MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY HUYNH CONG MINH SHADOW ECONOMY IN THE RELATIONSHIP WITH FDI, INSTITUTIONAL QUALITY, AND INCOME INEQUALITY: EMPIRICAL EVIDENCE FROM ASIAN COUNTRIES PhD THESIS Ho Chi Minh City – 2018 MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY HUYNH CONG MINH SHADOW ECONOMY IN THE RELATIONSHIP WITH FDI, INSTITUTIONAL QUALITY, AND INCOME INEQUALITY: EMPIRICAL EVIDENCE FROM ASIAN COUNTRIES Major: Development Economics Code: 9310105 PhD THESIS Advisors: Dr Nguyen Hoang Bao Dr Nguyen Vu Hong Thai Ho Chi Minh City – 2018 i This thesis submitted to the School of Economics, University of Economics Ho Chi Minh City, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in development economics ii DECLARATION I hereby declare that this thesis is my own research Data and results are reliable, clearly originated, and have never been published in any other study The author iii ACKNOWLEDGEMENTS First of all, I would like to express my great gratitude to Dr Nguyen Hoang Bao and Dr Nguyen Vu Hong Thai for their invaluable supervision and inspirations Thank you so much for keeping me on track throughout the research process, giving wise comments, advices and encouragement during such a long academic journey Then I am honestly grateful to Dr Pham Khanh Nam, Dr Truong Dang Thuy, Dr Le Van Chon, Dr Vo Tat Thang, Dr Vo Hong Duc, Associate Pro Dr Nguyen Huu Dung, Dr Nguyen Luu Bao Doan, Dr Pham Thi Thu Tra, Dr Pham Thi Bich Ngoc, Associate Pro Dr Vuong Duc Hoang Quan and the two independent Reviewers for their valuable comments and encouragements so that I can improve the quality of my thesis I cannot forget showing my special thanks to lecturers at school of economics as well as those at University of Economics HCMC such as Professor Dr Nguyen Trong Hoai, Dr Pham Khanh Nam, Dr Truong Dang Thuy, Associate Pro Dr.Nguyen Manh Hung, Dr Tran Thi Tuan Anh, Associate Pro Dr Tran Tien Khai… for their academic and practical instructions during my time of study and research at the university Last but not least, I am deeply grateful to my beloved family, including my deceased father, my 83-year-old mother as well as my sisters and brothers who always support and encourage me in time for completing the thesis iv TABLE OF CONTENTS Declaration Acknowledgements Table of contents List of Abbreviations List of Tables List of Figures Pages Chapter 1: Introduction 1.1 Research context and gaps 1.2 Research objectives 13 1.3 Research questions……………………………………………… 13 1.4 Research subjects and scope 13 1.5 Research methodology and data ………………………………… 14 1.6 Contributions 15 1.7 Limitations 17 1.8 Thesis outline 18 Chapter 2: Literature review and hypotheses 19 2.1 Shadow economy 20 2.1.1 Theories on shadow economy 20 2.1.1.1 Definition 20 2.1.1.2 Schools of thought 21 2.1.2 Empirical studies on shadow economy 31 2.1.2.1 Methods to estimate the size of the shadow economy 31 v 2.1.2.2 Determinants (causes) 35 2.1.2.3 The impacts of shadow economy (effects) 40 2.2 Shadow economy, FDI and Institutional quality 44 2.2.1 FDI and institutional quality 44 2.2.1.1 Theories on FDI (Definition, Theories, Determinants) 44 2.2.1.2 Theories of institutional quality (Definition, Theories, Determinants) 47 2.2.1.3 The relationship between institutional quality and FDI 48 2.2.2 Institutional quality and shadow economy 54 2.2.2.1 The effect of institutional quality on shadow economy 55 2.2.2.2 The effect of shadow economy on institutional quality 57 2.2.3 Shadow economy and FDI 59 2.2.3.1 The effects of FDI and FDI-institutional quality interaction on