Transcript Slide 1

Utilizing CBMS in Monitoring and Targeting
the Poor: The case of Barangay Kemdeng,
San Vicente, Palawan
A CBMS Philippines Research Paper
prepared for the PEP Network Meeting
June 18, 2004
Outline of presentation
• Part 1:
– Objectives
– Physical Characteristic of Kemdeng
– Results of the 2000 and 2002 CBMS Survey
• Part 2:
– Use of Scores in Ranking Households
– Uses of CBMS at the local level
– Conclusions and Recommendations
General Objectives
• Monitor the welfare conditions of local people
particularly the poor
– Examine the changes over time of CBMS core
indicators using the survey result in 2000 and 2002
• Provide an aggregate measure of poverty to be
able to target the poor
- Use of composite index
Barangay Kemdeng: Physical Characteristic
Ugnayan
Mahayahay
Maunlad
Viscua
Maningning
Nagkakaisa
Barangay Kemdeng: Demography
• In 2000, there were 135 hhlds with a population
of 713 persons and hhld size of 5.3
• These figures declined in 2002 with 127 hhlds,
612 persons and hhld size of 4.8
• The main reason for the decline in population
count is migration
– due to closure of small-scale silica mining operation in
Purok Maunlad in 2000
– other family members who study or work in other
locations in Puerto Princesa city or in Manila
Barangay Kemdeng: Demography
• The number of IP households or Tagbanuas
increased from 6 hhlds or 24 persons in 2000 to
10 hhlds or 44 persons in 2002. All IP hhlds in
the barangay live in Purok Ugnayan
• There are more males than females with sex
ratio of 110.9 in 2000 and 114.7 in 2002.
Barangay Kemdeng: Health and Nutrition
• In 2000, no infant deaths were reported in the
survey
• There were 3 infant deaths according to the
2002 survey
– Due to poor health conditions of infants when born
– Due to lack of access to safe water and poor
sanitation
Barangay Kemdeng: Health and Nutrition
• In 2000, 7 ( or 2 males and 5 females) severely
malnourished children were recorded among 137
children
• No malnourished children were found among the IP
hhlds.
Due to the conduct of feeding programs by barangay
officials, only one child remained severely malnourished
in 2002 from among the 7 children who were reported
malnourished in 2000
Barangay Kemdeng: Health and Nutrition
• In 2002, 6 ( 2 males and 4 females) case of severely
malnourished children were recorded. Two out of the
five new cases are member of IP hhlds.
• The explanation for the malnutrition prevalence
are:
– Busyness of some mothers in their work
– Poor health status of some of the mothers
– Lack of money of some households to be able to
complete the six month nutrition regime
– Due to the poor access to safe water and sanitation in
the barangay
Barangay Kemdeng: Access to Basic
Services
• In 2000, only 44 hhlds or 32.6% have access to
safe drinking water.
• 2002 survey results show a drastic decline with
only 22 hhlds or 17.3% have access to safe
water.
• In both surveys reveal that all IP households do
not have access to safe water
– The decline was due to the fact that 3 existing deep
wells have been damaged and now inoperative,
affecting at least 20 hhlds.
Barangay Kemdeng: Access to Basic
Services
• Most of these hhlds now tap unsafe water
sources such as dug wells, rivers and
undeveloped springs for their water needs.
Barangay Kemdeng: Access to Basic
Services
• In 2000, 80 hhlds or 59.3% have access to
sanitary toilet facility
• The 2002 survey reveal a drastic decline with
only 31 hhlds or 24.4% of hhlds with access
• The reason for these are:
– Toilet bowls distributed in previous sanitation program
were not durable
– Decline in access to safe water supply, particularly
deep wells. Some hhlds opted to build and use closed
or open pits which do not need water to clean and
maintain.
Barangay Kemdeng: Access to Basic
Services
– The number of hhlds with access to safe water and
sanitary toilet drastically declined from 77.3% in 2000
to only 27.3% in 2002.
• In both survey years, IP hhlds do not have
access to water-sealed toilets. Some use
closed/open pits while others do not have any
kind of sanitation facility.
Barangay Kemdeng: Access to Basic
Services
• Only 8 households (5.9%) have access to
electricity in 2000 while only 11 hhlds or 8.7%
have or avail of these services in 2002.
