in cooperation with Australian Government

2006 and 2009Municipal and City Level

Poverty Estimates

Republika ng Pilipinas

PAMBANSANG LUPON SA UGNAYANG PANG-ESTADISTIKA(NATIONAL STATISTICAL COORDINATION BOARD)http://www.nscb.gov.ph

in cooperation with

The WORLD BANK and

Australian Government

31 December 2013 Makati City, Philippines

2006 and 2009

Municipal and City Level Poverty Estimates

The 2006 and 2009 Municipal and City Level Poverty Estimates is a major output

of the Project on the Generation of 2006 and 2009 Small Area Estimates of Poverty

implemented by the National Statistical Coordination Board (NSCB) with funding

assistance from the World Bank, Australian Government and the Philippine

Government

31 December 2013 Makati City, Philippines

2006 and 2009 Municipal and City Level Poverty Estimates

is a publication prepared by the Poverty, Human Development, and Gender Statistics Division

of the NATIONAL STATISTICAL COORDINATION BOARD (NSCB).

For technical inquiries, please contact us at: (632) 896-7981 or email us at [email protected].

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Published by the National Statistical Coordination Board

Midland Buendia Building 403 Sen. Gil Puyat Avenue

Makati City 1200 Philippines

with funding assistance from the

World Bank Australian Government and

Philippine Government

31 December 2013

The 2006 and 2009 Municipal and City Level Poverty Estimates

is available in electronic formats

(Excel/Word/PDF in CDRom).

For details, please contact us at (632) 890-8456 or at [email protected].

mailto:[email protected]

mailto:[email protected]

FOREWORD

This report is the third of the series featuring Municipal and City level poverty estimates

released by the National Statistical Coordination Board for 2006 and 2009. The generation

of these estimates is part of the output of the “Project on the Generation of 2006 and 2009

Small Area Estimates of Poverty”. The project was implemented by the National Statistical

Coordination Board (NSCB) with funding assistance from the World Bank (WB), Australian

Government and the Philippine Government. It is a follow-up study to the earlier NSCB

projects on “Poverty Mapping in the Philippines” funded through the WB-Asia Europe

Meeting Trust Fund and the “Intercensal Updating of Small Area Poverty Estimates” through

the WB Trust Fund for Statistical Capacity Building, which generated provincial and

municipal level poverty estimates for 2000 and 2003, respectively, using small area

estimation (SAE) techniques.

Similar to the earlier efforts, the SAE methodology employed in the project combined survey

and census data to produce reliable poverty estimates at lower levels of geographic

disaggregation. The SAE methodology was based on the Elbers, Lanjouw and Lanjouw

(ELL) methodology developed at the WB, which was subsequently modified to come up with

estimates for intercensal years.

We acknowledge the valuable assistance provided by our Project Consultant, Dr. Zita VJ.

Albacea of the University of the Philippines Los Baños (UPLB) as well as inputs from the

Project’s Technical Adviser, Dr. Romulo A. Virola. We also express our deepest

appreciation to Ms. Rashiel Velarde and her Team at the WB, for their encouraging support

in this undertaking and for the untiring efforts to help us improve the Philippine Statistical

System.

This report also highlights actual policy uses of the small area poverty estimates in the

Philippines emphasizing the relevance of the project outputs to national policymaking. It is

hoped that the results of this project will further help local communities and policymakers in

the formulation of appropriate programs and improvements in targeting schemes aimed at

reducing poverty.

JOSE RAMON G. ALBERT

Secretary General

Table of Contents

Page

I. Introduction 1

II. 2006 and 2009 Municipal and City Level Poverty Estimates 4

III. Actual Policy Uses

A. Targeting Beneficiaries of Programs/Projects 14

B. Policy Formulation, Planning and Monitoring 15

IV. Conclusions and Recommendations 16

V. Annex

A. Definition of Terms 17

B. Methodology

1. Background 18

2. Data Sources 20

3. Implementation of the Methodology

a. Introduction/Background 21

b. Selection of Explanatory Variables 22

c. Statistical Modeling 35

d. Development and Selection of Regional Models 36

e. Comparison of Estimates 40

4. Limitations of the Study 41

C. Validation Workshops

1. Objectives 42

2. Mechanics 43

3. Workshop Design 44

4. Validation and Ocular Forms 47

5. Matrix of Findings 49

D. Advocacy 50

E. Lessons Learned 53

F. 2006 and 2009 Municipal and City Level Poverty Estimates 54

References

Project Staff

NSCB Publications Multisectoral Statistics

The Philippine Statistical Yearbook *

The Countryside in Figures * (Philippines, selected provinces)

Regional Social and Economic Trends (RSET) (CAR, I , V, VI, VIII, IX , X, XI, XII)*

Metro Manila: Gateway to the Philippines

Economic Statistics

National Accounts of the Philippines: Quarterly, Annual and Annual with Consolidated Accounts and Income and Outlay Accounts *

Gross Regional Domestic Product *

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Input-Output Accounts of the Philippines *

Economic Indicators *

Quarterly Economic Indices*

Foreign Direct Investments*

Food Balance Sheet of the Philippines*

Leading Economic Indicators Social Statistics

Official Poverty Statistics of the Philippines*

Municipal and City Level Poverty Estimates

Official Poverty Statistics for the Basic Sectors in the Philippines

Statistical Handbook on Women and Men (Philippines, CAR, I, V, VI, VIII, IX, X, XI, XII)*

Report on the Philippine Human Development Index

Philippine National Health Accounts

National Education Expenditure Accounts

Poverty Maps (Selected Provinces)* Environmental Statistics

Compendium of Philippine Environment Statistics*

Statistical Standards and Classifications

Philippine Classification of Individual Consumption According to Purpose (PCOICOP)*

Philippine Standard Classification for Education (PSCEd)*

Philippine Standard Commodity Classification (PSCC)*

Philippine Standard Geographic Classification (PSGC)*

Philippine Standard Industrial Classification (PSIC)*

Philippine Standard Occupational Classification (PSOC)*

Philippine Central Product Classification (PCPC)*

Reference Materials

Philippine Statistical Development Program*

NSCB Annual Report*

Profile of Censuses and Surveys conducted by the Philippine Statistical System*

Directory of Government Statistical Services in the Philippines (DGSSP)*

A Guide to Statistics for Business Planning

Framework for the Development of Environment Statistics

State of the Philippine Land and Soil Resources

Statistics for Entrepreneurs

Proceedings of Conventions

National Convention on Statistics*

Asian Regional Section, International Conference on Statistical Computing

InformationSheets

Statwatch (Philippines, CAR, I, V, VI, VIII, IX, X, XI, XII and selected provinces and cities)

Factsheets (Philippines, CAR, I, V, VI, VIII, IX, X, XI, XII)

MDG Watch (Philippines, CAR, I, V, VI, VIII, IX, X, XI, XII)

Genderwatch (VI)

Statwatch on Children (VI)

Stat Informer (VI)

Stat Trivia (CAR)

Statistics Series

Technical Papers

Things Statisticians Wanted to Know About the Tourism Satellite Account but were Afraid to Ask (2012)

Major Revisions on the Philippine System of National Accounts: Implementation of the 2008 System of National Accounts (2012)

Gearing a National Statistical System Towards the Measurement of the Impact of Climate Change: The Case of the Philippines (2008)

Distributive Trade Statistics in the Philippines (2006)

Official Poverty Statistics in the Philippines: Methodology and 2003 Estimates (2006)

Green GDP Towards Sustainable Development: The Philippine Experience (2005)

Real Estate Price Index: A Model for the Philippines (2004)

Official Provincial Poverty Statistics in the Philippines and the Issue of Comparability Across Space (2003)

The NSCB: Our Products and Services (2003)

Enhancing the Relevance of the Philippine System of National Accounts (2002)

The Philippine Tourism Satellite Accounts: Dealing with Data Shortfalls (2002)

Development, Institutionalization and Improvement of the Philippine National Health Accounts (2001)

Measuring the Contribution of the Informal Sector in the Philippines (2001)

Rebasing, Linking and Constant Price Estimation of the National Accounts of the Philippines (2001)

Recent Initiatives of the NSCB in Improving Official Statistics in the Philippines (2001)

Environmental Accounting in the Philippines (2000)

Poverty Assessment in the Philippines (2000)

Online Articles and References

Beyond the Numbers

Sexy Statistics

StatFocus

Statistically Speaking

Sexy Statistics

Statistical Indicators for Philippine Development (StatDev)

Philippine Standard Geographic Codes

Provincial and Municipal Profiles

Statistical Reference System

Official Concepts and Definitions for Statistical Purposes

Technical Notes

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2006 and 2009 Municipal and City Level Poverty Estimates Page 1

I. Introduction

Poverty reduction remains the overarching goal of the Philippine government. The main

vision of the 2011-2016 Philippine Development Plan is to achieve rapid, sustainable and

inclusive growth that will generate employment opportunities and reduce poverty. This is

also in consonance with the Millennium Development Goals (MDGs), which embodies

specific targets and milestones in eliminating extreme poverty worldwide. Specifically, MDG

1 aims to halve the poverty rate in 2015 from its baseline rate in 1990. Given limited

resources, achieving significant poverty reduction entails the development and

implementation of poverty programs that are based on timely and relevant national and sub-

national poverty statistics.

Official poverty statistics in the country are generated by the National Statistical Coordination

Board (NSCB) in accordance with Executive Order (EO) No. 352, Designation of Statistical

Activities that will Generate Critical Data for Decision-making of the Government and Private

Sector. The official poverty estimation methodology is developed by the Technical

Committee on Poverty Statistics, which has a multi-sectoral representation consisting of

noted experts in poverty measurement coming from the academe, producers and users of

poverty statistics from both government and non-government organizations. Official poverty

statistics released by NSCB include national, regional and provincial poverty estimates

directly estimated from the triennial Family Income and Expenditure Survey conducted by

the National Statistics Office (NSO). These are defined and estimated in line with Republic

Act (RA) 8425, the Social Reform and Poverty Alleviation Act, which refers to the poor as

those families and individuals whose income fall below the poverty threshold and who

cannot afford to provide for their minimum basic needs in a sustained manner.

With the increasing clamour for lower disaggregation of poverty statistics for better targeted

poverty reduction programs, the NSCB embarked on a Poverty Mapping Project with funding

assistance from the World Bank Asia Europe Meeting (ASEM) Trust Fund in 2004. This

Project made possible the release of 2000 poverty estimates for all the 1,622 municipalities

in the country through small area estimation in 2005. Small area estimation is a statistical

methodology that allows the estimation at lower levels of disaggregation by combining

information collected from a survey with data from other sources such as the census. A

variant of this methodology, called the Elbers, Lanjouw and Lanjouw (ELL) Method, was

applied in the Project using the 2000 Census of Population and Housing (CPH), 4th Round of

the 2000 Labor Force Survey (LFS) and 2000 FIES.

Recognizing the need to update these 2000 city and municipal level poverty estimates, the

NSCB implemented the “Intercensal Updating of Small Area Poverty Estimates Project” in


2006 through the World Bank Trust Fund for Statistical Capacity Building (WB TFSCB). The

study aimed to explore the possibility of generating reliable 2003 city and municipal level

poverty estimates using a slight modification of the ELL Methodology used in the earlier

Project, but still using 2000 census data. The results of these projects were utilized in a

number of projects by the government and private sector, including the identification of

municipalities where household information for the National Household Targeting System for

Poverty Reduction (NHTSPR) of the Department of Social Welfare and Development

(DSWD) will be collected.

In 2014, the DSWD plans to collect data for their NHTSPR. This system will serve as the

DSWD guide in the identification and updating of their beneficiaries for the flagship program

of the government, called the Pantawid Pamilya Program. Hence, the need for updated city

and municipal level poverty estimates, as well as demand for trend analysis among the city

and municipal level poverty estimates need not be over emphasized. In response, the

NSCB, with funding assistance from Australian Government, WB and the national

government, again undertook a project to generate 2006 and 2009 city and municipal level

poverty estimates. It is hoped that the results of this Project, like the earlier NSCB initiatives,

will be a useful guide to local government units, policy makers and program implementers in

formulating/designing intervention programs aimed at reducing poverty.

Sub-national statistics like the municipal and city level estimates were commonly obtained

using a model-based approach. Hence, the estimates from this approach are based on

certain assumptions which play vital role in the limitation of its use. Like other estimates,

these are presented with their measures of precision and reliability, specifically their

standard error and coefficient of variation. This is done to caution users that this set of

estimates is just one of the many possible estimates that could be obtained and as these are

not exact values but rather, most likely values. These estimates are very useful in targeting

the poor localities, especially if the estimates are with small standard error and coefficient of

variation.

The estimates were arbitrarily grouped so that the municipalities and cities are more likely to

have the same level of poverty status. There are five groups identified which are arbitrarily

described as (1) ‘least poor’; (2) ‘mildly poor’; (3) ‘moderately poor’; (4) ‘highly poor’; and (5)

‘severely poor’. In terms of numerical values, ‘least poor municipalities and cities’ are those

with estimated poverty incidence of at most 20% while those who are described as ‘mildly

poor’ are municipalities and cities with estimated poverty incidence greater than 20% but at

most 40%. The ‘moderately poor municipalities and cities are those with poverty incidence

greater than 40% but at most 60%; while the ‘highly poor municipalities and cities’ are those


with poverty incidence greater than 60% but at most 80%. The group, which probably needs

help the most, are the ‘severely poor municipalities and cities’ which have poverty incidence

greater than 80%.

Knowing to which group a specific municipality or city belongs is useful for national planners

in targeting the rightful beneficiaries of a poverty alleviation program. On the other hand,

local chief executives of the country’s municipalities and cities will have the useful

information describing poverty in their localities based on these estimates.

In terms of monitoring the performance of a municipality or city, its membership to a group

could be observed if there is a change in the grouping to where the municipality or city

belongs. A shift in the group where a municipality or city belongs, from a higher to lower

group in terms of poverty incidence signals that the municipality or a city has improved its

poverty status. Such information on poverty dynamics is useful for both the national and

local executives especially if there is interest in monitoring the performance of a municipality

or city in relation to their poverty alleviation programs or initiatives.

The rank of the estimates could also be used in monitoring the performance of a municipality

or city relative to others. A big movement in the ranks could indicate a change in the poverty

status of a municipality or city. However, it should be emphasized that although there might

be shift in the group to which a municipality or city belongs, or even in the ranking, the

observed change might not be statistically significant. Likewise, there could be observed

changes in the estimates across time but those changes may not be declared statistically

significant. In such cases, it could be said that the change is not large enough to indicate a

significant difference based on the random sample used in the estimation. Thus data users

need to be aware of these technical matters in interpreting data.

But in general, when used appropriately, these small area estimates are useful information in

targeting and monitoring the poor municipalities and cities in the country.


II. 2006 and 2009 Municipal and City Level Poverty Estimates

The Philippines is composed of 17 administrative regions which are further divided into 80

provinces. In 2009, there were 1,647 municipalities and cities of which 137 are cities and the

rest, municipalities. In 2006, there were 1,641 municipalities and cities, lower than the 2009

count as new municipalities were created, while some municipalities successfully

transformed into cities on or before 2009. Small area estimates of poverty statistics were

obtained for these municipalities and cities, and the 14 districts in the City of Manila which

are labelled as cities in this study.

The distribution of the 1,641 municipality or city level estimates of poverty incidence among

population in 2006 is presented in the following table (Table 1) and figure (Figure 1). None of

the municipalities and cities are considered severely poor (i.e., having poverty incidence

greater than 80%). Most of municipalities and cities (717 out of 1,641) are mildly poor. The

Municipality of San Andres in the Province of Quezon (with poverty incidence of 78% in

2006) is an outlier. Here, the estimate of poverty incidence is reliable since its coefficient of

variation is only 8.17%. Note that the Municipality of San Andres is classified as a highly

poor municipality. On the average, for every 100 residents of this municipality, 78 are poor.

Table 1. Distribution of municipalities and cities based on poverty incidence among population, 2006.

Poverty Classification

Poverty Incidence Among Population

(%)

Count %

Least Poor At most 20 370 23 Mildly Poor 20.01 to 40.0 717 44 Moderately Poor 40.01 to 60.0 484 29 Highly Poor 60.01 to 80.0 70 4 Severely Poor Greater than 80.0 0 0

0 20 40 60 80Poverty Incidence

Figure 1. Box-plot of the distribution of municipalities and cities based on poverty incidence among Population, 2006.

For the year 2009, the distribution of the 1,647 municipality or city level estimates of poverty

incidence among population is presented in Table 2 and Figure 2. There is a slight difference

in the 2009 distribution compared to the 2006 distribution of municipalities and cities in Table

1 and Figure 1. There is no outlier or extreme value observed among the poverty incidence

San Andres, Quezon


estimates for year 2009 but the group with the highest count is still the group of mildly poor

municipalities and cities. The municipality with the highest poverty incidence among

population is the Municipality of Siayan in the Province of Zamboanga del Norte with poverty

incidence of 80%. This is also a reliable estimate since the estimate’s coefficient of variation

is only 5.63%. This municipality is also classified as highly poor.

Table 2. Distribution of municipalities and cities based on poverty incidence among population, 2009.

Poverty Classification

Poverty Incidence Among Population

(%)

Count %

Least Poor At most 20 432 26 Mildly Poor 20.01 to 40.0 628 38 Moderately Poor 40.01 to 60.0 524 32 Highly Poor 60.01 to 80.0 63 4

Severely Poor Greater than 80.0 0 0

0 20 40 60 80Poverty Incidence

Figure 2. Box-plot of the distribution of municipalities and cities based on poverty incidence among population, 2009.

The distribution of the estimates for 2006 and 2009 (see Figure 3) only slightly differs. The

percentages of severely poor and highly poor remain the same after three years. However,

there is an increase in the percentages of least poor and moderately poor from 2006 to

2009. A decrease in the percentage of mildly poor is also observed, after three years. Some

of the municipalities and cities that were included in the decreasing mildly poor, were able to

cope with their poverty situation and thus resulted to an increase in the percentage of the

least poor. Meanwhile, others were not able to improve on poverty, thus resulting to an

increase in the percentage of moderately poor.

Figure 3. Grouping of municipalities and cities based on poverty incidence

among population in 2006 and 2009.


Figure 4. Poverty map of the municipalities and cities by poverty classification in 2006.


Figure 5. Poverty map of the municipalities and cities by poverty classification in 2009.


Similar observations can be found in the poverty maps at the municipal and city level

estimates by poverty classification (shown in the previous two pages). The municipalities

and cities grouped accordingly and represented by the same colours indicate similarities of

the poverty classification of the municipalities and cities in 2006 and 2009. The complete list

of estimates is found in the Annex Table.

The differences in the magnitude of the estimates were obtained and only 18% of these

estimates are said to be statistically significant at the 5% level. In terms of counts, there

were 293 out of the 1,641 municipalities and cities with a change in their magnitude of

poverty incidence. Out of these 293, there are 27 cities. Although there is an observed

difference in the estimated poverty incidence of the 293 municipalities and cities, 104 of

these or 35% did not result to a change in their poverty classification. Twenty one of the 27

cities with a reported significant change in their magnitude of poverty incidence did not shift

to another poverty classification. For those with significant change in magnitude resulting to

a shift in poverty classification, 81 out of 293 or only 4.9% of the 1,641 municipalities and

cities became poorer in terms of poverty classification. Of these 81, only two are cities,

namely, Tacloban City (of Leyte, Region VIII) and Naga City (of Camarines Sur, Region V).

There were 91 municipalities and cities (of which three are cities) with a reported significant

change in poverty incidence, particularly, a shift in lower poverty classification in 2009

compared to 2006. These three cities that improved on their poverty classification include

Canlaon City of Negros Oriental, Region VII; Panabo City of Davao del Norte, Region XI;

and Tangub City of Misamis Occidental, Region X. Since 91 out of 1,641 municipalities and

cities is also only around 5.5%, this suggests that there is not much change in poverty

conditions in 2009 compared to 2006.

Identifying the top 40 poorest municipalities in 2006, Table 3 list these municipalities with

their estimated poverty incidences and corresponding standard errors as well as coefficients

of variation (all in percent). The 40 poorest municipalities are found in nine regions, four of

which are in Mindanao, two are in Visayas and the other three in Luzon. Region VII or

Central Visayas has the most number of municipalities in the top 40. These municipalities

are found in the Provinces of Cebu, Bohol and Negros Oriental. Only one municipality

(Municipality of Matuguinao in Western Samar) is found in Region VIII or Eastern Visayas.

Six of the 40 municipalities are found in Region IV-A or CALABARZON and all of them are

found in the Province of Quezon. Each of the Regions IX, X and Caraga has five

municipalities identified in the list. These three regions, together with ARMM, are all found in

Mindanao. ARMM has three of its municipalities that were identified in the top 40. CAR and

Region IV-B have also three municipalities each that are found in the list.


Table 3.Top 40 poorest municipalities in 2006. RANK REGION PROVINCE MUNCIPALITY ESTIMATE SE CV

1 Region IV-A Quezon San Andres 78.3 6.4 8.1

2 Region X Misamis Occidental Concepcion 76.5 5.4 7.1

3 CAR Abra Boliney 76.0 9.2 12.1

4 Region VII Bohol Batuan 75.3 5.6 7.4

5 Region VII Bohol Carmen 75.0 5.8 7.7

6 Region IV-A Quezon Jomalig 74.9 7.6 10.1

7 Region IV-B Palawan Cagayancillo 74.5 7.3 9.8

8 Region IV-A Quezon Buenavista 74.4 5.4 7.2

9 Caraga Agusan del Sur La Paz 74.2 4.7 6.3

10 Region X Misamis Oriental Magsaysay 73.9 6.8 9.2

11 Region X Misamis Occidental Don Victoriano Chiongbian 73.7 6.6 8.9

12 Region IX Zamboanga del Norte Siayan 72.3 6.5 9.0

13 CAR Kalinga Tinglayan 72.0 9.5 13.2

14 Region IV-B Oriental Mindoro Bulalacao 71.3 5.6 7.9

15 Region IV-A Quezon Patnanungan 71.2 8.0 11.3

16 Region IX Zamboanga del Norte Gutalac 71.1 5.4 7.6

17 Region IX Zamboanga del Norte Baliguian 70.4 6.9 9.8

18 Caraga Agusan del Sur Loreto 70.3 4.0 5.7

19 ARMM Sulu Luuk 70.2 8.0 11.4

20 ARMM Sulu Tongkil 69.8 8.5 12.2

21 Caraga Agusan del Sur San Luis 69.7 3.7 5.3

22 Region IV-A Quezon San Narciso 68.7 5.0 7.3

23 Caraga Agusan del Sur Esperanza 66.9 3.6 5.4

24 CAR Kalinga Tanudan 66.6 8.6 12.9

25 Region X Misamis Occidental Bonifacio 66.6 5.7 8.5

26 Region VII Cebu Tabuelan 66.5 5.0 7.6

27 Region X Lanao del Norte Tagoloan 66.5 8.5 12.7

28 Region IV-A Quezon Mulanay 66.3 6.4 9.7

29 Region IX Zamboanga del Norte Sibuco 66.0 6.4 9.7

30 Region VII Bohol Dagohoy 65.9 4.7 7.1

31 Region IV-B Romblon San Jose 65.8 6.8 10.4

32 Region IX Zamboanga del Norte Sirawai 65.5 7.1 10.8

33 Region VII Negros Oriental Jimalalud 65.3 4.1 6.3

34 Caraga Surigao del Norte Basilisa (Rizal) 65.1 4.3 6.5

35 Region VII Cebu Santa Fe 65.0 4.7 7.3

36 ARMM Sulu Kalingalan Caluang 65.0 10.9 16.8

37 Region VII Bohol Danao 64.7 4.8 7.4

38 Region VII Bohol Catigbian 64.3 6.7 10.4

39 Region VII Bohol San Miguel 64.2 3.8 6.0

40 Region VIII Samar (Western) Matuguinao 64.2 5.3 8.2


In terms of precision and reliability, all estimates are said to be precise and at most with

acceptable measures of reliability (at most 20% CV). Only 12 of the 40 estimates have CVs

greater than 10% but less than 20% which could be described as estimates with acceptable

measure of reliability. In fact, of the 40 CVs, the highest coefficient is only 16%. The other 28

estimates all have coefficients at most 10%. Thus, all of these 40 estimates could be very

well used to target the municipalities that are highly poor.

Thirteen of these 40 municipalities remained to be highly poor in the year 2009 based on the

estimates obtained for that year. The Municipality of Siayan in the Province of Zamboanga

Del Norte in Region IX is said to be the poorest municipality in 2009. It is one of the 13

municipalities that remained to be highly poor since 2006. The 13 municipalities identified in

Table 4 are with poverty incidence greater than 60% but at most 80% in 2006. Although in

terms of magnitude, there were observed changes in the estimated poverty incidences of

these 13 municipalities, only the Municipality of Concepcion in Misamis Occidental, Region X

has a significant change at 5% level. This observed change in the poverty incidence

estimate, however, is not enough to improve the poverty classification of the residents of this

municipality. Thus, all of these 13 municipalities remained to be highly poor in 2009.

Table 4. Estimated poverty incidence and their coefficient of variation of municipalities in the top 40 with no change in poverty classification from 2006 to 2009.

REGION PROVINCE MUNCIPALITY 2006 2009

POVERTY INCIDENCE

CV POVERTY

INCIDENCE CV

Caraga Agusan del Sur La Paz 74.2 6.33 66.7 5.85

Caraga Agusan del Sur San Luis 69.7 5.31 62.0 4.52

Caraga Agusan del Sur Esperanza 66.9 5.38 61.9 4.36

Region IX Zamboanga del Norte Siayan 72.3 8.99 79.9 5.63

Region IX Zamboanga del Norte Gutalac 71.1 7.59 70.4 6.53

Region IX Zamboanga del Norte Baliguian 70.4 9.80 75.3 6.51

Region IX Zamboanga del Norte Sibuco 66.0 9.70 68.2 7.62

Region IX Zamboanga del Norte Sirawai 65.5 10.84 61.7 10.05

Region VII Bohol Danao 64.7 7.42 62.1 6.44

Region X Misamis Oriental Magsaysay 73.9 9.20 60.3 6.47

Region X Misamis Occidental Don Victoriano Chiongbian 73.7 8.96 65.7 7.91

Region X Lanao del Norte Tagoloan 66.5 12.78 69.4 8.36

Region X Misamis Occidental Concepcion 76.5* 7.06 62.3* 6.74

*change in the estimates is statistically significant at 5% level.

Nineteen of the 40 poorest municipalities who were once highly poor in 2006 are classified

moderately poor in 2009. Although there was an improvement in their poverty classification,

the decrease in the estimated poverty incidence was not significant at 5% level for 11 out of

these 19 municipalities. The other eight municipalities, namely: Municipalities of Loreto in

Agusan del Sur, Caraga; San Narciso in Quezon, Region IV-A; Jimalalud in Negros Oriental,


including Batuan and Carmen in Bohol, Region VII; Bonifacio in Misamis Occidental, Region

X; Bulalacao in Oriental Mindoro, Region IV-B; and Luuk in Sulu, ARMM have significant

changes in their estimates (see Table 5). The statistically significant change in the poverty

incidence estimates in these eight municipalities, further supports the observed shift of their

poverty classification from higher to lower poverty status.

Table 5. Estimated poverty incidence and their coefficient of variation of municipalities in the top 40 with one-level shift in poverty classification from 2006 to 2009.

REGION PROVINCE MUNCIPALITY 2006 2009

POVERTY INCIDENCE

CV POVERTY

INCIDENCE CV

ARMM Sulu Tongkil 69.8 12.18 51.2 12.50

ARMM Sulu Kalingalan Caluang 65.0 16.77 48.3 15.53

ARMM Sulu Luuk 70.2* 11.40 47.9* 14.41

CAR Abra Boliney 76.0 12.11 50.6 18.77

Caraga Surigao del Norte Basilisa (Rizal) 65.1 6.61 55.7 7.36

Caraga Agusan del Sur Loreto 70.3* 5.69 56.9* 6.85

Region IV-A Quezon San Narciso 68.7* 7.28 41.1* 8.03

Region IV-B Romblon San Jose 65.8 10.33 50.5 16.63

Region IV-B Oriental Mindoro Bulalacao 71.3* 7.85 51.5* 12.23

Region VII Cebu Tabuelan 66.5 7.52 53.8 8.92

Region VII Bohol Dagohoy 65.9 7.13 56.0 7.50

Region VII Cebu Santa Fe 65.0 7.23 56.2 9.61

Region VII Bohol Catigbian 64.3 10.42 51.3 6.63

Region VII Bohol San Miguel 64.2 5.92 53.6 7.65

Region VII Bohol Batuan 75.3* 7.44 46.8* 7.26

Region VII Bohol Carmen 75.0* 7.73 55.2* 5.98

Region VII Negros Oriental Jimalalud 65.3* 6.28 50.2* 7.37

Region VIII Samar (Western) Matuguinao 64.2 8.26 57.5 8.17

Region X Misamis Occidental Bonifacio 66.6* 8.56 44.9* 8.91 *change in the estimates is statistically significant at 5% level.

On the other hand, the remaining eight municipalities in the top 40 poorest municipalities,

which are mostly found in Luzon, have estimated poverty incidences that resulted to a shift

in two levels from 2006 to 2009. These changes are also supported by the changes in the

magnitudes of the estimated poverty incidence that were found to be statistically significant

at 5% level. The estimates for these eight municipalities are found in Table 6. However, note

that the coefficients of variation in these estimates are mostly between 10% and 20%. Thus,

caution must be employed in the use and interpretation of these estimates. More so, one of

the poverty incidence estimates in 2009 has a coefficient of variation slightly higher than

20%. In particular, it is observed that the poverty incidence estimate of the Municipality of

Cagayancillo in Palawan, Region IV-B is not reliable. Hence, greater caution must be done

in interpreting the results from this municipality.


Table 6. Estimated poverty incidence and coefficient of variation of municipalities in the top 40 with two-level shift in poverty classification from 2006 to 2009.

REGION PROVINCE MUNCIPALITY

2006 2009

POVERTY

INCIDENCE CV

POVERTY

INCIDENCE CV

CAR Kalinga Tinglayan 72.0* 13.19 34.1* 15.54

CAR Kalinga Tanudan 66.6* 12.91 30.7* 19.87

Region IV-A Quezon San Andres 78.3* 8.17 39.0* 13.33

Region IV-A Quezon Jomalig 74.9* 10.15 39.0* 13.08

Region IV-A Quezon Buenavista 74.4* 7.26 34.9* 6.59

Region IV-A Quezon Patnanungan 71.2* 11.24 36.0* 15.83

Region IV-A Quezon Mulanay 66.3* 9.65 31.5* 7.94

Region IV-B Palawan Cagayancillo 74.5* 9.80 36.6* 21.04 *change in the estimates is statistically significant at 5% level.

Table 7 shows the top 10 poorest cities among the 117 cities as of 2006, with their

corresponding estimates, standard error and coefficient of variation (all in percent). These

ten poorest cities are found in six out of the 17 regions in the country. In terms of magnitude

of the estimates, the poorest city (Tangub City of Misamis Occidental, Region X) in 2006 has

a lower estimated poverty incidence compared to the estimates of all of the top 40 poorest

municipalities. All of the poverty incidence estimates for these 10 cities are said to be precise

and with coefficient of variation at most 15.32% which means that these estimates are with

acceptable measures of reliability.

Table 7. Ten Poorest Cities in 2006.

RANK REGION PROVINCE MUNCIPALITY ESTIMATE SE CV

1 Region X Misamis Occidental Tangub City 63.8 5.9 9.26

2 Region VII Negros Oriental Bais City 54.3 3.7 6.89

3 Region VII Negros Oriental Canlaon City 54.0 6.6 12.29

4 Region VII Negros Oriental Bayawan City 50.9 7.8 15.32

5 Region IX Zamboanga del Norte Dapitan City 46.7 5.3 11.27

6 Region V Albay Ligao City 45.9 3.0 6.47

7 Region X Misamis Oriental Gingoog City 44.1 3.1 7.01

8 Region VI Negros Occidental Sipalay City 39.4 4.4 11.18

9 Region VI Iloilo Passi City 36.5 2.7 7.26

10 Region XI Davao del Norte Island Garden City of Samal 35.7 2.6 7.17

Only one of these ten cities is classified as highly poor and six are moderately poor. The

other three cities are classified as mildly poor in 2006. Tangub City of Misamis Occidental,

Region X which is the lone city to be classified as highly poor in 2006 was estimated to have

lower poverty incidence in 2009. Hence, it is classified as moderately poor in 2009 with an

estimated poverty incidence of 43.1%. Such change is declared statistically significant at 5%

level (see Table 8). It is one of the four cities in the top ten with significant change in its


estimated poverty incidence. Thus, after three years, Tangub City was able to move out of

being highly poor.

The six cities classified as moderately poor in 2006 are the cities of Bais, Canlaon and

Bayawan, all in Negros Oriental, Region VII; Dapitan City of Zamboanga del Norte, Region

IX; Ligao City of Albay, Region V; and Gingoog City of Misamis Oriental, Region X. After 3

years, the Cities of Bayawan, Ligao and Gingoog remained to be moderately poor while the

other three cities have lower estimated poverty incidence. Thus, these were classified in

lower category as mildly poor. However, only the cities of Bais and Canlaon have statistically

significant change in their estimates at 5% level.

The 8th, 9th and 10th poorest cities identified earlier, were all classified as mildly poor in 2006.

In 2009, Passi City of Iloilo, Region VI and the Island Garden City of Samal in Davao del

Norte, Region XI remained to be mildly poor. However, Sipalay City of Negros Occidental,

Region VI has higher estimated poverty incidence and was classified as moderately poor in

2009. Among these three cities, only Passi City has a statistically significant change in its

poverty incidence estimate. But such change did not result in a change in its poverty

classification, i.e., it remained to be mildly poor in 2009.

Table 8. Estimated poverty incidences and their coefficients of variation of the top 10 cities in 2006 and 2009.

REGION PROVINCE MUNCIPALITY

2006 2009

POVERTY

INCIDENCE CV

POVERTY

INCIDENCE CV

Region X Misamis Occidental Tangub City 63.8* 9.25 43.1* 5.80

Region VII Negros Oriental Bais City 54.3* 6.81 37.2* 8.06

Region VII Negros Oriental Canlaon City 54.0* 12.22 35.4* 12.43

Region VII Negros Oriental Bayawan City 50.9 15.32 42.6 7.75

Region IX Zamboanga del Norte Dapitan City 46.7 11.35 40.0 11.25

Region V Albay Ligao City 45.9 6.54 40.5 5.43

Region X Misamis Oriental Gingoog City 44.1 7.03 48.7 4.93

Region VI Negros Occidental Sipalay City 39.4 11.17 45.9 10.89

Region VI Iloilo Passi City 36.5* 7.40 24.5* 11.84

Region XI Davao del Norte Island Garden City of Samal 35.7 7.28 32.8 8.54 *change in the estimates is statistically significant at 5% level.


III. Actual Policy Uses

In the past releases of the Municipal and City level poverty estimates, various government

agencies have demonstrated actual policy uses of these estimates. Given the relevance and

importance of these estimates for targeting beneficiaries of programs/projects, policy

formulation and planning, and poverty monitoring, the NSCB responds to the need for more

updated poverty statistics. The updated Municipal and City level poverty estimates for 2006

and 2009 have likewise exhibited actual policy uses.

A list of the actual policy uses of the 2006 and 2009 Municipal and City level poverty

estimates has been compiled below to serve as reference for other policy- and decision-

makers, and program implementers.

A. Targeting Beneficiaries of Programs/Projects

1. The Department of Social Welfare and Development (DSWD) has been continuously

using the small area estimates of poverty in identifying and prioritizing provinces and

municipalities across the country for their National Household Targeting System for

Poverty Reduction (NHTS-PR), which serves as basis in identifying beneficiaries for the

Pantawid Pamilya Program (or formerly known as 4Ps, which stands for Pantawid

Pamilyang Pilipino Program).

2. The Provincial Government of Eastern Samar used the small area estimates in the

identification of project sites of UNICEF, UNFPA, ECCD, PLAN Philippines,

PNRC/Agencia Espanola de Cooperacion Internacionale (AECI), DA/ADB Infrastructure

for Rural Productivity Enhancement Sector (InFRES) Project and GTZ Livelihood

Programs and Projects. The poverty data were also used in the identification of project

beneficiaries of development interventions such as light, housing, water and sanitation,

feeding program, literacy mapping, livelihood projects, Philhealth membership coverage,

medical and dental missions, and other related services.

3. The Provincial Government of Southern Leyte utilized SAE in identifying the poor

municipalities, for possible interventions geared towards poverty alleviation, in

coordination with other departments implementing poverty-related programs.

4. In Central Visayas, the SAE was used in the identification of beneficiaries for the

National Community Driven Development Program (NCDDP). This program is the


scaling up of the operations of the community-driven development approach of Kalahi-

CIDSS, which will cover 104 towns in the region. These towns will undergo an enrolment

process this year.

