Ministry of Education and Training University of Economics Ho Chi Minh City ******** Research Topic CORRUPTION AND DETERMINANTS OF FISCAL DEFICITS IN ASIA PACIFIC COUNTRIES Contributor Nguyen Phuc Canh Ho Chi Minh City, Aug/2017 i Ministry of Education and Training University of Economics Ho Chi Minh City ******** Research Topic CORRUPTION AND DETERMINANTS OF FISCAL DEFICITS IN ASIA PACIFIC COUNTRIES Ref code: CS – 2017 - 17 Contributor Nguyen Phuc Canh Ho Chi Minh City, Aug/2017 ii Table of content Abstract v Chapter 1: INTRODUCTION 1.1 The motivations of the study 1.2 The scope of the study 1.3 The contributions of the study 1.4 The methodology Chapter 2: LITERATURE REVIEW 2.1 The fiscal deficits and determinants 2.2 The external debt and fiscal deficits 10 2.3 The government size and fiscal deficits 12 2.4 The corruption controlling and fiscal deficits 13 2.5 The effects of corruption controlling under the constraints of external debt and government size 15 Chapter 3: METHODOLOGY AND DATA 18 3.1 Methodology 18 3.2 Data 20 Chapter 4: RESULTS AND DISCUSSIONS 23 4.1 The corruption controlling and fiscal deficits 23 4.2 The effects of corruption controlling under the constraints of external debt and government size 26 4.3 Robustness check 28 Chapter 5: SOME REMARKING CONCLUSIONS 31 Acknowledgement 32 References 33 iii Lists of Tables and Figures Tables Table Data definitions and sources 19 Table Data descriptions 20 Table Correlation matrix 22 Table The effect of Control of corruption and fiscal deficits 24 Table The effects of Control of corruption and its interactions with government expenditure and external debt on fiscal deficits 26 Table The effects of Control of corruption and its interactions with government revenue and external debt on fiscal deficits 27 Table The effects of Control of corruption on fiscal deficits in pre and post 2008 global financial crisis 28 Table The effects of Control of corruption and its interactions with government expenditure and external debt on fiscal deficits in pre and post 2008 global financial crisis 29 Figures Figure Economic growth of areas Figure Government expenditure growth rates in Asia Pacific areas Figure Primary fiscal balance in Asia Pacific countries (%/GDP) iv Abstract The fiscal policy conducting with the aim of sustainable development is under strong debate from both scholar and practice, in which the institution-based solutions for the fiscal consolidation are suggested as essential measures to complement for the ineffective of market-based solutions The study contributes to the literature and practice by emphasizing the roles of corruption controlling on fiscal deficits in the context of 26 Asia Pacific countries for the period 2002 – 2015 By recruiting the system-GMM estimators for unbalance panel data, the study finds the significant evidences that the better corruption controlling eliminates fiscal deficits Notably, the corruption controlling measures have stronger effects in low indebted countries with small government size The result has significant implications for policymakers in fiscal consolidation and sustainable policy setting Keywords: corruption, fiscal deficit, external debt, government size JEL classifications: E62, H11, H62, H63 v Chapter 1: INTRODUCTION 1.1 The motivations of the study The excessive fiscal deficits in a long-run period are considered as the fundamental problem and the cause of recent severe debt crisis such as crisis in Mexico and Argentina in 1990s, crisis in European in 2000s (Cole & Kehoe, 1996; Featherstone, 2011; Ruščáková & Semančíková, 2016) For instance, Ruščáková and Semančíková (2016) summarize that worsening values of macro fundamental variables including the fiscal deficits had predominantly significant effect on the origin of the European debt crisis beside other drivers such as high international risk, the negative impact of rescue activities, news about sovereign rating downgrades, etc However, the one of most important factor is the