11th National Convention on Statistics (NCS) EDSA Shangri-La Hotel

October 4-5, 2010

THE SOCIAL AND ECONOMIC DIMENSIONS OF RURAL POVERTY IN THE PROVINCE OF MASBATE

by

Bernadette M. Gavino-Gumba

For additional information, please contact:

Author’s name

Bernadette M. Gavino-Gumba

Designation Associate Professor Affiliation Ateneo de Naga University Address Department of Social Sciences, Ateneo de Naga University Tel. no. 54 472 2368 Local 2013 E-mail bernsgumba@yahoo.com

THE SOCIAL AND ECONOMIC DIMENSIONS OF RURAL POVERTY IN THE PROVINCE OF MASBATE

by

Bernadette M. Gavino-Gumba

ABSTRACT

I. Introduction

This study analyzed the rural poverty phenomenon in Masbate, one of the poorest

provinces in the Philippines, with poverty incidence of 51.0% in 2006. The province has been in the list of top ten poorest since 1997, ranking first in 2000, third in 2003, and eighth in 2006. Seven of the ten poorest in 2000 were able to cast off their “poorest” tags in 2003, majority registering double-digit declines in their poverty incidences. On the other hand, Masbate and two others remained in the list, with Masbate as the only province which had consistently been in the ten poorest since 1997 (National Statistical Coordination Board, 2008).

Table 1. Ten poorest provinces in the Philippines, 2003 and 2006

Province

Poverty incidence (%)

Rank 2006

Rank 2003

Province

Poverty incidence

(%)

Rank 2006

Rank 2003

Tawi-tawi 78.9 1 31 Lanao del Sur 52.5 6 25

Zamboanga del Norte

63.0 2 1 Northern Samar

52.2 7 38

Maguindanao 62.0 3 2 Masbate 51.0 8 3

Apayao 57.5 4 69 Abra 50.1 9 19

Surigao del Norte 53.2 5 4 Misamis Occidental

48.8 10 7

National Statistical Coordination Board, 2008

A. Statement of the Problem

The general objective of this study was to analyze the rural poverty phenomenon in Masbate. Specifically, the study sought to answer the following:

1. What is the status of poverty and deprivation in the communities of Masbate in terms of

economic and social indicators? 2. How does the economic indicator relate to the social indicators of deprivation in the

communities? 3. How have local government units addressed economic and social indicators of poverty?

B. Scope and Delimitation

The study covered 20 municipalities and one city of Masbate. Since the inquiry primarily

used secondary data, it was limited to available information a substantial part of which used 2005

Page 1 of 20

figures, except on housing and literacy which were based in the period 2000. It was constrained by wide distances among the 21 communities of the province, the unstable political situation, insurgency and violence, and the natural calamities that frequently beset the island province of Masbate. Data-gathering was conducted in the first quarter of 2008.

C. Significance of the Study

Poverty studies are some of the research topics that are on top of the list of both government and academic institutions. In the past decade, poverty researches have expanded significantly to include economic and social indicators. Aside from income, consumption and productive assets are economic measures, while examples of social indicators are nutrition, sanitation, access to safe drinking water, access to electricity, school enrollment rates, literacy rates, access to healthcare, infant and maternal mortality, access to social opportunities, access to land and credit, participation in decision-making, infrastructure and access to markets (Deichmann, 1999).

Poverty and deprivation are multidimensional issues. Although monetary indicators are widely

considered as the most reliable measures of poverty (Deichmann, 1999), social and structural indicators describe facets of human well being that are not easily captured by purely economic measures. In response to these challenges, this inquiry utilized multidimensional indicators of deprivation and spatial poverty measure.

For policymakers, the study was envisioned to provide detailed information on the socio-

economic condition of people in the rural areas. The study could provide guidelines on the specific structural and legislative changes needed to directly boost people’s economic participation and access to resources and social services.

For the researchers and people in the academe, the results of this study could be used in the

preparation of policy papers on poverty issues and policy alternatives. The data generated in this investigation can be used to develop framework/ methodologies/ tools/ guidelines vis-à-vis poverty alleviation programs that may effectively target various facets of poverty.

I. THEORETICAL FRAMEWORK

The theoretical framework of this study is primarily based on the Deprivation Trap Theory of Robert Chambers (Swanepoel, 2003). According to Chambers, the poor is trapped in a cycle of poverty called the deprivation trap. There are five clusters of disadvantage among poor households: (a) they are poor; (b) physically weak; (c) isolated; (d) vulnerable; and (e) powerless.

Poverty determines all the other clusters of disadvantage because it contributes to: (a)

physical weakness because of lack of food and poor health; (b) isolation because of the inability to pay for education; (c) vulnerability because of lack of assets and inability to meet contingencies such as illness; and (d) powerlessness because of the low status that goes with lack of wealth. Physical weakness contributes to poverty through inability to engage in income-generating activities and less opportunities for those who are physically weak. Isolation is typically illustrated by a lack of proper education, remoteness and being out of contact with the wider world. The isolation of the poor sustains their poverty because social services do not reach those who are living in remote areas. Vulnerability relates to poverty through the lack of assets for humane living and livelihood. Powerlessness contributes to poverty through limiting or preventing access to resources, there is a lack of legal redress for abuses, and enhances the weakness of the poor in the negotiations.

Page 2 of 20

Analytical Framework

Following is a presentation of the flow of this investigation guided by a framework illustrated herewith (Please refer to Figure 1 in File GUMBA_framework). The analytical framework is based on the theoretical framework presented in the preceding section.

