Does income per capita affect carbon dioxide emissons in some east asian countries

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 DOES INCOME PER CAPITA AFFECT CARBON DIOXIDE EMISSIONS IN SOME EAST ASIAN COUNTRIES? A thesis submitted in partial fulfilment of the requirements for the degree of J., MASTER OF ARTS IN DEVELOPMENT ECONOMICS By PHAM THI THU HUYEN Academic Supervisor: PHAM KHANH NAM HO CHI MINH CITY, MAY 2012 ACKNOWLEDGEMENT This thesis could not complete without considerable and kindly mental supports from my supervisor, Dr Pham Khanh Nam, who spent his valuable time to help me to find materials, books and super my schedule tightly He also response quickly as soon as I asked for help and give comments, which partly contribute to the success of this thesis From bottom of my heart, I sincerely thank him for all I grateful acknowledge to Prof., Dr Nguyen Trong Hoai, Dr Nguyen Van Ngai and Dr Phan Dinh Nguyen- Public Defense Committee for their important comments and explanations that support me to fulfill the thesis This study also benefits greatly from the enthusiastic assistance of Dr Le Van Chon, whom I got knowledge on econometric and suggested the suitable models for the study I would like to express my thanks for all students of MDE 16 for their unceasing assistance and encouragement during the course I also show deep gratitude to the lectures, VNP staffs, library staffs for their helps in accumulating knowledge, accessing dataset and materials as well Last but not least, it gives my deepest grateful to my family members, husband, managers and colleagues for their dear encouragement, give favorable times and opportunities to finish the M.A course as well as the thesis I pledge to bear full responsibilities for errors, omissions and shortcomings of the study TABLE OF CONTENTS CHAPTER 1: INTRODUCTION ! 1.1 Problem Statement 1.2 Objectives of study 1.3 Research questions 1.4 Scope of the research 1.5 Structure ofthe thesis S CHAPTER 2: EMPIRICAL AND THEORETICAL BACKGROUND 2.1 Theoretical background 2.2 Empirical review CHAPTER 3: RESEARCH METHODOLOGY 14 The conceptual framework 14 Variables 15 2.1 Dependent environment variables IS 3.2.2 Explanatory variables I? GDP per capita 17 Foreign Direct Investment (FDI) !? Trade openness 19 Population density 20 3.3 Data 22 3.4 The Econometric model 22 CHAPTER4: DATA ANALYSIS 28 4.1 Carbon Dioxide Emissions and GDP for East Asian countries 28 4.2 Descriptive analysis 30 4.3 The Environment Kuznets curve (EKC) 32 4.4 Determinants of pollution 40 CHAPTER 5: CONCLUSION AND POLICY IMPLICATIONS 46 I Main findings and policy implications 46 5.2 Limitation of the research and recommendations for further study 50 REFERENCES 52 11 APPENDICES A: Summary of empirical studies on different the EKC hypothesis 57 B: Description of variables and data sources 71 C: Description of C0 -GDP of six East Asian countries individually 74 D: Estimated results 78 E: Tests 82 LIST OF FIGURES Figure 2.1 The Kuznets Curve (1955) and the Environmental Kuznets Curve Figure 2.2 The Environmental Kuznets Curve in N-shape Figure 3.1 Conceptual framework of the study 14 Figure 4.1 C02 emissions for the period of 1990-2007 28 Figure 4.2 C0 emissions and GDP for the period of 1990-2007 29 Figure 4.3 The EKC shape for six East Asian countries 37 Figure 5.1 An overview of determinants on environmental quality 48 iii LIST OF TABLES Table 3.1 Summary of variables description 21 Table 4.1 Summary Statistic on the sample observations 30 Table 4.2 Correlation on the sample observations 31 Table 4.3 Estimated results for the EKC with different models 33 (without time trend) Table 4.4 A comparison of estimated results for the EKC with FEM 34 models Table 4.5 Estimated results for the EKC (N-shape) with FEM 36 Table 4.6 Estimated results for EKC with FEM time effects 38 Table Estimated results for FEM with extended model (time 41 effects) lV ABBREVIATIONS EKC Environmental Kuznets curve FDI Foreign Direct Investment NGOs Non-government organizations C02 Carbon dioxide emissions per capita GDP Gross