Poverty Dynamics in Brazil: Patterns, Associated Factors and Policy Challenges
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Poverty Dynamics in Brazil: Patterns, Associated Factors and Policy Challenges

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Apresentação em inglês sobre as dinâmicas da pobreza no Brasil: padrões, fatores associados e desafios, mostrada na “Conferência Internacional sobre Sustentabilidade e Promoção da Classe ...

Apresentação em inglês sobre as dinâmicas da pobreza no Brasil: padrões, fatores associados e desafios, mostrada na “Conferência Internacional sobre Sustentabilidade e Promoção da Classe Média”, por Luis F. Lopez Calva do Banco Mundial, ocorrida em 25 de setembro de 2013. Veja mais na matéria: http://ow.ly/poL9G

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    Poverty Dynamics in Brazil: Patterns, Associated Factors and Policy Challenges Poverty Dynamics in Brazil: Patterns, Associated Factors and Policy Challenges Presentation Transcript

    • POVERTY DYNAMICS IN BRAZIL: PATTERNS, ASSOCIATED FACTORS AND POLICY CHALLENGES Lead Authors: Rogerio Bianchi Santarrosa Anna Fruttero Luis F. Lopez Calva Maria Ana Lugo With support by: Raul Andres Castaneda, Samantha Lach, Jordan Solomon
    • ACKNOWLEDGEMENTSACKNOWLEDGEMENTSACKNOWLEDGEMENTSACKNOWLEDGEMENTS The team is grateful to Melanie Allwine, François Bourguignon, Francisco Ferreira, Peter Lanjouw Jamele Rigolini and Shabana Singh who collaborated with the team and provided important inputs and comments. Maria Concepcion Steta and Joana Da Silva also provided useful comments and became a fundamental source of support in the preparation of the final output. Background work for this Report was presented at the author‘s workshop in Washington DC in July 2012, George Washington University Development Tea Seminar Series, and IPEA-Brasilia.
    • Economic growth and falling inequality contributed 56% and 44%, respectively of the decline in poverty between 2000 and 2010. LACachieved impressivegainsinsharedprosperityinthelast15 years,exceeding itspastperformance… For the first time in 2011, the middle class exceeds the poor, due to growth (77%) and improved income distribution (23%). 2000 2002 2004 2006 2008 2010 0 10 20 30 40 Headcount(%) Middle Class Vunerable Poor
    • In Brazil, growth accounted for 54% of the decline in poverty between 2001 and 2011. While redistribution contributed 46% to decrease poverty. …overthisperiod Brazil hasexperiencedsteadyeconomicgrowth andsubstantialreductionof inequality Poverty in Brazil has declined since the 2003. In 2011, 24.5% of the population was poor ($4 USD/day, PPP 2005). By 2008, the middle class outnumbered the poor.* 2000 2002 2004 2006 2008 2010 22 23 24 25 26 27 28 PercapitaGDP(perday,PPPConstant2005$) 0.50 0.52 0.54 0.56 0.58 0.60 0.62 GiniCoefficient GDP per capita/day Gini The middle class figure shown above is constructed under the World Bank definition, World Bank (2012) and was constructed only to inform international comparisons. Roland1
    • Slide 4 Roland1 Separate labels vulnerable / middle class Roland Clarke, 3/1/2013
    • Main Policy Questions • Brasil sem miseria strategy has set as its goal to eliminate extreme poverty in Brazil • There are three main pillars in the strategy: • “Active search” and income guarantee (reaching those who have been excluded for different reasons) • Minimum income guarantee • Productive inclusion (those who leave poverty must be incorporated to the productive world) • Access to services (close existing coverage gaps in basic services)
    • Somequestions arise • What does it mean to “eliminate” poverty? (transient versus chronic poverty) • How to measure chronic poverty? • What is the right “policy mix” to deal with both aspects of poverty?