crisis of confidence due to the long lasting deficits in the fiscal budgets Therefore, the measures to handle the budget deficits with the aim at sustainable development are under strong attention from both scholars and policymakers In the theoretical and empirical literature of fiscal consolidation, the market-based and institution-based solutions are both examined by researchers to find the efficiency way of fighting excessive budget deficits Whereas, the market-based solutions from internal measures such as cut government spending, tax increases, stimulate economic growth to external measures of international organizations (e.g., IMF, World Bank) such as increase the borrowing interest rate, limit the ability to borrow, decrease the credit worthy ranking) are under consideration and implementation Unfortunately, the market-based solutions such as setting high interest rates for high deficit government in getting new debt to stimulate them lower the deficits are not effective Maltritz and Wüste (2015) document that European large governments such as Germany or France agreed to provide funds for troubled countries at comparably low interest rates for during the crisis with the aim at helping them out of default; thus, the market-based solution basing on the setting high interest rate is not effective in recent European debt crisis The institution-based solutions are, in turn, implied with more significant in the literature (Maltritz & Wüste, 2015), in which corruption controlling not only reduces the wasted government spending, but also stimulates the economic activities that enhances the government revenues In addition, Martinez-Vazquez et al (2007) notice that the corruption has been downplayed by many governments since it was considered as a cultural and political issues and measuring corruption was nearly impossible so that corruption controlling was hardly seen as an economic objective for development reforms However, the negative damages of corruption on the economic development, especially in poor countries, are evidenced in studies recent decade Dal Bó and Rossi (2007), for instance, find that besides other factors such as public ownership, inflation, and lack of law and order, corruption appears to play a separate and more robust role in damaging the efficiency of firms in 13 Latin American countries over the period 1994-2001 Dimakou (2015) notices that corruption constrains the fiscal capacity to tax and increases the reliance on inflation Moreover, the new dataset of institutional framework (World Governance Indicators – World Bank), which include the indicator of controlling corruption, is provided with more reliable information and better measuring method in evaluating the corruption situation (Kaufmann et al., 2007) Thus, the question about the roles of corruption in tackling the fiscal deficits has re-emphasized Apparently, Arestis (2011) notices that recent developments of “New Consensus in Macroeconomics” in macroeconomic policy have downgraded the roles of fiscal policy, but researchers and authorizers must careful consider other determinants of fiscal policy such as the institutional frameworks, debt burden, and also government size This rehighlights the interests in examining the associations of corruption controlling with other economic drivers of fiscal deficits Therefore, this study sheds lights on the effects of corruption controlling and its interactions with other aspects of fiscal policy including government size and external debt burden on fiscal deficits 1.2 The scope of the study The study goes to examine the effects of corruption controlling on fiscal deficits and its interactions with external debt and government size in the context of 26 Asia Pacific countries In which, the better corruption controlling is in line with the less corruption Therefore, in the understanding we can see the corruption and the corruption controlling have opposite meanings The 26 Asia Pacific countries, which are mainly developing