The effect of corruption on economic growth in southeast asia countries

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The effect of corruption on economic growth in southeast asia countries

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UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE EFFECT OF CORRUPTION ON ECONOMIC GROWTH IN ASIAN COUNTRIES BY LE KIM DUNG MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, Dec 2016 UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE 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 II ACKNOWLEDGEMENT I would like to express my gratitude to interesting and extensive Vietnam– Neitherlands Master Program in Development Economics, as well as honest thanks to many people who built and developed this program such as management board, lecturers, tutors, and librarians Fulfillment this course, I acquired useful knowledge, approached new things, were straightforward to expess ideas 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 Contents………………………………………………………………………………… III List of tables……………………………………………………………………………… IV List of figures V Abstract………………………………………………………………………………… CHAPTER 1: INTRODUCTION 1.1 Research problem 1.2 Research objectives and research questions 1.2.1 Research objectives 1.2.2 Research questions 1.3 Thesis Structure CHAPTER 2: LITERATURE REVIEW 2.1 Theoretical concepts related to economic growth and corruption 2.2 Effect of corruption on economic growth: theoretical literatures 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 3.3 Data 31 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 LE KIM DUNG Page 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 LE KIM DUNG Page methodology, a one-unit increase in 2SLS, OLS corruption perception 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 Aidt et al., Threshold (2008) model, General, data set of 67- Non-linearity of corruptiontest 71 hypothesis developed and growth developing countries correlation The effects of corruption on Sample period is from growth depends on quality 1996-2002 governance regimes In the countries with high quality institutions regimes, it has a large and significant negative effect Adversely, there is no impact in countries with low quality governance regimes Mohamed Cross-country Data covering 82 both Negative Dribi (2013) regression, developed Channel developing LE KIM DUNG impacts of and corruption on growth The over the most important Page 65 Methodology period 1980-2002 transmission channels through which corruption operates are human capital (-0.5%) and political instability (-0.46%) The contribution of capital, human investment, inflation, political instability to negative impact of corruption on growth is 36.6%, 22.9%, 6.6%, and 33.8% respectively Corruption has effect positive growth via on government expenditure channel 10 Haque and Threshold Data Kneller model developed and strong developing countries relationship (2009) covering 54 There is existence of a mutual negative between with observed period corruption and economic 1980-2003 growth Corruption changeable and is this relationship depends on the culture, any changes in culture tends to the destruction of the threshold Almost resources belongs to the state, government principally