5. In the Cordillera Administrative Region (CAR), scholars for the Students Grants-in-Aid

Program for Poverty Alleviation (SGP-PA) of the DSWD, State Universities and Colleges

(SUCs) and Department of Labor and Employment (DOLE) were selected from 37 poor

municipalities identified by the NSCB in CAR. Each scholar is provided a maximum of

PhP 60,000 grant a year. These scholars are also recipients of the CCT in CAR.

6. The Technical Education and Skills Development Authority (TESDA) in Region 12

targeted participants/beneficiaries for their skills training, which is dubbed cash-for-

training program or C4TP, from the poorest of the poor municipalities in the region. The

Program mainly aims to provide more livelihood opportunities and eventually improve the

socio-economic status of the region’s poorest of the poor households that are supported

by the government’s Pantawid Pamilya.

7. The Municipal and City level poverty estimates were used to identify the beneficiaries of

the Kalahi-CIDSS in the following areas: a) Malate and Manila of the National Capital

Region (NCR), b) Cavite of CALARZON Region, c) Bicol region, d) Negros Oriental in

Central Visayas, and e) Butuan City, Agusan del Norte in Caraga, for the implementation

of the program in 2013.

B. Policy Formulation, Planning and Monitoring

1. The National Nutrition Council (NNC) used the SAE of poverty in the analysis of the

different causes of malnutrition in their Regional Nutrition Strategic Plan 2011-2016. The

estimates were also used to correlate and/or validate the prevalence rate of malnutrition

in a particular municipality.

2. The Provincial Government of Eastern Samar and its component municipalities used

SAE in the formulation/updating of the Provincial Development and Physical Framework

Plan, Comprehensive Development Plans and Comprehensive Land Use Plans of

municipalities.

3. The Caucus of Development NGO Networks (CODE-NGO) used the 2009 SAE as

baseline data in the conduct of Civil Society Satisfaction Report Card (CSRC) survey for


2012-2015. The overall objective of the project is to contribute in the poverty reduction

of 10 poorest municipalities in Eastern Visayas through the improvement of local poverty

reduction action plans and budgets, and local government service delivery, particularly in

health and agriculture/fishery.

4. The Provincial Government of La Union and San Fernando City used the poverty

estimates as basis in formulating and implementing poverty programs and projects in the

city, as well as in the whole province.

IV. Conclusions and Recommendations

1. Using the modified ELL methodology, there were 1,338 municipalities and cities in 2006

that had poverty incidence with CVs lower or equal to 20%. In 2009, these increased to

1,446 municipalities and cities. This means that reliable estimates of poverty incidence

at the Municipal and City levels can be generated using the small area estimation

methodology.

2. In the development of the regional models, consideration of other indicators, such as

tourism and migration indicators, may help in further improving the accuracy of the

poverty estimates.

3. Recognizing the importance of Municipal and City level poverty estimates, there is a

need to seriously consider the development of an official methodology for the generation

of regular Municipal and City level poverty estimates and its possible inclusion in the

official poverty statistics regularly generated by the NSCB.

4. Behind all these efforts by the NSCB to generate small area estimates of poverty, there

is a need for continuous statistical capacity building among the producers, users and the

providers of statistics. As the NSCB responds to the need to produce more relevant

statistics, data users should demonstrate better use of statistics in policy-making and

program implementation.


V. Annex

A. Definition of Terms

1. Poor – Based on Republic Act 8425, otherwise known as Social Reform and Poverty

Alleviation Act, dated 11 December 1997, the poor refers to individuals and families

whose income fall below the poverty threshold as defined by the government and/or

those that cannot afford in a sustained manner to provide their basic needs of food,

health, education, housing and other amenities of life. It may be estimated in terms of

percentages (poverty incidence) and total number of poor families (magnitude of poor

families)

2. Poverty Threshold - the minimum income/expenditure required for a family/individual to

meet the basic food and non-food requirements. Basic food requirements are currently

based on 100% adequacy for the Recommended Energy and Nutrient Intake (RENI) for

protein and energy equivalent to an average of 2000 kilocalories per capita, and 80%

adequacy for other nutrients. On the other hand, basic non-food requirements, indirectly

estimated by obtaining the ratio of food to total basic expenditures from a reference

group of families, cover expenditure on: 1) clothing and footwear; 2) housing; 3) fuel,

light, water; 4) maintenance and minor repairs; 5) rental of occupied dwelling units; 6)

medical care; 7) education; 8) transportation and communication; 9) non-durable

furnishings; 10) household operations; and 11) personal care & effects. Mathematically,

poverty threshold is computed as:

Food Expenditure is actual food expenditure of families within the +/- ten percentile of the

food threshold while Total Basic Threshold is total expenditures of families within the +/-

ten percentile of the food threshold.

3. Poverty Incidence - the proportion of families/individuals with per capita

income/expenditure less than the per capita poverty threshold to the total number of

families/individuals. Poverty incidence (usually expressed in percent) is estimated as

ratio of the number of families/individuals with per capita annual income/expenditure less

than the per capita poverty threshold and the total number of families/individuals.


B. Methodology

This section presents a general description on small area estimation following the Elbers,

Lanjouw and Lanjouw (ELL) methodology implemented in the Philippines for the intercensal

years 2006 and 2009 using the PovMap software. As the methodology used in this updating

is similar to the previous poverty mapping project undertaken by NSCB, up to a certain

extent, some parts of this section are lifted directly from the previous Estimation of Local

Poverty in the Philippines report.

1. Background In this study, the main consideration is to identify local areas that need to be prioritized in

poverty alleviation programs. These areas, which have uncontained pockets of poverty, are

often sought through the use of nationwide survey data that provide information on poverty

indicators. These surveys usually have a great deal of information, such as income and

expenditure, but have limited sample size that can only provide reliable estimates at larger

geographic disaggregation such as regions, but not at smaller geographic level such as

provinces or municipalities or cities. The census, on the other hand, has complete coverage

and therefore can produce reliable estimates at smaller geographic levels. However, the

census usually has limited information and does not contain data on income and

expenditure, which are the variables usually needed as inputs in poverty estimation.

A solution to this problem is the use of small area estimation (SAE) technique. There are

numerous SAE techniques that can actually be used to generate statistics at the local area.

One of these techniques is a methodology developed by the World Bank, which is commonly

referred to as the Elbers, Lanjouw and Lanjouw (ELL) methodology. Such methodology

requires the use of census and survey data sets conducted on the same year. In the

Philippines, this situation occurred in the year 2000. Consequently, a Poverty Mapping

Project implemented by the NSCB in 2005 with funding assistance from the World Bank

used the ELL method to generate the Municipal and City level poverty statistics for 2000.

The project made use of the FIES, LFS and CPH data sets that were all gathered in the

same year, 2000, as required in the methodology. More so, the methodology in the project

made use of a single regression model1 for the whole country to predict the family income

per capita in logarithmic form.

1 Regression is a statistical tool used to predict one variable using other variables/information. For example, one can predict a salesperson’s total yearly sales using information on age, education and years of experience of the sales person.


An update of the 2000 Municipal and City level poverty estimates was again generated by

NSCB with funding assistance from the WB. This case, however, is different from the

previous project since Municipal and City level poverty estimates will be generated for 2003,

a year when there will be no census to be conducted but there will be a nationwide survey,

which is the usual source of poverty statistics. Thus, in updating the small area poverty

estimates from the census year 2000 to the intercensal year 2003, a slightly different

approach was used.

The information from the 2003 FIES, 2004 January LFS and 2000 CPH were combined to

estimate poverty incidence for the provincial and municipal levels. Statistical regression is

again used to predict per capita family income, expressed in natural logarithmic form Y,

using explanatory variables, which are denoted as X.

Similar with the 2000 poverty mapping project, X can be classified into two types: the survey-

obtainable variables, at the household or individual level (e.g., educational attainment of

household head); and the census-derivable location variables, which correspond to

barangay or municipal means (e.g. average family size in the barangay). It is important that

the X’s used in modelling should be comparable both in the survey and the census. In

general, comparability means that X has the same definition in both survey and census.

However, the 2000 poverty mapping project, comparability assessment was more

straightforward because the data sets used (i.e., FIES, LFS and CPH) have the same

reference period: the year 2000. Selection of survey-obtainable variables was done by

examining the survey and census questionnaires to identify which questions elicit equivalent

information. In several cases, equivalence was achieved by collapsing some categories of

answers. When common variables had been identified, the appropriate summary statistics

were compared for the survey and the census data.

It is ideal that the summary statistics for the census data be within the confidence interval for

the survey. Comparability assessment is not required for the case of location-effect variables

because these are essentially sourced from the census, which were only merged with the

survey; and as long as the geographic configurations between survey and census are the

same.

Assessing comparability in the case of updating small area poverty statistics for non-census

years require more attention. It should be noted that the survey data were taken in 2003

while census data were obtained in 2000, while the goal is to come up with 2003 poverty

statistics at the small area level. Hence, there is a time component that should be taken into


consideration. Using the same methodology as in the 2000 poverty mapping project will

result to ambiguity since such procedure captures relationship between Y and X, through

regression modelling using 2003 survey information but fitting the model using 2000 census

data, which is of a different reference period.

The same is the case for this project where generation of 2006 and 2009 Municipal and City

level poverty estimates will be done using 2000 Census of Population and Housing (CPH)

and 2007 Population Census will be used respectively since 2006 and 2009 are non-census

years like 2003.

2. Data Sources

In the generation of the 2006 and 2009 Municipal and City level poverty estimates in the

Philippines using the ELL methodology, the following data sets were used:

a. For the generation of the 2006 Municipal and City level poverty estimates

2006 Official Provincial Poverty Thresholds (disaggregated by urban and rural areas).

These are generated by the National Statistical Coordination Board (NSCB) for each of the

provinces, urban and rural areas, based on the methodology per NSCB Resolution No. 9,

Series of 2011 - Approving the Refinements in the Official Poverty Estimation Methodology.

2006 Family Income and Expenditure Survey (FIES)

The FIES is a nationwide survey conducted by the National Statistics Office (NSO) every

three years, which consists of 70 pages of information on household income and

expenditure, as well as, some socio-demographic characteristics of the family. It is the main

source of income and expenditure data in the estimation of official poverty statistics in the

country. The 2006 FIES is a regular module of the Integrated Survey of Households (ISH),

which contains 38,483 sample households, distributed across the 17 regions of the country.

January 2007 Labor Force Survey (LFS)

The LFS is another regular module of the ISH of NSO conducted every quarter of the year.

It collects data on the demographic and socio-economic characteristics of population 15

years old and over and the major source of official employment data of the country. The

FIES is actually a rider to the LFS. Hence, most, if not all, of sample households in the 2006

FIES are also available in the January 2007 LFS.


2000 Census of Population and Housing (CPH)

The CPH is a complete enumeration of the population in the country conducted at least

every ten years. It is a vital source of information on the composition of the population and

characteristics of their housing units. It covers all areas under the jurisdiction of the

Philippines as defined by the 1987 Constitution.

b. For the generation of the 2009 Municipal and City level poverty estimates

2009 Official Provincial Poverty Thresholds (disaggregated by urban and rural areas).

These are also generated by the NSCB for each of the provinces, urban and rural areas,

based on the methodology per NSCB Resolution No. 9, Series of 2011 - Approving the

Refinements in the Official Poverty Estimation Methodology.

2009 Family Income and Expenditure Survey (FIES)

The 2009 FIES contains 38,400 sample households distributed across the 17 regions of the

country.

January 2010 Labor Force Survey (LFS)

Most, if not all, of sample households in the 2009 FIES are also available in the January

2010 LFS.

2007 Census of Population (PopCen)

Similar to the 2000 CPH, the 2007 PopCen is a complete enumeration of the population in

the country. However, unlike the 2000 CPH, information collected in the 2007 PopCen is

more limited.

3. Implementation of the Methodology

a. Introduction/Background

In introducing the concept of small area estimation, we consider the thrust of the national

government of alleviating poverty in the country. To maximize the effect of any poverty

alleviation program, there are a number of factors that have to be carefully taken into

account before implementation. One of the most common considerations is the proper

identification of priority areas. Answers to questions such as which areas need most help

and assistance from the government are often sought from national surveys that provide

information on poverty indicators. Needless to say, users want surveys to have as much

coverage as that of a census. However, this is not usually feasible because survey coverage

is directly proportional to the amount of administrative and financial resources available to


carry out the survey. Thus, surveys being incomplete enumeration of all populations units

have limitations and sampling errors. Due to the sampling design, surveys may not be

representative at the province and district level, such that estimates may tend to be biased.

In this context, survey domains provide information on the level of disaggregation of direct

estimates that can be derived from a survey which are theoretically reliable. For example,

the domain of the 2006 FIES conducted by NSO corresponds to the geographic region.

Therefore, it is not surprising to get relatively high standard errors for some poverty

estimates at the provincial level. This could imply that the sample is not representative at

that level, and so, the estimates may tend to be biased. Further, analogous estimates at the

municipal level is expected to be less reliable should these be generated directly from the

survey. In this example, the sets of geographic provinces and municipalities are referred to

as statistical small areas. Hence, small area estimation is a collection of statistical

techniques designed to provide reliable estimates beyond the survey domain. There are a

number of small area techniques and among them is the ELL method, which was used by

the NSCB to generate the Municipal and City poverty statistics for 2000 and 2003.

In updating the small area poverty estimates from the 2000 and 2007 census years to the

intercensal years 2006 and 2009, respectively, a similar approach to the generation of the

2003 Municipal and City level poverty estimates was used. As mentioned in the previous

section, for the generation of the 2006 small area poverty estimates, information from the

2006 FIES, 2007 January Labor Force Survey (LFS), and 2000 Census of Population and

Housing (CPH) were combined to estimate poverty incidence among population for each of

the Municipal and City in the country. On the other hand, for the estimation of the 2009

Municipal and City level poverty estimates, we made used of 2007 CPH, 2009 FIES and

2010 January LFS.

Regression modelling was used to predict per capita family income, expressed in natural

logarithmic form2, Y, using explanatory variables, which we denote as X. The explanatory

variables were limited to time-invariant variables.

b. Selection of Explanatory Variables

Similar to the earlier poverty mapping project, the explanatory variables, X, can be classified

into two types: the survey-obtainable variables, at the household or individual level (e.g.,

2 Using natural logarithmic form of income is a usual approach in a number of econometric models. This is done because log of income has symmetric distribution (while income has a highly skewed distribution). The error term in the model, which denotes the unexplained part of the dependent variable, is also assumed symmetric. Such that a model specification where the dependent variable and the error term have a similar distribution will be preferred to a model where they have very different distributions. For a more thorough discussion of this approach, the readers are referred to statistical regression theory texts.


educational attainment of household head, etc.); and the census-derivable location

variables, which correspond to barangay or municipal/city means (e.g., existence of a market

in the barangay, proportion of households with no toilet in the city/municipality). It is

important that the variables, X, used in modelling should be (a) available both in the survey

and census; (b) definition is comparable and/or consistent in both the survey and census

(i.e., X follows the same definition in both survey and census) and (c) have survey and

census statistics (mean value) that match.

It may be noted that the overall objective is to compute Municipal and City level poverty

statistics, with reliable and/or acceptable levels of precision. This can be done by modelling

income using X and fitting the resulting model using its census counterpart. Once this has

been done, there will be predicted (per capita) income for all family units in the census.

Effectively, strength is borrowed from the census which has a larger coverage than the

survey. Note that such procedure requires that the variables constituting X should also be

available from the census. In addition to availability, comparability is also an essential

component in order to make the substitution of X with its census counterpart for computing

predicted (per capita) family income become valid.

In the earlier poverty mapping project, specifically in the generation of 2000 Municipal and

City level poverty estimates, comparability assessment is more straightforward as the data

sets used (i.e., FIES, LFS and CPH) have the same reference period (i.e., 2000). Selection

of survey-obtainable explanatory data can be done by examining the survey and census

questionnaires to identify which questions elicit equivalent information. In several cases,

equivalence may be achieved by collapsing some categories of answers. When common

variables have been identified, the appropriate summary statistics are compared for the

survey and the census data. For variables to be considered as consistent, summary

statistics for the census data should be within the confidence interval for the survey.

Comparability assessment is not required for the case of location-effect variables as these

are sourced from the census, which were merged with the survey; and as long as the

geographic configurations between survey and census are the same.

Assessing comparability in the case of updating small area poverty statistics requires more

attention. Note that survey data is for 2006 and 2009, while census data is for 2000 and

2007, and our goal is to come up with 2006 and 2009 poverty statistics at the small area

level. Hence, the time component has to be taken into consideration; otherwise, ambiguity

may arise when the relationship between Y and X is captured through regression modelling

using 2006 (or 2009) survey information but fitting the model using 2000 (or 2007) census


data. To address the issue, survey-obtainable variables were carefully screened by

examining the survey and census questionnaires not only to identify which questions elicit

equivalent information but also those, which are time-invariant.

Time invariance, as used in this Project, means that the characteristic is not likely to change

from time to time (i.e., stable over time). For some of the variables, this can be done by

purposely collapsing some categories of answers to pre-defined categories. For example, a

binary variable hea_noed can be created, with value 1 if the head of the household did not

have any formal education, 0 otherwise. If the head of the household has no formal

education in 2006 (or 2009), he / she also has no formal education in 2000 (or 2009). When

as many as possible of these “at least” type of variables have been generated, appropriate

summary statistics are compared for the survey and census data. A variable will be included

in the list of explanatory variables X if the summary statistics for the census data is within the

confidence interval of the survey data. Likewise, we also include in the list of explanatory

variables X, location-effect variables represented by the census means. Table 9 shows the

list of these variables grouped accordingly.

Table 9. List of Auxiliary Variables for 2006 and 2009 SAE.

A. Household Characteristics

Variable Definition 2006 2009

ALL_ATCOLL Proportion of household members who have at least college education / /

ALL_ATCOLLGRAD Proportion of household members who is at least college graduate / /

ALL_ATEGRAD Proportion of household members who is at least elementary graduate / /

ALL_ATHSGRAD Proportion of household members who have is least high school graduate / /

ALL_ATLEASTHH Proportion of household members who have at least high school education / /

ALL_ATLOWED Proportion of household members who have at least elementary education / /

ALL_NOED Proportion of household members who have no education (with preschool) / /

ALL_NOGRADE Proportion of household members who have no education (without preschool) / /

ALL_POSTBACC Proportion of household members who have finished post graduate studies / /

DOM_HELP 1 if household has domestic help; 0 otherwise / /

EXTENDED_FAM 1 if the household is extended; 0 otherwise / /

HEA_ATCOLL 1 if the household head has at least college education; 0 otherwise / /

HEA_ATCOLLGRAD 1 if the household head has at least finished college education; 0 otherwise / /

HEA_ATEGRAD 1 if the household head is at least elementary graduate; 0 otherwise / /

HEA_ATHSGRAD 1 if the household head is at least high schoolgraduate; 0 otherwise / /

HEA_ATLEASTHH 1 if the household head has at least high school education; 0 otherwise / /

HEA_ATLOWED 1 if the household head has at least elementary education; 0 otherwise / /

HEA_NOED 1 if the household head has no education (with preschool) ; 0 otherwise / /

HEA_NOGRADE 1 if the household head has no education (without preschool) ; 0 otherwise / /



HEA_POSTBACC 1 if the household head has finished post graduate studies; 0 otherwise / /

HEAD_MALE 1 if head is male; 0 otherwise / /

HH_KIDS 1 if household has at least a member who is son or daughter of the household head; 0 otherwise

/ /

HMS_DIVORCED 1 if the marital status of household head is divorced; 0 otherwise / /

HMS_MARRIED 1 if the marital status of household head is married; 0 otherwise / /

HMS_SINGLE 1 if the marital status of household head is single; 0 otherwise / /

HMS_WIDOWED 1 if the marital status of household head is widowed; 0 otherwise / /

LOT_OWN 1 if lot is owned; 0 otherwise / /

LOT_RENT 1 if lot is rented; 0 otherwise / /

LOT_RENTFWC 1 if lot is rent-free with consent of owner; 0 otherwise / /

LOT_RENTFWOC 1 if lot is rent-free without consent of owner; 0 otherwise / /

MEN_ATCOLL Proportion of male members in the household who have at least college undergrad education

/ /

MEN_ATCOLLGRAD Proportion of male members in the household who have at least college education

/ /

MEN_ATEGRAD Proportion of male members in the household who have at least finished elementary education

/ /

MEN_ATHSGRAD Proportion of male members in the household who have at least finished high school

/ /

MEN_ATLEASTHH Proportion of male members in the household who have at least high school undergrad education

/ /

MEN_ATLOWED Proportion of male members in the household who have at least elementary education

/ /

MEN_NOED Proportion of male members who do not have education (with preschool) / /

MEN_NOGRADE Proportion of male members in the household who have no grade completed / /

MEN_POSTBACC Proportion of male members in the household who have finished post graduate studies

/ /

NO_SPOUSE 1 if no spouse in the family; 0 otherwise / /

ROOF_LIGHT 1 if roof is made of light materials (cogon, nipa, anahaw) ; 0 otherwise / /

ROOF_LIGHT_OLD 1 if roof is made of light materials (cogon, nipa, anahaw) without wood; 0 otherwise

/ /

ROOF_MIXTR_OLD 1 if roof is made of predominantly strong materials; 0 otherwise / /

ROOF_OTH 1 if roof is made of other materials; 0 otherwise / /

ROOF_SALVAGED 1 if roof is made of salvaged materials (makeshift/improvised); 0 otherwise / /

ROOF_SALVAGED_OLD 1 if roof is made of salvaged materials (makeshift/improvised); 0 otherwise / /

ROOF_STRONG 1 if roof is made of strong materials (galvanized, iron, al, tile, concrete, brick, stone, asbestos); 0 otherwise

/ /

ROOF_STRONG_OLD 1 if roof is made of strong materials (galvanized, iron, al, tile, concrete, brick, stone, asbestos) without half-galvanized iron and half concrete; 0 otherwise

/ /

SINGLE_FAM 1 if the household is single family; 0 otherwise / /

SPO_ATCOLL 1 if the household spouse has at least college education; 0 otherwise / /

SPO_ATCOLLGRAD 1 if the household spouse has at least finished college education; 0 otherwise / /

SPO_ATEGRAD 1 if the household spouse is at least elementary graduate; 0 otherwise / /

SPO_ATHSGRAD 1 if the household spouse is at least high school graduate; 0 otherwise / /

SPO_ATLEASTHH 1 if the household spouse has at least high school education; 0 otherwise / /

SPO_ATLOWED 1 if the household spouse has at least elementary education; 0 otherwise / /

SPO_NOED 1 if the household spouse has no education (with preschool) ; 0 otherwise / /

SPO_NOGRADE 1 if the household spouse has no education (without preschool) ; 0 otherwise / /

SPO_POSTBACC 1 if the household spouse has finished post graduate studies; 0 otherwise / /



URB 1 if urban; 0 otherwise / /

WALL_LIGHT 1 if wall is made of light materials; 0 otherwise / /

WALL_MAKESHIFT_OLD 1 if wall is made of salvaged materials (makeshift/improvised); 0 otherwise / /

WALL_MIX_OLD 1 if wall is made of predominantly strong materials; 0 otherwise / /

WALL_OTH 1 if wall is made of other materials; 0 otherwise / /

WALL_SALVAGED 1 if wall is made of salvaged materials (makeshift/improvised) ; 0 otherwise / /

WALL_STRONG 1 if roof is made of strong materials (galvanized, iron, al, tile, concrete, brick, stone, asbestos); 0 otherwise

/ /

WALL_STRONG_OLD 1 if roof is made of strong materials (galvanized, iron, al, tile, concrete, brick, stone, asbestos) without glass and half concrete brick, stone and wood; 0 otherwise

/ /

WOM_ATCOLL Proportion of female members in the household who have at least college undergrad education

/ /

WOM_ATCOLLGRAD Proportion of female members in the household who have at least college education

/ /

WOM_ATEGRAD Proportion of female members in the household who have at least finished elementary education

/ /

WOM_ATHSGRAD Proportion of female members in the household who have at least finished high school

/ /

WOM_ATLEASTHH Proportion of female members in the household who have at least high school education

/ /

WOM_ATLOWED Proportion of female members in the household who have at least elementary education

/ /

WOM_NOED Proportion of female members who do not have education (with preschool) / /

WOM_NOGRADE Proportion of female members in the household who have no grade completed / /

WOM_POSTBACC Proportion of female members in the household who have finished post graduate studies

/ /

BUILDING_COMMERCIAL 1 if the type of house is a commercial/industrial/agricultural; 0 otherwise /

BUILDING_DUPLEX 1 if the type of house is a duplex; 0 otherwise /

BUILDING_MULTIRESIDENTIAL 1 if the type of house is a multi-unit residential/apartment/accessoria/condo/townhouse; 0 otherwise

/

BUILDING_OTHERS 1 if the type of house is other housing unit; 0 otherwise /

BUILDING_SINGLE 1 if the type of house is a single house; 0 otherwise /

FLOOR_10_TO_19 1 if the housing unit floor area is 10 to 19 sq. ; 0 otherwise /








FLOOR_LESS_10 1 if the housing unit floor area is less than 10 sq. ; 0 otherwise /

FLOOR_OVER_200 1 if the housing unit floor area is 200 sq. m. and over; 0 otherwise /

B. Barangay Characteristics


BGY_ALL_COED Average proportion of household members with college education in the barangay

/ /

BGY_FAMSIZE Average family size in the barangay / /

BGY_PER_61UP Average proportion of household members aged 61 and above in the barangay / /



BGY_PER_GKID Average proportion of household members who are grandsons/granddaughters of head in the barangay

/ /

BGY_PER_HHALL1 Average proportion of members age <1 in the barangay / /

BGY_PER_HHALL1524 Average proportion of members ages 15-24 in the barangay / /



BGY_PER_HHALL25UP Average proportion of members ages 25 and up in the barangay / /


BGY_PER_KIDS Average proportion of household members who are children of the household head in the barangay

/ /

BGY_PER_KIDSINLAW Average proportion of household members who are sons/daughters in law of head in the barangay

/ /

BGY_PER_NONREL Average proportion of members who are non-relatives: boarders, domestic help, other in the barangay

/ /

BGY_PER_OTHREL Average proportion of household members who are other relatives of head in the barangay

/ /

BGY_PER_PARENT Average proportion of household members who are parents of head in the barangay

/ /

BGY_PER_SIB Average proportion of household members who are brother/sister of head in the barangay

/ /

BGY_WOM_COED Average proportion of women household members with college education in the barangay

/ /

BGY_WOM_ELED Average proportion of women household members with elementary education in the barangay

/ /

BGY_WOM_HSED Average proportion of women household members with high school education in the barangay

/ /

BGY_OCC_AGRI Average number of members who are farmers, forestry workers and fishermen in the barangay

/

BGY_OCC_CLERKS Average number of members who are clerks in the barangay /

BGY_OCC_LABORERS Average number of members who are laborers and unskilled workers in the barangay

/

BGY_OCC_OFFICIALOFGOVT Average number of members who are officials of gov't and special interest organizations, corporate executives, managers, managing proprietors and supervisors in the barangay

/

BGY_OCC_PLANT Average number of members who are plant and machine operators and assemblers in the barangay

/

BGY_OCC_PROF Average number of members who are professionals in the barangay /

BGY_OCC_SERVICE Average number of members who are services workers and shop and market sales workers in the barangay

/

BGY_OCC_SPECIAL Average number of members who are special occupations in the barangay /

BGY_OCC_TECH Average number of members who are technicians and associate professionals in the barangay

/

BGY_OCC_TRADE Average number of members who are trades and related workers in the barangay

/

C. 2000 CPH and 2007 PopCen Barangay Listing


BGY_AGRI 1 if the barangay has at least 50proportion of of the 10 years old and over population are farmers, farm labourers, fishermen, loggers and forest product gatherers; 0 otherwise

/ /

BGY_CAPITOL 1 if the barangay has a town/city hall or provincial capitol; 0 otherwise / /

BGY_CHURCH 1 if the barangay has a church, chapel or mosque with religious service at least once a month; 0 otherwise

/ /

BGY_CELLPHONE 1 if the barangay has cellular phone signal; 0 otherwise / /

BGY_COLLEGE 1 if the barangay has college; 0 otherwise / /



BGY_COMWORK 1 if the barangay has community works system; 0 otherwise / /

BGY_ELECTRIC 1 if the barangay has electric power; 0 otherwise / /

BGY_ELEM 1 if the barangay has elementary school; 0 otherwise / /

BGY_HEALTH 1 if the barangay has a puericulture center/barangay health center; 0 otherwise / /

BGY_HIGHSCH 1 if the barangay has a high school; 0 otherwise / /

BGY_HIGHWAY 1 if the barangay is accessible to national highway; 0 otherwise / /

BGY_HOSP 1 if the barangay has a hospital; 0 otherwise / /

BGY_LIBRARY 1 if the barangay has a public library; 0 otherwise / /

BGY_MARKET 1 if the barangay has a market place or building were trading activities are carried on at least once a week; 0 otherwise

/ /

BGY_PLAZA 1 if the barangay has public plaza; 0 otherwise / /

BGY_POST 1 if the barangay has postal service; 0 otherwise / /

BGY_STREETS 1 if the barangay has a street pattern, i.e. networks of streets of at least 3 streets or roads; 0 otherwise

/ /

BGY_TELEP 1 if the barangay has a telephone system; 0 otherwise / /

BGY_TOWNCITY 1 if the barangay is a part of the town/city proper or former poblacion of the municipality, or poblacion/city district; 0 otherwise

/ /

BGY_HALL 1 if the barangay has a barangay hall; 0 otherwise /

BGY_HOUSPRJ 1 if the barangay has a housing project; 0 otherwise /

BGY_TELEG 1 if the barangay has a telelgraph system; 0 otherwise /

BGY_COMEST 1 if the barangay has a commercial establishment; 0 otherwise /

BGY_COMEST_10 1 if the barangay has at least 10 commercial establishments; 0 otherwise /

BGY_COMEST_1TO9 1 if the barangay has at most 9 commercial establishments; 0 otherwise /

BGY_FINEST 1 if the barangay has a financial establishment; 0 otherwise /

BGY_FINEST_10 1 if the barangay has at least 10 financial establishments; 0 otherwise /

BGY_FINEST_1TO9 1 if the barangay has at most 9 financial establishments; 0 otherwise /

BGY_LODEST 1 if the barangay has a lodging establishment; 0 otherwise /

BGY_LODEST_10 1 if the barangay has at least 10 lodging establishments; 0 otherwise /

BGY_LODEST_1TO9 1 if the barangay has at most 9 lodging establishments; 0 otherwise /

BGY_MANEST 1 if the barangay has a manufacturing establishment; 0 otherwise /

BGY_MANEST_10 1 if the barangay has at least 10 manufacturing establishments; 0 otherwise /

BGY_MANEST_1TO9 1 if the barangay has at most 9 manufacturing establishments; 0 otherwise /

BGY_RECEST 1 if the barangay has a recreational establishment; 0 otherwise /

BGY_RECEST_10 1 if the barangay has at least 10 recreational establishments; 0 otherwise /

BGY_RECEST_1TO9 1 if the barangay has at most 9 recreational establishments; 0 otherwise /

BGY_SEREST 1 if the barangay has a service establishment; 0 otherwise /

BGY_SEREST_10 1 if the barangay has at least 10 service establishments; 0 otherwise /

BGY_SEREST_1TO9 1 if the barangay has at most 9 service establishments; 0 otherwise /

BGY_CEMETERY 1 if the barangay has a cemetery; 0 otherwise /

BGY_FIRE 1 if the barangay has public fire-protection service; 0 otherwise /

BGY_SWEEPER 1 if the barangay has a public street sweeper; 0 otherwise /

BGY_SEAPORT 1 if the barangay has seaport in operation; 0 otherwise /

BGY_COMEST_W10 Number of commercial establishments in the barangay with less than 10 employees (Q6a1)

/

BGY_COMEST_W99 Number of commercial establishments in the barangay with at least 10 but less than 100 employees (Q6a2)

/



BGY_COMEST_W100 Number of commercial establishments in the barangay with at least 100 employees (Q6a3)

/

BGY_ W2COMEST_W10 Number of commercial establishments outside the barangay but within 2 kms with less than 10 employees (Q6b1)

/

BGY_ W2COMEST_W99 Number of commercial establishments outside the barangay but within 2 kms with at least 10 but less than 100 employees (Q6b2)

/

BGY_ W2COMEST_W100 Number of commercial establishments outside the barangay but within 2 kms with at least 100 employees (Q6b3)

/

BGY_TCOMEST Total number of commercial establishments in the barangay (equal to the sum of Q6a1+Q6a2+Q6a3)

/

BGY_W2TCOMEST Total number of commercial establishments outside the barangay but within 2 kms from barangay hall (equal to the sum of Q6b1+Q6b2+Q6b3)

/

BGY_PCOMEST_W10 Proportion of commercial establishments in the barangay with less than 10 employees (equal to Q6a1/BGY_TCOMEST)

/

BGY_PCOMEST_W99 Proportion of commercial establishments in the barangay with at least 10 but less than 100 employees (equal to Q6a2/BGY_TCOMEST)

/

BGY_PCOMEST_W100 Proportion of commercial establishments in the barangay with at least 100 employees (equal to Q6a3/ BGY_TCOMEST)

/

BGY_W2PCOMEST_W10 Proportion of commercial establishments outside the barangay but within 2 kms from barangay hall with less than 10 employees (equal to Q6b1/BGY_W2TCOMEST)

/

BGY_W2PCOMEST_W99 Proportion of commercial establishments outside the barangay but within 2 kms from barangay hall with at least 10 but less than 100 employees (equal to Q6b2/BGY_ W2TCOMEST)

/

BGY_W2PCOMEST_W100 Proportion of commercial establishments outside the barangay but within 2 kms from barangay hall with at least 100 employees (equal to Q6b3/ BGY_ W2TCOMEST)

/

BGY_PREDCOMEST

Predominant type (based on employment size) of commercial establishments in the barangay (takes the value 3 (LARGE) if BGY_PCOMEST_100 = MAX (BGY_PCOMEST_100, BGY_PCOMEST_99, BGY_PCOMEST_10); takes the value 2 (MEDIUM) if BGY_PCOMEST_99 = MAX (BGY_PCOMEST_100, BGY_PCOMEST_99, BGY_PCOMEST_10); takes the value 1 (SMALL) if BGY_PCOMEST_10 = MAX (BGY_PCOMEST_100, BGY_PCOMEST_99, BGY_PCOMEST_10);

/

BGY_W2PRCOMEST

Predominant type (based on employment size) of commercial establishments outside the barangay but within 2 kms from barangay hall (takes the value 3 (LARGE) if BGY_W2PCOMEST_100 = MAX (BGY_ W2PCOMEST_100, BGY_ W2PCOMEST_99, BGY_ W2PCOMEST_10); takes the value 2 (MEDIUM) if BGY_ W2PCOMEST_99 = MAX (BGY_ W2PCOMEST_100, BGY_ W2PCOMEST_99, BGY_ W2PCOMEST_10); takes the value 1 (SMALL) if BGY_ W2PCOMEST_10 = MAX (BGY_ W2PCOMEST_100, BGY_ W2PCOMEST_99, BGY_ W2PCOMEST_10);

/

BGY_RECEST_W10 Number of recreational establishments in the barangay with less than 10 employees (Q7a1)

/

BGY_RECEST_W99 Number of recreational establishments in the barangay with at least 10 but less than 100 employees (Q7a2)

/

BGY_RECEST_W100 Number of recreational establishments in the barangay with at least 100 employees (Q7a3)

/

BGY_ W2RECEST_W10 Number of recreational establishments outside the barangay but within 2 kms with less than 10 employees (Q7b1)

/

BGY_ W2RECEST_W99 Number of recreational establishments outside the barangay but within 2 kms with at least 10 but less than 100 employees (Q7b2)

/

BGY_ W2RECEST_W100 Number of recreational establishments outside the barangay but within 2 kms with at least 100 employees (Q7b3)

/

BGY_DRECEST_W10

Descriptive distance of the nearest recreational establishments with less than 10 employees (if Q7a1=0 & Q7b1=0 then value to take is Q7c1; Otherwise, value to take is 0 which represents that a recreational establishment is at most 2 kms from barangay hall)

/

BGY_DRECEST_W99

Descriptive distance of the nearest recreational establishments with at least 10 but less than 100 employees (if Q7a2=0 & Q7b2=0 then value to take is Q7c2; Otherwise, value to take is 0 which represents that a recreational establishment is at most 2 kms from barangay hall)

/



BGY_DRECEST_W100

Descriptive distance of the nearest recreational establishments at least 100 employees (if Q7a3=0 & Q7b3=0 then value to take is Q7c3; Otherwise, value to take is 0 which represents that a recreational establishment is at most 2 kms from barangay hall )

/

BGY_TRECEST Total number of recreational establishments in the barangay (equal to the sum of Q7a1+Q7a2+Q7a3)

/

BGY_W2TRECEST Total number of recreational establishments outside the barangay but within 2 kms from barangay hall (equal to the sum of Q7b1+Q7b2+Q7b3)

/

BGY_PRECEST_W10 Proportion of recreational establishments in the barangay with less than 10 employees (equal to Q7a1/BGY_TRECEST)

/

BGY_PRECEST_W99 Proportion of recreational establishments in the barangay with at least 10 but less than 100 employees (equal to Q7a2/BGY_TRECEST)

