Community-Based Monitoring System (CBMS) as a tool for Promoting Equity. Mr. Joel Bancolita, Senior Research Associate.

1. Community-Based Monitoring
System (CBMS)
As a Tool for Promoting Equity
Joel E. Bancolita
PEP-Asia CBMS Network
This work was carried out by the PEP Asia-CBMS Network Team of the Angelo King Institute for Economic and Business Studies (AKI) of
De La Salle University, Manila with support from the International Development Research Centre (IDRC) and the UK Department for
International Development (DFID)

2. Outline of Presentation
• Background
– Rationale for CBMS
– Central Issues in Poverty Reduction
– Existing Sources of Data
• CBMS Methodology
• Current Applications of CBMS
• Coverage of CBMS Implementation

3. Rationale for CBMS
• CBMS, as one of the tools developed
in the early 1990s, aims to address
the:
– Need to track the impacts of policies,
programs and various shocks on the
poor and the vulnerable
– Lack of necessary disaggregated data
that can be used as inputs to
policymaking and program
implementation
– Need for a sustainable mechanism
that would facilitate evidence-based
decision making and impact-
monitoring at lower geopolitical
levels
The what and
when of anti-
poverty
programs
The who, the
where and the
why of poverty
Central Issues
in Poverty
Reduction

4. Decentralization creates new information
demands that may be best satisfied with CBMS
National
Provincial
Municipal/City
Village/Barangay
Administrative
Structure
Information
availability
National
surveys
CBMScanfillthegap

5. Objectives of CBMS
To provide policymakers and program implementers with
a regular source of necessary disaggregated data for:
• Determining the nature and extent of poverty
• Formulating appropriate policies and programs
• Identifying eligible beneficiaries for targeted programs
• Impact Monitoring
– Programs
– Shocks

6. What is CBMS?
• CBMS is designed as an organized process of data
collection, processing, validation, and integration
of data in the local development processes
• It generates a core set of indicators that are
being measured to determine the welfare status
of the population. These indicators capture the
multidimensional aspects of poverty.

7. Key features of CBMS
• It involves a census of households and not a sample survey
• It is rooted in local government and promotes community
participation
• It uses local personnel and community volunteers as monitors
• It has a core set of indicators (outcome and impact indicators)
• It establishes databanks at all geopolitical levels
• It is conducted regularly.

8. Dimensions Indicator
Health and Nutrition Proportion of children under 5 who died
Proportion of women who died due to pregnancy
related causes
Proportion of children aged 0-5 who are
malnourished
Housing Proportion of households in makeshift housing
Proportion of households who are
informal settlers
Proportion of households without access to safe
water supply
Proportion of households without access to sanitary
toilet facilities

9. Dimensions Indicator
Education Proportion of children 6-11 years old who are not
attending elementary school
Proportion of children 12-15 years old who are not
attending secondary school
Proportion of children 6-15 years old who are not
attending school
Income and Livelihood Proportion of households with income below the
poverty threshold
Proportion of households with income below the
food threshold
Proportion of households who experienced hunger
due to food shortage
Proportion of persons in the labor force who are
unemployed
Peace and Order Proportion of persons who are victims of crime

10. Methodology CBMS
Data Collection • Household census done by trained local
enumerators
• Instruments for Data Collection
o 12 page household profile questionnaire (available
in English and local dialect)
o 6 page village profile questionnaire
Data Processing • Done by trained local data processors using a
freeware customized for CBMS data encoding,
processing, consolidation, and digitized poverty
mapping.
Validation • Survey findings are presented and discussed in a
community forum

11. Methodology CBMS
Establishment of Database • Databases are established at
different geopolitical levels
(province/municipal/city/
village level)
• A CBMS national repository
is currently maintained at
Ministry of Interior and Local
Government (DILG), National
Anti-Poverty Commission
(NAPC), and at the PEP Asia-
CBMS Network Office.