concerns with LE KIM DUNG Page 66 corruption, so development traps move up 11 Mina GMM Data covering 33 Corruption has a strong Baliamoune- African countries with negative impact on Lutz and observed period from domestic investment and Leonce 1982 to 2001 economic growth General Corruption as queuing money” efficient model economic growth Ndikumana (2008) 12 13 Lui (1985) Leff (1964) Equilibrium Analytical is “speed to “Grease the wheel” thesis, General method positive between relationship corruption and growth 14 Lien (1986) General Competitive bribery Corruption may be helpful game with incomplete to economic development information 15 Kaufmann Build up the Global and Wei model (1999) on countries in 1996 and expressed differently, they Stackellberg 1997 game based survey 3866 from firms no evidences support for 48 the “speed money” thesis, refuted “efficient grease” thesis, so corruption reduces economic growth LE KIM DUNG Page 67 APPENDIX B: Sample of countries Armenia 16 Nepal Azerbaijan 17 Pakistan Bangladesh 18 Srilanka China 19 Jajikistan India 20 Brunei Danissalam Iran Islamic Republic 21 Cambodia Israel 22 Timor - Leste Japan 23 Indonesia Jordan 24 Lao PDR 10 Kazakhstan 25 Malaysia 11 Korea Republic 26 Myanmar 12 Kyrgyz Republic 27 Philippines 13 Lebanon 28 Singapore 14 Mongolia 29 Thailand 15 Oman 30 Viet Nam LE KIM DUNG Page 68 APPENDIX C: REGRESSION RESULTS C.1 Declare data to the panel encode country, gen(id) xtset id year panel variable: id (strongly balanced) time variable: year, 1996 to 2014 delta: unit C.2 Calculating capital from the gross domestic fixed investment tsset id year by id: egen avg_ggfK=mean( igrowth ) replace avg_ggfK=avg_ggfK/100 gen depreciation=0.05 by id: gen K= iusd[1]/(depreciation+avg_ggfK) by id: replace K=(1-depreciation)* L.K+ iusd if _n>1 C.3 Descriptive statistics Graph: graph twoway (lfit variable1 variable2) (scatter variable1 variable2) Descriptive statistics: sum gdpgrowth cpiunit igrowth hc piunit govgdp opengdp Corellations: correlate gdpgrowth cpiunit igrowth hc piunit govgdp opengdp VIF Collin cpiunit igrowth hc piunit govgdp opengdp LE KIM DUNG Page 69 collin cpiunit igrowth hc piunit govgdp opengdp (obs=253) Collinearity Diagnostics SQRT RVariable VIF VIF Tolerance Squared -cpiunit 1.87 1.37 0.5358 0.4642 igrowth 1.21 1.10 0.8233 0.1767 hc 1.64 1.28 0.6084 0.3916 piunit 1.82 1.35 0.5487 0.4513 govgdp 1.27 1.13 0.7887 0.2113 opengdp 1.11 1.05 0.8993 0.1007 -Mean VIF 1.49 Cond Eigenval Index 4.8912 1.0000 0.8147 2.4503 0.7867 2.4935 0.2572 4.3610 0.1840 5.1564 0.0481 10.0817 0.0182 16.4125 Condition Number 16.4125 Eigenvalues & Cond Index computed from scaled raw sscp (w/ intercept) Det(correlation matrix) 0.2820 C.4 Regression results Pooled OLS regression results of GDP model (Model 1) LE KIM DUNG Page 70 reg gdpgrowth cpiunit igrowth hc piunit govgdp opengdp Source SS df MS Model Residual 1597.41618 3635.4249 266.236029 246 14.77815 Total 5232.84108 252 20.7652424 gdpgrowth Coef cpiunit igrowth hc piunit govgdp opengdp _cons -.5154352 1652213 0129003 -.1179124 -.0358273 004797 5.012839 Std Err .2099528 0185209 0153824 3505925 0226089 005932 1.466208 t -2.46 8.92 0.84 -0.34 -1.58 0.81 3.42 Number of obs F( 6, 246) Prob > F R-squared Adj R-squared Root MSE