shadow economy 59 2.2.3.2 The effects of shadow economy on FDI 59 2.3 Shadow economy and income inequality 61 2.3.1 Income inequality 61 2.3.1.1 Definition 61 2.3.1.2 Theories 62 2.3.1.3 Measurements 65 2.3.1.4 Determinants 66 2.3.2 The impact of shadow economy on income inequality 67 Chapter 3: Methodology, model specifications, and data 73 3.1 Analytical framework 74 3.2 Empirical models and data 77 3.3 Econometric methodology 88 3.4 The sample selection of 19 Asian countries and their backgrounds on research problems 93 vi Chapter 4: Shadow economy, FDI and Institutional quality: empirical evidence from Asian countries 96 4.1 Introduction 96 4.2 Data analysis 97 4.2.1 Data descriptive statistics 97 4.2.2 Unit-root test 99 4.2.3 Correlation analysis 101 4.3 Estimation results and discussions 102 Chapter 5: The impacts of shadow economy on income inequality in developing Asia 113 5.1 Introduction 113 5.2 Data descriptive statistics 116 5.3 Empirical results and discussions 119 Chapter 6: Conclusions and policy implications 125 6.1 Conclusions 125 6.2 Policy implications 128 6.3 Limitations and further research implications 129 List of publications 130 References 131 Appendices 158 vii LIST OF ABBREVIATIONS 2SLS: Two-stage Least Squares 3SLS: Three-stage Least Squares ARDL: Autoregressive-distributed lag model AR1: First-order Autocorrelation AR2: Second-order Autocorrelation ECM: Error correction model EFR: Economic Freedom Report FDI: Foreign direct investment FE: Fixed Effects FH: The Freedom House GCI: Global Competitiveness Index GDP: Gross Domestic Products GLS: Generalized Least Squares GNI: Gross National Income MENA: Middle East and North Africa MIMIC: Multiple Indicators Multiple Causes MNCs: Multinational Corporations HDR: Human Development Report HF: The Heritage Foundation ICRG: The International Country Risk Guide IEF: Index of Economic Freedom viii ILO: International Labor Organization IMF: International Monetary Fund IQ: Institutional quality JGLS: Joint Generalized Least Squares OLI: Ownership, Location, and Internalization OLS: Ordinary Least Squares POLS: Pooled Ordinary Least Squares PRS: Political Risk Services Group RE: Random Effects SEM: Simultaneous equation model SGMM: Two Steps System Generalized Method of Moments SURE: Seemingly Unrelated Regression UNESCO: United Nations Educational Scientific and Cultural Organization UNCTAD: United Nations Conference on Trade and Development UNDP: United Nations Development Programme WB: World Bank WDI: World Development Indicators WEF: World Economic Forum WGIs: Worldwide Governance Indicators 163 20% Income share held by highest 20% INC_HIGH EST20 % WDI, WB Medina & Schneider (2018) + - ILOSTAT database - IMF + Independent Variables Shadow economy SHADOW Employment EMPLOY_ Rice and Lozada, SERVICES 1980; Mocan, 1999 Inflation CPI Rice and Lozada, 1980; Mocan, 1999 The country level of shadow economy as a percentage of official GDP (%) Employment in services (% of total employment) Inflation, consumer prices (annual %) Trade Openness OPEN Barro, 2000; Wood, 1997 Ratio of import & export in GDP (%) WDI, WB - Institutional quality INSTQUA LITY Chong and Gradstein, 2007; Carmignani, 2009 The component Institutions of Global Competitiveness Index (GCI) GCI, World Economic Forum - Economic Freedom Report 2016, the Fraser Institute Human Developme nt Report, UNDP +/- Economic freedom ECO_FRE EDOM Berggren, 1999, 2003; Scully, 2002; Ashby and Sobel, 2008; Carter, 2006 Education EDU_HDR Knight and Sabot, 1983; Winegarden, 1979; O‘neill, 1995; Gregorio and Lee, 2002; Scale from (lowest quality) to (highest quality) Economic freedom index scale of to 10, higher scores imply higher levels of economic freedom Education index, scale (lowest) – 1(highest) - 164 Corruption CORRUPT ION Gupta et al., 2002; Gyimah-Brempong, 2002; and Apergis, 2010 Natural resources and land distributions LANDPER PERSON Deininger and Squire, 1998; Fum and Hodler, 2010 Control of corruption index Scale: -2.5 (more corrupt) to 2.5 (less corrupt) Arable land (hectares per person) WGI, WB - WDI, WB +/- 165 E THE RESULTS OF PEARSON’S CORRELATION ANALYSIS pwcorr shadow instquality di labor laborquality wage open tel gdpg fuel democ eco_free edu gniperc govt_burden tax global corrupt > urban, sig star(10) shadow instqu~y shadow di labor laborq~y wage open 1.0000 instquality -0.2668* 0.0000 1.0000 di -0.4111* 0.0000 0.3567* 0.0000 1.0000 labor -0.1711* 0.0020 0.1042* 0.0615 0.2132* 0.0001 1.0000 laborquality 0.0996* 0.0740 0.3725* 0.0000 0.1762* 0.0015 0.1367* 0.0140 wage 0.1048* 0.0600 0.1540* -0.1974* -0.0459 0.0055 0.0004 0.4113 0.2317* 0.0000 1.0000 open 0.0309 0.5801 0.7070* 0.0000 0.1396* 0.0120 0.2084* 0.0002 0.3421* 0.0000 0.0528 0.3442 1.0000 tel -0.0569 0.3079 0.4438* 0.0000 0.3062* 0.0000 0.0902 0.1056 0.4671* 0.0000 0.2697* 0.0000 0.3879* 0.0000 gdpg -0.3286* 0.0000 0.0423 0.4489 0.2883* 0.0000 0.3321* -0.0974* -0.0794 0.0000 0.0805 0.1546 -0.0995* 0.0740 fuel -0.1034* 0.0634 0.1204* 0.0306 0.1158* 0.0375 0.2779* 0.0000 -0.0628 0.2606 democ eco_free 0.0556 0.3191 -0.4452* -0.1850* 0.0000 0.0008 0.2708* 0.0000 0.5013* 0.0000 0.0265 0.6351 edu 0.0215 0.7000 0.5689* 0.0000 gniperc -0.0475 0.3948 1.0000 0.3832* -0.0234 0.0000 0.6758 0.2933* -0.2623* -0.2262* -0.2290* 0.0000 0.0000 0.0000 0.0000 -0.2168* 0.0001 0.4690* 0.0000 0.1968* 0.0004 0.4210* 0.0000 0.3512* 0.0000 0.0740 0.1845 0.7363* 0.0000 0.2102* 0.0001 0.4864* 0.0000 0.6088* 0.0000 0.0613 0.2717 0.0064 0.9086 0.4886* 0.0000 0.2359* 0.0000 0.4436* 0.0000 -0.3225* 0.0000 0.4913* 0.0000 0.1291* -0.0361 0.0203 0.5185 0.1811* 0.0011 0.0632 0.2573 0.2612* 0.0000 tax -0.0391 0.4837 0.2147* 0.0001 0.1571* 0.0047 0.3650* 0.0000 0.4941* 0.0000 0.0306 0.5832 0.3989* 0.0000 global -0.0437 0.4334 0.4853* -0.0298 0.0000 0.5934 -0.0973* 0.0807 0.5936* 0.0000 0.2770* 0.0000 0.3689* 0.0000 -0.1853* 0.0008 0.6626* 0.0000 0.2339* 0.0000 0.0736 0.1869 0.3868* 0.0000 0.1476* -0.1069* 0.0079 0.0549 govt_burden corrupt 0.3918* -0.0754 0.0000 0.1766 u_rate 0.4751* -0.1774* -0.2146* -0.2830* 0.0000 0.0014 0.0001 0.0000 0.2458* 0.0000 retire 0.5193* -0.1566* -0.1108* 0.0000 0.0048 0.0466 0.1664* 0.0027 0.1317* -0.1908* -0.0485 0.0179 0.0006 0.3849 0.0827 0.1380 0.6763* 0.0000 urban -0.2199* 0.0001 0.5219* 0.0000 0.0808 0.1476 0.2900* 0.0000 0.3620* 0.0000 166 tel tel gdpg fuel edu gniperc 1.0000 gdpg -0.1546* 0.0054 fuel 0.1295* 0.0199 0.1762* 0.0015 1.0000 democ -0.1882* 0.0007 0.2169* 0.0001 0.0633 0.2563 eco_free democ eco_free 1.0000 0.3124* -0.1935* -0.0282 0.0000 0.0005 0.6131 1.0000 -0.4646* 0.0000 1.0000 edu 0.6025* -0.0776 0.0000 0.1639 0.2961* -0.2948* 0.0000 0.0000 0.4653* 0.0000 1.0000 gniperc 0.5122* -0.0305 0.0000 0.5846 0.3313* -0.1235* 0.0000 0.0264 0.4318* 0.0000 0.6016* 0.0000 1.0000 govt_burden 0.4126* -0.0317 0.0000 0.5701 0.3579* 0.0000 0.2988* 0.0000 0.5904* 0.0000 tax 0.3283* -0.0534 0.0000 0.3384 0.2264* 0.0000 0.0559 0.3168 0.4258* 0.0000 0.1875* 0.0007 0.4121* -0.1595* 0.0000 0.0040 0.0432 0.4393 -0.3824* 0.0000 0.5901* 0.0000 0.5183* 0.0000 0.5865* 0.0000 -0.0146 0.7938 -0.4301* 0.0000 0.2661* 0.0000 0.3131* 0.0000 0.2925* 0.0000 global corrupt 0.3332* 0.0000 u_rate -0.0780 0.1618 retire 0.0364 0.5146 urban 0.0068 0.9029 -0.2159* 0.0001 0.0038 0.9457 -0.2504* 0.0000 0.1122* -0.0793 0.0439 0.1553 0.1108* 0.0466 0.1693* -0.0029 0.0023 0.9582 -0.0245 0.6609 0.1157* 0.0377 0.0867 0.1198 0.1434* 0.0098 0.0747 0.1802 0.3706* -0.3258* 0.0000 0.0000 0.3702* 0.0000 0.4767* 0.0000 0.6881* 0.0000 global u_rate retire 0.3938* -0.0237 0.0000 0.6712 govt_b~n -0.0242 0.6647 tax 0.2436* 0.0000 corrupt govt_burden 1.0000 tax 0.0335 0.5487 1.0000 global 0.5757* 0.0000 0.1585* 0.0043 1.0000 corrupt 0.2720* 0.0000 0.1115* 0.0453 0.2433* 0.0000 1.0000 u_rate -0.1955* -0.0066 0.0004 0.9064 0.0440 0.4304 0.0226 0.6858 retire -0.1783* -0.1050* 0.0013 0.0594 0.0372 0.5055 -0.2199* 0.0001 urban 0.4885* 0.0000 0.2796* 0.0000 0.6252* 0.0000 0.3456* 0.0000 urban 1.0000 0.1587* 0.0042 1.0000 0.1009* -0.1671* 0.0701 0.0026 1.0000 167 F STATA COMMAND (STATA 14) FOR MODEL use "F:\PhDThesis\Shadow FDI InsQ.dta" xtset country year gen interaction= fdi* instquality Descriptive Statistics sum fdi shadow instquality di labor laborquality wage open tel gdpg fuel democ eco_free edu gniperc govt_burden tax global corrupt u_rate retire urban moments2 fdi shadow instquality di labor laborquality wage open tel gdpg fuel democ eco_free edu gniperc govt_burden tax global corrupt u_rate retire urban sktest fdi shadow instquality di labor laborquality wage open tel gdpg fuel democ eco_free edu gniperc govt_burden tax global corrupt u_rate retire urban Pearson’s correlation analysis pwcorr shadow instquality di labor laborquality wage open tel gdpg fuel democ eco_free edu gniperc govt_burden tax global corrupt u_rate retire urban Unit-root test xtfisher fdi, pp xtfisher instquality, pp xtfisher shadow, pp xtfisher di, pp xtfisher gdpg, pp xtfisher labor, pp xtfisher laborquality, pp xtfisher wage, pp xtfisher d.wage, pp xtfisher fuel, pp xtfisher open, pp xtfisher d.open, pp xtfisher tel, pp xtfisher D.tel, pp xtfisher edu, pp 168 xtfisher d.edu, pp xtfisher gniperc, pp xtfisher d.gniperc, pp xtfisher democ, pp xtfisher govt_burden, pp xtfisher tax, pp xtfisher global, pp xtfisher corrupt, pp xtfisher u_rate, pp xtfisher retire, pp Estimations 4.1 3SLS **Specification reg3 (fdi instquality shadow di gdpg labor laborquality d.wage fuel) (instquality fdi shadow d.edu d.open d.gniperc democ) (shadow fdi instquality interaction govt_burden tax global gdpg u_rate retire urban i.country i.year), ols est sto spe2ols estat hettest reg3 (fdi instquality shadow di gdpg labor laborquality d.wage fuel) (instquality fdi shadow d.edu d.open d.gniperc democ) (shadow fdi instquality interaction govt_burden tax global gdpg u_rate retire urban i.country i.year), 3sls est sto spe23sls estat hettest hausman spe2ols spe23sls **Specification reg3 ( fdi instquality shadow di gdpg labor laborquality d.wage d.tel d.open fuel i.country i.year) ( instquality fdi shadow democ eco_free d.edu d.open d.gniperc) ( shadow fdi instquality interaction govt_burden tax global gdpg eco_free corrupt u_rate retire urban i.country i.year), ols est sto spe3ols 169 estat hettest test reg3 ( fdi instquality shadow di gdpg labor laborquality wage tel open fuel i.country i.year) ( instquality fdi shadow democ eco_free edu open gniperc) ( shadow fdi instquality interaction govt_burden tax global gdpg eco_free corrupt u_rate retire urban i.country i.year), 3sls est sto spe33sls estat hettest test hausman spe3ols spe33sls 4.2 Two Steps System GMM **FDI equation *Specification xtdpdsys fdi instquality shadow, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test *Specification xtdpdsys fdi instquality shadow di gdpg