– Due to limited coverage and cost of electric power
Barangay Kemdeng: Education
Elementary school participation rates
among 6-11 years old children
90
80
80.8
81.8
80
76.6
75
78.7
Proportion
70
60
50
2000
40
2002
40
28.6
30
20
10
0
Elementary
IP
Male
Female
Barangay Kemdeng: Education
• Teachers provide free lunch for students,
especially to IP students
• Reasons for decline:
– School has only 3 classrooms
– Families have difficulty in meeting other school
expenses
– Some students are already working in the fields,
especially IP children
Barangay Kemdeng: Education
Secondary school participation rates
among 12-15 year old children
40
35
Proportion
30
35.5
30.6
30
27.3
25
25
24
2000
20
2002
15
10
5
0
0
0
Secondary
IP
Male
Female
Barangay Kemdeng: Education
• Reasons for low participation in secondary
school:
– Distant location of the nearest secondary school in
Poblacion (by boat or 12 km walk)
– Some students are already working to help earn
income for their households
Barangay Kemdeng: Education
School participation rates
among 6-16 year old children
100
90
82
87.3
82.4
87.5
81.6
87
80
Proportion
70
60
2000
45.5
50
2002
40
33.3
30
20
10
0
Total
IP
Male
Female
Barangay Kemdeng: Education
• There are children 6-11 years old who are still
attending daycare, kindergarten or preparatory
level
• There are children 12-15 who are still at the
elementary level
Barangay Kemdeng: Employment
Employment Rate
100 100
100
89.7 92.3
96.1 94.9
88.2
90
78.2
80
Proportion
70
60
2000
50
2002
40
30
20
10
0
Total
IP
Male
Female
Barangay Kemdeng: Employment
• Agriculture employs 72.6% of the employed in
the barangay.
• Fishing and forestry are also among the
common occupations of those employed
• Share of the employed in the industry sector
declined from 7.5% in 2000 to 3.8% in 2002
• Most male workers are in the agriculture sector
while females are in the services sector
• Most employed IP are in the agriculture sector,
undertaking farming activities in the upland and
clearing of timberland
Barangay Kemdeng: Enabling
Incidence of Poverty
100
90
83.3
80
Proportion
70
64.4
60
2000
45.9
50
40
40
40
30
33.3
27.6
15.7
20
10
0
Total
IP
Poverty
Total
Subsistence
IP
2002
Barangay Kemdeng: Enabling
– More accurate income estimates were taken
from the 2002 CBMS survey
– In 2000 CBMS, only income from
wages/salaries and entrepreneurial activities
were considered.
– To get a more accurate information on
income, other income from other sources and
other receipts were included in the 2002
questionnaire
Barangay Kemdeng: Summary of results
• Based on the CBMS results, the barangay has
not been performing well.
• Areas to prioritize:
–
–
–
–
–
–
Access to safe water
Access to sanitary toilet
Access to electricity
Health and nutrition
Employment
Elementary and secondary participation
Barangay Kemdeng: Summary of results
• Gender concerns:
– Males are more vulnerable in the areas of health
while females are not performing well in nutrition
– Females slightly performs better when it comes to
elementary participation while males are performing
well in secondary school participation rate
– Males are dominantly employed in agriculture while
females are more employed in the services sector
Barangay Kemdeng: Summary of results
• IPs are more marginalized in areas of education,
literacy and access to basic services
• The indicators are interrelated and explains
some of the trends
Barangay Kemdeng: Benefit Incidence
Analysis
Proportion and distribution of households with children 6-16 years old
who are attending public school, by per capita income decile
Per Capita
Income
Decile
Total
Househol
ds with
childre 611 years
old
Households with children attending elementary school
Magnitude
Proportion (row)
Proportion (column)
Kemdeng
70
64
91.4
100
1st
7
6
85.7
9.4
2nd
7
6
85.7
9.4
3rd
7
6
85.7
9.4
4th
7
7
100
10.9
5th
7
7
100
10.9
6th
7
7
100
10.9