The status of poverty in the communities of Masbate is examined in the context of its social

and economic dimensions. Poverty is analyzed vis-à-vis the Deprivation Trap Theory of Robert Chambers (Swanepoel, 2003). The social and economic dimensions of rural poverty were explored by looking into the income and non-income measures of poverty and deprivation. The income measure of poverty was the small area poverty incidence provided by the National Statistical Coordination Board. As illustrated in the inner circle labeled Deprivation Trap, rural poverty is closely interconnected with physical weakness, isolation, vulnerability and powerlessness.

In line with one of the research problems, the indicators of deprivation were examined as

contributory factors to rural poverty. Rural poverty was determined primarily through the small area poverty incidence while the non-income measures of deprivation are enumerated herewith. Physical weakness was indicated by lack of access to water and sanitary facilities, high malnutrition, high maternal and infant mortality. Isolation was denoted by low school participation, high dropout, low cohort survival and high illiteracy. Vulnerability was signified by absence or lack of assets and poor housing. Lastly, powerlessness was represented by lack of access to social organizations and cooperatives, low internal revenue allotment, low income class, and high incidence of crimes.

As called for by one problem of the inquiry, existing development programs in the selected

municipalities and barangays were identified. The study looked into the major programs provided by local government units and agencies.

II. RESEARCH METHODOLOGY

The investigation employed written document analysis for the analysis of economic and social indicators, key informant interview and focused group discussion for the validation of the indicators and gathering of data on local government programs. The unit of analysis was the municipality. The community profiles were derived from the National Statistical Coordination Board, the Provincial Planning and Development Office, Municipal Planning and Developmet Office, Municipal Health Offices, Social Welfare Department, Education Department, the Diocese of Masbate Social Action Foundation, and Peace and Equity Foundation, Inc. Other secondary data used were annual investment plans of the province and municipalities, memoranda, announcements, written reports and news clippings.

A. Data Collection Procedure

The research project ran for a total of 11 months. It involved one month of preparatory activities and finalization of the research instruments; a total of five months of fieldwork for gathering of secondary data, key informant interviews and focused group discussions; three months of written document analysis; and two months of full time report writing. The research team consisted of three persons - the main researcher and two field enumerators - who visited the areas interchangeably in a span of five months. The author was the main researcher and supervisor of the entire research work. The two enumerators worked hand in hand in the gathering of primary and secondary data.

Page 3 of 20

B. Statistical Treatment

The research dealt on both quantitative and qualitative data. Poverty was measured using small area poverty incidence estimates which were generated from the National Statistical Coordination Board (NSCB), one of the sources of official poverty statistics in the Philippines. These estimates were derived as part of the country’s efforts toward the Millennium Development Goals, the aim of which is to reduce extreme poverty by half by 2010 (Juan-Albacea, 2007). The Philippines has embarked on a number of locations for specific poverty measurement efforts, referring to poverty statistics at the smaller level of geographic disaggregation - provincial, municipal, city and barangay. In the municipal level, the poorest 25% of municipalities in a province are selected in a multi-stakeholders provincial forum, using three categories of indicators: (a) quality of human capital; (b) housing and amenities; and (c) access to centers of trade (Department of Social Welfare and Development, 2007).

The methods of data processing included frequency distribution tables, computation of percentage and correlation statistics. The investigation correlated rural poverty with indicators of deprivation as illustrated in the Deprivation Trap, namely physical weakness, isolation, vulnerability and powerlessness.

Table 2. Variables used for the indicators of deprivation

Indicators of deprivation

Variables

Physical weakness

proportion of children severely and moderately malnourished estimated infant mortality rate estimated maternal mortality rate proportion of households without access to potable water proportion of households without access to sanitary toilet

Isolation school participation rates in elementary and high school dropout rates in elementary and high school cohort survival rates in elementary and high school over 10 illiteracy rate distance from Masbate City

Vulnerability proportion of households with strong outer wall materials proportion of households with strong outer roof materials proportion of households with makeshift housing proportion of households with at least one household convenience proportion of households with lot owned/amortized proportion of households with house owned/amortized proportion of households owning agricultural land

Powerlessness number of cooperatives in the area number of non-government organizations estimated internal revenue allotment income class crimes against person crimes against property crimes against person and property

Page 4 of 20

To determine the correlation between these factors and poverty, the research utilized Pearson Product Moment Correlation or commonly known as Pearson’s correlation. The NSCB small area poverty incidence estimates are the Y variables while the pre-identified factors were operated as X variables.

Figure 2: Formula of Pearson’s Correlation r n ∑xy − ∑x ∑y xy = ———————————— _______________________

√ [∑x² − (∑x)²] [n∑y² − (∑y)²]

(Weisstein, 1999)

The correlation between two variables reflects the degree to which the variables are related. The Pearson’s correlation is the most common measure of correlation which measures the strength of the linear relationship between two variables or the tendency of the variables to increase or decrease together. It ranges from +1.0, which means that there is a perfect positive linear relationship, to -1.0, which means that there is perfect negative or inverse relationship (Weisstein, 1999).

III. FINDINGS

A. Status of Poverty and Deprivation

This segment discusses the poverty condition of Masbate and its 21 communities. The status of poverty was described in terms of economic and social indicators. The table presents the poverty situation of the Philippines and the Bicol Region. Among the Bicol provinces, Masbate had one of the lowest poverty thresholds in 2006 which means that the cost of living in the province was relatively low compared to other Bicol provinces. Moreover, the province’s poverty line increased by only 13.9% from 2003 to 2006, which implies that prices of goods and services increased within the three-year period. Masbate’s per capita income for all income groups increased by 25%, more than enough to compensate for the rise in the poverty threshold (National Statistical Coordination Board, 2008). This explains why despite the climb in the poverty line, poverty incidence in 2006 decreased from 55.9 to 51%.