    • Methodology for Policy Use • Use synthetic panels to characterize the different mobility groups • Use a combination of multidimensional and monetary measures to distinguish the “chronic” from the “transient” poor
    • Characterizing Mobility: Leavers and stayers
    • Founded optimism: Brazil’s impressive social record • Poverty has decreased through last decade, using both national and international lines
    • Founded optimism: Brazil’s impressive social record • This result of a progressive income growth and declining inequality Growth Incidence Curves for Brazil, 2003Growth Incidence Curves for Brazil, 2003Growth Incidence Curves for Brazil, 2003Growth Incidence Curves for Brazil, 2003----2011201120112011
    • BrazilandtheBottom40%growthrate Growth rate of income of the bottom 40% in LAC, 2000-2011 . 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% Brazil LAC AnnualizedGrowthRateAnnualizedGrowthRateAnnualizedGrowthRateAnnualizedGrowthRate Annualized Growth Mean Income Bottom 40% Annualized Growth Mean Income
    • Who left, who stayed? Povertydynamics: 2003-2011 • Using Methodology in Lanjouw, et al (2011), Cruces, et al (2012) to construct synthetic panels from a series of cross sections (PNAD) • Lower and upper bounds • 3 economic groups (following SAE’s Study): - Poor (income below R$140 per month) - Vulnerable (R$140 – R$250) - Middle Class and Upper Class (R$250 - )
    • Destination: 2011 PoorPoorPoorPoor (0-140 Reais) VulnerableVulnerableVulnerableVulnerable (140 – 250 Reais) MiddleMiddleMiddleMiddle Class +Class +Class +Class + (250 Reais +) Origin:2003200320032003 PoorPoorPoorPoor (0-140 Reais) 14.0% 6.7% 1.9% VulnerableVulnerableVulnerableVulnerable (140 – 250 Reais) 0.5% 7.0% 11.2% MiddleMiddleMiddleMiddle Class +Class +Class +Class + (250 Reais+) 0.0% 0.9% 57.8% TOTALTOTALTOTALTOTAL 2003200320032003 22.6% 18.7% 58.7% 100.0%TOTAL 2011TOTAL 2011TOTAL 2011TOTAL 2011 14.5% 14.6% 70.9% NB: Results are lower bounds estimates Who left, who stayed? Poverty dynamics: 2003-2011
    • Destination: 2011 PoorPoorPoorPoor (0-140 Reais) VulnerableVulnerableVulnerableVulnerable (140 – 250 Reais) MiddleMiddleMiddleMiddle Class +Class +Class +Class + (250 Reais +) Origin:2003200320032003 PoorPoorPoorPoor (0-140 Reais) 14.0% 6.7% 1.9% VulnerableVulnerableVulnerableVulnerable (140 – 250 Reais) 0.5% 7.0% 11.2% MiddleMiddleMiddleMiddle Class +Class +Class +Class + (250 Reais+) 0.0% 0.9% 57.8% TOTALTOTALTOTALTOTAL 2003200320032003 22.6% 18.7% 58.7% 100.0%TOTAL 2011TOTAL 2011TOTAL 2011TOTAL 2011 14.5% 14.6% 70.9% CHRONICALLY POOR POVERTY LEAVERS POVERTY ENTRANTS NB: Results are lower bounds estimates Who left, who stayed? Poverty dynamics: 2003-2011
    • Profileof poverty leavers • Exiting poverty in Brazil between 2003 and 2011 is highly correlated with educational achievement, even more than in the previous poverty reduction period of the early 1990s • Probability to exit poverty in the 2000s is greater in households headed by women • Those who manage to get out of poverty systematically show better labor market conditions, starting out in the formal economy as employees or employers. • A larger share of people by ethnic groups and regions (urban and rural) were able to exit poverty, vis-à-vis the 1990s
    • Whatdoes it mean to eliminate poverty?