7th
7
6
85.7
9.4
8th
7
6
85.7
9.4
9th
7
6
85.7
9.4
10th
7
7
100
10.9
Barangay Kemdeng: Benefit Incidence
Analysis
Proportion in each decile of households with
children attending public school
100.0
Proportion
95.0
90.0
85.0
80.0
75.0
1st
2nd
3rd
4th
5th
6th
7th
Per Capita Income Decile
8th
9th
10th
Barangay Kemdeng: Benefit Incidence
Analysis
Proportion of households with children
attending public school across deciles
11.5
Proportion
11.0
10.5
10.0
9.5
9.0
8.5
1st
2nd
3rd
4th
5th
6th
7th
Per Capita Income Decile
8th
9th
10th
Barangay Kemdeng: Benefit Incidence
Analysis
• The heads of these households have low
educational attainment, only reaching at
least the elementary level
• No access to basic services
• Two out of the six households are IP
households
• Proximity of the household to the location
of the school
Barangay Kemdeng: Benefit Incidence
Analysis
Use of Scores in
Ranking the Households
Comparison between Simple and
Categorically Weighted Composite
Indicator
Rationale of Composite Indicator
• Richer concept of multidimensional poverty
• Identifying the poorest households
• Discriminating between geopolitical and sub-geopolitical
units
• Resource allocation
• Impact assessment
Composite Indicator: Brief Description
• Ideally, must summarize the characteristics of a
particular household drawn from a set of indicators
• A function of the set of indicators
• Categories could be equally or differentially weighted
• Eventually, must draw household ranking and poverty
rates
Definition/Denotation of Terms
• Target or Population Units – 127 households of Brgy. Kemdeng,
San Vicente, Palawan
• Poverty Attributes – CBMS core socio-economic indicators
• Poverty Measure – quantifier or criterion in classifying a population
unit
• Poverty Indicator – transformation or realization of the poverty
measure
• Poverty Rate – relative magnitude of poor households using the
poverty indicator
• Composite Poverty Measure, Poverty Indicator and Poverty
Rate – multidimensional function of the set of univariate Poverty
Indicators.
Methods Utilized: At a Glance
• Simple Scoring
- Function of binary scores of the welfare indicators
- Intuitively, the interest is the number of welfare indicators
successfully attained
- Poverty attributes are weighted equally
- Poverty attributes and population units are treated independently
• Categorical Weighting
- Function of varying weights of categories within welfare
indicators
- Does not imply that the concern is the number of indicators
successfully attained
- Poverty thresholds are derived
- Relative weights are used, therefore, poverty attributes and
population units are not treated independently
The CBMS Core Household Indicators
• Health
- With child death
- With malnourished children 0-5 years old
• Education and literacy
- With members 6-16 years old not attending school
- With illiterate members
• Housing
- Tenure status of house and lot
- Construction of the house
The CBMS Core Household Indicators
• Access to basic services
- Source of drinking water
- Toilet facility
- Electricity
• Enabling
- Subsistence status
- Poverty status
- With at least one employed member
- With underemployed member
• Peace and order
- With victims of crime
Composite Indicator using
Simple Scoring
Construction, Ranking and Poverty Rates
Simple Scoring: Construction
• Poverty indicators are transformed with a
uniform direction
• One (1) is assigned to the positive category and
zero (0) to the negative ones to form the profiles
of the households
• Percent of scores in each household is derived
Simple Scoring: Poorest Households
Bottom
households that
attained less
than 50 percent
of the indicators
Rank
ID
Purok
1
74
Nagkakaisa
2
122
3
63
4
107
5
117
6
32
7
119
Simple
Household Composite
Head
Poverty
Measure
Yayen,
Nelson
Binggon,
Ugnayan
Manuel
Abanes,
Mahayahay
Ronie
Yayen,
Ugnayan
Romeo jr.