P>|t| 0.015 0.000 0.402 0.737 0.114 0.419 0.001 = = = = = = 253 18.02 0.0000 0.3053 0.2883 3.8442 [95% Conf Interval] -.9289696 1287415 -.0173978 -.8084585 -.0803591 -.0068871 2.124915 -.1019008 2017011 0431984 5726337 0087044 016481 7.900763 FEM regression results of GDP model (Model 1) xtreg gdpgrowth cpiunit igrowth hc piunit govgdp opengdp,fe Fixed-effects (within) regression Group variable: id Number of obs Number of groups = = 253 26 R-sq: Obs per group: = avg = max = 9.7 15 within = 0.2561 between = 0.0323 overall = 0.1786 corr(u_i, Xb) F(6,221) Prob > F = -0.1936 gdpgrowth Coef cpiunit igrowth hc piunit govgdp opengdp _cons 3331118 1561048 -.0219766 1347567 -.1257954 024225 4.599427 603185 0186316 0405505 7562715 1001291 0187165 3.710579 sigma_u sigma_e rho 2.6531922 3.6222947 34917027 (fraction of variance due to u_i) F test that all u_i=0: LE KIM DUNG Std Err F(25, 221) = t P>|t| = = 0.55 8.38 -0.54 0.18 -1.26 1.29 1.24 2.24 0.581 0.000 0.588 0.859 0.210 0.197 0.216 12.68 0.0000 [95% Conf Interval] -.8556188 1193865 -.1018917 -1.35567 -.3231256 -.0126607 -2.71322 1.521842 1928231 0579385 1.625183 0715347 0611108 11.91207 Prob > F = 0.0010 Page 71 REM regression results of GDP model (Model 1) xtreg gdpgrowth cpiunit igrowth hc piunit govgdp opengdp,re Random-effects GLS regression Group variable: id Number of obs Number of groups = = 253 26 R-sq: Obs per group: = avg = max = 9.7 15 within = 0.2431 between = 0.5533 overall = 0.3046 corr(u_i, X) Wald chi2(6) Prob > chi2 = (assumed) gdpgrowth Coef cpiunit igrowth hc piunit govgdp opengdp _cons -.4756252 1599184 0088387 -.1357008 -.0378981 0070921 5.065353 2696616 0180012 0192831 4215096 0260947 0080145 1.804259 sigma_u sigma_e rho 1.164715 3.6222947 09370082 (fraction of variance due to u_i) Std Err z P>|z| -1.76 8.88 0.46 -0.32 -1.45 0.88 2.81 0.078 0.000 0.647 0.747 0.146 0.376 0.005 = = 95.31 0.0000 [95% Conf Interval] -1.004152 1246367 -.0289555 -.9618445 -.0890428 -.0086161 1.52907 0529017 1952002 0466329 6904429 0132465 0228003 8.601637 Hausman test for FEM and REM of GDP model (Model 1) hausman fixed random Coefficients (b) (B) fixed random cpiunit igrowth hc piunit govgdp opengdp 3331118 1561048 -.0219766 1347567 -.1257954 024225 -.4756252 1599184 0088387 -.1357008 -.0378981 0070921 (b-B) Difference sqrt(diag(V_b-V_B)) S.E .808737 -.0038136 -.0308153 2704574 -.0878973 0171329 5395505 0048054 0356722 6279141 0966691 0169138 b = consistent under Ho and Ha; obtained from xtreg B = inconsistent under Ha, efficient under Ho; obtained from xtreg Test: Ho: difference in coefficients not systematic chi2(6) = (b-B)'[(V_b-V_B)^(-1)](b-B) = 7.16 Prob>chi2 = 0.3059 LE KIM DUNG Page 72 Shapiro – Wilk W test for normality of residual in OLS regression (Model 1) swilk r Shapiro-Wilk W test for normal data Variable Obs W V z Prob>z r 253 0.82547 31.988 8.067 0.00000 Homoscedasticity of residuals test (Model 1) White’s test: estat imtest Cameron & Trivedi's decomposition of IM-test Source chi2 df Heteroskedasticity Skewness Kurtosis 55.20 7.92 1.85 27 0.0011 0.2439 0.1738 Total 64.98 34 0.0011 p Breusch - Pagan test: estat hettest Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of gdpgrowth chi2(1) Prob > chi2 = = 4.69 0.0304 Homoscedasticity of residuals test (Model 