12. CBMS
PROCESS
(APP)
Step 1
Advocacy /
Organization
Step 2
Data Collection,
GPS Reading
and
Data Transmission
(Integrated Training
Modules 1 and 2)
Step 3
Processing and
Mapping
(Training
Module 3)
Step 4
Data validation
And Community
Consultation
Step 6
Plan Formulation
(Training Module 4)
Step 7
Dissemination/
Implementation
And Monitoring
Step 5
Knowledge
(Database)
Management

13. • Web and Android-
based Mobile Data
Capture System
• CBMS StatSimPro
• Quantum GIS
(QGIS)
Android-
Based Mobile
Data Capture
(Scan)
QGIS
Software
CBMS
StatSimPro
CBMS Data
and
Indicators
CBMS Web
Server
(Portal)
CBMS Softwares are provided to
LGU partners implementing
CBMS for Free

14. CBMS Accelerated Poverty
Profiling (CBMS-APP)

15. CURRENT APPLICATIONS OF CBMS

16. Data Generated from CBMS
• Data can be disaggregated across population
sub-groups, and by geo-political levels (by
barangay/village, municipality/city, province)
• CBMS, conducted on a regular basis, can
generate panel data that can aid tracking of
conditions of households/ groups of
population over time.

17. Poverty Maps
• “The Many Faces of
Poverty”, Volume 4
1. Balanga City
2. Masbate City
3. Olongapo City
4. Pasay City
5. Science City of Munoz
6. Tabaco City
7. Tayabas City
Use of CBMS in Poverty/development profiling, analysis and diagnostics

18. Human Development Report
Palawan is the first
province to come up with
the publication of the
Human Development
Report in 2000 and 2006
which marks its
achievement of being the
first province to use
household level data as
basis for its development
agenda
Use of CBMS in Poverty/development profiling, analysis and diagnostics

19. Uses of CBMS
• For preparation of local development plans,
budgets, and other policy-action programs
– Annual investment plans
– Disaster risk reduction management plans
– Gender and development plans
– Local poverty reduction action plans

20. Diagnosing non-participation
Use of CBMS for design of interventions and targeting of program beneficiaries
123 out of 326
children 12-15 years
old are not attending
secondary school
Households with
children 12-15 years
who are not in
secondary school,
Barangay 179, Pasay
City

21. Disparity of school attendance across income class and age
Proportion of children 6-15 who are not attending school, 2011 and 2014 (CBMS APP
Partial results)
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
1 2 3 4 5 6 7 8 9 10
Income decile
All: 2011
All: 2014
Male: 2011
Male: 2014
Female: 2011
Female: 2014
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
6 7 8 9 10 11 12 13 14 15
Age

22. As MDG Benchmarking & Monitoring Tool
Sub-national MDG Reports Using
CBMS Data
1. Agusan del Norte
2. Agusan del Sur
3. Biliran
4. Camarines Norte
5. Eastern Samar
6. Marinduque
7. Romblon
8. Siquijor
9. Sarangani
10. Batangas
11. Valenzuela City
Use of CBMS for monitoring the achievement of the MDGs through Sub-national MDG
Reports
2010 2013

23. Uses of CBMS
• For enriching existing databases
– Household /individual level databases
– Digitized poverty maps

24. Proportion of Households who have Experienced
Hunger by Municipality, Barangay
Agusan del Sur, 2005
Sibagat
14.2
Talacogon
6.8
Esperanza
24.8
Bunawan
12.3
San Luis
6.6
Trento
7.0Loreto
17.9
Rosario
9.9
Sta. Josefa
11.1
La Paz
21.4
Veruela
39.8
San Francisco
7.2
Prosperidad
9.3
Bayugan
14.1
Sibagat
14.2
Talacogon
6.8
Esperanza
24.8
Bunawan
12.3
San Luis
6.6
Trento
7.0
Loreto
17.9
Rosario
9.9
Sta. Josefa
11.1
La Paz
21.4
Veruela
39.8
San Francisco
7.2
Prosperidad
9.3
Bayugan
14.1
Agusan del Sur: 13.9