    • But... challenges remain • There is however, an important number of people who remain poor in monetary terms, as well as in terms of access to basic services • About 4444....7777 percentpercentpercentpercent of the population lives below the official extreme poverty line of R$70 (Reais) per month (Pnad 2011); they are about 9999 millionmillionmillionmillion who remain in extreme poverty • 12121212....4444 percentpercentpercentpercent live below the R$140 official poverty line (Pnad 2011). This amounts to more than 24242424 millionmillionmillionmillion Brazilians whom, despite the efforts of social programs, continue to live in poverty • Eliminating extreme poverty, within the context of the BSM program, necessarily entails the identification of the chronically poor
    • Chronicversus transient poverty
    • But what does it mean to live in chronic poverty? Conceptand Measurement • One way to approach this issue is to use the idea of “ultra poverty”: persistence of poverty over time, depth of poverty, and multidimensionality (complexity) • The typical notion of “chronicity” refers mainly to persistence. Two approaches: • The componentscomponentscomponentscomponents approach tries to distinguish permanent versus transitory income generation, and compares to a standard • The spellsspellsspellsspells approach defines it in terms of number of periods in which the income is below the standard
    • Using Non-Monetary Dimensions to Approximate Chronic Poverty in Brazil • Social programs in Brazil, including within the BSM strategy, rely primarily on income-based indicators to select the beneficiaries • Given their volatility and issues related to incentives, income indicators may be complemented with alternative methodologies to target social programs in the most efficient and equitable way. • Multidimensional measures of poverty could be a good instrument to enhance the incidence of programs. • Those who are both monetary and multidimensionally poor in one period are systematically –and considerably—more likely to have been monetary poor in other periods. • Association between the complexity (multidimensionality) and persistence aspects of the ultra poverty concept
    • Using Non-Monetary Dimensions to Approximate Chronic Poverty in Brazil • Multidimensional measurement of poverty using a dual cut-off (Alkire and Foster, 2011) • The first cut-off, the traditional poverty line “z”, identifies whether individuals are poor within a given dimension • The second cutoff, the dimensional one, establishes the proportion of dimensions “k”, in which an individual must be identified as poor to be considered multi- dimensionally poor
    • Chronicityof Poverty • The main idea in the estimation of exit from chronic poverty is that the time spent in poverty (or the duration in poverty) affects whether an individual will leave poverty in a given period. • The longer a person remains in poverty, the less likely it is that she will exit poverty (this is the poverty trap argument) • Looking at whether an individual will leave poverty today depends on an a number of individual factors (level of education, etc.) but also on the number of years she has been poor.
    • Conjectures • First: people who are both monetary and multidimensionally poor are more likely to have been poor in previous periods, compared to those who are monetary but NOT multidimensionally poor today • The longer you are poor (both Monetary and MPI) the less likely you are to escape monetary poverty in the future
    • Chile – Changes in probabilities BaseBaseBaseBase modelmodelmodelmodel: the household head is male, is married, and has lower-secondary education; in 2002 he was a skilled manual worker, living in an urban area of the Metropolitan region; he has faced shocks between 2001 and 2006; andandandand hehehehe waswaswaswas notnotnotnot incomeincomeincomeincome poorpoorpoorpoor andandandand multidimensionalmultidimensionalmultidimensionalmultidimensional poorpoorpoorpoor atatatat thethethethe samesamesamesame timetimetimetime inininin 2001200120012001.... 0.489 0.190 0.068 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Incomepoor& multid. poorin 2001 Incomepoorbut non-multid. poorin2001 Non-income poorbut multid. poorin2001 Marginal effects for being income poor inMarginal effects for being income poor inMarginal effects for being income poor inMarginal effects for being income poor in 2006200620062006 0.061 0.128 0.230 0.533 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Base Non-income poorbut multid.poorin2001 Incomepoorbut non- multid.poorin2001 Incomepoor& multid. poor in2001 0.067 0.169 0.471 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 Non-income poorbutmultid. poorin2001 Incomepoorbut non-multid. poorin2001 Incomepoor& multid. poorin 2001 Magnitude of changes in probabilityMagnitude of changes in probabilityMagnitude of changes in probabilityMagnitude of changes in probabilityProbabilities of being incomeProbabilities of being incomeProbabilities of being incomeProbabilities of being income----poor in 2006poor in 2006poor in 2006poor in 2006
