive relationship with political instability index The country with less corruption will be the more stable political country As in the conceptual framework we say that “corruption makes political discontent among citizens and bureaucratic officials and even among bureaucratic officials This is the root of political instability.” The graph between corruption index and political index prove that More corruption will make political
CI instability increase The correlation in this case is 0.504 This shows positive and strong linear relationship between corruption index and political instability index
However through the scatter graph between political instability and growth, there is not clear conclusion made between them There is not clear effect of political instability on growth through this way So we cannot draw a conclusion through the link among corruption, political instability, and growth under this approach There is just the same direction effect of corruption on political instability Under approach of inferential statistics this issue will be examined again
And the last channel is human capital Here in this paper, human capital is presented by percent of number of enrolment in engineering over total population This is a kind of human capital
Figure 5.11: Scatter graph between CI and EEPC
According to this graph, there is not a clear relationship between corruption and this kind of human capital We cannot specific how corruption affects human capital The correlation 0.037 also cannot show the relationship between them As the same as the
CI case human capital and growth that we have just considered above, scatter graph also cannot explain about the relationship between them So in the case of human capital channel, under approach of descriptive statistics like this, there is no conclusion about how corruption, human capital, and growth are related together This relationship is also examined again under context of inferential statistics in next part of the paper
So until now when all transmission channels of corruption on growth has been considered under context of descriptive statistics (scatter graph and correlation), there are only two conclusion that are available The first that is more corruption will support indirectly growth through transmission channel of government expenditure And the second that is more corruption will create more growth through openness channel
Although corruption and political instability also have the clear relationship, however political instability does not affect growth clearly So we cannot conclude about the relationship among corruption, political instability, and growth by this way
All the relationship that examined in this chapter will be analyzed in next chapter under another approach However in this chapter there are at least two evident to say that corruption is good for growth through transmission channels such as government expenditure and the openness Before come to next chapter, we will present the last graph in this chapter to see how corruption related directly to growth
Figure 5.12: Scatter graph between CI and g
Following this graph, there is a clear downward slopping trend line So corruption has negative relationship with growth That mean more corruption will make more growth
The country (in group of developing countries) will be less growth if it is less corruption The correlation between CI and g is -0.385
In this chapter we are going to use regression approach to examine effects of corruption on growth through transmission channels The analysis is going to be divided into two parts The first part is to examine the direct effect of corruption on growth and the effects of transmission channels on growth The second part is to consider the effects of corruption on transmission channels Combining the effects of corruption on these transmission channels and the effects of transmission channels on growth we will receive the total indirect effect of corruption on growth And finally from the total indirect effect of corruption on growth and the direct effect of corruption on growth we will have total effect of corruption on growth
6.1- DIRECT EFFECT OF CORRUPTION ON GROWTH AND EFFECTS OF TRANSMISSION CHANNELS ON GROWTH
Using approach in Methodology chapter, OLS method is going to used in this case
And the result of this regression is in below table 6.1:
REGRESSION ANALYSIS
Table 6.1: OLS of transmission channels and corruption on growth
Note: Symbols *, **, *** stand for significant level of 10%, 5%, 1% Standard errors are in parenthesis under coefficients
The test for heteroskedasticity has been applied by the method of Breusch- Pagan/Cook-Weisberg With confident level of 80%, the regression has passed this test We do not worry about heteroskedasticity in this regression
The above table shows the result of regression OLS of all transmission channels and corruption on growth This represents effects of transmission channels such as capital investment, government size, openness, human capital, and political instability on growth It also includes corruption variable in this regression The effect of corruption on growth is divided into two parts such as direct and indirect effect The appearance of corruption variable in this regression is in order to show direct effect of corruption on growth And the indirect effect of corruption on growth is through transmission channels Corruption affects transmission channel and then transmission channels affect growth The first OLS regression shows how corruption affects directly on growth and presents effects of transmission channels on growth