1)- Ramsey Reset test LE KIM DUNG Page 73 linktest Source SS df MS Model Residual 1782.76177 3450.07931 250 891.380884 13.8003172 Total 5232.84108 252 20.7652424 gdpgrowth Coef _hat _hatsq _cons 1.66222 -.0572969 -1.530081 Std Err .2032026 0156345 6777408 t 8.18 -3.66 -2.26 Number of obs F( 2, 250) Prob > F R-squared Adj R-squared Root MSE = = = = = = 253 64.59 0.0000 0.3407 0.3354 3.7149 P>|t| [95% Conf Interval] 0.000 0.000 0.025 1.262013 -.088089 -2.86489 2.062427 -.0265047 -.1952713 ovtest Ramsey RESET test using powers of the fitted values of gdpgrowth Ho: model has no omitted variables F(3, 243) = 9.12 Prob > F = 0.0000 3SLS regression for several equations *Reg3 command with Gross domestic fixed investment (I) – proxy for capital reg3(gdpgrowth cpiunit piunit igrowth govgdp opengdp hc)( piunit cpiunit govgdp lngdpusd lnpop urbanpop dli dlmi dumi dhio dhino)( igrowth cpiunit hc lngdpusd opengdp dli dlmi dumi dhio dhino)( govgdp cpiunit hc lngdpusd urbanpop dli dlmi dumi dhio dhino)( opengdp cpiunit lngdpusd hc govgdp dli dlmi dumi dhio dhino)( hc cpiunit lngdpusd edugdp lnpop urbanpop dli dlmi dumi dhio dhino) Three-stage least-squares regression Equation Obs Parms RMSE "R-sq" chi2 P gdpgrowth piunit igrowth govgdp opengdp hc 185 185 185 185 185 185 9 9 10 4.006249 7128735 13.72176 11.00549 41.12856 12.30538 0.2516 0.4546 0.0995 0.2965 0.0833 0.6324 26.47 158.65 64.87 408.54 1336.21 8050.52 0.0002 0.0000 0.0000 0.0000 0.0000 0.0000 LE KIM DUNG Page 74 Coef Std Err z P>|z| [95% Conf Interval] gdpgrowth cpiunit piunit igrowth govgdp opengdp hc _cons -.5311143 3607524 2174544 -.098411 0118931 0128801 5.34869 4511615 1.313489 1126636 0643737 0133055 0281042 3.955681 -1.18 0.27 1.93 -1.53 0.89 0.46 1.35 0.239 0.784 0.054 0.126 0.371 0.647 0.176 -1.415375 -2.213638 -.0033621 -.2245811 -.0141851 -.0422031 -2.404302 353146 2.935143 438271 0277591 0379714 0679632 13.10168 piunit cpiunit govgdp lngdpusd lnpop urbanpop dli dlmi dumi dhio dhino _cons 291338 0050093 1211904 -.1801784 -.013966 -1.701556 -1.143323 -.6586265 -.7084234 -.1502332 075922 0079304 1167812 1244048 0056436 5428494 4378157 3635242 361688 (omitted) 1.428438 3.84 0.63 1.04 -1.45 -2.47 -3.13 -2.61 -1.81 -1.96 0.000 0.528 0.299 0.148 0.013 0.002 0.009 0.070 0.050 1425336 -.0105341 -.1076965 -.4240074 -.0250272 -2.765521 -2.001426 -1.371121 -1.417319 4401425 0205526 3500773 0636506 -.0029047 -.6375903 -.2852201 0538677 000472 -0.11 0.916 -2.94992 2.649453 igrowth cpiunit hc lngdpusd opengdp dli dlmi dumi dhio dhino _cons 3.784624 0460711 -3.762947 -.0847588 87.30483 97.5052 94.13109 81.44498 76.78346 2.470471 1449955 1.539685 0932207 39.52311 43.69549 47.39989 44.37718 42.40005 (omitted) 1.53 0.32 -2.44 -0.91 2.21 2.23 1.99 1.84 1.81 0.126 0.751 0.015 0.363 0.027 0.026 0.047 0.066 0.070 -1.057411 -.2381149 -6.780674 -.2674679 9.840956 11.86362 1.229012 -5.532695 -6.319112 8.626659 3302571 -.7452203 0979504 164.7687 183.1468 187.0332 168.4226 159.886 govgdp cpiunit hc lngdpusd urbanpop dli dlmi dumi dhio dhino _cons 3.013211 080342 -4.192961 -.1885901 97.85523 113.9276 114.7613 123.8547 109.0643 1.095067 1121554 6285869 0652022 18.20078 20.1155 21.41964 24.40042 22.22862 (omitted) 2.75 0.72 -6.67 -2.89 5.38 5.66 5.36 5.08 4.91 0.006 0.474 0.000 0.004 