Utilizing CBMS in Monitoring and Targeting the Poor: The case of Barangay Kemdeng, San Vicente,...

Utilizing CBMS in Monitoring and Targeting the Poor: The case of Barangay Kemdeng, San Vicente, PalawanA CBMS Philippines Research Paper prepared for the PEP Network MeetingJune 18, 2004

Outline of presentationPart 1:

ObjectivesPhysical Characteristic of KemdengResults of the 2000 and 2002 CBMS Survey

Part 2:

Use of Scores in Ranking HouseholdsUses of CBMS at the local levelConclusions and Recommendations

General ObjectivesMonitor 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

Barangay Kemdeng: DemographyIn 2000, there were 135 hhlds with a population of 713 persons and hhld size of 5.3These figures declined in 2002 with 127 hhlds, 612 persons and hhld size of 4.8The main reason for the decline in population count is migration

due to closure of small-scale silica mining operation in Purok Maunlad in 2000other family members who study or work in other locations in Puerto Princesa city or in Manila

Barangay Kemdeng: DemographyThe 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.

Other results:

Barangay Kemdeng: Health and NutritionIn 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 bornDue to lack of access to safe water and poor sanitation

Barangay Kemdeng: Health and NutritionIn 2000, 7 ( or 2 males and 5 females) severely malnourished children were recorded among 137 childrenNo 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 NutritionIn 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 workPoor health status of some of the mothersLack of money of some households to be able to complete the six month nutrition regimeDue to the poor access to safe water and sanitation in the barangay

Barangay Kemdeng: Access to Basic ServicesIn 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 ServicesMost 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 ServicesIn 2000, 80 hhlds or 59.3% have access to sanitary toilet facilityThe 2002 survey reveal a drastic decline with only 31 hhlds or 24.4% of hhlds with accessThe reason for these are:

Toilet bowls distributed in previous sanitation program were not durableDecline 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 ServicesThe 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 ServicesOnly 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

Chart3

80.876.6

4028.6

8075

81.878.7

2000

2002

Proportion

Elementary school participation rates among 6-11 years old children

Sheet1 (3)

Demography

20002002

Households135127

Persons713612

HH size5.34.8

Participation in Schools by level

2000200220002002

NumberNumberPercentPercent

Total8287.3

IP33.345.5

Male82.487.5

Female81.687

Sheet1 (3)

00

00

00

00

2000

2002

Proportion

School participation rates

Sheet1 (2)

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Secondary30.627.3

IP00

Male35.530

Female2524

Sheet1 (2)

00

00

00

00

2000

2002

Proportion

Secondary school participation rates

Sheet1

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Elementary848280.876.6

IP224028.6

Male48458075

Female363781.878.7

Sheet1

00

00

00

00

2000

2002

Proportion


Sheet2

Sheet3

Barangay Kemdeng: EducationTeachers provide free lunch for students, especially to IP studentsReasons for decline:

School has only 3 classroomsFamilies have difficulty in meeting other school expensesSome students are already working in the fields, especially IP children


Chart2

30.627.3

00

35.530

2524

2000

2002

Proportion

Secondary school participation ratesamong 12-15 year old children

Sheet1 (2)

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Secondary30.627.3

IP00

Male35.530

Female2524

Sheet1 (2)

00

00

00

00

2000

2002

Proportion


Sheet1

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002



IP224028.6

Male48458075

Female363781.878.7

Sheet1

00

00

00

00

2000

2002

Proportion

Elementary school participation rates

Sheet2

Sheet3

Barangay Kemdeng: EducationReasons 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


Chart4

8287.3

33.345.5

82.487.5

81.687

2000

2002

Proportion

School participation rates among 6-16 year old children

Sheet1 (3)

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Total8287.3

IP33.345.5

Male82.487.5

Female81.687

Sheet1 (3)

2000

2002

Proportion


Sheet1 (2)

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Secondary30.627.3

IP00

Male35.530

Female2524

Sheet1 (2)

2000

2002

Proportion


Sheet1

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002



IP224028.6

Male48458075

Female363781.878.7

Sheet1

2000

2002

Proportion


Sheet2

Sheet3

Barangay Kemdeng: EducationThere are children 6-11 years old who are still attending daycare, kindergarten or preparatory levelThere are children 12-15 who are still at the elementary level

Barangay Kemdeng: Employment

Chart6

89.792.3

100100

96.194.9

78.288.2

2000

2002

Proportion

Employment Rate

Sheet1 (6)

Demography

20002002

Households135127

Persons713612

HH size5.34.8

Underemployment Rate

2000200220002002


Total56.791.6

IP00

Male57.894.7

Female54.485

Sheet1 (6)

2000

2002

Proportion


Sheet1 (5)