/

BGY_PRECEST_W100 Proportion of recreational establishments in the barangay with at least 100 employees (equal to Q7a3/ BGY_TRECEST)

/

BGY_W2PRECEST_W10 Proportion of recreational establishments outside the barangay but within 2 kms from barangay hall with less than 10 employees (equal to Q7b1/BGY_W2TRECEST)

/

BGY_W2PRECEST_W99 Proportion of recreational establishments outside the barangay but within 2 kms from barangay hall with at least 10 but less than 100 employees (equal to Q7b2/BGY_ W2TRECEST)

/

BGY_W2PRECEST_W100 Proportion of recreational establishments outside the barangay but within 2 kms from barangay hall with at least 100 employees (equal to Q7b3/ BGY_ W2TRECEST)

/

BGY_PREDRECEST

Predominant type (based on employment size) of recreational establishments in the barangay (takes the value 3 (LARGE) if BGY_PRECEST_100 = MAX (BGY_PRECEST_100, BGY_PRECEST_99, BGY_PRECEST_10); takes the value 2 (MEDIUM) if BGY_PRECEST_99 = MAX (BGY_PRECEST_100, BGY_PRECEST_99, BGY_PRECEST_10); takes the value 1 (SMALL) if BGY_PRECEST_10 = MAX (BGY_PRECEST_100, BGY_PRECEST_99, BGY_PRECEST_10);

/

BGY_W2PRRECEST

Predominant type (based on employment size) of recreational establishments outside the barangay but within 2 kms from barangay hall (takes the value 3 (LARGE) if BGY_W2PRECEST_100 = MAX (BGY_ W2PRECEST_100, BGY_ W2PRECEST_99, BGY_ W2PRECEST_10); takes the value 2 (MEDIUM) if BGY_ W2PRECEST_99 = MAX (BGY_ W2PRECEST_100, BGY_ W2PRECEST_99, BGY_ W2PRECEST_10); takes the value 1 (SMALL) if BGY_ W2PRECEST_10 = MAX (BGY_ W2PRECEST_100, BGY_ W2PRECEST_99, BGY_ W2PRECEST_10);

/

BGY_MANEST_W10 Number of manufacturing establishments in the barangay with less than 10 employees (Q8a1)

/

BGY_MANEST_W99 Number of manufacturing establishments in the barangay with at least 10 but less than 100 employees (Q8a2)

/

BGY_MANEST_W100 Number of manufacturing establishments in the barangay with at least 100 employees (Q8a3)

/

BGY_ W2MANEST_W10 Number of manufacturing establishments outside the barangay but within 2 kms with less than 10 employees (Q8b1)

/

BGY_ W2MANEST_W99 Number of manufacturing establishments outside the barangay but within 2 kms with at least 10 but less than 100 employees (Q8b2)

/

BGY_ W2MANEST_W100 Number of manufacturing establishments outside the barangay but within 2 kms with at least 100 employees (Q8b3)

/

BGY_TMANEST Total number of manufacturing establishments in the barangay (equal to the sum of Q8a1+Q8a2+Q8a3)

/

BGY_W2TMANEST Total number of manufacturing establishments outside the barangay but within 2 kms from barangay hall (equal to the sum of Q8b1+Q8b2+Q8b3)

/

BGY_PMANEST_W10 Proportion of manufacturing establishments in the barangay with less than 10 employees (equal to Q8a1/BGY_TMANEST)

/

BGY_PMANEST_W99 Proportion of manufacturing establishments in the barangay with at least 10 but less than 100 employees (equal to Q8a2/BGY_TMANEST)

/

BGY_PMANEST_W100 Proportion of manufacturing establishments in the barangay with at least 100 employees (equal to Q8a3/ BGY_TMANEST)

/

BGY_W2PMANEST_W10 Proportion of manufacturing establishments outside the barangay but within 2 kms from barangay hall with less than 10 employees (equal to Q8b1/BGY_W2TMANEST)

/



BGY_W2PMANEST_W99 Proportion of manufacturing establishments outside the barangay but within 2 kms from barangay hall with at least 10 but less than 100 employees (equal to Q8b2/BGY_ W2TMANEST)

/

BGY_W2PMANEST_W100 Proportion of manufacturing establishments outside the barangay but within 2 kms from barangay hall with at least 100 employees (equal to Q8b3/ BGY_ W2TMANEST)

/

BGY_PREDMANEST

Predominant type (based on employment size) of manufacturing establishments in the barangay (takes the value 3 (LARGE) if BGY_PMANEST_100 = MAX (BGY_PMANEST_100, BGY_PMANEST_99, BGY_PMANEST_10); takes the value 2 (MEDIUM) if BGY_PMANEST_99 = MAX (BGY_PMANEST_100, BGY_PMANEST_99, BGY_PMANEST_10); takes the value 1 (SMALL) if BGY_PMANEST_10 = MAX (BGY_PMANEST_100, BGY_PMANEST_99, BGY_PMANEST_10);

/

BGY_W2PRMANEST

Predominant type (based on employment size) of manufacturing establishments outside the barangay but within 2 kms from barangay hall (takes the value 3 (LARGE) if BGY_W2PMANEST_100 = MAX (BGY_ W2PMANEST_100, BGY_ W2PMANEST_99, BGY_ W2PMANEST_10); takes the value 2 (MEDIUM) if BGY_ W2PMANEST_99 = MAX (BGY_ W2PMANEST_100, BGY_ W2PMANEST_99, BGY_ W2PMANEST_10); takes the value 1 (SMALL) if BGY_ W2PMANEST_10 = MAX (BGY_ W2PMANEST_100, BGY_ W2PMANEST_99, BGY_ W2PMANEST_10);

/

BGY_LODEST_W10 Number of lodging establishments in the barangay with less than 10 employees (Q9a1)

/

BGY_LODEST_W99 Number of lodging establishments in the barangay with at least 10 but less than 100 employees (Q9a2)

/

BGY_LODEST_W100 Number of lodging establishments in the barangay with at least 100 employees (Q9a3)

/

BGY_ W2LODEST_W10 Number of lodging establishments outside the barangay but within 2 kms with less than 10 employees (Q9b1)

/

BGY_ W2LODEST_W99 Number of lodging establishments outside the barangay but within 2 kms with at least 10 but less than 100 employees (Q9b2)

/

BGY_ W2LODEST_W100 Number of lodging establishments outside the barangay but within 2 kms with at least 100 employees (Q9b3)

/

BGY_TLODEST Total number of lodging establishments in the barangay (equal to the sum of Q9a1+Q9a2+Q9a3)

/

BGY_W2TLODEST Total number of lodging establishments outside the barangay but within 2 kms from barangay hall (equal to the sum of Q9b1+Q9b2+Q9b3)

/

BGY_PLODEST_W10 Proportion of lodging establishments in the barangay with less than 10 employees (equal to Q9a1/BGY_TLODEST)

/

BGY_PLODEST_W99 Proportion of lodging establishments in the barangay with at least 10 but less than 100 employees (equal to Q9a2/BGY_TLODEST)

/

BGY_PLODEST_W100 Proportion of lodging establishments in the barangay with at least 100 employees (equal to Q9a3/ BGY_TLODEST)

/

BGY_W2PLODEST_W10 Proportion of lodging establishments outside the barangay but within 2 kms from barangay hall with less than 10 employees (equal to Q9b1/BGY_W2TLODEST)

/

BGY_W2PLODEST_W99 Proportion of lodging establishments outside the barangay but within 2 kms from barangay hall with at least 10 but less than 100 employees (equal to Q9b2/BGY_ W2TLODEST)

/

BGY_W2PLODEST_W100 Proportion of lodging establishments outside the barangay but within 2 kms from barangay hall with at least 100 employees (equal to Q9b3/ BGY_ W2TLODEST)

/

BGY_PREDLODEST

Predominant type (based on employment size) of lodging establishments in the barangay (takes the value 3 (LARGE) if BGY_PLODEST_100 = MAX (BGY_PLODEST_100, BGY_PLODEST_99, BGY_PLODEST_10); takes the value 2 (MEDIUM) if BGY_PLODEST_99 = MAX (BGY_PLODEST_100, BGY_PLODEST_99, BGY_PLODEST_10); takes the value 1 (SMALL) if BGY_PLODEST_10 = MAX (BGY_PLODEST_100, BGY_PLODEST_99, BGY_PLODEST_10);

/



BGY_W2PRLODEST

Predominant type (based on employment size) of lodging establishments outside the barangay but within 2 kms from barangay hall (takes the value 3 (LARGE) if BGY_W2PLODEST_100 = MAX (BGY_ W2PLODEST_100, BGY_ W2PLODEST_99, BGY_ W2PLODEST_10); takes the value 2 (MEDIUM) if BGY_ W2PLODEST_99 = MAX (BGY_ W2PLODEST_100, BGY_ W2PLODEST_99, BGY_ W2PLODEST_10); takes the value 1 (SMALL) if BGY_ W2PLODEST_10 = MAX (BGY_ W2PLODEST_100, BGY_ W2PLODEST_99, BGY_ W2PLODEST_10);

/

BGY_FINEST_W10 Number of financial establishments in the barangay with less than 10 employees (Q10a1)

/

BGY_FINEST_W99 Number of financial establishments in the barangay with at least 10 but less than 100 employees (Q10a2)

/

BGY_FINEST_W100 Number of financial establishments in the barangay with at least 100 employees (Q10a3)

/

BGY_ W2FINEST_W10 Number of financial establishments outside the barangay but within 2 kms with less than 10 employees (Q10b1)

/

BGY_ W2FINEST_W99 Number of financial establishments outside the barangay but within 2 kms with at least 10 but less than 100 employees (Q10b2)

/

BGY_ W2FINEST_W100 Number of financial establishments outside the barangay but within 2 kms with at least 100 employees (Q10b3)

/

BGY_TFINEST Total number of financial establishments in the barangay (equal to the sum of Q10a1+Q10a2+Q10a3)

/

BGY_W2TFINEST Total number of financial establishments outside the barangay but within 2 kms from barangay hall (equal to the sum of Q10b1+Q10b2+Q10b3)

/

BGY_PFINEST_W10 Proportion of financial establishments in the barangay with less than 10 employees (equal to Q10a1/BGY_TFINEST)

/

BGY_PFINEST_W99 Proportion of financial establishments in the barangay with at least 10 but less than 100 employees (equal to Q10a2/BGY_TFINEST)

/

BGY_PFINEST_W100 Proportion of financial establishments in the barangay with at least 100 employees (equal to Q10a3/ BGY_TFINEST)

/

BGY_W2PFINEST_W10 Proportion of financial establishments outside the barangay but within 2 kms from barangay hall with less than 10 employees (equal to Q10b1/BGY_W2TFINEST)

/

BGY_W2PFINEST_W99 Proportion of financial establishments outside the barangay but within 2 kms from barangay hall with at least 10 but less than 100 employees (equal to Q10b2/BGY_ W2TFINEST)

/

BGY_W2PFINEST_W100 Proportion of financial establishments outside the barangay but within 2 kms from barangay hall with at least 100 employees (equal to Q10b3/ BGY_ W2TFINEST)

/

BGY_PREDFINEST

Predominant type (based on employment size) of financial establishments in the barangay (takes the value 3 (LARGE) if BGY_PFINEST_100 = MAX (BGY_PFINEST_100, BGY_PFINEST_99, BGY_PFINEST_10); takes the value 2 (MEDIUM) if BGY_PFINEST_99 = MAX (BGY_PFINEST_100, BGY_PFINEST_99, BGY_PFINEST_10); takes the value 1 (SMALL) if BGY_PFINEST_10 = MAX (BGY_PFINEST_100, BGY_PFINEST_99, BGY_PFINEST_10);

/

BGY_W2PRFINEST

Predominant type (based on employment size) of financial establishments outside the barangay but within 2 kms from barangay hall (takes the value 3 (LARGE) if BGY_W2PFINEST_100 = MAX (BGY_ W2PFINEST_100, BGY_ W2PFINEST_99, BGY_ W2PFINEST_10); takes the value 2 (MEDIUM) if BGY_ W2PFINEST_99 = MAX (BGY_ W2PFINEST_100, BGY_ W2PFINEST_99, BGY_ W2PFINEST_10); takes the value 1 (SMALL) if BGY_ W2PFINEST_10 = MAX (BGY_ W2PFINEST_100, BGY_ W2PFINEST_99, BGY_ W2PFINEST_10);

/

BGY_REPEST_W10 Number of repair establishments in the barangay with less than 10 employees (Q11a1)

/

BGY_REPEST_W99 Number of repair establishments in the barangay with at least 10 but less than 100 employees (Q11a2)

/

BGY_REPEST_W100 Number of repair establishments in the barangay with at least 100 employees (Q11a3)

/

BGY_ W2REPEST_W10 Number of repair establishments outside the barangay but within 2 kms with less than 10 employees (Q11b1)

/

BGY_ W2REPEST_W99 Number of repair establishments outside the barangay but within 2 kms with at least 10 but less than 100 employees (Q11b2)

/



BGY_ W2REPEST_W100 Number of repair establishments outside the barangay but within 2 kms with at least 100 employees (Q11b3)

/

BGY_TREPEST Total number of repair establishments in the barangay (equal to the sum of Q11a1+Q11a2+Q11a3)

/

BGY_W2TREPEST Total number of repair establishments outside the barangay but within 2 kms from barangay hall (equal to the sum of Q11b1+Q11b2+Q11b3)

/

BGY_PREPEST_W10 Proportion of repair establishments in the barangay with less than 10 employees (equal to Q11a1/BGY_TREPEST)

/

BGY_PREPEST_W99 Proportion of repair establishments in the barangay with at least 10 but less than 100 employees (equal to Q11a2/BGY_TREPEST)

/

BGY_PREPEST_W100 Proportion of repair establishments in the barangay with at least 100 employees (equal to Q11a3/ BGY_TREPEST)

/

BGY_W2PREPEST_W10 Proportion of repair establishments outside the barangay but within 2 kms from barangay hall with less than 10 employees (equal to Q11b1/BGY_W2TREPEST)

/

BGY_W2PREPEST_W99 Proportion of repair establishments outside the barangay but within 2 kms from barangay hall with at least 10 but less than 100 employees (equal to Q11b2/BGY_ W2TREPEST)

/

BGY_W2PREPEST_W100 Proportion of repair establishments outside the barangay but within 2 kms from barangay hall with at least 100 employees (equal to Q11b3/ BGY_ W2TREPEST)

/

BGY_PREDREPEST

Predominant type (based on employment size) of repair establishments in the barangay (takes the value 3 (LARGE) if BGY_PREPEST_100 = MAX (BGY_PREPEST_100, BGY_PREPEST_99, BGY_PREPEST_10); takes the value 2 (MEDIUM) if BGY_PREPEST_99 = MAX (BGY_PREPEST_100, BGY_PREPEST_99, BGY_PREPEST_10); takes the value 1 (SMALL) if BGY_PREPEST_10 = MAX (BGY_PREPEST_100, BGY_PREPEST_99, BGY_PREPEST_10);

/

BGY_W2PRREPEST

Predominant type (based on employment size) of repair establishments outside the barangay but within 2 kms from barangay hall (takes the value 3 (LARGE) if BGY_W2PREPEST_100 = MAX (BGY_ W2PREPEST_100, BGY_ W2PREPEST_99, BGY_ W2PREPEST_10); takes the value 2 (MEDIUM) if BGY_ W2PREPEST_99 = MAX (BGY_ W2PREPEST_100, BGY_ W2PREPEST_99, BGY_ W2PREPEST_10); takes the value 1 (SMALL) if BGY_ W2PREPEST_10 = MAX (BGY_ W2PREPEST_100, BGY_ W2PREPEST_99, BGY_ W2PREPEST_10);

/

BGY_SEREST_W10 Number of service establishments in the barangay with less than 10 employees (Q12a1)

/

BGY_SEREST_W99 Number of service establishments in the barangay with at least 10 but less than 100 employees (Q12a2)

/

BGY_SEREST_W100 Number of service establishments in the barangay with at least 100 employees (Q12a3)

/

BGY_ W2SEREST_W10 Number of service establishments outside the barangay but within 2 kms with less than 10 employees (Q12b1)

/

BGY_ W2SEREST_W99 Number of service establishments outside the barangay but within 2 kms with at least 10 but less than 100 employees (Q12b2)

/

BGY_ W2SEREST_W100 Number of service establishments outside the barangay but within 2 kms with at least 100 employees (Q12b3)

/

BGY_TSEREST Total number of service establishments in the barangay (equal to the sum of Q12a1+Q12a2+Q12a3)

/

BGY_W2TSEREST Total number of service establishments outside the barangay but within 2 kms from barangay hall (equal to the sum of Q12b1+Q12b2+Q12b3)

/

BGY_PSEREST_W10 Proportion of service establishments in the barangay with less than 10 employees (equal to Q12a1/BGY_TSEREST)

/

BGY_PSEREST_W99 Proportion of service establishments in the barangay with at least 10 but less than 100 employees (equal to Q12a2/BGY_TSEREST)

/

BGY_PSEREST_W100 Proportion of service establishments in the barangay with at least 100 employees (equal to Q12a3/ BGY_TSEREST)

/

BGY_W2PSEREST_W10 Proportion of service establishments outside the barangay but within 2 kms from barangay hall with less than 10 employees (equal to Q12b1/BGY_W2TSEREST)

/

BGY_W2PSEREST_W99 Proportion of service establishments outside the barangay but within 2 kms from barangay hall with at least 10 but less than 100 employees (equal to Q12b2/BGY_

/



W2TSEREST)

BGY_W2PSEREST_W100 Proportion of service establishments outside the barangay but within 2 kms from barangay hall with at least 100 employees (equal to Q12b3/ BGY_ W2TSEREST)

/

BGY_PREDSEREST

Predominant type (based on employment size) of service establishments in the barangay (takes the value 3 (LARGE) if BGY_PSEREST_100 = MAX (BGY_PSEREST_100, BGY_PSEREST_99, BGY_PSEREST_10); takes the value 2 (MEDIUM) if BGY_PSEREST_99 = MAX (BGY_PSEREST_100, BGY_PSEREST_99, BGY_PSEREST_10); takes the value 1 (SMALL) if BGY_PSEREST_10 = MAX (BGY_PSEREST_100, BGY_PSEREST_99, BGY_PSEREST_10);

/

BGY_W2PRSEREST

Predominant type (based on employment size) of service establishments outside the barangay but within 2 kms from barangay hall (takes the value 3 (LARGE) if BGY_W2PSEREST_100 = MAX (BGY_ W2PSEREST_100, BGY_ W2PSEREST_99, BGY_ W2PSEREST_10); takes the value 2 (MEDIUM) if BGY_ W2PSEREST_99 = MAX (BGY_ W2PSEREST_100, BGY_ W2PSEREST_99, BGY_ W2PSEREST_10); takes the value 1 (SMALL) if BGY_ W2PSEREST_10 = MAX (BGY_ W2PSEREST_100, BGY_ W2PSEREST_99, BGY_ W2PSEREST_10);

/

BGY_NISHDANGER Number of households found as informal settlers in danger areas in the barangay (Q13a)

/

BGY_NISHGOVT Number of households found as informal settlers in government lands in the barangay (Q13b)

/

BGY_NISHPRIV Number of households found as informal settlers in private lands in the barangay (Q13c)

/

BGY_TNISH Total number of households found as informal settlers in the barangay (equal to as the sum of Q13a+Q13b+Q13c)

/

BGY_PISHDANGER Proportion of households found as informal settlers in danger areas in the barangay (Q13a/ BGY_TNISH)

/

BGY_PISHGOVT Proportion of households found as informal settlers in government lands in the barangay (Q13b/ BGY_TNISH)

/

BGY_PISHPRIV Proportion of households found as informal settlers in private lands in the barangay (Q13c/ BGY_TNISH)

/

D. Municipal and City Characteristics


HOU_COELPG Proportion of households that use electricity or lpg for cooking /

HOU_CONST Proportion of houses in the barangay that are under construction /

HOU_DILAP Proportion of houses in the barangay that are condemned/dilapidated /

HOU_LAN_AG1 Proportion of households that own agricultural lands /

HOU_LAN_AG2 Proportion of households that own agricultural lands acquired through CARP

/

HOU_LAN_OTH Proportion of households that own other agricultural lands /

HOU_LAN_RES Proportion of households that own other residential lands /

HOU_LI_ELE Proportion of households that use electricity for lighting /

HOU_NOTOI Proportion of households with no toilet /

HOU_OWN_RAD Proportion of households who have radio /

HOU_OWN_REF Proportion of households who have refrigerator /

HOU_OWN_TEL Proportion of households who have telephone /

HOU_OWN_TV Proportion of households who have TV /

HOU_OWN_VCR Proportion of households who have VCR /

HOU_OWN_VEH Proportion of households who have motorized vehicle /

HOU_OWN_WAS Proportion of households who have washing machine /

HOU_REN Proportion of houses that are rented /



HOU_RENF1 Proportion of houses that are rent-free with consent of owner /

HOU_RENF2 Proportion of houses that are rent-free without consent of owner /

HOU_UNTOI Proportion of households with unsanitory (open pit) toilet /

HOU_WADUNS Proportion of households that use an unsanitary water source for drinking

/

MUN_OCC_CLERKS Average number of members who are clerks in the municipality /

MUN_OCC_FARMERS Average number of members who are farmers, forestry workers and fishermen in the municipality

/

MUN_OCC_LABORERS Average number of members who are laborers and unskilled workers in the municipality

/

MUN_OCC_OFFICIALOFGOVT

Average number of members who are officials of gov't and special interest organizations, corporate executives, managers, managing proprietors and supervisors in the municipality

/

MUN_OCC_PLANT Average number of members who are plant and machine operators and assemblers in the municipality

/

MUN_OCC_PROF Average number of members who are professionals in the municipality /

MUN_OCC_SERVICE Average number of members who are services workers and shop and market sales workers in the municipality

/

MUN_OCC_SPECIAL Average number of members who are special occupations in the municipality

/

MUN_OCC_TECH Average number of members who are technicians and associate professionals in the municipality

/

MUN_OCC_TRADE Average number of members who are trades and related workers in the municipality

/

PER_ENG Proportion of persons 5 and older who speak English /

PER_LIT Proportion of persons 5 and older who can read in some language /

PER_NONPHI Proportion of non-Philippine citizens /

PER_SCH_ABR Proportion of persons ages 5 to 18 who attended school in foreign country

/

PER_SCH_CIT Proportion of persons ages 5 to 18 who attended school in same city/municipality

/

PER_SCHOOL Proportion of persons ages 5 to 18 who attended school from June 99-March 2000

/

PER_TAGA Proportion of persons 5 and older who speak Filipino/Tagalog /

PER_WOR_ABR Proportion of persons who worked overseas /

PER_WOR_GOV Proportion of who worked for private government /

PER_WOR_PRE Proportion of who worked for private establishment /

PER_WOR_PRH Proportion of who worked for private household /

c. Statistical Modelling

This section provides a brief discussion of the regression modelling3 for per capita income.

Since there is limited number of time invariant variables at the household level, the

explanatory variables X is dominated more by the location-effect variables. Recall that the

dependent variable Y is expressed at the household level. To capture a significant amount of

3 The reader is being referred to the NSCB(2005) Estimation of Local Poverty in the Philippines for a more detailed discussion

of multicollinearity, heteroscedasticity and bootstrapping.


variability of Y, it is operationally useful to construct more time-invariant variables. This was

done by computing two-way interactions among variables in X. Interactions of explanatory

variables with urbanity were also computed. These approaches generated more household-

level auxiliary data.

Separate models were fitted for each geographic region. The objective is to tailor the model

to account for the differences of geographic regions in the country, such as spatial

peculiarities. The set of geographic barangays comprise the clusters. Per geographic region,

computing through PovMap begins in the estimation of the income function,

lnYij = E[lnYij | Xij] + uij (1)

where Yij is the per capita income of jth household in ith cluster, X is the explanatory variable

and u is the error component. This error component uij can be attributed into two

components: variability among the clusters and variability among households. Thus, we can

represent uij as,

uij = hi + eij (2)

where hi is the cluster component and eij is the household component. For each region, a

number of candidate models were estimated. As mentioned earlier, estimation of these

models was implemented using PovMap, a software developed by World Bank for this

purpose.

d. Development and Selection of Regional Models

After model estimation and fitting of parameter estimates to census, it is necessary to undo

the log transformation of Y, also implemented through PovMap. The estimated per capita

income is then compared with the set of official provincial poverty thresholds for the years

2006 and 2009 to compute the poverty estimates. These estimates were determined at the

municipal/city, provincial and regional levels. Bootstrapping was undertaken and estimates

were summarized by their mean and standard deviation giving a point estimate and standard

error for the desired level of disaggregation. Bootstrapping is used to provide accurate

estimates of the standard errors. As imputed income depends non-linearly on the stochastic

variables involved (the estimated model parameters, the correlated error terms), computing

the standard errors analytically will be very demanding.

Assessment of candidate models for each region involved comparison of the similarity of (a

subset of) parameter estimates and similarity of small area estimates, in addition to basic

statistical criterion such as adjusted R squares, among others. This approach of assessment


is also useful in identifying over-fitted models, aberrant fluctuations as well as robustly

significant variables. Further, the resulting model-based poverty estimates at the regional

levels were also compared to direct survey estimates.

Selection of a reasonable model for a specific region was done by considering the following

guidelines:

The relationship of the variables, whether positive or negative, on Y is generally

consistent with earlier empirical research results on poverty (e.g. education should have

a positive effect on income).

The models should be robust, which means that small changes to the model do not

greatly affect the significance or signs of the variables.

A model that has an R-square of at least 40% generally possesses a good characteristic

in predicting the independent variable; in this case, the per capita income.

Inclusion of additional independent variables in the model increases the value of the R-

squared. However, the principle of parsimony states that the lower the number of

independent variables, the better the model.

The estimated 2006 and 2009 regional and provincial poverty incidence based on SAE

methodology should not largely differ from the 2006 and 2009 Official Regional and

Provincial Poverty Estimates (i.e., within two standard error away from the official

estimates). Further, ranking of the official provincial estimates within a region should be

preserved, unless provincial estimates are relatively too close that their confidence

intervals will be overlapping, hence, ranking of the provinces may not be significant.

The variables to be included in the model should not be highly correlated with each

other. For example, it is expected that there will be high correlation between the

proportion of household members that completed at least high school education and the

proportion of women that finished at least grade 6/elementary education. In such a case,

only one variable is maintained in the model.

In some instances that the regional models do not reflect the characteristics of a

province, city and/or municipality, the use of provincial dummy variables were done to

capture the unique characteristics of the province and down to the Municipal and City


level. An observation will have the dummy value of 1 if he/she belongs to that province, 0

otherwise. In this case, the dummy variable will help to adjust the model to account for

the unique characteristics of some provinces.

Table 10. Provincial Dummy Variables Included in the Regional Models 2006 and 2009 SAE

Year Province Region

2006

Abra CAR

Eastern Samar and Leyte* VIII

Misamis Occidental X

Zamboanga Del Norte IX

2009

Camarines Sur V

Capiz VI

Eastern Samar VIII

Iloilo VI

La Union I

Lanao Del Sur and Maguindanao* ARMM

Mountain Province CAR

Romblon IV-A

Surigao Del Norte Caraga

Zamboanga Del Norte IX

*dummy equal to 1 if the observation belongs to either of the provinces

In selecting the best possible model, another criterion considered is the number of

municipalities and cities whose estimates have relatively low CVs. As much as possible,

it is desired that municipalities and cities would have CVs not greater than 20 percent.

The following illustrates the criteria followed in the SAE model selection (e.g. the 2006

Modelling Summary of Region IV-A):

Statistics

Model 1

Adjusted R-squared 0.4344

Number of observations 3602

Number of vars (excluding intercept) 6

Variables included

BGY_FAMSIZE -0.0731

HH_KIDS -0.459

MUN_OCC_FARMERS -0.6711

ALL_ATLEASTHH 0.8803

At least 40% R-squared

Non-multicollinear variables


ROOF_STRONG_OLD 0.385

URB 0.1827

Region/ Province

2006 Official Poverty Estimates

2006 Model-based estimate

Model 1

Estimates Coefficient

of Variation (CV)

Standard

Error (SE) 2 sigma

Rank Estimate

Difference with

Official Rank

Region IV-A 12.3 10.5 1.3 2.6 11.77 0.53

Batangas 16.4 15.1 2.5 5 4 14.23 2.17 4

Cavite 6.2 22.2 1.4 2.8 3 6.96 (0.76) 3

Laguna 5.7 19.5 1.1 2.2 2 4.72 0.98 2

Quezon 35.2 13.4 4.7 9.4 5 30.4 4.8 5

Rizal 3.6 24.2 0.9 1.8 1 4.63 (1.03) 1

The following may also be noted:

Since variables used in model-building were limited to those that are considered to

be time-invariant, variables such as household size and number of children were

replaced with proxy indicators such as cluster means (i.e. average household size in

a barangay). These variables, however, were not always significant. In cases that

they are found to be significant, it was noted that these proxy indicators are not able

to capture the dependency variables adequately, which are negatively correlated with

income. Hence, it is expected to over-predict income, resulting to an underestimation

of poverty.

The assumption that the geographic distribution of households (household

characteristics) has been stable over time may have been optimistic. It is possible

that migration, and/or variations in birth and death rates between the poor and non-

poor may have altered the picture.

Consistent

rankings Difference within 2-sigma

Difference within 2-sigma

Correct

signs of the

coefficients

Figure 6. Illustration on Criteria Used for Model Selection


Table 11. Characteristics of the Regional Models.

Region Number of Observations

Adjusted R-square (in percent)

2006 2009 2006 2009

NCR 4,455 4,285 34.1 35.1

CAR 1,536 1,581 50.8 47.3

Region I 2,259 2,277 40.0 35.2

Region II 1,900 1,901 37.9 45.3

Region III 3,114 3,027 40.4 37.7

Region IV-A 3,609 3,661 43.4 40.1

Region IV-B 1,655 1,667 44.6 44.1

Region V 2,250 2,212 48.5 42.6

Region VI 2,716 2,592 42.3 44.5

Region VII 2,503 2,526 47.4 45.6

Region VIII 1,944 2,012 41.8 44.8

Region IX 1,572 1,655 51.0 49.1

Region X 1,724 1,768 42.4 48.1

Region XI 2,029 2,151 49.8 45.7

Region XII 1,923 1,928 40.3 46.9

Caraga 1,644 1,568 40.5 41.2

ARMM 1,649 1,588 30.0 31.9

e. Comparison of Estimates

The 2006 and 2009 Municipal and City level poverty estimates in this report were all

generated using the same ELL methodology developed by World Bank. Regional models

were also developed and used for both 2006 and 2009 to estimate per capita income for

each of the households in the census, which served as reference in the estimation of the

Municipal and City level poverty estimates. Both set of estimates were also generated using

the PovMap software developed by World Bank for the implementation of the ELL technique.

However, it may also be noted that for the estimation of the 2006 Municipal and City level

poverty estimates, this report utilized data from the 2000 Census of Population and Housing

(CPH), which is a census conducted six years prior to the conduct of the 2006 FIES. On the

other hand, the 2009 Municipal and City level poverty estimates were generated using 2007

Census of Population, only two years away from the conduct of the FIES but has limited

variables compared to the 2000 CPH.

Having presented their similarities and differences in analysing the resulting poverty

incidences across the years, which is actually the mean of 100 simulations done in PovMap,

it is important to consider the estimated standard error of the estimates to ensure that

observed increases and decreases are significant. Further, a test of significance of the

difference between two average poverty incidences could be done.

4. Limitations of the Study

a. Data

In the absence of a census, as well as panel data in 2006 and 2009, in which case, survey

household income from 2006 (or 2009) can be linked to X variables in 2000 (or 2007), only

time-invariant variables4 or location effect variables/census means were considered in the

development of the regression models to predict income of households in 2006 and 2009.

As a result, variables such as household size and number of children were replaced with

proxy indicators such as cluster means (i.e., average household size in a barangay). These

variables, however, were not always significant. In cases that they are found to be

significant, it was noted that these proxy indicators are not able to capture the dependency

variables adequately, which is expected to be negatively correlated with income. Hence,

there may be cases that income could be overestimated, resulting to an underestimation of

poverty. Although the 2006 and 2009 estimates may be viewed as comparable but with

careful consideration of their standard errors, one limitation is that the gap between the

survey and census years most especially in the 2006 SAE where there is a 6 year gap

between the 2006 survey data and 2000 census. This could mean that some of the time-

invariant variables may have actually changed given the 6 year difference and compared

with the 2 year difference between the 2007 PopCen and 2009 FIES.

b. Dropped observations in the PovMap process

The PovMap only proceeds if the barangay clusters have at least two observations. A

solution that was made is to filter the data set by keeping the clusters with at least two

observations, causing some observations to be dropped in the modelling process.

4 Time-invariant variables are variables considered to be “stable” over time.


c. Regional model may not necessarily capture the unique characteristics of

provinces/municipalities

As models specified are at the regional level, characteristics of the municipalities and cities

atypical of the province/region may not be fully captured by the model.

1. Region IV-A Although the regional model contains good characteristics, out of the 142 Municipal and

City poverty estimates in Region IV-A, 67municipalities and cities (47%) in 2006 are

considered unreliable having coefficients of variation greater than 20 percent while 47

unreliable municipalities and cities (33%) in 2009 were generated.

2. Masbate

It was observed in the 2009 SAE modelling process that the regional and Masbate

poverty estimate of Region V is outside the allowable 2 standard deviations of the 2009

Official Provincial Poverty Statistics. Almost all of the models yielded in the same result.

While the Project Team recognizes that there may be other variables that are correlated with

income, these, however, were not included in the model developed for the region due to

some constraints (e.g., limited time, data, manpower and financial resources).

C. Validation Workshop 1. Objectives

Similar to the past two poverty mapping projects that the NSCB TS conducted in 2004-2005

and 2006-2008, validation activities on the 2009 city/municipality poverty statistics through a

one-day workshop and ocular assessment in a selected region/province, particularly Region

VIII and the provinces of Leyte and Western Samar, were undertaken. The validation

activities were conducted by the NSCB TS with the participation of representatives from the

World Bank and Australian Government and the two local World Bank Consultants. The

main objective of the validation activities is to assess the acceptability and consistency of the

estimates generated. These exercises were done to evaluate how well the estimates relate

to the assessment of local government units, the academe, civil society organizations, as

well as local communities in the region/province. Specifically, the validation activities aim to:


a. Solicit the workshop participants’ expert opinion and intimate knowledge of the poverty

situation in Leyte and in specific localities through a validation form where participants of

the workshop will assess the status of the municipalities in the province based on

identified poverty indicators;

b. Present the initial results of the Project on the Generation of the 2009 City/Municipal

Poverty Statistics, including some background on the methodology, variables used, and

the statistical tests undertaken;

c. Serve as a forum for the exchange of ideas and discussion of the provincial and

municipal level poverty estimates produced through the project and to evaluate how well

they relate to the assessment of the local participants; and

d. Conduct ocular assessment of the socio-economic, demographic, and housing

characteristics of cities/municipalities vis-à-vis the results of the regional model and

city/municipality poverty estimates in the Region.

2. Mechanics

a. Validation Workshop

Invited workshop participants were composed of:

Provincial key informants with detailed knowledge of all the municipalities in the

province, e.g., provincial planning and development coordinator.

Municipal key informants, e.g., representatives from the municipal planning and

development offices.

In Part I of the validation form, the participants were asked to assess the indicators that

turned out to be significant in the SAE model of Region VIII. Specifically, the participants

were asked to provide their “best” estimate of selected poverty-related characteristics of

households from their respective city/municipality.

The indicators are:

Educational attainment of male and female household members;

Households with a son/daughter of the head


Household members who are working as clerks in the barangay

Household in the barangay is into agriculture

Members of the immediate (nuclear) family

In Part II of the validation form, the participants were asked to provide information on the

average number of poor per 10 persons/individuals residing in their respective

city/municipality and other cities/municipalities where they have some reasonable knowledge

of.

The poverty estimates of the cities/municipalities in the province based on the participants’

scoring were compared with the poverty estimates of cities/municipalities based on the SAE.

b. Ocular Assessment

Ocular assessment was conducted in four municipalities in Leyte and three municipalities in

Western Samar. This was in collaboration with the Municipal Planning and Development

Coordinators (MPDCs) of the sampled cities/municipalities. Members of the Team,

consisting of NSCB TS Directorate and Staff and representatives from the World Bank and

Australian Government, were asked to accomplish an Ocular Assessment Form (See

Section C.4) containing the different variables found to be significant in the regional model.