Domestic Products GHG Greenhouse gas OLS Ordinary least square FEM Fixed Effects Model REM Random Effects Model X Import M Export NAFTA The North American Free Trade Agreement v CHAPTER 1: INTRODUCTION 1.1 Problem Statement For many centuries, the environmental degradation has become the issue of life with economic development Since the industrial revolution began in 18th century, it was as a real problem Industrial revolution with the technological progress brought great achievements, especially the worldwide usage of fossil fuels and coal in various industries As a result, global economy has growth fast along with human who significantly consumed natural resources leading environmental quality is worsening seriously (Irina, 2008) This implies that economic growth may affect environmental quality Every nation wishes to pursue targets of economic growth without damaging environment This is not feasible when history shows that any country becomes an industrial power, in the process of development, causing environmental damages, which cannot solve for a short time In order to serve quick economic growth targets, the policies of incomprehensive industrialization and urbanization with massive exploitation of natural resources have caused environmental problems in these countries for recent years Consequently, the air pollutions and global warming have continuously increased by human's uncontrolled activities in the development process For China case, environmental degradation is becoming serious problems, which not only affects strongly to domestic but also causes international consequences Some specialists judged that environmental pollution is creating challenges to government It is also a long-term burden on the Chinese people and "China's problem has become the world's problem" (Kahn and Yardley, 2007, p.2) In the current context, environmental problem is not for an individual country to cope with It becomes the common hot issues and needs co-operation of worldwide countries because of its global matter Kim ( 1996) revealed that due to the quick economic growth, environmental pollution has been in red alarm in China and it crosses the boundaries to South Korea and Japan Especially, the global pollutants, in which carbon dioxide emissions are particular pollutant, causing global warming Carbon dioxide emissions have dramatically increased for recent century due to human economic development Measuring environmental-economic relationship is necessary for any country to orient adequate economic- environmental policy The Environment Kuznets curve (EKC) is reckoned as the best ruler in estimating this relationship since Grossman and Krueger made empirical study on the impact of the economic growth on environment in NAFTA countries in 1991 Under the EKC hypothesis, environmental quality changes with income levels It displays in a bell shape curve Environment degrades with income levels in the first stage of development and then improves as soon as it passes a definite high-income level Researchers use the EKC hypothesis commonly to connect economic growth with environmental reduction in both single countries and country groups with different models Local pollutants and global pollutants are treated as dependent variables Beside income, other factors are applied as explanatory variables Although the results are not the same for all studies, the economic growth links the environmental deterioration and vice versa However, this theory has still been debated for years because various empirical studies found ambiguous results on the EKC but it has meaning for policy makers to find the best solutions for development sustainability (Dinda, 2004) In this study, the research concerns if fast economic growth affects the environmental quality in some East Asian countries, specifically six countries consist of three developing countries in Southeast Asia: Malaysia, Thailand, Vietnam and one developing country: China and two developed country in Northeast Asia: Korea and Japan, using cross- country balanced panel data set for the period of 