labor laborquality d.wage fuel, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test *Specification xtdpdsys fdi instquality shadow di gdpg labor laborquality d.wage fuel d.open d.tel, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test 170 **INSTITUTIONAL QUALITY equation *Specification xtdpdsys instquality fdi shadow, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test *Specification xtdpdsys instquality fdi shadow d.edu d.open d.gniperc, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test *Specification xtdpdsys instquality fdi shadow d.edu d.open d.gniperc democ eco_free , lags(1) twostep vce(robust) artests(2) estat abond estat sargan test **SHADOW equation *Specification xtdpdsys shadow fdi instquality, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test *Specification xtdpdsys shadow fdi instquality interaction govt_burden tax global gdpg u_rate retire urban, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test mfx 171 *Specification xtdpdsys shadow fdi instquality interaction govt_burden tax global gdpg u_rate retire urban eco_free corrupt, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test mfx 172 H STATA COMMAND (STATA 14) FOR MODEL use "F:\PhDThesis\Shadowandinequality.dta" xtset country year Summary statistics sum gini lowest20 highest20 shadow employ inflation open inst ecofree edu corrupt land moments2 lowest20 highest20 shadow employ inflation open inst ecofree edu corrupt land sktest lowest20 highest20 shadow employ inflation open inst ecofree edu corrupt land Pearson’s correlation analysis pwcorr gini lowest20 highest20 shadow employ inflation open inst ecofree edu corrupt land Unit-root test Xtfisher gini, pp xtfisher lowest20, pp xtfisher highest20, pp xtfisher shadow, pp xtfisher employ, pp xtfisher inflation, pp xtfisher open, pp xtfisher inst, pp xtfisher ecofree, pp xtfisher edu, pp xtfisher corrupt, pp xtfisher land, pp Estimation 4.1 The estimated results testing the impact of shadow economy on Gini from Pooled Ordinary Least Squares, Fixed Effects and Random Effects 173 **Pooled Ordinary Least Squares reg gini shadow employ inflation open inst ecofree edu corrupt land est sto giniPOLS *Breusch and Pagan test for heteroskedasticity estat hettest *Wooldridge test for autocorrelation in panel data tsset xtserial gini shadow employ inflation open inst ecofree edu corrupt land **Fixed Effects xtreg gini shadow employ inflation open inst ecofree edu corrupt land, fe est sto giniFE *Modified Wald test for groupwise heteroskedasticity in fixed effect regression model xttest3 *Wooldridge test for autocorrelation in panel data tsset xtserial gini shadow employ inflation open inst ecofree edu corrupt land *Fixed-effects GLS regression (to solve heteroskedasticity) xtgls gini shadow employ inflation open inst ecofree edu corrupt land i.year, panels(h) **Random Effects xtreg gini shadow employ inflation open inst ecofree edu corrupt land, re est sto giniRE *Breusch and Pagan Lagrangian multiplier test xttest0 174 *Wooldridge test for autocorrelation in panel data tsset xtserial gini shadow employ inflation open inst ecofree edu corrupt land *Random-effects GLS regression (to solve heteroskedasticity) xtgls gini shadow employ inflation open inst ecofree edu corrupt land, panels(h) *Hausman Test hausman giniFE giniRE 4.2 The estimated results testing the impact of shadow economy on the income share held by lowest 20% from Pooled Ordinary Least Squares, Fixed Effects and Random Effects **Pooled Ordinary Least Squares reg lowest20 shadow employ inflation open inst ecofree edu corrupt land est sto