Padilla,
Ugnayan
Ricardo
Badenas,
Maunlad
Luorbar
Padilla,
Ugnayan
Baltazar
33.3
33.3
35.7
35.7
41.7
42.9
45.5
Simple Scoring: Well-off Households
Top households
that attained
more than 80
percent of the
indicators
Rank
ID
Purok
Household Head
Simple
Composite
Poverty
Measure
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
72
21
34
93
100
78
86
95
54
55
56
68
38
30
101
80
26
Mahayahay
Maningning
Maunlad
Nagkakaisa
Ugnayan
Nagkakaisa
Nagkakaisa
Nagkakaisa
Viscua
Viscua
Viscua
Mahayahay
Maunlad
Maunlad
Ugnayan
Nagkakaisa
Maningning
De Gusman, Noli
Refianco, Mamento
Almoguerra, Eger
Zabanal, Begesdes
llavan, agustin
Bacul, Senecio
Caranza, Joseph
Vicente, Danilo
Abique, Jesus
Magahis, Dominador
Abique, Remy
legaspi, eddie
Estoce, Avelio
Dulgeme, Pedro
yayen, francisco
Labrador, Rodencion
Dejosco, Kenny
81.8
81.8
81.8
81.8
81.8
83.3
84.6
84.6
84.6
84.6
84.6
85.7
85.7
90.9
90.9
92.3
100
Simple Scoring: Poverty Rates
Brackets of Simple Scores
Simple Composite
Poverty measure
>=30 to <40 percent
>=40 to <50 percent
>=50 to <60 percent
>=60 to <70 percent
>=70 to <80 percent
>=80 to <90 percent
>=90 to <100 percent
100 percent
Frequency Proportion Cumulative
4
3
34
38
31
13
3
1
3.2
2.4
26.8
29.9
24.4
10.2
2.4
0.8
3.2
5.5
32.3
62.2
86.6
96.9
99.2
100
Simple Scoring:
Summary of Characteristics
• Relatively easy and apparently doable
• Weights are equally and arbitrarily set
• Profile and composite poverty measure of each
household remains the same even when population units
are increased/decreased
• Weights remain the same no matter how many indicators
are included/excluded
• Composite poverty rate may vary greatly depending on
the number of indicators that must be attained
Simple Scoring: Validation
• Bottom Households
- Nelson Yayen, although in the bottom, has
considerably adequate income
- Manuel Binggon, Ricardo Padilla and Baltazar Padilla
are heads of IP households
• Top Households
- Kenny Dejosco is the barangay Captain
- Pedro Dulgeme is a tourist caretaker
- Rodencion Labrador is formerly a Municipal Council
candidate
Categorically Weighted
Composite Indicator
Construction, Ranking and Poverty Rates
Categorically Weighted Composite
Indicator: Construction
• Poverty indicators are transformed or retained in raw (as is)
categories possessing some ordinal characteristics
• A dimension reduction technique (Multiple Correspondence
Analysis) is applied on the set of population units and their poverty
attributes
• Elimination of poverty attributes is done during the dimension
reduction process
• A set of category weights within indicators is derived to form the
profiles and composite poverty measures
• Poverty thresholds are defined to compute poverty rates
Introduction to Multiple
Correspondence Analysis (MCA)
• An exploratory technique designed to analyze multi-way
tables containing some measure of correspondence
between the rows and columns
• The goal is to depict the characteristics of a set of
variables in a low dimensional way
• Variables must be either in categorical or ordinal scale
• Dimensions extracted are arranged in terms of amount
of variation explained
Categorically Weighted Composite Indicator: First MCA
Measure of Dispersion of each
Indicator, Preliminary
Indicators
Dim 1
Dim 2
Discrimination Measures
Overall (Eigenvalue)
0.1895
0.1572
TOILF2
WATSRC4
W1NTLIT
POVSUB
WELEC
W1UNDEMP
NTSCH
WMALN2
TENURE4
WVICT
W1JOB
WCHILDD2
0.5823
0.384
0.3812
0.2994
0.2963
0.2013
0.1395
0.0894
0.063
0.0178
0.0045
0.0043
0.5287
0.1703
0.2585
0.1394
0.0011
0.3006
0.2782
0.0626
0.0346
0.0585
0.1808
0.0096
.6
T O ILF 2
.5
.4
W 1UNDEMP
NT SCH
.3
W 1JO B
.2
.1
W 1NT LIT
W AT SRC4
PO VSUB
W MALN2
W VICT
T
ENURE4
WNMSH
CHILDD2
W ELEC
0.0
-.1
-.1
0.0
.1
Dimension 1
.2
.3
.4
.5
.6
Categorically Weighted Composite Indicator:
First MCA
W 1JOB
Category Quantifications
of two of the least
dispersed indicators
1.00
2.00
Missing
NMSH
1.00
2.00
Missing
Marginal
Frequency
126
1
0
Category
Quantifications
Dimension
1
2
.023
-.032
.278
1.574
Marginal
Frequency
125
2
0
Category
Quantifications
Dimension
1
2
.017
.034
.516
-3.377
Categorically Weighted Composite
Indicator: First MCA
• The first set of indicators drew a very low measure of
information of 0.1895 in the first axis and 0.1572 in the
second axis
• Toilet facility is the most dispersed indicator given the
first MCA
• ‘Child death,’ ‘at least one employed member’ and
‘makeshift housing’ are the indicators that have the
lowest discriminations
• All of the indicators follow ordering consistency with
respect to the first axis except the two of the least
dispersed indicators
