UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM – NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS IMPACT OF ECONOMIC VOLATILITY ON CORPORATE INCOME TAX RATE: THE CASE OF 20 ASIAN COUNTRIES MASTER OF ARTS IN DEVELOPMENT ECONOMICS BY TRUONG HOANG YEN Academic Supervisor Dr NGUYEN HOANG BAO HO CHI MINH CITY, JANUARY 2015 UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HO CHI MINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM – NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS IMPACT OF ECONOMIC VOLATILITY ON CORPORATE INCOME TAX RATE: THE CASE OF 20 ASIAN COUNTRIES A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By TRUONG HOANG YEN Academic Supervisor Dr NGUYEN HOANG BAO HO CHI MINH CITY, JANUARY 2015 ABSTRACT This paper examines the impact of economic volatility on the corporate income tax rate in the context of globalization and international taxation competition The impact is analyzed by two models, direct and indirect effect model The former investigates directly the relationship of corporate income tax rates and economic volatility in terms of real interest rate, exchange rate, and growth rate The latter applies a system of equations to examine simultaneously the determinants of tax rate and tax base The study finds out that economic volatility impacts negatively on corporate income tax rate and also negatively on foreign direct investment (FDI) inflows Moreover, corporate income tax rate affects negatively and significantly on FDI inflows, meanwhile FDI inflows influence corporate income tax rate with positive and significant impact CONTENTS CHAPTER ONE: INTRODUCTION 1.1 Problem statement 1.2 Research objectives and research questions 1.3 The structure of research CHAPTER TWO: LITERATURE REVIEW 2.1 Theoretical literature 2.1.1 Roles of corporate income tax rate 2.1.2 Economic volatility 2.1.3 Foreign direct investment 2.1.4 Tax competition 11 2.2 Empirical literature 15 2.2.1 Economic volatility 15 2.2.2 Corporate income tax rate 17 2.2.3 FDI inflows 19 2.2.4 FDI outflows 19 2.2.5 Country size 20 2.2.6 Capital openness 21 2.2.7 Government expenditure 22 2.2.8 Productivity 23 2.2.9 Employment rate and demographic structure of population 23 2.2.10 Personal income tax rate 24 CHAPTER THREE: ECONOMIC VOLATILITY AND CORPORATE INCOME TAX: DESCRIPTIVE AND DATA ANALYSIS 25 3.1 Variable measurements 25 3.1.1 Measurement of economic volatility 25 3.1.2 Measurement of corporate income tax rate 26 3.1.3 Measurement of capital openness index 26 3.2 Summary of variables description and data sources 28 3.3 Descriptive statistics 29 CHAPTER FOUR: METHODOLOGY AND RESULTS 33 4.1 Analytical framework 33 4.2 Direct effects 34 4.2.1 Model specification 34 4.2.2 Method specification 37 4.2.3 Results 38 4.2.4 Indirect effects 43 4.3.1 Model specification 43 4.3.2 Method specification 46 4.3.3 Results 48 CHAPTER FIVE: CONCLUSIONS AND IMPLICATIONS 53 5.1 Major findings 53 5.2 Policy implications 55 5.3 Limitations and suggestions for further study 56 REFERENCES 57 APPENDICES 63 A Graphs 63 B Tests 67 C Estimations 70 D Others 78 LIST OF FIGURES Figure 1.1 Average top statutory corporate income tax rate in 20 Asian countries .2 Figure 1.2 FDI inflows in 20 Asian countries Figure 2.1 Theoretical framework 15 Figure 3.1 Corporate income tax rate, capital openness index and FDI inflows (1982-2011) 33 Figure 3.2: Corporate income tax rate, Real interest, Exchange rate, Growth volatility, and FDI inflows (1982-2011) 35 Figure 4.1 Direct effect framework 39 Figure 4.3 Method for Direct effect model 41 Figure 4.2 Indirect effect framework .49 Figure 4.4 Method for Indirect effect model 52 LIST OF TABLES Table 3.1 Variables description and data sources 29 Table 3.2 Descriptive statistics 31 Table 4.1: List of variables in direct effect model 38 Table 4.2: Direct approach in various methods with interest rate volatility 43 Table 4.3: GMM estimation with and without volatility in three proxies .47 Table 4.4: List of variables in indirect effect model 48 Table 4.5: Indirect approach with interest rate volatility through various estimators 53 CHAPTER ONE: INTRODUCTION 1.1 Problem statement Taxation is the major source of government revenues for funding public expenditure, such as infrastructure, education, public health, and other social investment programs Governments adjusted their