Leaving no one behind in Asia and the Pacific

Transcription

1 Leaving no one behind in Asia and the Pacific Addis Ababa, April 18 20, 2018 Predrag Savic, ESCAP POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 1

2 Outline 1. Outline 2. Context 3. Poverty in Asia and the Pacific 4. Inequality in Asia and the Pacific 5. Identification of those left behind 6. Average progress conceals those left behind 7. Policy options POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 2

3 Context Leave no behind a rallying cry of the Sustainable Development Goals and a critical part of Agenda 2030 Relevance for the Third UN decade for the Eradication of Poverty Plan of Action Matrix (Thematic Areas 1, 3, 5, 7, 8) POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 3

4 Poverty in Asia and the Pacific POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 4

5 ESCAP region still home to almost half of the worlds poor SHARE OF GLOBAL POPULATION LIVING ON LESS THAN $1.90 PER DAY, 2013 Latin America and the Caribbean 4% Rest of the world 1% Asia and the Pacific 43% Sub-Saharan Africa 51% Eastern Europe and Central Asia 1% POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 5

6 Where do the poor live in Asia and the Pacific? SHARE OF ASIA-PACIFIC POPULATION LIVING ON LESS THAN $1.90 PER DAY, 2013 East and North-East Asia 6% South-East Asia 11% North and Central Asia 5% Pacific island developing States 1% South and South-West Asia 77% POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 6

7 East Asia POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 7

8 South Asia POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 8

9 Asia and the Pacific poverty Shifts in poverty in Asia and the Pacific People living in poverty (millions) USD 3.10 USD Proportion of population in Asia-Pacific living in poverty (%) SSWA ENEA SEA NCA Pacific % of population Source:United Nations ESCAP Statistical Yearbook for Asia and the Pacific POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 9

10 Inequality in Asia and the Pacific POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 10

11 Income Inequality by Region 60 Gini coefficient, 1990 and Gini index Asia-Pacific Europe Western Asia Africa Latin America and the Caribbean Note: Regional Gini, population weighted average POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 11

12 Income Inequality in Asia and the Pacific POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 12

13 Wealth inequality 3000 Numbers of billionaires & their net worth by region, , No. of Billionaires Net worth Billion ($) 2, ,712 Numbers Africa Western Asia Latin America and the Caribbean Europe Asia-Pacific North America Source: ESCAP, based on Forbes online(accessed in January 2018). POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 13

14 Who are those left behind? POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 14

15 Background 21 countries in Asia and the Pacific For 11 countries, surveys available in two points in time Nationally representative household surveys: DHS Demographic and Health Survey MICS - Multiple Indicator Cluster Surveys POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 15

16 Background 15 Opportunities -Access to a good or service, which society accepts should be universal. Circumstancesused to determine groups of the furthest behind: Individual, household, geographic characteristics outside individual s control, for example: gender, wealth, geographic location, etc. Ideally, circumstances should not determine an individual s access to opportunities. POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 16

17 Classification Tree The primary goal of the analysis undertaken is to identify the groups with the lowest and highest access to opportunities A tree classification method is an algorithm that estimates the accessibility by partitioning the sample into different groups based on the circumstances chosen. Opportunities: professional help during childhood, contraception, children enthropometrics, sec and higher education, access to finance, clean fuels, electricity, clean water, safe sanitation. POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 17

18 Identifying the Furthest Behind Example of secondary education attainment in Mongolia, using the tree classification 100% 90% Top 60 Size: 61% Females Males Females in top 60 households Size: 32% Secondary education attainment rates 80% 70% 60% 50% 40% 30% Population Size: 100% Bottom 40 Size: 39% Males in top 60 households Size: 29% People in bottom 40 urban households Size 14% Females in bottom 40 rural households Size: 12% 20% Rural Size: 25% Males in bottom 40 rural households Size: 13% 10% Source: SDD elaboration based on DHS and MICS data, latest year POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 18