1990-2007 Four developing countries are emergmg economies China is now one of the world's largest economies with World Bank's ranked by nominal GDP at the third in 2009, the second position in 20 10 and predicts to keep the second rank in 20 11 Thailand and Malaysia name in the second generation of newly industrialized economies Vietnam is also thought as the third generation of newly industrialize economy with fast GDP growth in the period of 2000-2009 While Japan and South Korea list the developed countries in East Asian region These countries are not avoidable the environmental damages during the fast economic growth (Nguyen, 2009; Choi et al, 2010) One of the significant messages of the EKC is that it is not necessary to damage environment during the development and growth if there is suitable policy in technology application Estimating the economic-environmental relationship bases on an EKC can make important sense in policy implications for six East Asian countries Developing countries like China, Thailand, Malaysia and Vietnam can get lessons and experiences from high income countries such as Japan and South Korea Tl-Je new emerging country like Vietnam draws more useful lesson in policy establishment from fast developing economies as China, Malaysia and Thailand in term of economic growth and environmental problems solving This study suggests that there is the existence of an EKC for six East Asian countries It means that income affects environmental damages and it will cure environment when income reach high level Rapid economic growth is vital but not necessary to damage environment Moreover, empirical results shows that beside GDP per capita, other factors contribute environmental pollution Foreign Direct Investment and Trade intensity have positive relation with C0 emissions but they are not significant statistically Population density is contrary Its coefficient has against sign as expected and has statistically significant at 10 percent level There is a negative relationship between population density and C0 emissions per capita It Data from World Development Indicator database, World Bank, I July 2011 http://siteresources.worldbank.org/DAT ASTA TISTICS/Resources/GDP.pdf) (Available at means that population density increases leading to reduce pollution Further study with other pollutants and control variables are suggested reconfirming the EKC hypothesis and making firm policies for six countries 1.2 Objectives of study The objectives related to six countries in East Asia (China, Vietnam, Thailand, Malaysia, Japan and South Korea) of the thesis include: • To examine the existence of an Environmental Kuznets curve (EKC) for a group of six countries • To find the role of other factors beside income such as trade openness, foreign direct investment (FDI) and population density in determining environmental quality • To recommend general policies for sustainable development in term of environment and economy of six East Asian countries 1.3 Research questions Some questions should be presumed in this thesis as following: Does the Environmental Kuznets curve actually exist in a group of six East Asian countries? Does income (GDP per capita) impact on the environmental quality in six East Asian countries? What is the role of other factors beside income, such as population density, trade openness, foreign direct investment (FDI) affect the environmental quality in six East Asian countries? What are recommendations to develop economy environmental protection in six East Asian countries? harmony with Vincent ( 1997) Hung and Shaw (2006) Malaysia Taiwan 1987-1991 1988-1997 Panel data Particulates GOP 13 states SOx capita follow an inverted U- NOx Population shaped pattern co density N02 Population so2 density equation co Number simultaneity PM10 Specialists and income per capita of air quality As protection there Air pollution increase in the level of inspection N02 and CO, followed rate by Panel data (two - model) Income per No Yes The inverted U-shape relationships are found of per between air pollutants income