taxation policies to facilitate economic growth (Barro, 1991; Bleaney, Gemmell, and Kneller, 2001) On the purpose of providing an economic environment to foster economic growth, corporate income tax plays a crucial role in the taxation system, especially an important part in tax reform (Arnold et al., 2011) Corporate income tax serves the economy with three vital functions Firstly, the corporate income tax rate is regarded as an effective way to raise tax revenues Secondly, corporate income tax is popularly perceived as fair charges for public goods and services consumed by companies Lastly, corporate income tax is considered as a reasonable substitute for personal income tax Because it is hard to administer personal tax on capital income, especially the gains which are retained in a company (Bird, 1996; Devereux and Sørensen, 2006) In high tax rate countries, governments have to allow some profit shifting because of tax competition from lower tax rate countries (Becker and Fuest, 2012) Therefore, governments also restrain that process by competing in reducing the effective average tax rate and statutory tax rate (Devereux, Lockwood, and Redoano, 2008) During the period from the 1980s to the late 1990s, the average corporation tax rate decreased from nearly 40% to around 30%, specifically, in the European countries from 38% in 1990 to 33% in 2000 (De Mooij and Ederveen, 2003; Devereux et al., 2008) Figure 1.1 presents the dramatic downturn of average top statutory tax rate on corporate income of 20 Asian countries from more than 40% in 1982 to approximated 25% in 2011 Different from European countries, Asian countries decrease their statutory corporate income tax rate roughly after 2007 The highest rate of statutory corporate income tax is 60% in Pakistan in 1989 whereas the lowest one is 12% in Macau from 2005 to 2011 In 2011, policy makers in Pakistan reduce this variable to 35%, nearly 50% reduction This may imply a serious competition on corporate income tax rate between these countries for recent three decades (Devereux et al., 2008) Corporate tax rate (%) 40 35 30 25 1980 1985 1990 1995 Year 2000 2005 2010 Source: Author’s collected dataset Figure 1.1 Average top statutory corporate income tax rate in 20 Asian countries In order to attract more capital inflows, governments compete each other by reducing corporate income tax rate (Genschel and Schwarz, 2011), because a corporate income tax rate rise conducts to a decline in multinational investment (Hong and Smart, 2010) As illustrated in Figure 1.2, the inward FDI volume is increasing sharply and significantly From the roughly zero initial level in 1982, FDI inflows increase approximately to the landmark of 200 billion US dollars in 2011 Despite the crises in 1997 and 2008, this tendency still continues over time The combination of downward trend in corporate income tax rates and upward tendency in capital inflows illustrates the tax competition among countries for the purpose of capital attractiveness 200 150 100 50 1980 1985 1990 1995 Year 2000 2005 2010 Source: UNCTAD (2014) Figure 1.2 FDI inflows in 20 Asian countries From another point of view, economic volatility is believed as a determinant of tax reform (Feldstein, 1976) It is considered as disincentive for investments because it distorts the location decision for investments to other stable economy instead of the volatile one In order to stimulate FDI inflows, the corporate income tax rates have to be kept at a sufficient low level in order to reduce costs of capital and enhance investment incentives (Panteghini and Schjelderup, 2006) Consequently, the corporate income tax setting process is influenced by economic volatility (Ghinamo, Panteghini, and Revelli, 2010) An enormous number of researches study tax competition among jurisdictions However, there is a lack of study investigating the tax competition under the impact of economic volatility This subject is examined in the theoretical study of Panteghini and Schjelderup (2006), and the empirical studies of Slemrod (2004) as well as Ghinamo et al (2010) These studies contribute to the theoretical framework of timing choices in the investment decisions of multinational enterprises This framework is regarded as the plausible explanation for the corporate income tax rate setting process under the influence of economic volatility