Demography

20002002

Households135127

Persons713612

HH size5.34.8

Employment Rate

2000200220002002


Total89.792.3

IP100100

Male96.194.9

Female78.288.2

Sheet1 (5)

2000

2002

Proportion

Employment Rate

Sheet1 (4)

Demography

20002002

Households135127

Persons713612

HH size5.34.8

Labor force participation rate

2000200220002002


Total65.850.1

IP

Male82.962.6

Female35.935.6

Sheet1 (4)

2000

2002

Proportion

Labor Force Participation Rate

Sheet1 (3)

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Total8287.3

IP33.345.5

Male82.487.5

Female81.687

Sheet1 (3)

2000

2002

Proportion


Sheet1 (2)

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Secondary30.627.3

IP00

Male35.530

Female2524

Sheet1 (2)

2000

2002

Proportion


Sheet1

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002



IP224028.6

Male48458075

Female363781.878.7

Sheet1

2000

2002

Proportion


Barangay Kemdeng: EmploymentAgriculture employs 72.6% of the employed in the barangay.Fishing and forestry are also among the common occupations of those employedShare of the employed in the industry sector declined from 7.5% in 2000 to 3.8% in 2002Most male workers are in the agriculture sector while females are in the services sectorMost employed IP are in the agriculture sector, undertaking farming activities in the upland and clearing of timberland

Barangay Kemdeng: EnablingPovertySubsistence

Chart1

64.427.6

83.340

45.915.7

33.340

2000

2002

Proportion

Incidence of Poverty

Sheet1 (7)

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Total64.427.6

IP83.340

Total45.915.7

IP33.340

Sheet1 (7)

2000

2002

Proportion


Sheet1 (6)

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Total56.791.6

IP00

Male57.894.7

Female54.485

Poverty

Subsistence

Sheet1 (6)

2000

2002

Proportion


Sheet1 (5)

Demography

20002002

Households135127

Persons713612

HH size5.34.8

Employment Rate

2000200220002002


Total89.792.3

IP100100

Male96.194.9

Female78.288.2

Sheet1 (5)

2000

2002

Proportion

Employment Rate

Sheet1 (4)

Demography

20002002

Households135127

Persons713612

HH size5.34.8

Labor force participation rate

2000200220002002


Total65.850.1

IP

Male82.962.6

Female35.935.6

Sheet1 (4)

2000

2002

Proportion

Labor Force Participation Rate

Sheet1 (3)

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Total8287.3

IP33.345.5

Male82.487.5

Female81.687

Sheet1 (3)

2000

2002

Proportion


Sheet1 (2)

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002


Secondary30.627.3

IP00

Male35.530

Female2524

Sheet1 (2)

2000

2002

Proportion


Sheet1

Demography

20002002

Households135127

Persons713612

HH size5.34.8


2000200220002002



IP224028.6

Male48458075

Female363781.878.7

Sheet1

2000

2002

Proportion


Barangay Kemdeng: Enabling

More accurate income estimates were taken from the 2002 CBMS surveyIn 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 resultsBased on the CBMS results, the barangay has not been performing well.Areas to prioritize:

Access to safe waterAccess to sanitary toiletAccess to electricityHealth and nutritionEmploymentElementary and secondary participation

Barangay Kemdeng: Summary of resultsGender concerns:

Males are more vulnerable in the areas of health while females are not performing well in nutritionFemales slightly performs better when it comes to elementary participation while males are performing well in secondary school participation rateMales 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 servicesThe indicators are interrelated and explains some of the trends

Barangay Kemdeng: Benefit Incidence AnalysisProportion and distribution of households with children 6-16 years old who are attending public school, by per capita income decile

Per Capita Income DecileTotal Households with childre 6-11 years oldHouseholds with children attending elementary schoolMagnitudeProportion (row)Proportion (column)Kemdeng706491.41001st7685.79.42nd7685.79.43rd7685.79.44th7710010.95th7710010.96th7710010.97th7685.79.48th7685.79.49th7685.79.410th7710010.9

Barangay Kemdeng: Benefit Incidence Analysis

Barangay Kemdeng: Benefit Incidence AnalysisThe heads of these households have low educational attainment, only reaching at least the elementary levelNo access to basic servicesTwo out of the six households are IP householdsProximity of the household to the location of the school

Barangay Kemdeng: Benefit Incidence Analysis

Use of Scores in Ranking the HouseholdsComparison between Simple and Categorically Weighted Composite Indicator

Rationale of Composite IndicatorRicher concept of multidimensional poverty

Identifying the poorest households

Discriminating between geopolitical and sub-geopolitical units

Resource allocation

Impact assessment

Composite Indicator: Brief DescriptionIdeally, 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 TermsTarget 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 GlanceSimple Scoring