IS a grows, first an decrease However, air pollution capita does not significantly Man-made affect income capital stock per capita Employment Education 69 All pollutants did not DOE EPA data '· I Government expenditure per capita Notes: • WIR: World Resources Institute • GEMS: Global Environment Monitoring System • lEA: International Energy Agency • EPA: US Environmental Protection Agency • OECD: Organization for Economic Cooperation and Development • UNEP: United Nations Environment Programme Ozone Secretariat • WDI: World Bank's World Development Indicators • BESD: World Bank's Bank Economic and Social Database • CCIW: Canada Center for Inland Waters • MARC: Monitoring and Assessment Research Center • ORNL: Oak Ridge National Laboratory • NBS: National Bureau of Statistics • FAO: Food and Agriculture Organization • DOE: Malaysian Department ofEnvironment 70 I I Appendix 8: Description of variables and data sources Variables Description Unit Source Definition Carbon Metric dioxide per capita Dioxide ton Those stemming from the burning of fossil fuels Carbon Analysis and the manufacture of cement They include Information emissions per carbon dioxide produced during consumption of Center, capita solid, liquid, and gas fuels and gas flaring Environmental Sciences Division, Oak Ridge National Laboratory, Tennessee, the United States of America GDP Gross In thousand The total output of a country's economy divided by World Domestic US Product capita Bank's World Dollars midyear population in constant 2000 US Dollars, Development Indicator per (constant 2000 prices) which allow for the comparison of GDP across years without interference from the effects of inflation on prices GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included m the value of the products It Is 71 calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources FDI Foreign Direct In Investment current The net inflows of investment to acquire a lasting World US Dollars Bank, Global interest in or management control over an Development Finance enterprise operating in an economy other than that of the investor It is the sum of equity capital, reinvested earnings, other long-term capital, and short-term capital, as shown in the balance of payments TRADE Bank national Trade In intensity Dollars of goods and services in GDP It is calculated by accounts data and OECD (constant formula: (X+M)/GDP) US A share of the sum of exports (X) and imports (M) World National Accounts data 2000 prices) POP Population density Persons/km:z Population density ts calculated by mid-year Food population divided by land area m square Organization kilometers Population bases on the de facto Bank 72 and Agriculture and World defmition of population, which counts all residents regardless of legal status or citizenship, except for refugees not permanently settled in the country of asylum and who are generally considered part of the population of their country of origin Land area is a country's total area, excluding area under inland water bodies, national claims to continental shelf, and exclusive economic zones In most cases, the definition of inland water bodies includes major rivers and lakes Source: Data and definition are from World Bank's http://data worldbank.org/indicator 73 World Development Indicator Available at Appendix C: Description of C02 -GDP of six East Asian countries individually Japan's C02-GOP N d me :t:: - B l994' 8.CX) 2007 ~a; !3 E Q)co 2001 Sm (.) 1992 1999 'It a; -~3 34000 36000 38000 40000 42000 GOP per capita South Korea's C02-GOP 2007 Ill :t:: B-0> c:CX) U) :~ ~ N or-u 1993 1992 1991 co 1990 6000 8000 10000 12000 GOP per capita 74 14000 16000 China's C02-GOP • L{) 2007 006 005 i~v 2004 & Ill c: "gj E Q)C') N (.) N 500 1000 GOP per capita 1500 2000 Malaysia's C02-GOP ~~ ~OO F = 0.1294 35.04 0.0000 C02 coef GDP_k GDP_ksq 6639978 -.0119696 0579473 0010011 11.46 -11.96 0.000 0.000 5487429 -.0139608 7792527 -.0099784 1948524 2970882 4900125 i)S24635 9734099 1.134076 1.179643 7735103 7194385 9654495 1.042567 1.103546 358431 581947 570596 1.601695 772832 