Moreover, these studies also involve the effect of globalization on the relationship between corporate income tax rate and economic volatility Besides, the framework of timing choices in the investment decisions of multinational enterprises is employed to illustrate the mechanism of capital mobility Under the motivation from the works of Panteghini and Schjelderup (2006) and Ghinamo et al (2010), this research investigates the relationship of the top statutory tax rates on corporate income and economic volatility in terms of real interest rate, nominal exchange rate, and GDP growth rate This relationship is also examined with consideration of influences from globalization in terms of FDI flows and capital market openness The highlight of the paper is that the lag effects of public policies and investment decisions are taken into account 1.2 Research objectives and research questions This study aims to investigate the corporate income tax rate setting process in scope of 20 Asian countries from 1982 to 2011 The process is examined under the impact of economic volatility in terms of real interest rate, nominal exchange rate, and growth Moreover, this impact is also assessed in the context of globalization, in particular, capital mobility in terms of FDI inflows into the country Based on these objectives, the goals of the study are to answer the following questions: - Does economic volatility, in terms of real interest rate, nominal exchange rate, and growth, affect corporate income tax rates? - How is the influence of FDI inflows on the relationship between economic volatility and corporate income tax rates? o Does economic volatility affect FDI inflows? o How FDI inflows influence corporate income tax rates and vice versa? A.5 rate Correlation between corporate income tax rate and employment 48 46 Employment rate (%) Corporate tax rate (%) 40 35 30 44 42 25 1980 1990 2000 2010 Year Corporate tax rate A.6 Employment rate Correlation between FDI inflows and lagged GDP 11 13 10 Lagged GDP FDI inflows 12.5 12 11.5 11 1980 1990 2000 Year FDI inflows Lagged GDP 65 2010 A.7 Correlation between FDI inflows and government expenditure 11 Governement expenditure (%) 18 FDI inflows 10 17 16 15 14 1980 1990 2000 2010 Year FDI inflows Governement expenditure 66 B Tests B.1 Test for multicollinearity Collinearity Diagnostics SQRT RVariable VIF VIF Tolerance Squared -Ctax 3.83 1.96 0.2610 0.7390 Ptax 3.69 1.92 0.2708 0.7292 IntRateSd 2.62 1.62 0.3816 0.6184 GrowthSd 1.97 1.40 0.5069 0.4931 XRateSd 2.35 1.53 0.4253 0.5747 GDPpwgr 1.21 1.10 0.8239 0.1761 CapO 2.50 1.58 0.3998 0.6002 old 5.48 2.34 0.1826 0.8174 young 7.41 2.72 0.1350 0.8650 EmpRate 3.99 2.00 0.2505 0.7495 FDIi 12.79 3.58 0.0782 0.9218 FDIo 13.16 3.63 0.0760 0.9240 GovExp 2.66 1.63 0.3759 0.6241 lGDP 6.49 2.55 0.1540 0.8460 -Mean VIF 5.01 Cond Eigenval Index 4.5138 1.0000 2.7084 1.2910 1.8912 1.5449 1.3415 1.8343 1.0074 2.1168 0.7451 2.4612 0.4738 3.0865 0.3980 3.3679 0.3140 3.7916 10 0.2206 4.5235 11 0.1738 5.0967 12 0.1040 6.5873 13 0.0645 8.3662 14 0.0440 10.1334 Condition Number 10.1334 Eigenvalues and Cond Index computed from deviation sscp (no intercept) Det(correlation matrix) 0.0000 B.2 Test CtaxL1: predetermined in direct effect model B.2.1 Test with lags from the first level as instruments Tests of endogeneity of: CtaxL1 H0: Regressor is exogenous Wu-Hausman F test: Durbin-Wu-Hausman chi-sq test: 2.95103 3.05415 67 F(1,256) Chi-sq(1) P-value = 0.08703 P-value = 0.08053 B.2.2 Test with lags from the second level as instruments Tests of endogeneity of: CtaxL1 H0: Regressor is exogenous Wu-Hausman F test: Durbin-Wu-Hausman chi-sq test: B.3 1.96159 2.03792 F(1,256) Chi-sq(1) P-value = 0.16255 P-value = 0.15342 Wooldridge test for autocorrelation in direct effect model H0: no first-order autocorrelation F( 1, 14) = 30.381 Prob > F = 0.0001 B.4 - Durbin-Wu-Hausman endogeneity test in direct effect model In case of interest rate volatility Tests of endogeneity of: Ptax H0: Regressor is exogenous Wu-Hausman F test: Durbin-Wu-Hausman chi-sq test: - F(1,274) Chi-sq(1) P-value = 0.09222 P-value = 0.08590 9.61830 9.69451 F(1,291) Chi-sq(1) P-value = 0.00212 P-value = 0.00185 9.19615 9.28204 F(1,291) Chi-sq(1) P-value = 0.00264 P-value = 0.00231 In case of exchange rate volatility Tests of endogeneity of: CtaxL1 H0: Regressor is exogenous