Growing Together with Growth Polarization and Income Inequality

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1 Growing Together with Growth Polarization and Income Inequality Sudip Ranjan Basu, Ph.D. Economist, United Nations ESCAP UN DESA Expert Group Meeting on the World Economy (LINK Project) United Nations Headquarters October 2013, New York

2 UN SG s Global Call Equity and social justice Tackling inequality, eradicating poverty and promoting shared prosperity must be at the heart of the UN sustainable development agenda 2

3 Outline Stylized facts: Issues and Trends Database and Methodology Key results and analysis Conclusions and way forward 3

4 Stylized facts: Issues and trends 4

5 Tracking Inequality Research Gini-1912 Klein 1950 Mitra 1954 Tinbergen 1957 Tobin 1970 Atkinson 1970 UN MDG 2000 Kaldor 1957 Sen 1973 Milanovic 2002 Kuznets 1955 Singer 1949 UN 1949 Hirschman 1958 Chenery 1960 Kravis 1960 Scitovsky 1964 Ram 1979 Theil 1979 Shorrocks 1980 Maddison 1998 UN ESCAP 1998 Krugman 1995 X Sala I Martin 2006 Klein 2009 UN GA 2010, 2012 UN 2013 Stiglitz 2013 Source: SRBasu-2013, computed from Google Scholar site, accessed on 18 October 4 pm Bangkok, Thailand. 5

6 Global Output: A comparison GDP per capita, $PPP 2005[ normalization 1950=100] Global convergence: Moving up but still a long way to go Source: PW 8.0 data accessed on 10 October2013 6

7 It s a Billionaires World Comparing with developing world Billionaires net worth increasing significantly Several regions and LDCs worth less than billionaires Source: Forbes online, accessed on 18 October

8 Measuring inequality trends Gini index: Difference between early 1990s and late 2000s Note: Author s compilation of the two sources below, using gross income at the household level Source: The World Bank, Branco Milanovic 2013; Frederick Solt

9 Inequality promotes risks Social and economic inequalities can tear the social fabric, undermine social cohesion and prevent nations from thriving Societies where opportunities are scarce are vulnerable to upheaval and conflict Can jeopardize the well-being of large segments of the population through low earnings/wages, and leads to decrease in healthy life and development Vulnerable populations have lower levels of education, lack skills and abilities that can allow them to compete in labour market Structural barrier constraining domestic markets Can breed crime, disease and environmental degradation and hamper economic growth and thereby poverty reduction Inequality of opportunities impede development of capabilities If inequalities continue to widen, development may not be sustainable 9

10 Policies to promote equity A suggested framework Forward-looking macroeconomic policies Institutional and governance policies Social welfare programmes -Provisioning of quality basic public services -Investing in people, their growth and capabilities -Employment generation, sufficient, productive and decent -Financial Market Policies -Trade Polices -Institution Building Polices -Promoting women s empowerment -Strengthening regulations and judiciary -Reforming public finance system including income tax base/ tax administrations & corporate tax -Welfare enhancing programmes for education, health, food, housing and social security/legislations -Employment guarantee programmes -Minimum wages -Land reforms - 10

11 Types of Inequality Social and economic inequalities Social: Education & health services, wages and land assets Income: GDP per capita, or household income/expenditure Spatial inequalities Inequalities between regions, subregions and countries Inequalities within countries at subnational level Rural and urban areas Horizontal inequalities Social groups such as youth, older persons, indigenous persons, Also, minorities, persons with disabilities and migrants workers 11

12 Database and Methodology 12

13 UN country groupings Selected 157 economies from all UN regional commissions ECE (Europe) Austria Bulgaria Croatia Denmark France Germany Greece Hungary Israel Italy Norway Slovenia Spain Switzerland United Kingdom ESCAP (Asia-Pacific) Australia Bangladesh China India Indonesia Iran Pakistan Philippines Korea, Rep Russian Federation Thailand Turkey ECA (Africa) Angola Botswana Cameroon Djibouti Ethiopia Ghana Kenya Lesotho Malawi Nigeria Senegal Sierra Leone South Africa Zimbabwe ECLAC (Latin America & Caribbean) Argentina Brazil Canada Chile Colombia Costa Rica Dominican Republic Ecuador Mexico Paraguay Peru Uruguay USA Venezuela ESCWA (Western Asia) Qatar Morocco Saudi Arabia Jordan Lebanon Egypt Oman Tunisia Syria Bahrain Kuwait Yemen Note: Gini index information available for 147 countries and GDP per capita for 157 countries LDCs: 34 countries; Emerging: 25 countries, Developing: 83 countries; Developed: 34; Transition: 15 13