19 Identifying the Furthest Behind Example of stunting prevalence in Pakistan, using the tree classification Stunting prevalence rate 70% 60% 50% 40% 30% Population Size 100% Mother's Education at Primary level Size: 72% Bottom 40 Size: 40% Top 60 Size: 32% Mother's Education at Secondary level Boys in Bottom 40 households whose mother has Primary education Size: 20% Girls in Bottom 40 households whose mother has Primary education Size: 20% Children in urban and Top 60 households whose mother has Primary education Size: 14% Children in rural and Top 60 households whose mother has Primary education Size: 19% Children whose mother has Secondary education Size: 19% 20% Mother's Education at Secondary or Higher level Size: 28% Mother's Education at Higher level Children whose mother has Higher education Size: 9% 10% Source: SDD elaboration based on DHS and MICS data, latest year POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 19

20 Inequality in Secondary Education Attainment 100 Individuals aged 20 to 35 years of age, latest year Average attainment rate Group attainment rate (highest) Group attainment rate (lowest) 20 0 Kazakhstan Armenia Kyrgyzstan Philippines Mongolia Tajikistan Turkmenistan Thailand Indonesia Viet Nam Vanuatu Pakistan Timor Leste Bangladesh Lao PDR India Afghanistan Bhutan Myanmar Cambodia Maldives Attainment rate (% ) Source: SDD elaboration based on DHS and MICS data, latest year POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 20

21 Inequality in access to nutrition (stunting) Gaps between best of and worst off groups Source: SDD elaboration based on DHS and MICS data, latest year POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 21

22 Characteristics of those furthest behind/ahead FURTHEST BEHIND FURTHEST AHEAD Count Count Circumstances (times) Circumstances (times) Bottom 40 of wealth distribution 80 Top 60 of wealth distribution 69 Lower and primary education 74 Secondary and higher education 53 Female 63 Male 50 Living in a rural area 42 Living in an urban area 46 Age Age Male 16 Female 17 Age Age Source: SDD elaboration based on DHS and MICS data, secondary education, latest year POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 22

23 Average progress over time conceals detailed picture - Secondary education Source: SDD elaboration based on DHS and MICS data, secondary education, latest year POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 23

24 Average progress over time stunting Source: SDD elaboration based on DHS and MICS data, secondary education, latest year POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 24

25 D-index The dissimilarity index, or D-index, measures how all different groups of fare in terms of accessing a certain opportunity. = ( ) For example, two countries with identical average rates may have a very different D-indexes depending on how equitably access to an opportunity is distributed. Takes values from 0-1, similar to Gini Can be decomposed POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 25

26 D-index -ESCAP POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 26

27 Shapely decomposition What is the marginal contribution of each circumstance to inequality of opportunities secondary education? POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 27

28 Shapely decomposition What is the marginal contribution of each circumstance to inequality of opportunities stunting? POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 28

29 Ethnicity, Religion & Language - Common identity: affects composition of furthest behind groups -11 MICS + DHS India -In Turkmenistan, 65% urban, top 60 Turkmen-speaking completed secondary, 78% urban, top 60 Uzbek-speaking -In Lao PDR, ethnic Lao 3 x more likely than minor ethnicities to access clean fuels -In Sri Lanka, 58% Christian, Hindu and Muslim younger and older males are employed full time, compared with 35% Buddhists -In India, Scheduled caste status is critical in determining secondary education attainment, incidence of stunting, access to clean fuels, safe sanitation and bank account ownership POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 29

30 Relevance for Policymaking 1. Furthest behindare hardest to identify: need better data 2. Compounding factors: need interministerial and multi-stakeholder collaboration 3. Economic growth is not enough: need social protection and investment in quality services POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 30

31 Policy Optionsand Reccommendations Better data and research Political commitment Public support & trust in institutions Multi ministerial & stakeholder collaboration Strengthen social protection Reducing poverty and inequality requires Decent work creation and labourmarket interventions Tax policies Understanding the impact and drivers Human rightsbased approach POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 31

32 Thank you! POVERTY AND INEQUALITY IN ASIA AND THE PACIFIC 32