1964655 1960328 19 :"32 19, 15 20 011 2038099 205675 2019376 2039644 2079456 2089539 2118853 2146859 2197253 224376 2304645 23783 0.99 51 - 48 3.28 4.84 5.56 5.74 3.83 3.53 4.64 4.99 5.21 6.33 7.20 7.00 6.95 7.45 0.324 0.135 0.015 0.002 0.000 0.000 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 -.1959095 -.0946032 0970354 2569161 5736071 728706 7705638 3718645 3137616 5518541 6269665 6821147 9314298 1.144923 1.124321 1.143311 1.299798 5856144 6887796 8829897 1.048011 373213 1.539446 588722 1.175156 1.125115 379045 1.458168 524977 785433 2.018972 2.016871 2.06008 2.245867 _cons 1.08189 342909 3.16 0.002 3998581 763923 sigma_u sigma_e rho 99329817 33965371 89531395 t 10 11 12 13 14 15 16 17 18 F test that all u_i=O: Std Err = = t P>ltl [95% conf Interval] (fraction of variance due to u_i) F(5, 83) = 78 90.79 Prob > F = 0.0000 • Estimated results for Fixed Effects Model for the EKC (without time trend) Fixed-effects (within) regression Group variable: state Number of obs Number of groups = = 108 R-sq: obs per group: = avg = max = 18 18.0 18 within = 0.7408 between = 0.8248 overall = 0.8026 corr(u_i, xb) • Std Err t GDP_k GDP_ksq _cons 1.015438 -.0139572 -.6543284 0633616 0013608 3550032 sigma_u sigma_e rho 4.0852984 4732019 98676093 (fraction of variance due to u_i) F(5, 100) = 1.141146 -.0112574 0499879 8897304 -.0166569 -1.358645 Prob > F = 0.0000 57.78 Estimated results for Fixed Effects Model for the EKC (with time trend) within = 0.8470 between = 0.8999 overall = 0.8953 corr(u_i, Xb) = = 108 obs per group: avg = max = 18 18.0 18 Number of obs Number of groups Fixed-effects (within) regression Group variable: state R-sq: 0.000 0.000 0.068 142.90 0.0000 [95% conf Interval] coef 16.03 -10.26 -1.84 P>ltl = = C02 F test that all u_i=O: • F(2,100) Prob > F = -0.9275 F(4,98) Prob > F = -0.3254 Std Err coef GDP_k GDP_ksq t tsq _cons 7062673 -.0121102 1080351 - 0013725 8341525 0620134 0010808 029436 0014857 35558 sigma_u sigma_e rho 1.1688066 3672266 91015417 (fraction of variance due to u_i) 11.39 -11.21 3.67 -0.92 2.35 F(5, 98) = 79 77.97 P>ltl 0.000 0.000 0.000 0.358 0.021 135.65 0.0000 [95% Conf Interval] C02 F test that all u_i=O: t = 5832036 -.014255 0496203 -.0043208 1285156 8293309 -.0099654 1664499 0015758 1.539789 Prob > F = 0.0000 • • Estimated results for Fixed Effects Model for the EKC (N- shape) Fixed-effects (within) regression Group variable: state R-sq: within = 0.9132 between = 0.8868 overall = 0.8789 corr(u_i, • Number of obs Number of groups X b) obs per group: = avg = max = F(3,99) Prob > F = -0.8597 Std Err GDP_k GDP_ksq GDP_kcb _cons 2.354925 -.1036598 0012989 -1.643681 1023851 0064458 0000926 2181913 sigma_u sigma_e rho 2.3976862 27521337 98699621 (fraction of variance due to u_i) • • 80 23.00 -16.08 14.02 -7.53 130.83 P>ltl 0.000 0.000 0.000 0.000 18 347 0.00 [95% conf Interva coef F(5, 99) = t = = C02 F test that all u_i=O: = = 2.151771 -.1164496 0011151 -2.07662 2.558 -.090 00148 -1.2107 Prob > F = 0.00 • • Estimated results for extended model (with time effects) xtreg C02 GDP_k GDP_ksq FDI TRADE POP i.t, fe Fixed-effects (within) regression Group variable: state Number of obs Number of groups R-sq: obs per group: = avg = max = within = 0.9085 between = 0.2285 overall = 0.2581 corr(u_i, Xb) F(22,80) Prob > F = -0.5643 Std Err 108 = 18 18.0 18 36.11 0.0000 C02 coef GDP_k GDP_ksq FDI TRADE POP 8598346 -.0136298 51e-12 1.074421 -.0271261 0728483 001112 3.05e-12 4148518 0069955 11.80 -12.26 0.49 2.59 -3.88 0.000 0.000 0.623 0.011 0.000 7148618 -.0158428 -4 57e-12 2488395 -.0410475 1.004807 -.0114168 7.58e-12 1.900002 -.0132046 1778832 2949456 4864069 6021229 8833677 1.063925 1.133464 8085796 7073336 8832588 1.083741 1.115415 1.337087 1.434999 367659 1.418466 513844 1827481 1843335 1874875 195296 "069237 ?.2754 0.97 1.60 2.59 3.08 4.27 5.01 5.21 333 0.114 0.011 0.003 0.000 0.000 -.1857972 -.0718898 1132948 2F ·14 5415635 661781 8595189 9907744 1.295159 1.486367 56· 1.23 1.15c, 379653 56825 623859 1.873413 2.045379 2.024354 2.080056 2.258566 _cons 5.022612 7.206166 sigma_u sigma_e rho 3.7548662 31433471 99304074 t P>ltl [95% conf Interval] t ""' • 10 11 12 13 14 15 16 17 18 F test that all u_i=O: 471'-64 '4111 3.7~ ~7864 £.