Data disaggregated by income and/or other dimensions of poverty

Transcription

1 ESA/STAT/AC.320/8 Expert Group Meeting on Data Disaggregation June 2016 New York Data disaggregated by income and/or other dimensions of poverty By Leonardo Athias 2016

2 Expert Group Mee,ng on Data Disaggrega,on Session 5 Data disaggregated by income and/or other dimensions of poverty Concrete examples of current work and specific strategies Monday, 27 June 2016 Leonardo Athias Brazilian InsBtute of Geography and StaBsBcs - IBGE

3 1) Problem statement 2) Concrete examples 3) Methodological challenges Contents 4) Iden,fica,on of priority issues to be addressed for future guidance for SDG follow up and review

4 1) Problem statement Brazil is a big middle income country with high levels of inequality HDR, 2015, p. 217 Along with urban/rural, gender, racial, and regional inequali,es, income is one of the main inequali,es if not the most studied 8.5 m km

5 2) Concrete examples: income disaggrega,on Educa,onal achievement Average years of schooling of people 25 y.o.+ per quin,les of average monthly household per capita income - Brazil st quin,le 2 nd quin,le 3 rd quin,le 4 th quin,le 5 th quin,le Source: Source: IBGE, PNAD

6 2) Concrete examples: income disaggrega,on Dwelling characteris,cs Propor,on of overcrowded households, total and 1 st quin,le of average monthly household per capita income - Brazil /2014 Note: overcrowding is defined as >3 persons per dormitory. Source: IBGE, PNAD 1 st quin,le

7 2) Concrete examples: MDG monitoring MDG na,onal monitoring reports disclosed UN indicators and Na,onal indicators for Goal 1 such as: Na,onal income concentrated by 20% richest Income concentra,on and Gini index 20% poorest 20%- 80% middle 20% richest Gini index Percentage of total income Middle income group Middle income group (+6.9 p.p.) concentrated most of the 8% lost by 20% richest in the period Data source: IBGE, PNAD Source: 5 th MDG na,onal monitoring report,

8 2) Concrete examples: MDG monitoring MDG na,onal monitoring reports disclosed UN indicators and Na,onal indicators for Goal 1 such as: Na,onal income concentrated by 20% richest Distribu,on of popula,on in the 10% poorest and 1% richest, by race White Black / Brown Data source: IBGE, PNAD Source: 3 rd MDG na,onal monitoring report,

9 3) methodological challenges: data sources IBGE main household surveys Decennial census (municipality level), short/long form Provides: total/labor/other income (reference month - July) Regular income data with annual nabonal Labor Force Survey, (State, Metropolitan areas, urban/rural) Provides: total/labor/other income (reference month - Sept.) TransiBon since 2012 to panel LFS (HH stays 5 quarters), similar to Ireland and Mexico LFS. QuesBonnaire revision: Oct/2015 Provides: total/labor/other income (reference: last month) Budget survey is less frequent, , , Provides: consumpbon, total/disposable income (reference: 12 months)

10 3) methodological challenges: data sources Income as variable and as disaggrega,on DistribuBon of personal or household (per capita) income by. percenbles of income (20%,10%) 1/4, 1/2, 5+ minimum wage (today ~ US$500 PPP2011) classes Other usual disaggregabon: Sex Age groups Race Urban/rural Regions Disability (census data)

11 3) Methodological challenges Brazil ConsumpBon is beger indicator for monitoring (Goal 1) than income, but no annual recollecbon Many income lines Expenditure survey, 5x5 years (recommendabon) PerspecBve: conbnuous Budget survey Income quinbles/deciles: LFS with complex samples, minimum income & Bes, database order, metadata DisaggregaBon when near the target, e.g., US$1.25 PPP extreme poverty in LaBn America // discussions in regional monitoring, populabon & development

12 3) Methodological challenges Interna,onal level India comment on / indicators: In Asia consumpbon expenditure is collected instead of income SDGs: Many themes and data sources (if available) how to link? QuesBons about unifying income and consumpbon sources in World Bank data Metadata from PovcalNet: Uses both income and consumpbon because of (un)availability and study with 20 countries ConsumpBon aggregates differ Many decisions regarding income/consumpbon / poverty in all its dimensions, people living below (Tier 3) How about transparency, replicability?

