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Presentation made by government of Colombia during Indonesia’s study visit to South America Social Policies on June 2012. The study tour was organized by UNDP/IPC-IG.
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Multidimensional Poverty Index for
Colombia and its applications
(MPI-Colombia)
HDCA Conference, The Hague, 2011
ROBERTO ANGULOBEATRIZ YADIRA DÍAZ
RENATA PARDO
National Planning Department
Division of Social Promotion and Quality of Life
September 2011
Technical team:
Roberto Angulo (DNP-DDS)
Renata Pardo (DNP-DDS)
Beatriz Yadira Díaz (DNP-Essex)
Yolanda Riveros (DNP-DDS)
National Planning Department:
Technical Divisions
OPHI:
Sabina Alkire
Diego Zavaleta
José Manuel Roche
James Foster (George Washington University)
Aknowledge:
Esteban Piedrahíta
Juan Mauricio Ramírez
José Fernando Arias
Hernando José Gómez
“Any exercise of measurement and indexation
is basically an exercise of reflection, analysis
and judgement, and not only of observation,
registration, or chronic”.
Amartya Sen 1998
The MPI-Colombia:
•Is a poverty measure proposed by theNational Planning Department based onthe Alkire&Foster methodology
•Was developed as an instrument fordesign and monitoring public policy
•Complements the income povertymeasure
•Was socialized with the Colombianacademy and policy makers
Colombia’s unit of analysis:
The household
The household as the
analysis unit
• Normative: The guarantee of living conditions is not given by the
responsibility of individuals in isolation - (Political Constitution of
Colombia). Co-responsibility.
• Empirical: There is evidence that in Colombia the household
responds in adverse situations, not individuals in isolation – there is
a combination of actions involving different household members
• Social Policy: Instruments, programs and strategies for reducing
poverty in Colombia are focused at the household level and not on
individuals in isolation - SISBEN, UNIDOS network strategy, Familias
en Acción (conditional cash transfer program)
Dimensions and Variables:
I P M
1. Frequent usage (national or
international). Literature review,
discussion with experts and inclusion in
other indices – IPM-OPHI International,
BNI, LCI y Sisbén III.
2. Variables sensitive to public policy
implementation
3. Availability of data within the Living
Standards Measurement Surveys (LSMS)
Accuracy of the estimated
variables for each of the
study’s domains (ecv<15%).
*DANE follows:
0-7: Accurate estimation
8-14: acceptable accuracy
15-20 : accuracy is not so good
20-25: inaccurate
Choosing dimensions and variables
Criteria for selecting
variablesCriteria for validating
variables
Dimensions and variables
Education Childhood & youth
Labor Health Public utilities &
housing conditions
Household education conditions
Educational achievement: A
household is deprived if the average
level of education for individuals 15
and older within the household is
below 9.
Literacy: A household is deprived if at
least one household member 15 or
older does not know how to read or
write
Childhood and youth
conditions
School attendance: a household is
deprived if at least one child between ages
6 and 16 within the household does not
attend school
No school lag: a household is deprived if
any of the children between ages 7 and 17
is lagging in school (approved school years
is less than the normative number of school
years)
Access to child care services: A household
is deprived if at least one child between 0
and 5 years old, does not have
simultaneous access to health, proper
nutrition, and adult supervision or
education.
Children not working: A household is
deprived if there is at least one child
between 12 and 17 in child labor conditions
Labor
Absence of long-term
unemployment: A household is
deprived if there is someone in
long-term unemployment (>12
months)
Formal employment: A household
is deprived if there is at least
someone holding an informal job or
someone in unemployment.
Salud
Health insurance: A household is
deprived if there is at least one member
(over 5 years old) without health
insurance.
Access to health services: A household is
deprived if at least one household
member faced access barriers to health
care services when needed.
Servicios públicos y
condiciones de la vivienda
Access to drinking water: Urban households are deprived
they have no access to public water services.
Rural households - deprived when the water used to prepare
food is obtained from a well, rainwater, a river, spring water
source, public well, water truck or water carrier
Adequate elimination of sewer waste: Urban households –
deprived if they have no access to public sewer service. Rural
households - deprived if they have a toilet without a sewer
connection, a latrine or if they simply do not have a sewage
system
Adequate flooring: Households with dirt floors are deprived
Adequate walls: Urban households - deprived when exterior
walls are built of untreated wood, boards, planks, guadua (a
type of bamboo) or other vegetable, zinc, cloth, cardboard,
waste material or when no exterior walls exist
madera burda, tabla, tablón, guadua, otro vegetal, Zinc, tela,
cartón, deshechos y sin paredes. For Rural households -
untreated wood & board are considered adequate materials
No critical overcrowding: Urban households deprived if there
are 3 or more p.p.r. Rural households – more than 3 p.p.r.