Categorically Weighted Composite Indicator: Final MCA
Indicators
Measure of Dispersion of
each Indicator, Final
Discrimination Measures
.5
TOILF2
W1UNDEMP
.4
NTSCH
W1NTLIT
.3
WATSRC4
.2
POVSUB
.1
WVICTWMALN2
TENURE4
0.0
WELEC
-.1
0.0
.1
Dimension 1
.2
.3
.4
.5
.6
Dim 1
Dim 2
Overall (Eigenvalue)
0.2432
0.1955
TOILF2
WATSRC4
W1NTLIT
WELEC
POVSUB
W1UNDEMP
NTSCH
WMALN2
TENURE4
WVICT
0.584
0.3785
0.363
0.3007
0.2919
0.1994
0.1367
0.0974
0.0635
0.0168
0.4721
0.2272
0.326
0.0047
0.1043
0.3805
0.3254
0.0537
0.0126
0.0482
Categorically Weighted Composite
Indicator: Final MCA
• The measure of information has increased given
the final set of indicators
• Toilet facility is still the most dispersed indicator
given the final MCA
• Now, all of the indicators follow ordering
consistency with respect to the first axis and
ordinal direction of poverty
Categorically Weighted Composite Indicator:
Final MCA
Category Quantifications, Final
• Note that
quantifications to
the right of the first
axis are categories
attributed to welloff characteristics
Dimension 2
• The first axis can
be called the
poverty axis also
because the first
axis explains the
most variation
Quantifications
2
T ENURE4
1.00
Non subsiste
2.00
3.00
2.00 2.00
3.00 1.00
1.00
Dug/shallow
2.00
1.00
Deep/artesia
Non-poor
2.00
2.00
1.00
2.00
3.00
Poor
1.00
1
0
T O ILF 2
W AT SRC4
W ELEC
1.00
1.00
4.00
-1
W MALN2
W VICT
2.00
-2
W 1NT LIT
W 1UNDEMP
-3
NT SCH
Comm water s
-4
PO VSUB
-2
-1
Dimension 1
0
1
2
3
4
5
Categorically Weighted Composite Indicator:
Poverty Weights and Thresholds
• The category quantifications in the first axis are adjusted in scale
preserving the nature of ordering and distances to reflect a set of
positive weights
• Household profiles are based on the category weights
• Composite poverty measure in each household is the averaged
profile
• Poverty thresholds in each indicator is defined
• Overall poverty threshold is the average of the individual poverty
thresholds
Categorically Weighted Composite
Indicator: Poorest Households
Bottom ten
households according
to the Weighted
Composite Poverty
Measure
Rank
1
2
3
4
5
6
7
8
9
10
ID
Purok
122
117
63
74
107
118
115
120
90
62
Household Head
Ugnayan binggon, manuel
Ugnayan padilla, ricardo
Mahayahayabanes, ronie
Nagkakaisa Yayen, Nelson
Ugnayan yayen, romeo jr.
Ugnayan trepit, prodencio
Ugnayan delos reyes, jaime
Ugnayan sabenacio, antero
Nagkakaisa Pefrianco, Domingo
MahayahayLlavan, Baltazar
Weighted
Composite
Poverty Measure
226.4
324.2
485.1
492.8
492.8
537.1
630.3
649.1
649.5
688.9
Categorically Weighted Composite
Indicator: Well-off Households
Top ten households
according to the
Weighted Composite
Poverty Measure
Rank
ID
118
119
120
121
122
123
124
125
126
127
78
38
95
56
86
55
101
80
30
26
Purok
Household Head
Nagkakaisa Bacul, Senecio
Maunlad Estoce, Avelio
Nagkakaisa Vicente, Danilo
Viscua
Abique, Remy
Nagkakaisa Caranza, Joseph
Viscua
Magahis, Dominador
Ugnayan yayen, francisco
Nagkakaisa Labrador, Rodencion
Maunlad Dulgeme, Pedro
ManingningDejosco, Kenny
Weighted
Composite Poverty
Measure
2121.6
2201.1
2233.5
2233.5
2234
2234
2313.3
2411.3
3209.5
3564.2
Categorically Weighted Composite
Indicator: Validation Exercise
• Bottom Households
- Two bottom households of Manuel Binggon and Ricardo Padilla
are IP households
- Prodencio Trepit and Jaime Delos Reyes are also heads of IP
households
- Nelson Yayen has considerably adequate income
- Romeo Yayen Jr. only gets their livelihood from fishing
• Top Households
- Kenny Dejosco is the barangay Captain
- Pedro Dulgeme is a tourist property caretaker
- Rodencion Labrador is formerly a Municipal Council Candidate
Categorically Weighted Composite Indicator:
Poverty Rate and Correlations
Variable
Per capita income
Total household income
Household size
Educational attainment
Composite Poverty
Significance
Measure
0.4192
0.3506
-0.1774
0.4285
• Composite poverty measure
increases as per capita
income or educational
attainment increases
• Composite poverty measure
decreases as household size
decreases
0.000
0.000
0.046
0.000
Purok
Composite Poverty
Threshold=2284.94
Total
Poverty rate
Household Magnitude Proportion
Kemdeng
127
123
96.9
Mahayahay
Maningning
Maunlad
Nagkakaisa
Ugnayan
Viscua
15
27
19
25
30
11
15
26
18
24
29
11
100
96.3
94.7
96
96.7
100
Categorically Weighted Composite Indicator:
gender
Group Statistics
COMPINDE
Sex
Male
Female
N
116
11
Mean
1304.6647
1589.7727
Std. Deviation
510.26036
617.80953
Std. Error
Mean
47.37649
186.27658
Independent Samples Test
Levene's Test for
Equality of Variances
F
COMPINDE
Equal variances
assumed
Equal variances
not assumed
Sig .