25. Proportion of households who have
experienced hunger by Barangay
Municipality of Esperanza, Agusan del Sur, 2005
Las Nieves, Agusan del Norte
Bayugan
San Luis
Agusan del Sur: 13.9
Esperanza: 24.8

26. Uses of CBMS
• For monitoring impacts of programs
• Examples:
–Conditional Cash Transfer (4Ps)
–Unconditional Cash Transfer (UCT)
–Water project

27. Location of 4Ps
beneficiary
households with
children not
attending school,
Pasay City, 2014
Source: CBMS Census,
Pasay City 2014 (Partial
results)

28. Impact of 4Ps on school participation rate
of 6-14 year old children
Matching using PSM
Difference in difference
School
participation rate
among 6-14 (Set
2012/2013)
4Ps non-4Ps
2011 0.888 0.926
2014 0.969 0.971
Difference 0.082 0.045 0.840
0.860
0.880
0.900
0.920
0.940
0.960
0.980
1 2
4Ps:2012,2013
control:2012.2013

29. 2011
Age group
School Participation Status of Panel Members
Aged 6-18 among 4Ps Beneficiaries for 2012
2011
2011
118
children
6-18
years old
2011 School
participation 2014
7
23
children
15-18 years
old
95
children
6-14 years
old
10
1
(10%)
9
(90%)
10
(8.5%)
9
(11%)
85
(72%)
73
(89%)
1
(25%)
3
(75%)14
(11.9%)
3
9
(7.6%)
2
(100%)

30. Mid-upper arm circumference (MUAC)
• All MUACs increased and
significant in ALL areas
and outside Tacloban
Round 1 Round 2 t P-value
ALL 14.90 15.31 6.554 0.000
Tacloban City 15.24 15.30 0.717 0.475
Outside
Tacloban City 14.70 15.32 7.423 0.000
14.30
14.40
14.50
14.60
14.70
14.80
14.90
15.00
15.10
15.20
15.30
15.40
ROUND 1 ROUND 2
MUAC
ALL Tacloban City Outside Tacloban City

31. Mid-Upper Arm Circumference of
children 0-5 by age
Age (1st
round) Round 1 Round 2 t
P-
value
0 14.1 14.7 4.3400.000
1 14.4 14.8 3.4720.001
2 15.0 15.6 4.3020.000
3 15.5 15.7 0.8730.385
4 15.7 15.7 0.0940.926
5 15.9 16.2 1.5170.136
13.0
13.5
14.0
14.5
15.0
15.5
16.0
16.5
0 1 2 3 4 5
AGE
MUAC
Round 1 Round 2
• All MUACs increased and
significant in ages 0,1,2

32. Malnutrition and child diet diversity
• Proportion of malnourished children decreased significantly among
households with increased child diet diversity
• Among households with decreased child diet diversity, malnutrition
prevalence increased although insignificant
Malnutrition
Prevalence
Round 1 Round 2 t P-value
Increased
child diet
diversity 8.1% 4.2% 1.679 0.094
Decreased
child diet
diversity 4.3% 5.7% -0.851 0.395
4.0%
4.5%
5.0%
5.5%
6.0%
6.5%
7.0%
7.5%
8.0%
8.5%
ROUND 1 ROUND 2
Malnutrition
Increased child diet diversity Decreased child diet diversity

33. Outcome/Impact Monitoring
Implementation of Poder Project, Brgy. Añgas, Tabaco City 2009
Before After

34. Uses of CBMS
• As basis for response during disaster,
calamities and emergencies
• Vulnerability to Climate Change
–Vulnerability index is a composite of
exposure to hazard, sensitivity and lack of
adaptive capacity

35. Climate Change Vulnerability Index per Municipality,
Province of Marinduque, 2011
Climate Change Vulnerability Index per Barangay
Province of Marinduque, 2011
Boac
0.309
Santa Cruz
0.789
Toriijos
0.371
Buenavista
0.518
Gasan
0.522
Mogpog
0.518
Boac
Santa Cruz
Toriijos
Buenavista
Gasan
Mogpog