-t94364 2434639 2554914 269502 306714 3299868 3324467 3742203 3.15 3.54 4.45 4.37 4.96 4.68 4.14 4.27 4.05 0.002 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 6414839 7008006 383878 2599943 3868645 5992325 6069706 8007609 8246186 7109646 756876 7691215 1.097228 4.58 0.000 2.839058 ~4119 o.oon a.oon (fraction of variance due to u_i) F(S, 80) = 81 38.25 Prob > F = 0.0000 • Appendix E: Tests • F -test for Overall Significant regress GDP_k C02 source ' lOS 544.712647 829395721 1176.51185 107 10.9954378 coef GDP_k GDP_ksq _cons 8834554 -.0179444 532143 C02 source 0343336 0008909 1372764 2, Prob •;o~', = = GDP_ksq FDI TRADE 0.000 0.000 0.000 ss 8153783 -.0197109 1.259949 Total 1176.51185 107 10.9954378 GDP_k GDP_ksq FDI TRADE POP _cons Coef 1.024592 -.0206309 2.54e-11 5564778 -.0031355 8620072 test GDP_k GDP_ksq FDI Std Err .0360888 0008994 3.35e-12 1484046 0008098 2590935 TRADE 108 Number of obs = F( 5, 102) = 595.76 0.0000 Prob > F 0.9669 R-squared Adj R-squared = 0.9653 61797 Root MSE MS df t 28.39 -22.94 7.58 3.75 -3.87 3.33 POP GDP_k = GDP_ksq = FDI = TRADE = POP = constraint dropped 102) = 733.34 4, Prob > F = 0.0000 82 P>iti 0.000 0.000 0.000 0.000 0.000 0.001 [95% conf Interval] 9530095 -.0224149 1.87e-11 2621181 -.0047418 3480965 = = = = = = 108 656.76 0.0000 0.9260 0.9246 91071 [95% conf Interval] POP 227.511866 102 381887417 F( 25.73 -20.14 11.16 P>ltl 656.76 0.0000 1137.55933 38.9525165 1) 2) 3) 4) 5) t GDP_ksq Model Residual C02 I ( ( ( ( ( std Err Number of obs F( 2, 105) Prob > F R-squared Adj R-squared Root MSE GDP_k = GDP_ksq = F( regress I MS 1089.42529 87.0865507 C02 test GDP_k ( 1) ( 2) df 55 Model Residual Total GDP_ksq 1.096174 -.0188469 3.20e-ll 8508376 -.0015292 375918 9515325 -.016178 804337 • Hausman test coefficients - (b) (b-B) Difference (B) fixed GDP k GDP ksq 1.m 5438 - 0139572 B= Ho: Te~: GDP_k GDP_ksq FDI TRADE POP _It_2 _It_3 _It_4 _It_5 _It_6 _It_7 _It_8 _It_9 _It_10 _It_11 _It_12 _It_13 _It_14 _It_15 _It_16 _It_17 _It_18 Test: b inconsis~ent chi2(2) = Prob>ehi2 = Ho: s.E .0378665 0004934 1560851 0002644 = consis~ent under Ho and Ha; obtained from under Ha, efficient under Ho; obtained from difference in coefficients not ~reg ~reg sys~ema~ic (b-B)'[(V_b-V_B)A(-1)](b-B) 28.72 0.0000 - - Coefficients - (B) (b) fixed (b-B) Difference sqrt(diag(V_b-v_B)) s.E 1.106344 -.023028 l.OOe-11 -.3070483 -.0062667 2217277 3001093 4489065 5904926 916116 1.078778 1.12682 7453541 6519058 9689344 1.046935 1.07703 358721 61967 1.613268 674027 724959 -.2465091 0093982 -8.49e-12 381469 -.0208594 -.0438445 -.0051637 0375003 0116303 -.0327483 -.0148531 0066442 0632255 0554278 -.0856756 0368059 0383851 -.0216337 -.1846714 -.2456082 -.2555609 - 2111153 124949 001751 3.36e-12 7100419 012461 0363856 0532033 0753208 1161564 162219 1801806 1947367 1773579 209837 2761494 2621323 290391 3233541 4002936 4449011 4541187 5157746 8598346 -.0136298 Sle-12 1.074421 -.0271261 1778832 2949456 4864069 6021229 8833677 1.063925 1.133464 8085796 7073336 8832588 1.083741 1.115415 337087 1.434999 367659 1.418466 513844 B 8593529 - 0142216 sqr~(diag(v_b-v_a)) b = consistent under Ho and Ha; obtained from xtreg = inconsistent under Ha, efficient under Ho; obtained from xtreg difference in coefficients not systematic = (b-B)'((V_b-V_B)A(-1)](b-B) 59.93 = 0.0000 Prob>chi2 = chi2(5) (V_b-V_B is not positive definite) ~ 83 ... Curve Turning Point Income !~ ! Developing Economies Turning Point Income Developed Economies Environmental Decay Environmental Improvement j .= i I > =====> Per Capita Income Per Capita Income. .. rising of income per capita in the first stage of economic growth process When it reaches a certain income level so called turning point, environmental degradation lessens while per capita income. .. questions Some questions should be presumed in this thesis as following: Does the Environmental Kuznets curve actually exist in a group of six East Asian countries? Does income (GDP per capita)