Table 3. Poverty in the Bicol provinces, 2003 and 2006

Poverty Threshold

(pesos per annum per Poverty Incidence

(% of families)

Province 2003 2006 2003 2006

Philippines 12,309 15,057 24.4 26.9Bicol Region 12,379 15,015 40.6 41.8Albay 12,915 16,128 34.4 37.8Camarines Norte 12,727 14,854 46.1 38.4Camarines Sur 11,873 14,634 40.1 41.2Catanduanes 11,815 13,654 31.8 37.3Masbate 12,504 14,248 55.9 51.0Sorsogon 12,452 15,687 33.7 43.5National Statistical Coordination Board, 2008

Page 5 of 20

The next table exhibits the 20 towns and one city in terms of major island classification and political subdivisions. All the towns in the separate islands of Burias and Ticao belong to the first district. The mainland is divided into the second and third districts. Each of the three subdivisions has a share of a number of municipalities which belong to the ten poorest in the province and the region.

Table 4. Island classification and political subdivision in Masbate

Municipality Island District NSCB small

area poverty incidence estimates,

2005 1 Claveria 69.792 San Pascual

Burias Island 75.52

3 Batuan 57.634 Monreal 68.855 San Fernando 57.246 San Jacinto

Ticao Island

First District

57.317 Balud 68.928 Mandaon 63.329 Aroroy 67.6010 Baleno 64.5311 Milagros 65.7312 Masbate City 41.1813 Mobo

Masbate Island

Second District

64.7214 Uson 67.9415 Cawayan 74.0116 Palanas 63.1717 Dimasalang 64.1518 Placer 72.1119 Cataingan 62.8520 PV Corpus 60.9921 Esperanza

Third District

69.05National Statistical Coordination Board, 2008

The NSCB small area poverty incidence estimates reveal the portion of the household

population which does not have adequate income to purchase food and non-food needs in a year. Based on the estimates, the top ten poorest in the province, arranged from poorest, are San Pascual, Cawayan, Placer, Claveria, Esperanza, Balud, Monreal, Uson, Aroroy, and Milagros. In San Pascual, 75.52% of the household population live below the poverty line, Cawayan 74.01%, Placer 72.11% and Claveria 69.79%.

The next portion presents the important indicators to describe and analyze the deprivation

in the study areas, in terms of physical weakness, isolation, vulnerability, and powerlessness. Physical weakness. Most malnourished children are found in Baleno, followed by Claveria,

Placer, Esperanza and San Pascual. These are among the poorest in the province, with exception to Baleno. On the other hand, in spite of its high income poverty incidence, Balud enlisted the least proportion of malnourished children, followed by Milagros, San Jacinto and Uson. Households of Balud, Milagros and Uson, although they live in the poorest towns, receive

Page 6 of 20

effective feeding programs for their children through government and non-government organizations.

Table 5. Health conditions in the province of Masbate

Municipality

Proportion of children severely and moderately

malnourished (% of children 0-7

years, POPCOM, 1Q

2005)

Estimated infant mortality

rate (deaths per 100 births,

PHO, 2005)

Estimated maternal

mortality rate (deaths per 100 births,

PHO, 2005)

1 Claveria 31.40 1.01 2.882 San Pascual 25.63 3.53 6.313 Batuan 15.87 0.76 0.004 Monreal 20.02 0.61 8.115 San

Fernando 24.13 1.02 2.54

6 San Jacinto 14.06 2.65 0.007 Balud 13.39 2.02 2.138 Mandaon 20.52 0.61 0.009 Aroroy 24.62 0.99 4.1610 Baleno 31.42 0.66 0.0011 Milagros 14.01 0.17 4.1512 Masbate City 22.91 0.34 0.4213 Mobo 21.95 0.11 0.0014 Uson 14.43 0.66 1.4715 Cawayan 19.07 1.96 0.9316 Palanas 15.48 0.82 0.0017 Dimasalang 23.42 2.78 1.6318 Placer 29.75 1.24 1.5519 Cataingan 23.86 1.12 0.0020 PV Corpus 20.83 0.00 0.0021 Esperanza 28.73 0.26 0.00 MASBATE

PROVINCE 21.83 1.06 2.71

The estimated infant mortality rate is highest in San Pascual which is likewise the poorest

town in the province and the region. It once more landed among the communities with the highest estimated maternal mortality rate. It is second to Monreal, then followed by Aroroy and Milagros.

The next table shows the proportion of households without access to potable water and

proportion of households without access to sanitary toilets in each town. Balud has the largest portion of the population with no access to potable water, followed by Cawayan, Placer, Cataingan and Uson. These are also among the poorest towns, excluding Cataingan. Conversely, Aroroy and Monreal, though classified among the poorest, have better access to potable water than their wealthier counterparts. Cawayan has the considerable number of households with no access to sanitary toilets, followed by San Pascual, Placer and San Jacinto. Except San Jacinto, these towns are among the poorest. But Balud and Aroroy registered higher proportion of households with access to sanitary toilets although they are among those with highest poverty incidence.