Function of binary scores of the welfare indicatorsIntuitively, the interest is the number of welfare indicators successfully attainedPoverty attributes are weighted equallyPoverty attributes and population units are treated independently

Categorical Weighting

Function of varying weights of categories within welfare indicatorsDoes not imply that the concern is the number of indicators successfully attainedPoverty thresholds are derivedRelative weights are used, therefore, poverty attributes and population units are not treated independently

The CBMS Core Household IndicatorsHealth

With child deathWith malnourished children 0-5 years old

Education and literacy

With members 6-16 years old not attending schoolWith illiterate members

Housing

Tenure status of house and lotConstruction of the house

The CBMS Core Household IndicatorsAccess to basic services

Source of drinking waterToilet facilityElectricity

Enabling

Subsistence statusPoverty statusWith at least one employed memberWith underemployed member

Peace and order

With victims of crime

Composite Indicator using Simple ScoringConstruction, Ranking and Poverty Rates

Simple Scoring: ConstructionPoverty 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 HouseholdsBottom households that attained less than 50 percent of the indicators

Sheet1

RankIDPurokHousehold HeadSimple Composite Poverty Measure

174NagkakaisaYayen, Nelson33.3

2122UgnayanBinggon, Manuel33.3

363MahayahayAbanes, Ronie35.7

4107UgnayanYayen, Romeo jr.35.7

5117UgnayanPadilla, Ricardo41.7

632MaunladBadenas, Luorbar42.9

7119UgnayanPadilla, Baltazar45.5

Sheet2

Sheet3

Simple Scoring: Well-off HouseholdsTop households that attained more than 80 percent of the indicators

Sheet1

RankIDPurokHousehold HeadSimple Composite Poverty Measure

11172MahayahayDe Gusman, Noli81.8

11221ManingningRefianco, Mamento81.8

11334MaunladAlmoguerra, Eger81.8

11493NagkakaisaZabanal, Begesdes81.8

115100Ugnayanllavan, agustin81.8

11678NagkakaisaBacul, Senecio83.3

11786NagkakaisaCaranza, Joseph84.6

11895NagkakaisaVicente, Danilo84.6

11954ViscuaAbique, Jesus84.6

12055ViscuaMagahis, Dominador84.6

12156ViscuaAbique, Remy84.6

12268Mahayahaylegaspi, eddie85.7

12338MaunladEstoce, Avelio85.7

12430MaunladDulgeme, Pedro90.9

125101Ugnayanyayen, francisco90.9

12680NagkakaisaLabrador, Rodencion92.3

12726ManingningDejosco, Kenny100

Sheet2

Sheet3

Simple Scoring: Poverty RatesBrackets of Simple Scores

Sheet1

Simple Composite Poverty measureFrequencyProportionCumulative

>=30 to =40 to =50 to =60 to =70 to =80 to =90 to

Simple Scoring: Summary of CharacteristicsRelatively 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: ValidationBottom 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 CaptainPedro Dulgeme is a tourist caretakerRodencion Labrador is formerly a Municipal Council candidate

Categorically Weighted Composite IndicatorConstruction, Ranking and Poverty Rates

Categorically Weighted Composite Indicator: ConstructionPoverty 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 MCAMeasure of Dispersion of each Indicator, Preliminary

Sheet1

IndicatorsDim 1Dim 2

Overall (Eigenvalue)0.18950.1572

TOILF20.58230.5287

WATSRC40.3840.1703

W1NTLIT0.38120.2585

POVSUB0.29940.1394

WELEC0.29630.0011

W1UNDEMP0.20130.3006

NTSCH0.13950.2782

WMALN20.08940.0626

TENURE40.0630.0346

WVICT0.01780.0585

W1JOB0.00450.1808

WCHILDD20.00430.0096

Sheet2

Sheet3

Categorically Weighted Composite Indicator: First MCACategory Quantifications of two of the least dispersed indicators

Categorically Weighted Composite Indicator: First MCAThe 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 MCAMeasure of Dispersion of each Indicator, Final

Sheet1

IndicatorsDim 1Dim 2IndicatorsDim 1Dim 2

Overall (Eigenvalue)0.18950.1572Overall (Eigenvalue)0.24320.1955

TOILF20.58230.5287TOILF20.5840.4721

WATSRC40.3840.1703WATSRC40.37850.2272

W1NTLIT0.38120.2585W1NTLIT0.3630.326

POVSUB0.29940.1394WELEC0.30070.0047

WELEC0.29630.0011POVSUB0.29190.1043

W1UNDEMP0.20130.3006W1UNDEMP0.19940.3805

NTSCH0.13950.2782NTSCH0.13670.3254

WMALN20.08940.0626WMALN20.09740.0537

TENURE40.0630.0346TENURE40.06350.0126

WVICT0.01780.0585WVICT0.01680.0482

W1JOB0.00450.1808

WCHILDD20.00430.0096

Sheet2

Sheet3

45.bin

Categorically Weighted Composite Indicator: Final MCAThe 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 MCACategory Quantifications, FinalNote that quantifications to the right of the first axis are categories attributed to well-off characteristics

The first axis can be called the poverty axis also because the first axis explains the most variation

Categorically Weighted Composite Indicator: Poverty Weights and ThresholdsThe 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

Sheet1

RankIDPurokHousehold HeadWeighted Composite Poverty Measure

1122Ugnayanbinggon, manuel226.4

2117Ugnayanpadilla, ricardo324.2

363Mahayahayabanes, ronie485.1


5107Ugnayanyayen, romeo jr.492.8

6118Ugnayantrepit, prodencio537.1

7115Ugnayandelos reyes, jaime630.3

8120Ugnayansabenacio, antero649.1

990NagkakaisaPefrianco, Domingo649.5

1062MahayahayLlavan, Baltazar688.9

Sheet2

Sheet3

Categorically Weighted Composite Indicator: Well-off Households

Top ten households according to the Weighted Composite Poverty Measure

Sheet1

















12286NagkakaisaCaranza, Joseph2234

12355ViscuaMagahis, Dominador2234




12726ManingningDejosco, Kenny3564.2

Sheet2

Sheet3

Categorically Weighted Composite Indicator: Validation ExerciseBottom Households

Two bottom households of Manuel Binggon and Ricardo Padilla are IP householdsProdencio Trepit and Jaime Delos Reyes are also heads of IP householdsNelson Yayen has considerably adequate incomeRomeo Yayen Jr. only gets their livelihood from fishing

Top Households

Kenny Dejosco is the barangay CaptainPedro Dulgeme is a tourist property caretakerRodencion Labrador is formerly a Municipal Council Candidate

Categorically Weighted Composite Indicator: Poverty Rate and CorrelationsComposite poverty measure increases as per capita income or educational attainment increases

Composite poverty measure decreases as household size decreases

Composite Poverty Threshold=2284.94

Sheet1














11938MaunladEstoce, Avelio2201.1PurokTotal HouseholdsssPoverty rate

12095NagkakaisaVicente, Danilo2233.5MagnitudeProportion


12286NagkakaisaCaranza, Joseph2234Kemdeng12712396.9


124101Ugnayanyayen, francisco2313.3Mahayahay1515100

12580NagkakaisaLabrador, Rodencion2411.3Maningning272696.3

12630MaunladDulgeme, Pedro3209.5Maunlad191894.7

12726ManingningDejosco, Kenny3564.2Nagkakaisa252496

Ugnayan302996.7

Viscua1111100

Sheet2

Sheet3

Sheet1














11938MaunladEstoce, Avelio2201.1PurokTotal HouseholdsPoverty rate

12095NagkakaisaVicente, Danilo2233.5MagnitudeProportion


12286NagkakaisaCaranza, Joseph2234Kemdeng12712396.9


124101Ugnayanyayen, francisco2313.3Mahayahay1515100

12580NagkakaisaLabrador, Rodencion2411.3Maningning272696.3

12630MaunladDulgeme, Pedro3209.5Maunlad191894.7

12726ManingningDejosco, Kenny3564.2Nagkakaisa252496

Ugnayan302996.7

Viscua1111100

VariableComposite Poverty MeasureSignificance

Per capita income0.41920.000

Total household income0.35060.000

Household size-0.17740.046

Educational attainment0.42850.000

Sheet2

Sheet3

Categorically Weighted Composite Indicator: gender

Categorically Weighted Composite Indicator: Sector

Categorically Weighted Composite Indicator: Meaning of the Second AxisThe second axis could be viewed as a grouping scale of the puroks of the barangay

The northwestern barangays cluster together, as well as southwestern barangays

Ugnayan, the IP community separates from the rest of the puroks

Income Summary

Source of IncomeObsMeanStandard DeviationMinMax

Total Income from Entrpreneurial Activities12784546.790498.40761000

Total Income from Salaries and Wages12712583.631963.50192000

Total Income from Other Sources12712277.129564.20295200

Total Income from Wages and Entrepreneurial Activities12797130.492435.90809000

Total Household Income127109229.291960.86400818600

dim-purok

PurokMean Scores

Poverty AxisSecond Axis

Ugnayan-0.4576-0.7534

Maningning0.01760.0650

Nagkakaisa0.19000.1811

Viscua0.70760.3231

Mahayahay0.03750.3564

Maunlad0.17790.3626

dim-purok

Purok

Mean

Dimension 2

Sheet1

PurokTotal HouseholdsPoverty rateCorrelations

MagnitudeProportion

Composite Poverty MeasureSignificance

Kemdeng12712396.94Total household income0.35060.0001

Household size-0.17740.0461

Mahayahay1515100.00Educational attainment0.42850.0000

Maningning272696.31

Maunlad191894.71

Nagkakaisa252496.01

Ugnayan302996.71

Viscua1111100.00

Purok

Mean

Dimension 1

Poverty Axis

Second Axis

Mean Scores, by Purok

Totinr

rankhcnpurokmname02totinr02

147MaunladTabangay, Floresto0

26ManingningRadam, Felix0

383NagkakaisaAbus, Cherlito0

499Ugnayanmabutin, flaviano0

521ManingningRefianco, Mamento570

6119Ugnayanpadilla, baltazar4000

789NagkakaisaBacuel, Pepe Sr.6000

8124Ugnayanyayen, romeo sr.8000

9117Ugnayanpadilla, ricardo12000

10107Ugnayanyayen, romeo jr.12000

1149ViscuaNangit, Enrique15000

1285NagkakaisaLlavan, Rey15000

137Maningningabela, Trinidad15000

1436Maunladdacillo, Vicente15000

15118Ugnayantrepit, prodencio15000

16101Ugnayanyayen, francisco16000

1781NagkakaisaSolis, Noel16500

1872Mahayahayde gusman, noli16500

1919ManingningZabanal, Victor18500

2038MaunladEstoce, Avelio19250

2197Ugnayanabigue, francisco20000

2223ManingningLaguta, Renato22592

2362MahayahayLlavan, Baltazar23610

2445MaunladCabanes, Garciano24000

25122Ugnayanbinggon, manuel28000

2661MahayahayBadenas, Querubin30000

2759Mahayahaybesitulo, antonio31840

28109Ugnayancasuga, audy32500

2974NagkakaisaYayen, Nelson34800

30123Ugnayancasuga, aurelio36000

3142MaunladCabebe, Josie36000

3263Mahayahayabanes, ronie36000

3339MaunladYayen, Elva36200

3410ManingningPacaldo, Espectation38600

35102Ugnayangaayono, eddie41000

3692NagkakaisaBaconga, Rosendo42000

3757ViscuaBaquiran, Reynan46000

3870Mahayahaysubron, rubie46800

3932MaunladBadenas, Luorbar47920

40103Ugnayanbaconga, prescilia49000

4167MahayahayPolinar, Brexcio49000

42110Ugnayancaab, anasita50885

43120Ugnayansabenacio, antero51000

44105Ugnayandecio, rolly51200

4520ManingningLlauan, Alex53544

4690NagkakaisaPefrianco, Domingo55000

4794Mahayahaymangaya, ricky57800

4888NagkakaisaBesitulo, Gerry58000

4994NagkakaisaRaet, Reynaldo58500

5025ManingningLaguna, Rolando60575

5137Maunladdacillo, Edgar63200

5296NagkakaisaSolis, Welhim65140

5371Mahayahaycabillan, edwin66000

5411ManingningCamposano, alvin66500

551ManingningBaconga, Reynaldo70200

56104Ugnayanyayen, edgar70480

5753ViscuaMondragon, Randy72000

58106Ugnayanyayen, edwin72000

59111Ugnayanpadilla, diomedes72000

6054ViscuaAbique, Jesus73744

6164Mahayahayfernandez, ramil76860

6282NagkakaisaAbanes, Emerita77520

6335MaunladFamoso, Agustina82000

64108Ugnayancaab, matio82770


6656ViscuaAbique, Remy87890

67113Ugnayancamot, elpidio90000

6828MaunladJardin, Lamberto92360

6965Mahayahayloque, rene95560

7016ManingningDacillo, Generoso Jr.98544

715ManingningBaconga, Tranquilino99200

7218ManingningOab, Nexon99720

7358ViscuaBaquiran, Ihimenado100890

7479NagkakaisaCamena, Eulequio101000


7613ManingningLagutan, reynaldo103000

77114Ugnayancamot, elmer103200

7876NagkakaisaDacillo, Virgilia103860

7941MaunladDagsan, Ernesto104000

802ManingningMontecillo, Rodel105100

8143MaunladMadamo, Yully107750

829ManingningDela Torre, Gregorio110000

83125Ugnayancaab, ernesto110800

8427ManingningGabasan, Nerwin110800

8517ManingningOab, andres115000

8648ViscuaBacuel, Carolina115600

8730MaunladDulgeme, Pedro120000

88112Ugnayanramilo, francisco121000

8946MaunladCabanes, Prudencio121110

90127NagkakaisaGabasan, Sixto123040

9122ManingningPaz, Pablito126500

9260Mahayahayopeder, moeses126549

9344MaunladAbian, Nerio126600

9424ManingningDionisio, Julius128000

9587NagkakaisaLlavan, Sergio Sr.130000

9691NagkakaisaYayen, Lope133860

9766Mahayahayello, felix136380

9831Maunladsolis, Bernabe140000

9951ViscuaAbique, William142000

1008ManingningGepella, Melchor148950

10184NagkakaisaTabarangao, Roger150000

10250ViscuaCastro, Roque150000

103115Ugnayandelos reyes, jaime150000

104126Ugnayansabenascio, oscar150000

10595NagkakaisaVicente, Danilo154600

10669Mahayahaycadlaon, rodolfo157875

10712ManingningCastro, Marcelo Jr.158500

10829MaunladJardin, Felizardo160284

109121Ugnayansabenacio, juanito165000

11068Mahayahaylegaspi, eddie169000

11134MaunladAlmoguerra, Eger170952


11377NagkakaisaComena, Eddie177060

11415ManingningOab, Prudente178000

115116Ugnayanbeloya, virgilio180000

11675NagkakaisaOab, Roman Sr.181280

11778NagkakaisaBacul, Senecio192000

11852ViscuaAmparo, Victor192000

1194ManingningDelos Santos, Arsenio198000

12040NagkakaisaAbian, rafael206500

12180NagkakaisaLabrador, Rodencion207000

12214ManingningTrinidad, Jose234200

12393NagkakaisaZabanal, Begesdes239976

12498Ugnayanllavan, elesio242000

12533MaunladMaceda, Jovencio325080

1263ManingningPacaldo, Juan333000

127100Ugnayanllavan, agustin809000

Totin

rankhcnpurokmname02totin02

1119Ugnayanpadilla, baltazar6400

289NagkakaisaBacuel, Pepe Sr.7800

3107Ugnayanyayen, romeo jr.13800

4118Ugnayantrepit, prodencio16800

5124Ugnayanyayen, romeo sr.16800

699Ugnayanmabutin, flaviano17600

7117Ugnayanpadilla, ricardo18000

885NagkakaisaLlavan, Rey18000

923ManingningLaguta, Renato26792

1081NagkakaisaSolis, Noel27100

1119ManingningZabanal, Victor27300

12122Ugnayanbinggon, manuel29800

1361MahayahayBadenas, Querubin30000

1472Mahayahayde gusman, noli30900

1545MaunladCabanes, Garciano32400

1649ViscuaNangit, Enrique33000

1762MahayahayLlavan, Baltazar33760

1847MaunladTabangay, Floresto35600

1936Maunladdacillo, Vicente35800

20109Ugnayancasuga, audy37300

21123Ugnayancasuga, aurelio37800

2263Mahayahayabanes, ronie37800

2359Mahayahaybesitulo, antonio37840

2439MaunladYayen, Elva41600

2542MaunladCabebe, Josie43200

26102Ugnayangaayono, eddie43400

2774NagkakaisaYayen, Nelson44400

28110Ugnayancaab, anasita47227

2921ManingningRefianco, Mamento49370

3070Mahayahaysubron, rubie51000

3132MaunladBadenas, Luorbar51520

3257ViscuaBaquiran, Reynan52000

33120Ugnayansabenacio, antero52200

3410ManingningPacaldo, Espectation53000

35105Ugnayandecio, rolly53000

36103Ugnayanbaconga, prescilia53800

3767MahayahayPolinar, Brexcio56000

3890NagkakaisaPefrianco, Domingo56800

3994NagkakaisaRaet, Reynaldo58900

4094Mahayahaymangaya, ricky59600

4183NagkakaisaAbus, Cherlito61600

4220ManingningLlauan, Alex62344

4388NagkakaisaBesitulo, Gerry65000

4425ManingningLaguna, Rolando65375

4511ManingningCamposano, alvin65800

4696NagkakaisaSolis, Welhim66940

4782NagkakaisaAbanes, Emerita67320

4854ViscuaAbique, Jesus67564

49101Ugnayanyayen, francisco68200

5037Maunladdacillo, Edgar73800

51111Ugnayanpadilla, diomedes73800

52104Ugnayanyayen, edgar77280

531ManingningBaconga, Reynaldo78250

5453ViscuaMondragon, Randy79800

55106Ugnayanyayen, edwin82600

56108Ugnayancaab, matio84330

5764Mahayahayfernandez, ramil85660

5835MaunladFamoso, Agustina86800

5956ViscuaAbique, Remy89690

6028MaunladJardin, Lamberto94160

6197Ugnayanabigue, francisco98000

6276NagkakaisaDacillo, Virgilia98880

6316ManingningDacillo, Generoso Jr.102744

6418ManingningOab, Nexon103320

6579NagkakaisaCamena, Eulequio103400

66113Ugnayancamot, elpidio103400

6765Mahayahayloque, rene103960


69114Ugnayancamot, elmer105000

7058ViscuaBaquiran, Ihimenado105690

715ManingningBaconga, Tranquilino107600

722ManingningMontecillo, Rodel108100


74125Ugnayancaab, ernesto112600

7543MaunladMadamo, Yully113750

7627ManingningGabasan, Nerwin114400

7741MaunladDagsan, Ernesto114800

787Maningningabela, Trinidad115600

7913ManingningLagutan, reynaldo118600

8092NagkakaisaBaconga, Rosendo119800

8117ManingningOab, andres121000

82112Ugnayanramilo, francisco121000

8346MaunladCabanes, Prudencio121110

8493NagkakaisaZabanal, Begesdes121668

8571Mahayahaycabillan, edwin121800

86127NagkakaisaGabasan, Sixto123040

8748ViscuaBacuel, Carolina124000

8822ManingningPaz, Pablito129500

8944MaunladAbian, Nerio130200

9024ManingningDionisio, Julius132200

9160Mahayahayopeder, moeses133364

9291NagkakaisaYayen, Lope139860

9366Mahayahayello, felix141180

9431Maunladsolis, Bernabe143600

9530MaunladDulgeme, Pedro144000

9651ViscuaAbique, William145600

9787NagkakaisaLlavan, Sergio Sr.148000

9869Mahayahaycadlaon, rodolfo148815

99115Ugnayandelos reyes, jaime150900

10084NagkakaisaTabarangao, Roger151200

101126Ugnayansabenascio, oscar151200

10229MaunladJardin, Felizardo151585

10338MaunladEstoce, Avelio151650

1049ManingningDela Torre, Gregorio153200

10550ViscuaCastro, Roque154800

10695NagkakaisaVicente, Danilo156400

1078ManingningGepella, Melchor157350

10812ManingningCastro, Marcelo Jr.164500

109121Ugnayansabenacio, juanito165600

11034MaunladAlmoguerra, Eger175272

11168Mahayahaylegaspi, eddie176200


113116Ugnayanbeloya, virgilio180900

11477NagkakaisaComena, Eddie181020

11515ManingningOab, Prudente181600

11675NagkakaisaOab, Roman Sr.183680

11778NagkakaisaBacul, Senecio192000

1184ManingningDelos Santos, Arsenio201600

11940NagkakaisaAbian, rafael210100

12052ViscuaAmparo, Victor216000

12114ManingningTrinidad, Jose244200

12298Ugnayanllavan, elesio245600

12380NagkakaisaLabrador, Rodencion250200

1246ManingningRadam, Felix295200

1253ManingningPacaldo, Juan335640

12633MaunladMaceda, Jovencio370680

127100Ugnayanllavan, agustin818600

Plots

quant

rowtypelevelvardim1dim2

QUANTNon-poorPOVSUB0.352-0.026

QUANTNon subsistent poorPOVSUB-0.60.759

QUANTPoorPOVSUB-1.007-0.476

QUANTWith members 6-16 years old not attending schoolNTSCH-1.003-1.284

QUANTAll members 6-16 years old attending schoolNTSCH-0.0690.501

QUANTWith underemployed memberW1UNDEMP-0.110.19

QUANTWith no underemployed memberW1UNDEMP1.547-2.101

QUANTWith illiterate memberW1NTLIT-1.133-1.103

QUANTAll members literateW1NTLIT0.3380.292

QUANTWith victims of crimeWVICT-0.6031.08

QUANTNo victims of crimeWVICT0.051-0.049

QUANTAll children 0-5 normalWMALN20.1540.247

QUANTWith children 0-5 1st degree malnourishedWMALN2-0.134-0.391

QUANTWith children 0-5 2nd degree malnourishedWMALN2-1.49-0.488

QUANTWith access to electricityWELEC1.804-0.227

QUANTWith no access to electricityWELEC-0.1430.017

QUANTComm water systemWATSRC44.214-3.768

QUANTDeep/artesian wellWATSRC40.6780.003

QUANTDug/shallow well, River, lake, otherWATSRC4-0.1790.066

QUANTWater sealed - ownedTOILF21.372-0.497

QUANTWater sealed - sharedTOILF21.0130.236

QUANTOpen/closed pitTOILF2-0.2230.475

QUANTNo toiletTOILF2-0.972-1.354

QUANTFormal tenureTENURE40.1660.016

QUANTOwn house, rent-free lotTENURE4-0.268-0.201

QUANTRent-free House and LotTENURE4-0.6190.254

quant

0

0

0

POVSUB

Dimension 1

Dimension 2

POVSUB

comp_full

Poverty Threshold ComputationEigenvalues - reduced 3

IndicatorLevelFrequencyDim 1Dim 2weightminweightpDimensionEigenvalue

WCHILDD2With child death2-0.49000179310.5525979787-1125.490-1125.4900.010.18954471410.4353673324