and emerging countries that we exclude the advanced countries, are the fruitful sample to examine the roles of corruption controlling on fiscal deficits due to their high economic development in along with the variety of corruption situation and the structural changes in the economic development In fact, the Asia Pacific area is the one of most dynamic and highest economic growth in the period of 2000-2015 (see Fig 1) The real GDP growth rate of this area is average higher than US, OECD, and European countries While, its growth rate is less impacted in the 2008 global financial crisis 26 Asia Pacific countries in this study including: Afghanistan, Armenia, Azerbaijan, Bangladesh, Bhutan, China, Fiji, Georgia, India, Indonesia, Kyrgyz Republic, Lao People's Democratic Republic, Malaysia, Maldives, Mongolia, Nepal, Philippines, Papua New Guinea, Samoa, Solomon Islands, Sri Lanka, Tajikistan, Thailand, Tonga, Vanuatu, Vietnam Economic growth (annual, %) 14.0 12.0 10.0 8.0 6.0 4.0 2.0 0.0 -2.0 -4.0 -6.0 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 East Asia & Pacific Euro area Europe & Central Asia Latin America & Caribbean Middle East & North Africa OECD members Sub-Saharan Africa United States 2015 Figure Economic growth of areas Source: World Development Indicators (Worldbank) On the aspect of government operation, the general government expenditure increased in the pre-2008 global financial crisis, and they expended the government spending higher in the crisis that presents the government policies to tackle with the crisis through the stimulus packages and expansionary fiscal policy (see Fig.2) This fact shows the important role of fiscal policy in macroeconomic policies of governments in this area General government final consumption expenditure (annual % growth) 6.0 5.0 4.0 3.0 2.0 1.0 0.0 2002 2003 2004 2005 2006 2007 2008 East Asia & Pacific 2009 2010 2011 2012 2013 Europe & Central Asia Figure Government expenditure growth rates in Asia Pacific areas 2014 2015 Source: World Development Indicators (Worldbank) Furthermore, the fiscal budgets were usually under the deficit situations across countries in the whole period (see Fig.3), except some small countries such as Georgia, Mongolia, and Tonga in some short period of years This fact provides a suitable sample for us to examine the determinants of fiscal deficits Primary fiscal balance (%/GDP) 10.0 0.0 -5.0 -10.0 -15.0 AFGHANISTAN AFGHANISTAN ARMENIA ARMENIA AZERBAIJAN BANGLADESH BANGLADESH BHUTAN Fiji Fiji GEORGIA INDIA INDIA INDONESIA KYRGYZ REPUBLIC KYRGYZ REPUBLIC LAO PEOPLE'S… LAO PEOPLE'S… MALAYSIA MALDIVES MALDIVES MONGOLIA Nepal Nepal PHILIPPINES PAPUA NEW GUINEA PAPUA NEW GUINEA China SAMOA SAMOA SOLOMON ISLANDS SOLOMON ISLANDS SRI LANKA TAJIKISTAN TAJIKISTAN Thailand TONGA TONGA VANUATU Vietnam Vietnam 5.0 -20.0 -25.0 -30.0 Figure Primary fiscal balance in Asia Pacific countries 2002-2015 (%/GDP) Source: Key economic indicators (ADB) As a result, the developing countries in Asia Pacific area are the fruitful sample for examining the effects of corruption and its interactions with other drivers on fiscal deficits Whereas, we examine the effects of corruption controlling and its interactions with the external debt and government size on fiscal deficits in the period of 2002 – 2015 This period of time is recruited due to the availability of data from the World Governance Indicators of World Bank that provides the yearly data from 2002 and the lasted data in 2015 1.3 The contributions of the study Andrés, A R (2006) Software piracy and income inequality Applied Economics Letters, 13(2), 101-105 Antelo, M., & Peón, D (2014) Fiscal consolidation and the sustainability of public debt in the GIPSI countries Cuadernos de Economía, 37(103), 52-71 doi:https://doi.org/10.1016/j.cesjef.2013.10.002 Antunes, A R., & Cavalcanti, T V (2003) Corruption, credit market imperfections, and economic development 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realint dunem exp rev