Page 7 of 20

Table 6. Access to potable water and sanitary toilet of households in Masbate

Municipality Proportion of households

without access to potable water

(PHO, 2005, %)

Proportion of HHs without

access to sanitary toilets

(PHO, 2005, %)

1 Claveria 32.51 66.48

2 San Pascual 49.61 78.67

3 Batuan 55.69 62.28

4 Monreal 18.46 52.19

5 San Fernando 38.55 61.21

6 San Jacinto 35.84 72.66

7 Balud 98.27 39.85

8 Mandaon 14.15 58.23

9 Aroroy 26.28 41.67

10 Baleno 43.23 39.32

11 Milagros 50.71 58.08

12 Masbate City 14.89 44.82

13 Mobo 17.80 50.68

14 Uson 61.88 62.78

15 Cawayan 90.55 78.78

16 Palanas 27.69 66.63

17 Dimasalang 47.04 61.33

18 Placer 86.92 75.78

19 Cataingan 63.66 63.66

20 PV Corpus 29.62 54.14

21 Esperanza 29.92 60.07

MASBATE PROVINCE

46.37 59.95

Isolation. The highest elementary participation rates were observed in San Fernando, Batuan and Masbate City. Esperanza topped in terms of school participation rate in elementary

Page 8 of 20

while Milagros has one of the highest school participation rates in secondary education together with better off communities like Batuan, San Fernando and Masbate City. Other poorest towns noted the lowest participation rates – Cawayan and Claveria in elementary, and Claveria again and Uson in secondary. There were more students that dropped out from elementary in Cataingan, Dimasalang, Claveria, Esperanza and Mandaon; and from high school in Mobo, Aroroy, Placer, Baleno and Claveria. School-age children in Claveria seemed to be the most disinterested in schooling as proven by the town’s dwindling participation rates in elementary and secondary education, coupled with high drop out rates in both levels.

Table 7. State of education in the province of Masbate

Participation Rate (%, DEPED, 2005)

Drop-out rate (%, DEPED, 2005)

Cohort survival rate (%, DEPED, 2005)

Illiteracy rate (%,

NSO, 2000

Municipality

Elementary Secondary Elementary Secondary Elementary Secondary

1 Claveria 71.89 72.27 2.67 9.22 50.52 53.09 3.93

2 San Pascual 82.90 76.90 1.96 7.31 41.11 52.73 3.90

3 Batuan 98.82 84.34 2.10 4.28 60.36 60.71 9.11

4 Monreal 87.12 78.48 0.51 8.55 53.37 51.13 1.24

5 San Fernando 99.36 82.28 2.29 5.52 45.47 58.20 0.77

6 San Jacinto 88.35 77.57 0.31 5.60 66.95 72.19 0.74

7 Balud 89.60 75.17 1.57 7.77 76.91 73.14 3.79

8 Mandaon 81.18 75.31 2.62 5.73 41.09 66.29 2.80

9 Aroroy 91.23 78.21 1.38 12.36 54.75 50.79 3.07

10 Baleno 88.91 76.18 0.70 9.87 60.56 47.28 0.89

11 Milagros 90.57 81.44 2.46 8.67 49.65 59.94 3.27

12 Masbate City 95.16 81.71 0.55 5.16 63.00 76.76 1.90

13 Mobo 92.55 73.44 0.83 19.13 56.19 32.88 2.56

14 Uson 91.73 73.89 1.43 8.01 58.97 62.79 4.37

15 Cawayan 77.95 75.64 0.34 4.20 47.72 63.63 5.77

16 Palanas 94.96 70.58 1.41 5.42 50.69 75.63 5.70

17 Dimasalang 78.58 76.86 3.49 5.26 56.18 68.79 3.38

18 Placer 86.29 76.43 0.76 9.97 55.40 50.67 6.38

19 Cataingan 84.89 79.04 3.51 6.41 47.52 55.05 5.90

20 PV Corpus 92.21 69.05 0.51 8.22 56.40 80.76 5.54

21 Esperanza 96.42 78.34 2.62 7.69 56.34 51.81 5.23

MASBATE PROVINCE

NA NA NA NA NA NA 3.64

Page 9 of 20

The cohort survival rate in elementary was highest in Balud followed by San Jacinto, Masbate City and Baleno. Except Balud, these towns are among the better-off communities of the province. According to the Department of Education, the presence of public elementary schools in each barangay in Balud are probable reasons why Balud has shown satisfactory records in terms of cohort survival rates. Moreover, the number of public schools and teachers are enough to accommodate the children who are supposed to go to school. The highest cohort survival rates in high school were recorded in Balud, PV Corpus, Masbate City and Palanas. The lowest cohort survival rates in elementary were observed both from among poorer municipalities, San Pascual and Cawayan, and well-off towns like Mandaon and San Fernando. Similarly, the lowest secondary level cohort survival rates were shared both by poorer municipalities like Placer and Aroroy, and relatively affluent communities like Mobo and Baleno.

Latest data from the Census on Housing and Population show that the illiteracy rate in

Esperanza was among the highest in Masbate. Esperanza registered the seventh highest illiteracy rate. The lowest illiteracy rates were recorded in San Jacinto, San Fernando and Masbate City which are better-off towns.

The figure presents the relative distance of towns from Masbate City, the main source of

basic needs and resources. Among the towns located in the mainland where Masbate City is, Esperanza and Placer appeared to be the farthest from the city which may account for the areas’ poor access to basic needs like food and clothing.

