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 Média”, por Luis F. Lopez Calva do Banco Mundial, ocorrida em 25 de setembro de 2013. Veja mais na matéria: http://ow.ly/poL9GTRANSCRIPT
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
ACKNOWLEDGEMENTS ACKNOWLEDGEMENTS ACKNOWLEDGEMENTS ACKNOWLEDGEMENTS
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.
LAC achieved impressive gains in shared prosperity in the last 15 years, exceeding its past performance…
For the f irst t ime 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.
… over this period Brazil has experienced steady economic growth and substantial reduction of inequality
Pover ty in Brazi l has decl ined 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
Per capita GDP (per day, PPP Constant 2005 $)
0.50
0.52
0.54
0.56
0.58
0.60
0.62
Gini Coefficient
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 classRoland 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)
Some questions 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
Brazil and the Bottom 40% growth rate
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
An
nu
alize
d G
row
th R
ate
An
nu
alize
d G
row
th R
ate
An
nu
alize
d G
row
th R
ate
An
nu
alize
d G
row
th R
ate
Annualized Growth Mean Income Bottom 40% Annualized Growth Mean Income
Who left, who stayed?Poverty dynamics: 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
Poor Poor Poor Poor (0-140 Reais)
VulnerableVulnerableVulnerableVulnerable(140 – 250
Reais)
MiddleMiddleMiddleMiddle Class + Class + Class + Class + (250 Reais +)
Ori
gin
: 2
00
32
00
32
00
32
00
3
Poor Poor Poor Poor (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
Poor Poor Poor Poor (0-140 Reais)
VulnerableVulnerableVulnerableVulnerable(140 – 250
Reais)
MiddleMiddleMiddleMiddle Class + Class + Class + Class + (250 Reais +)
Ori
gin
: 2
00
32
00
32
00
32
00
3
Poor Poor Poor Poor (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
POORPOVERTY LEAVERS
POVERTY
ENTRANTS
NB: Results are lower bounds estimates
Who left, who stayed?Poverty dynamics: 2003-2011
Profile of poverty leavers
• Exiting poverty in Brazil between 2003 and 2011 is highlycorrelated with educational achievement, even more than inthe previous poverty reduction period of the early 1990s
• Probability to exit poverty in the 2000s is greater inhouseholds headed by women
• Those who manage to get out of poverty systematically showbetter labor market conditions, starting out in the formaleconomy as employees or employers.
• A larger share of people by ethnic groups and regions (urbanand rural) were able to exit poverty, vis-à-vis the 1990s
What does it mean to eliminate poverty?
But... challenges remain
• There is however, an important number of people who remain poorin monetary terms, as well as in terms of access to basic services
• About 4444....7777 percentpercentpercentpercent of the population lives below the officialextreme poverty line of R$70 (Reais) per month (Pnad 2011); theyare about 9999 millionmillionmillionmillion who remain in extreme poverty
• 12121212....4444 percentpercentpercentpercent live below the R$140 official poverty line (Pnad2011). 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 BSMprogram, necessarily entails the identification of the chronicallypoor
Chronic versus transient poverty
But what does it mean to live in chronic poverty?Concept and 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 components components components components 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, relyprimarily on income-based indicators to select the beneficiaries
• Given their volatility and issues related to incentives, incomeindicators may be complemented with alternative methodologiesto target social programs in the most efficient and equitable way.
• Multidimensional measures of poverty could be a good instrumentto enhance the incidence of programs.
• Those who are both monetary and multidimensionally poor in oneperiod are systematically –and considerably—more likely to havebeen monetary poor in other periods.
• Association between the complexity (multidimensionality) andpersistence 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
Chronicity of 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
Income poor & multid. poor in
2001
Income poor but non-multid.
poor in 2001
Non-income poor but multid.
poor in 2001
Marginal effects for being income poor in Marginal effects for being income poor in Marginal effects for being income poor in Marginal 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 poor but
multid. poor in 2001
Income poor but non-
multid. poor in 2001
Income poor & multid. poor
in 2001
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 poor but multid.
poor in 2001
Income poor but non-multid.
poor in 2001
Income poor & multid. poor in
2001
Magnitude of changes in probability Magnitude of changes in probability Magnitude of changes in probability Magnitude of changes in probability Probabilities 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 poor but
multid. poor in 2002
Income poor but non-
multid. poor in 2002
Income poor & multid. poor
in 2002
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 in Marginal effects for being income poor in Marginal effects for being income poor in Marginal 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
Income poor & multid. poor in
2002
Income poor but non-multid.
poor in 2002
Non-income poor but multid.
poor in 2002
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 probability Magnitude of changes in probability Magnitude of changes in probability Magnitude 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 poor but multid.
poor in 2002
Income poor but non-multid.
poor in 2002
Income poor & multid. poor in
2002
Multidimensional and income poverty
• 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%
Inco
me
po
or
Multi-dimensionally poor
Ho
use
ho
ld p
er
ca
pit
a in
co
me
Ho
use
ho
ld p
er
ca
pit
a in
co
me
Ho
use
ho
ld p
er
ca
pit
a in
co
me
Ho
use
ho
ld p
er
ca
pit
a in
co
me
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%
Inco
me
po
or
Multi-dimensionally poor
Ho
use
ho
ld p
er
ca
pit
a in
co
me
Ho
use
ho
ld p
er
ca
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a in
co
me
Ho
use
ho
ld p
er
ca
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a in
co
me
Ho
use
ho
ld p
er
ca
pit
a in
co
me
Number of deprivationsNumber of deprivationsNumber of deprivationsNumber of deprivations
MPI and multidimensional targeting vis-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