0.000 0.000 0.000 0.000 0.000 8669185 -.1394785 -5.424969 -.3163841 62.18236 74.50196 72.77962 76.03077 65.49704 5.159503 3001624 -2.960954 -.0607962 133.5281 153.3533 156.7431 171.6786 152.6316 opengdp cpiunit lngdpusd hc govgdp dli dlmi dumi dhio dhino _cons 13.81335 -2.194812 -.1303527 2.772454 55.17744 53.2372 94.88242 -8.781279 28.33626 3.309795 2.239632 3143452 2992204 61.42185 68.41274 71.45393 80.22844 72.7963 (omitted) 4.17 -0.98 -0.41 9.27 0.90 0.78 1.33 -0.11 0.39 0.000 0.327 0.678 0.000 0.369 0.436 0.184 0.913 0.697 7.326276 -6.58441 -.7464579 2.185993 -65.20717 -80.8493 -45.16471 -166.0261 -114.3419 20.30043 2.194786 4857525 3.358916 175.562 187.3237 234.9295 148.4636 171.0144 LE KIM DUNG Page 75 hc cpiunit lngdpusd edugdp lnpop urbanpop dli dlmi dumi dhio dhino _cons -3.50982 13.95158 1.551186 -17.7138 -.1379824 34.80135 45.61234 38.92841 51.56339 34.59282 Endogenous variables: Exogenous variables: dhino edugdp 1.321533 2.020281 647293 2.078573 0886948 18.30126 19.63624 21.32442 23.37033 21.59988 (omitted) -2.66 6.91 2.40 -8.52 -1.56 1.90 2.32 1.83 2.21 1.60 0.008 0.000 0.017 0.000 0.120 0.057 0.020 0.068 0.027 0.109 -6.099978 9.991906 2825151 -21.78773 -.311821 -1.068452 7.126013 -2.866683 5.75838 -7.742162 -.9196627 17.91126 2.819857 -13.63987 0358562 70.67116 84.09867 80.7235 97.36841 76.92781 gdpgrowth piunit igrowth govgdp opengdp hc cpiunit lngdpusd lnpop urbanpop dli dlmi dumi dhio *Reg3 command with Capital stock series (K) calculated following method proposed by Rodney Smith (2010) – proxy for capital reg3(gdpgrowth cpiunit piunit k govgdp opengdp hc)( piunit cpiunit govgdp lngdpusd lnpop urbanpop dli dlmi dumi dhio dhino)( k cpiunit hc lngdpusd opengdp dli dlmi dumi dhio dhino)( govgdp cpiunit hc lngdpusd urbanpop dli dlmi dumi dhio dhino)( opengdp cpiunit lngdpusd hc govgdp dli dlmi dumi dhio dhino)( hc cpiunit lngdpusd edugdp lnpop urbanpop dli dlmi dumi dhio dhino) Three-stage least-squares regression Equation Obs Parms RMSE "R-sq" chi2 P gdpgrowth piunit k govgdp opengdp hc 163 163 163 163 163 163 8 6.793868 5307033 7.53e+12 11.29342 48.94792 10.14695 -0.9598 0.6592 -0.1752 0.3207 -0.2401 0.6399 15.53 423.78 73.67 383.47 382.98 0.0083 0.0000 0.0000 0.0000 0.0000 LE KIM DUNG Page 76 Coef Std Err z P>|z| [95% Conf Interval] gdpgrowth cpiunit piunit k govgdp opengdp hc _cons -2.291075 2.143574 -8.18e-13 1160065 0139704 -.0231121 14.96907 1.051429 2.106806 3.64e-13 0952292 0144517 0445894 7.961554 -2.18 1.02 -2.25 1.22 0.97 -0.52 1.88 0.029 0.309 0.025 0.223 0.334 0.604 0.060 -4.351839 -1.985691 -1.53e-12 -.0706393 -.0143544 -.1105057 -.6352904 -.2303119 6.272839 -1.05e-13 3026524 0422952 0642815 30.57343 piunit cpiunit govgdp lngdpusd lnpop urbanpop dli dlmi dumi dhio dhino _cons 3528733 0162985 -.0194493 -.0638124 -.0071141 -1.66031 -.7669472 -.4353058 1124231 4863594 0523065 0050658 0778651 0848336 003856 3774399 2987061 2483506 2563291 (omitted) 9348662 6.75 3.22 -0.25 -0.75 -1.84 -4.40 -2.57 -1.75 0.44 0.000 0.001 0.803 0.452 0.065 0.000 0.010 0.080 0.661 2503544 0063698 -.172062 -.2300831 -.0146718 -2.400079 -1.3524 -.9220641 -.3899727 4553923 0262272 1331635 1024583 0004436 -.9205418 -.181494 0514524 6148189 0.52 0.603 -1.345945 2.318664 cpiunit hc lngdpusd opengdp dli dlmi dumi dhio