fisde 1.0000 gdpg 0.1779 0.0007 1.0000 inf 0.1125 0.0333 0.1940 0.0002 1.0000 realint -0.0430 0.4261 -0.0517 0.3353 -0.3746 0.0000 1.0000 dunem -0.1030 0.0609 -0.0735 0.1790 -0.0820 0.1335 0.0422 0.4496 1.0000 exp -0.3696 0.0000 -0.1979 0.0002 0.0390 0.4620 0.1715 0.0014 0.0259 0.6377 1.0000 rev 0.2390 0.0000 -0.0948 0.0731 0.1118 0.0345 0.1541 0.0041 -0.0351 0.5233 0.8139 0.0000 1.0000 debt -0.1854 0.0004 -0.0155 0.7709 0.1176 0.0263 0.3819 0.0000 -0.0223 0.6855 0.2115 0.0001 0.1057 0.0467 concorrup -0.1187 0.0246 -0.1177 0.0251 -0.1670 0.0014 -0.1006 0.0605 -0.0275 0.6144 0.3192 0.0000 0.2594 0.0000 debt concor~p debt 1.0000 concorrup 0.0176 0.7404 1.0000 40 Dynamic panel-data estimation, two-step system GMM Group variable: count Time variable : year Number of instruments = 24 F(7, 26) = 1839.46 Prob > F = 0.000 Number of obs Number of groups Obs per group: avg max fisde Coef Std Err fisde L1 .5599827 0288035 gdpg inf realint dunem debt exp 0846279 152437 1841053 -.0642803 -.0353744 -.1092662 0123809 0186116 0362548 0110773 0048203 0108574 t = = = = = 318 26 12.23 13 P>|t| [95% Conf Interval] 19.44 0.000 5007763 619189 6.84 8.19 5.08 -5.80 -7.34 -10.06 0.000 0.000 0.000 0.000 0.000 0.000 0591787 1141802 1095824 -.0870501 -.0452826 -.131584 1100771 1906937 2586282 -.0415105 -.0254662 -.0869485 Warning: Uncorrected two-step standard err ors are unreliable Instruments for first differences equation Standard D.(gdpg inf L.realint dunem debt L.exp) GMM-type (missing=0, separate instruments for each period unless collapsed) L4.L.fisde Instruments for levels equation Standard gdpg inf L.realint dunem debt L.exp GMM-type (missing=0, separate instruments for each period unless collapsed) DL3.L.fisde Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(17) = 49.26 but not weakened by many instruments.) overid restrictions: chi2(17) = 22.48 weakened by many instruments.) -3.22 -0.98 Pr > z = Pr > z = 0.001 0.329 Prob > chi2 = 0.000 Prob > chi2 = 0.167 Difference-in-Hanse n tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(8) = 10.17 Prob > Difference (null H = exogenous): chi2(9) = 12.31 Prob > iv(gdpg inf L.realint dunem debt L.exp) Hansen test excluding group: chi2(11) = 13.50 Prob > Difference (null H = exogenous): chi2(6) = 8.99 Prob > 41 chi2 = chi2 = 0.253 0.196 chi2 = chi2 = 0.262 0.174 Dynamic panel-data estimation, two-step system GMM Number of obs Number of groups Obs per group: avg max Group variable: count Time variable : year Number of instruments = 25 F(8, 26) = 4615.03 Prob > F = 0.000 fisde Coef Std Err fisde L1 .5498677 0371972 gdpg inf realint dunem debt exp concorrup 0878865 2095926 2339653 -.055181 -.0406493 -.1082746 1.119825 0155118 0363399 0568131 0124428 0068929 0159569 2266046 t = = = = = 318 26 12.23 13 P>|t| [95% Conf Interval] 14.78 0.000 4734077 6263277 5.67 5.77 4.12 -4.43 -5.90 -6.79 4.94 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0560016 1348948 1171843 -.0807576 -.0548178 -.1410745 6540325 1197715 2842904 3507462 -.0296045 -.0264807 -.0754746 1.585617 Warning: Uncorrected two-step standard errors are unreliable Instruments for first differences equation Standard D.(gdpg inf L.realint dunem debt L.exp concorrup) GMM-type (missing=0, separate instruments for each period unless collapsed) L4.L.fisde Instruments for levels equation Standard gdpg inf L.realint dunem debt L.exp concorrup GMM-type (missing=0, separate instruments for each period unless collapsed) DL3.L.fisde Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(17) = 48.06 but not weakened by many instruments.) overid restrictions: chi2(17) = 19.94 weakened by many instruments.) -3.08 -0.98 Pr > z = Pr > z = 0.002 0.326 Prob > chi2 = 0.000 Prob > chi2 = 0.277 Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels = 9.87 Prob > Hansen test excluding group: chi2(8) = 10.07 Prob > Difference (null H = exogenous): chi2(9) iv(gdpg inf L.realint dunem debt L.exp concorrup) chi2(10) = 13.11 Prob > Hansen test excluding group: = 6.83 Prob > Difference (null H = exogenous): chi2(7) 42 chi2 = chi2 = 0.274 0.345 chi2 = chi2 = 0.218 0.447 Dynamic panel-data estimation, two-step system GMM Group variable: count Time variable : year Number of instruments = 24 F(9, 26) = 3060.92 Prob > F = 0.000 Number of obs Number of groups Obs per group: avg max fisde Coef Std Err fisde L1 .5701157 0533174 gdpg inf realint dunem debt exp concorrup debtconcorrup 1472948 1006047 1191915 -.0712812 -.0498729 -.0475782 2.465204 -.0355848 0147355 0272553 0241102 0156633 0056942 010066 2021873 0042893 t = = = = = 318 26 12.23 13 P>|t| [95% Conf Interval] 10.69 0.000 4605201 6797112 10.00 3.69 4.94 -4.55 -8.76 -4.73 12.19 -8.30 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.000 1170055 0445805 0696322 -.1034775 -.0615774 -.0682693 2.049602 -.0444015 1775841 1566289 1687507 -.0390849 -.0381684 -.0268872 2.880806 -.026768 Warning: Uncorrected two-step standard errors are unreliable Instruments for first differences equation Standard D.(gdpg inf L.realint dunem debt L.exp concorrup debtconcorrup) GMM-type (missing=0, separate instruments for each period unless collapsed) L4.L2.fisde Instruments for levels equation Standard gdpg inf L.realint dunem debt L.exp concorrup debtconcorrup GMM-type (missing=0, separate instruments for each period unless collapsed) DL3.L2.fisde Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(15) = 28.44 but not weakened by many instruments.) overid restrictions: chi2(15) = 21.16 weakened by many instruments.) -3.12 -0.98 Pr > z = Pr > z = 0.002 0.329 Prob > chi2 = 0.019 Prob > chi2 = 0.132 Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for l evels Hansen test excluding group: chi2(7) = 14.00 Prob > chi2 Difference (null H = exogenous): chi2(8) = 7.16 Prob > chi2 iv(gdpg inf L.realint dunem debt L.exp concorrup debtconcorrup) Hansen test excluding group: chi2(7) = 4.75 Prob > chi2 Difference (null H = exogenous): chi2(8) = 16.41 Prob > chi2 43 = = 0.051 0.519 = = 0.690 0.037 Dynamic panel-data estimation, two-step system GMM Group variable: count Time variable : year Number of instruments = 25 = 68597.27 F(10, 26) = 0.000 Prob > F Number of obs Number of groups Obs per group: avg max fisde Coef Std Err fisde L1 .5614378 0411391 gdpg inf realint dunem debt exp concorrup debtconcorrup expconcorrup 1774904 0967419 1140557 -.0590032 -.0352776 -.0820355 6.051024 -.0203079 -.1852863 0148239 0397 0358382 0160471 0097328 0132825 9252249 0085764 0465662 = = = = = 318 26 12.23 13 P>|t| [95% Conf Interval] 13.65 0.000 4768753 6460004 11.97 2.44 3.18 -3.68 -3.62 -6.18 6.54 -2.37 -3.98 0.000 0.022 0.004 0.001 0.001 0.000 0.000 0.026 0.000 1470194 0151374 0403892 -.0919884 -.0552836 -.109338 4.149197 -.037937 -.2810046 2079614 1783464 1877223 -.026018 -.0152716 -.054733 7.952851 -.0026787 -.0895681 t Warning: Uncorrected two-step standard errors are unreliable Instruments for first differences equation Standard D.(gdpg inf L.realint dunem debt L.exp L.concorrup L.debtconcorrup L.expconcorrup) GMM-type (missing=0, separate instruments for each period unless collapsed) L4.L2.fisde Instruments for levels equation Standard gdpg inf L.realint dunem debt L.exp L.concorrup L.debtconcorrup L.expconcorrup GMM-type (missing=0, separate instruments for each period unless collapsed) DL3.L2.fisde Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but = 28.24 overid restrictions: chi2(15) but not weakened by many instruments.) = 21.40 overid restrictions: chi2(15) weakened by many instruments.) Pr > z = Pr > z = 0.001 0.320 Prob > chi2 = 0.020 Prob > chi2 = 0.125 -3.30 -0.99 Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels chi2(7) = 12.42 Prob > chi2 = 0.088 Hansen test excluding group: = 8.98 Prob > chi2 = 0.344 Difference (null H = exogenous): chi2(8) iv(gdpg inf L.realint dunem debt L.exp L.concorrup L.debtconcorrup L.expconcorrup) Hansen test excluding group: chi2(6) = 4.92 Prob > chi2 = 0.554 = 16.47 Prob > chi2 = 0.058 Difference (null H = exogenous): chi2(9) 44 Dynamic panel-data estimation, two-step system GMM Group variable: count Time variable : year Number of instruments = 24 F(7, 26) = 3866.24 Prob > F = 0.000 Number of obs Number of groups Obs per group: avg max fisde Coef Std Err fisde L1 .7522635 0313726 gdpg inf realint dunem debt rev 1280618 0750547 0917708 -.0569465 -.0209262 -.0866081 0141027 0211187 0323447 0131255 0046679 0113738 t = = = = = 318 26 12.23 13 P>|t| [95% Conf Interval] 23.98 0.000 6877761 8167508 9.08 3.55 2.84 -4.34 -4.48 -7.61 0.000 0.001 0.009 0.000 0.000 0.000 0990733 0316447 0252853 -.0839263 -.0305213 -.1099874 1570502 1184647 1582563 -.0299667 -.0113311 -.0632289 Warning: Uncorrected two-step standard err ors are unreliable Instruments for first differences equation Standard D.(gdpg inf L.realint dunem debt L.rev) GMM-type (missing=0, separate instruments for each period unless collapsed) L4.L.fisde Instruments for levels equation Standard gdpg inf L.realint dunem debt L.rev GMM-type (missing=0, separate instruments for each period unless collapsed) DL3.L.fisde Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(17) = 43.52 but not weakened by many instruments.) overid restrictions: chi2(17) = 22.03 weakened by many instruments.) -3.31 -0.96 Pr > z = Pr > z = 0.001 0.336 Prob > chi2 = 0.000 Prob > chi2 = 0.183 Difference-in-Hanse n tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(8) = 12.06 Prob > Difference (null H = exogenous): chi2(9) = 9.97 Prob > iv(gdpg inf L.realint dunem debt L.rev) Hansen test excluding group: chi2(11) = 15.20 Prob > Difference (null H = exogenous): chi2(6) = 6.84 Prob > 45 chi2 = chi2 = 0.148 0.353 chi2 = chi2 = 0.174 0.336 Dynamic panel-data estimation, two-step system GMM Group variable: count Time variable : year Number of instruments = 25 F(8, 26) = 9289.87 Prob > F = 0.000 Number of obs Number of groups Obs per group: avg max fisde Coef Std Err fisde L1 .7298944 0375571 gdpg inf realint dunem debt rev concorrup 1277227 1268483 1411822 -.0513325 -.0247615 -.09592 8227638 0155616 0435852 0584898 0136073 0070529 0157996 2334819 t = = = = = 318 26 12.23 13 P>|t| [95% Conf Interval] 19.43 0.000 6526946 8070941 8.21 2.91 2.41 -3.77 -3.51 -6.07 3.52 0.000 0.007 0.023 0.001 0.002 0.000 0.002 0957354 0372576 0209546 -.0793027 -.0392589 -.1283965 3428348 15971 216439 2614098 -.0233623 -.0102641 -.0634436 1.302693 Warning: Uncorrected t wo-step standard errors are unreliable Instruments for first differences equation Standard D.(gdpg inf L.realint dunem debt L.rev concorrup) GMM-type (missing=0, separate instruments for each period unless collapsed) L4.L.fisde Instruments for levels equation Standard gdpg inf L.realint dunem debt L.rev concorrup GMM-type (missing=0, separate instruments for each period unless collapsed) DL3.L.fisde Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(17) = 43.31 but not weakened by many instruments.) overid restrictions: chi2(17) = 22.57 weakened by many instruments.) -3.20 -0.96 Pr > z = Pr > z = 0.001 0.338 Prob > chi2 = 0.000 Prob > chi2 = 0.164 Differenc e-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for levels Hansen test excluding group: chi2(8) = 11.72 Prob > Difference (null H = exogenous): chi2(9) = 10.85 Prob > iv(gdpg inf L.realint dunem debt L.rev concorrup) Hansen test excluding group: chi2(10) = 12.20 Prob > Difference (null H = exogenous): chi2(7) = 10.37 Prob > 46 chi2 = chi2 = 0.164 0.286 chi2 = chi2 = 0.272 0.168 Dynamic panel-data estimation, two-step system GMM Group variable: count Time variable : year Number of instruments = 26 F(9, 26) = 65985.80 Prob > F = 0.000 Number of obs Number of groups Obs per group: avg max fisde Coef Std Err fisde L1 .7328804 0421742 gdpg inf realint dunem debt rev concorrup debtconcorrup 1419191 1338322 1500054 -.0507575 -.036925 -.0758369 1.911332 -.0207655 0187175 0454507 0545865 0176072 0064514 0148091 2920447 0058468 t = = = = = 318 26 12.23 13 P>|t| [95% Conf Interval] 17.38 0.000 6461901 8195706 7.58 2.94 2.75 -2.88 -5.72 -5.12 6.54 -3.55 0.000 0.007 0.011 0.008 0.000 0.000 0.000 0.001 1034448 0404069 0378013 -.0869495 -.0501859 -.1062773 1.311025 -.0327838 1803934 2272575 2622095 -.0145654 -.023664 -.0453964 2.511638 -.0087472 Warning: Uncorrected two-step standard errors are unreliable Instruments for first differences eq uation Standard D.