13 4) Iden,fica,on of priority issues to be addressed for future guidance for SDG follow up and review Pressures regarding censuses and surveys: periodicity, coverage, more & more & more quesbons? How to set the limits of disaggregabon? How to prioribze disaggregabon types?

14 4) Iden,fica,on of priority issues to be addressed for future guidance for SDG follow up and review Pressures regarding censuses and surveys: periodicity, coverage, more & more & more quesbons? How to set the limits of disaggregabon? How to prioribze disaggregabon types? NSO = official stabsbcs How to integrate other data sources? Non- official data, data with high error margins How to compose using records and census/survey data?

15 THANK YOU! IBGE hhp:// E- mail

16 BACKUP Data sources & HH income components Canberra Group Handbook 2 nd edi,on (UNECE, 2011) IBGE surveys: HH Budget survey (POF) Con,nuous LFS (PNADC) LFS (PNAD) Census long form Conceptual definition Operational definition HH Budget survey (POF) Continuous LFS (PNADC) LFS (PNAD) Census long form 1 Income from employment ] Employee income Included Wages and salaries Included Cash bonuses and gratuities Included Commissions and tips Included Directors fees Included Profit-sharing bonuses and other forms of profit-related pay Included Shares offered as part of employee remuneration Included Free or subsidised goods and services from an employer Included Severance and termination pay Included Employers social insurance contributions Included Income from self-employment Included Profit/loss from unincorporated enterprise Included Goods and services produced for barter, less cost of inputs Included Goods produced for own consumption, less cost of inputs Included 2 Property income Income from financial assets, net of expenses Included Income from non-financial assets, net of expenses Included Royalties Included 3 Income from household production of services for own consumption Net value of owner-occupied housing services Included Value of unpaid domestic services Value of services from household consumer durables 4 Current transfers received Not Included Not Included Social security pensions / schemes Included Pensions and other insurance benefits Included Social assistance benefits (excluding social transfers in kind, see 10) Included Current transfers from non-profit institutions Included Current transfers from other households Included 5 Income from production (sum of 1 and 3) 6 Primary income (sum of 2 and 5) 7 Total income (sum of 4 and 6) 8 Current transfers paid Direct taxes (net of refunds) Included Compulsory fees and fines Included Current inter-household transfers paid Included Employee and employers social insurance contributions Included Current transfers to non-profit institutions Included 9 Disposable income (7 less 8) 10 Social transfers in kind (STIK) received Not Included 11 Adjusted disposable income (9 plus 10) Note: directly captured; captured aggregated with other components; most recent survey presented: POF , PNAD , 2016 PNADC Oct/15 onward; Census Source: IBGE, internal documenta,on; UNECE, 2011, p

17 BACKUP Propor,on of popula,on below the interna,onal poverty line, by sex, age, employment status and geographical loca,on (urban/rural) Propor,on of popula,on living below the na,onal poverty line, by sex and age Propor,on of men, women and children of all ages living in poverty in all its dimensions according to na,onal defini,ons Growth rates of household expenditure or income per capita among the bohom 40 per cent of the popula,on and the total popula,on Propor,on of people living below 50 per cent of median income, by age, sex and persons with disabili,es By 2020, enhance capacity- building support to developing countries, including for least developed countries and small island developing States, to increase significantly the availability of high- quality,,mely and reliable data disaggregated by income, gender, age, race, ethnicity, migratory status, disability, geographic loca,on and other characteris,cs relevant in na,onal contexts

18 BACKUP Gini index of monthly income of 15 y.o. + persons with income by State Source: