Corruption and Bribery on Transition Economies : Case Study for SEE Countries

In this research paper is analyzed corruption and bribery on transition economies with case study of SEE countries and the main theoretical arguments for discussions are as following: the effect of corruption in economic growth, mobilization of different countries or institutions against corruption (prevent corruption through institutional policies and anti corruption programs), the level of corruption in SEE countries, effect of corruption in public sector and in economic efficiency. In methodology, the secondary data that used are collected from international institutions and they are calculated through STATA program. The main analyses are descriptive statistic, OLS method of regression and correlation matrix. The variables that are used in research paper are: corruption and bribery & bureaucracy costs (as dependent variable), then economic growth, political stability, economic freedom, transition reforms and education index (as independent variables). Based on empirical results, in the OLS analysis is found that corruption has positive impact on economic growth but bribery and has negative impact on economic growth of SEE countries then in T-statistic analysis all independent variables have shown negative significance (T<2) on corruption and bribery. In correlation methods, economic growth has higher negative correlation with bribery than with corruption. In conclusion, all of SEE countries must attempt to fight against corruption and it is very serious problem for economic sustainable, political stability and institutional consolidation, process of integration and in other important challenges. In fact, corruption index in 2014 shown that the most of SEE countries are ranking under 50 out 100, it means high level of corruption.


Introduction
In the recent decades, corruption is become the most important issue for transition economies.During the transition processes in SEE countries, corruption has been constantly a phenomenon accompanying from communist regime to liberalization markets.It has had an effect on low institutional performance, lack of transparency in public sector and distrust of the citizens towards in government institutions, (SELDI Report, 2002) & (Svendsen, G.T., 2003).Also, in transition economies were constantly faced with different crisis from Euro zone and global financial crisis then corruption has bring more damage and trouble in these economies, (Sanfey, P. & Zeh, S., 2012).According to (World Bank Report, 2011) corruption has not been only obstacle in SEE economies, so as other obstacle identified bribery (administrative bribes) and unofficial payments in very sensitive institutions, such as: areas of taxes, customs, imports and courts but recently SEE countries have started to improve in context of bribery.But most of SEE countries are oriented to prevent or fight corruption (bribery) through three general categories: fight against corruption by government institutions (different agencies), different structural reforms in institutions for reducing corruption, membership in international organization (such as: UN, EU) to prevent corruption, (Ewoh et al, 2013).

A Review of Selected Literature
Large and persistent differences of corruption across transition countries are a challenging research issue, (Sah, 2007), for this reason the corruption activities for transition countries have been interesting for research since middle of the 1990's.In fact, this period represented the time when transition countries started economic transformation and corruption was an integral part of the process of economic transition in these countries.Corruption has reflected in various indicators of economy, such as: in reducing the level of FDI and domestic investment, the embezzlement of public funds, lower productivity in growth, decline of capital accumulation and growth, etc; (Jimenez, M.D.M.S & Jimenez, J.S, 2007) & (Blackburn, K. & Powell, J, 2011).Also corruption (through bribe paying) hampers international trade particular in countries with high export rate (De Jong, E. & Bogmans, Ch, 2011).As argued (Farooq et al, 2013) & (Osipian, 2012), in long time relationship, corruption impedes economic growth especially in financial development (weakens the financial capital), free trade (reduces domestic production) and human development (reduces the level of human capital and slowing the pace of its development), etc.
For this reason different international institutions invited countries with high level of corruption for fighting through institutions government policies and for preventing through other non-government institutions.As argued (Khoman, 2015), the corruption was involved in many countries in the world, including departments from simple administrative services to complex corruption (political favors for corruption), this form of corruption is widespread and pernicious.According to Ban Kim Mon's message (United National Secretary General) on International Anti -Corruption Day "corruption is a threat to development, democracy and stability in global aspect" and this will be the biggest challenge in the future (United Nation, 2010), so preventing corruption by government institution and other relevant institutions is the most important issue in transition countries.Most of transition countries have ratified anti -corruption programs by national parliaments (Michael, B, 2010) but the problem is that anti -corruption programs are not being implemented (anti-corruption legal work has not yet succeeded their execution) by different political and business pressure.
Corruption can affect anywhere in different ways: macro environment (where correlation with corruption is from 0.40 to 0.45), economic development, socio -cultural factors, political / legal stability (Judge et al, 2011) and fighting corruption is a political criteria for transition countries to integration into international organization (EU).As argued by (Dzhumashev, 2014) & (Graeff, P. & Mehlkopb, G, 2003), the significant effect in corruption outcomes are these important factors: the quality of governance, the level economic performance, the size of public spending, economic freedom, etc.This means that the greater level of these factors will have the lower impact of corruption and in otherwise the impact of corruption will be higher.Many authors have research the relationship between corruption and economic growth and most of them agreed that the corruption have negative impact in economic growth (Mauro, P, 1997) & (Mo, 2001) & (Aidt, 2009) Other authors argued that exist a negative rate of correlation between corruption and the average rate of per-capita income growth in countries with democratic regime (Mendez, F. & Sepulveda, F, 2006) also countries with capital account liberalization (financial openness) and government corruption has a negative impact on growth (Kunieda et al, 2014).