Dimensions on a scale: Selecting the
weighting structure and the cut-offs
Weighting
scheme
Nested weighting structure:
•Each dimension has the same weight (0.2)
•Each variable has the same weight within
each dimension
Weighting scheme
Dimensions (5) & variables (15)
EducationChildhood & youth
conditionsLabor Health
Public utilities &
housing conditions
Educational
achievement
Literacy
School
atendance
No school
lag
Access to
child care
services
Absence of
child
employment
Absence of
long-term
unemployment
Health insurance
Access to health
care services
when needed
Access to
improved
drinking water
Adequate
flooring
No critical
overcrowding
Adequate
elimination of
sewer waste
Adequate
walls
Formal
employment0.1
0.1
0.1
0.05
0.04
0.2 0.2 0.2 0.2 0.2
Criteria for selecting k:
1. Sample estimates robustness for each of the MPI
indicators (H, M0, M1 & M2). evc<15% for each of the
analysis domain
Robust band of k values: H & M0 [k=1/15, k=6/15]
M1 & M2 [k=1/15, k=5/15]
2. Statistical significance: no overlap of confidence interval
at 95% for the estimated measures.
Second Cut-off point k
Second cut-off point:
identifying the poor
Criterion of reasonability
Weighting scheme and
cut-off point k
MedianPopulation that perceives themselves as poor 5.0Population below the income poverty line 5.1Population that perceives themselves as poor and is below the income poverty line
5.4
Non-poor population by perception 3.0Population over income poverty line 3.0Total population 3.8
Median of the number of deprivations count C, 2008
Source: DNP-SPSCV calculations using SMLS 2008
A non-poor person (objectively or subjectively) faces on average 3 deprivations,
which suggests that with a low value of k we would capture people with
deprivations not necessarily related to poverty conditions.
Chosen cut-off k=5/15, that is 33% of
deprivations: H & M0
Weighting scheme and
cut-off point k
Measurement results
K=5/15
Source: DNP, DDS, SPSCV. 2011
K 1997 2003 2008 2010
5/15 48% 47% 45% 43%
Poverty headcount ratio (H)
Average deprivation share (A)
60.4%
49.2%
34.7%30.4%
0%
10%
20%
30%
40%
50%
60%
70%
1997 2003 2008 2010
23
Deprivation rates
Poor vs. non-poor
SOURCE: DNP-DDS-SPSCV
1%
2%
1%
8%
4%
2%
9%
6%
10%
6%
3%
13%
27%
43%
75%
8%
13%
16%
16%
17%
20%
22%
29%
30%
30%
45%
47%
62%
95%
99%
External wall materials
Child labor
School attendance
Longstanding unemployment
Access to health care services if …
Floors
Access to infant care services
Access to improved water sources
Overcrowding
Elimination of sewer waste
Illiteracy
Healthcare coverage
School lag
Educational achievement
Formal employment rate
Percentage of households facing deprivation in each variable
Poor Non-poor
Headcount ratio (H) urban-rural
K=5/15
0%
20%
40%
60%
80%
100%
1997 2003 2008 2010
51%40%
27% 23%
86%77%
60%53%
Headcount ratio (H)
Urban Rural
1.69 1.93
2.21 2.26
1
2
3
1997 2003 2008 2010
H rural/H urban
Poverty decreases notably, but
urban-rural differences increase
Source: DNP, DDS, SPSCV. 2011
Adjusted headcount ratio,
poverty gap and severity
results
Adjusted Headcount ratio (M0) K=5/15
Source: DNP, DDS, SPSCV. 2011
0%
20%
40% 29%23%
16%13%
1997 2003 2008 2010
0%
10%
20%
M1 M2
23% 20%
17% 15%
11%10%
9%8%
1997
2003
2008
2010
Gap (M1) &
Severity (M2)
K=4/11
Dominance analysis
I P M
1. For any value of k for
every year of analysis
(1997-2010 National)
Headcount ratio (H) for any value
of k/15 (1997-2008)
Source: DNP, DDS, SPSCV. 2011
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1997
2003
2008
2010
Adjusted headcount ratio (M0) for
any value of k/15 (1997-2008)
Source: DNP, DDS, SPSCV. 2010
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