Wu-Hausman F test: Durbin-Wu-Hausman chi-sq test: - 2.85519 2.94950 In case of growth volatility Tests of endogeneity of: CtaxL1 H0: Regressor is exogenous Wu-Hausman F test: Durbin-Wu-Hausman chi-sq test: B.5 Test for omission in direct effect model H0: no omitted variables F( 3, 301) = Prob > F = F( 30, 274) = Prob > F = B.6 2.13 0.0968 1.89 0.0044 Pagan and Hall's test of heteroskedasticity in direct effect model IV heteroskedasticity test(s) using levels of IVs only Ho: Disturbance is homoskedastic Pagan-Hall general test statistic : 21.460 Chi-sq(13) P-value = 0.0643 B.7 Test for additional endogenous variables – Indirect effect model B.7.1 The Tax rate equation Regressors tested: CtaxL1 Ptax Tests of endogeneity of: CtaxL1 H0: Regressor is exogenous Wu-Hausman F test: Durbin-Wu-Hausman chi-sq test: Tests of endogeneity of: Ptax H0: Regressor is exogenous Wu-Hausman F test: Durbin-Wu-Hausman chi-sq test: 3.26806 3.36184 F(1,301) Chi-sq(1) P-value = 0.07164 P-value = 0.06672 6.94902 7.06300 F(1,301) Chi-sq(1) P-value = 0.00882 P-value = 0.00787 68 B.7.2 The Tax base equation Regressors tested: CtaxL1 lGDPL1 Tests of endogeneity of: CtaxL1 H0: Regressor is exogenous Wu-Hausman F test: Durbin-Wu-Hausman chi-sq test: Tests of endogeneity of: lGDPL1 H0: Regressor is exogenous Wu-Hausman F test: Durbin-Wu-Hausman chi-sq test: B.8 16.42246 15.92388 F(1,261) Chi-sq(1) P-value = 0.00007 P-value = 0.00007 9.83286 9.76632 F(1,261) Chi-sq(1) P-value = 0.00191 P-value = 0.00178 Breusch-Pagan test of independence of equations in system Ho: independence of residuals Correlation matrix of residuals: Ctax FDIi Ctax 1.0000 FDIi -0.6886 1.0000 Breusch-Pagan test of independence: chi2(1) = B.9 140.339, Pr = 0.0000 Check identification status of simultaneous equations system Endogenous coefficients matrix Ctax FDIi Ctax -1 FDIi -1 Exogenous coefficients matrix FDIiL1 GDPpwgrL1 Ctax FDIi FDIoL1 lGDPL1 EmpRateL1 GovExp young old Ptax CapO CtaxL1 IntRateSdL1 5 5 5 5 0 5 0 5 Eq is identified Eq is identified System is identified B.10 Heteroskedasticity test in system of equations ================================================= * System Heteroscedasticity Tests (3sls) ================================================= *** Single Equation Heteroscedasticity Tests: Ho: Homoscedasticity - Ha: Heteroscedasticity Eq Ctax : Engle LM ARCH Test: E2 = E2_1 = 0.2476 P-Value > Chi2(1) 0.6187 Eq Ctax : Hall-Pagan LM Test: E2 = Yh = 22.9500 P-Value > Chi2(1) 0.0000 Eq Ctax : Hall-Pagan LM Test: E2 = Yh2 = 28.2831 P-Value > Chi2(1) 0.0000 Eq Ctax : Hall-Pagan LM Test: E2 = LYh2 = 16.7281 P-Value > Chi2(1) 0.0000 -Eq FDIi: Engle LM ARCH Test: E2 = E2_1 =187.1776 P-Value > Chi2(1) 0.0000 Eq FDIi: Hall-Pagan LM Test: E2 = Yh = 4.5096 P-Value > Chi2(1) 0.0337 Eq FDIi: Hall-Pagan LM Test: E2 = Yh2 = 4.3032 P-Value > Chi2(1) 0.0380 Eq FDIi: Hall-Pagan LM Test: E2 = LYh2 = 4.9856 P-Value > Chi2(1) 0.0256 -*** Overall System Heteroscedasticity Tests: Ho: No Overall System Heteroscedasticity - Breusch-Pagan LM Test - Likelihood Ratio LR Test - Wald Test = 132.6629 = 179.7786 = 213.7072 P-Value > Chi2(1) P-Value > Chi2(1) P-Value > Chi2(1) 69 0.0000 0.0000 0.0000 C Estimations C.1 Direct effect model – OLS (with Interest rate volativity) Source | SS df MS Number of obs = 315 -+ -F( 10, 304) = 408.68 Model | 16992.2102 10 1699.22102 Prob > F = 0.0000 Residual | 1263.98174 304 4.15783466 R-squared = 0.9308 -+ -Adj R-squared = 0.9285 Total | 18256.192 314 58.1407388 Root MSE = 2.0391 -Ctax | Coef Std Err t P>|t| [95% Conf Interval] -+ -CtaxL1 | 883046 0245405 35.98 0.000 8347553 9313367 lGDPL1 | 1910153 1165435 1.64 0.102 -.0383187 4203493 EmpRateL1 | -1.630919 2.511095 -0.65 0.517 -6.572247 3.310409 GDPpwgrL1 | -2.164827 2.476528 -0.87 0.383 -7.038133 2.70848 GovExp | -2.497422 3.047209 -0.82 0.413 -8.493714 3.49887 young | 0803618 0375002 2.14 0.033 0065689 1541546 old | 114134 0665301 1.72 0.087 -.0167838 2450519 Ptax | 0487223 0142795 3.41 0.001 0206232 0768214 CapO | 0758662 1136995 0.67 0.505 -.1478715 2996039 IntRateSdL1 | -.0152985 0581018 -0.26 0.792 -.1296312 0990342 _cons | -2.674533 2.077506 -1.29 0.199 -6.762647 1.41358 C.2 Direct effect model – FE (with Interest rate volatility) Fixed-effects (within) regression Group variable: ctrycode R-sq: within = 0.7935 between = 0.8512 overall = 0.8355 Number of obs = 315 Number of