dhino _cons 0 0 0 0 0 (omitted) (omitted) (omitted) (omitted) (omitted) (omitted) (omitted) (omitted) (omitted) (omitted) govgdp cpiunit hc lngdpusd urbanpop dli dlmi dumi dhio dhino _cons 2.92036 -.12081 -4.820014 -.1170038 -16.36479 3.755742 4.398207 19.11476 138.2962 1.136993 1201664 6327436 0615617 8.806624 6.339598 5.635531 5.717651 (omitted) 22.61606 2.57 -1.01 -7.62 -1.90 -1.86 0.59 0.78 3.34 0.010 0.315 0.000 0.057 0.063 0.554 0.435 0.001 6918938 -.3563318 -6.060169 -.2376625 -33.62546 -8.669642 -6.64723 7.908368 5.148825 1147118 -3.579859 003655 8958745 16.18113 15.44364 30.32115 6.11 0.000 93.96953 182.6229 opengdp cpiunit lngdpusd hc govgdp dli dlmi dumi dhio dhino _cons 10.53922 -.2746877 -.1141282 3.440073 7.936822 18.29189 58.7074 -46.81049 -7.118219 3.149465 2.063139 318493 2524114 23.81489 17.03485 15.29559 15.8938 (omitted) 69.81846 3.35 -0.13 -0.36 13.63 0.33 1.07 3.84 -2.95 0.001 0.894 0.720 0.000 0.739 0.283 0.000 0.003 4.366382 -4.318365 -.7383629 2.945356 -38.7395 -15.09581 28.7286 -77.96176 16.71206 3.76899 5101066 3.93479 54.61314 51.67958 88.68621 -15.65922 -0.10 0.919 -143.9599 129.7234 k LE KIM DUNG Page 77 hc cpiunit lngdpusd edugdp lnpop urbanpop dli dlmi dumi dhio dhino _cons -1.735516 12.03271 -1.407223 -16.09899 -.2030719 -.0072011 13.50716 6.983277 21.00772 62.17129 Endogenous variables: Exogenous variables: dhino edugdp 1.007481 1.482803 5206183 1.539084 0657741 6.949825 5.589678 4.754113 4.669553 (omitted) 15.93179 -1.72 8.11 -2.70 -10.46 -3.09 -0.00 2.42 1.47 4.50 0.085 0.000 0.007 0.000 0.002 0.999 0.016 0.142 0.000 -3.710142 9.126465 -2.427616 -19.11554 -.3319867 -13.62861 2.551591 -2.334613 11.85556 2391098 14.93895 -.3868293 -13.08244 -.074157 13.6142 24.46272 16.30117 30.15987 3.90 0.000 30.94555 93.39703 gdpgrowth piunit k govgdp opengdp hc cpiunit lngdpusd lnpop urbanpop dli dlmi dumi dhio reg3( gdpgrowth cpiunit piunit igrowth govgdp opengdp hc)( igrowth cpiunit hc opengdp lngdpusd)( hc cpiunit lngdpusd)( piunit cpiu > nit govgdp lngdpusd)( govgdp cpiunit hc lngdpusd)( opengdp cpiunit hc govgdp lngdpusd) Equation is not identified does not meet order conditions Equation gdpgrowth: gdpgrowth cpiunit piunit igrowth govgdp opengdp hc Exogenous variables: cpiunit lngdpusd r(481); *Reg3 command with CPI in square format reg3(gdpgrowth sqcpi piunit igrowth govgdp opengdp hc)( piunit sqcpi govgdp lngdpusd lnpop urbanpop dli dlmi dumi dhio dhino)( igr > owth sqcpi hc lngdpusd opengdp dli dlmi dumi dhio dhino)( govgdp sqcpi hc lngdpusd urbanpop dli dlmi dumi dhio dhino)( opengdp sqc > pi lngdpusd hc govgdp dli dlmi dumi dhio dhino)( hc sqcpi lngdpusd edugdp lnpop urbanpop dli dlmi dumi dhio dhino) Three-stage least-squares regression Equation Obs Parms gdpgrowth piunit igrowth govgdp opengdp hc 213 213 213 213 213 213 LE KIM DUNG 10 9 9 RMSE "R-sq" chi2 P 4.539146 7171053 15.34428 12.46649 38.45849 13.9284 -0.0377 0.4196 0.1196 0.0063 0.1248 0.5866 25.15 362.13 77.87 343.91 1287.23 382.05 0.0003 0.0000 0.0000 0.0000 0.0000 0.0000 Page 78 Coef gdpgrowth sqcpi piunit igrowth govgdp opengdp hc _cons Std Err z P>|z| [95% Conf Interval] -.0362319 -.1178872 2436632 -.1114456 0061845 0343141 2.290303 0344232 9214 0820773 0518022 0150394 0320252 2.813812 -1.05 -0.13 2.97 -2.15 0.41 1.07 0.81 