    • 0.115 0.264 0.354 0.494 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Base Non-income poorbut multid.poorin2002 Incomepoorbut non- multid.poorin2002 Incomepoor& multid. poor in2002 Mexico – Changes in probabilities BaseBaseBaseBase modelmodelmodelmodel: the household head is male, is married, and has lower-secondary education; in 2002 he was a skilled manual worker, living in an urban area of the Western region; he has faced shocks between 2002 and 2005; andandandand hehehehe waswaswaswas notnotnotnot incomeincomeincomeincome poorpoorpoorpoor andandandand multidimensionalmultidimensionalmultidimensionalmultidimensional poorpoorpoorpoor atatatat thethethethe samesamesamesame timetimetimetime inininin 2002200220022002.... Marginal effects for being income poor inMarginal effects for being income poor inMarginal effects for being income poor inMarginal effects for being income poor in 20052005200520050.426 0.258 0.143 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 Incomepoor& multid. poorin 2002 Incomepoorbut non-multid. poorin2002 Non-income poorbut multid. poorin2002 Probabilities of being incomeProbabilities of being incomeProbabilities of being incomeProbabilities of being income----poor in 2005poor in 2005poor in 2005poor in 2005 Magnitude of changes in probabilityMagnitude of changes in probabilityMagnitude of changes in probabilityMagnitude of changes in probability 0.149 0.239 0.379 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 Non-income poorbutmultid. poorin2002 Incomepoorbut non-multid. poorin2002 Incomepoor& multid. poorin 2002
    • Multidimensional and incomepoverty • Chronic poverty can be identified in the absence of panel data using a multidimensional approach to poverty • Use of synthetic panel over two periods, from 1999 to 2011 • Results suggest that people who were not only income poor, but also multi-dimensionally poor in the initial period had a significantly lower probability to emerge from monetary poverty.
    • Multidimensional and income poverty 0 3238 6476 012345678 Non-monetary poor but deprived 8.2% Better off 65.1% $R70 $R140 1999199919991999 Transiently poor 11.9% Chronic poor 14.7% Incomepoor Multi-dimensionally poor HouseholdpercapitaincomeHouseholdpercapitaincomeHouseholdpercapitaincomeHouseholdpercapitaincome Number of deprivationsNumber of deprivationsNumber of deprivationsNumber of deprivations
    • Multidimensional and income poverty 0 3238 6476 012345678 Non-monetary poor but deprived 4.1% Better off 83.5% $R70 $R140 2011201120112011 Transiently poor 9.1% Chronic poor 3.3% Incomepoor Multi-dimensionally poor HouseholdpercapitaincomeHouseholdpercapitaincomeHouseholdpercapitaincomeHouseholdpercapitaincome Number of deprivationsNumber of deprivationsNumber of deprivationsNumber of deprivations
    • MPI and multidimensional targetingvis-à-vis income alone • Groups that are reached using income and multidimensional poverty status (MPI) thresholds show: • more severe levels of deprivations and possess on average less assets • significantly lower level of education (two years of schooling on average), substantively higher illiteracy rates (~50 percent) and lower enrollment rates for children • While transient poverty may be largely associated with temporary unemployment, chronic poverty—identified through the multidimensional measures—is related to lower productivity and lower wages • Using MPI criteria to fine-tune identification leads to a higher concentration of target groups in rural areas, where the level of deprivations is higher.
    • Conclusion • Social indicators have shown remarkable progress in Brazil during the last decade; nevertheless, many individuals remain who have not benefited from Brazil’s rapid development • This study looks at ways to better characterize the different types of poverty, with existing data, in order to select the different instruments to reach them effectively • The transient poor will require fundamentally policies related to productivity and income-generation capacity