groups = 16 Obs per group: = avg = 19.7 max = 29 F(10,289) = 111.03 corr(u_i, Xb) = 0.4454 Prob > F = 0.0000 -Ctax | Coef Std Err t P>|t| [95% Conf Interval] -+ -CtaxL1 | 7888583 0350382 22.51 0.000 719896 8578207 lGDPL1 | -1.329433 8956689 -1.48 0.139 -3.092295 433428 EmpRateL1 | 9289452 7.657126 0.12 0.904 -14.14186 15.99975 GDPpwgrL1 | -1.743445 2.625724 -0.66 0.507 -6.911412 3.424523 GovExp | -4.944103 4.71024 -1.05 0.295 -14.21483 4.326621 young | 019964 0984348 0.20 0.839 -.173776 213704 old | 0367209 1093838 0.34 0.737 -.1785691 2520109 Ptax | 0287415 0250938 1.15 0.253 -.0206482 0781312 CapO | 0813527 2849503 0.29 0.775 -.4794884 6421937 IntRateSdL1 | 0271435 068401 0.40 0.692 -.1074838 1617708 _cons | 22.1711 13.60929 1.63 0.104 -4.614803 48.957 -+ -sigma_u | 2.9951358 sigma_e | 2.0219797 rho | 68693417 (fraction of variance due to u_i) -F test that all u_i=0: F(15, 289) = 1.34 Prob > F = 0.1749 70 C.3 Direct effect model – 2SLS (with Interest rate volatility) IV (2SLS) estimation -Estimates efficient for homoskedasticity only Statistics consistent for homoskedasticity only Number of obs = 286 F( 10, 275) = 311.14 Prob > F = 0.0000 Total (centered) SS = 15051.8048 Centered R2 = 0.9190 Total (uncentered) SS = 303647.1531 Uncentered R2 = 0.9960 Residual SS = 1219.868314 Root MSE = 2.065 -Ctax | Coef Std Err z P>|z| [95% Conf Interval] -+ -Ptax | 0436812 0214055 2.04 0.041 0017273 0856352 CtaxL1 | 8643101 0311314 27.76 0.000 8032937 9253266 lGDPL1 | 2821285 1370928 2.06 0.040 0134316 5508255 EmpRateL1 | -2.553544 2.952053 -0.87 0.387 -8.339461 3.232374 GDPpwgrL1 | -2.968937 2.795213 -1.06 0.288 -8.447453 2.509579 GovExp | -1.102454 3.261643 -0.34 0.735 -7.495156 5.290248 young | 0879384 0426142 2.06 0.039 0044162 1714607 old | 1289833 0770393 1.67 0.094 -.022011 2799777 CapO | 0765184 1314753 0.58 0.561 -.1811684 3342052 IntRateSdL1 | -.0352557 0638703 -0.55 0.581 -.1604392 0899278 _cons | -3.135623 2.191338 -1.43 0.152 -7.430566 1.15932 -Underidentification test (Anderson canon corr LM statistic): 202.506 Chi-sq(4) P-val = 0.0000 -Weak identification test (Cragg-Donald Wald F statistic): 164.928 Stock-Yogo weak ID test critical values: 5% maximal IV relative bias 16.85 10% maximal IV relative bias 10.27 20% maximal IV relative bias 6.71 30% maximal IV relative bias 5.34 10% maximal IV size 24.58 15% maximal IV size 13.96 20% maximal IV size 10.26 25% maximal IV size 8.31 Source: Stock-Yogo (2005) Reproduced by permission -Sargan statistic (overidentification test of all instruments): 6.117 Chi-sq(3) P-val = 0.1061 -endog- option: Endogeneity test of endogenous regressors: 2.949 Chi-sq(1) P-val = 0.0859 Regressors tested: Ptax -Instrumented: Ptax Included instruments: CtaxL1 lGDPL1 EmpRateL1 GDPpwgrL1 GovExp young old CapO IntRateSdL1 Excluded instruments: PtaxL2 PtaxL3 PtaxL4 PtaxL5 71 C.4 Direct effect model – GMM (with Interest rate volatility) Dynamic panel-data estimation, two-step system GMM -Group variable: ctrycode Number of obs = 315 Time variable : year Number of groups = 16 Number of instruments = 17 Obs per group: = Wald chi2(10) = 1.25e+06 avg = 19.69 Prob > chi2 = 0.000 max = 29 -Ctax | Coef Std Err z P>|z| [95% Conf Interval] -+ -CtaxL1 | 7952866 0358095 22.21 0.000 7251012 8654719 lGDPL1 | 4237358 0965115 4.39 0.000 2345768 6128949 EmpRateL1 | -3.493477 2.524866 -1.38 0.166 -8.442123 1.455169 GDPpwgrL1 | -9.749523 13.05663 -0.75 0.455 -35.34006 15.84101 GovExp | 5.329695 3.208043 1.66 0.097 -.9579537 11.61734 young | 1032057 0571847 1.80 0.071 -.0088743 2152857 old | 1329421 1423139 0.93 0.350 -.145988 4118722 Ptax | 0211978 0298259 0.71 0.477 -.0372598 0796555 CapO | -.0559819 1206688 -0.46 0.643 -.2924884 1805245 IntRateSdL1 | -.1268227 0579345 -2.19 0.029 -.2403721 -.0132732 _cons | -2.479149 1.93598 -1.28 0.200 -6.2736 1.315301 -Warning: Uncorrected two-step standard errors are unreliable Instruments for first differences equation Standard D.(CtaxL1 IntRateSdL1 lGDPL1 EmpRateL1 GDPpwgrL1 GovExp young old CapO) GMM-type (missing=0, separate instruments for each period unless collapsed) L(7/12).L.Ptax collapsed Instruments for levels equation Standard CtaxL1 IntRateSdL1 lGDPL1 EmpRateL1 GDPpwgrL1 GovExp young old CapO _cons GMM-type (missing=0, separate instruments for each period unless collapsed) DL6.L.Ptax collapsed -Arellano-Bond test for AR(1) in first differences: z = -2.51 Pr > z = 0.012 Arellano-Bond test for AR(2) in first differences: z = 1.23 Pr > z = 0.218 -Sargan test of overid restrictions: chi2(6) = 11.58 Prob > chi2 = 0.072 (Not robust, but not weakened by many instruments.) Hansen test of overid restrictions: chi2(6) = 5.37 Prob > chi2 = 0.498 (Robust, but weakened by many instruments.) Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(5) = 4.58 Prob > chi2 = Difference (null H = exogenous): chi2(1) = 0.78 Prob > chi2 = 72 0.469 0.376 C.5 Direct effect model – GMM (with Exchange rate volatility) Dynamic panel-data estimation, two-step system GMM -Group variable: ctrycode Number of obs = 380 Time variable : year Number of groups = 16 Number of instruments = 16 Obs per group: = Wald chi2(10) = 18827.18 avg = 23.75 Prob > chi2 = 0.000 max = 29 -Ctax | Coef Std Err z P>|z| [95% Conf Interval] -+ -CtaxL1 | 7805132 0713569 10.94 0.000 6406563 9203701 lGDPL1 | 4279129 1587338 2.70 0.007 1168004 7390254 EmpRateL1 | -7.291657 4.299 -1.70 0.090 -15.71754 1.134228 GDPpwgrL1 | -2.724441 6867101 -3.97 0.000 -4.070368 -1.378514 GovExp | 3.287593 4.105956 0.80 0.423 -4.759933 11.33512 young | 1025122 0319264 3.21 0.001 0399376 1650868 old | 1859541 0571761 3.25 0.001 073891 2980171 Ptax | 0558514 0274115 2.04 0.042 0021259 1095769 CapO | -.0156516 1250899 -0.13 0.900 -.2608233 2295201 XRateSd | -1.527135 4884658 -3.13 0.002 -2.484511 -.5697598 _cons | -2.140697 2.129459 -1.01 0.315 -6.314359 2.032966 -Warning: Uncorrected two-step standard errors are unreliable Instruments for first differences equation Standard D.(Ptax L.XRateSd lGDPL1 EmpRateL1 GDPpwgrL1 GovExp young old CapO) GMM-type (missing=0, separate instruments for each period unless collapsed) L(7/11).L.CtaxL1 collapsed Instruments for levels equation Standard Ptax L.XRateSd lGDPL1 EmpRateL1 GDPpwgrL1 GovExp young old CapO _cons GMM-type (missing=0, separate instruments for each period unless collapsed) DL6.L.CtaxL1 collapsed -Arellano-Bond test for AR(1) in first differences: z = -2.32 Pr > z = 0.020 Arellano-Bond test for AR(2) in first differences: z = 0.74 Pr > z = 0.462 -Sargan test of overid restrictions: chi2(5) = 19.30 Prob > chi2 = 0.002 (Not robust, but not weakened by many instruments.) Hansen test of overid restrictions: chi2(5) = 8.88 Prob > chi2 = 0.114 (Robust, but weakened by many instruments.) Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(4) = 4.21 Prob > chi2 = Difference (null H = exogenous): chi2(1) = 4.67 Prob > chi2 = 73 0.378 0.031 C.6 Direct effect model – GMM (with Growth volatility) Dynamic panel-data estimation, two-step system GMM -Group variable: ctrycode Number of obs = 380 Time variable : year Number of groups = 16 Number of instruments = 15 Obs per group: = Wald chi2(10) = 71882.95 avg = 23.75 Prob > chi2 = 0.000 max = 29 -Ctax | Coef Std Err z P>|z| [95% Conf Interval] -+ -CtaxL1 | 7496297 0592886 12.64 0.000 6334262 8658332 lGDPL1 | 3767347 110109 3.42 0.001 1609251 5925443 EmpRateL1 | -8.186378 3.233842 -2.53 0.011 -14.52459 -1.848164 GDPpwgrL1 | -2.901682 1.0069 -2.88 0.004 -4.87517 -.9281942 GovExp | 6.152824 3.638706 1.69 0.091 -.9789087 13.28456 young | 1190892 0269196 4.42 0.000 0663277 1718507 old | 2072717 0566423 3.66 0.000 0962549 3182885 Ptax | 0706719 0206675 3.42 0.001 0301643 1111795 CapO | 1167801 1068529 1.09 0.274 -.0926479 326208 GrowthSdL1 | -1.256471 4.64299 -0.27 0.787 -10.35656 7.843623 _cons | -1.715862 1.291157 -1.33 0.184 -4.246484 8147592 -Warning: Uncorrected two-step standard errors are unreliable Instruments for first differences equation Standard D.(Ptax L.GrowthSd lGDPL1 EmpRateL1 GDPpwgrL1 GovExp young old CapO) GMM-type (missing=0, separate instruments for each period unless collapsed) L(9/12).L.CtaxL1 collapsed Instruments for levels equation Standard Ptax L.GrowthSd lGDPL1 EmpRateL1 GDPpwgrL1 GovExp young old CapO _cons GMM-type (missing=0, separate instruments for each period unless collapsed) DL8.L.CtaxL1 collapsed -Arellano-Bond test for AR(1) in first differences: z = -2.30 Pr > z = 0.022 Arellano-Bond test for AR(2) in first differences: z = 0.66 Pr > z = 0.509 -Sargan test of overid restrictions: chi2(4) = 15.59 Prob > chi2 = 0.004 (Not robust, but not weakened by many instruments.) Hansen test of overid restrictions: chi2(4) = 4.12 Prob > chi2 = 0.389 (Robust, but weakened by many instruments.) Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(3) = 3.84 Prob > chi2 = Difference (null H = exogenous): chi2(1) = 0.29 Prob > chi2 = 74 0.279 0.593 C.7 Indirect effect model – OSL Multivariate regression -Equation Obs Parms RMSE "R-sq" F-Stat P -Ctax 296 10 1.927154 0.9409 453.90 0.0000 FDIi 296 8845929 0.7694 160.71 0.0000 -| Coef Std Err t P>|t| [95% Conf Interval] -+ -Ctax | CtaxL1 | 8533126 0272975 31.26 0.000 7996974 9069278 FDIiL1 | -.4731904 2109434 -2.24 0.025 -.8875056 -.0588753 FDIoL1 | 0960274 1308087 0.73 0.463 -.1608947 3529495 lGDPL1 | 3083794 1854374 1.66 0.097 -.0558393 6725981 EmpRateL1 | 1.060753 2.615571 0.41 0.685 -4.076506 6.198011 GovExp | -3.228328 3.196006 -1.01 0.313 -9.505622 3.048965 young | 0701149 036341 1.93 0.054 -.0012627 1414924 old | 1270081 0661433 1.92 0.055 -.0029043 2569204 Ptax | 0337749 0190488 1.77 0.077 -.003639 0711887 CapO | 0448794 123064 0.36 0.715 -.1968314 2865901 _cons | 235942 2.3395 0.10 0.920 -4.359083 4.830967 -+ -FDIi | CtaxL1 | -.1665837 0076326 -21.83 0.000 -.1815749 -.1515926 IntRateSdL1 | -.0362365 0291691 -1.24 0.215 -.0935277 0210548 lGDPL1 | 8616075 0419598 20.53 0.000 7791939 944021 GDPpwgrL1 | -.462472 1.053662 -0.44 0.661 -2.531975 1.607031 GovExp | -1.714997 1.14966 -1.49 0.136 -3.973051 5430574 CapO | 38967 0377418 10.32 0.000 3155411 4637988 _cons | 4.527488 5336791 8.48 0.000 3.479286 5.57569 C.8 Indirect effect model – 2SLS Two-stage least-squares regression -Equation Obs Parms RMSE "R-sq" F-Stat P -Ctax 280 10 1.938158 0.9380 392.16 0.0000 FDIi 280 8491433 0.7722 160.66 0.0000 -| Coef Std Err t P>|t| [95% Conf Interval] -+ -Ctax | CtaxL1 | 8479863 0336956 25.17 0.000 7817963 9141764 FDIiL1 | -.8722989 2384364 -3.66 0.000 -1.340672 -.4039262 FDIoL1 | 2330581 1367212 1.70 0.089 -.0355102 5016263 lGDPL1 | 4008762 2145247 1.87 0.062 -.0205256 822278 EmpRateL1 | -1.191622 2.982979 -0.40 0.690 -7.051237 4.667994 GovExp | 4.414038 3.540486 1.25 0.213 -2.540718 11.36879 young | -.0128191 0394076 -0.33 0.745 -.0902294 0645913 old | 0360196 0706868 0.51 0.611 -.102834 1748732 Ptax | -.0142333 0246458 -0.58 0.564 -.0626462 0341796 CapO | 0562667 1296473 0.43 0.664 -.198406 3109394 _cons | 6.510328 2.469856 2.64 0.009 1.658666 11.36199 -+ -FDIi | CtaxL1 | -.1861165 0081197 -22.92 0.000 -.2020664 -.1701667 IntRateSdL1 | -.06062 028619 -2.12 0.035 -.1168377 -.0044023 lGDPL1 | 9355133 0444272 21.06 0.000 8482427 1.022784 GDPpwgrL1 | -1.956076 1.046732 -1.87 0.062 -4.012225 1000729 GovExp | -.4938249 1.191911 -0.41 0.679 -2.835157 1.847507 75 CapO | 4012794 0372813 10.76 0.000 3280459 4745128 _cons | 4.127558 5404143 7.64 0.000 3.065995 5.189121 -Endogenous variables: Ctax FDIi Ptax CtaxL1 lGDPL1 Exogenous variables: FDIiL1 FDIoL1 EmpRateL1 GovExp young old CapO IntRateSdL1 GDPpwgrL1 PtaxL2 PtaxL3 CtaxL2 CtaxL3 lGDPL2 lGDPL3 C.9 Indirect effect model – SURE Seemingly unrelated regression, iterated -Equation Obs Parms RMSE "R-sq" chi2 P -Ctax 296 10 2.584672 0.8896 2554.57 0.0000 FDIi 296 8744838 0.7692 963.51 0.0000 | Coef Std Err z P>|z| [95% Conf Interval] -+ -Ctax | CtaxL1 | 1.187975 030987 38.34 0.000 1.127242 1.248708 FDIiL1 | 1.488762 2091779 7.12 0.000 1.07878 1.898743 FDIoL1 | 1100038 1300182 0.85 0.398 -.1448272 3648348 lGDPL1 | -1.394302 2021532 -6.90 0.000 -1.790515 -.9980891 EmpRateL1 | 1.803943 2.593351 0.70 0.487 -3.278932 6.886818 GovExp | 1.422211 3.903536 0.36 0.716 -6.228578 9.073001 young | 0629496 0365067 1.72 0.085 -.0086022 1345014 old | 0965097 0663641 1.45 0.146 -.0335614 2265809 Ptax | 0274166 0188833 1.45 0.147 -.0095939 0644272 CapO | -.7323804 1447463 -5.06 0.000 -1.016078 -.4486828 _cons | -8.271027 2.541237 -3.25 0.001 -13.25176 -3.290294 -+ -FDIi | CtaxL1 | -.1662216 0075164 -22.11 0.000 -.1809534 -.1514898 IntRateSdL1 | -.0246167 0217572 -1.13 0.258 -.06726 0180266 lGDPL1 | 866527 0414863 20.89 0.000 7852153 9478387 GDPpwgrL1 | -.7181225 7760452 -0.93 0.355 -2.239143 8028982 GovExp | -1.767306 1.133566 -1.56 0.119 -3.989055 4544432 CapO | 3916312 0376627 10.40 0.000 3178136 4654488 _cons | 4.439021 515856 8.61 0.000 3.427962 5.45008 76 C.10 Indirect effect model – 3SLS Three-stage least-squares regression, iterated -Equation Obs Parms RMSE "R-sq" chi2 P -Ctax 280 10 2.585839 0.8852 2217.57 0.0000 FDIi 280 8382533 0.7723 966.19 0.0000 -| Coef Std Err z P>|z| [95% Conf Interval] -+ -Ctax | CtaxL1 | 1.228051 0372828 