Figure 3: A matrix on distance of each municipality to commercial center

Data from Provincial Government of Masbate, 2009

Mandaon

Aroroy

Baleno

Milagros

Mobo

Uson

Cawayan

Palanas

Dimasalang

Placer

Cataingan

PV Corpus

Esperanza

Claveria

San Pascual

Batuan

Monreal

San FernandoSan Jacinto

Balud

0

20

40

60

80

100

120

Claveria

San P

ascu

al

Batua

n

Monreal

San Fe

rnan

do

San J

acint

oBa

lud

Manda

on

Aroroy

Balen

o

Mila

gros

Masba

te C

ityMob

oUso

n

Caway

an

Palan

as

Dimas

alang

Plac

er

Catain

gan

PV C

orpu

s

Espe

ranz

a

Series1Series2

Vulnerability. Concerning housing, a larger number of households in the province’s capital

has strong outer wall materials, strong outer roof materials, and with at least one household

Page 10 of 20

convenience; as well as the least number of households with makeshift housing. Conversely, most households in poorest areas like San Pascual, Balud and Cawayan are deprived of such housing resources. San Pascual ranked last in terms of the proportion of households with strong outer wall materials. It also ranked among the last in terms of the proportion of households with strong outer roof materials.

Table 8. Condition of housing and amenities of households in Masbate.

Municipality

Proportion of HHs with strong

outer wall materials (%, NSO, 2000)

Proportion of HHs with strong

outer roof materials (%, NSO, 2000)

Proportion of HHs with makeshift

housing (%, NSO, 2000)

Proportion of HHs with at

least one HH convenience (NSO, 2000)

1 Claveria 30.27 12.60 68.46 64.01

2 San Pascual 22.24 13.60 75.33 72.91

3 Batuan 66.94 9.29 32.46 83.08

4 Monreal 39.07 13.11 60.25 64.57

5 San Fernando 64.33 16.13 35.20 76.55

6 San Jacinto 56.55 15.57 42.27 74.79

7 Balud 31.64 24.91 64.81 71.55

8 Mandaon 27.54 20.64 69.93 71.01

9 Aroroy 45.06 29.01 52.11 69.81

10 Baleno 50.91 15.73 48.64 64.45

11 Milagros 40.79 20.27 58.18 63.98

12 Masbate City 68.63 51.70 28.16 76.08

13 Mobo 40.20 23.64 22.20 66.55

14 Uson 45.63 20.63 53.63 73.80

15 Cawayan 28.15 25.55 67.79 66.66

16 Palanas 40.54 21.53 57.85 68.66

17 Dimasalang 51.98 18.59 47.06 71.74

18 Placer 31.95 29.92 60.80 66.39

19 Cataingan 42.16 30.74 52.33 61.19

20 PV Corpus 46.28 33.40 42.80 62.19

21 Esperanza 44.44 34.05 50.34 73.00

MASBATE PROVINCE

42.81 25.22 52.86 63.15

On the other hand, San Pascual was first in the list with largest proportion of households with makeshift housing. Esperanza and Placer listed a relatively big percentage of households with strong outer roof materials. An interview with a personnel of Provincial Planning and Development Office revealed that Esperanza and Placer are both located along the coastline and

Page 11 of 20

facing the open sea. Thus, households made sure that their housing materials are sturdy to protect their families from natural calamities. The table further shows that Batuan had the biggest proportion of households with at least one household convenience followed by San Fernando and Masbate City. This could be due to the possibility that households here want to indulge themselves to some of the small comforts of life.

The next table displays the proportion of households with lot owned or amortized,

proportion of households with house owned or amortized, and proportion of households owning agricultural land. The municipalities with the largest proportion of households with lot owned or amortized are Baleno, Palanas, San Jacinto and Balud. Except Balud, these towns are better-off. In contrast, households in Esperanza, Placer, and Milagros cannot afford to buy their residential lots.

Table 9. Ownership of lot, house, and agricultural land in the province of Masbate

Municipality Proportion of HHs with lot

owned/ amortized (%, NSO, 2000)

Proportion of HHs with

house owned/ amortized (%, NSO, 2000)

Proportion of HHs owning agricultural

land (%, NSO, 2000)

1 Claveria 41.15 69.59 17.70

2 San Pascual 45.29 65.31 21.37

3 Batuan 38.79 48.68 19.02

4 Monreal 47.98 64.28 21.60

5 San Fernando 44.72 81.03 19.14

6 San Jacinto 60.58 79.37 29.99

7 Balud 52.44 80.78 17.92

8 Mandaon 48.36 71.60 25.17

9 Aroroy 43.77 73.70 20.17

10 Baleno 69.41 82.39 23.03

11 Milagros 37.50 77.58 11.26

12 Masbate City 40.64 71.10 11.78

13 Mobo 48.30 68.61 21.95

14 Uson 45.76 62.80 18.84

15 Cawayan 48.55 82.77 21.87

16 Palanas 61.78 81.83 43.73

17 Dimasalang 43.83 78.54 43.90

18 Placer 32.41 63.81 20.91

19 Cataingan 50.48 76.86 29.24

20 PV Corpus 37.64 64.12 29.84

21 Esperanza 37.50 63.09 23.31

Page 12 of 20

MASBATE PROVINCE

45.64 72.42 20.96

With house ownership, Cawayan led the rest having the largest proportion of households

with house owned or amortized, with Balud, Baleno and Palanas. Despite more households owning their houses, Cawayan’s high poverty incidence may not be an inconsistency because families in this place may still be unable to purchase all their day-to-day economic needs like food, clothing, education and health care. The municipalities with smallest proportion of households owning their houses included Esperanza, San Pascual, Batuan and Uson. Except Batuan, these are communities with highest poverty incidence.

The largest proportion of households which owned agricultural land is in Dimasalang,

followed by Palanas, San Jacinto and PV Corpus. These are wealthier towns. On the contrary, very few households in Balud owned agricultural land, which may be one reason why the area remains poor. Balud is joined at the bottom by Milagros, Claveria and Uson, which are also destitute.