0.293 0.898 0.003 0.031 0.681 0.284 0.416 -.1037002 -1.923798 0827946 -.212976 -.0232922 -.0284541 -3.224668 0312363 1.688024 4045317 -.0099152 0356612 0970822 7.805273 0210677 0026539 028902 -.1371901 -.0125082 3591928 9298866 1.482116 1.825168 2.586785 0072288 0071229 0986949 1093507 0049913 9673367 1.076071 1.147118 1.24906 1.167926 (omitted) 2.91 0.37 0.29 -1.25 -2.51 0.37 0.86 1.29 1.46 2.21 0.004 0.709 0.770 0.210 0.012 0.710 0.388 0.196 0.144 0.027 0068995 -.0113067 -.1645365 -.3515135 -.022291 -1.536752 -1.179174 -.7661933 -.6229446 2976919 035236 0166144 2223405 0771333 -.0027254 2.255138 3.038947 3.730426 4.273281 4.875879 1615508 -.173493 -2.269752 0804484 61.09225 71.88759 67.7751 70.0511 57.32626 2018683 1585172 1.161091 0886733 31.81856 34.12979 37.32329 34.76761 34.38101 (omitted) 0.80 -1.09 -1.95 0.91 1.92 2.11 1.82 2.01 1.67 0.424 0.274 0.051 0.364 0.055 0.035 0.069 0.044 0.095 -.2341037 -.484181 -4.545448 -.093348 -1.27097 4.994428 -5.377197 1.907839 -10.05929 5572053 137195 005945 2542448 123.4555 138.7808 140.9274 138.1944 124.7118 2229148 413168 -2.681226 -.2617451 55.16064 61.72489 61.77293 64.91247 60.86328 1225449 1430322 6079888 0827808 17.31701 20.02316 21.47295 23.71441 21.61668 (omitted) 1.82 2.89 -4.41 -3.16 3.19 3.08 2.88 2.74 2.82 0.069 0.004 0.000 0.002 0.001 0.002 0.004 0.006 0.005 -.0172688 1328301 -3.872862 -.4239926 21.21992 22.48022 19.68672 18.43309 18.49537 4630984 6935059 -1.489589 -.0994977 89.10135 100.9696 103.8591 111.3919 103.2312 sqcpi lngdpusd hc govgdp dli dlmi dumi dhio dhino _cons 9389266 -3.212123 0959796 2.388698 117.7774 100.5592 138.0724 52.2139 90.64192 3459667 1.908151 3473433 3234937 51.40269 59.18146 62.88264 69.01432 63.13604 (omitted) 2.71 -1.68 0.28 7.38 2.29 1.70 2.20 0.76 1.44 0.007 0.092 0.782 0.000 0.022 0.089 0.028 0.449 0.151 2608443 -6.952031 -.5848007 1.754662 17.02993 -15.4343 14.82469 -83.05168 -33.10244 1.617009 5277843 77676 3.022734 218.5248 216.5528 261.3201 187.4795 214.3863 sqcpi lngdpusd edugdp lnpop urbanpop dli dlmi dumi dhio dhino _cons -.2083366 9.614833 3.641052 -11.50255 1379663 -1.116159 10.75759 4.841872 10.86474 5.176104 1347169 1.861799 5386872 1.984609 0880008 8.476607 6.733199 5.503794 5.806897 (omitted) 19.7149 -1.55 5.16 6.76 -5.80 1.57 -0.13 1.60 0.88 1.87 0.122 0.000 0.000 0.000 0.117 0.895 0.110 0.379 0.061 -.4723768 5.965774 2.585245 -15.39232 -.0345121 -17.73 -2.439241 -5.945366 -.5165692 0557037 13.26389 4.69686 -7.612789 3104447 15.49768 23.95441 15.62911 22.24605 0.26 0.793 -33.4644 43.81661 piunit sqcpi govgdp lngdpusd lnpop urbanpop dli dlmi dumi dhio dhino _cons igrowth sqcpi hc lngdpusd opengdp dli dlmi dumi dhio dhino _cons govgdp sqcpi hc lngdpusd urbanpop dli dlmi dumi dhio dhino _cons opengdp hc Endogenous variables: Exogenous variables: edugdp LE KIM DUNG gdpgrowth piunit igrowth govgdp opengdp hc sqcpi lngdpusd lnpop urbanpop dli dlmi dumi dhio dhino Page 79 ... to economic growth and corruption 2.2 Effect of corruption on economic growth: theoretical literatures 2.3 Effect of corruption on economic growth: empirical studies 11 2.3.1 The. .. 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. .. 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

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