The Evolution of Global Inequalities: the impact on politics and the - PowerPoint PPT Presentation

Hosted by the International Inequalities Institute The Evolution of Global Inequalities: the impact on politics and the economy Professor Branko Milanovic Senior Scholar, Luxembourg Income Study Centre Visiting Presidential Professor, Graduate Centre, City University of New York Professor Mike Savage Chair, LSE Hashtag for Twitter users: #LSEBranko

Inequality in the age of globalization Branko Milanovic Spring/Summer 2017 Branko Milanovic

Largely based on: 3

Brief structure of the talk • Global inequality: in the past and now • Technical problems of measurement • How the world has changed between 1988 and 2013 • [Political implications of the changes] • [Kuznets waves?] • Issues of justice, politics and migration Branko Milanovic

1. Global inequality: key developments Branko Milanovic

Global and US Gini over two centuries 75 Lahoti, Jayadev, Reddy Global (LM) 70 65 Global (BM) 60 55 50 US inequality 45 40 35 30 1800 1850 1900 1950 2000 2050 Branko Milanovic History…/the past.xls

La longue durée: From Karl Marx to Frantz Fanon and back to Marx? Location 80 Forecast 60 Gini index Location Location 40 Location 20 Class Class Class 0 1850 2011 2050 Branko Milanovic History../the_past.xls

• In the long ‐ run inequality is determined by the spread of the technological revolutions: the West in the 19 th century, Asia today • In the medium ‐ run global inequality is determined by: • What happens to within ‐ country income distributions? • Is there a catching up of poor countries? • Are mean incomes of populous & large countries (China, India) growing faster or slower that the rich world? Branko Milanovic

0.75 Three concepts of inter ‐ national income inequality, 1952 ‐ 2015 Global inequality 0.70 Population ‐ weighted inter ‐ country inequality 0.65 0.60 Gini 0.55 Unweighted inter ‐ country inequality 0.50 0.45 All in 2011 PPPs 0.40 1940 1950 1960 1970 1980 1990 2000 2010 2020 Branko Milanovic Interyd\...3concepts..xls

Key developments, 1988 ‐ 2011 16.0 4.5 4.0 14.0 3.5 12.0 3.0 Top 1% share (left axis) 10.0 Mean to median ratio 2.5 (right axis) 8.0 2.0 6.0 1.5 4.0 1.0 2.0 0.5 0.0 0.0 1988 1993 1998 2003 2008 2011 Branko Milanovic

Gini and percentage of world population with income less than 1/2 global median, 1988 ‐ 2011 30 70 69 25 68 Percentage of relatively poor 67 20 66 Global Gini 15 65 64 10 63 62 5 61 0 60 1988 1993 1998 2003 2008 2011 Axis Title % ppl under 1/2 median Gini with 2011 PPPs Summary.xls

Global income distribution in 2011 with 2011 PPPs .8 Global median .6 Absolute poverty Global density mean .4 Median of WENAO .2 91% 50% 10% 73% 0 600 2100 5500 14600 log of annual PPP real income twoway (kdensity loginc_11_11 [w=popu] if loginc_11_11>2 & bin_year==2011, bwidth(0.2)) , legend(off) title(Global income distribution in 2011 with 2011 PPPs) xtitle(log of annual PPP real income) ytitle(density) xlabel(2.8"600" 3.3"2100" 3.74"5500" 4.2"14600", labsize(small) angle(90)) Using combine88_11.dta

Large gaps in mean country incomes raise two important issues • Political philosophy: is the “citizenship rent” morally acceptable? Does global equality of opportunity matter? • Global and national politics: Migration and national welfare state • (will address both at the end) Branko Milanovic

Different countries and income classes in global income distribution in 2008 90 100 USA percentile of world income distribution 80 Brazil 70 60 50 Russia 40 30 China 20 India 10 Branko Milanovic 1 1 20 40 60 80 100 country percentile From calcu08.dta

Different countries and income classes in global income distribution in 2011 100 USA percentile in global income distribution 80 Russia Brazil 60 40 India 20 0 1 20 50 80 100 percentile of country's income distribution India with 2011 income data Branko Milanovic Final11.dta using michele_graph.do but with india consumption replaced by india income

Why international aid is unlikely to involve regressive transfers? 100 90 Netherlands percentile of world income distribution 80 70 60 50 Guinea 40 30 Mali 20 Tanzania 10 Madagascar 1 1 20 40 60 80 100 percentile of country's income distribution

2. Technical issues in the measurement of global inequality Branko Milanovic

Three important technical issues in the measurement of global inequality • The ever ‐ changing PPPs in particular for populous countries like China and India • The increasing discrepancy between GDP per capita and HS means, or more importantly consumption per capita and HS means • Inadequate coverage of top 1% (related also to the previous point) Branko Milanovic