32.94 0.000 1.154978 1.301124 FDIiL1 | 1.139404 2360219 4.83 0.000 6768091 1.601998 FDIoL1 | 2786372 1357284 2.05 0.040 0126144 54466 lGDPL1 | -1.503552 2316961 -6.49 0.000 -1.957668 -1.049436 EmpRateL1 | -.842022 2.947621 -0.29 0.775 -6.619253 4.935209 GovExp | 7.877459 4.270956 1.84 0.065 -.493462 16.24838 young | -.018633 039282 -0.47 0.635 -.0956244 0583583 old | -.0142819 0706988 -0.20 0.840 -.1528489 1242851 Ptax | -.0179197 0243698 -0.74 0.462 -.0656837 0298443 CapO | -.7483586 1516204 -4.94 0.000 -1.045529 -.4511881 _cons | -1.256429 2.671283 -0.47 0.638 -6.492048 3.97919 -+ -FDIi | CtaxL1 | -.1851936 0079776 -23.21 0.000 -.2008295 -.1695578 IntRateSdL1 | -.0495602 0214538 -2.31 0.021 -.091609 -.0075114 lGDPL1 | 9375998 0438997 21.36 0.000 8515579 1.023642 GDPpwgrL1 | -1.722088 7760086 -2.22 0.026 -3.243037 -.2011391 GovExp | -.6280747 1.171622 -0.54 0.592 -2.924411 1.668261 CapO | 4023173 0372035 10.81 0.000 3293999 4752348 _cons | 4.056268 5232936 7.75 0.000 3.030631 5.081904 -Endogenous variables: Ctax FDIi Ptax CtaxL1 lGDPL1 Exogenous variables: FDIiL1 FDIoL1 EmpRateL1 GovExp young old CapO IntRateSdL1 GDPpwgrL1 PtaxL2 PtaxL3 CtaxL2 CtaxL3 lGDPL2 lGDPL3 77 D Others D.1 Details of data sources No Variable Corporate income tax rate 10 11 12 Volatility in GDP growth rate Volatility in real interest rate Volatility in exchange rate Country size Capital openness index Government expenditure Productivity Employment rate Old Young Personal income tax rate 13 FDI inflows 14 FDI outflows Notation Ctax Data source World Tax Database KPMG Trading Economics GrowthSd Penn World Tables (PWT) IntRateSd World Development Indicators (WDI) XRateSd World Development Indicators (WDI) GDP Penn World Tables (PWT) CapO Chinn and Ito KAOPEN GovExp Penn World Tables (PWT) GDPpwgr Calculated from Penn World Tables (PWT) EmpRate Penn World Tables (PWT) old World Development Indicators (WDI) young World Development Indicators (WDI) Ptax World Tax Database World Tax Indicators KPMG Trading Economics FDIi UNCTAD, Data Center FDIo UNCTAD, Data Center 78 Link http://www.bus.umich.edu/ http://www.kpmg.com http://www.tradingeconomics.com https://pwt.sas.upenn.edu/ http://data.worldbank.org http://data.worldbank.org https://pwt.sas.upenn.edu/ http://web.pdx.edu/~ito/Chinn-Ito_website.htm https://pwt.sas.upenn.edu/ https://pwt.sas.upenn.edu/ https://pwt.sas.upenn.edu/ http://data.worldbank.org http://data.worldbank.org http://www.bus.umich.edu/ http://icepp.gsu.edu/world-tax-indicators http://www.kpmg.com http://www.tradingeconomics.com http://unctadstat.unctad.org http://unctadstat.unctad.org D.2 List of measurements for economic volatility The wide variety of general types of measurements for economic volatility, which have been applied in several studies is presented as following: No 10 11 Measures of volatility Absolute value of percentage change Average absolute value of percentage change Moving average of the standard deviation of percentage change Standard deviation from a trend equation Standard deviation from a first-order autoregressive equation Long-run volatility as V and U measures from Perée and Steinherr (1989)’s models Residuals from ARIMA model Conditional variance from ARCH, GARCH, GARCH-M, SWARCH models Variance from Linear moment models Variance around trend predicted from (lnVt = β + β1t + β2t2 + εt, where t presents for time period) Non-parametric techniques Source: McKenzie (1999), (Ćorić and Pugh (2010)) and author’s compilation D.3 List of Asian countries in the dataset Bangladesh, Brunei, Cambodia, China, Hong Kong, India, Indonesia, Japan, Korea, Republic of, Lao People's Democratic Republic, Macau, Malaysia, Myanmar, Pakistan, Philippines, Singapore, Sri Lanka, Taiwan, Thailand, Vietnam 79 ... JANUARY 201 5 ABSTRACT This paper examines the impact of economic volatility on the corporate income tax rate in the context of globalization and international taxation competition The impact is... al., 201 0; Oates, 1972) 2.2.10 Personal income tax rate Rosen (200 4) used the concept of double taxation to illustrate the tendency of taxation reaction Virtually, the corporate incomes are taxed... Devereux et al (200 2) classified the measurements of the corporate income tax rate into two groups of corporate income taxes The first group of measures bases on tax legislation, consisting of effective