lowest20POLS *Breusch-Pagan / Cook-Weisberg test for heteroskedasticity estat hettest *Wooldridge test for autocorrelation in panel data tsset xtserial lowest20 shadow employ inflation open inst ecofree edu corrupt land **Fixed Effects xtreg lowest20 shadow employ inflation open inst ecofree edu corrupt land, fe est sto lowest20FE *Modified Wald test for groupwise heteroskedasticity in fixed effect regression model xttest3 *Wooldridge test for autocorrelation in panel data tsset xtserial lowest20 shadow employ inflation open inst ecofree edu corrupt land 175 *Fixed-effects GLS regression (to solve heteroskedasticity and autocorrelation) xtgls lowest20 shadow employ inflation open inst ecofree edu corrupt land i.year, panels(h) **Random Effects xtreg lowest20 shadow employ inflation open inst ecofree edu corrupt land, re est sto lowest20RE *Breusch and Pagan Lagrangian multiplier test xttest0 *Wooldridge test for autocorrelation in panel data tsset xtserial lowest20 shadow employ inflation open inst ecofree edu corrupt land **Hausman Test hausman lowest20FE lowest20RE 4.3 The estimated results testing the impact of shadow economy on the income share held by highest 20% from Pooled Ordinary Least Squares, Fixed Effects and Random Effects **Pooled Ordinary Least Squares reg highest20 shadow employ inflation open inst ecofree edu corrupt land est sto highest20POLS *Breusch-Pagan / Cook-Weisberg test for heteroskedasticity estat hettest *Wooldridge test for autocorrelation in panel data tsset xtserial highest20 shadow employ inflation open inst ecofree edu corrupt land **Fixed Effects xtreg highest20 shadow employ inflation open inst ecofree edu corrupt land, fe est sto highest20FE 176 *Modified Wald test for groupwise heteroskedasticity in fixed effect regression model xttest3 *Wooldridge test for autocorrelation in panel data tsset xtserial highest20 shadow employ inflation open inst ecofree edu corrupt land *Fixed-effects GLS regression (to solve heteroskedasticity) xtgls highest20 shadow employ inflation open inst ecofree edu corrupt land, panels(h) **Random Effects xtreg highest20 shadow employ inflation open inst ecofree edu corrupt land, re est sto highest20RE *Breusch and Pagan Lagrangian multiplier test xttest0 *Wooldridge test for autocorrelation in panel data tsset xtserial highest20 shadow employ inflation open inst ecofree edu corrupt land **Hausman Test hausman highest20FE highest20RE 4.3 The estimated results testing the impact of shadow economy on gini, the income share held by lowest 20% and the income share held by highest 20% from steps system GMM xtdpdsys gini shadow employ inflation open inst ecofree edu corrupt land, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test xtdpdsys lowest20 shadow employ inflation open inst ecofree edu corrupt land, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test 177 xtdpdsys highest20 shadow employ inflation open inst ecofree edu corrupt land, lags(1) twostep vce(robust) artests(2) estat abond estat sargan test ... examine the causal relationship among FDI, institutional quality and shadow economy in Asian countries; (2) to investigate the impact of shadow economy on income inequality and the channel of the. ..MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY HUYNH CONG MINH SHADOW ECONOMY IN THE RELATIONSHIP WITH FDI, INSTITUTIONAL QUALITY, AND INCOME INEQUALITY: EMPIRICAL. .. rapid rising income inequality with their increases in Gini indexes by 18.8%, 14.9% and 14.1% respectively The income inequality was also found rising in Sri Lanka, Laos, Pakistan, Vietnam and Tajikistan