14 Methodology Gini coefficient of inequality Generalized entropy class (GE) to allow inequality across groups to be broken down into within group inequality and between group inequality Polarization index (Basu 2009) as ratio of between group inequality in total inequality (within group inequality + between group inequality) Composite measure Composite index (Basu, Klein and Nagar 2005; and Nagar and Basu 2002), a weighted average measure of standardized indicators for each country for each period defined Using a multivariate statistical method of latent variable Higher values of indices imply higher/better quality Regression analysis Dep. var: Gini index, Indep. vars: Institutions, policies, geography, etc OLS, 2SLS, Panel Data/GMM 14

15 Human capital and Policies Measuring by using indicators Human Capital Adult literacy, Combined enrolment, Mean years of schooling & education expenditure Macroeconomic Policies: Inflation, Real exchange rates, Current account & public debt Financial Market Policies: Liquid Liabilities, Financial System Deposits and Private Credit Trade Policies: Tariff, Peaks (international & national peaks) & Specific rates 4 indicators to reflect the effective foreign market access Institutions: Economic (Law & Order, Corruption, Regulations), Social (Civil liberties, Women s rights & empowerment, and Political (Political rights, democracy, decentralisations) Institutions 23 Indicators to capture comprehensive nature of institutions 15

16 Databases GDP per capita, expenditure based: The Next Generation of the Penn World Table (Feenstra, Robert C., Robert Inklaar and Marcel Timmer, 2013) UN National accounts statistics, World Bank ICP, PPP exchange rates Gini index: Description of all the Ginis dataset, Branko Milanovic, the World Bank, Summer 2013 Standardizing the World Income Inequality Database, Frederick Solt, 2012 Compilation by author, based on gross income per household database Composite measures: PRS ICRG, POLCON Henisz Dataset, Freedom House, CIRI Human Rights, PRIO, Polity IV Project and other sources, UN Agencies Time series: 1950 to 2011 (Inequality/Polarization analysis) (Regression analysis) 16

17 Key results and analysis 17

18 1:Global Inequality 18

19 Inequality trends: Global GDP per capita, computing Gini Index and Theil entropy measure Inequality remains elevated globally over the decades Note: 1950 to 1959: About 70 countries, 1960 to 1989: About 126 countries, 1990 to 2011: 147 countries, of which developing 73, developed 34, Emerging 25, Transition 15. Source: SRBasu

20 Inequality trends: Developing GDP per capita, computing Gini Index and Theil entropy measure Inequality shows increasing trends in developing countries Note: 1950 to 1959: About 70 countries, 1960 to 1989: About 126 countries, 1990 to 2011: 147 countries, Developing: Developing 73, Emerging 25 and Transition 15= Total 113 countries. Source: SRBasu

21 2: Regional Inequality 21

22 Inequality trends: Regions GDP per capita, computing Gini Index Inequality shows increasing trends across regions Note: 1950 to 1959: About 70 countries, 1960 to 1989: About 126 countries, 1990 to 2011: 147 countries ECA= 44, ECE=36, ECLAC=27, ESCAP=32, ESCWA=8 Source: SRBasu

23 Inequality trends: Developing Regions GDP per capita, computing Gini Index Asia-Pacific shows increasing inequality trends over the past decades, and remains stubbornly high in Africa Note: 1950 to 1959: About 46 countries, 1960 to 1989: About 99 countries, 1990 to 2011: 113 countries Developing: Developing 73, Emerging 25 and Transition 15= Total 113 countries ECA=44, ECE=7, ECLAC=25, ESCAP=29, ESCWA=8 Source: SRBasu