3. Workshop Design

a. Validation Workshop – held in Palo, Leyte with the following participants:

Participants Leyte

Local Government Units 31

Academe 2

Civil Society Organizations 5

Regional/Provincial Government Agencies 12

Other Participants/Guests 1

TOTAL 51

Number of Municipalities 22

b. Ocular Assessment – conducted in Leyte and Samar of Region VIII

Province/City/Municipality Rationale for choosing the place

1. Leyte

(22 July 2013)

four municipalities

(Palo, Tanauan, Sta. Fe, and Tacloban City)

Cluster 3 in the 2009 Official Poverty Statistics; Representative of a “not very poor” province

Implements Kapit-Bisig Laban sa Kahirapan- Comprehensive and Integrated Delivery of Social Services (KALAHI-CIDDS)

Beneficiary of the Conditional Cash Transfer (CCT) Program (Pantawid Pamilya) of the DSWD


Province/City/Municipality Rationale for choosing the place

2. Western Samar

(23 July 2013)

three municipalities

(Sta. Rita, Pinabacdao, Babatngon)

Cluster 2 in the 2009 Official Poverty Statistics; Representative of a “poor” province

Implements Kapit-Bisig Laban sa Kahirapan- Comprehensive and Integrated Delivery of Social Services (KALAHI-CIDDS)

Beneficiary of the CCT Program (Pantawid Pamilya) of the DSWD

The Team conducted the following activities:

Ocular assessment of community/housing characteristics of sampled barangays in the

cities/municipalities covered

Interviews with the MPDCs, some barangay officials and local residents.

Interviews and courtesy calls with the Mayors of Babatngon, Leyte and Sta. Rita,

Western Samar

Specific observations in the ocular assessment conducted in 7 municipalities in Region VIII:

Province/ Municipality

Ocular Assessment of Community/Housing Characteristics

Leyte

Palo Predominantly non-agricultural households in a barangay Presence of offices (seat of most government offices in Leyte/Region VIII) Presence of elementary schools and high schools Presence of colleges Houses made of strong materials

Tanauan Predominantly non-agricultural households in a barangay Presence of offices and manufacturing plants Presence of elementary schools and high school Absence of colleges/universities Houses predominantly made of strong and mixed materials

Tacloban City Predominantly non-agricultural households in a barangay Presence of offices and private establishments Presence of elementary schools and high school (both public and private) Presence of colleges/universities Houses predominantly made of strong materials

Sta. Fe Predominantly agricultural households in a barangay Presence of offices (seat of most government offices in Leyte/Region VIII) Presence of elementary schools and high schools Absence of colleges/universities Houses made of mixed (strong and weak) and weak materials


Province/ Municipality

Ocular Assessment of Community/Housing Characteristics

Babatngon Predominantly agricultural households in a barangay Absence of offices Presence of elementary schools per barangay Presence of high school Presence of one private school Absence of colleges/universities Houses predominantly made of weak materials

Samar

Sta. Rita Predominantly non-agricultural households in a barangay Absence of offices Presence of elementary schools Presence of high school only in Poblacion Area Absence of colleges/universities Houses predominantly made of weak materials

Pinabacdao Predominantly non-agricultural households in a barangay Absence of offices Presence of elementary schools Presence of high school in at least two barangays sampled Absence of colleges/universities Houses predominantly made of weak materials

Basey Predominantly agricultural households in a barangay Absence of offices Presence of elementary schools Absence of high schools and colleges/universities Houses predominantly made of weak materials

In Leyte, Tacloban City, the capital of the province, and Palo and Tanauan which are

municipalities adjacent to it, have poverty incidences between 20.0 to 30.0 percentage point.

These three localities were predominantly non-agricultural, with schools up to tertiary levels,

and with offices and establishments. In contrast, the municipalities of Sta. Fe and

Babatngon, which are far from Tacloban City compared to Palo and Tanuan, have poverty

incidences above 30.0 percentage points and were predominantly agricultural with at most

high schools.


4. Forms a. Validation Workshop

VALIDATION FORM FOR THE SAE OF POVERTY INCIDENCE IN 2009 Ctrl No. ________ CITY/MUNICIPALITY/PROVINCE BEING ASSESSED: ______________________________________________________ PRINTED NAME OF KEY INFORMANT: ________________________________________________________________ POSITION OF THE KEY INFORMANT: _______________________________________________________________PART I: On the average, FOR EVERY 10 HOUSEHOLDS in your city/municipality, provide your “best” estimate on the number of households possessing the following characteristics in 2009:

INDICATOR ANSWER Ex. Number of household members

working in the government

2 (Note: Answer will range from 0-10)

Number of male household

members who have at least

college education

Number of female household

members who are at least high

school graduates

Number of households with a

son/daughter of the household

head in the household

Number of households who reside

in a barangay with at least 50% of

its at least 10 yrs. old population

are farmers, farm laborers,

fishermen, loggers and forest

product gatherers;

Number of household members

who are working as clerks in the

barangay

Number of members of the

immediate (nuclear) family

PART II: In 2009, on the average, FOR EVERY 10 PERSONS/INDIVIDUALS residing in the following cities/municipalities, provide your “best” estimate on the number of poor persons/individuals. Answers may range from 0 (i.e., not a single person in the city/municipality is poor) to 10 (i.e., all persons in the city/municipality are considered poor). Fill out only the cities/municipalities where you have reasonable knowledge on its poverty situation. Note: Respondent does not necessarily have to provide answers to all cities/municipalities)

Municipality/City ANSWER

Ex. Makati City 1 (Note: Answer will range from 0-10)

Abuyog

Alangalang Albuera Babatngon Barugo Bato Baybay Burauen Calubian Capoocan Carigara Dagami Dulag Hilongos Hindang Inopacan Isabel Jaro Javier (Bugho) Julita Kananga Lapaz Leyte MacArthur Mahaplag Matag-ob Matalom Mayorga Merida Ormoc City Palo Palompon Pastrana San Isidro San Miguel Santa Fe Tabango Tabontabon Tacloban City Tanauan Tolosa Tunga Villaba


b. Ocular Assessment

GENERATION OF 2009 SMALL AREA ESTIMATES OF POVERTY

Ocular Assessment in Leyte/Samar Date: __ July 2012

Observer: ________________________ Province: ________________________ Please check if the following characteristics are present in the sample barangays of the identified municipalities:

Sample

Predominantly non-

agricultural (i.e., non-

farming/non-fishing/non-

forest products gathering)

households in a barangay

Offices Elementary School

High School College/ University

Predominantly composed of housing units

made of strong materials (wall

and roof)

Municipality

Average:

Barangay 1

Barangay 2

Barangay 3

Municipality

Average:

Barangay 1

Barangay 2

Barangay 3

Municipality

Average:

Barangay 1

Barangay 2

Barangay 3

Municipality

Average:

Barangay 1

Barangay 2

Barangay 3

Municipality

Average:

Barangay 1

Barangay 2

Barangay 3


5. Matrix of Findings

Some of the general insights and findings on the validation workshop are as follows:

The participants found the definitions of some indicators being assessed confusing, thus,

requiring further explanations from the Team members.

As the design of the validation form is expected to exhibit memory bias, some

participants encountered difficulties in recalling the situation in 2009.

The results of the accomplished validation forms were presented after the workshop

proper, hence, providing insights/clarifications to the participants on the rankings of

cities/municipalities based on SAE and participants’ own assessment.

In general, the SAE rankings were consistent with the participants’ assessment.

- Of the 27 municipalities in Leyte initially classified as “poor”, 21 are consistent with

SAE rankings.

- Of the 16 municipalities initially classified “less poor”, 10 are consistent with SAE

rankings.


D. Advocacy

1. Dissemination Forum

a. National

A National Dissemination Forum was held on 30 July 2012 at the Crowne Plaza Galleria

Manila. During the forum, the 2009 city and municipal level poverty estimates, as well as the

methodology and variables used, were presented. The forum also served as a venue for the

exchange and discussion of ideas among various stakeholders and users regarding the

small area poverty estimates and methodology.

Some of the important points raised during the forum are:

Demand for more poverty statistics (e.g., barangay SAE of poverty, longer time series of

the SAE of poverty) from users, particularly the National Anti-Poverty Commission

(NAPC);

Need for the statistical community to communicate the statistics they produce (e.g., SAE

of Poverty); and

Computation of the R-squared and coefficient of variation to validate the reliability of the

estimates.

b. Regional

Aside from the national dissemination forum held in Metro Manila, regional dissemination

fora were also conducted to widely disseminate the small area poverty estimates in the

Visayas and Mindanao regions. Two regional fora were held in August 2012 and June 2013.

b.1 Davao City

During the 2012 Annual Conference of the Philippine Statistical Association (PSA) held in

Apo View Hotel, Davao City last 16 August 2012, a Special Forum on the 2009 City and

Municipal Level Estimates of Poverty was simultaneously held. The forum was attended by

users and stakeholders from both national and local government agencies and academic

institutions from various parts of the countries.


Below are the important points raised during the forum:

Clustering is highly appreciated; however, it is not safe to compare ‘Least Poor’ with

‘Poorest’. It was suggested that a more appropriate term be used;

Consider underemployment in the SAE model and stress effect activities (e.g.,

hypothesis testing) in measuring the poverty reduction between 2003 and 2009; and

The SAE of poverty should be mainstreamed, i.e., to lobby for the regular generation of

the estimates using government funds, considering its importance in local-level policy

making and program planning.

b.2 Cebu City

The 2006 and 2009 City and Municipal Level Poverty Statistics were released on 17 June

2013 at Crowne Regency Hotel, Cebu City. It was attended by various government

agencies, local government units and other users and stakeholders from the province of

Cebu and neighboring provinces in Central Visayas.

Below are the important points raised during the forum:

In Region VII, Cebu is not considered an agricultural area. Hence, the criteria or basis for

determining whether a household is poor or not in the region should be clarified. It was

explained that in generating the SAE of poverty, the following were considered: official

definition of poor; and significance of the variables/predictors. It was also noted that the

predicting variables were dependent on the characteristics of the region.

On the documentation of the utilization of the poverty statistics at the national level, the

NSCB Central Office listed the programs and policy uses from national government

agencies, while at the local level, the NSCB Regional Divisions documented the reports

provided by Regional Statistical Coordination Committee (RSCC). However, it was noted

that documenting the actual policy uses of poverty and other related statistics is a

challenge for the government. It was stressed that the government cannot regularly

generate all statistics requested by its stakeholders if it has no intended use on

policies/programs.

Comparing and ranking of the estimates can still be done even if there are different

models for each region. The models are different but the methodology is the same.

Using the standard errors generated, one can compare the estimates.


2. Web article

A Statistically Speaking article “Poverty Reduction: Successful Municipalities”, written by Dr.

Romulo Virola was published on August 2012 in the NSCB website. The article provided

background and results of the 2009 Small Area Estimates of Poverty.

3. Various presentations to various agencies/organizations

Several presentations on the 2006 and 2009 city and municipal level poverty estimates were

also conducted to disseminate the results and methodology, to solicit comments, and to

advocate for support, specifically from policymakers, in order to have the necessary

resources to sustain its regular generation.

a. Monitoring and Evaluation (M&E) Network

In the 2nd M&E Network Forum held on 7 November 2012 at Crowne Plaza Manila Galleria,

the results of the 2009 SAE of Poverty were presented. The forum was participated by a

group of development practitioners from the government, development partner agencies,

academe and civil society organizations.

b. NSCB/UNICEF Forum on Local Level Statistics on Children

The results of the 2009 SAE of Poverty were presented during the NSCB/UNICEF Forum on

Local Level Statistics on Children held last 31 May 2013 at Crowne Plaza Galleria Manila.

Various users and stakeholders of statistics on children attended the said forum.

c. Meeting of the Regional Tripartite Wage and Productivity Board (RTWPB) IX

During the meeting of the RTWPB IX held last 29 April 2013, NSCB IX presented the results

of the 2009 SAE. It was noted that official poverty statistics were used as one of the bases

for the computation of minimum wage in the region.

d. National Nutrition Council (NNC) IX Forum

The 2009 SAE was also presented during a forum conducted by the National Nutrition

Council IX last July 26, 2013 at the Marcian Business Center, Zamboanga City. The forum

was envisioned to increase awareness of the Local Government Officials and other

stakeholders on hunger issues and to generate collective actions in identifying strategies to

mitigate the problem.


E. Lessons Learned

A. On the data/software to be used

1. It was recognized that while programs to prepare the data that were used in previous

SAE exercises can be very useful, it is still very important to review the questionnaire

and data dictionary of the surveys/census to ensure that variables or questions are

still the same. It may happen that changes result in microdata of a recent

surveys/census, such as the generation of new categories.

2. In addition to considering the coefficient of variation as a means of checking whether

the trends observed are real, it is also useful to conduct test of significant difference

between the estimates generated for 2003 and 2006, 2006 and 2009, and 2003 and

2009. For this Report, this was conducted to check if the increase/decrease in

poverty incidence among cities/municipalities for the years covered are significant/not

significant.

3. It can also be very useful if there will be some technical support from the group that

developed PovMap can easily help out whenever there are problems experienced in

processing the data.

4. There is a need to improve the design of the validation workshop to ensure that the

potential information that could be derived from the exercise will be maximized.

5. The result of the validation workshop usually reflects the statistical development of

the LGUs. Hence, it is important that statistical appreciation among LGUs is

developed.


Annex F

2006 and 2009 Municipal and City Level

Poverty Estimates


Municipal and City Level Small Area Poverty Estimates; 2006 and 2009

Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

NCR 1st district Tondo 4.1 2.9 0.5 0.8 12.6 27.5 3.3 5.0 1.6 4.2

Binondo 1.8 1.0 0.3 0.7 18.1 68.0 1.2 2.3 0.0 2.2

Quiapo 5.3 2.1 0.4 0.9 7.9 42.4 4.6 6.0 0.6 3.5

San Nicolas 4.9 2.4 0.5 1.4 9.6 57.0 4.1 5.7 0.1 4.7

Santa Cruz 4.3 1.7 0.6 0.5 14.3 32.5 3.3 5.3 0.8 2.5

Sampaloc 5.8 1.3 0.7 0.3 11.9 23.6 4.7 6.9 0.8 1.8

San Miguel 3.1 1.4 1.5 0.9 47.2 67.4 0.7 5.5 0.0 2.9

Ermita 4.4 1.5 2.5 1.0 56.4 68.7 0.3 8.5 0.0 3.1

Intramuros 3.0 2.5 0.6 1.2 20.9 48.0 2.0 4.1 0.5 4.5

Malate 6.4 1.8 0.6 0.5 8.9 29.1 5.5 7.3 0.9 2.6

Paco 6.0 1.8 0.4 0.6 5.8 31.3 5.5 6.6 0.9 2.8

Pandacan 6.0 1.9 0.5 0.6 7.8 33.0 5.2 6.8 0.9 2.9

Port Area 13.2 11.9 2.0 6.8 15.2 57.5 9.9 16.5 0.6 23.1

Santa Ana 4.7 2.2 0.8 0.6 17.8 29.0 3.3 6.0 1.1 3.2

2nd district Mandaluyong City 6.1 1.8 1.1 0.8 17.6 45.1 4.3 7.9 0.5 3.2

Marikina City 6.0 2.2 0.7 0.9 11.9 41.1 4.9 7.2 0.7 3.8

Pasig City 5.0 2.2 0.5 0.8 9.5 37.3 4.2 5.7 0.9 3.5

Quezon City 4.1 2.4 0.7 0.6 16.0 25.3 3.0 5.1 1.4 3.4

San Juan 2.9 1.5 2.0 0.6 67.0 42.5 0.0 6.2 0.4 2.5

3rd district Kalookan City 5.0 3.1 1.0 0.9 19.1 28.2 3.5 6.6 1.7 4.5

Malabon 6.1 4.0 1.0 1.7 15.8 41.4 4.5 7.7 1.3 6.7

Navotas 6.2 3.8 1.4 1.8 22.6 48.4 3.9 8.6 0.8 6.8

Valenzuela City 5.1 3.7 1.1 1.3 21.1 33.4 3.3 6.9 1.7 5.8

4th district Las Piñas City 3.9 2.8 1.0 1.0 25.5 37.8 2.3 5.5 1.0 4.5

Makati City 2.9 1.4 0.6 0.6 20.5 42.3 1.9 3.9 0.4 2.3

Muntinlupa City 4.9 2.4 1.0 1.2 20.3 49.6 3.3 6.5 0.4 4.4

Parañaque City 5.5 2.0 0.5 1.0 8.6 41.9 4.7 6.2 0.4 3.6

Pasay City 5.3 1.7 0.6 0.5 11.0 26.4 4.3 6.2 1.0 2.5

Pateros 8.2 3.0 2.2 1.9 27.3 64.9 4.5 11.9 0.0 6.2

Taguig 4.3 2.7 0.8 1.1 19.3 41.5 2.9 5.6 0.8 4.5

CAR Abra Bangued 16.6 16.8 3.4 2.1 26.9 12.7 10.9 22.2 13.2 20.3

Boliney 76.0 50.6 9.2 9.5 22.9 18.9 60.9 91.1 34.9 66.2

Bucay 42.6 36.2 6.4 5.8 22.1 16.1 32.2 53.1 26.6 45.8

Bucloc 58.0 77.2 9.5 10.1 26.4 13.0 42.5 73.6 60.6 93.7

Daguioman 46.8 32.2 10.5 8.8 32.4 27.3 29.4 64.1 17.7 46.6

Danglas 40.2 32.0 6.5 7.3 25.5 22.8 29.4 51.0 20.0 44.0

Dolores 23.7 33.5 5.1 5.0 28.7 15.0 15.3 32.1 25.2 41.7

La Paz 37.6 36.0 6.8 5.4 25.4 14.9 26.4 48.7 27.1 44.8

Lacub 58.8 67.2 8.2 9.5 22.5 14.2 45.3 72.4 51.6 82.9

Lagangilang 30.1 27.5 6.1 4.5 27.9 16.5 20.1 40.1 20.0 34.9

Lagayan 35.0 41.4 8.5 7.8 34.3 18.8 21.0 48.9 28.6 54.3

Langiden 44.1 46.0 8.8 8.1 29.8 17.6 29.7 58.5 32.7 59.4

Licuan-Baay (Licuan) 39.7 46.7 8.0 8.4 26.5 18.0 26.6 52.7 32.9 60.5

Luba 50.5 36.2 8.4 6.7 26.3 18.5 36.6 64.4 25.2 47.2

Malibcong 48.9 55.6 6.8 8.8 20.2 15.8 37.6 60.1 41.1 70.0

Manabo 33.3 34.9 6.7 6.9 29.6 19.8 22.2 44.4 23.5 46.3

Peñarrubia 29.6 35.7 7.6 7.0 33.7 19.6 17.0 42.2 24.2 47.2

Pidigan 22.7 25.9 5.7 4.9 32.9 18.9 13.3 32.1 17.8 33.9

Pilar 41.0 42.8 6.8 6.2 23.0 14.4 29.8 52.2 32.7 53.0

Sallapadan 25.5 62.0 6.0 8.2 31.3 13.2 15.7 35.3 48.6 75.4

San Isidro 50.8 42.3 7.0 6.7 21.3 15.9 39.2 62.3 31.3 53.4

San Juan 40.2 33.7 6.4 6.6 23.0 19.7 29.6 50.7 22.8 44.6

San Quintin 21.0 28.7 6.8 6.7 41.0 23.3 9.8 32.2 17.7 39.7

Tayum 23.4 23.7 5.7 4.4 32.6 18.7 14.1 32.8 16.4 31.0

Tineg 62.9 43.2 7.5 8.6 20.4 19.9 50.5 75.2 29.1 57.4

Tubo 53.3 56.4 8.3 9.4 23.3 16.6 39.7 67.0 41.0 71.7

Villaviciosa 49.7 49.1 8.3 7.7 25.2 15.7 36.0 63.3 36.4 61.8

90% Confidence Interval

ProvinceRegion

Poverty Incidence Standard Error

Municipality/City

Coefficient of Variation

200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Benguet Atok 7.6 39.7 3.0 9.9 51.4 24.9 2.6 12.5 23.4 56.0

Baguio City 1.2 2.4 0.5 0.8 55.6 31.3 0.4 2.1 1.2 3.7

Bakun 17.0 53.7 4.8 9.6 38.5 17.9 9.2 24.8 37.9 69.4

Bokod 5.1 21.5 2.2 4.8 59.3 22.4 1.5 8.8 13.6 29.5

Buguias 6.4 42.0 2.5 8.1 50.0 19.2 2.4 10.5 28.7 55.2

Itogon 5.8 8.9 2.3 2.6 52.9 29.0 2.0 9.6 4.7 13.2

Kabayan 18.0 58.6 5.1 7.3 37.7 12.5 9.7 26.3 46.6 70.7

Kapangan 25.9 37.7 5.6 6.6 27.9 17.5 16.7 35.0 26.8 48.5

Kibungan 22.3 67.9 5.6 11.3 32.5 16.7 13.1 31.6 49.3 86.5

La Trinidad 1.6 5.4 0.7 1.5 56.5 27.3 0.4 2.8 3.0 7.9

Mankayan 6.6 16.5 2.3 4.3 46.6 26.2 2.8 10.3 9.4 23.5

Sablan 14.1 19.3 3.8 5.4 32.7 27.7 7.9 20.3 10.5 28.1

Tuba 6.4 14.2 2.1 3.2 40.7 22.7 3.0 9.9 8.9 19.5

Tublay 11.3 30.4 3.5 6.9 39.3 22.7 5.6 16.9 19.1 41.8

Ifugao Banaue 29.3 20.9 4.9 3.4 22.4 16.3 21.4 37.3 15.3 26.5

Hungduan 43.9 29.9 7.1 5.8 23.0 19.3 32.1 55.6 20.4 39.4

Kiangan 20.6 22.9 3.9 5.0 24.7 21.9 14.2 26.9 14.6 31.1

Lagawe 27.4 19.9 3.2 3.5 15.1 17.4 22.2 32.6 14.2 25.5

Lamut 20.4 18.2 3.2 3.3 20.0 18.3 15.1 25.7 12.7 23.7

Mayoyao 38.5 34.1 4.8 4.1 18.0 11.9 30.6 46.4 27.4 40.8

Alfonso Lista (Potia) 30.6 37.1 4.3 4.5 19.1 12.2 23.5 37.6 29.6 44.5

Aguinaldo 42.2 33.2 5.8 6.0 19.3 18.1 32.7 51.8 23.3 43.0

Hingyon 25.4 25.2 5.2 5.7 26.5 22.7 16.9 33.9 15.8 34.7

Tinoc 52.0 49.6 7.5 7.5 21.8 15.0 39.7 64.4 37.3 61.9

Asipulo 55.0 47.5 7.8 9.3 22.2 19.5 42.3 67.8 32.2 62.8

Kalinga Balbalan 35.4 30.1 5.8 5.7 22.3 19.1 26.0 44.9 20.6 39.5

Lubuagan 35.6 24.8 5.7 5.3 21.7 21.2 26.2 45.0 16.1 33.5

Pasil 44.8 26.5 6.5 4.5 22.0 16.9 34.1 55.5 19.2 33.9

Pinukpuk 33.9 29.9 5.1 4.3 20.4 14.5 25.5 42.2 22.8 37.0

Rizal (Liwan) 28.0 25.3 5.2 5.4 24.8 21.2 19.5 36.5 16.5 34.1

Tabuk 18.1 17.3 3.2 2.8 22.3 16.3 12.9 23.3 12.7 22.0

Tanudan 66.6 30.7 8.6 6.1 21.5 20.0 52.5 80.7 20.6 40.7

Tinglayan 72.0 34.1 9.5 5.3 24.8 15.5 56.4 87.7 25.4 42.7

Mountain Province Barlig 20.2 27.4 4.6 8.3 33.7 30.4 12.6 27.8 13.7 41.1

Bauko 13.4 34.4 2.8 7.8 28.4 22.7 8.7 18.0 21.6 47.2

Besao 19.2 26.9 4.2 7.7 29.9 28.7 12.3 26.0 14.2 39.6

Bontoc 15.1 16.7 5.1 4.9 41.6 29.4 6.6 23.5 8.6 24.8

Natonin 59.2 37.4 9.5 9.2 25.4 24.5 43.6 74.7 22.4 52.5

Paracelis 43.1 46.7 5.5 10.0 17.5 21.4 34.1 52.0 30.3 63.2

Sabangan 11.4 26.0 3.0 8.1 36.3 31.1 6.5 16.2 12.7 39.4

Sadanga 55.1 39.0 8.2 10.9 23.2 27.8 41.5 68.6 21.2 56.9

Sagada 11.2 35.4 2.5 9.0 29.1 25.4 7.1 15.3 20.6 50.2

Tadian 23.9 36.2 3.9 7.2 23.5 20.0 17.4 30.3 24.3 48.0

Apayao Calanasan (Bayag) 34.6 32.9 7.5 7.0 29.2 21.4 22.2 47.0 21.3 44.4

Conner 35.1 30.3 5.4 4.6 20.0 15.2 26.3 43.9 22.7 37.8

Flora 23.0 26.2 4.5 5.3 24.9 20.1 15.7 30.4 17.6 34.9

Kabugao 39.2 40.6 5.6 5.3 19.9 13.0 30.0 48.4 31.9 49.2

Luna 16.8 28.8 3.0 4.7 22.4 16.4 11.9 21.7 21.0 36.5

Pudtol 26.1 29.8 4.0 5.5 19.2 18.3 19.5 32.6 20.8 38.7

Santa Marcela 18.2 23.8 3.9 4.9 27.4 20.7 11.9 24.6 15.7 31.9

Region I Ilocos Norte Adams 39.9 29.4 0.4 1.1 33.3 8.5 39.2 40.6 27.6 31.3

Bacarra 11.7 13.2 0.5 2.3 16.4 11.7 10.9 12.5 9.4 17.0

Badoc 19.6 19.6 0.5 1.4 11.5 11.3 18.8 20.3 17.2 21.9

Bangui 24.5 12.6 0.4 2.1 12.0 13.6 23.8 25.2 9.2 16.0

Batac 11.2 15.3 0.4 1.6 15.4 9.6 10.6 11.7 12.6 17.9

Burgos 27.6 16.8 3.5 5.3 12.7 23.5 21.8 33.4 8.1 25.6

Carasi 26.4 22.6 8.0 1.3 30.1 8.7 13.3 39.5 20.4 24.8


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Currimao 21.5 15.2 2.4 2.1 11.1 13.1 17.6 25.5 11.7 18.7

Dingras 19.5 16.3 2.2 2.6 11.4 9.8 15.8 23.1 11.9 20.6

Dumalneg 31.6 21.6 11.7 5.7 37.0 26.3 12.3 50.8 12.3 30.9

Banna 21.8 17.8 2.3 2.2 10.7 12.2 17.9 25.6 14.2 21.4

Laoag City 6.5 9.9 1.2 0.8 18.8 8.2 4.5 8.5 8.6 11.2

Marcos 27.8 18.7 3.7 2.0 13.1 10.9 21.8 33.8 15.4 22.0

Nueva Era 37.7 24.9 4.7 2.7 12.5 10.7 29.9 45.5 20.5 29.3

Pagudpud 29.6 20.2 3.1 1.3 10.3 6.3 24.6 34.6 18.1 22.3

Paoay 12.2 14.9 2.2 1.2 17.6 7.9 8.7 15.7 12.9 16.8

Pasuquin 22.2 14.1 2.5 1.6 11.2 11.4 18.1 26.3 11.5 16.7

Piddig 20.6 16.3 2.1 2.6 10.2 16.1 17.1 24.0 12.0 20.6

Pinili 21.9 17.6 2.6 2.3 11.7 13.0 17.6 26.1 13.9 21.4

San Nicolas 7.3 12.3 1.8 1.1 24.0 9.2 4.4 10.2 10.4 14.1

Sarrat 20.2 14.0 2.6 1.9 13.0 13.5 15.9 24.5 10.9 17.1

Solsona 21.6 15.0 2.5 1.3 11.4 8.7 17.6 25.7 12.8 17.1

Vintar 18.7 16.8 2.1 2.0 11.0 12.0 15.3 22.1 13.5 20.1

Ilocos Sur Alilem 37.5 27.4 5.8 2.4 15.5 8.6 28.0 47.1 23.5 31.3

Banayoyo 19.2 20.9 3.2 2.6 16.9 12.6 13.8 24.5 16.6 25.2

Bantay 13.2 16.4 2.4 1.9 18.4 11.3 9.2 17.1 13.4 19.5

Burgos 26.4 26.5 2.6 3.2 9.9 12.2 22.1 30.7 21.2 31.8

Cabugao 23.5 20.7 2.2 2.4 9.2 11.4 19.9 27.0 16.8 24.5

Candon City 17.5 17.8 2.2 2.0 12.6 11.0 13.9 21.1 14.5 21.0

Caoayan 12.5 14.4 2.1 1.4 17.1 9.9 9.0 16.0 12.0 16.7

Cervantes 38.2 24.5 5.1 3.6 13.2 14.6 29.9 46.5 18.6 30.3

Galimuyod 33.5 20.6 3.7 2.8 11.0 13.8 27.4 39.6 15.9 25.2

Gregorio del Pilar 29.3 26.1 6.2 3.4 21.0 13.1 19.2 39.5 20.5 31.7

Lidlidda 21.6 17.3 3.6 3.4 16.4 19.9 15.8 27.5 11.6 22.9

Magsingal 18.9 18.1 2.7 2.5 14.4 13.9 14.4 23.3 14.0 22.3

Nagbukel 26.0 28.4 4.4 4.6 16.7 16.0 18.9 33.2 20.9 35.9

Narvacan 17.2 17.7 2.0 1.9 11.7 11.0 13.9 20.6 14.5 20.9

Quirino 35.8 27.2 5.8 4.3 16.2 15.8 26.3 45.3 20.1 34.2

Salcedo 30.8 22.7 3.8 2.8 12.2 12.5 24.6 36.9 18.0 27.4

San Emilio 33.8 23.7 4.9 4.7 14.6 19.9 25.6 41.9 15.9 31.4

San Esteban 19.0 15.7 3.7 2.9 19.6 18.6 12.8 25.1 10.9 20.5

San Ildefonso 16.8 15.4 2.7 2.4 15.9 15.4 12.4 21.2 11.5 19.3

San Juan 13.9 18.0 2.3 2.3 16.7 12.8 10.1 17.7 14.2 21.8

San Vicente 10.7 12.9 2.7 2.8 24.8 21.5 6.3 15.1 8.4 17.5

Santa 20.0 13.6 2.4 2.3 12.0 16.9 16.1 24.0 9.8 17.4

Santa Catalina 6.3 11.7 2.2 2.3 35.2 19.6 2.6 9.9 7.9 15.5

Santa Cruz 33.2 24.0 2.3 2.3 7.0 9.7 29.4 37.1 20.2 27.8

Santa Lucia 21.8 25.1 2.3 2.8 10.6 11.2 18.0 25.6 20.5 29.8

Santa Maria 17.2 16.9 2.2 2.1 13.0 12.7 13.5 20.9 13.4 20.4

Santiago 24.0 20.9 2.7 2.4 11.1 11.4 19.6 28.3 17.0 24.8

Santo Domingo 17.1 16.4 2.0 2.0 11.5 12.3 13.9 20.3 13.1 19.7

Sigay 36.2 27.2 7.5 5.5 20.7 20.1 23.8 48.5 18.2 36.1

Sinait 16.7 18.7 2.6 2.5 15.5 13.2 12.5 21.0 14.6 22.7

Sugpon 51.7 35.4 7.2 7.4 14.0 20.9 39.8 63.6 23.2 47.6

Suyo 39.8 24.4 5.3 4.4 13.2 18.1 31.2 48.5 17.1 31.7

Tagudin 23.7 20.6 2.1 1.9 8.9 9.3 20.2 27.1 17.4 23.7

Vigan City 6.9 12.4 1.6 1.6 23.2 12.9 4.3 9.5 9.8 15.1

La Union Agoo 23.2 21.3 2.0 2.2 8.8 10.3 19.8 26.5 17.7 24.9

Aringay 32.9 26.0 3.2 3.5 9.6 13.4 27.7 38.0 20.3 31.7

Bacnotan 18.6 21.1 1.9 1.8 10.3 8.4 15.4 21.7 18.2 24.0

Bagulin 49.5 35.1 5.5 3.6 11.2 10.2 40.3 58.6 29.2 41.0

Balaoan 27.8 26.6 3.0 2.2 10.6 8.2 23.0 32.7 23.0 30.2

Bangar 27.3 27.9 2.3 3.3 8.3 11.9 23.5 31.0 22.4 33.4

Bauang 20.5 20.3 2.0 2.2 9.9 10.7 17.1 23.8 16.8 23.9


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Burgos 40.8 26.2 5.1 2.8 12.5 10.6 32.4 49.2 21.6 30.8

Caba 29.6 25.2 3.5 1.8 11.7 7.2 23.9 35.3 22.2 28.2

Luna 23.5 24.7 2.1 2.9 8.8 11.8 20.1 26.9 19.9 29.5

Naguilian 27.0 21.9 2.4 2.8 9.0 12.9 23.0 31.0 17.3 26.5

Pugo 27.6 27.4 3.4 2.6 12.2 9.4 22.1 33.2 23.1 31.6

Rosario 26.0 24.8 2.1 3.6 8.2 14.4 22.5 29.5 18.9 30.6

San Fernando City 14.4 15.0 1.7 1.3 11.7 8.9 11.6 17.2 12.8 17.1

San Gabriel 39.9 29.7 4.0 4.0 10.0 13.6 33.3 46.5 23.0 36.3

San Juan 25.6 22.7 2.3 2.8 9.1 12.3 21.8 29.4 18.1 27.3

Santo Tomas 33.4 22.7 3.2 1.4 9.7 6.3 28.1 38.7 20.4 25.0

Santol 39.7 32.7 5.1 3.2 12.8 9.8 31.3 48.0 27.4 38.0

Sudipen 33.1 25.8 3.5 3.6 10.4 14.0 27.4 38.8 19.9 31.8

Tubao 31.4 26.2 3.4 3.5 10.8 13.3 25.8 37.0 20.5 32.0

Pangasinan Agno 32.1 28.4 2.9 3.3 9.0 11.5 27.3 36.9 23.0 33.7

Aguilar 31.1 26.0 3.1 2.1 9.9 8.1 26.0 36.1 22.5 29.4

Alaminos City 24.8 19.9 2.2 2.0 8.8 10.1 21.2 28.4 16.6 23.2

Alcala 24.4 20.3 2.8 1.5 11.5 7.5 19.7 29.0 17.8 22.8

Anda 31.6 25.9 3.2 2.1 10.0 8.0 26.4 36.8 22.5 29.3

Asungan 22.2 20.4 2.6 2.0 11.5 10.0 18.0 26.4 17.0 23.7

Balungo 31.7 21.4 3.5 2.1 11.1 10.0 25.9 37.5 17.9 24.9

Bani 29.9 21.0 2.8 1.1 9.4 5.3 25.2 34.5 19.1 22.8

Basista 29.9 24.6 4.1 1.2 13.6 5.0 23.2 36.6 22.6 26.6

Bautista 30.1 23.4 3.6 2.2 11.8 9.4 24.2 35.9 19.8 27.0

Bayambang 27.4 24.2 2.0 1.9 7.1 7.9 24.2 30.6 21.0 27.3

Binalonan 17.3 14.8 2.0 1.4 11.6 9.7 14.0 20.6 12.4 17.2

Binmaley 22.7 17.5 2.0 1.7 8.8 9.6 19.4 26.0 14.8 20.3

Bolinao 35.7 28.7 3.0 2.8 8.4 9.7 30.7 40.6 24.1 33.2

Bugallon 30.1 24.8 2.9 1.9 9.5 7.6 25.4 34.8 21.6 27.9

Burgos 33.5 28.7 3.4 2.8 10.1 9.8 27.9 39.0 24.1 33.3

Calasiao 23.1 17.2 2.5 1.9 10.7 11.1 19.0 27.1 14.1 20.4

Dagupan City 15.7 13.9 2.5 1.0 15.9 7.0 11.6 19.8 12.3 15.5

Dasol 31.0 25.3 3.1 2.4 9.9 9.6 26.0 36.0 21.3 29.3

Infanta 39.0 24.0 3.8 2.6 9.8 11.0 32.7 45.3 19.6 28.3

Labrador 31.7 18.6 3.9 1.8 12.2 9.9 25.3 38.0 15.5 21.6

Lingayen 24.0 18.3 2.6 1.1 11.0 5.8 19.6 28.3 16.6 20.1

Mabini 40.3 21.5 3.6 1.6 8.8 7.6 34.5 46.2 18.8 24.2

Malasiqui 28.2 24.5 2.0 1.5 7.2 6.3 24.9 31.6 21.9 27.0

Manaoag 22.4 22.3 2.3 2.5 10.4 11.2 18.5 26.2 18.2 26.4

Mangaldan 22.7 17.8 2.2 1.3 9.7 7.0 19.1 26.3 15.8 19.9

Mangatarem 30.8 25.5 1.9 2.0 6.0 8.0 27.7 33.8 22.2 28.8

Mapandan 23.8 21.3 3.2 2.1 13.4 10.0 18.6 29.0 17.8 24.8

Natividad 19.9 21.5 2.8 2.8 14.1 12.8 15.3 24.5 17.0 26.1

Possorubio 24.3 20.0 2.1 1.4 8.7 7.2 20.8 27.8 17.6 22.3

Rosales 26.4 17.9 2.2 1.9 8.2 10.4 22.8 30.0 14.8 21.0

San Carlos City 29.5 26.4 1.8 1.9 6.2 7.3 26.5 32.5 23.2 29.6

San Fabian 32.8 22.1 2.5 2.3 7.5 10.3 28.7 36.8 18.3 25.8

San Jacinto 24.2 21.1 2.8 2.6 11.6 12.3 19.5 28.8 16.9 25.4

San Manuel 28.2 21.3 3.3 2.1 11.7 10.0 22.8 33.6 17.8 24.8

San Nicolas 25.3 18.9 2.1 1.2 8.3 6.6 21.9 28.8 16.8 20.9

San Quintin 26.0 20.5 2.9 2.3 11.3 11.2 21.2 30.8 16.7 24.3

Santa Barbara 28.2 20.4 2.4 2.1 8.4 10.2 24.3 32.1 16.9 23.8

Santa Maria 24.2 18.3 2.6 2.5 10.5 13.8 20.0 28.4 14.1 22.4

Santo Tomas 22.8 17.5 3.7 1.2 16.3 6.6 16.7 29.0 15.6 19.4

Sison 29.2 18.9 2.7 1.7 9.1 8.8 24.8 33.5 16.1 21.6

Sual 36.7 26.7 3.2 1.3 8.8 4.9 31.4 42.0 24.5 28.9

Tayug 15.5 16.4 2.6 1.2 16.9 7.3 11.2 19.8 14.5 18.4

Umingan 38.5 22.9 2.5 2.2 6.5 9.6 34.3 42.6 19.3 26.5


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Urbiztondo 33.2 31.7 3.1 3.0 9.3 9.6 28.1 38.3 26.7 36.7

