A CBMS Philippines Research Paper prepared for the PEP Network Meeting June 18, 2004

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

2. 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

3. 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

4. Ugnayan Mahayahay Maunlad Nagkakaisa Viscua Maningning Barangay Kemdeng: Physical Characteristic

5. 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

6. 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.

7. 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

8. 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

9. 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

10. 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.

11. 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.

12. 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.

13. 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.

14. 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

15. Barangay Kemdeng: Education

16. 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

17. Barangay Kemdeng: Education

18. 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

19. Barangay Kemdeng: Education

20. 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

21. Barangay Kemdeng: Employment

22. 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

23. Barangay Kemdeng: Enabling Poverty Subsistence

24. 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

25. 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

26. 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

27. 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

28. 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

29. Barangay Kemdeng: Benefit Incidence Analysis

30. Barangay Kemdeng: Benefit Incidence Analysis

31. 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

32. Barangay Kemdeng: Benefit Incidence Analysis

33. Use of Scores in Ranking the Households Comparison between Simple and Categorically Weighted Composite Indicator

34. Rationale of Composite Indicator • Richer concept of multidimensional poverty • Identifying the poorest households • Discriminating between geopolitical and sub-geopolitical units • Resource allocation • Impact assessment

35. 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

36. 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.

37. 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

38. 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

39. 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

40. Composite Indicator using Simple Scoring Construction, Ranking and Poverty Rates

41. 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

42. Simple Scoring: Poorest Households Bottom households that attained less than 50 percent of the indicators

43. Simple Scoring: Well-off Households Top households that attained more than 80 percent of the indicators

44. Simple Scoring: Poverty Rates Brackets of Simple Scores

45. 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

46. 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

47. Categorically Weighted Composite Indicator Construction, Ranking and Poverty Rates

48. 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

49. 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

50. Categorically Weighted Composite Indicator: First MCA Measure of Dispersion of each Indicator, Preliminary