Households in Masbate City tend not to own agricultural land probably because the

province’s capital has evolved into an urban center where the land resources are used for commercial and trading rather than agricultural purposes. However, being the richest in the province, Masbate City has relatively smaller proportion of households owning or amortizing their lot but contrastingly has bigger proportion of households owning or amortizing their house. Apparently, there is so much inequality in land distribution in the province because not one municipality recorded majority of households owning agricultural land. The unstable tenure of farmers may be probable reason of high poverty incidence.

Powerlessness. Among all towns, only Esperanza has no cooperative and therefore

no access to any services such organization had to offer. Cawayan has only one cooperative while Placer, Batuan, San Fernando, Baleno, Mobo, and PV Corpus have two cooperatives each. All these fail in comparison with Masbate City which has 52 cooperatives. However, Milagros has 13, Esparanza and Baleno each has only one non-government organization, followed by Placer, Cataingan, and Batuan with two each. Again, Masbate City is better off with 92 non-government organizations, followed by Monreal with 13 and Milagros with 10.

The poorest towns fared poorly in terms of internal revenue allotment per person

which is an indicator of the municipality’s weak capacity to lobby for more share in government funds. Aroroy has the lowest allotment, followed by Cawayan, Uson and Placer. Batuan has the highest allotment, more than 650% higher than Arroyo’s. Other municipalities with the highest internal revenue allotment are Baleno, Esperanza and Monreal.

Table 10. Number of cooperatives, NGOs, estimated IRA and income class of Municipalities

Municipality Number of

cooperatives (CDA, 2005)

Number of NGOs (SEC, 2005)

Estimated IRA per capita

(Php, PPDO, 2005)

Income class

(PPDO, 2005)

1 Claveria 4 6 829.99 4th

2 San Pascual 6 4 878.55 4th

Page 13 of 20

3 Batuan 2 2 1389.10 5th

4 Monreal 6 13 1174.24 4th

5 San Fernando 2 8 1130.20 5th

6 San Jacinto 3 4 1021.95 4th

7 Balud 3 3 4th

8 Mandaon 7 4 994.22 4th

9 Aroroy 6 24 183.01 2nd

10 Baleno 2 1 1266.58 4th

11 Milagros 13 10 3rd

12 Masbate City 52 92 5th

13 Mobo 2 5 4th

14 Uson 6 8 724.98 4th

15 Cawayan 1 5 716.45 3rd

16 Palanas 5 3 1131.90 4th

17 Dimasalang 5 6 1163.44 4th

18 Placer 2 2 757.48 4th

19 Cataingan 3 2 800.81 3rd

20 PV Corpus 2 3 997.44 4th

21 Esperanza 0 1 1174.45 5th

MASBATE PROVINCE

132 206 587.4138 2nd

Another indicator of powerlessness is income class since government income may spell a

difference in its capacity to deliver basic services and facilitate people’s access to resources. The Local Government Code provides that revenue allotment is higher for local government units which belong to lower income class. There is no community in the province that belongs to first income class. Only Aroroy made it to second income class while about 62% of the total number of municipalities was fourth class. Esperanza is fifth class. Specifically, it has one ambulance vehicle which brings patients to the nearest hospital located in Cataingan or Cawayan. Focused group discussion participants relayed that a patient who is identified as a supporter of the opposition would find it very difficult to get the approval of the LGU to be transferred to the nearest hospital. They mentioned stories about election-related killings in the area.

San Pascual is fourth class. Focused group discussion respondents said that Yung mga

programa ng munisipyo namin, hindi suportado ng probinsiya kasi yung mayor naming, tiga-oposisyon (The programs of our municipality are not supported by the provincial government because our mayor is from the opposition). They further claimed that elected officials ensure that only political allies benefit from government programs. They revealed that Nagkahati-hati ang Masbate sa mga political clans at dynasties (Masbate is divided into political clans and dynasties).

Page 14 of 20

The number of crimes against person is highest in Aroroy followed by Masbate City. It is lowest in San Pascual and PV Corpus at one incidence each. The number of crimes against property is highest in Masbate City while none was registered in San Pascual, Batuan, San Fernando, San Jacinto, Baleno, Mandaon, Mobo, Uson, Dimasalang, Cataingan, PV Corpus and Esperanza. Expectedly, this condition is true in Masbate communities for probable reason that there is not much valuable property in these depressed areas. The crime rate is highest in Aroroy and lowest in San Pascual, PV Corpus and Dimasalang.

Table 11. Number of crimes against person and property in Masbate

Municipality Crimes

against person (PNP,

2005)

Crimes against

property (PNP, 2005)

Estimated crimes against person and property per 1000 population (PNP,

2005)

1 Claveria 8 1 0.22

2 San Pascual 1 0 0.02

3 Batuan 5 0 0.44

4 Monreal 4 3 0.33

5 San Fernando 6 0 0.30

6 San Jacinto 10 0 0.39

7 Balud 9 0 0.28

8 Mandaon 16 0 0.46

9 Aroroy 40 3 0.68

10 Baleno 8 2 0.45

11 Milagros 4 2 0.12

12 Masbate City 20 4 0.31

13 Mobo 6 0 0.19

14 Uson 6 0 0.12

15 Cawayan 6 1 0.12

16 Palanas 2 1 0.12

17 Dimasalang 2 0 0.09

18 Placer 8 2 0.20

19 Cataingan 5 0 0.10

20 PV Corpus 1 0 0.04

21 Esperanza 3 0 0.20

MASBATE PROVINCE

206 19 0.29

Page 15 of 20

B. Correlation Between Poverty and Social Indicators of Deprivation This section presents the correlation of poverty incidence as economic indicator, with the

social indicators of deprivation. Details of these indicators are discussed in Chapter III, anchored on the four pre-identified factors by Chambers’ Theory of Deprivation Trap (Swanepoel, 2003).