Urdaneta City 18.9 14.4 2.1 1.2 11.1 8.4 15.5 22.4 12.4 16.3

Villasis 19.4 17.0 2.7 1.7 14.0 9.8 14.9 23.8 14.3 19.7

Laoac 26.5 21.0 2.7 1.2 10.0 5.9 22.1 30.9 19.0 23.0

Region II Batanes Basco 4.1 5.1 2.0 1.9 49.4 36.8 0.8 7.4 2.0 8.2

Itbayat 18.2 12.6 6.4 4.2 35.0 33.4 7.7 28.6 5.7 19.5

Ivana 21.9 8.9 12.0 3.8 54.8 42.2 2.1 41.7 2.7 15.1

Mahatao 13.5 8.9 4.7 3.8 34.6 42.8 5.8 21.2 2.6 15.1

Sabtang 10.0 11.4 5.0 3.9 50.0 33.8 1.8 18.2 5.1 17.8

Uyugan 6.0 8.1 3.2 3.2 54.3 39.6 0.6 11.3 2.8 13.3

Cagayan Abulog 18.0 21.6 3.2 2.6 17.6 12.1 12.8 23.2 17.3 25.9

Alcala 22.3 21.8 2.2 2.3 9.7 10.4 18.7 25.9 18.1 25.5

Allacapan 23.8 21.2 3.9 2.6 16.1 12.4 17.5 30.2 16.9 25.5

Amulung 36.7 27.9 4.2 2.1 11.5 7.5 29.8 43.7 24.4 31.3

Aparri 17.1 15.4 2.9 1.7 17.1 11.2 12.3 21.9 12.6 18.3

Baggao 30.0 22.6 2.5 1.9 8.3 8.6 25.9 34.1 19.4 25.8

Ballesteros 16.7 22.7 2.6 2.5 15.8 11.1 12.4 21.1 18.5 26.9

Buguey 20.8 22.4 2.6 2.3 12.4 10.2 16.6 25.0 18.6 26.1

Calayan 24.2 27.7 4.8 4.1 19.7 14.9 16.4 32.1 20.9 34.4

Camalaniugan 19.5 16.9 2.7 1.9 13.9 11.5 15.0 24.0 13.7 20.1

Claveria 10.8 15.1 2.1 1.8 19.3 12.1 7.3 14.2 12.1 18.1

Enrile 24.8 19.8 3.4 2.3 13.8 11.5 19.2 30.5 16.0 23.5

Gattaran 24.6 19.2 2.3 1.9 9.5 9.9 20.7 28.4 16.1 22.4

Gonzaga 19.9 16.6 3.0 2.4 15.2 14.5 14.9 24.9 12.6 20.6

Iguig 22.3 19.5 3.7 2.3 16.4 11.7 16.3 28.3 15.8 23.3

Lal-lo 15.3 16.7 2.5 2.2 16.1 13.1 11.2 19.3 13.1 20.3

Lasam 18.5 18.2 2.2 2.2 12.1 11.8 14.8 22.2 14.7 21.8

Pamplona 19.7 20.7 3.5 2.6 17.9 12.4 13.9 25.5 16.4 24.9

Penablanca 24.5 18.2 4.0 2.4 16.1 13.0 18.0 31.0 14.3 22.1

Piat 29.3 22.5 4.0 2.8 13.7 12.5 22.7 35.8 17.9 27.1

Rizal 28.1 26.1 3.3 2.8 11.8 10.9 22.7 33.5 21.5 30.8

Sanchez-Mira 12.8 13.4 2.3 2.2 18.0 16.6 9.0 16.6 9.8 17.1

Santa Ana 14.7 16.3 3.7 2.7 25.4 16.2 8.6 20.9 12.0 20.7

Santa Praxedes 12.2 17.2 3.6 3.7 29.8 21.4 6.2 18.2 11.1 23.2

Santa Teresita 18.6 18.6 3.0 3.1 16.3 16.5 13.6 23.6 13.6 23.7

Santo Nino 28.0 26.3 3.4 3.0 12.1 11.2 22.4 33.6 21.5 31.2

Solana 32.8 22.5 3.8 2.0 11.5 8.8 26.6 39.0 19.3 25.8

Tuao 32.3 22.7 4.0 2.3 12.4 10.2 25.7 38.9 18.9 26.5

Tuguegarao City 7.7 8.5 2.1 1.1 27.0 12.9 4.3 11.1 6.7 10.3

Isabela Alicia 18.3 17.2 2.0 2.0 11.1 11.8 15.0 21.6 13.8 20.5

Angadanan 26.9 18.9 3.0 1.8 11.1 9.4 22.0 31.9 16.0 21.8

Aurora 15.9 16.4 2.3 1.9 14.2 11.9 12.1 19.6 13.2 19.6

Benito Soliven 32.0 25.4 5.0 2.9 15.5 11.3 23.9 40.2 20.7 30.1

Burgos 19.1 18.2 3.0 3.3 15.7 18.1 14.1 24.0 12.8 23.6

Cabagan 22.9 16.6 3.1 1.8 13.6 11.0 17.8 28.0 13.6 19.5

Cabatuan 13.7 12.7 2.1 2.1 15.5 16.8 10.2 17.2 9.2 16.3

Cauayan City 16.8 15.9 1.9 1.5 11.4 9.6 13.7 20.0 13.4 18.4

Cordon 20.4 16.3 2.6 2.0 12.5 12.4 16.2 24.6 13.0 19.6

Dinapigue 13.6 13.8 5.3 4.9 39.2 35.3 4.8 22.3 5.8 21.7

Divilican 25.3 23.6 6.8 4.1 26.7 17.4 14.2 36.4 16.8 30.3

Echague 20.4 15.2 1.9 1.4 9.1 9.2 17.3 23.4 12.9 17.5

Gamu 14.8 14.8 2.7 2.6 18.1 17.7 10.4 19.2 10.5 19.1

Ilagan 21.6 15.3 2.2 1.3 10.1 8.3 18.0 25.1 13.2 17.4

Jones 20.5 15.5 2.8 2.1 13.9 13.7 15.8 25.2 12.0 19.0

Luna 16.1 13.8 2.4 2.2 15.2 16.2 12.1 20.1 10.2 17.5

Maconacon 10.1 9.9 2.9 2.4 29.0 24.3 5.3 14.9 5.9 13.8

Delfin Albano 19.1 19.9 2.3 2.2 12.0 11.2 15.4 22.9 16.2 23.5


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Mallig 23.6 23.8 3.1 2.7 13.1 11.4 18.5 28.7 19.3 28.3

Naguilian 22.9 18.7 2.7 2.0 11.6 10.5 18.5 27.2 15.4 21.9

Palanan 21.3 19.8 4.2 2.9 19.6 14.9 14.4 28.2 14.9 24.6

Quezon 21.4 23.8 3.0 3.4 13.9 14.2 16.5 26.3 18.2 29.4

Quirino 24.8 20.4 3.7 2.2 14.8 10.8 18.7 30.8 16.8 24.0

Ramon 15.7 16.3 2.7 2.1 17.3 13.1 11.2 20.2 12.8 19.8

Reina Mercedes 23.5 14.0 3.6 2.5 15.3 17.9 17.6 29.4 9.9 18.1

Roxas 16.1 15.8 2.3 2.1 14.3 13.2 12.3 19.9 12.4 19.3

San Agustin 19.6 11.8 2.7 2.0 13.7 17.1 15.2 24.0 8.5 15.1

San Guillermo 36.1 21.6 6.6 2.5 18.2 11.6 25.3 46.9 17.5 25.7

San Isidro 18.5 17.3 2.9 2.7 15.6 15.6 13.7 23.2 12.9 21.7

San Manuel 22.7 20.5 2.9 2.4 12.9 11.9 17.9 27.5 16.5 24.5

San Mariano 29.8 24.2 4.5 2.0 15.0 8.3 22.4 37.2 20.9 27.5

San Mateo 14.3 14.6 2.0 2.1 13.9 14.2 11.0 17.5 11.2 18.1

San Pablo 24.9 19.7 3.7 3.3 14.8 16.7 18.8 30.9 14.3 25.1

Santa Maria 28.3 24.4 4.1 2.9 14.4 11.8 21.6 35.0 19.6 29.2

Santiago City 9.8 10.8 2.2 1.6 22.1 14.3 6.2 13.3 8.3 13.4

Santo Tomas 23.5 18.5 3.4 2.4 14.5 12.9 17.9 29.1 14.5 22.4

Tumaini 23.8 19.8 2.5 1.8 10.6 9.0 19.6 28.0 16.8 22.7

Nueva Vizcaya Ambaguio 17.8 15.5 4.5 3.9 25.3 25.1 10.4 25.2 9.1 21.9

Aritao 12.7 16.2 2.4 2.1 19.0 13.1 8.7 16.7 12.7 19.7

Bagabag 12.9 13.4 2.2 2.2 16.8 16.2 9.3 16.5 9.8 16.9

Bambang 10.8 11.3 1.7 1.5 15.8 13.6 8.0 13.6 8.8 13.8

Bayombong 7.1 8.6 1.6 1.4 22.9 16.7 4.4 9.7 6.3 11.0

Diadi 18.8 17.6 2.8 2.1 14.8 12.1 14.2 23.4 14.0 21.1

Dupax del Norte 16.5 11.4 3.0 2.5 18.2 21.6 11.5 21.4 7.4 15.4

Dupax del Sur 15.0 15.4 3.1 2.5 20.5 16.4 9.9 20.1 11.2 19.6

Kasibu 15.8 13.6 2.9 2.1 18.4 15.5 11.0 20.6 10.1 17.1

Kayapa 15.8 16.1 3.1 2.4 19.5 14.9 10.7 20.8 12.2 20.1

Quezon 18.5 16.6 3.3 3.3 17.9 19.6 13.1 24.0 11.2 22.0

Santa Fe 15.2 11.4 5.1 2.6 33.4 23.1 6.8 23.5 7.1 15.8

Solano 6.9 10.1 1.4 1.7 20.8 17.3 4.5 9.2 7.2 12.9

Villaverde 12.3 11.1 3.1 2.7 25.1 24.4 7.2 17.3 6.6 15.5

Alfonso Castaneda 14.1 14.0 3.9 4.6 27.4 33.1 7.8 20.5 6.4 21.6

Quirino Aglipay 22.0 16.3 3.1 2.4 14.3 14.8 16.9 27.2 12.4 20.3

Cobarronguis 12.1 11.8 2.5 2.3 21.0 19.5 7.9 16.2 8.0 15.5

Diffun 23.0 17.5 2.9 1.9 12.6 10.6 18.2 27.7 14.4 20.5

Madella 17.5 14.4 2.7 2.0 15.4 13.9 13.1 21.9 11.1 17.7

Saguday 20.1 18.8 3.4 3.3 16.8 17.5 14.6 25.7 13.4 24.1

Nagtipunan 23.4 15.4 5.3 3.1 22.6 20.1 14.7 32.1 10.3 20.5

Region III Bataan Abucay 8.7 7.0 2.2 2.1 24.9 29.5 5.2 12.3 3.6 10.4

Bagac 15.7 19.7 3.3 3.3 21.0 16.8 10.3 21.1 14.2 25.1

City of Balanga 7.8 5.9 1.7 1.2 21.4 21.1 5.0 10.5 3.8 7.9

Dinalupihan 12.6 11.7 2.1 1.9 16.5 16.2 9.2 16.1 8.6 14.9

Hermosa 13.5 12.6 2.5 2.0 18.1 16.0 9.5 17.5 9.3 15.9

Limay 6.6 7.4 2.3 2.4 34.5 32.5 2.8 10.3 3.4 11.3

Mariveles 12.1 7.2 2.2 1.8 18.3 24.7 8.5 15.8 4.3 10.1

Morong 16.1 20.8 4.5 4.8 28.0 22.9 8.7 23.5 13.0 28.7

Orani 11.3 10.4 1.8 1.8 16.0 17.6 8.3 14.2 7.4 13.4

Orion 9.5 9.5 1.9 1.8 19.9 19.0 6.4 12.7 6.6 12.5

Pilar 7.2 8.9 1.7 2.0 23.5 23.0 4.4 10.0 5.5 12.2

Samal 15.3 12.0 3.2 2.2 21.2 18.0 9.9 20.6 8.4 15.5

Bulacan Angat 11.4 7.8 2.3 1.9 19.9 24.9 7.6 15.1 4.6 10.9

Balagtas 4.7 5.5 1.8 1.9 38.3 33.9 1.7 7.6 2.4 8.5

Baliuag 4.3 5.7 1.3 1.3 29.1 22.6 2.3 6.4 3.6 7.8

Bocaue 4.0 3.4 1.6 1.4 38.5 40.6 1.5 6.6 1.1 5.7

Bulacan 5.2 3.6 1.7 1.3 33.2 36.9 2.4 8.1 1.4 5.8


ProvinceRegion


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200920062009200620092006

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Limit

Upper

Limit

Bustos 10.0 8.1 2.6 2.0 25.7 24.3 5.8 14.3 4.9 11.4

Calumpit 5.3 6.4 1.0 1.5 19.2 22.8 3.6 6.9 4.0 8.8

Guiguinto 5.0 4.1 1.4 1.3 28.2 31.3 2.7 7.4 2.0 6.2

Hagonoy 6.7 8.6 1.5 1.6 22.5 18.4 4.2 9.2 6.0 11.3

Malolos 3.6 5.2 0.9 0.8 24.0 15.5 2.2 5.1 3.9 6.5

Marilao 6.6 3.4 1.7 1.3 26.1 37.1 3.8 9.5 1.3 5.4

Meycauayan 4.2 4.5 1.2 1.3 28.3 27.9 2.2 6.1 2.4 6.6

Norzagaray 10.2 10.0 3.4 2.4 33.1 24.0 4.6 15.7 6.1 13.9

Obando 6.2 6.8 2.0 2.1 32.9 30.8 2.8 9.5 3.4 10.3

Pandi 14.1 7.6 2.5 1.7 18.1 22.0 9.9 18.2 4.8 10.3

Paombong 7.6 7.1 2.1 1.8 28.2 25.5 4.0 11.1 4.1 10.1

Plaridel 5.2 5.0 1.4 1.5 27.3 29.4 2.9 7.5 2.6 7.4

Pulilan 10.6 6.9 2.2 1.4 20.2 20.8 7.1 14.2 4.6 9.3

San Idelfonso 18.2 12.3 2.2 1.5 11.9 12.0 14.6 21.7 9.9 14.8

San Jose Monte City 5.0 5.8 0.9 1.1 18.8 19.0 3.5 6.5 4.0 7.6

San Miguel 13.8 11.8 1.8 1.6 13.3 13.5 10.8 16.9 9.2 14.4

San Rafael 11.4 8.3 1.9 1.4 16.6 16.3 8.3 14.5 6.1 10.5

Santa Maria 5.6 5.0 1.2 1.3 21.5 26.2 3.6 7.5 2.8 7.1

Dona Remedios Trinidad 48.3 35.2 7.2 5.4 15.0 15.4 36.4 60.1 26.3 44.1

Nueva Ecija Allaga 30.5 25.4 4.0 3.6 13.1 14.2 23.9 37.1 19.5 31.4

Bongabon 29.5 21.7 2.8 2.8 9.3 13.0 25.0 34.1 17.1 26.4

Cabanatuan City 12.2 10.9 1.2 1.1 9.8 9.9 10.2 14.2 9.1 12.7

Cabiao 17.2 15.2 2.7 2.5 15.7 16.4 12.8 21.7 11.1 19.3

Carranglan 38.4 32.3 4.4 4.0 11.5 12.4 31.2 45.7 25.7 38.9

Cuyapo 26.1 27.2 2.5 2.4 9.4 8.9 22.1 30.2 23.3 31.2

Gabaldon 32.4 29.2 3.9 3.4 12.1 11.6 26.0 38.8 23.7 34.8

Gapan City 14.9 14.0 2.5 2.0 16.5 14.3 10.9 18.9 10.7 17.3

Gen Mamerio Natividad 33.2 26.8 4.3 3.1 12.9 11.4 26.2 40.3 21.8 31.8

Gen Tinio 19.7 15.7 4.9 3.3 24.8 20.8 11.7 27.7 10.3 21.1

Guimba 35.1 25.2 3.3 2.3 9.5 9.1 29.6 40.6 21.4 28.9

Jaen 22.5 19.0 2.7 2.7 11.9 14.2 18.1 26.9 14.5 23.4

Laur 30.5 31.2 3.6 3.5 11.6 11.1 24.6 36.3 25.5 36.9

Licab 22.2 25.5 3.5 4.1 15.8 16.1 16.4 27.9 18.8 32.3

Llanera 32.1 25.7 4.1 3.1 12.6 11.8 25.4 38.8 20.7 30.8

Lupao 34.6 26.4 3.7 3.3 10.8 12.3 28.5 40.8 21.1 31.8

Munoz City 26.0 21.4 2.7 2.6 10.4 12.0 21.5 30.4 17.1 25.6

Nampicuan 28.1 25.8 4.1 3.3 14.6 12.9 21.3 34.8 20.3 31.3

Palayan City 15.4 16.0 2.6 2.1 17.0 13.0 11.1 19.6 12.6 19.4

Pantabangan 34.1 21.8 4.4 3.2 12.8 14.5 26.9 41.3 16.6 27.1

Penafranda 16.4 11.3 3.9 3.1 23.5 27.1 10.0 22.7 6.3 16.3

Quezon 29.2 26.7 3.8 3.3 12.9 12.2 23.0 35.4 21.4 32.1

Rizal 30.2 19.3 3.3 2.4 10.9 12.5 24.8 35.6 15.4 23.3

San Antonio 23.4 17.2 4.1 3.3 17.5 18.9 16.7 30.1 11.9 22.6

San Isidro 14.6 11.8 3.1 2.7 20.9 22.5 9.6 19.6 7.4 16.1

Sab Jose City 24.5 19.1 3.2 2.2 13.1 11.7 19.2 29.8 15.5 22.8

San Leonardo 19.8 13.6 3.5 2.5 17.4 18.6 14.1 25.5 9.5 17.8

Santa Rosa 24.6 15.0 2.8 2.0 11.5 13.0 20.0 29.3 11.8 18.2

Santo Domingo 30.8 20.3 4.3 2.5 13.8 12.3 23.8 37.8 16.2 24.4

Talavera 21.2 18.3 2.4 1.8 11.4 10.1 17.2 25.2 15.3 21.3

Talugtug 42.2 36.0 4.3 3.0 10.2 8.3 35.1 49.3 31.1 40.9

Zaragoza 20.2 19.3 3.0 2.6 15.0 13.6 15.3 25.2 15.0 23.6

Pampanga Angeles City 5.5 5.0 1.1 1.1 19.3 22.4 3.8 7.3 3.2 6.9

Apalit 9.6 9.1 2.3 2.1 24.3 22.7 5.8 13.4 5.7 12.5

Arayat 9.4 8.7 1.9 1.6 20.6 18.3 6.2 12.6 6.1 11.3

Bacolor 5.5 6.2 2.1 1.8 38.0 28.3 2.0 8.9 3.3 9.1

Candaba 22.5 17.7 3.0 2.7 13.3 15.3 17.6 27.4 13.2 22.1

Floridablanca 8.1 13.4 1.6 1.6 20.0 11.6 5.4 10.7 10.9 16.0


ProvinceRegion


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200920062009200620092006

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Upper

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Limit

Upper

Limit

Guagua 4.1 7.4 1.0 1.3 23.9 17.9 2.5 5.8 5.3 9.6

Lubao 10.5 10.6 1.7 1.5 16.3 13.9 7.7 13.3 8.2 13.1

Mabalacat 7.0 7.2 2.3 2.1 33.4 29.5 3.2 10.8 3.7 10.6

Macabebe 10.2 9.2 2.1 1.9 20.9 20.9 6.7 13.7 6.0 12.3

Magalang 10.8 8.1 2.0 1.9 18.8 23.4 7.5 14.2 5.0 11.2

Masantol 14.9 9.1 2.5 2.2 16.8 24.0 10.8 19.0 5.5 12.7

Mexico 7.4 7.7 1.6 1.4 21.4 18.5 4.8 10.0 5.4 10.1

Minalin 6.4 9.0 2.0 2.1 31.6 22.8 3.1 9.8 5.7 12.4

Porac 11.1 11.3 2.3 2.1 20.7 18.3 7.3 14.8 7.9 14.7

San Fernando City 4.3 4.8 1.0 1.1 22.8 22.9 2.7 5.8 3.0 6.6

San Luis 20.3 16.2 4.1 2.9 20.0 17.7 13.6 27.0 11.5 20.9

San Simon 8.7 9.1 2.1 2.4 23.8 25.8 5.3 12.1 5.2 13.0

Santa Ana 13.0 11.0 3.0 2.4 23.0 22.0 8.1 18.0 7.0 14.9

Santa Rita 5.7 9.4 2.3 2.8 40.5 30.3 1.9 9.4 4.7 14.1

Santo Tomas 5.1 6.0 2.1 2.3 40.4 39.3 1.7 8.4 2.1 9.8

Sasmuan 12.1 11.5 2.5 2.3 20.3 20.3 8.1 16.2 7.6 15.3

Tarlac Anao 13.9 18.0 2.4 3.3 17.3 18.1 10.0 17.9 12.6 23.3

Bamban 7.6 10.6 2.8 3.4 37.2 32.0 2.9 12.2 5.0 16.2

Camiling 10.7 15.8 1.3 1.8 12.1 11.6 8.6 12.9 12.8 18.8

Capas 11.3 13.2 2.9 2.5 25.9 19.3 6.5 16.1 9.0 17.3

Concepcion 12.4 13.5 2.2 1.9 17.5 13.9 8.9 16.0 10.4 16.6

Gerona 13.9 17.6 1.7 2.2 12.0 12.4 11.1 16.6 14.0 21.2

La Paz 21.2 17.0 3.0 2.5 13.9 14.5 16.3 26.0 13.0 21.1

Mayantoc 24.2 28.3 2.9 4.0 12.1 14.0 19.4 29.0 21.8 34.8

Moncada 14.5 15.9 2.3 2.1 16.0 13.4 10.7 18.3 12.4 19.4

Paniqui 8.4 12.8 1.4 1.6 16.5 12.5 6.1 10.6 10.1 15.4

Pura 13.3 14.7 3.0 2.7 22.4 18.1 8.4 18.2 10.3 19.0

Ramos 19.0 16.7 3.9 3.2 20.7 19.2 12.5 25.5 11.4 22.0

San Clemente 24.2 18.2 4.8 3.1 19.9 17.3 16.3 32.2 13.0 23.3

San Manuel 16.7 17.0 3.3 3.1 19.6 18.4 11.3 22.1 11.9 22.1

Santa Ignacia 23.9 21.8 3.0 2.9 12.6 13.1 18.9 28.8 17.1 26.5

Tarlac City 7.1 8.7 1.0 0.8 14.6 9.5 5.4 8.8 7.4 10.1

Victoria 21.6 20.2 2.8 2.7 13.1 13.3 17.0 26.3 15.8 24.6

San Jose 37.8 32.1 5.8 3.9 15.3 12.1 28.3 47.2 25.7 38.4

Zambales Botolan 22.4 17.4 4.3 2.4 19.2 14.0 15.3 29.4 13.4 21.4

Cabanglan 9.2 21.2 2.2 2.7 24.2 12.5 5.6 12.9 16.9 25.6

Candelabra 13.1 18.2 2.7 2.9 20.5 16.1 8.7 17.6 13.4 23.0

Castillejos 6.2 12.5 2.1 2.6 34.4 21.1 2.7 9.6 8.1 16.8

Iba 10.9 12.5 3.0 2.8 27.1 22.2 6.0 15.7 7.9 17.1

Masinloc 15.1 18.2 2.5 3.4 16.4 18.4 11.0 19.2 12.7 23.8

Olongapo City 4.7 4.5 1.3 1.6 28.2 35.1 2.5 6.8 1.9 7.0

Paluig 19.2 21.3 3.3 2.7 17.2 12.7 13.8 24.7 16.8 25.7

San Antonio 11.4 12.0 3.0 2.1 26.8 17.8 6.4 16.4 8.5 15.5

San Felipe 7.7 14.5 2.2 3.7 28.5 25.4 4.1 11.3 8.4 20.5

San Marcelino 12.5 14.8 2.5 2.0 19.9 13.5 8.4 16.6 11.5 18.1

San Narciso 9.0 10.7 1.7 2.1 19.0 19.4 6.2 11.8 7.3 14.1

Santa Cruz 18.2 18.7 2.6 2.7 14.3 14.3 13.9 22.5 14.3 23.1

Subic 7.9 11.5 1.9 2.5 24.3 21.8 4.7 11.0 7.4 15.6

Aurora Baler 11.6 9.6 2.6 2.2 22.2 23.4 7.4 15.8 5.9 13.2

Casiguran 29.1 19.7 4.0 3.5 13.7 17.5 22.5 35.6 14.0 25.4

Dilasag 34.8 19.2 5.6 3.9 16.0 20.4 25.6 43.9 12.7 25.6

Dinalungan 31.0 25.6 5.0 4.9 16.2 19.2 22.8 39.3 17.5 33.7

Dingalan 29.3 14.5 5.6 4.2 18.9 28.8 20.2 38.5 7.6 21.3

Dipaculao 28.5 17.9 3.7 3.1 12.9 17.3 22.5 34.5 12.8 23.0

Maria Aurora 18.4 13.2 2.3 2.0 12.3 15.4 14.7 22.2 9.9 16.6

San Luis 26.0 13.8 3.9 3.1 14.9 22.0 19.6 32.3 8.8 18.9


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200920062009200620092006

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Region IV-A Batangas Agoncillo 19.3 15.4 3.2 1.9 16.6 12.1 14.0 24.6 12.3 18.4

Alitagtag 7.5 8.6 2.2 1.5 28.8 17.0 3.9 11.0 6.2 11.1

Balayan 17.2 14.1 2.1 1.3 12.2 9.0 13.7 20.6 12.0 16.1

Balete 24.6 17.2 4.4 2.8 18.0 16.2 17.3 31.9 12.6 21.8

Batangas City 8.1 7.1 1.0 0.7 11.7 9.7 6.6 9.7 6.0 8.3

Bauan 6.1 2.7 1.5 0.7 23.8 24.4 3.7 8.5 1.6 3.8

Calaca 28.1 17.8 3.5 1.7 12.5 9.4 22.4 33.9 15.1 20.6

Calatagan 28.8 21.9 3.2 2.4 11.0 10.8 23.5 34.0 18.0 25.7

Cuenca 8.7 9.9 2.5 1.6 29.2 16.5 4.5 12.9 7.2 12.6

Ibaan 14.8 12.1 2.6 1.8 17.3 15.0 10.6 19.0 9.1 15.0

Laurel 29.8 21.8 4.5 2.5 15.1 11.3 22.4 37.2 17.7 25.8

Lemery 19.6 14.3 2.3 1.3 11.6 8.9 15.9 23.4 12.2 16.4

Lian 25.6 16.5 3.5 2.4 13.6 14.7 19.9 31.4 12.5 20.5

Lipa City 5.1 3.9 1.1 0.6 20.9 16.3 3.4 6.9 2.8 4.9

Lobo 39.5 19.1 5.2 2.1 13.1 10.7 31.0 48.0 15.7 22.4

Mabini 12.6 11.7 2.0 1.5 15.8 12.9 9.3 15.9 9.2 14.2

Malvar 7.5 6.5 2.1 1.5 27.6 22.2 4.1 10.8 4.1 8.9

Mataas Na Kahoy 8.7 9.8 2.2 2.0 24.8 20.1 5.2 12.3 6.5 13.0

Nasugbu 17.9 17.3 2.5 2.0 13.7 11.3 13.9 22.0 14.1 20.6

Padre Garcia 17.3 16.5 3.7 2.5 21.1 15.4 11.3 23.3 12.3 20.6

Rosario 22.3 16.8 2.7 1.4 12.0 8.1 17.9 26.7 14.5 19.0

San Jose 11.6 11.2 2.6 1.7 22.1 15.3 7.4 15.8 8.4 14.1

San Juan 24.1 15.4 2.6 1.7 10.8 11.0 19.8 28.4 12.6 18.2

San Luis 14.9 9.5 2.9 1.6 19.1 17.1 10.3 19.6 6.9 12.2

San Nicolas 8.5 5.3 2.2 1.5 26.2 27.5 4.8 12.1 2.9 7.8

San Pascual 7.4 5.8 1.8 1.2 23.9 20.1 4.5 10.3 3.9 7.7

Santa Teresita 12.5 9.4 2.7 2.0 22.0 20.8 8.0 17.0 6.2 12.6

Santo Tomas 10.0 8.6 2.0 1.4 19.7 16.3 6.7 13.2 6.3 10.9

Taal 4.6 4.1 1.2 1.0 25.4 23.2 2.7 6.5 2.6 5.7

Talisay 7.5 5.6 1.9 1.5 25.5 26.3 4.4 10.7 3.2 8.1

City Of Tanauan 7.1 4.0 1.2 0.7 17.4 16.6 5.0 9.1 2.9 5.1

Taysan 21.2 16.6 3.4 2.0 16.1 12.2 15.6 26.8 13.3 19.9

Tingloy 44.0 26.2 5.0 2.7 11.4 10.5 35.7 52.2 21.7 30.7

Tuy 26.6 18.0 3.4 1.9 12.9 10.6 20.9 32.2 14.9 21.2

Cavite Alfonso 17.3 13.8 2.4 1.6 14.1 11.9 13.3 21.3 11.1 16.5

Amadeo 13.4 6.3 2.4 1.2 17.8 19.2 9.5 17.3 4.3 8.2

Bacoor 5.2 3.6 1.0 0.6 19.7 17.1 3.5 6.8 2.6 4.6

Carmona 5.0 3.4 1.9 1.7 37.3 48.4 1.9 8.0 0.7 6.2

Cavite City 4.7 5.5 0.8 0.9 16.7 15.5 3.4 6.0 4.1 6.9

Dasmariñas 5.2 5.3 1.1 0.8 21.5 15.8 3.4 7.0 3.9 6.6

General Emilio Aguinaldo 22.0 13.7 3.5 2.1 15.9 15.4 16.2 27.7 10.2 17.2

General Trias 4.8 3.5 1.6 1.0 34.2 29.3 2.1 7.5 1.8 5.2

Imus 3.0 2.3 0.6 0.4 19.7 16.2 2.0 4.0 1.7 3.0

Indang 9.6 6.7 1.7 0.9 17.6 13.5 6.8 12.3 5.2 8.2

Kawit 5.8 4.8 1.4 1.1 23.7 22.5 3.5 8.0 3.0 6.6

Magallanes 28.7 19.4 4.6 2.7 16.1 13.8 21.1 36.3 15.0 23.8

Maragondon 22.2 16.3 3.1 2.2 14.1 13.3 17.1 27.3 12.7 19.9

Mendez (Mendez-Nuñez) 7.6 4.5 2.1 1.1 27.6 23.5 4.1 11.1 2.8 6.3

Naic 11.6 8.4 2.0 1.5 17.3 18.1 8.3 14.9 5.9 10.8

Noveleta 2.9 3.0 1.1 1.0 39.4 34.8 1.0 4.7 1.3 4.7

Rosario 7.8 5.9 2.0 1.3 25.8 22.4 4.5 11.1 3.7 8.1

Silang 11.6 11.0 1.8 1.3 15.4 11.6 8.7 14.6 8.9 13.1

Tagaytay City 7.6 5.6 1.7 1.0 21.9 18.4 4.9 10.3 3.9 7.3

Tanza 8.3 5.4 1.4 1.0 16.5 17.8 6.0 10.6 3.8 7.0

Ternate 12.0 16.5 3.6 2.8 30.0 16.8 6.1 17.9 11.9 21.0

Trece Martires City 3.9 4.3 1.4 1.3 35.6 30.9 1.6 6.2 2.1 6.5

Gen. Mariano Alvarez 4.4 5.7 1.2 1.1 28.0 19.7 2.4 6.4 3.8 7.5


ProvinceRegion


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200920062009200620092006

2006 2009



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Limit

Upper

Limit

Laguna Alaminos 5.4 6.4 1.6 1.6 30.4 25.5 2.7 8.0 3.7 9.1

Bay 6.3 2.8 1.8 1.0 28.8 36.5 3.3 9.2 1.1 4.4

Biñan 2.0 1.7 0.8 0.7 40.9 43.1 0.7 3.4 0.5 2.9

Cabuyao 2.9 1.7 1.1 0.7 38.1 38.9 1.1 4.7 0.6 2.7

Calamba City 2.4 2.0 0.7 0.5 29.8 25.9 1.2 3.6 1.2 2.9

Calauan 16.6 12.0 3.2 1.9 19.2 16.1 11.3 21.8 8.8 15.2

Cavinti 13.5 11.5 3.3 1.9 24.2 16.5 8.1 18.9 8.4 14.6

Famy 15.8 11.0 3.9 2.5 24.7 22.6 9.4 22.2 6.9 15.0

Kalayaan 17.7 12.8 7.0 5.0 39.4 39.4 6.2 29.1 4.5 21.0

Liliw 10.5 7.6 2.0 1.5 19.1 19.2 7.2 13.8 5.2 10.0

Los Baños 2.6 1.6 1.1 0.8 41.3 46.0 0.8 4.4 0.4 2.9

Luisiana 8.7 8.2 2.6 1.5 29.6 17.9 4.5 13.0 5.7 10.6

Lumban 6.9 7.2 1.8 1.7 26.0 23.5 3.9 9.8 4.4 9.9

Mabitac 11.4 14.4 3.1 2.7 27.0 18.7 6.4 16.5 10.0 18.9

Magdalena 12.4 13.8 2.6 2.1 21.1 15.2 8.1 16.7 10.3 17.2

Majayjay 24.4 13.4 4.2 1.7 17.4 12.7 17.4 31.3 10.6 16.2

Nagcarlan 9.4 7.3 1.8 1.2 19.4 16.9 6.4 12.4 5.2 9.3

Paete 2.2 3.2 1.3 1.7 61.8 53.3 0.0 4.4 0.4 6.1

Pagsanjan 2.8 2.8 1.1 0.9 38.2 32.9 1.0 4.6 1.3 4.4

Pakil 14.4 8.9 3.2 2.2 21.8 24.6 9.2 19.6 5.3 12.5

Pangil 11.8 7.4 3.9 2.2 32.8 29.3 5.5 18.2 3.8 11.0

Pila 5.3 3.4 1.9 1.0 35.6 30.4 2.2 8.3 1.7 5.1

Rizal 5.7 5.8 2.4 1.7 41.8 30.1 1.8 9.5 2.9 8.7

San Pablo City 3.5 2.7 0.7 0.5 19.9 19.8 2.4 4.7 1.8 3.6

San Pedro 1.9 1.4 0.9 0.6 49.0 41.1 0.4 3.5 0.5 2.4

Santa Cruz 3.4 2.3 1.1 0.8 32.7 33.5 1.6 5.2 1.0 3.6

Santa Maria 20.6 16.8 3.1 2.1 15.0 12.2 15.5 25.6 13.4 20.2

Santa Rosa City 1.7 1.5 0.8 0.6 46.0 40.1 0.4 3.1 0.5 2.4

Siniloan 9.5 11.4 2.2 2.2 22.6 19.7 6.0 13.1 7.7 15.1

Victoria 5.6 3.7 2.6 1.5 45.5 39.1 1.4 9.8 1.3 6.1

Quezon Agdangan 41.9 19.8 5.6 2.6 13.4 12.9 32.7 51.2 15.6 24.0

Alabat 30.0 17.0 4.0 1.9 13.3 11.3 23.5 36.6 13.9 20.2

Atimonan 16.6 12.7 2.4 1.4 14.5 11.1 12.7 20.5 10.4 15.0

Buenavista 74.4 34.9 5.4 2.3 7.2 6.5 65.6 83.2 31.2 38.6

Burdeos 52.3 39.3 5.5 3.8 10.5 9.6 43.3 61.3 33.1 45.5

Calauag 43.4 25.8 3.9 1.8 8.9 6.8 37.0 49.7 22.9 28.6

Candelaria 10.0 10.6 2.2 1.6 22.0 15.1 6.4 13.6 8.0 13.3

Catanauan 50.0 27.8 4.7 2.0 9.4 7.1 42.3 57.7 24.6 31.1

Dolores 16.6 13.3 4.1 2.5 24.4 18.4 9.9 23.3 9.3 17.4

General Luna 42.4 27.5 3.8 2.5 9.0 9.0 36.1 48.7 23.4 31.6

General Nakar 49.7 27.8 5.5 3.0 11.1 10.9 40.6 58.8 22.8 32.8

Guinayangan 46.9 27.5 4.5 1.8 9.6 6.5 39.5 54.3 24.5 30.4

Gumaca 19.7 16.7 2.3 1.6 11.7 9.3 15.9 23.5 14.2 19.3

Infanta 26.4 15.0 3.5 2.3 13.1 15.2 20.7 32.1 11.3 18.8

Jomalig 74.9 39.0 7.6 5.1 10.1 13.2 62.5 87.3 30.5 47.4

Lopez 38.9 21.7 3.6 1.4 9.3 6.5 32.9 44.8 19.4 24.1

Lucban 12.2 5.2 2.4 1.3 19.5 24.7 8.3 16.1 3.1 7.2

Lucena City 5.4 3.6 1.5 0.9 27.3 24.7 2.9 7.8 2.1 5.1

Macalelon 55.7 29.5 5.7 2.5 10.3 8.3 46.3 65.1 25.4 33.5

Mauban 29.3 21.5 3.2 1.9 10.9 9.0 24.1 34.6 18.3 24.7

Mulanay 66.3 31.5 6.4 2.5 9.7 7.9 55.8 76.8 27.4 35.6

Padre Burgos 33.6 17.2 4.4 2.4 13.1 13.7 26.4 40.8 13.3 21.1

Pagbilao 12.9 13.4 2.3 2.0 17.5 14.9 9.2 16.7 10.1 16.7

Panukulan 54.9 34.5 6.3 3.3 11.5 9.5 44.5 65.3 29.1 39.9

Patnanungan 71.2 36.0 8.0 5.7 11.3 15.8 58.0 84.4 26.7 45.3

Perez 50.5 29.7 6.1 3.3 12.2 11.2 40.4 60.6 24.2 35.2

Pitogo 37.0 24.2 3.6 2.0 9.7 8.2 31.1 42.9 20.9 27.4


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Plaridel 15.6 12.3 3.9 2.2 24.8 17.7 9.2 21.9 8.7 15.9