It also includes initial income Y0 in this regression LY0 is the logarithm of GDP per capita in 1990 The minus sign of the coefficient of LY0 shows negative relationship between initial income and growth That means the countries with higher initial income level will have smaller economic growth and vice versa This is suitable with the consequence from growth theory of Solo The countries with the same technology and rate of investment will have higher growth rate if their income is lower
The coefficient of capital investment which presented by growth rate of gross fix capital formation (gFC) is positive and statistically significant at 1% The effect of capital investment is positive on growth With rate of capital investment increases 1%, the growth increases by approximately 0.14% This is also suitable with growth model of Solo Investment is the key of economic growth If you want to increase growth, you must boost investment This result is the same as in the case of consideration of capital investment and growth by descriptive statistics in previous part
The same as capital investment, the coefficient of government size which is presented by growth rate of general government final consumption expenditure (gGX) is also positive However the coefficient is just statistically significant at 5% The government size has the same directional relationship with growth With 1% increasing of government expenditure, the economic growth increases approximately 0.14% As in Marta Pascual and Santiago Álvarez-García (2006), they had a research on effect of government spending on economic growth in European countries The result was also that government spending had positive relationship with growth Or in Herrera (2007), the research found that “By increasing the efficiency of public spending, the government can permanently increase the rate of productivity growth and, hence, affect the growth rate of GDP” Here in the context of this paper, in developing countries, the government expenditure also has positive effect on growth This is also suitable with the result of examining the relationship between government size and growth under approach of descriptive statistics in previous chapter
The coefficient of openness which is presented by growth rate of total trade (gTT) has also positive sign This coefficient is statistically significant at level of 5% When the openness increases up 1%, the growth is going to increase approximately at 0.11% In previous part, the scatter graph and correlation has showed that the openness has positive relationship with economic growth This result is the same as the one we have here by the way of regression Or as in Gundlach (1996), he also found that the opened developing countries grew faster than the closed developing countries There are many researches and discussions about the openness and economic growth However here in this paper we just want to see the empirical result of relationship between the openness and growth and through that we establish the link from corruption to economic growth
The other transmission channel is human capital that is represented by percent of number of enrolment in engineering over total population (EEPC) relates positively with growth We choose percent of number of enrolment in engineering over total population to present for human capital because we would like to examine the type of investment in human capital However the coefficient here is not statistically significant even at 10% So up to the level of significant of 10%, we cannot conclude that human capital has important role on growth Anyway this result shows us that human capital, especially investment type in engineering of human capital, has positive relationship with economic growth If we would like to increase growth 0.658 %, we approximately increase percent of number of enrolment in engineering over total population up to 0.01%
The last transmission channel is included in this regression is political instability As the same as the case of human capital, political instability is not statistically significant even at 10% However the result still shows that the political instability has positive relationship with economic growth That means if the country has stable politics that will be the good background to improve economic According to this result, if political instability index is up to 1 unit, growth will increase 0.33 % This result is also same as the result of Muscatelli, Darby, and Li (2000) The finding of this research is that the political instability would make economic growth low The political instability can destroy environment of investment, and lower economic growth
We did include corruption in this regression along with transmission channels so that we can examine the direct effect of corruption on growth The corruption index is chosen to represent for corruption Higher corruption index shows the country is less corruption and vice versa So in the result this corruption index has negative relationship with economic growth That means the corruption will make the countries grow faster The countries with less corruption will grow slower In this case when corruption index increases 1 unit, economic growth will decrease 0.71 % Moreover the coefficient here is statistically significant at 10% So with level of significant at 10%, the corruption has an important role on growth This is just the direct effect of total effect (direct and indirect effects) of corruption on growth So after we examine the indirect effects of corruption through transmission channel to economic growth, we will have total view of corruption on growth However until now, with the direct impact of corruption on growth, this result is not like the expected direction of relationship between corruption and growth We have expected that more corruption will make economic growth lower However in the Introduction part, we have stated that corruption may have positive and negative effect on growth This result leads to positive effect of corruption on growth More corruption will make more growth
6.2- EFFECTS OF CORRUPTION ON TRANSMISSION CHANNELS AND GROWTH
In this part we are going to examine the effects of corruption on growth As introduced in Methodology and Data section, the method used here is 2SLS The importance is the effect of corruption on transmission channel So the coefficient of corruption index variable in regression is important In regression, there are two independent variables such as corruption index variable and log of initial GDP at base year of 1990 So in this case we worry the endogenous problem happening with corruption index variable To deal with problem we are going approach 2SLS Beside that there is going to have a check of endogeneity at every case of examining And the instrument variable being used here is legal origin (LO)
6.2.1- Effect of corruption on government expenditure
Table 6.2: 2SLS of gGX-CI
Note: Standard errors are in parenthesis under coefficients
In test of endogeneity, we conclude that endogenous phenomenon is significant at level of 15% (refer table A1 in Appendix) So in the case of examining effect of corruption on government expenditure, the method of 2SLS is suitable
This is the result of 2SLS method for relationship of corruption and government size
According this result table, there is a negative relationship between corruption index and government expenditure More detail when corruption index increases up 1%, government expenditure will decrease approximately -3.48% Or we can say when the countries become cleaner from corruption the government will spend less So government spending is the opportunity to corrupt and take private benefit
In Conceptual Framework we have showed two situations that corruption relates with government expenditure Corruption makes government expenditure bigger and corruption narrows government expenditure Here the result shows that in research scope of this paper, corruption makes government expenditure become bigger
However in this result the coefficient is not significant at 1%, 5%, and 10% It is a quite weak significant level (20%)
Now we can infer the result of the channel of corruption, government size, and growth
More corruption increases government expenditure And more government expenditure will increase growth So the link between them shows that more corruption will support for growth And this result is the same as the result from descriptive statistics
In descriptive statistics section, corruption also has same direction relationship with growth So through regression analysis and descriptive statistics analysis, the result is the same
6.2.2- Effect of corruption on capital investment
Table 6.3: 2SLS of gFC-CI
Note: Standard errors are in parenthesis under coefficients
This is the result of 2SLS, the coefficient is positive So according to this, the corruption has negative effect on capital investment However in this result we see the coefficient is not significant
CONCLUSION REMARKS
human capital (EEPC) does not show that it is an important transmission channel
‐ And with the last channel, corruption relates negatively with political instability However in this case the effect of corruption on political instability is not significant and small So in the context of this paper, the political instability transmission channel is not meaningfull
Summarizing all effects of corruption on economic growth through these channels, total effect of corruption on economic growth is positive Corruption has same direction relationship with economic growth
Beside the achievements, this paper also has considerable drawback And this drawback is in methodology part According to the approach in methodology section, we use model (4.1) to estimate the direct effect of corruption on growth and the effects of five transmission channels on growth And the model (4.2) is used to find out the effect of corruption on every transmission channel So through model (4.1) and (4.2) we have a link to among corruption – transmission channel – economic growth This is how we estimation indirect effect of corruption on gowth through every transmission channel However also through this link, the drawback exists The model (4.2) expresses the relationship between corruption and transmission channels So this represents the correlation between corruption and every transmission channel And in model (4.1) corruption and transmission channels are all explanatory variables It is highly possible there is the phenomenon of multicollinearity exsiting in equation (4.1)
And this phenomenon is going to affect estimation in (4.1)
On the view of statistics, multicollinearity may not affect the coefficients of estimation