Physical Weakness. Positive correlation was observed between poverty incidence and the

proportion of malnourished children, estimated infant mortality rate, estimated maternal mortality rate, proportion of households without access to potable water, and proportion of households without access to sanitary toilet. The coefficients 0.31 and 0.42 show moderate degree of correlation between poverty and infant mortality rate and maternal mortality rate. This suggests that more infants and mothers in poor municipalities die during or short after birth. The Pearson’s r 0.44 signifies that high scores in poverty incidence are associated with notable low scores in access to potable water.

Table 12. Correlation between NSCB poverty incidence estimates and

indicators of physical weakness

Indicators of physical weakness Pearson’s coefficient (r)

Proportion of malnourished children 0.19

Estimated infant mortality rate 0.31

Estimated maternal mortality rate 0.42

Proportion of households without access to potable water 0.44

Proportion of households without access to sanitary toilets 0.35

Isolation. Negative correlation was observed between economic poverty and elementary school participation rate, secondary school participation rate, elementary cohort survival rate, and secondary cohort survival rate. The coefficient -0.40 means that towns with high poverty incidence have significantly low school participation rates.

Positive correlation exists between poverty incidence and elementary school drop out rate, secondary school drop out rate and distance from the center of trade and commerce. The coefficients 0.10 and 0.27 mean that higher scores in school drop out rates were associated with nominally high scores in the rates of poverty. This may be explained by the likelihood that more needy families in Masbate face difficulties in pursuing the education of their young but given opportunities of free education, they strongly prefer to send their children to school.

Table 13. Correlation between NSCB poverty incidence estimates and

indicators of isolation

Indicators of isolation Pearson’s coefficient (r)

School participation rate – elementary -0.19

School participation rate – secondary -0.40

Drop out rate – elementary 0.10

Drop out rate – secondary 0.27

Page 16 of 20

Cohort survival rate – elementary -0.28

Cohort survival rate – secondary -0.44

Distance from Masbate City - mainland towns (DPWH, in km.) 0.09

Distance from Masbate City - island towns (Philippine Coast Guard, in nautical miles)

0.91

Vulnerability. There is negative association between poverty incidence and the proportion of

households with house owned or amortized, proportion of households with lot owned or amortized, proportion of households with strong outer wall materials, proportion of households with strong roof materials, and proportion of households with at least one household convenience. The proportion of households with strong outer wall materials is very strongly correlated with poverty incidence at -0.82; while the number of households with strong roof materials is negatively and moderately correlated with poverty incidence at -0.46. The coefficient -0.20 implies that families in Masbate, whether from poor or rich municipalities, can afford at least one piece of appliance. Although their houses may not be sturdy enough, families in the poorest communities may possibly want to indulge themselves to some of the small comforts of life. It is a lot easier and financially manageable to buy a television or stereo set than spending for house renovation.

Table 14. Correlation between NSCB poverty incidence estimates and

indicators of vulnerability

Indicators of vulnerability Pearson’s coefficient (r)

Proportion of households with house owned/ amortized -0.11

Proportion of households with lot owned/ amortized -0.10

Proportion of households with strong outer wall materials -0.82

Proportion of households with strong roof materials -0.46

Proportion of households with makeshift housing 0.73

Proportion of households with at least one household convenience

-0.20

Proportion of households owning agricultural land 0.05

On the other hand, there is positive relationship between poverty incidence and proportion

of households with makeshift housing and proportion of households owning agricultural land. The coefficient 0.73 purports that higher poverty incidence is associated with poorer shelter and housing conditions. The coefficient 0.05 denotes that poorer towns are endowed with more land than their richer counterpart. But it was also noted earlier that in all municipalities of Masbate, majority households do not own agricultural land. Moreover, this statistical result may imply that in Masbate, mere access to land is not a key element to poverty alleviation. Such resource may be left underutilized or not used at all for several reasons, such as lack of capital, credit facilities, technology and technical know-how.

Powerlessness. Poverty incidence is negatively related with number of cooperatives,

number of non-government organizations, estimated internal revenue allotment, income class, crimes against person and crimes against property. The coefficients -0.68 denote that indigent neighbourhoods are less likely to have cooperatives and NGOs in the area. This may also be an

Page 17 of 20

explanation that poverty alleviation programs of cooperatives and NGOs are effective and sustained in uplifting the economic conditions of their communities.

Table 15. Correlation between NSCB poverty incidence estimates and

indicators of powerlessness.

Indicators of powerlessness Pearson’s coefficient (r)

Number of cooperatives -0.68

Number of NGOs -0.68

Estimated IRA per capita -0.45

Income class -0.44

Crimes against person -0.21

Crimes against property -0.22

Internal revenue allotment comes from national taxes granted to cash-strapped LGUs. The coefficient -0.45 uncovers the possibility that poor municipalities do not receive their fair share of national government funds. Income class, on the other hand, reflects the capacity of an LGU to raise revenues. The coefficient -0.44 reveals that poorer towns have lesser capacity to support their LGUs and that these LGUs do not have much income-earning activities. Moreover, government revenues may have been transformed into developmental programs that benefited the underprivileged.

C. Development Programs of Local Government Units

For the identification of development programs, the inquiry gathered the municipal investment plans of the 21 communities from documents of plans, memoranda, announcements, written reports and news clippings. The information was summarized through a matrix of development programs (Please refer to Table 16 in File GUMBA_devprograms).