Polillo 36.5 27.0 4.5 2.2 12.2 8.3 29.1 43.8 23.3 30.6

Quezon 49.8 29.2 4.6 2.5 9.2 8.6 42.3 57.3 25.0 33.3

Real 26.0 17.1 3.9 2.0 14.9 11.8 19.6 32.4 13.8 20.4

Sampaloc 18.7 11.9 4.3 2.2 23.1 18.8 11.6 25.9 8.3 15.6

San Andres 78.3 39.0 6.4 5.2 8.1 13.3 67.8 88.8 30.5 47.5

San Antonio 15.8 16.7 2.9 2.4 18.1 14.4 11.1 20.5 12.7 20.6

San Francisco (Aurora) 63.5 41.4 5.8 3.3 9.2 7.9 53.9 73.1 36.0 46.8

San Narciso 68.7 41.1 5.0 3.3 7.3 8.1 60.4 76.9 35.7 46.6

Sariaya 21.0 14.5 2.9 1.7 13.6 11.8 16.3 25.7 11.7 17.3

Tagkawayan 41.8 23.7 4.3 2.0 10.2 8.3 34.8 48.8 20.4 26.9

Tayabas 12.4 10.5 2.1 1.4 16.6 13.0 9.1 15.8 8.2 12.7

Tiaong 16.2 13.8 2.8 1.9 17.5 13.5 11.5 20.8 10.7 16.8

Unisan 40.4 21.2 4.3 1.6 10.7 7.6 33.3 47.6 18.5 23.8

Rizal Angono 2.5 2.4 1.6 1.2 62.2 49.4 0.0 5.1 0.5 4.4

Antipolo City 4.7 3.6 1.5 1.0 33.0 29.3 2.1 7.2 1.8 5.3

Baras 9.0 11.4 3.3 2.8 36.1 24.8 3.7 14.3 6.8 16.1

Binangonan 5.0 4.0 1.3 0.8 26.1 19.5 2.8 7.1 2.7 5.3

Cainta 2.8 1.4 1.7 0.8 59.4 56.6 0.1 5.6 0.1 2.8

Cardona 6.5 5.5 2.0 1.6 30.7 28.3 3.2 9.8 3.0 8.1

Jala-Jala 14.9 15.7 3.5 2.5 23.5 16.0 9.2 20.7 11.6 19.8

Rodriguez (Montalban) 5.8 4.5 2.3 1.6 38.5 35.3 2.1 9.5 1.9 7.1

Morong 4.8 2.2 2.2 1.1 44.9 50.0 1.3 8.4 0.4 4.1

Pililla 5.7 5.9 2.0 2.0 35.1 33.3 2.4 9.0 2.7 9.1

San Mateo 3.6 2.2 1.4 0.8 38.0 37.6 1.4 5.9 0.8 3.5

Tanay 10.4 10.5 2.7 2.0 25.5 18.9 6.0 14.7 7.3 13.8

Taytay 2.8 3.2 1.8 1.5 63.7 47.1 0.0 5.8 0.7 5.7

Teresa 2.7 3.3 1.5 1.6 55.1 47.3 0.3 5.2 0.7 5.9

Region IV-B Marinduque Boac 24.7 26.5 2.9 2.3 11.8 8.6 19.9 29.4 22.8 30.3

Buenavista 50.3 36.9 5.1 4.8 10.1 13.0 42.0 58.6 29.0 44.8

Gasan 39.4 30.7 4.7 3.8 12.0 12.4 31.6 47.2 24.4 37.0

Mogpog 31.8 26.8 3.5 3.0 10.9 11.1 26.1 37.5 21.9 31.7

Santa Cruz 40.9 30.6 4.2 2.6 10.4 8.5 33.9 47.8 26.3 34.8

Torrijos 50.0 35.2 3.9 4.2 7.9 12.0 43.6 56.5 28.2 42.1

Occidental Mindoro Abra de Ilog 54.8 37.5 6.7 6.1 12.2 16.4 43.8 65.8 27.4 47.5

Calintaan 41.5 34.2 6.5 6.4 15.7 18.7 30.8 52.2 23.6 44.7

Looc 30.4 32.4 5.0 5.5 16.3 17.0 22.2 38.6 23.3 41.5

Lubang 18.3 23.8 4.1 3.7 22.3 15.7 11.6 25.0 17.6 29.9

Magsaysay 51.4 38.3 6.0 6.0 11.7 15.8 41.6 61.3 28.3 48.2

Mamburao 30.8 28.9 5.4 5.3 17.6 18.2 21.9 39.7 20.3 37.6

Paluan 58.7 38.0 5.1 6.0 8.7 15.6 50.3 67.1 28.2 47.8

Rizal 48.1 36.0 5.5 5.4 11.5 15.0 39.0 57.2 27.2 44.9

Sablayan 46.3 34.8 4.1 4.5 8.9 12.9 39.5 53.0 27.5 42.2

San Jose 30.1 29.8 3.6 3.0 12.1 10.2 24.2 36.1 24.8 34.8

Santa Cruz 50.8 38.1 6.2 6.1 12.2 16.0 40.6 61.0 28.1 48.1

Oriental Mindoro Baco 57.2 44.5 4.1 3.9 7.2 8.8 50.4 64.0 38.0 50.9

Bansud 45.2 39.0 5.2 5.6 11.6 14.4 36.6 53.8 29.8 48.2

Bongabong 45.2 35.8 4.0 3.4 8.9 9.4 38.6 51.8 30.2 41.4

Bulalacao 71.3 51.5 5.6 6.3 7.9 12.3 62.0 80.5 41.1 61.9

Calapan City 21.6 23.0 3.1 2.4 14.3 10.4 16.5 26.7 19.0 26.9

Gloria 31.3 35.5 4.5 3.7 14.2 10.5 24.0 38.7 29.4 41.7

Mansalay 54.5 41.8 4.7 5.5 8.6 13.2 46.8 62.1 32.7 50.9

Naujan 43.2 38.4 2.6 3.2 6.0 8.3 38.9 47.5 33.2 43.7

Pinamalayan 33.0 31.7 3.1 3.1 9.3 9.7 28.0 38.0 26.6 36.7

Pola 41.9 37.9 4.3 4.5 10.3 11.7 34.8 49.0 30.6 45.3

Puerto Galera 35.4 23.9 6.0 4.2 17.0 17.4 25.5 45.2 17.1 30.7

Roxas 24.3 29.7 4.0 3.8 16.5 12.9 17.7 30.8 23.4 36.0

San Teodoro 40.8 33.6 6.2 5.3 15.2 15.8 30.6 51.1 24.8 42.3

Socorro 36.6 36.8 4.2 4.2 11.4 11.5 29.7 43.4 29.8 43.8

Victoria 34.4 35.2 3.6 3.4 10.5 9.6 28.4 40.4 29.6 40.7


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Palawan Aborlan 37.3 23.4 4.5 4.1 12.0 17.7 30.0 44.7 16.6 30.2

Agutaya 42.8 36.1 8.1 8.6 19.0 23.9 29.4 56.2 21.9 50.3

Araceli 43.9 35.1 6.2 5.8 14.1 16.5 33.7 54.1 25.5 44.6

Balabac 52.4 44.2 7.5 8.0 14.3 18.0 40.1 64.8 31.1 57.3

Bataraza 44.2 27.5 5.8 4.5 13.0 16.2 34.7 53.7 20.2 34.8

Brooke's Point 36.1 26.7 4.6 3.7 12.8 13.7 28.5 43.7 20.6 32.7

Busuanga 40.2 26.5 5.8 4.8 14.5 18.0 30.6 49.7 18.6 34.3

Cagayancillo 74.5 36.6 7.3 7.7 9.8 21.1 62.6 86.5 23.9 49.4

Coron 33.2 28.4 4.9 4.6 14.7 16.1 25.2 41.2 20.9 35.9

Cuyo 28.8 20.4 3.9 3.5 13.5 17.2 22.4 35.1 14.6 26.1

Dumaran 62.2 41.6 6.1 5.7 9.8 13.8 52.2 72.3 32.1 51.0

El Nido 47.3 29.7 5.5 5.0 11.7 16.9 38.2 56.4 21.4 37.9

Linapacan 63.4 18.1 7.5 5.3 11.9 29.5 51.1 75.8 9.3 26.9

Magsaysay 34.8 17.6 5.6 3.6 16.1 20.6 25.5 44.0 11.7 23.6

Narra 27.5 21.4 4.2 3.8 15.1 17.5 20.7 34.3 15.2 27.6

Puerto Princesa City 9.2 15.5 1.9 2.2 21.2 14.2 6.0 12.4 11.9 19.1

Quezon 25.4 34.0 5.1 5.6 20.3 16.5 16.9 33.8 24.8 43.3

Roxas 29.4 24.9 3.5 3.4 11.7 13.6 23.7 35.1 19.3 30.5

San Vicente 38.4 25.6 6.2 4.7 16.1 18.2 28.2 48.5 18.0 33.2

Taytay 54.5 35.1 4.4 4.1 8.0 11.6 47.3 61.7 28.4 41.8

Culion 40.8 28.5 6.0 4.7 14.8 16.3 30.9 50.7 20.8 36.1

Rizal 43.7 32.7 6.1 5.9 13.9 18.2 33.7 53.7 22.9 42.5

Sofronio Espanola 42.0 30.1 5.8 6.0 13.8 19.8 32.4 51.5 20.3 40.0

Romblon Alcantara 32.8 37.3 5.2 6.5 15.8 17.4 24.2 41.3 26.6 48.0

Banton 42.4 38.0 4.8 5.9 11.2 15.6 34.6 50.3 28.2 47.7

Cajidiocan 47.4 50.4 5.6 6.5 11.8 12.8 38.2 56.6 39.8 61.0

Calatrava 47.3 47.4 6.3 8.1 13.4 17.2 36.9 57.7 34.0 60.8

Concepcion 40.3 41.9 5.9 4.9 14.6 11.6 30.6 49.9 33.9 49.9

Corcuera 60.4 46.6 6.2 6.1 10.2 13.0 50.2 70.6 36.6 56.6

Looc 33.3 48.8 4.5 6.3 13.6 12.9 25.9 40.8 38.4 59.1

Magdiwang 48.8 45.9 5.7 6.7 11.6 14.5 39.4 58.1 35.0 56.9

Odiongan 27.6 35.9 3.4 4.5 12.2 12.6 22.1 33.2 28.5 43.3

Romblon 51.4 39.2 7.6 5.4 14.8 13.8 38.9 64.0 30.3 48.1

San Agustin 42.5 43.5 5.2 6.1 12.2 14.0 34.0 51.0 33.4 53.6

San Andres 45.1 45.5 5.5 6.7 12.2 14.7 36.0 54.1 34.6 56.5

San Fernando 53.1 47.4 6.0 6.9 11.2 14.5 43.3 62.9 36.1 58.7

San Jose 65.8 50.5 6.8 8.4 10.4 16.6 54.5 77.0 36.7 64.3

Santa Fe 53.5 50.1 5.0 6.4 9.3 12.7 45.3 61.7 39.6 60.7

Ferrol 42.9 45.7 7.1 7.6 16.5 16.6 31.3 54.5 33.3 58.2

Santa Maria 48.8 45.7 6.9 8.0 14.2 17.5 37.4 60.2 32.5 58.8

Region V Albay Bacacay 40.3 40.1 3.0 2.4 7.4 6.0 35.4 45.2 36.2 44.0

Camalig 42.1 38.7 2.6 2.2 6.2 5.8 37.8 46.4 35.0 42.3

Daraga (Locsin) 29.4 29.7 2.7 2.0 9.1 6.7 25.0 33.8 26.4 33.0

Guinobatan 39.1 37.2 2.5 2.2 6.4 5.9 35.0 43.2 33.6 40.8

Jovellar 58.3 52.7 3.8 3.7 6.6 7.1 52.0 64.6 46.6 58.8

Legazpi City 26.2 30.7 3.2 2.1 12.3 6.7 20.9 31.5 27.3 34.1

Libon 55.8 48.3 3.1 2.7 5.6 5.6 50.7 60.9 43.8 52.7

Ligao City 45.9 40.5 3.0 2.2 6.5 5.3 41.0 50.8 37.0 44.1

Malilipot 34.9 37.3 4.1 3.4 11.7 9.0 28.2 41.6 31.7 42.8

Malinao 47.3 40.2 3.2 2.8 6.8 7.0 42.0 52.5 35.6 44.9

Manito 49.0 45.4 4.1 4.1 8.3 9.1 42.4 55.7 38.6 52.2

Oas 48.4 42.9 2.8 2.2 5.7 5.1 43.9 53.0 39.4 46.5

Pio Duran 57.7 51.3 3.6 3.0 6.2 5.8 51.8 63.6 46.4 56.1

Polangui 39.2 37.8 2.8 2.4 7.0 6.2 34.7 43.7 34.0 41.7

Rapu-Rapu 53.5 58.6 3.7 3.2 6.9 5.5 47.4 59.6 53.3 64.0

Santo Domingo 32.1 34.2 3.3 2.8 10.3 8.3 26.7 37.5 29.5 38.8

Tabacco City 33.3 35.1 3.4 2.3 10.2 6.5 27.7 38.9 31.4 38.9

Tiwi 38.1 37.9 3.5 2.9 9.3 7.6 32.3 44.0 33.1 42.6


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Camarines Norte Basud 36.9 38.3 3.7 2.8 10.0 7.4 30.8 42.9 33.6 42.9

Capalonga 48.4 48.2 4.3 3.3 8.9 6.8 41.4 55.5 42.8 53.6

Daet 16.6 21.0 2.8 2.1 17.0 9.9 12.0 21.3 17.5 24.4

San Lorenzo Ruiz 43.4 45.4 6.0 5.1 13.7 11.3 33.6 53.2 37.0 53.8

Jose Panganiban 32.9 37.3 3.3 3.0 9.9 7.9 27.5 38.2 32.5 42.2

Labo 34.9 36.5 2.3 2.1 6.5 5.8 31.1 38.6 33.0 40.0

Mercedes 42.4 43.4 3.7 3.0 8.8 7.0 36.3 48.6 38.4 48.4

Paracale 36.2 35.6 3.2 2.8 8.9 7.8 30.9 41.5 31.0 40.1

San Vicente 35.3 34.7 5.4 4.3 15.2 12.4 26.5 44.2 27.6 41.8

Santa Elena 50.3 43.1 5.2 3.7 10.3 8.7 41.9 58.8 36.9 49.2

Talisay 32.1 28.6 4.2 3.1 13.2 10.9 25.1 39.0 23.5 33.7

Vinzons 42.9 42.1 4.2 3.4 9.7 8.1 36.1 49.8 36.4 47.7

Camarines Sur Baao 40.1 37.4 3.5 3.4 8.7 34.4 45.9 31.8 42.9

Balatan 50.6 50.0 5.1 4.1 10.1 8.1 42.2 59.1 43.3 56.6

Bato 38.9 40.1 3.8 2.9 9.8 7.1 32.6 45.2 35.4 44.8

Bombon 35.4 35.1 5.9 5.1 16.8 14.4 25.6 45.1 26.8 43.4

Buhi 41.0 44.0 2.9 2.7 7.1 6.2 36.2 45.8 39.5 48.4

Bulaa 46.0 46.0 3.6 3.2 7.7 6.9 40.2 51.9 40.8 51.2

Cabusao 43.8 46.1 5.7 5.6 13.0 12.0 34.5 53.2 37.0 55.2

Calabanga 38.8 42.7 2.8 2.6 7.3 6.1 34.1 43.4 38.4 47.0

Camaligan 22.6 29.4 4.3 4.0 19.2 13.5 15.4 29.7 22.9 35.9

Canaman 27.3 32.4 3.0 2.8 10.9 8.5 22.4 32.2 27.9 37.0

Caramoan 51.7 53.5 2.9 2.9 5.6 5.4 47.0 56.5 48.7 58.3

Del Gallego 51.6 52.4 4.3 3.4 8.2 6.6 44.6 58.6 46.8 58.1

Gainza 41.3 46.0 6.0 6.2 14.5 13.5 31.4 51.1 35.7 56.2

Garchitorena 58.4 59.0 5.1 3.2 8.7 5.4 50.1 66.7 53.7 64.2

Goa 33.9 41.2 3.4 2.8 10.1 6.8 28.3 39.5 36.6 45.8

Iriga City 25.8 31.5 2.7 2.5 10.4 7.8 21.4 30.2 27.5 35.6

Lagonoy 37.8 46.7 3.1 3.1 8.1 6.6 32.8 42.9 41.6 51.8

Libmanan 51.1 46.9 2.6 2.7 5.1 5.7 46.8 55.4 42.5 51.3

Lupi 57.5 49.9 3.7 3.4 6.4 6.7 51.5 63.5 44.4 55.4

Magarao 32.7 40.3 3.7 4.7 11.3 11.7 26.6 38.8 32.5 48.0

Milaor 36.9 36.6 3.5 3.3 9.6 8.9 31.1 42.7 31.3 42.0

Minalabac 51.5 48.4 4.0 3.6 7.7 7.4 45.0 58.1 42.5 54.3

Nabua 31.9 35.5 3.1 3.0 9.7 8.6 26.8 37.1 30.5 40.5

Naga City 16.6 24.4 2.6 2.4 15.3 9.8 12.4 20.8 20.5 28.3

Ocampo 51.1 43.8 3.6 3.1 7.1 7.1 45.2 57.1 38.7 49.0

Pamplona 48.1 46.7 4.4 3.8 9.2 8.1 40.9 55.4 40.5 53.0

Pasacao 50.0 48.7 4.8 4.7 9.6 9.6 42.1 57.9 41.0 56.4

Pili 34.0 33.1 3.3 2.4 9.8 7.4 28.5 39.5 29.0 37.1

Presentacion 52.8 50.2 5.6 4.6 10.6 9.1 43.5 62.0 42.7 57.7

Ragay 47.6 46.4 3.4 3.1 7.2 6.6 41.9 53.2 41.3 51.5

Sagnay 48.3 51.8 3.9 3.6 8.2 7.0 41.8 54.8 45.8 57.7

San Fernando 40.0 41.6 3.7 3.1 9.3 7.6 33.9 46.1 36.4 46.7

San Jose 35.2 39.1 3.3 3.2 9.4 8.1 29.8 40.7 33.9 44.3

Sipocot 44.0 43.8 2.6 2.7 5.9 6.2 39.7 48.3 39.4 48.3

Siruma 56.3 58.1 4.4 4.0 7.8 6.8 49.0 63.6 51.6 64.6

Tigaon 39.3 41.9 3.9 2.9 10.0 6.9 32.8 45.8 37.1 46.6

Tinambac 51.3 53.2 3.3 3.3 6.4 6.3 45.9 56.7 47.7 58.7

Catanduanes Bagamanoc 38.8 38.0 4.0 4.0 10.2 10.4 32.3 45.3 31.5 44.5

Baras 48.2 39.0 4.4 2.7 9.1 7.0 41.0 55.3 34.5 43.5

Bato 33.1 30.9 3.8 2.7 11.3 8.6 27.0 39.3 26.5 35.3

Caramoran 48.4 49.7 3.8 3.9 7.9 7.8 42.1 54.8 43.3 56.0

Gigmoto 44.2 41.5 5.1 4.2 11.5 10.0 35.8 52.6 34.6 48.3

Pandan 45.9 45.0 3.6 3.2 7.9 7.1 39.9 51.8 39.7 50.2

Panganiban 38.8 35.0 3.6 3.9 9.1 11.3 33.0 44.7 28.5 41.5

San Andres 39.2 36.6 3.5 2.6 8.8 7.1 33.5 44.9 32.4 40.9

San Miguel 52.2 36.5 4.4 2.9 8.4 7.9 45.0 59.4 31.7 41.2

Viga 40.3 41.2 3.3 2.8 8.1 6.7 34.9 45.6 36.6 45.7

Virac 19.9 22.7 2.2 1.5 11.1 6.4 16.2 23.5 20.3 25.1


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Masbate Aroroy 49.0 45.5 3.2 3.2 6.6 7.0 43.6 54.3 40.3 50.8

Baleno 41.2 39.7 4.1 3.5 10.1 8.7 34.3 48.0 34.0 45.4

Balud 55.1 43.1 3.9 3.7 7.1 8.7 48.6 61.5 36.9 49.2

Batuan 34.5 37.0 4.2 4.2 12.2 11.4 27.6 41.5 30.1 44.0

Cataingan 52.5 41.5 3.7 2.8 7.1 6.6 46.4 58.6 36.9 46.0

Cawayan 50.9 47.6 3.5 3.2 6.8 6.7 45.1 56.6 42.3 52.9

Claveria 47.9 46.7 3.5 4.1 7.2 8.8 42.3 53.6 39.9 53.4

Dimasalang 46.0 41.3 4.1 3.3 9.0 7.9 39.2 52.7 35.9 46.7

Esperanza 49.9 45.5 4.1 3.5 8.2 7.6 43.2 56.6 39.8 51.2

Mandaon 52.3 41.1 4.0 3.3 7.7 8.1 45.7 58.9 35.6 46.5

Masbate City 29.1 28.9 3.1 2.3 10.5 8.0 24.1 34.1 25.1 32.7

Milagros 52.1 45.3 3.4 3.2 6.5 7.0 46.5 57.6 40.1 50.5

Mobo 45.8 37.4 3.6 3.0 7.9 8.0 39.9 51.8 32.5 42.4

Monreal 54.9 44.7 5.0 4.2 9.0 9.4 46.8 63.1 37.8 51.6

Palanas 53.0 40.4 4.1 3.2 7.8 8.0 46.2 59.8 35.1 45.7

Pio V. Corpuz 40.5 43.8 4.6 3.8 11.5 8.6 32.8 48.1 37.7 50.0

Placer 59.0 47.0 3.8 3.2 6.5 6.8 52.6 65.3 41.7 52.2

San Fernando 34.6 38.1 3.4 3.0 9.7 7.9 29.0 40.1 33.2 43.1

San Jacinto 39.6 39.1 4.1 3.7 10.4 9.5 32.8 46.4 33.0 45.2

San Pascual 61.7 52.7 4.4 3.4 7.1 6.5 54.5 68.9 47.0 58.3

Uson 54.5 42.9 4.0 2.9 7.4 6.8 47.8 61.1 38.1 47.8

Sorsogon Bacon 35.4 36.2 3.1 2.7 8.6 7.5 30.3 40.4 31.8 40.7

Barcelona 37.2 39.1 3.3 3.1 8.8 7.9 31.8 42.6 34.0 44.1

Bulan 40.7 38.8 2.5 2.6 6.2 6.6 36.5 44.8 34.6 43.1

Bulusan 35.3 32.9 3.6 2.6 10.2 8.0 29.3 41.2 28.6 37.2

Casiguran 41.8 38.9 3.2 3.1 7.6 7.9 36.6 47.0 33.9 44.0

Castilla 52.9 44.4 3.9 3.0 7.4 6.8 46.4 59.3 39.4 49.4

Donsol 54.6 47.3 3.1 3.1 5.6 6.6 49.5 59.6 42.2 52.4

Gubat 31.7 33.6 2.5 2.4 7.9 7.2 27.6 35.8 29.6 37.6

Irosin 33.4 34.2 3.4 2.7 10.2 7.9 27.8 38.9 29.7 38.6

Juban 44.1 41.6 3.9 3.3 8.8 8.0 37.7 50.5 36.1 47.0

Magallanes 53.4 44.6 3.5 3.5 6.6 7.8 47.6 59.2 38.8 50.3

Matnog 46.7 43.2 2.9 2.8 6.1 6.6 42.0 51.4 38.5 47.8

Pilar 54.8 44.3 3.2 2.5 5.8 5.5 49.5 60.0 40.3 48.3

Prieto Diaz 40.1 36.7 3.7 3.1 9.1 8.5 34.1 46.2 31.6 41.8

Santa Magdalena 32.4 35.8 4.1 3.8 12.8 10.6 25.6 39.1 29.6 42.0

Sorsogon City 23.6 27.6 3.2 2.3 13.6 8.3 18.3 28.9 23.8 31.3

Region VI Aklan Altavas 34.3 48.9 3.7 4.6 10.8 9.4 28.3 40.4 41.3 56.4

Balete 45.1 52.7 5.6 5.0 12.3 9.5 36.0 54.2 44.5 60.9

Banga 23.4 39.6 2.6 2.9 11.2 7.4 19.1 27.6 34.8 44.4

Batan 27.7 45.7 4.1 4.2 14.7 9.2 21.0 34.4 38.8 52.6

Buruanga 33.8 47.0 4.4 4.5 13.0 9.5 26.6 41.0 39.7 54.4

Ibajay 36.3 39.6 2.9 3.4 8.0 8.7 31.6 41.1 33.9 45.2

Kalibo 7.8 24.9 1.7 3.3 21.1 13.2 5.1 10.5 19.5 30.3

Lezo 16.0 39.1 2.6 4.1 16.3 10.6 11.7 20.2 32.3 45.9

Libacao 43.3 62.3 4.8 4.3 11.2 6.9 35.3 51.2 55.2 69.4

Madalag 51.2 63.3 4.3 4.2 8.4 6.6 44.1 58.2 56.5 70.2

Makato 25.6 48.9 2.7 3.8 10.4 7.8 21.3 30.0 42.7 55.2

Malay 27.6 24.8 4.8 4.7 17.3 19.0 19.7 35.5 17.0 32.5

Malinao 37.0 43.3 3.5 4.0 9.6 9.2 31.2 42.8 36.7 49.8

Nabas 36.6 36.9 3.4 3.5 9.3 9.5 31.0 42.2 31.1 42.6

New Washington 28.3 42.0 3.3 4.2 11.7 10.1 22.9 33.7 35.1 49.0

Numancia 11.0 24.4 2.2 2.9 20.3 11.7 7.3 14.7 19.7 29.0

Tangalan 43.6 42.5 4.6 4.8 10.6 11.2 36.0 51.2 34.7 50.3


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Antique Anini-Y 37.9 45.4 4.0 4.0 10.4 8.9 31.4 44.4 38.8 52.1

Barbaza 28.5 46.3 3.0 3.6 10.6 7.7 23.5 33.5 40.4 52.1

Belizon 20.3 25.8 4.3 5.1 21.0 19.6 13.3 27.3 17.5 34.2

Bugasong 31.5 39.7 3.4 3.3 10.7 8.3 26.0 37.0 34.2 45.1

Caluya 43.4 49.7 5.0 5.6 11.6 11.3 35.2 51.7 40.5 58.9

Culasi 33.6 37.2 2.9 3.2 8.6 8.6 28.9 38.3 31.9 42.5

Tobias Fornier 31.1 44.1 3.0 3.6 9.7 8.1 26.1 36.0 38.2 50.0

Hamtic 30.6 38.5 3.0 3.4 9.8 8.9 25.7 35.6 32.9 44.1

Lauan-an 36.1 42.1 3.7 4.0 10.1 9.5 30.1 42.1 35.5 48.7

Libertad 36.4 37.3 4.4 4.9 12.0 13.2 29.2 43.6 29.1 45.4

Pandan 33.9 40.1 3.0 3.7 8.9 9.2 28.9 38.9 34.0 46.1

Patnongon 33.7 41.8 3.8 4.1 11.4 9.8 27.4 40.0 35.0 48.6

San Jose 12.6 23.8 1.8 3.0 14.0 12.5 9.7 15.6 18.9 28.7

San Remigio 52.0 55.5 3.8 4.1 7.3 7.3 45.7 58.3 48.8 62.1

Sebaste 35.1 43.0 5.4 6.2 15.5 14.4 26.2 44.1 32.8 53.1

Sibalom 33.1 37.5 2.7 2.8 8.3 7.5 28.6 37.6 32.9 42.1

Tibiao 31.7 49.6 3.8 4.3 12.0 8.7 25.4 37.9 42.5 56.7

Valderama 34.2 43.5 3.9 3.7 11.5 8.4 27.7 40.7 37.5 49.5

Capiz Cuartero 40.9 27.3 3.9 4.7 9.6 17.3 34.4 47.3 19.5 35.0

Dao 30.2 26.2 4.1 4.8 13.6 18.5 23.4 36.9 18.2 34.2

Dumalag 38.4 15.6 4.1 3.8 10.6 24.4 31.7 45.1 9.4 21.9

Dumarao 41.2 26.7 3.3 4.5 7.9 16.7 35.9 46.6 19.4 34.0

Ivisan 28.0 20.2 4.3 4.6 15.3 22.6 21.0 35.1 12.7 27.7

Jamindan 47.3 32.8 3.9 4.5 8.2 13.6 41.0 53.7 25.5 40.1

Ma-ayon 49.7 25.5 3.1 4.0 6.3 15.7 44.6 54.9 18.9 32.1

Mambusao 40.2 19.4 3.6 3.6 9.0 18.5 34.2 46.1 13.5 25.4

Panay 23.9 23.1 4.0 3.5 16.6 15.0 17.4 30.4 17.4 28.8

Panitan 28.0 22.1 2.7 4.1 9.7 18.6 23.5 32.4 15.3 28.8

Pilar 45.9 22.2 3.4 4.2 7.5 18.7 40.2 51.5 15.3 29.0

Pontevedra 33.6 17.8 3.4 3.5 10.2 19.5 28.0 39.2 12.1 23.4

President Roxas 31.8 20.4 4.1 4.4 12.8 21.7 25.1 38.5 13.1 27.7

Roxas City 17.3 12.1 1.8 2.7 10.2 22.4 14.4 20.2 7.6 16.5

Sapi-An 40.1 24.3 4.3 4.9 10.7 20.1 33.1 47.2 16.2 32.3

Sigma 36.5 17.5 3.8 3.7 10.3 21.0 30.3 42.7 11.4 23.5

Tapaz 47.9 29.0 3.5 3.6 7.2 12.3 42.2 53.6 23.1 34.8

Iloilo Ajuy 34.8 30.9 3.7 3.6 10.6 11.5 28.7 40.9 25.1 36.7

Alimodian 36.5 30.4 3.1 4.0 8.6 13.2 31.4 41.7 23.8 37.0

Anilao 30.3 31.5 3.8 4.5 12.4 14.2 24.1 36.5 24.1 38.9

Badiangan 23.1 18.5 2.5 2.9 10.9 15.8 19.0 27.2 13.7 23.3

Balasan 24.0 30.4 2.5 3.9 10.5 12.9 19.9 28.1 24.0 36.9

Banate 26.6 19.8 4.0 3.3 15.1 16.6 20.0 33.1 14.4 25.2

Barotac Nuevo 19.7 15.9 2.1 2.5 10.6 15.9 16.3 23.1 11.7 20.1

Barotac Viejo 35.2 26.2 3.3 3.8 9.5 14.5 29.7 40.7 20.0 32.5

Batad 46.9 33.1 4.6 4.7 9.7 14.3 39.4 54.4 25.3 40.9

Bingawan 38.4 26.8 4.8 5.6 12.6 20.7 30.5 46.4 17.7 35.9

Cabatuan 24.6 15.2 2.0 2.0 8.3 13.1 21.3 28.0 11.9 18.5

Calinog 29.8 29.6 2.4 3.5 8.2 11.8 25.7 33.8 23.9 35.4

Carles 51.5 46.8 3.8 5.2 7.4 11.1 45.2 57.7 38.2 55.3

Concepcion 47.4 48.4 4.3 4.7 9.1 9.6 40.3 54.5 40.8 56.0

Dingle 22.7 17.3 2.2 2.8 9.6 16.2 19.1 26.2 12.7 22.0

Duenas 30.7 22.3 2.6 3.1 8.4 13.9 26.5 35.0 17.2 27.4

Dumangas 25.2 16.0 2.0 2.3 7.7 14.5 22.0 28.4 12.2 19.8

Estancia 30.3 22.1 3.4 3.2 11.3 14.3 24.7 35.9 16.9 27.3

Guimbal 21.0 15.8 2.7 2.4 12.9 15.0 16.6 25.5 11.9 19.7

Igbaras 33.0 29.2 3.6 3.8 11.0 12.8 27.0 39.0 23.0 35.4

Iloilo City 4.9 7.6 0.9 1.0 17.4 13.3 3.5 6.4 5.9 9.2

Janiuay 27.1 25.8 2.6 2.8 9.5 10.9 22.9 31.3 21.2 30.5


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Lambunao 40.7 23.2 3.4 3.3 8.3 14.1 35.1 46.2 17.8 28.5