24 3: Estimating Polarization 24

25 Polarization: Divide continues GDP per capita, based on Theil Entropy measure Income gap is increasing between developed and developing countries Developed vs Developing Note: 1950 to 1959: About 46 countries, 1960 to 1989: About 99 countries, 1990 to 2011: 113 countries Developing: Developing 73, Emerging 25 and Transition 15= Total 113 countries Source: SRBasu

26 Polarization: Asia-Pacific GDP per capita, based on Theil Entropy measure [ UN ESCAP] Income gap is declining between Asia-Pacific and rest of the world Asia-Pacific Developing vs Rest of World Note: 1950 to 1959: About 46 countries, 1960 to 1989: About 99 countries, 1990 to 2011: 113 countries Developing: Developing 73, Emerging 25 and Transition 15= Total 113 countries, ECA=44, ECE=7, ECLAC=25, ESCAP=29, ESCWA=8 Source: SRBasu

27 Polarization: Africa GDP per capita, based on Theil Entropy measure [ UN ECA] Income gap is increasing between Africa and rest of the world Africa vs Rest of World Note: 1950 to 1959: About 46 countries, 1960 to 1989: About 99 countries, 1990 to 2011: 113 countries Developing: Developing 73, Emerging 25 and Transition 15= Total 113 countries, ECA=44, ECE=7, ECLAC=25, ESCAP=29, ESCWA=8 Source: SRBasu

28 Polarization: Americas GDP per capita, based on Theil Entropy measure [ UN ECLAC] Flattening of income gap between Americas and rest of the world Americas Developing vs Rest of World Note: 1950 to 1959: About 46 countries, 1960 to 1989: About 99 countries, 1990 to 2011: 113 countries Developing: Developing 73, Emerging 25 and Transition 15= Total 113 countries, ECA=44, ECE=7, ECLAC=25, ESCAP=29, ESCWA=8 Source: SRBasu

29 Polarization: Europe GDP per capita, based on Theil Entropy measure [ UN ECLAC] Income gap remains between Europe and rest of the world Europe vs Rest of World Note: 1950 to 1959: About 46 countries, 1960 to 1989: About 99 countries, 1990 to 2011: 113 countries Developing: Developing 73, Emerging 25 and Transition 15= Total 113 countries, ECA=44, ECE=7, ECLAC=25, ESCAP=29, ESCWA=8 Source: SRBasu

30 Polarization: Western Asia GDP per capita, based on Theil Entropy measure [ UN ESCWA] Western Asia vs Rest of World Note: 1950 to 1959: About 46 countries, 1960 to 1989: About 99 countries, 1990 to 2011: 113 countries Developing: Developing 73, Emerging 25 and Transition 15= Total 113 countries, ECA=44, ECE=7, ECLAC=25, ESCAP=29, ESCWA=8 Source: SRBasu

31 4: Inequality, but why? 31

32 Human capital Knowledge development Index, higher value better [ World] Better human capital remains key to addressing inequality 70 Gini= *Knowledge (p=0.38) NAM ZAF PRT BOLZWE GTM BRA BWA AGO HND COL PRY PAN ZMB ECU CHL JAM DEU PHL PER LTU LVA FRA GBR NGA KENSLV DOM MEX LKA DNK USA ARG THA HUN RUS MLT GRC ITA AUT SGP ISR NZL SWE FIN NOR NPL NLD KHM COG CRI GEO LBN POL AUS IRL BEL CANCHE BGD CIV CMR VEN IRNARM ISL MOZ MYS GAB EST SEN CHN URY TUR KGZ CZE SVN LUX MAR ESP GHA TUN MDA UZBJOR JPN TZA BEN VNM TTO YEM ETH EGY SYR SVK MNG TGO IND IDN AZE IRQTKM BIH TJK KAZ UKR HRV BGR KOR ALB PAK BLR Knowledge development Source: SRBasu,

