ESA/STAT/AC.320/8
Expert Group Meeting on Data Disaggregation
27-29 June 2016
New York
Data disaggregated by income and/or other dimensions of poverty By Leonardo Athias ATHIAS,L.
2016
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 ATHIAS,L.
2016
2
Contents 1) Problem statement 2) Concrete examples 3) Methodological challenges 4) Iden,fica,on of priority issues to be addressed for future guidance for SDG follow up and review ATHIAS,L.
2016
3 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 km2 ATHIAS,L.
2016
4 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 -­‐ 2014 1st quin,le 2nd quin,le 3rd quin,le 4th quin,le 5th quin,le Source: Source: IBGE, PNAD ATHIAS,L.
2016
5 2) Concrete examples: income disaggrega,on Dwelling characteris,cs Propor,on of overcrowded households, total and 1st quin,le of average monthly household per capita income -­‐ Brazil -­‐ 2004/2014 1st quin,le Note: overcrowding is defined as >3 persons per dormitory. Source: IBGE, PNAD ATHIAS,L.
2016
6 2) Concrete examples: MDG monitoring Percentage of total income MDG na,onal monitoring reports disclosed “UN indicators” and “Na,onal indicators” for Goal 1 such as: • Na,onal income concentrated by 20% richest 20% poorest 20%-­‐80% middle 20% richest Gini index Income c
oncentra,on a
nd G
ini i
ndex 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: 5th MDG na,onal monitoring report, 2014. ATHIAS,L.
2016
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 • Distribu,on of popula,on in the 10% poorest and 1% richest, by race White Black / Brown Data source: IBGE, PNAD Source: 3rd MDG na,onal monitoring report, 2007. ATHIAS,L.
2016
8 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, 1981-­‐2015 (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) ATHIAS,L.
2016
Budget survey is less frequent, 2002-­‐2003, 2008-­‐2009, … Provides: consumpBon, total/disposable income (reference: 12 months) 9 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) ATHIAS,L.
2016
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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 ATHIAS,L.
2016
DisaggregaBon when near the target, e.g., US$1.25 PPP extreme poverty in LaBn America // discussions in regional monitoring, populaBon & development 11 3) Methodological challenges Interna,onal level India comment on 1.1.1./1.1.2. 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 ATHIAS,L.
2016
Many decisions regarding income/consumpBon /“poverty in all its dimensions”, “people living below…” (Tier 3) How about transparency, replicability? 12 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? ATHIAS,L.
2016
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? 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? ATHIAS,L.
2016
14 THANK YOU ! IBGE hhp://www.ibge.gov.br/english/ E-­‐mail [email protected] ATHIAS,L.
2016
15 Operational
definition
HH Budget
survey
(POF)
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
Conceptual definition
BACKUP Data sources & HH income components Canberra Group Handbook 2nd edi,on (UNECE, 2011) IBGE surveys: HH Budget survey (POF) Con,nuous LFS (PNADC) LFS (PNAD)
Census long form Continuous
Census
LFS (PNAD)
LFS (PNADC)
long form
1 Income from employment
]
√√
√
2 Property income
Income from financial assets, net of expenses
Included
√
√
√
Income from non-financial assets, net of expenses
Included
√√
√√
√√
√
Royalties
Included
√√
√
√
√
Included
√√
√√
3 Income from household production of services for own consumption
Net value of owner-occupied housing services
Value of unpaid domestic services —
Not Included
Value of services from household consumer durables —
Not Included
4 Current transfers received
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
√√
√√
√√
√
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
√√
Not 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
9 Disposable income (7 less 8)
10 Social transfers in kind (STIK) received
11 Adjusted disposable income (9 plus 10)
ATHIAS,L.
2016
Note: √√ directly captured; √ captured aggregated with other components; most recent survey presented: POF 2008-­‐2009, PNAD 2011-­‐15, PNADC Oct/15 onward; Census 2010. Source: IBGE, internal documenta,on; UNECE, 2011, p.24. 16 ATHIAS,L.
2016
BACKUP 1.1.1 Propor,on of popula,on below the interna,onal poverty line, by sex, age, employment status and geographical loca,on (urban/rural) 1.2.1 Propor,on of popula,on living below the na,onal poverty line, by sex and age 1.2.2 Propor,on of men, women and children of all ages living in poverty in all its dimensions according to na,onal defini,ons 10.1.1 Growth rates of household expenditure or income per capita among the bohom 40 per cent of the popula,on and the total popula,on 10.2.1 Propor,on of people living below 50 per cent of median income, by age, sex and persons with disabili,es 17.18 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 17 BACKUP Gini index of monthly income of 15 y.o. + persons with income by State -­‐ 2014 ATHIAS,L.
2016
Source: 18