Leganes 14.0 15.2 2.3 2.9 16.2 18.8 10.3 17.7 10.5 19.9

Lemery 34.8 33.8 3.6 4.2 10.2 12.3 29.0 40.7 27.0 40.7

Leon 35.3 33.7 2.8 4.4 8.0 13.1 30.6 39.9 26.4 40.9

Maasin 37.4 22.6 2.8 2.7 7.4 12.1 32.9 42.0 18.1 27.0

Miag-ao 28.1 26.1 2.2 2.9 7.9 11.0 24.4 31.7 21.4 30.8

Mina 21.2 15.5 3.2 2.9 14.9 18.5 16.0 26.4 10.8 20.3

New Lucena 26.9 16.8 3.5 2.9 12.9 17.3 21.2 32.6 12.0 21.6

Oton 18.0 15.8 2.2 2.2 12.4 14.2 14.4 21.7 12.1 19.5

Passi City 36.5 24.5 2.7 2.9 7.3 12.0 32.1 40.8 19.6 29.3

Pavia 10.6 10.2 1.9 2.1 18.1 20.3 7.4 13.7 6.8 13.6

Pototan 18.8 17.3 2.0 2.4 10.8 13.9 15.5 22.2 13.4 21.3

San Dionisio 43.2 42.3 4.0 4.6 9.2 10.9 36.6 49.7 34.7 49.8

San Enrique 34.5 28.3 3.0 3.7 8.7 13.0 29.5 39.4 22.3 34.4

San Joaquin 36.1 38.3 2.6 4.2 7.2 10.8 31.8 40.4 31.4 45.1

San Miguel 18.4 17.9 2.8 2.9 15.0 15.9 13.9 23.0 13.2 22.6

San Rafael 39.0 30.1 5.6 5.3 14.3 17.5 29.9 48.2 21.4 38.7

Santa Barbara 14.7 13.5 1.8 2.0 12.3 14.5 11.7 17.6 10.3 16.8

Sara 31.7 24.1 2.6 3.1 8.1 12.9 27.5 35.9 19.0 29.2

Tigbauan 24.9 23.3 2.0 3.0 7.9 12.9 21.6 28.1 18.4 28.3

Tubungan 37.4 35.5 2.4 4.2 6.5 11.8 33.4 41.4 28.6 42.4

Zarraga 12.2 15.4 2.4 2.6 19.4 16.7 8.3 16.1 11.2 19.7

Negros Occidental Bacolod City 3.4 11.2 1.0 2.0 29.3 18.2 1.8 5.1 7.8 14.5

Bago City 21.2 20.7 2.9 3.0 13.6 14.5 16.5 26.0 15.8 25.7

Binalbagan 23.4 28.9 4.0 4.4 17.0 15.1 16.9 30.0 21.7 36.1

Cadiz City 26.2 27.3 4.2 3.4 16.0 12.5 19.3 33.1 21.7 32.9

Calatrava 38.3 39.1 3.2 3.4 8.4 8.7 33.0 43.6 33.5 44.7

Candoni 45.0 41.9 6.2 5.2 13.7 12.4 34.9 55.2 33.3 50.4

Cauayan 44.2 55.2 4.5 4.7 10.3 8.6 36.7 51.6 47.4 62.9

Enrique B. Magalona 21.9 24.7 2.8 3.2 12.6 12.8 17.4 26.4 19.5 29.8

Escalante City 27.8 25.6 3.8 3.8 13.8 14.8 21.5 34.2 19.3 31.8

Himamaylan City 30.5 31.4 3.6 3.6 11.8 11.4 24.5 36.4 25.5 37.3

Hinigaran 29.1 30.6 3.2 3.9 11.1 12.6 23.8 34.4 24.2 36.9

Hinoba-An (Asia) 34.0 52.8 4.9 5.8 14.3 10.9 26.0 42.0 43.4 62.3

Ilog 27.0 39.1 3.7 4.9 13.7 12.4 20.9 33.0 31.1 47.0

Isabela 36.1 33.8 3.1 4.0 8.6 11.7 31.0 41.2 27.3 40.3

Kabankalan City 35.4 40.9 3.6 3.2 10.3 7.8 29.4 41.4 35.6 46.1

La Carlota City 17.9 19.3 2.8 3.4 15.4 17.5 13.3 22.4 13.7 24.8

La Castellana 32.4 29.7 5.5 5.2 16.9 17.6 23.4 41.5 21.1 38.3

Manapla 26.9 28.4 5.0 4.8 18.6 16.8 18.7 35.2 20.5 36.2

Moises Padilla (Magallon) 40.4 40.6 5.7 5.5 14.0 13.5 31.1 49.7 31.6 49.7

Murcia 25.1 20.7 3.4 3.8 13.5 18.4 19.5 30.7 14.5 27.0

Pontevedra 20.1 20.4 3.7 3.3 18.5 16.1 14.0 26.2 15.0 25.8

Pulupandan 17.8 24.6 2.1 3.2 11.8 13.1 14.3 21.3 19.3 29.9

Sagay City 27.7 28.0 4.1 3.2 14.9 11.6 20.9 34.6 22.6 33.3

San Carlos City 28.0 34.0 3.9 4.4 14.1 12.8 21.5 34.5 26.9 41.2

San Enrique 21.3 21.8 4.5 5.1 21.0 23.4 14.0 28.7 13.4 30.2

Silay City 18.7 17.6 3.2 3.7 17.3 21.2 13.4 24.0 11.4 23.7

Sipalay City 39.4 45.9 4.4 5.0 11.2 11.0 32.2 46.7 37.6 54.2

Talisay City 11.1 15.7 2.0 2.9 18.1 18.7 7.8 14.4 10.9 20.5

Toboso 34.5 31.8 6.2 6.1 18.1 19.2 24.2 44.7 21.8 41.8

Valladolid 14.4 21.2 2.7 3.4 18.7 16.3 10.0 18.8 15.5 26.8

Victorias City 18.4 19.2 3.0 3.0 16.2 15.4 13.5 23.4 14.3 24.0

Salvador Benedicto 50.1 55.9 7.9 8.1 15.7 14.6 37.1 63.1 42.5 69.2

Guimaras Buenavista 22.5 23.9 2.4 2.5 10.6 10.4 18.5 26.4 19.8 28.0

Jordan 24.6 17.7 3.4 3.3 13.9 18.4 19.0 30.2 12.3 23.0

Nueva Valencia 29.7 36.4 3.4 3.9 11.4 10.7 24.2 35.3 30.0 42.8

San Lorenzo 45.4 44.0 5.1 5.5 11.3 12.5 37.0 53.8 34.9 53.1

Sibunag 42.1 49.3 4.6 5.7 11.0 11.6 34.5 49.7 39.9 58.8


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Region VII Bohol Alburquerque 24.8 25.4 3.9 3.3 15.8 13.1 18.4 31.2 20.0 30.9

Alicia 49.5 53.7 5.4 4.5 10.9 8.4 40.6 58.4 46.3 61.2

Anda 47.4 49.6 4.5 4.2 9.6 8.5 39.9 54.8 42.7 56.5

Antequera 49.9 36.8 5.2 3.1 10.4 8.4 41.4 58.4 31.7 41.9

Baclayon 25.1 23.9 3.5 2.7 14.1 11.3 19.3 30.9 19.4 28.3

Balilihan 48.3 51.9 3.5 2.9 7.3 5.5 42.4 54.1 47.1 56.6

Batuan 75.3 46.8 5.6 3.4 7.4 7.3 66.1 84.4 41.2 52.5

Bilar 43.9 47.9 4.3 3.5 9.7 7.4 36.9 51.0 42.1 53.7

Buenavista 56.2 55.9 3.2 3.1 5.7 5.5 50.9 61.5 50.8 61.0

Calape 39.9 40.4 2.8 2.7 7.0 6.6 35.4 44.5 36.0 44.8

Canduay 38.0 52.3 4.1 3.0 10.8 5.8 31.3 44.8 47.3 57.3

Carmen 75.0 55.2 5.8 3.3 7.7 5.9 65.5 84.5 49.8 60.5

Catigbian 64.3 51.3 6.7 3.4 10.4 6.7 53.3 75.3 45.6 56.9

Clarin 40.5 39.2 3.5 3.3 8.6 8.4 34.8 46.3 33.8 44.6

Corella 27.1 32.0 4.9 4.1 18.2 12.9 19.0 35.2 25.2 38.7

Cortes 26.4 26.9 3.6 3.6 13.7 13.4 20.5 32.3 21.0 32.8

Dagohoy 65.9 56.0 4.7 4.2 7.1 7.5 58.2 73.6 49.0 62.9

Danao 64.7 62.1 4.8 4.0 7.4 6.4 56.8 72.6 55.5 68.6

Dauis 40.5 30.1 3.9 3.6 9.5 12.1 34.2 46.8 24.1 36.1

Dimiao 45.1 42.4 3.2 3.6 7.0 8.4 39.9 50.3 36.6 48.3

Duero 38.0 51.7 3.1 3.2 8.0 6.2 33.0 43.0 46.4 57.0

Garcia Hernandez 35.3 46.8 3.1 2.8 8.8 6.0 30.2 40.4 42.2 51.4

Guindulman 41.2 47.2 3.3 3.4 7.9 7.1 35.8 46.6 41.7 52.7

Inabanga 48.5 47.1 2.8 2.4 5.9 5.0 43.8 53.2 43.2 51.0

Jagna 34.2 36.4 2.7 2.2 8.0 6.1 29.7 38.7 32.8 40.1

Jetafe 50.1 60.1 3.9 2.9 7.7 4.8 43.8 56.5 55.4 64.9

Lila 36.6 42.6 4.1 3.8 11.1 8.9 29.9 43.3 36.3 48.9

Loay 29.7 28.4 3.4 3.0 11.5 10.4 24.1 35.4 23.5 33.2

Loboc 26.0 32.8 2.7 2.9 10.5 8.7 21.5 30.5 28.1 37.5

Loon 39.4 38.8 3.0 2.2 7.6 5.6 34.5 44.3 35.2 42.3

Mabini 46.5 58.4 3.9 3.2 8.5 5.5 40.0 52.9 53.1 63.7

Maribojoc 25.2 24.9 3.4 2.9 13.6 11.7 19.6 30.8 20.1 29.7

Panglao 30.2 33.3 4.6 4.2 15.1 12.5 22.7 37.7 26.4 40.1

Pilar 62.2 67.1 4.0 3.9 6.5 5.8 55.5 68.8 60.7 73.4

Pres. Carlos P. Garcia 49.8 62.1 3.8 3.7 7.6 5.9 43.6 56.0 56.0 68.1

Sagbayan 57.1 48.8 6.0 3.8 10.6 7.7 47.2 67.0 42.6 55.0

San Isidro 47.8 64.0 5.2 4.8 10.9 7.6 39.2 56.4 56.0 72.0

San Miguel 64.2 53.6 3.8 4.1 6.0 7.6 57.9 70.5 46.9 60.3

Sevilla 59.9 52.2 4.5 3.6 7.5 6.9 52.5 67.3 46.3 58.2

Sierra Bullones 47.7 54.4 4.0 4.3 8.4 7.9 41.2 54.3 47.3 61.4

Sikatuna 38.0 45.9 5.6 4.7 14.8 10.3 28.7 47.2 38.1 53.7

Tagbilaran City 10.4 11.0 1.9 2.2 18.3 19.5 7.3 13.6 7.5 14.6

Talibon 43.9 51.4 3.8 3.2 8.7 6.2 37.6 50.1 46.2 56.6

Trinidad 57.9 56.6 4.0 3.8 7.0 6.7 51.3 64.6 50.4 62.8

Tubigon 41.5 37.4 3.2 2.5 7.7 6.8 36.2 46.7 33.2 41.5

Ubay 57.2 50.1 3.3 2.9 5.7 5.8 51.9 62.5 45.3 54.9

Valencia 43.0 50.4 2.9 2.9 6.8 5.7 38.2 47.8 45.7 55.2

Bien Unido 45.2 63.7 4.6 4.0 10.3 6.2 37.5 52.8 57.2 70.3

Cebu Alcantara 47.9 51.2 6.4 4.5 13.2 8.8 37.5 58.4 43.7 58.6

Alcoy 53.0 47.1 5.9 5.2 11.2 10.9 43.3 62.7 38.6 55.5

Alegria 62.7 62.4 5.0 4.7 8.0 7.5 54.4 70.9 54.6 70.1

Aloguinsan 61.7 49.4 6.1 4.9 9.8 9.9 51.7 71.7 41.3 57.4

Argao 41.7 43.6 2.5 2.4 6.0 5.4 37.5 45.8 39.7 47.4

Asturias 52.3 44.2 4.6 3.5 8.8 7.9 44.7 59.8 38.5 49.9

Badian 60.5 53.5 3.5 3.2 5.8 5.9 54.6 66.3 48.2 58.7

Balamban 41.6 37.6 3.7 3.5 8.9 9.2 35.5 47.7 31.9 43.3

Bantayan 48.9 55.1 3.4 3.0 6.9 5.5 43.3 54.4 50.2 60.1


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Barili 51.3 40.7 3.4 2.6 6.6 6.5 45.7 56.9 36.3 45.0

Bogo 37.7 37.0 3.3 3.1 8.7 8.5 32.3 43.0 31.8 42.1

Boljoon 52.1 48.6 5.8 4.4 11.0 9.0 42.6 61.5 41.4 55.8

Borbon 51.2 43.7 4.2 3.4 8.1 7.8 44.4 58.1 38.1 49.3

Carcar 35.0 27.2 4.2 3.6 12.0 13.1 28.1 41.9 21.3 33.1

Carmen 32.6 31.4 3.5 3.2 10.6 10.2 26.9 38.3 26.1 36.6

Catmon 43.7 39.9 3.8 3.8 8.8 9.6 37.4 50.0 33.6 46.2

Cebu City 14.5 13.9 1.9 1.5 13.0 10.7 11.4 17.6 11.5 16.4

Compostela 29.0 27.8 4.0 4.0 13.8 14.5 22.4 35.6 21.1 34.4

Consolacion 22.7 17.4 3.4 3.1 15.1 18.0 17.1 28.4 12.3 22.6

Cordoba 29.0 25.9 4.6 3.8 15.9 14.7 21.4 36.6 19.6 32.2

Daanbantayan 42.1 42.9 3.2 3.2 7.7 7.4 36.8 47.4 37.7 48.1

Dalaguete 54.2 55.6 3.6 3.0 6.7 5.4 48.2 60.1 50.7 60.5

Danao City 30.7 31.6 3.2 2.8 10.5 9.0 25.4 36.1 26.9 36.2

Dumanjug 48.0 47.6 3.5 3.1 7.3 6.6 42.3 53.8 42.5 52.8

Ginatilan 41.5 58.0 4.8 4.0 11.5 6.9 33.6 49.4 51.4 64.6

Lapu-Lapu City 16.6 19.6 2.4 2.4 14.2 12.2 12.8 20.5 15.7 23.6

Liloan 22.0 18.0 3.9 3.1 17.8 17.3 15.5 28.4 12.9 23.0

Madridejos 45.1 50.6 4.0 4.1 8.8 8.0 38.5 51.7 43.9 57.3

Malabuyoc 59.4 50.7 4.8 4.3 8.1 8.4 51.5 67.3 43.7 57.7

Mandaue City 14.5 14.1 2.5 2.0 17.4 14.4 10.3 18.6 10.7 17.4

Medellin 39.6 35.8 4.3 3.2 10.9 9.0 32.5 46.6 30.5 41.1

Minglanilla 25.9 20.4 3.8 2.7 14.7 13.4 19.6 32.1 15.9 24.9

Moalboal 45.0 48.9 4.5 3.4 10.0 6.9 37.6 52.4 43.4 54.5

Naga 31.4 27.1 2.9 2.4 9.1 8.7 26.7 36.1 23.2 31.0

Oslob 55.1 50.9 4.0 3.4 7.3 6.8 48.4 61.7 45.2 56.5

Pilar 42.7 48.9 4.7 4.4 11.0 9.0 35.0 50.4 41.6 56.1

Pinamungahan 41.6 46.4 3.6 3.3 8.6 7.1 35.7 47.4 40.9 51.8

Poro 49.3 45.1 4.5 4.1 9.1 9.1 41.9 56.6 38.3 51.9

Ronda 57.3 46.5 4.1 3.9 7.2 8.4 50.4 64.1 40.1 52.9

Samboan 49.5 53.1 4.9 4.0 9.9 7.5 41.4 57.5 46.5 59.6

San Fernando 31.0 26.2 3.0 3.5 9.7 13.2 26.1 36.0 20.5 31.9

San Francisco 60.7 59.5 4.1 4.0 6.8 6.8 53.9 67.4 52.8 66.1

San Remigio 50.8 45.7 3.1 3.2 6.1 7.0 45.7 56.0 40.4 50.9

Santa Fe 65.0 56.2 4.7 5.4 7.3 9.6 57.3 72.8 47.4 65.1

Santander 56.3 41.9 5.2 4.2 9.3 10.1 47.7 64.9 35.0 48.8

Sibonga 42.2 41.8 3.8 3.2 8.9 7.7 36.0 48.4 36.5 47.1

Sogod 44.6 44.7 4.8 3.8 10.7 8.5 36.8 52.5 38.5 50.9

Tabogon 48.1 47.0 4.1 3.3 8.5 7.1 41.4 54.8 41.6 52.5

Tabuelan 66.5 53.8 5.0 4.8 7.6 9.0 58.2 74.8 45.9 61.8

Talisay City 18.6 18.0 3.1 2.6 16.7 14.3 13.5 23.7 13.7 22.2

Toledo City 34.3 31.5 2.8 2.3 8.1 7.1 29.7 38.8 27.8 35.2

Tuburan 58.4 45.9 3.6 2.6 6.1 5.7 52.6 64.3 41.6 50.1

Tudela 41.7 42.7 6.2 6.1 14.9 14.2 31.5 51.9 32.7 52.6

Negros Oriental Amlan 25.7 24.1 4.9 4.9 18.9 20.3 17.7 33.7 16.1 32.2

Ayungon 49.7 51.6 4.1 3.7 8.3 7.2 42.9 56.5 45.5 57.7

Bacong 24.2 20.8 2.9 2.5 12.1 11.9 19.3 29.0 16.7 24.8

Bais City 54.3 37.2 3.7 3.0 6.9 8.1 48.1 60.4 32.3 42.2

Basay 50.9 45.8 6.4 5.8 12.6 12.6 40.4 61.5 36.3 55.3

Bayawan City 50.9 42.6 7.8 3.3 15.3 7.7 38.1 63.8 37.2 48.0

Bindoy 56.7 59.9 5.7 3.7 10.1 6.2 47.3 66.1 53.8 66.0

Canlaon City 54.0 35.4 6.6 4.4 12.3 12.3 43.1 64.9 28.3 42.6

Dauin 33.1 32.4 3.8 3.4 11.4 10.6 26.8 39.3 26.8 38.1

Dumaguete City 9.5 7.4 1.6 1.4 17.0 18.6 6.9 12.2 5.1 9.7

Guihulngan 58.6 45.0 4.8 3.2 8.2 7.1 50.7 66.5 39.8 50.3

Jimalalud 65.3 50.2 4.1 3.7 6.3 7.3 58.6 72.1 44.1 56.2

La Libertad 55.9 50.2 4.1 3.5 7.4 6.9 49.1 62.7 44.5 55.9


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Mabinay 56.6 48.8 4.0 3.4 7.1 7.0 50.0 63.2 43.2 54.5

Manjuyod 35.5 42.5 4.3 3.4 12.2 8.1 28.4 42.6 36.8 48.1

Pamplona 47.3 35.5 4.6 3.0 9.7 8.5 39.8 54.8 30.5 40.5

San Jose 26.2 28.7 3.5 4.4 13.2 15.3 20.5 31.9 21.5 36.0

Santa Catalina 53.0 39.5 4.4 3.6 8.2 9.1 45.8 60.1 33.6 45.4

Siaton 49.6 48.5 4.4 3.6 8.8 7.5 42.4 56.8 42.5 54.5

Sibulan 21.1 17.4 3.4 2.5 15.9 14.6 15.6 26.6 13.2 21.6

Tanjay City 29.2 27.1 3.4 3.1 11.6 11.4 23.6 34.7 22.0 32.1

Tayasan 57.4 48.5 4.2 3.5 7.2 7.2 50.6 64.2 42.7 54.3

Valencia 36.0 27.3 3.3 2.5 9.2 9.2 30.5 41.4 23.1 31.4

Vallehermoso 43.8 47.2 5.8 5.1 13.1 10.7 34.4 53.3 38.8 55.5

Zamboanguita 38.9 39.1 5.0 5.0 12.8 12.7 30.7 47.1 31.0 47.3

Siquijor Enrique Villanueva 29.8 28.2 3.8 4.0 12.8 14.0 23.6 36.1 21.7 34.7

Larena 21.0 21.0 3.0 2.6 14.4 12.3 16.0 26.0 16.7 25.2

Lazi 40.1 39.5 4.7 3.5 11.7 8.8 32.4 47.8 33.7 45.2

Maria 36.3 39.1 3.9 3.3 10.6 8.3 29.9 42.6 33.8 44.5

San Juan 39.5 42.9 4.9 4.0 12.5 9.3 31.4 47.6 36.3 49.4

Siquijor 28.9 27.0 2.7 2.4 9.4 8.7 24.4 33.3 23.1 30.9

Region VIII Eastern Samar Arteche 48.7 55.8 4.1 4.5 8.5 8.1 41.9 55.5 48.3 63.2

Balangiga 36.9 44.2 4.0 4.8 10.7 10.9 30.4 43.5 36.2 52.1

Balangkayan 41.3 48.6 4.0 5.1 9.7 10.6 34.7 47.9 40.2 57.0

Borongan 26.4 37.6 1.6 2.9 6.1 7.7 23.7 29.0 32.9 42.4

Can-avid 44.3 50.0 2.9 3.8 6.5 7.5 39.5 49.0 43.9 56.2

Dolores 44.0 50.2 2.9 3.8 6.6 7.5 39.2 48.8 44.0 56.3

General MacArthur 47.3 48.8 2.8 4.2 6.0 8.6 42.6 51.9 42.0 55.7

Giporlos 44.3 44.9 4.1 4.2 9.2 9.3 37.7 51.0 38.0 51.8

Guiuan 35.1 42.0 2.4 3.7 6.7 8.9 31.3 39.0 35.8 48.1

Hernani 42.3 48.7 4.2 4.8 10.0 9.9 35.3 49.2 40.8 56.7

Jipapad 41.3 60.6 4.9 5.2 11.9 8.6 33.2 49.4 52.0 69.1

Lawaan 34.0 45.7 4.0 5.0 11.7 10.9 27.5 40.6 37.5 53.9

Llorente 41.3 47.2 2.6 3.5 6.2 7.4 37.1 45.5 41.5 52.9

Maslog 57.8 60.2 6.0 5.8 10.3 9.6 48.0 67.6 50.7 69.6

Maydolong 43.9 49.1 3.5 4.2 7.9 8.5 38.2 49.7 42.2 55.9

Mercedes 44.3 39.6 4.7 4.1 10.7 10.3 36.5 52.1 32.9 46.3

Oras 42.5 51.1 2.6 4.0 6.1 7.9 38.2 46.8 44.5 57.7

Quinapondon 50.3 51.9 3.7 4.2 7.4 8.2 44.1 56.4 44.9 58.8

Salcedo 40.1 45.8 2.7 3.9 6.8 8.5 35.6 44.5 39.4 52.2

San Julian 32.4 45.2 3.4 4.4 10.4 9.8 26.9 37.9 37.9 52.4

San Policarpo 38.2 46.4 3.6 4.6 9.4 10.0 32.3 44.1 38.8 54.0

Sulat 28.9 42.0 2.9 4.7 10.0 11.1 24.1 33.7 34.4 49.6

Taft 34.9 42.2 2.7 3.9 7.9 9.2 30.4 39.4 35.8 48.5

Leyte Abuyog 37.3 35.4 2.3 2.0 6.1 5.5 33.5 41.0 32.1 38.6

Alangalang 35.7 34.9 2.2 2.5 6.1 7.1 32.1 39.3 30.8 39.0

Albuera 28.9 33.6 2.9 3.6 10.2 10.7 24.1 33.7 27.7 39.5

Babatngon 38.6 38.6 2.9 3.1 7.6 8.0 33.8 43.4 33.5 43.7

Barugo 33.2 36.6 2.7 2.8 8.0 7.6 28.9 37.6 32.0 41.2

Bato 35.1 36.4 2.7 2.7 7.8 7.5 30.6 39.6 31.9 40.9

Baybay 29.5 31.0 1.6 1.7 5.5 5.4 26.8 32.1 28.3 33.7

Burauen 32.1 33.3 2.0 1.9 6.2 5.6 28.9 35.4 30.2 36.4

Calubian 34.0 36.2 2.1 2.4 6.2 6.7 30.5 37.5 32.2 40.2

Capoocan 38.1 39.8 3.3 3.6 8.6 9.0 32.7 43.5 33.9 45.6

Carigara 31.4 32.1 1.9 2.2 6.1 6.9 28.2 34.5 28.5 35.8

Dagami 30.6 35.0 2.5 2.0 8.3 5.8 26.4 34.7 31.7 38.3

Dulag 32.2 33.6 2.3 2.3 7.0 6.9 28.5 35.9 29.7 37.4

Hilongos 29.6 30.6 2.0 2.1 6.7 6.9 26.3 32.8 27.2 34.1

Hindang 24.1 32.1 2.7 3.1 11.1 9.8 19.7 28.5 26.9 37.2

Inopacan 30.1 30.7 3.1 3.3 10.3 10.8 25.0 35.2 25.3 36.2


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Isabel 18.4 23.7 2.3 2.4 12.6 10.1 14.6 22.2 19.7 27.6

Jaro 35.1 37.4 2.3 2.6 6.6 6.9 31.3 38.9 33.1 41.6

Javier (Bugho) 38.0 36.7 3.0 2.7 7.8 7.4 33.1 42.9 32.2 41.1

Julita 29.9 33.3 2.8 2.9 9.2 8.6 25.3 34.4 28.6 38.1

Kananga 37.8 40.6 3.3 3.8 8.8 9.4 32.3 43.3 34.4 46.9

Lapaz 29.1 35.8 2.5 2.7 8.5 7.5 25.0 33.2 31.4 40.3

Leyte 47.8 46.7 3.3 3.5 7.0 7.4 42.3 53.3 41.0 52.4

MacArthur 34.2 36.6 2.9 3.0 8.4 8.1 29.5 39.0 31.7 41.5

Mahaplag 41.8 41.2 3.4 3.6 8.1 8.6 36.2 47.4 35.3 47.0

Matag-ob 37.5 35.7 3.7 3.4 9.9 9.4 31.4 43.6 30.1 41.2

Matalom 33.0 34.7 2.7 2.7 8.1 7.6 28.6 37.4 30.3 39.0

Mayorga 31.9 36.4 3.2 3.1 10.0 8.4 26.6 37.1 31.3 41.4

Merida 28.3 32.0 2.9 3.2 10.3 10.0 23.5 33.0 26.7 37.2

Ormoc City 25.5 28.3 1.6 1.8 6.3 6.5 22.9 28.1 25.3 31.4

Palo 19.5 24.6 2.1 1.8 10.7 7.4 16.1 23.0 21.6 27.6

Palompon 30.1 30.3 2.0 2.0 6.5 6.5 26.9 33.4 27.1 33.5

Pastrana 41.6 35.9 3.0 2.9 7.3 8.0 36.6 46.6 31.2 40.6

San Isidro 37.4 41.2 3.5 3.6 9.4 8.6 31.6 43.2 35.4 47.1

San Miguel 39.2 35.9 3.3 3.2 8.4 9.0 33.8 44.6 30.6 41.2

Santa Fe 33.2 31.4 3.4 3.9 10.2 12.3 27.6 38.7 25.0 37.7

Tabango 37.7 40.8 3.7 4.4 9.7 10.7 31.6 43.7 33.6 47.9

Tabontabon 34.4 36.8 4.1 3.4 11.9 9.2 27.7 41.1 31.2 42.4

Tacloban City 10.9 20.5 1.5 1.5 13.8 7.1 8.4 13.3 18.0 22.9

Tanauan 25.1 27.0 2.0 2.3 8.1 8.5 21.7 28.5 23.2 30.7

Tolosa 18.2 24.4 2.5 2.8 13.8 11.4 14.1 22.3 19.9 29.0

Tunga 21.2 23.1 3.1 3.5 14.5 15.3 16.1 26.2 17.3 28.8

Villaba 36.5 35.4 2.9 2.4 7.8 6.9 31.8 41.2 31.4 39.4

Northern Samar Allen 21.4 31.5 2.7 2.6 12.6 8.3 17.0 25.8 27.2 35.8

Biri 39.4 50.7 5.0 4.6 12.6 9.1 31.2 47.6 43.1 58.3

Bobon 34.2 45.9 3.3 3.3 9.5 7.1 28.9 39.6 40.6 51.3

Capul 38.5 41.6 4.2 4.6 10.8 11.1 31.7 45.4 34.0 49.2

Catarman 29.8 43.4 2.2 2.5 7.4 5.8 26.2 33.5 39.3 47.5

Catubig 47.1 52.8 2.9 3.0 6.2 5.6 42.3 51.9 47.9 57.7

Gamay 40.4 48.7 3.1 3.4 7.6 6.9 35.3 45.4 43.2 54.3

Laoang 39.5 47.6 2.2 2.8 5.4 5.8 35.9 43.0 43.1 52.2

Lapinig 54.4 51.9 4.5 4.5 8.2 8.7 47.1 61.7 44.5 59.3

Las Navas 58.8 57.1 3.6 3.2 6.2 5.6 52.8 64.8 51.8 62.3

Lavezares 51.1 45.6 3.9 3.6 7.6 7.8 44.7 57.5 39.8 51.5

Mapanas 54.8 58.4 4.4 5.1 8.0 8.8 47.5 62.0 49.9 66.8

Mondragon 42.6 52.2 3.6 3.6 8.6 6.8 36.6 48.6 46.4 58.1

Palapag 50.4 52.1 3.3 2.8 6.6 5.3 44.9 55.8 47.5 56.6

Pambujan 47.3 51.6 3.7 3.6 7.8 7.0 41.2 53.4 45.6 57.5

Rosario 39.3 41.6 3.9 3.9 10.0 9.4 32.8 45.7 35.1 48.0

San Antonio 28.3 32.5 4.2 4.1 14.9 12.6 21.4 35.3 25.7 39.2

San Isidro 35.0 43.6 3.5 3.9 9.9 8.9 29.3 40.8 37.2 50.0

San Jose 32.2 46.1 3.4 3.4 10.6 7.3 26.6 37.8 40.6 51.6

San Roque 49.3 52.7 3.9 4.0 7.9 7.6 42.9 55.7 46.2 59.3

San Vicente 30.1 43.5 4.6 4.7 15.1 10.8 22.6 37.5 35.7 51.2

Silvino Lobos 59.8 64.8 4.4 3.8 7.3 5.9 52.7 67.0 58.5 71.1

Victoria 34.7 37.7 3.4 3.7 9.9 9.8 29.0 40.3 31.6 43.8

Lope De Vega 52.5 58.2 4.0 4.7 7.7 8.0 45.9 59.2 50.5 65.9

Samar (Western) Almagro 28.5 39.5 2.8 3.4 9.7 8.7 24.0 33.1 33.8 45.1

Basey 30.9 39.1 2.4 2.6 7.9 6.7 26.9 34.9 34.7 43.4

Calbayog City 28.8 38.7 2.0 1.9 7.0 4.9 25.5 32.1 35.6 41.8

Calbiga 40.0 39.0 3.5 3.0 8.6 7.6 34.4 45.7 34.2 43.9

Catbalogan 21.1 33.6 2.2 2.6 10.3 7.7 17.6 24.7 29.3 37.9

Daram 47.2 51.2 2.9 3.1 6.1 6.0 42.4 52.0 46.1 56.2


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Gandara 37.9 43.8 2.7 2.2 7.0 5.0 33.5 42.3 40.2 47.4

Hinabangan 36.1 43.8 3.4 3.5 9.3 8.1 30.6 41.6 38.0 49.6

Jiabong 48.4 41.7 4.3 3.7 9.0 8.8 41.2 55.5 35.6 47.7

Marabut 35.0 44.4 2.9 3.2 8.2 7.3 30.2 39.7 39.1 49.7

Matuguinao 64.2 57.5 5.3 4.7 8.2 8.1 55.5 72.8 49.8 65.1

Motiong 60.6 45.9 5.4 3.9 9.0 8.6 51.7 69.6 39.4 52.4

Pinabacdao 39.1 45.0 3.3 3.2 8.3 7.0 33.8 44.5 39.8 50.2

San Jose de Buan 55.0 57.8 5.0 5.2 9.1 8.9 46.7 63.3 49.3 66.2

San Sebastian 49.0 43.0 4.8 3.7 9.8 8.6 41.1 56.9 36.9 49.0

Santa Margarita 36.1 40.7 2.8 3.5 7.6 8.6 31.5 40.6 35.0 46.5

Santa Rita 42.0 41.3 3.1 3.2 7.4 7.8 36.9 47.1 35.9 46.6

Santo Nino 38.6 45.3 4.1 4.7 10.7 10.4 31.8 45.4 37.5 53.1

Talalora 37.7 47.0 4.1 4.9 10.9 10.3 30.9 44.5 39.0 55.0

Tarangnan 44.9 46.3 3.4 3.2 7.5 6.9 39.4 50.4 41.0 51.5

Villareal 36.5 42.1 2.9 2.8 7.9 6.6 31.7 41.3 37.5 46.6

Paranas (Wright) 38.3 42.5 2.6 2.9 6.8 6.9 34.0 42.6 37.7 47.4

Zumurraga 46.1 49.9 3.1 3.8 6.8 7.7 40.9 51.2 43.6 56.2

Tagapul-an 38.3 42.5 4.1 4.2 10.6 9.9 31.7 45.0 35.5 49.4

San Jorge 36.6 42.3 3.1 2.8 8.3 6.7 31.6 41.6 37.6 46.9

Pagsanghan 31.8 40.6 3.6 3.5 11.3 8.7 25.9 37.6 34.8 46.3

Southern Leyte Anahawan 22.4 29.7 3.2 3.7 14.1 12.5 17.2 27.6 23.6 35.8

Bontoc 35.8 43.2 2.5 2.7 7.1 6.3 31.6 39.9 38.7 47.7

Hinunangan 27.6 37.6 2.4 2.7 8.7 7.1 23.6 31.5 33.2 42.0

Hinundayan 17.5 31.7 2.5 3.3 14.3 10.3 13.4 21.6 26.3 37.1

Libagon 30.3 42.1 3.1 3.7 10.2 8.9 25.2 35.4 35.9 48.2

Liloan 30.1 39.3 2.5 3.2 8.4 8.1 25.9 34.3 34.1 44.6

Maasin City 23.9 31.4 1.9 2.0 8.1 6.3 20.7 27.0 28.1 34.6

Macrohon 25.9 33.6 2.2 2.6 8.6 7.8 22.3 29.6 29.3 37.9

Malitbog 25.4 40.6 2.4 2.9 9.3 7.2 21.5 29.2 35.7 45.4

Padre Burgos 20.5 33.9 3.0 3.7 14.5 10.9 15.6 25.4 27.8 40.0

Pintuyan 30.6 43.2 2.9 3.5 9.5 8.1 25.9 35.4 37.4 49.0

Saint Bernard 34.0 42.7 2.6 3.0 7.6 6.9 29.7 38.2 37.9 47.6

San Francisco 26.3 36.7 2.6 2.6 9.9 7.2 22.0 30.6 32.4 41.1

San Juan (Cabalian)) 22.8 33.6 3.0 3.0 12.9 9.0 17.9 27.6 28.7 38.6

San Ricardo 27.6 42.5 3.7 3.4 13.4 8.0 21.5 33.7 36.9 48.1

Silago 30.6 38.1 3.4 4.2 11.0 11.0 25.0 36.1 31.2 44.9

Sogod 31.3 36.8 2.4 2.6 7.6 7.1 27.4 35.2 32.6 41.1

Tomas Oppus 27.3 39.7 2.7 2.8 9.9 7.0 22.9 31.8 35.2 44.3

Limasawa 25.1 37.3 4.1 4.9 16.4 13.1 18.3 31.8 29.3 45.3

Biliran Almera 20.5 26.8 3.2 3.5 15.8 13.0 15.2 25.8 21.1 32.5

Biliran 23.3 33.2 3.6 4.2 15.6 12.7 17.3 29.3 26.3 40.1

Cabucgayab 26.3 35.2 3.6 4.1 13.5 11.5 20.5 32.2 28.6 41.9

Caibiran 27.6 38.3 2.9 4.0 10.4 10.3 22.9 32.3 31.8 44.8

Culaba 27.4 35.5 3.4 3.5 12.6 9.9 21.7 33.0 29.7 41.3

Kawayan 24.2 33.5 3.4 3.5 13.9 10.4 18.6 29.7 27.8 39.2

Maripipi 20.1 28.0 2.7 3.5 13.3 12.5 15.7 24.5 22.2 33.8

Naval 19.9 27.8 2.5 2.4 12.6 8.6 15.8 24.1 23.8 31.7

Region IX Zamboanga del Norte Dapitan City 46.7 40.0 5.3 4.5 11.3 11.3 38.0 55.3 32.6 47.5

Dipolog City 33.0 26.8 5.5 5.2 16.7 19.5 24.0 42.1 18.2 35.4

Katipunan 58.9 57.1 6.0 4.4 10.2 7.7 49.0 68.8 49.9 64.3

La Libertad 43.0 45.0 7.2 7.5 16.7 16.7 31.2 54.9 32.6 57.4

Labason 54.7 48.9 6.6 6.0 12.1 12.2 43.8 65.5 39.1 58.7

Liloy 50.9 51.4 6.0 5.1 11.7 10.0 41.1 60.7 43.0 59.8

Manukan 58.9 68.2 5.6 5.4 9.5 7.9 49.6 68.1 59.4 77.1

Mutia 42.9 57.8 6.9 6.8 16.0 11.7 31.6 54.2 46.7 68.9

Piñan 45.8 55.5 5.9 5.4 12.8 9.7 36.1 55.4 46.7 64.4

Polanco 47.1 47.3 6.0 5.1 12.6 10.7 37.3 56.9 39.0 55.7


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Pres. Manuel A. Roxas 59.6 66.3 4.9 4.7 8.3 7.1 51.5 67.8 58.5 74.1