Effect of Corruption in Transition Countries
Corruption has been one of the major problems for transition countries over few recent decades particularly after transformation from command economy to global market economy.According to (World Bank, 2004), estimates about corruption (bribes pay) in every year is over US $ 1 trillion and countries that fight or prevent corruption through institutional policies and anti -corruption programs could improve their capita incomes by 400 percent, it continues to be one of the biggest challenges for global countries in modern economy.In some countries is very hard to overcome the problem of corruption because corruption has managed to have a large extent inside of different departments..According to (Transparency International Report, 2014), most of SEE countries have scored below levels (50 out of 100), that shows a serious problem of corruption, while the lowest level of corruption in global index is in Denmark (92 out of 100) and the highest level of corruption in global index has Somalia (8 out of 100), for further detail see table below.(Transparency Report, 2013) about 69 % of global countries have higher level of corruption (the index of corruption is under 50 out of 100).Regardless of the continuous progress across SEE countries and the establishment of a democratic political system on the one hand and lack of trust in the political system and increasing level of corruption in these countries on the other hand, signifies that corruption can bring one of the most serious threats for democracy, sustainability and stability in the countries of SEE, (McDevitt, 2013).The effects of corruption manifested between sector public (government institution) and private sector (people and private business).
According to (SELDI Report, 2013) & (Karklins, 2002) the corruption in SEE countries has shown two main types: a) "grand corruption" -the highest level of corruption in institutions (like as: top state officials, politicians, and business people, etc); "petty corruption" -includes simple administrative service in government institution (like as: bribing traffic cops, building inspectors, etc) and the second type associates with smaller payment and favors, gifts, etc.Many of research publications have suggested that corruption in transition economies has involved a lot of factors, such as government size, juridical system, education, religion, degree of economic freedom, welfare, geographic size of a country, (Goel, R.K. & Budak, J, 2006).These factors have reduced economic efficiency and overall economic performance.They have a direct negative implication in growth of SEE countries, (Budak, J. & Goel, R.K, 2004).In many of transition countries in the world a centralized administrative system has become a perfect opportunity to develop the corruption (Iwasaki, I. & Suzuki, T., 2010) while in countries that have the political institutions with high quality, corruption has a significant negative impact on economic growth, (Sena et al, 2008) but in countries with low-quality (less effective) institutions, corruption is less detrimental to economic efficiency (Meon, P.G. & Weill, L, 2010).The recent results show that the level of corruption will decline in SEE countries, if these countries include these important components: freedom economic (Pieroni, L. & d'Agostino, G, 2013), structural reform (Abed, G.T. & Davoodi, H.R, 2000) as well as economic performance (growth, inflation, the fiscal balance and FDI).This leads to structural reforms that dominate over the effect of corruption in SEE countries, (Abed, G.T. & Davoodi, H.R, 2000).

Methodology and Selected Data
In order to estimate the effect of corruption (bribery and bureaucracy) on transition countries, in case of SEE countries are used secondary data.They are collected by different international institutions (such as: World Bank, EBRD, IMF and Transparency International).Used data in research included the most of SEE countries (see Appendix 1/A) and most of variables that are used are from annual reports of 2014 (see Appendix 1/B).The main variables are: depend variables (corruption and bribery and bureaucracy costs) and independent variables (Economic Growth, Political Stability, Rule of Law, Economic Freedom, Transition Reform and Education Index).Data are calculated through program STATA (econometric -statistic program) then the main analyses are as following: descriptive statistics methods, multiple regression analysis and correlation method.The econometric models is to analyze the relationship between corruption (and Bribery & Bureaucracy) on economic growth and they are based on the following equations: Ln(CIt)+ +Ln(BBt) = 0 + 1ln(EGt) + 2ln(PSt) + 3ln(RLt) + 4ln(EFt) + 5ln(TRt) + 6ln(EIt) + t.Where the main variables for analyses are as following: • CI = Corruption Index; • BB = Bribery and Bureaucracy costs; • EG = Economic Growth; • PS = Political Stability; • RL = Rule of Law; • EF = Economic Freedom; • TR = Transition Reform;

Source: Authors
The value of Bribes and Bureaucracy costs variable are: the minimum is 15.3, maximum is 26.2 then value of mean and standard deviation are 20.9 respectively 3.45.Economic growth has values of minimum -3.3, maximum 3.1, mean 0.9 and standard deviation 1.89.The values of Political stability are as following: minimum and maximum -0.9 & 1.1 then mean and standard deviations are 0.2 & 0.61.Rule of Law have these values: minimum is -1.7, maximum is 1.0 then mean is 0.1 and standard deviation is 0.68.The value of minimum and maximum of Economics freedom are 6.6 respectively 7.6 then mean values is 7.2 and standard deviation is 0.28.Transition reforms have minimum value 2.8, maximum values 3.8 and mean 3.4 and standard deviation 0.32.In this research paper the values of Education Index are lowest from other variables: the minimum is 0.6 and maximum is 0.9 then mean is 0.7 and standard deviation is 0.10.The Table 3 is the most important analysis, and the OLS method analyzes the additional explanatory factors (or independent variables) have a systemic effect on the dependent variable.The main variables that are included in research paper are two dependent variables (corruption and bribery & bureaucracy) and other independent variables (Economic Growth, Political Stability, Rule of Law, Economic Freedom, Transition Reform and Education Index).
In OLS method are realized two regression analysis between dependent variables and independent variables: The first regression analysis is between corruption and independent variables and the results have found that Economic Growth has positive impact ( 1 = 0.74) on corruption.Explanation of result with positive impact is as following: when other variables in analysis (Political Stability, Rule of Law, Economic Freedom, Transition Reform and Education Index) are fixed or constant and when the economic growth increase for a unit, it will have effect in corruption with 0.74 per unit (positive impact).Also Rule of Law ( 3 = 2.31), Transition Reform ( 5 = 13.72) and Education Index ( 6 = 65.20)have positive impact on corruption.But the Political Stability has negative impact ( 2 = -6.95) on corruption.Explanation of results with negative impact is as following: when other variable that are included in analysis are fixed (constant) and when the political stability increase for a unit, it will have effect in corruption with -6.95 per unit (negative impact).Also Economic Index has negative impact ( 4 = 6.83) on corruption.
Through T-statistics, we can understand the explanatory capability (or significance) that the variables have between them and the significance can be positive (T > 2) or negative (T < 2).As argue the results in analysis (P t), all variables that are included in research (Economic Growth 0.47, Political Stability 0.19, Rule of Law 0.46, Economic Freedom 0.17, Transition Reform 0.06 and Education Index 0.08) have non -significance (T < 2) on corruption.Other important analysis in table 3 is the coefficient of determination (R²), it measures the correlation between dependent variable and independent variables, so the question is: What does mean the determination (R² = 0.99) between Corruption and Economic Growth, Political Stability, Rule of Law, Economic Freedom, Transition Reform and Education Index?It tells us: a) the relationship is positive between them; b) the relationship is quite strong (since the value of determination is pretty close to 1 (0.99) while 0.01% (100% -99%) are other factors that are not included in this model.

Source: Authors
The second regression analysis in table 3 is between bribery and bureaucracy costs as dependent variable and other independent variables and the results have found that Economic Growth has negative impact ( 1 = -1.30) on bribery and bureaucracy costs.Also Political Stability ( 2 = -0.08),Rule of Law ( 3 = -3.29),Economic Freedom ( 4 = -1.51)have negative impact on bribery and bureaucracy costs but only Transition Reform ( 5 = 5.39) and Education Index ( 6 = 18.30) have positive impact on bribery and bureaucracy costs.In T-statistic analysis the results shown that all independent variables (Economic Growth 0.14, Political Stability 0.98, Rule of Law 0.20, Economic Freedom 0.65, Transition Reform 0.24 and Education Index 0.43) are non -significant (T < 2) on dependent variable (bribery and bureaucracy costs).In the second regression analysis, the coefficient of determination is R² = 0.99 between dependent and independent variables, then the relationship between them is quite strong (since the value of determination is pretty close to 1 (0.99) while 0.01% (100% -99%) are other factors that are not included in this model.In table 4 is Correlation Matrix, it shows the level of relationship between dependent variable and independent variables.The first correlation matrix is between corruption and independent variables and the results shown that economic growth (-0.25) and economic freedom (-0.35) have negative correlation with corruption.Other independent variables (political stability 0.71, rule of law 0.91, transition reform 0.59 and education index 0.79) have positive correlation with corruption.The second correlation matrix is between bribery and bureaucracy costs and independent variables and the results shown that the same variables, economic growth (-0.78) and economic freedom (-0.55) have the highest negative correlation with bribery and bureaucracy costs than in corruption analysis.Other independent variables (political stability 0.43, rule of law 0.16, transition reform 0.03 and education index 0.42) have positive correlation with bribery and bureaucracy costs.Source: Authors

Conclusion
In this research paper is analysis corruption and bribery & bureaucracy costs on transition countries with case study of SEE countries.The data used are secondary data and they are collected from international institutions (World Bank, IMF, UNDP and EBRD).The most of data for analysis included one period of time ( 2014) and data are calculated by STATA program (econometric and statistical software).The main variables in research paper are as following: in one side are corruption and bribery & bureaucracy costs as depend variables and in other side are economic growths, political stability, rule of law, economic freedom, transition reform and education index as independent variables.The main analyses in research paper include descriptive statistic methods, regression analysis (OLS method).In OLS method and correlation matrix are realized two type of analyses: the first is between corruption and independent variables and the second is between bribery and bureaucracy costs and independent variables.At the first, the results of regression (OLS) method shown that economic growth ( 1=0.74) has positive impact on corruption.Also rule of law ( 3=2.31), transition reform ( 5=13.72) and education index ( 6=65.20) have positive impact on corruption.Political stability ( 2=-6.95) and economic freedom ( 2=-6.83) has negative impact on corruption.In Tstatistic analysis, the results shown that all independent variables are non -significant (T<2) on dependent variable.In Tstatistic analysis the results shown that all independent variables (T<2) are non-significant on dependent variable and the coefficient of determination in R² = 0.99.At the second, the results of regression (OLS) method shown that Economic Growth has negative impact ( 1=-1.30) on bribery and bureaucracy costs.Also Political Stability ( 2= -0.08), Rule of Law ( 3= -3.29), Economic Freedom ( 4= -1.51) have negative impact on bribery and bureaucracy costs.But only Transition Reform ( 5=5.39) and Education Index ( 6=18.30) have positive impact on bribery and bureaucracy costs.In T-statistic analysis the results shown that all independent variables are non -significant (T<2) on dependent variable.Then the coefficient of determination is R² = 0.99 between dependent and independent variables.

Table 1 .
Index of Corruption in SEE Countries 2012 -2014 If we refer table above, we can understand that the level of corruption on SEE countries has increased year by year from 2012 to 2014 but in the SEE countries 10 from 13 countries that are including in table above have the average score of corruption in 43.3 %.According to Source: Transparency International Report 2014, 2012, 2012 This part of research paper reflects the results of analysis, they are calculated through econometric program STATA.In fact, this is the most important part because here are interpreted the implications of the parameters (variables) that are involved in research paper with different methods (Statistic descriptive, Correlation method, Ordinary Least Squares method).In table 2 is Descriptive Statistic, which is a method for quantitative analysis data and it is used to describe the basic features of the data in a research paper.Most of variables that are included in research paper have 14 observations.The main analyses in table 2 are as following: the minimum value of the perceived level of corruption index is 33 (it means, the lowest value of "CI" in period of research) and maximum value is 58 (it means, the highest value of "CI" in period of research), the value of mean is 44.5 (it means, average value of "CI" in period of research) and standard deviation values is 7.22 (it means, how many the "CI" variable are quite close between 33 to 54).

Table 3 .
Test of Ordinary Least Squares (OLS) Method