33 Human capital, Developing Knowledge development Index, higher value better Investment in human capital is the most important factor for tackling scourge of inequality in developing countries 70 Gini= *Knowledge (p=0.03) NAM ZAF BOL ZWE GTM BRA BWA AGO HND COLPRY PAN ZMBECU CHL JAM PHL PER NGA KEN SLV DOM MEX LKA ARG THA RUS NPL KHM COG CRI GEO LBN BGD CIV CMR VEN IRNARM MOZ MYS GAB SEN CHN URY TUR KGZ MAR GHA TUN MDA UZBJOR TZA BEN VNM TTO YEM ETH EGY SYR MNG TGO IND IDN AZE IRQTKM BIH TJK KAZ UKR HRV ALB PAK KOR SGP Source: SRBasu, 2013 BLR Knowledge development 33

34 Policy variability Policy variability, based on four measures, higher value worse [World] Reducing policy uncertainties make a difference for inequality reduction 70 Gini= *policy (p=0.10) ZAF NAM VCT PRT COM LSO BRA BOL BWAGTMCPV ZWE BLZ AGO PAN COL BHS HNDPRY STP DEU SWZ JAM CHL ECU FRA PHL FJICAF GMB ZMB LKAUSA GBR DNK LTU LVA MUS AUT SLV MEX PER BFA SUR SGP FINSWE NORHUN MLT DOM KEN SLE LCA NGA THA NZL ITA ARG RUS LBN ISRNPL MWI GRC NLD CHE POLAUS IRLCAN BEL LBR BGD MYS IRN VEN NER BTN MDV CRI COG GEO MDG CIV CMRARMKHM RWA ISL CZE TUR SVNGIN MLI KGZ SEN ESTLUX ESP TCD TUN MARDJI UGA CHN MOZ MDAURY GAB BRB DMA UZB JOR MRT JPN GHA GNB TTO SYR UKR TKM ETH EGY TZA IND SVK LAO BEN BDI VNM YEM IDNIRQ AZE TJK TGO BIH KOR BGR HRV MNG KAZ PAK ALB Source: SRBasu, 2013 BLR Policy Variability 34

35 Policy variability, Developing Policy variability, based on four measures, higher value worse Better and improved policymaking pays off significantly in developing countries for promoting equity 70 Gini= *policy (p=0.05) ZAF NAM VCT COM LSO BRA BOL BWAGTMCPV ZWE BLZ AGO PAN COL BHS HNDPRY STP SWZ JAM CHL ECU PHL FJICAF GMB ZMB LKA MUS SLV MEX PER BFA SUR SGPDOM KEN SLE LCA NGA THA ARG RUS LBN NPLMWI LBR BGD MYS IRN VEN NER BTN MDV CRI COG GEO MDG CIV CMRARMKHM RWA TURGIN MLI KGZ SEN TCD TUN MARDJI UGA CHN MOZ MDAURY GAB BRB DMA UZB JOR MRT GHA GNB TTO SYR UKR TKM ETH EGY TZA LAO BEN BDI VNM IND YEM IDNIRQ AZE TJK TGO BIH KORHRV MNG KAZ PAK ALB Source: SRBasu, 2013 BLR Policy Variability 35

36 Institutions variability. Institutions variability, based on three measures, higher value worse [World] Also, institution building efforts need to continue 70 Gini= *Institutions (p=0.57) ZAF NAM PRT LSO BOL BWABRA GTM COL PRY PAN HND ZMB DEU SWZ JAM ECU CHL FJICAF FRA USA LTUBFA DNK GBR LVA PHL GMB MUSGP HUN ITA AUT DOM SLV LKAMEX PER KEN SLE NOR RUS NGA MWI NZL FINSWE THA GEO GRC CRI NPL CAN CHE CMR AUS MYS IRL POL MDG BELCIV BGD IRN ARMVEN KHM COG NER CZE GIN KGZ TUR SVN EST UGA CHN MLI MOZ URY DJI ESP GAB SEN JOR TUN MAR MDA JPN UZB GHA TCD GNB MRT TTO TZA VNM SYRLAO BEN TKM UKR SVK KAZ YEMIND AZE ETH EGY IRQ IDN MNG KOR TGO TJK BGR HRV PAK ALB ZWE BDI AGO RWA Source: SRBasu, 2013 BLR Institutions Variability 36