WCHILDD2With no child death68-0.03128981650.0947829436-71.870-1125.4901053.620.15718987970.3964717893

POVSUBNon-poor920.3549080372-0.0321714541815.192-2362.8113178.0

POVSUBNon subsistent poor15-0.59263047530.8323952574-1361.219-2362.8111001.6

Categorically Weighted Composite Indicator: Meaning of the Second Axis

Comparison between the Two MethodsAdvantages, Disadvantages and Utilization

Simple Scoring and Categorical Weighting: ComparisonSimple Scoring

Simple scoring is easier to adopt than the categorically weighted composite indicator as far as LGUs are concernedHowever, simple scoring does not utilize underlying discriminating nature of the indicatorsSimple scoring has an arbitrary set of weights and, hence, poverty ratesSimple weights do not change no matter how many indicators or population units are usedTies 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 thresholdsTies are among households are less probableMaybe difficult to be adoptedRelative weights are derived, thus, weights change depending on the dataset

Barangay Kemdeng: Uses of CBMSProvide crucial information to support planning and project implementation at the local levelsThe 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 resultsData are very useful to target beneficiaries of programsThey are helpful to identify the poor

Barangay Kemdeng: Conclusions and RecommendationsThe comparative analysis of data from two CBMS surveys is a useful procedure in impact assessment of programsConcern for careful planning of projects at the local level, most specially at the barangay levelComposite indices are good tools for ranking households, however, further work is needed to be done in this area

Other results:

RankIDPurok

Household

Head

Simple

Composite

Poverty

Measure

174Nagkakaisa

Yayen,

Nelson

33.3

2122Ugnayan

Binggon,

Manuel

33.3

363Mahayahay

Abanes,

Ronie

35.7

4107Ugnayan

Yayen,

Romeo jr.

35.7

5117Ugnayan

Padilla,

Ricardo

41.7

632Maunlad

Badenas,

Luorbar

42.9

7119Ugnayan

Padilla,

Baltazar

45.5

Proportion in each decile of households with

children attending public school

75.0

80.0

85.0

90.0

95.0

100.0

1st2nd3rd4th5th6th7th8th9th10th

Per Capita Income Decile

Proportion

Employment Rate

89.7

100

96.1

78.2

92.3

100

94.9

88.2

0

10

20

30

40

50

60

70

80

90

100

Total IP Male Female

Proportion

2000

2002


among 12-15 year old children

30.6

0

35.5

25

27.3

0

30

24

0

5

10

15

20

25

30

35

40

Secondary IP Male Female

Proportion

2000

2002

Elementary school participation rates

among 6-11 years old children

80.8

40

80

81.8

76.6

28.6

75

78.7

0

10

20

30

40

50

60

70

80

90

Elementary IP Male Female

Proportion

2000

2002


64.4

83.3

45.9

33.3

27.6

40

15.7

40

0

10

20

30

40

50

60

70

80

90

100

Total IP Total IP

Proportion

2000

2002

School participation rates

among 6-16 year old children

82

33.3

82.4

81.6

87.3

45.5

87.5

87

0

10

20

30

40

50

60

70

80

90

100

Total IP Male Female

Proportion

2000

2002

Proportion of households with children

attending public school across deciles

8.5

9.0

9.5

10.0

10.5

11.0

11.5

1st2nd3rd4th5th6th7th8th9th10th

Per Capita Income Decile

Proportion

RankIDPurokHousehold Head

Simple

Composite

Poverty

Measure

11172MahayahayDe Gusman, Noli81.8

11221ManingningRefianco, Mamento81.8

11334MaunladAlmoguerra, Eger81.8

11493NagkakaisaZabanal, Begesdes81.8

115100Ugnayanllavan, agustin81.8


11786NagkakaisaCaranza, Joseph84.6


11954ViscuaAbique, Jesus84.6

12055ViscuaMagahis, Dominador84.6


12268Mahayahaylegaspi, eddie85.7






Simple Composite

Poverty measure

FrequencyProportionCumulative

>=30 to =40 to =50 to =60 to =70 to =80 to =90 to

Utilizing CBMS in Monitoring and Targeting the Poor: The case of Barangay Kemdeng, San Vicente,...

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