(gdpg inf L.realint dunem debt L.rev concorrup debtconcorrup) GMM-type (missing=0, separate instruments for each period unless collapsed) L4.L.fisde Instruments for levels equation Standard gdpg inf L.realint dunem debt L.rev concorrup debtconcorrup GMM-type (missing=0, separate instruments for each period unless collapsed) DL3.L.fisde Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(17) = 43.31 but not weakened by many instruments.) overid restrictions: chi2(17) = 21.73 weakened by many instruments.) -3.11 -0.96 Pr > z = Pr > z = 0.002 0.336 Prob > chi2 = 0.000 Prob > chi2 = 0.195 Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instruments for l evels Hansen test excluding group: chi2(8) = 10.41 Prob > chi2 Difference (null H = exogenous): chi2(9) = 11.33 Prob > chi2 iv(gdpg inf L.realint dunem debt L.rev concorrup debtconcorrup) Hansen test excluding group: chi2(9) = 12.25 Prob > chi2 Difference (null H = exogenous): chi2(8) = 9.49 Prob > chi2 47 = = 0.238 0.254 = = 0.200 0.303 Dynamic panel-data estimation, two-step system GMM Group variable: count Time variable : year Number of instruments = 23 F(10, 26) = 430.78 Prob > F = 0.000 Number of obs Number of groups Obs per group: avg max fisde Coef fisde L1 .5614555 0542814 gdpg inf realint dunem debt rev concorrup debtconcorrup revconcorrup 1520338 1157019 1318462 -.0741685 -.0429528 -.0950595 4.340079 -.0185759 -.1592807 0218259 0675013 066358 02162 0123933 0240612 1.292106 0082433 0440263 Std Err t = = = = = 318 26 12.23 13 P>|t| [95% Conf Interval] 10.34 0.000 4498785 6730324 6.97 1.71 1.99 -3.43 -3.47 -3.95 3.36 -2.25 -3.62 0.000 0.098 0.058 0.002 0.002 0.001 0.002 0.033 0.001 1071701 -.0230491 -.0045546 -.1186091 -.0684275 -.1445181 1.684116 -.0355203 -.2497782 1968975 2544529 2682469 -.029728 -.0174781 -.0456009 6.996041 -.0016316 -.0687833 Warning: Uncorrected two-step standard errors are unreliable Instruments for first differences equation Standard D.(gdpg inf L.realint dunem debt rev concorrup debtconcorrup revconcorrup) GMM-type (missing=0, separate instruments for each period unless collapsed) L5.L2.fisde Instruments for levels equation Standard gdpg inf L.realint dunem debt rev concorrup debtconcorrup revconcorrup GMM-type (missing=0, separate instruments for each period unless collapsed) DL4.L2.fisde Arellano-Bond test for AR(1) in first differences: z = Arellano-Bond test for AR(2) in first differences: z = Sargan test of (Not robust, Hansen test of (Robust, but overid restrictions: chi2(13) = 16.24 but not weakened by many instruments.) overid restrictions: chi2(13) = 12.61 weakened by many instruments.) -3.20 -1.15 Pr > z = Pr > z = 0.001 0.251 Prob > chi2 = 0.236 Prob > chi2 = 0.479 Difference-in-Hansen tests of exogeneity of instrument subsets: GMM instru ments for levels Hansen test excluding group: chi2(6) = 4.59 Prob > chi2 = 0.598 Difference (null H = exogenous): chi2(7) = 8.02 Prob > chi2 = 0.331 iv(gdpg inf L.realint dunem debt rev concorrup debtconcorrup revconcorrup) Hansen test excluding group: chi2(4) = 2.51 Prob > chi2 = 0.642 Difference (null H = exogenous): chi2(9) = 10.09 Prob > chi2 = 0.343 48 ...Ministry of Education and Training University of Economics Ho Chi Minh City ******** Research Topic CORRUPTION AND DETERMINANTS OF FISCAL DEFICITS IN ASIA PACIFIC COUNTRIES Ref code:... controlling on fiscal deficits and its interactions with external debt and government size in the context of 26 Asia Pacific countries In which, the better corruption controlling is in line with... The fiscal deficits and determinants The rise and persistence of large fiscal deficits in many developed and developing countries from 1980s is one of the most striking macroeconomic debate in