V. CONCLUSION

Based on the findings, the following conclusions are hereby forwarded: 1. Poor municipalities in Masbate are most likely to have less access to potable water, less

access to sanitary toilet, high malnutrition, infant mortality and maternal mortality rates, low elementary and secondary participation rates, low elementary and secondary cohort survival rates, high illiteracy rate, less access to safe housing and lack of ownership of agricultural lands. This may be initially proven by the case of San Pascual being the poorest municipality in the province and the region, and consistently being among those with highest malnutrition, infant mortality and maternal mortality rates. The problem of rural poverty in Masbate may be explained by a web of factors logically outlined in Chamber’s Deprivation Trap Theory. Poor households cannot afford their basic food and health needs because of poverty and therefore cannot sustain engagement in economic activities. They do not have the energy and time to join social organizations or participate in political processes and they cannot meet family contingencies. Because of lack of knowledge and information, they cannot identify and assert their needs. Even if they are strong and healthy, their remoteness spells the absence of basic services, non-government organizations, cooperatives, external assistance to handle emergencies, and lack of contact with government leaders. Able-bodied members of the community prefer to work elsewhere and leave their local economies in stagnation. Poor households remain incapacitated to meet their needs because of lack of assets and properties,

Page 18 of 20

lack of information and isolation. In the end, they are left at the mercy of patrons and politicians. Their isolation and powerlessness limits or prevents their access to resources because they do not know how to assert their rights for humane living. They do not know how to negotiate and what to fight for. Their constant struggle to afford food and health care leaves them no time or energy to form or join organizations to strengthen their position in society. Poor families are unable to attract or demand government attention. Consequently, in most poor communities of Masbate, there is glaring lack of structures and mechanisms which are vital components to poverty reduction such as investment programs, employment opportunities, education personnel and facilities, health personnel and facilities, and social organizations.

2. The correlation results prove the following: (a) poverty is closely associated with

physical weakness and vice-versa; (b) isolation has a relationship with the poverty condition of communities and vice-versa; (c) poverty is correlated with poor quality of housing and deprivation of families from owning house and lot; it is related with the ondition of families in unsafe shelters; (d) the absence or lack of cooperatives and non-government organizations in the area as well as low internal revenue allotment per capita and income class are associated with poverty and vice-versa. These indicate that poverty is correlated with powerlessness.

3. There are comprehensive development plans at the municipal level, complete with data,

figures and documentation but this does not ensure a trickle down of benefits to the barangays. Moreover, projects are largely infrastructure which may cater to problems of isolation and vulnerability but not to physical weakness and powerlessness. Unless these structures can facilitate delivery of social services, people will remain poor.

BIBLIOGRAPHY Cooperative Development Authority (CDA), 2005. Republic of the Philippines. In Peace and Equity

Access for Community Empowerment Foundation (PEF), Inc., 2007. Poverty Map: Province of Masbate. Quezon City.

Deichmann, Uwe (1999). World Bank Website on Inequality, Poverty and Socio-economic

Performance. Retrieved October 18, 2009 from http://www.worldbank.org. Department of Education (DEPED), 2005. Republic of the Philippines.In Peace and Equity Access

for Community Empowerment Foundation (PEF), Inc., 2007. Poverty Map: Province of Masbate. Quezon City.

Department of Social Welfare and Development (DSWD), 2007. KALAHI-CIDDSS Kapit-Bisig Laban

sa Kahirapan-Comprehensive and Integrated Delivery of Social Services: Kapangyarihan at Kaunlaran sa Barangay. Retrieved September 4, 2007 from www.kalahi.dswd.gov.ph

Hennie Swanepoel and Frik de Beer, Introduction to Development Studies (Oxford University Press,

Southern Africa, May 31, 2003). Juan-Albacea, Zita Ph.D., 2007. Small Area Estimation of Sub-National Poverty Incidence.

Retrieved June 26, 2008 from http://siteresources.worldbank.org/ INTPGI/Resources, 2007. National Statistical Coordination Board (2008), Republic of the Philippines. Retrieved October 11,

2009 from http://www.nscb.gov.ph. National Statistics Office (NSO), 2000. In Peace and Equity Access for Community Empowerment

Foundation (PEF), Inc., 2007. Poverty Map: Province of Masbate. Quezon City.

Page 19 of 20

Philippine National Police, 2005. Republic of the Philippines.In Peace and Equity Access for Community Empowerment Foundation (PEF), Inc., 2007. Poverty Map: Province of Masbate. Quezon City.

Provincial Health Office (PHO), 2005. Republic of the Philippines.In Peace and Equity Access for

Community Empowerment Foundation (PEF), Inc., 2007. Poverty Map: Province of Masbate. Quezon City.

Population Commission (POPCOM), 2005. Republic of the Philippines.In Peace and Equity Access

for Community Empowerment Foundation (PEF), Inc., 2007. Poverty Map: Province of Masbate. Quezon City.

Provincial Government of Masbate, 2008. Republic of the Philippines. Retrieved October 22, 2008

from www.masbateonline.gov.ph Provincial Planning and Development Office, 2005. Provincial Government of Masbate. Republic of

the Philippines. Securities and Exchange Commission (SEC), 2005. Republic of the Philippines. In Peace and

Equity Access for Community Empowerment Foundation (PEF), Inc., 2007. Poverty Map: Province of Masbate. Quezon City.

Weisstein, Eric 1999. Wolfram Research Mathworld. Retrieved August 26, 2008 from

www.mathworld. wolfram.com.

Page 20 of 20