The issue of PPPs Branko Milanovic

The effect of the new PPPs on countries’ GDP per capita gain compared to 2005 ipc--normalized by the us level 150 SAU 100 SDN SDN ZMB JOR IDN GHA MNG SUR OMN KWT EGY PAK KAZ FJI BGD AZE QAT NPL YEM DZA CPV 50 CIV LAO THA MAC MDG LKA GTM PHL BRN VNM NER MAR RUS MLI VEN GNQ COG TCD ARE HTI MYS MDV IND MRT TGO KEN LSO NGA MDA AGO NAM BRA KGZ CHN SLE UGA SWZ LVA SGP BDI CHL MNE TUR NOR CMR PRY GEO GIN KHM BTN UKR BIH URY HUN CHE LUX SEN BGR MEX DNK ARM COL EST BLR LTU TTO DOM MKD ITA CAF ETH BOL TUN ZAF NZL MWI BEN BLZ PER MUS HRV MLT ECU AUS HND SLV GNB NIC SRB POL FRA BEL TJK SVK FIN JAM PRT GRC ESP TWN GAB DEU SWE AUT RWA CRI IRL USA 0 BFA TZA PAN NLD CAN ISL SVN ISR DJI ALB CZE HKG JPN MOZ GBR KOR LBR BWA CYP GMB BHS -50 COM 50000 100000 150000 gdppc in 2011ppp Branko Milanovic C:\Branko\worldyd\ppp\2011_icp\define

The effect of new PPPs Country GDP per capita GDP per capita increase (in %) increase population ‐ weighted (in %) Indonesia 90 ‐‐‐ Pakistan 66 ‐‐‐ Russia 35 ‐‐‐ India 26 ‐‐‐ China 17 ‐‐‐ Africa 23 32 Asia 48 33 Latin America 13 17 Eastern Europe 16 24 WENAO 3 2

Use of 2011 PPPs reduces global inequality by about 3 Gini points but leaves the trends the same 74.0 72.0 70.0 68.0 66.0 64.0 62.0 60.0 58.0 1988 1993 1998 2003 2008 2011 Gini with 2011 PPPs Gini with 2005 PPPs Branko Milanovic Using summary_data.xls

The gap between national accounts and household surveys Branko Milanovic

Global Gini with different definitions of income 74 72 Step 2 Step 1 70 HH survey 68 NA consumption 66 GDP per capita 64 62 60 1988 1993 1998 2003 2008 Summary_data.xls Branko Milanovic

Step 1 driven by low consumption shares in China and India (although on an unweighted base C/GDP decreases with GDP) C/GDP from national accounts in year 2008 1.2 share of consumption in GDP 1 USA .8 .6 India .4 China .2 1000 10000 50000 GDP per capita in ppp twoway scatter cons_gdp gdpppp if group==1 & cons_gdp<1.4 [w=totpop], xscale(log) xtitle(GDP per capita in ppp) xlabel(1000 10000 50000) ytitle(share of consumption in GDP) title(C/GDP from national accounts in year 2008) Branko Milanovic using final08,dta

Step 2. No clear (weighted) relationship between survey capture and NA consumption survey mean/consumption from national account in year 2008 1.2 China survey mean over NA consumption 1 .8 USA .6 .4 India .2 1000 10000 50000 GDP per capita in ppp twoway scatter scale2 gdpppp if group==1 & scale2<1.5 [w=totpop], xscale(log) xtitle(GDP per capita in ppp) xlabel(1000 10000 50000) ytitle(survey mean over NA consumption) title(survey mean/consumption from national account in year 2008) Branko Milanovic

The issue of top underestimation Branko Milanovic

Rising NAC/HS gap and top underestimation • If these two problems are really just one & the same problem. • Assign the entire positive (NA consumption – HS mean) gap to national top deciles • Use Pareto interpolation to “elongate” the distribution • No a priori guarantee that global Gini will increase Branko Milanovic

Top 1% share in US: Comparison between WTID fiscal data and factor income from LIS (both run across households/fiscal units; K gains excluded) 20 WTID data 18 16 14 12 LIS ‐ CPS data 10 8 6 4 2 0 1975 1980 1985 1990 1995 2000 2005 2010 2015 usa07_13.xls Branko Milanovic

But the rising gap between fiscal and HS income is not universal Top 1% share Norway: Comparison between WTID fiscal data and factor income from LIS (both run across households/fiscal units; K gains 14.0 excluded) WTID data 12.0 10.0 8.0 LIS data 6.0 4.0 2.0 0.0 1975 1980 1985 1990 1995 2000 2005 2010 2015 Branko Milanovic

With full adjustment (allocation to the top 10% + Pareto) Gini decline almost vanishes 80 Top ‐ heavy allocation of 78 the gap + Pareto adjustment 76 74 Survey data only 72 70 68 66 64 1988 1993 1998 2003 2008 Branko Milanovic Summary_data.xls

3. How has the world changed between the fall of the Berlin Wall and the Great Recession [based on joint work with Christoph Lakner] Branko Milanovic