37 Institutions variability, Developing Institutions variability, based on three measures, higher value worse Institution building must continue to be a focus in confronting damaging effects of inequality in developing countries 70 Gini= *Institutions (p=0.40) ZAF NAM LSO BOL BWABRA GTM COL PRY PAN HND ZMB SWZ JAM ECU CHL FJICAF BFA PHL MUSGP DOM SLV LKAMEX PER KEN RUS THA MWI GEO CRI NPL CMR MYS MDGCIV BGD IRN ARMVEN KHM COG NER GIN KGZ TUR UGA CHN MLI MOZ URY GAB SEN DJI JOR TUN MAR MDA UZB GHA TCD GNB MRT TTO TZA VNM SYRLAO BEN TKM UKR KAZ YEMIND AZE ETH EGY IRQ MNG KOR TGO TJK PAK ALB GMB SLE NGA IDN HRV ZWE BDI AGO RWA Source: SRBasu, 2013 BLR Institutions Variability 37

38 Conclusions and way forward 38

39 1: Key messages 39

40 Policy messages Global analysis Income inequality increasing across countries and within countries in many regions Subregional variations remain critical Polarization among developing and developed countries continues Income gap across regions show disturbing trends: Asia-Pacific declining Africa significantly increasing Western Asia increasing recently Europe some increase Americas low Investment in education is key to reduce income inequality Policies and institutions need to be strengthened 40

41 2: Suggested research tasks 41

42 Inequality research Data and policy research Inequality computation Gini index (1912) got several limitations though most widely available Palma measure (2006): Ratio of top 10% to ration of poorest 40% of population Still lacks to compute inequality in education, health and other forms of asset globally in the time series format Measurements and comparability of income Gini inequality measures due to definition, sources and household survey information Need to formulate statistical framework to standardised, UN Task Team on inequality: ECE,ESCAP,DESA,UNICEF, UNRISD, UN Women Impact assessment of inequality Need model framework to capture and analyse impact of income as well as other forms of social inequalities Inequality, macro modelling and sustainable development 42

43 3:Global Agenda on Inequality 43

44 Equality for shared prosperity Realizing the Future We Want for All A moral duty, a political necessity, and an imperative for the due protection of human rights ESCAP/ADB/UNDP Asia-Pacific Regional MDG Report 2012/13 Inequality issue was one of the key policy message that came out from Asia-Pacific sub-regional stakeholders consultations on post-2015 development agenda The Secretary-General's High-Level Panel of eminent persons on the Post-2015 Development Agenda, noted that Yet inequality remains and opportunity is not open to all. If inequalities continue to widen, development may not be sustainable Reducing inequality will need great transformative change Globally (in) equity is emerging as a central plank in discussions on the United Nations post-2015 development agenda 44

45 References Milanovic, Branko. DESCRIPTION OF ALL THE GINIS DATASET (2013), World Bank, Research Department, version Summer.. Available for download at Basu, Sudip Ranjan (2009): Comparing China and India: Is the dividend of economic reforms polarized?, European Journal of Comparative Economics, 6(1): 57-99; June. Basu, Sudip Ranjan, Lawrence R. Klein and A.L. Nagar (2005): Quality of Life: Comparing India and China, Project LINK UN DESA Expert Group Meeting on the World Economy, United Nations Office, Geneva, November. Nagar, A.L. and Sudip Ranjan Basu (2002): Weighting Socio-economic Indicators of Human Development: A Latent Variable Approach, Handbook of Applied Econometrics and Statistical Inference, Marcel Dekker, New York. Solt, Frederick (2009). Standardizing the World Income Inequality Database. Social Science Quarterly, 90(2): Available for download at SWIID Version 4.0, released September Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2013), "The Next Generation of the Penn World Table. Available for download at United Nations (2013): A NEW GLOBAL PARTNERSHIP: ERADICATE POVERTY AND TRANSFORM ECONOMIES THROUGH SUSTAINABLE DEVELOPMENT, The Report of the High-Level Panel of Eminent Persons on the Post-2015 Development Agenda 45

46 Thank you Phone:

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