36. Current and projected proportion of
households with malnourished children
Source: CBMS Censuses 2007-2010

37. Current and projected proportion of households with
malnourished children, Surigao del Norte
Source: CBMS Censuses
2007-2010

38. Current and projected vulnerability (in terms
of malnutrition) in Mainit, Surigao del Norte
Source: CBMS Censuses 2007-2010

39. Uses of CBMS
• As inputs in the Grassroots Participatory
Budgeting Process (GPB), formerly known
as Bottom-up budgeting
• As contained in JMC of DBM-DILG-DSWD-
NAPC in 2012 and 2014, the focus LGUS
shall collect and collate all relevant
information, statistics, and sex-
aggregated data for poverty reduction
planning from CBMS

40. CBMS design is flexible to accommodate
community-specific indicators
• Natural calamities and disaster management
• Environment Protection
• Women’s well being
• Child Labour
• Migration
• Disability
• Community service delivery
• Social Protection
• Entrepreneurship

41. CBMS Implementing Countries, 2000-present
AFRICA: Benin, Burkina Faso, Ethiopia, Ghana, Kenya, Nigeria, Niger, Senegal , South Africa, Tanzania, Togo
ASIA: Bangladesh, Cambodia, Indonesia, Lao PDR, Pakistan, Philippines, Sri Lanka, Viet Nam
SOUTH AMERICA: Argentina, Bolivia, Peru
NORTH AMERICA: Haiti

42. Coverage of CBMS implementation
in the Philippines
as of October 08, 2014
23,276 barangays
in 862 municipalities and 69 cities
in 73 provinces (32 of which are
provincewide)
CBMS APP track
CBMS PAPER track

43. About the CBMS Network
• The CBMS Network in
particular supports the
development and
institutionalization of
systems for monitoring
poverty at the local
level while promoting
equity and empowering
communities to
participate in the
development process

44. THANK YOU
PEP Asia - CBMS Network Office
Angelo King Institute for Economic and Business Studies
De La Salle University
Rm I-1016, 10th Floor, Angelo King International Center,
Estrada corner Arellano Streets, Malate, Manila
Telefax (632) 5262067
Email at: celia.reyes@benilde.edu.ph; cbms.network@gmail.com
Website: www.pep-net.org

45. To learn more
• Visit: http://pep-net.org
• You might want to attend the 11th CBMS
National Conference on Feb. 2-4, 2015 in
Manila
• Email: celia.reyes@benilde.edu.ph;
cbms.network@gmail.com

46. Proportion of children 0-5 who are
malnourished (using MUAC)
Round 1 Round 2 t
P-
value
ALL 5.3 4.8 0.406 0.685
Tacloban City 4.1 3.1 0.609 0.543
Outside
Tacloban City 6.0 5.8 0.105 0.917
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
ROUND 1 ROUND 2
Malnutrition
ALL Tacloban City Outside Tacloban City
• All proportions decreased
but not significantly

47. Proportion of households without access to safe water supply,
by municipality, Province of Marinduque
2005 2008
BOAC
GASAN
BUENAVISTA
TORRIJOS
SANTA CRUZ
MOGPOG
19.1
17.4
14.6
7.7
10.2
13.6
BOAC
GASAN
BUENAVISTA
TORRIJOS
SANTA CRUZ
MOGPOG
25.5
11.9
8.5
6.7
9.2
13.5
Source: CBMS Census 2005 and 2008, Province of Marinduque

48. Proportion of households without access to safe water supply,
by barangay, Province of Marinduque
2005 2008
BOAC
GASAN
BUENAVISTA
TORRIJOS
SANTA CRUZ
MOGPOG
25.5
11.9
8.5
6.7
9.2
13.5
BOAC
GASAN
BUENAVISTA
TORRIJOS
SANTA CRUZ
MOGPOG
19.1
17.4
14.6
7.7
10.2
13.6
Source: CBMS Census 2005 and 2008, Province of Marinduque