However it will affect the assessment of statistic significance of the coefficients because muticollinearity affects standart error estimation When multicollinearity exists, the OLS variances are often larger Larger variances also mean lager standard errors As a result, the t-stats values are going to become smaller in case of larger standard errors This will lead to wrong conclusion on statistic significant of coefficients For example in this paper, the coefficient of EEPC in regression of (4.1) is not significant at all This may be the result of multicollinearity phenomenon With insignificant coefficient of EEPC we cannot conclude the indirect effect of corruption on growth through this channel
So the existing of multicollinearity phenomenon in the model (4.1) is the biggest drawback of this paper This drawback can be seen as an avoidace for further researches on this subject And another approach such as system of equations can be used to solve this issue in future
Although corruption has positive relationship with economic growth, this should not be considered as a guideline for policy issues This should be considered like a characteristic, a feature of developing countries This can be seen as a property of development phase from developing countries to developed countries The developing countries should be careful in process of developing economic and fighting against corruption because in this phase it is possible that corruption goes in same direction with economic growth There should be more researches on the detailed relationship between corruption and economic growth in order to make sure that developing countries with fighting corruption are perfect and suitable If not fighting corruption can make intervention in developing economic
Or if it is considered like a guideline, it should be used under any certain conditions
What are these certain conditions? This will be the subject for studies beyond The conclusion of this paper supports for the hypothesis “grease the wheel” of corruption
The result of Meon and Weill (2008) was another evidence of “grease the wheel” hypothesis That paper concluded that “A possible policy implication of these results is that countries plagued with extremely inefficient institutional frameworks may benefit from allowing corruption to flourish This interpretation, however, is risky A country that would allow unfettered corruption may eventually find itself with an even worse global institutional framework, and thus be caught in a bad governance/low efficiency trap.” In that paper, corruption only supports for growth only in the condition of inefficient institutional frameworks Or in Kaouthar Gazdar (2012) showed that “corruption is positively associated with economic growth when the quality of governance is very low” Again in this paper low quality of governance is a condition on which corruption relates positively with growth
The result in this paper is also an evidence of “grease the wheel” hypothesis in developing countries We should not use this result as a guideline and through that let corruption free in society because corruption is positively associated with growth
Corruption can make many effects on economy and on society that we cannot predict its consequences Corruption can be positive relationship with growth only in some certain conditions Developing economic without corruption can be an ideal object we would like to have However the result in this paper is like a careful remind on the policy of fighting against corruption because in developing countries a characteristic of corruption is positively related with economic growth If we do not care about the conditions existing parallel with corruption, fighting corruption can make difficulty for growth For example, in Meon and Weill (2008), fighting corruption should go with improve the quality of governance, government efficiency And there are some ways to improve the quality of governance such as modernizing institutions, strengthening the administration and enhancing human right, security and justice…
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Table A1: 2SLS regression of CI and gGX and endogenous check
Instrumental variables (2SLS) regression Number of obs 33
Wald chi2(2) 2.55 Prob > chi2 0.2792 R‐squared = Root MSE 8.1386 gGX Coef Std Err z P>z [95% Conf Interval]
Tests of endogeneity Ho: variables are exogenous
Durbin (score) chi2(1) = 2.36199 (p = 0.1243) Wu‐Hausman F(1,29) = 2.23571 (p = 0.1457)
Instrumental variables (2SLS) regression Number of obs 33
Wald chi2(2) 1.34 Prob > chi2 0.5112 R‐squared 0.0449 Root MSE 11.527 gFC Coef Std Err z P>z [95% Conf Interval]
Table A2: 2SLS regression of CI and gFC and endogenous check
Table A3: 2SLS regression of CI and gTT and endogenous check
Tests of endogeneity Ho: variables are exogenous
Durbin (score) chi2(1) = 0.005418 (p 0.9413) Wu‐Hausman F(1,29) = 0.004762 (p 0.9455)
Instrumental variables (2SLS) regression Number of obs 34
Wald chi2(2) 3.87 Prob > chi2 0.1444 R‐squared =
Root MSE 11.808 gTT Coef Std Err z P>z [95% Conf Interval]
Tests of endogeneityHo: variables are exogenousDurbin (score) chi2(1) = 3.41073 (p = 0.0648)Wu‐Hausman F(1,30) = 3.34503 (p = 0.0774)
Table A4: 2SLS regression of CI and EEPC and endogenous check
Table A5: 2SLS regression of CI and PI and endogenous check
Instrumental variables (2SLS) regression Number of obs 34
EEPC Coef Std Err z P>z [95% Conf Interval]
Tests of endogeneity Ho: variables are exogenous
Durbin (score) chi2(1) = 2.90679 (p = 0.0882) Wu‐Hausman F(1,30) = 2.80459 (p = 0.1044)
Instrumental variables (2SLS) regression Number of obs 34
PI Coef Std Err z P>z [95% Conf Interval]
Tests of endogeneityHo: variables are exogenousDurbin (score) chi2(1) = 3.08086 (p =0.0792)Wu‐Hausman F(1,30) = 2.98928 (p = 0.0941)