.001
.982
t-test for Eq uality of Means
t
df
Sig . (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
-1.739
125
.085
-285.1081
163.95168
-609.589
39.37267
-1.483
11.331
.165
-285.1081
192.20691
-706.648
136.43171
Categorically Weighted Composite Indicator:
Sector
Group Statistics
SECGRP2
Agri
Non-ag ri
COMPINDE
N
98
24
Mean
1258.2786
1600.7167
Std. Deviation
453.22754
703.53006
Std. Error
Mean
45.78290
143.60747
Independent Samples Test
Levene's Test for
Equality of Variances
F
COMPINDE
Equal variances
assumed
Equal variances
not assumed
3.776
Sig .
.054
t-test for Eq uality of Means
t
df
Sig . (2-tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower
Upper
-2.944
120
.004
-342.4381
116.33404
-572.771
-112.105
-2.272
27.845
.031
-342.4381
150.72883
-651.270
-33.60647
Categorically Weighted Composite
Indicator: Meaning of the Second Axis
Purok
• The second axis could be
viewed as a grouping
scale of the puroks of the
barangay
Ugnayan
Maningning
Nagkakaisa
Viscua
Mahayahay
Maunlad
• The northwestern
barangays cluster
together, as well as
southwestern barangays
Mean Scores, by Purok
0.6000
0.4000
0.2000
Second Axis
• Ugnayan, the IP
community separates from
the rest of the puroks
Mean Scores
Poverty Axis
Second Axis
-0.4576
-0.7534
0.0176
0.0650
0.1900
0.1811
0.7076
0.3231
0.0375
0.3564
0.1779
0.3626
0.0000
-0.6000 -0.4000 -0.2000
0.0000 0.2000 0.4000 0.6000 0.8000
-0.2000
-0.4000
-0.6000
-0.8000
-1.0000
Poverty Axis
Categorically Weighted Composite
Indicator: Meaning of the Second Axis
Comparison between the Two
Methods
Advantages, Disadvantages and Utilization
Simple Scoring and Categorical Weighting: Comparison
• Simple Scoring
- Simple scoring is easier to adopt than the categorically weighted
composite indicator as far as LGU’s are concerned
- However, simple scoring does not utilize underlying discriminating
nature of the indicators
- Simple scoring has an arbitrary set of weights and, hence, poverty rates
- Simple weights do not change no matter how many indicators or
population units are used
- Ties are among households are more probable
• Categorically Weighted
- Categorically weighted composite indicator using MCA utilizes the
discriminating nature and associations of the indicators
- Has a constructive way of deriving weights and poverty thresholds
- Ties are among households are less probable
- Maybe difficult to be adopted
- Relative weights are derived, thus, weights change depending on the
dataset
Barangay Kemdeng: Uses of CBMS
• Provide crucial information to support planning
and project implementation at the local levels
• The comparison and analysis of the two survey
periods provides clear understanding of the
development of the barangay
– Allow the assessment, fine-tune or change programs
and project to yield more desirable results
• Data are very useful to target beneficiaries of
programs
• They are helpful to identify the poor
Barangay Kemdeng: Conclusions and
Recommendations
• The comparative analysis of data from two
CBMS surveys is a useful procedure in impact
assessment of programs
• Concern for careful planning of projects at the
local level, most specially at the barangay level
• Composite indices are good tools for ranking
households, however, further work is needed to
be done in this area