1997
2003
2008
2010
Adjusted poverty gap (M1) for any
value of k (1997-2010)
Fuente: DNP, DDS, SPSCV. 2010
0%
5%
10%
15%
20%
25%
30%
35%
40%
1/11 2/11 3/11 4/11 5/11 6/11 7/11 8/11 9/11 10/11 11/11
1997
2003
2008
2010
Adjusted poverty severity (M2) for
any value of k (1997-2008)
Fuente: DNP, DDS, SPSCV. 2010
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
1/11 2/11 3/11 4/11 5/11 6/11 7/11 8/11 9/11 10/11 11/11
1997
2003
2008
2010
a) The lines don’t intersect: Poverty has
decreased between 1997 and 2010 for any
value of k
b) The line ordering remains: Poverty has
decrease for all measures: headcount ratio,
adjusted headcount ratio, gap and severity
The poverty dominance analysis
allows to make conclusions that
are independet from the cut-off
point k selection
Further research
• Dimensions and variables for possible
consideration
– Quality of services: education, health, water provision
– Security and dignity
– Political participation
– Quality of employment
• Alternative schemes for assigning weights
– Data driven
– Budget allocation
– Collective preferences (participative processes)
MPI Colombia as an
instrument for public policy
design
3 applications
Poverty maps
Municipal MPI Colombia
(geographical targeting)
1
MPI proxy based on Census Data 2005
Municipal MPI Colombia
Headcount ratio, urban-rural areas, 2005
Municipal poverty headcount ratio for urban
areas, k=5/15, 2005
Municipal poverty headcount ratio for rural areas,
k=5/15, 2005
MPI-Colombia within the methodology for social
promotion from the extreme poverty strategy
2
I P M
A family is “promoted” from if:
Sufficient condition:
Not in extreme income
povertyNot multidimensionally
poor
&
MPI-Colombia goal for the Government’s National
Development Plan 2010-2014 & for monitoring
poverty reduction
3
From multidimensional to multisectorial…
15 goals I P M
If the Plan is accomplished, if
every ministry makes its job
and spends the committed
resources, the MPI decreases to
22% (more than 3 million
people out of poverty).
51
Poverty committee: monitoring poverty reduction
▪ Leaders
– Counselor for the Presidency
– National Planning Department
▪ Permanent members
– Ministry of Health
– Ministry of Labor
– Ministry of Housing
– Ministry of Agriculture
– Ministry of Education
– Ministry of Finance
MANDATORY PRESENCE
The President of Colombia
PobrezaLínea Base
PND 2008Dato 2010 Análisis
Meta
2011
Meta
cuatrienio
MPI (Multidimensional Poverty) 34.7% 30.4% 25.6% 22.5%
Educational achievement (≥15 yrs)
Literacy (≥15 yrs)
58.8% 55.4% 54.3% 56.8%
14.2% 13.2% 12.5% 12.0%
School attendance (6-16)
No school lag (7-17)
Access to child care services (0-5)
Children not working (12-17)
5.4% 4.6% 4.4% 5.0%
33.4% 35.1% 33.9% 33.1%
12.1% 11.8% 11.5% 10.6%
5.5% 4.6% 3.6% 2.9%
Long-term unemployment
Formal employment
9.6% 9.9% 9.5% 9.3%
80.6% 80.9% 77.2% 74.7%
Health insurance
Access to health services
24.2% 21.0% 8.7% 0.5%
8.9% 6.9% 5.3% 2.4%
Access to water source
Adequate sewage system
Adequate floors
Adequate external walls
No critical overcrowding
12.9% 11.6% 11.2% 10.9%
14.1% 12.0% 11.6% 11.3%
7.5% 6.3% 5.9% 5.6%
3.1% 3.0% 2.4% 2.1%
15.7% 15.1% 11.1% 8.4%
FUENTE: DNP-DDS-SPSCV
0%-10% avance 10%-25% avance >25% avance
A(1)
D(4)
B(2)
C(3)
E(5)
“If it was not for the hope that the scientific study of
social actions can lead to practical results in favor of
social improvement, not few students would have
considered the time devoted to these studies as lost.
This is true for all social sciences but especially for
economics. Because this aspect is precisely what
interests or inspires the most”.
PIGOU, A. C. (1920). The economics of welfare
54
Thank you