Rizal 47.0 37.3 6.4 5.4 13.7 14.5 36.4 57.5 28.4 46.1

Salug 54.8 60.2 6.3 5.3 11.5 8.7 44.5 65.2 51.6 68.8

Sergio Osmeña Sr. 59.3 65.8 5.5 5.6 9.2 8.4 50.3 68.3 56.7 74.9

Siayan 72.3 79.9 6.5 4.5 9.0 5.7 61.6 83.0 72.4 87.3

Sibuco 66.0 68.2 6.4 5.2 9.7 7.7 55.5 76.5 59.6 76.8

Sibutad 33.0 54.1 9.7 5.9 29.5 10.9 17.0 49.0 44.4 63.8

Sindangan 58.2 56.8 4.9 4.5 8.3 7.9 50.2 66.2 49.4 64.2

Siocon 59.8 63.6 6.3 5.8 10.5 9.2 49.4 70.1 54.0 73.2

Sirawai 65.5 61.7 7.1 6.2 10.8 10.1 53.9 77.1 51.4 71.9

Tampilisan 52.0 45.0 6.8 5.7 13.0 12.7 40.9 63.1 35.6 54.4

Jose Dalman (Ponot) 63.4 68.0 7.4 5.9 11.7 8.6 51.2 75.6 58.3 77.7

Gutalac 71.1 70.4 5.4 4.6 7.6 6.6 62.2 79.9 62.8 78.0

Baliguian 70.4 75.3 6.9 4.9 9.8 6.5 59.0 81.7 67.3 83.3

Godod 60.9 71.1 6.1 6.8 10.0 9.6 50.9 70.9 59.8 82.3

Bacungan (Leon T. Postigo) 63.9 66.0 5.7 6.2 8.8 9.4 54.6 73.2 55.7 76.2

Kalawit 60.4 65.8 7.4 6.8 12.2 10.3 48.3 72.5 54.6 77.0

Zamboanga del Sur Aurora 27.7 31.5 3.6 4.0 12.9 12.7 21.8 33.6 24.9 38.1

Bayog 29.2 43.6 5.0 6.1 17.1 14.0 21.0 37.4 33.6 53.6

Dimataling 37.1 46.8 6.3 6.8 17.0 14.5 26.7 47.4 35.6 57.9

Dinas 35.5 43.1 5.5 5.0 15.6 11.6 26.4 44.6 34.8 51.4

Dumalinao 28.4 38.8 5.1 5.2 18.0 13.3 20.0 36.9 30.3 47.2

Dumingag 35.6 42.8 5.1 4.6 14.3 10.7 27.2 44.0 35.3 50.3

Kumalarang 33.7 45.9 6.1 6.4 18.1 14.0 23.7 43.8 35.3 56.5

Labangan 29.6 33.9 5.2 4.6 17.4 13.5 21.1 38.1 26.4 41.5

Lapuyan 37.6 53.0 5.3 5.7 14.1 10.7 28.8 46.3 43.7 62.4

Mahayag 28.7 35.9 4.7 4.9 16.4 13.5 21.0 36.5 27.9 43.9

Margosatubig 27.7 39.0 6.2 6.8 22.5 17.4 17.5 37.9 27.8 50.2

Midsalip 37.6 52.7 5.4 6.4 14.4 12.2 28.7 46.5 42.1 63.2

Molave 24.0 26.5 4.1 4.1 17.0 15.6 17.3 30.7 19.7 33.2

Pagadian City 17.3 21.0 2.7 2.7 15.7 12.9 12.8 21.8 16.5 25.4

Ramon Magsaysay 25.8 36.6 4.6 5.2 17.9 14.1 18.2 33.4 28.1 45.1

San Miguel 27.7 41.6 5.5 6.4 19.8 15.4 18.7 36.7 31.0 52.2

San Pablo 30.8 47.0 4.9 5.8 15.9 12.4 22.8 38.8 37.4 56.6

Tabina 32.1 47.6 6.7 7.8 20.9 16.4 21.1 43.2 34.7 60.4

Tambulig 30.0 38.0 4.8 5.3 16.1 14.0 22.1 38.0 29.2 46.7

Tukuran 28.3 36.5 4.9 5.2 17.3 14.3 20.2 36.3 27.9 45.1

Zamboanga City 19.7 19.9 2.7 2.0 13.7 10.2 15.2 24.1 16.5 23.2

Lakewood 31.2 48.4 6.4 7.8 20.6 16.1 20.6 41.8 35.5 61.2

Josefina 24.4 40.9 5.5 7.4 22.3 18.1 15.5 33.4 28.8 53.1

Pitogo 30.7 49.8 5.3 7.9 17.2 15.8 22.0 39.4 36.8 62.7

Sominot 35.3 54.5 6.5 7.1 18.4 13.1 24.6 46.0 42.7 66.2

Vincenzo A. Sagun 34.7 46.5 6.1 6.3 17.7 13.4 24.6 44.7 36.2 56.8

Guipos 28.3 36.0 5.7 5.7 20.2 16.0 18.9 37.7 26.5 45.4

Tigbao 34.5 44.5 6.9 6.3 19.9 14.2 23.2 45.8 34.1 54.9

Zamboanga Sibugay Alicia 46.4 54.0 6.0 6.3 12.8 11.6 36.6 56.1 43.6 64.3

Buug 29.6 40.2 4.9 5.4 16.5 13.5 21.6 37.6 31.3 49.1

Diplahan 31.5 43.9 5.7 5.8 18.1 13.2 22.1 40.9 34.4 53.4

Imelda 38.2 42.4 6.4 5.4 16.6 12.8 27.8 48.7 33.5 51.4

Ipil 29.3 32.2 4.3 3.6 14.7 11.0 22.2 36.4 26.4 38.1

Kabasalan 39.6 36.7 5.7 4.0 14.3 10.8 30.3 48.9 30.2 43.3

Mabuhay 57.2 68.9 7.7 5.7 13.5 8.2 44.5 70.0 59.5 78.2

Malangas 34.8 40.5 5.2 5.0 15.0 12.3 26.2 43.4 32.3 48.7

Naga 40.8 36.4 5.8 4.1 14.3 11.3 31.2 50.4 29.6 43.2

Olutanga 41.3 61.7 6.8 6.8 16.4 11.0 30.2 52.5 50.5 72.8

Payao 46.5 63.3 6.0 7.0 12.9 11.1 36.6 56.4 51.7 74.8

Roseller Lim 41.1 51.2 5.8 4.9 14.2 9.6 31.5 50.7 43.1 59.4

Siay 42.6 48.3 6.3 4.7 14.8 9.7 32.2 52.9 40.6 56.0

Talusan 55.3 66.5 8.1 7.8 14.7 11.8 42.0 68.7 53.6 79.4

Titay 38.2 45.1 5.0 4.5 13.1 10.0 29.9 46.5 37.6 52.6

Tungawan 51.1 59.5 6.3 5.8 12.3 9.8 40.7 61.4 49.8 69.1

Isabela City Isabela City 22.4 23.0 3.4 2.9 15.0 12.6 16.9 28.0 18.2 27.8


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Region X Bukidnon Baungon 40.2 49.1 5.3 4.7 13.1 9.7 31.6 48.8 41.3 56.9

Damulog 42.4 52.2 4.9 4.9 11.6 9.4 34.3 50.5 44.1 60.2

Dangcagan 39.9 39.9 5.2 4.8 13.1 11.9 31.3 48.5 32.0 47.7

Don Carlos 39.5 42.0 4.0 3.3 10.0 7.9 33.0 46.1 36.5 47.4

Impasug-ong 43.0 46.1 5.5 4.7 12.7 10.1 34.0 52.0 38.5 53.8

Kadingilan 50.0 50.7 4.8 5.3 9.5 10.4 42.2 57.9 42.1 59.4

Kalilangan 33.8 51.3 5.3 5.1 15.7 9.9 25.1 42.5 42.9 59.7

Kibawe 48.1 46.8 4.0 3.2 8.2 6.9 41.5 54.6 41.5 52.0

Kitaotao 52.7 54.8 4.1 4.6 7.7 8.3 46.0 59.4 47.3 62.3

Lantapan 43.7 40.8 5.1 4.6 11.6 11.3 35.3 52.0 33.2 48.4

Libona 38.1 35.5 4.8 3.5 12.5 9.9 30.3 46.0 29.7 41.3

Malaybalay City 31.7 34.6 3.2 2.7 9.9 7.8 26.5 36.9 30.2 39.0

Malitbog 47.8 61.4 6.8 5.6 14.2 9.1 36.6 58.9 52.2 70.6

Manolo Fortich 31.6 33.5 3.2 3.3 10.1 9.9 26.3 36.9 28.1 39.0

Maramag 33.9 33.5 4.7 3.7 13.7 11.0 26.2 41.6 27.4 39.5

Pangantucan 41.6 53.2 4.2 3.8 10.0 7.1 34.7 48.4 47.0 59.4

Quezon 41.1 52.0 4.3 4.0 10.4 7.7 34.1 48.2 45.4 58.6

San Fernando 42.5 52.1 5.6 5.1 13.3 9.8 33.2 51.8 43.7 60.4

Sumilao 39.1 40.2 7.5 7.0 19.3 17.3 26.7 51.4 28.8 51.6

Talakag 53.8 50.3 4.5 3.9 8.3 7.8 46.5 61.2 43.8 56.7

Valencia City 35.1 35.8 3.5 3.1 9.9 8.5 29.4 40.8 30.8 40.9

Cabanglasan 50.5 45.2 4.1 5.2 8.1 11.4 43.7 57.2 36.7 53.7

Camiguin Catarman 47.4 58.4 6.4 4.3 13.4 7.4 36.9 57.8 51.3 65.5

Guinsiliban 47.5 45.7 6.2 5.4 13.0 11.7 37.4 57.6 36.9 54.5

Mahinog 36.5 45.9 5.0 4.0 13.6 8.7 28.3 44.7 39.3 52.4

Mambajao 37.4 36.2 4.9 4.1 13.1 11.4 29.3 45.4 29.4 43.0

Sagay 54.5 42.1 7.1 5.4 13.0 12.8 42.8 66.1 33.2 51.0

Lanao del Norte Bacolod 34.8 40.2 5.2 4.7 15.0 11.7 26.2 43.3 32.5 48.0

Baloi 33.2 48.3 4.5 3.9 13.5 8.0 25.9 40.6 42.0 54.7

Baroy 45.8 47.0 5.3 4.0 11.6 8.5 37.1 54.5 40.4 53.6

Iligan City 23.1 24.4 2.4 1.9 10.5 7.6 19.1 27.0 21.4 27.5

Kapatagan 42.5 47.6 4.8 3.3 11.4 7.0 34.6 50.5 42.2 53.1

Sultan Naga Dimaporo 48.9 59.9 4.4 3.8 9.0 6.4 41.6 56.2 53.6 66.2

Kauswagan 46.4 49.5 7.5 4.5 16.1 9.1 34.1 58.6 42.1 56.9

Kolambugan 38.4 41.7 4.5 3.3 11.6 8.0 31.1 45.7 36.2 47.2

Lala 35.1 37.0 4.0 3.1 11.3 8.5 28.6 41.7 31.9 42.1

Linamon 36.3 31.0 6.2 5.1 17.0 16.5 26.2 46.4 22.6 39.4

Magsaysay 46.6 59.2 4.5 3.8 9.6 6.4 39.2 53.9 52.9 65.4

Maigo 45.2 43.7 7.0 4.8 15.5 11.0 33.7 56.8 35.8 51.6

Matungao 37.8 59.3 5.7 5.6 15.1 9.5 28.4 47.2 50.0 68.5

Munai 42.5 67.5 5.3 3.6 12.5 5.4 33.7 51.3 61.5 73.4

Nunungan 51.9 67.9 4.5 4.1 8.7 6.1 44.4 59.4 61.1 74.7

Pantao Ragat 40.6 59.7 5.3 4.2 13.0 7.1 31.9 49.3 52.8 66.6

Poona Piagapo 48.3 66.8 4.7 3.9 9.7 5.8 40.6 56.1 60.4 73.1

Salvador 57.1 56.3 6.3 4.6 11.1 8.2 46.7 67.4 48.7 64.0

Sapad 45.9 62.0 5.4 4.5 11.8 7.3 37.0 54.8 54.6 69.5

Tagoloan 66.5 69.4 8.5 5.8 12.7 8.3 52.5 80.4 59.9 78.9

Tangcal 50.5 67.4 7.1 4.3 14.0 6.4 38.8 62.1 60.3 74.4

Tubad 34.4 48.3 3.9 3.1 11.3 6.4 28.0 40.8 43.2 53.4

Pantar 39.4 57.5 4.1 3.9 10.4 6.7 32.6 46.1 51.1 63.8

Misamis Occidental Aloran 39.1 42.7 6.0 2.9 15.3 6.9 29.2 49.0 37.9 47.5

Baliangao 48.5 37.7 5.8 4.0 12.0 10.6 39.0 58.1 31.1 44.3

Bonifacio 66.6 44.9 5.7 4.0 8.5 9.0 57.2 75.9 38.2 51.5

Calamba 38.7 41.4 5.6 3.3 14.5 7.9 29.5 48.0 36.0 46.8

Clarin 43.7 38.8 6.0 3.0 13.7 7.6 33.8 53.5 33.9 43.6

Concepcion 76.5 62.3 5.4 4.2 7.1 6.8 67.6 85.5 55.3 69.3

Jimenez 36.4 40.9 4.7 3.5 12.8 8.6 28.7 44.1 35.1 46.6


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Lopez Jaena 48.0 49.3 6.0 3.5 12.4 7.2 38.2 57.8 43.4 55.1

Oroquieta City 33.5 30.7 4.5 3.1 13.5 10.2 26.0 40.9 25.5 35.8

Ozamis City 30.6 29.8 4.3 2.4 14.1 8.1 23.5 37.7 25.8 33.7

Panaon 38.2 40.2 5.6 4.3 14.8 10.7 28.9 47.5 33.1 47.3

Plaridel 44.3 35.2 5.4 3.0 12.2 8.5 35.4 53.2 30.3 40.1

Sapang Dalaga 51.7 43.9 5.3 3.3 10.2 7.5 43.1 60.4 38.4 49.3

Sinacaban 42.7 38.9 5.8 3.4 13.6 8.8 33.1 52.2 33.2 44.5

Tangub City 63.8 43.1 5.9 2.5 9.3 5.8 54.1 73.5 39.0 47.2

Tudela 43.7 38.0 5.6 3.2 12.8 8.4 34.5 52.9 32.8 43.3

Don Victoriano Chiongbian 73.7 65.7 6.6 5.2 8.9 7.8 62.9 84.6 57.2 74.1

Misamis Oriental Alubijid 47.4 53.7 4.5 4.0 9.4 7.4 40.1 54.7 47.2 60.2

Balingasag 48.9 51.2 3.4 2.7 6.9 5.2 43.4 54.4 46.8 55.6

Balingoan 41.3 46.4 5.6 5.5 13.5 11.9 32.1 50.5 37.3 55.4

Binuangan 42.8 52.7 6.7 6.3 15.6 12.0 31.8 53.7 42.3 63.1

Cagayan De Oro City 19.4 22.8 2.7 2.2 13.7 9.8 15.0 23.8 19.1 26.4

Claveria 46.1 57.1 4.4 3.4 9.5 6.0 38.9 53.3 51.4 62.7

El Salvador 45.1 38.8 6.0 3.8 13.3 9.7 35.2 55.0 32.6 45.0

Gingoog City 44.1 48.7 3.1 2.4 7.0 4.8 39.0 49.2 44.8 52.5

Gitaguim 40.8 50.3 4.9 4.9 11.9 9.8 32.8 48.8 42.1 58.4

Initao 44.3 48.9 5.5 4.4 12.4 9.0 35.3 53.4 41.6 56.1

Jasaan 51.5 42.1 6.0 4.2 11.6 9.9 41.7 61.3 35.2 49.0

Kinoguitan 55.6 55.7 6.5 4.0 11.7 7.1 44.9 66.4 49.2 62.2

Lagonglong 47.9 49.9 5.1 4.6 10.6 9.2 39.5 56.3 42.4 57.4

Laguindingan 32.6 52.2 5.7 5.2 17.4 9.9 23.2 41.9 43.7 60.7

Libertad 46.2 55.5 7.4 5.5 15.9 10.0 34.1 58.2 46.4 64.6

Lugait 47.3 40.6 7.9 5.8 16.8 14.3 34.2 60.3 31.1 50.1

Magsaysay 73.9 60.3 6.8 3.9 9.2 6.4 62.6 85.1 53.9 66.7

Manticao 48.2 48.4 5.7 4.0 11.8 8.3 38.8 57.6 41.8 55.0

Medina 37.3 41.0 3.9 3.3 10.3 8.1 31.0 43.7 35.5 46.4

Naawan 48.6 45.7 5.8 5.1 11.9 11.1 39.1 58.2 37.4 54.0

Opol 30.4 31.1 3.9 3.2 12.7 10.2 24.1 36.8 25.9 36.2

Salay 48.8 47.1 5.5 4.7 11.2 9.9 39.8 57.8 39.4 54.7

Sugbongcogon 45.2 45.4 6.0 5.8 13.2 12.8 35.4 55.0 35.8 54.9

Tagoloan 39.6 35.9 4.8 4.7 12.2 13.1 31.6 47.5 28.2 43.7

Talisayan 49.0 48.2 4.9 3.8 10.0 8.0 40.9 57.0 41.9 54.5

Villanueva 40.9 40.5 5.8 3.9 14.1 9.7 31.3 50.4 34.0 46.9

Region XI Davao del Norte Asuncion (Saug) 38.4 41.0 4.2 4.2 11.0 10.2 31.5 45.3 34.1 47.9

Carmen 34.9 28.0 4.1 3.5 11.7 12.5 28.2 41.7 22.3 33.8

Kapalong 36.0 21.5 4.2 4.0 11.6 18.5 29.1 42.8 14.9 28.0

New Corella 38.4 38.2 4.3 4.4 11.1 11.6 31.4 45.4 30.9 45.5

Panabo City 24.5 14.8 2.7 2.2 11.2 14.8 19.9 29.0 11.2 18.4

Island Garden City of Samal 35.7 32.8 2.6 2.8 7.2 8.6 31.5 39.9 28.2 37.5

Santo Tomas 31.0 23.5 5.0 4.2 16.2 17.9 22.8 39.3 16.6 30.4

Tagum City 17.9 15.0 2.6 2.8 14.6 18.7 13.6 22.1 10.4 19.6

Talaingod 53.1 62.6 8.0 9.5 15.1 15.2 39.9 66.3 46.9 78.3

Braulio E. Dujali 26.9 40.8 5.5 7.2 20.3 17.5 17.9 35.8 29.1 52.6

San Isidro 37.9 53.6 4.9 5.5 12.8 10.3 29.9 45.9 44.5 62.7

Davao del Sur Bansalan 31.3 21.3 3.5 3.1 11.3 14.6 25.5 37.1 16.2 26.5

Davao City 15.7 13.2 1.4 1.3 9.0 9.4 13.4 18.0 11.2 15.3

Digos City 22.3 18.8 2.9 2.6 13.0 13.9 17.5 27.1 14.5 23.0

Hagonoy 32.8 22.9 4.0 3.2 12.2 14.0 26.2 39.3 17.6 28.1

Jose Abad Santos (Trinidad) 53.6 72.3 4.0 4.1 7.5 5.6 47.0 60.2 65.6 79.0

Kiblawan 45.3 57.4 3.4 3.8 7.5 6.5 39.7 50.9 51.2 63.6

Magsaysay 42.3 40.0 4.2 4.6 9.9 11.5 35.4 49.3 32.5 47.6

Malalag 39.6 41.2 4.7 4.0 11.9 9.6 31.9 47.3 34.7 47.8

Malita 53.0 63.8 4.1 3.5 7.7 5.5 46.3 59.8 58.0 69.6

Matanao 40.9 40.7 3.7 3.2 9.0 8.0 34.8 47.0 35.4 46.0

Padada 25.0 14.6 3.6 2.5 14.2 17.5 19.1 30.8 10.4 18.7

Santa Cruz 34.4 27.3 3.7 3.6 10.7 13.0 28.4 40.4 21.5 33.2

Santa Maria 47.5 48.5 3.8 4.4 8.0 9.0 41.2 53.7 41.4 55.7

Sulop 39.2 36.9 3.7 4.0 9.3 10.9 33.2 45.2 30.2 43.5

Sarangani 54.6 72.1 5.9 5.0 10.8 6.9 44.9 64.3 64.0 80.3

Don Marcelino 56.2 66.5 5.1 5.4 9.1 8.1 47.8 64.6 57.7 75.4


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Davao Oriental Baganga 28.3 44.0 3.3 4.6 11.5 10.5 23.0 33.7 36.4 51.6

Banaybanay 34.0 32.5 4.9 4.4 14.3 13.6 26.0 42.0 25.2 39.8

Boston 22.9 36.6 5.2 5.5 22.6 15.0 14.3 31.4 27.5 45.6

Caraga 37.8 58.0 4.6 4.1 12.3 7.0 30.2 45.5 51.3 64.7

Cateel 23.1 53.5 3.7 4.8 16.2 8.9 17.0 29.3 45.7 61.3

Governor Generoso 42.8 55.7 4.7 4.9 11.0 8.9 35.0 50.6 47.6 63.9

Lupon 36.8 42.9 4.3 4.6 11.8 10.6 29.6 43.9 35.4 50.4

Manay 39.2 58.7 4.5 4.9 11.6 8.4 31.8 46.7 50.6 66.7

Mati (Capital) 32.9 33.9 3.5 3.8 10.7 11.1 27.1 38.7 27.7 40.1

San Isidro 41.9 47.4 4.8 5.2 11.5 11.0 34.0 49.8 38.8 56.0

Tarragona 39.0 62.3 6.1 5.4 15.6 8.6 29.0 49.0 53.5 71.1

Compostela Valley Compostela 31.7 26.5 5.2 4.7 16.3 17.7 23.2 40.2 18.8 34.3

Laak (San Vicente) 36.5 54.7 3.3 4.3 9.0 7.8 31.1 41.9 47.6 61.7

Mabini (Doña Alicia) 31.9 29.8 4.6 4.1 14.3 13.9 24.4 39.4 23.0 36.6

Maco 35.2 30.6 3.1 2.6 8.9 8.6 30.0 40.4 26.2 34.9

Maragusan (San Mariano) 34.6 35.6 4.4 4.7 12.8 13.2 27.3 41.8 27.8 43.3

Mawab 34.7 32.7 4.9 4.5 14.2 13.8 26.6 42.8 25.2 40.1

Monkayo 25.7 32.9 3.1 4.2 11.9 12.7 20.7 30.7 26.1 39.8

Montevista 36.5 41.3 3.9 4.6 10.6 11.1 30.2 42.9 33.8 48.8

Nabunturan 27.2 28.3 3.1 3.9 11.5 13.7 22.0 32.3 21.9 34.7

New Bataan 30.7 42.0 4.8 5.5 15.8 13.0 22.7 38.7 33.0 51.0

Pantukan 34.4 28.3 4.7 4.8 13.8 17.0 26.6 42.2 20.4 36.1

Region XII North Cotabato Alamada 40.6 44.6 4.9 4.4 11.9 9.9 32.6 48.6 37.3 51.9

Carmen 39.4 50.4 3.9 5.7 9.9 11.2 32.9 45.8 41.1 59.7

Kabacan 30.6 35.0 3.8 3.3 12.4 9.5 24.3 36.8 29.6 40.5

Kidapawan City 20.0 19.2 3.3 2.6 16.5 13.7 14.5 25.4 14.9 23.5

Libungan 31.5 32.1 4.4 3.8 13.8 11.9 24.3 38.6 25.8 38.4

Magpet 43.9 36.7 3.8 3.8 8.5 10.3 37.7 50.1 30.4 42.9

Makilala 29.0 23.2 3.4 2.7 11.5 11.5 23.5 34.5 18.8 27.6

Matalam 35.8 34.9 3.6 3.2 10.1 9.1 29.8 41.7 29.7 40.1

Midsayap 31.5 33.0 2.3 2.9 7.2 8.6 27.8 35.3 28.3 37.7

M'lang 32.0 34.5 5.2 3.1 16.1 9.1 23.6 40.5 29.4 39.7

Pigkawayan 33.0 39.0 3.2 3.4 9.6 8.7 27.7 38.2 33.4 44.6

Pikit 51.9 48.5 4.6 3.6 8.9 7.3 44.3 59.5 42.7 54.4

President Roxas 36.7 35.3 4.5 3.8 12.3 10.8 29.3 44.1 29.0 41.6

Tulunan 34.7 38.2 3.7 3.7 10.5 9.6 28.7 40.7 32.2 44.3

Antipas 33.3 30.9 4.8 4.6 14.5 14.9 25.4 41.3 23.3 38.4

Banisilan 48.4 43.8 6.2 4.5 12.9 10.2 38.1 58.6 36.4 51.1

Aleosan 45.6 47.1 5.3 5.1 11.5 10.8 36.9 54.2 38.7 55.4

Arakan 45.8 48.0 4.2 4.7 9.2 9.8 38.9 52.7 40.3 55.8

South Cotabato Banga 30.6 31.3 3.5 3.6 11.3 11.4 24.9 36.2 25.4 37.1

General Santos 16.7 22.5 2.9 2.9 17.1 13.1 12.0 21.4 17.7 27.3

Koronodal City 19.9 21.7 3.0 2.7 15.2 12.5 14.9 24.8 17.2 26.1

Norala 26.3 33.1 3.5 4.1 13.3 12.5 20.5 32.0 26.3 39.9

Polomolok 21.2 22.8 3.8 3.4 17.9 15.1 15.0 27.4 17.1 28.5

Surallah 27.1 30.5 3.8 3.4 14.1 11.1 20.8 33.5 25.0 36.1

Tampakan 31.4 33.1 4.2 3.9 13.5 11.9 24.4 38.3 26.6 39.5

Tantangan 31.0 38.2 4.4 4.4 14.3 11.5 23.7 38.3 31.0 45.4

T'boli 49.8 52.7 4.9 3.8 9.9 7.3 41.7 58.0 46.4 59.0

Tupi 32.6 34.7 3.6 4.5 11.0 12.8 26.7 38.5 27.4 42.0

Santo Nino 28.1 32.1 5.3 4.7 19.0 14.5 19.3 36.8 24.5 39.8

Lake Sebu 55.1 52.8 7.3 5.6 13.2 10.5 43.1 67.1 43.7 62.0

Sultan Kudarat Bagumbayan 41.9 46.9 4.6 4.5 11.0 9.5 34.3 49.4 39.6 54.3

Colombio 45.5 54.4 5.6 5.7 12.4 10.5 36.2 54.7 45.0 63.8

Esperanza 31.3 33.2 5.3 3.5 17.0 10.5 22.5 40.1 27.5 39.0

Isulan 25.5 26.8 3.6 3.3 14.3 12.3 19.5 31.5 21.3 32.2

Kalamansig 47.3 50.6 4.9 4.9 10.3 9.6 39.2 55.3 42.6 58.6

Lebak 37.1 46.0 3.4 3.7 9.1 8.1 31.5 42.7 39.9 52.1

Lutayan 58.8 51.1 6.7 5.6 11.5 11.0 47.7 69.9 41.8 60.3

Lambayong 34.2 41.4 3.7 3.9 10.9 9.4 28.1 40.4 35.0 47.8

Palimbang 50.0 63.7 5.5 4.0 10.9 6.2 41.1 59.0 57.2 70.2

President Quirino 31.9 31.7 4.6 4.2 14.3 13.1 24.4 39.4 24.9 38.6

Tacurong City 19.6 18.5 2.8 2.5 14.3 13.6 15.0 24.2 14.3 22.6

Sen. Ninoy Aquino 40.9 47.6 3.8 4.6 9.2 9.6 34.7 47.1 40.1 55.1


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Sarangani Alabel 32.3 41.0 5.5 4.9 17.0 12.0 23.3 41.3 32.9 49.1

Glan 37.2 47.0 3.3 4.2 8.8 8.8 31.8 42.5 40.1 53.8

Kiamba 31.3 45.0 4.3 4.9 13.6 11.0 24.3 38.3 36.8 53.1

Maasim 37.7 52.2 5.0 5.8 13.2 11.2 29.5 45.9 42.6 61.8

Maitum 32.5 42.8 4.0 4.2 12.2 9.9 25.9 39.0 35.8 49.7

Malapatan 43.9 54.1 7.0 6.0 15.9 11.0 32.4 55.3 44.3 63.9

Malungon 37.9 45.3 3.8 4.1 10.0 9.0 31.7 44.1 38.6 52.1

Cotabato City Cotobato City 21.1 26.9 3.5 5.4 16.4 18.4 15.4 26.8 18.0 35.8

ARMM Basilan Lamitan 33.8 17.5 5.7 3.6 16.8 20.4 24.5 43.2 11.6 23.4

Lantawan 47.0 25.2 7.8 4.3 16.6 17.2 34.2 59.8 18.1 32.3

Maluso 48.0 39.2 8.1 6.7 17.0 17.0 34.6 61.4 28.2 50.1

Sumisip 49.6 29.4 6.8 4.9 13.7 16.8 38.4 60.7 21.3 37.5

Tipo-Tipo 38.7 28.0 8.9 6.3 23.1 22.4 24.0 53.4 17.7 38.3

Tuburan 50.7 37.6 12.3 7.4 24.2 19.7 30.5 70.9 25.5 49.8

Akbar 41.4 32.7 12.9 7.0 31.1 21.3 20.2 62.5 21.3 44.1

Al-barka 45.5 27.0 9.6 5.0 21.1 18.5 29.7 61.3 18.8 35.2

Hadji Mohammad Ajul 48.3 30.5 9.6 5.4 20.0 17.8 32.4 64.1 21.6 39.5

Ungkaya Pukan 47.0 26.5 10.0 5.8 21.4 21.8 30.5 63.5 17.0 35.9

Hadju Muhtamad - 35.5 - 6.6 - 18.6 - - 24.7 46.4

Tabuan-Lasa - 40.3 - 7.4 - 18.3 - - 28.1 52.4

Lanao del Sur Bacolod-Kalawi 33.6 29.4 9.1 4.1 27.0 13.9 18.7 48.5 22.7 36.1

Balabagan 28.7 34.4 6.8 4.7 23.7 13.6 17.5 39.8 26.8 42.1

Balindong (Watu) 36.8 42.9 9.1 7.0 24.6 16.3 21.9 51.7 31.4 54.4

Bayang 36.5 33.9 9.1 4.9 25.0 14.5 21.5 51.5 25.8 42.0

Binidayan 25.3 36.8 7.2 5.7 28.4 15.5 13.5 37.1 27.4 46.2

Bubong 35.0 42.6 10.1 7.0 28.7 16.5 18.5 51.6 31.0 54.1

Butig 30.6 37.1 7.6 6.1 24.8 16.4 18.1 43.0 27.1 47.1

Ganassi 30.2 34.8 7.1 4.9 23.4 14.0 18.6 41.9 26.8 42.8

Kapai 41.7 43.0 11.2 6.5 26.8 15.1 23.3 60.0 32.3 53.7

Lumba-Bayabao (Maguing) 24.3 38.8 5.6 5.7 22.9 14.8 15.2 33.4 29.3 48.2

Lumbatan 34.0 36.8 10.8 4.7 31.9 12.8 16.1 51.8 29.1 44.5

Madalum 27.9 32.6 6.1 4.5 21.9 13.9 17.9 37.9 25.1 40.0

Madamba 23.3 46.7 6.4 7.0 27.5 15.0 12.7 33.8 35.2 58.3

Malabang 28.8 37.7 6.8 5.1 23.5 13.7 17.7 39.9 29.2 46.2

Marantao 33.0 29.2 7.7 4.7 23.4 16.0 20.3 45.6 21.5 36.9

Marawi City 27.6 34.5 4.6 4.7 16.6 13.7 20.0 35.1 26.7 42.3

Masiu 32.8 39.4 7.7 6.9 23.6 17.6 20.1 45.5 28.0 50.7

Mulondo 37.1 54.2 10.0 10.2 26.8 18.8 20.7 53.4 37.4 71.0

Pagayawan (Tatarikan) 38.8 43.5 9.8 7.3 25.2 16.7 22.7 54.9 31.5 55.5

Piagapo 38.6 37.0 9.0 4.4 23.2 11.9 23.9 53.4 29.7 44.2

Poona Bayabao (Gata) 31.9 28.3 8.1 4.7 25.4 16.5 18.6 45.3 20.6 36.0

Pualas 25.6 27.5 6.2 4.7 24.0 17.0 15.5 35.7 19.8 35.2

Ditsaan-Ramain 33.0 41.9 7.5 6.1 22.6 14.6 20.7 45.2 31.9 51.9

Saguiaran 37.4 33.2 9.8 4.4 26.3 13.4 21.2 53.6 25.9 40.5

Tamparan 30.3 39.9 7.1 5.8 23.5 14.6 18.6 42.0 30.3 49.5

Taraka 30.9 38.0 8.4 5.4 27.2 14.3 17.1 44.7 29.1 46.9

Tubaran 40.3 44.4 9.0 7.3 22.4 16.4 25.5 55.1 32.4 56.4

Tugaya 39.7 45.3 11.8 7.9 29.7 17.4 20.4 59.1 32.3 58.3

Wao 27.6 25.5 6.3 4.2 22.8 16.4 17.2 38.0 18.6 32.3

Marogong 46.1 46.2 11.0 7.5 23.8 16.2 28.0 64.2 33.9 58.6

Calanogas 39.8 53.9 9.6 10.0 24.1 18.6 24.1 55.6 37.4 70.4

Buadiposo-Buntong 31.0 38.6 8.6 5.8 27.6 15.0 17.0 45.1 29.1 48.1

Maguing 33.0 29.9 7.3 4.1 22.1 13.6 21.0 45.1 23.2 36.6

Sultan Gumander 40.5 47.3 10.2 6.8 25.1 14.5 23.8 57.3 36.1 58.6

Lumbayanague 30.1 55.7 7.9 9.7 26.3 17.4 17.1 43.1 39.8 71.6

Bumbaran 34.1 37.8 7.9 6.3 23.2 16.6 21.0 47.1 27.4 48.1

Tagoloan II 45.7 59.3 13.3 9.3 29.0 15.6 23.9 67.5 44.0 74.5

Kapatagan 29.4 32.3 7.7 4.8 26.3 14.8 16.7 42.1 24.5 40.1

Sultan Dumalondong 46.0 51.4 15.6 10.5 33.9 20.4 20.4 71.6 34.1 68.7

Lumbaca-Unayan 34.8 36.0 11.0 6.9 31.6 19.1 16.7 52.9 24.7 47.3


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Maguindanao Ampatuan 36.1 51.9 9.8 6.2 27.1 11.9 20.0 52.2 41.7 62.1

Buldon 45.1 53.4 6.9 6.9 15.3 12.9 33.8 56.5 42.0 64.7

Buluan 47.3 50.7 14.3 10.6 30.3 20.8 23.7 70.9 33.4 68.1

Datu Paglas 47.2 48.4 8.0 5.2 16.9 10.8 34.0 60.3 39.8 57.0

Datu Piang 56.2 52.5 9.0 11.4 16.0 21.6 41.4 71.0 33.8 71.2

Datu Odin Sinsuat (Dinaig) 44.3 45.0 6.6 4.5 14.9 10.0 33.4 55.2 37.6 52.4

Shariff Aguak (Maganoy) 54.2 56.9 8.9 8.4 16.4 14.8 39.6 68.7 43.1 70.8

Matanog 52.5 43.7 10.5 7.3 20.0 16.7 35.3 69.7 31.7 55.7

Pagalungan 53.0 46.7 8.9 6.2 16.9 13.2 38.2 67.7 36.6 56.9

Parang 36.1 42.0 6.8 5.6 18.9 13.4 24.9 47.3 32.7 51.3

Sultan Kudarat (Nuling) 50.1 50.0 5.6 3.6 11.2 7.2 40.9 59.4 44.1 55.9

Sultan Sa Barongis (Lambayong) 61.8 61.1 10.1 6.1 16.3 10.0 45.2 78.3 51.1 71.1

Kabuntalan (Tumbao) 51.3 62.8 8.9 6.4 17.3 10.1 36.7 65.9 52.3 73.3

Upi 49.0 34.8 7.7 5.1 15.7 14.8 36.3 61.7 26.3 43.2

Talayan 56.7 50.9 9.1 5.7 16.1 11.1 41.7 71.6 41.6 60.3

South Upi 53.5 42.9 10.0 6.9 18.7 16.2 37.1 70.0 31.5 54.3

Barira 46.7 39.9 8.5 5.3 18.2 13.2 32.7 60.8 31.2 48.6

Gen. S. K. Pendatun 62.6 61.0 8.1 6.1 12.9 10.1 49.4 75.9 50.9 71.1

Mamasapano 59.0 55.8 10.1 7.5 17.2 13.5 42.3 75.7 43.4 68.2

Talitay 63.0 51.9 9.4 7.9 14.9 15.1 47.6 78.5 39.0 64.9

Pagagawan 50.7 53.0 9.0 6.0 17.8 11.4 35.9 65.6 43.1 62.9

Paglat 62.4 61.1 14.5 7.3 23.3 12.0 38.4 86.3 49.1 73.2

Sultan Mastura 48.3 44.4 8.7 6.4 18.0 14.5 34.0 62.5 33.8 55.0

Guindulungan 60.5 64.5 8.7 6.5 14.4 10.0 46.2 74.8 53.9 75.2

Datu Saudi-Ampatuan 53.2 43.4 8.3 7.9 15.6 18.3 39.6 66.9 30.3 56.5

Datu Unsay 63.0 47.1 10.8 9.9 17.1 21.1 45.3 80.7 30.7 63.4

Datu Abdullah Sangki 43.4 51.0 10.1 7.0 23.2 13.7 26.8 60.0 39.5 62.5

Rajah Buayan 55.5 53.9 11.2 6.2 20.2 11.6 37.0 74.0 43.7 64.2

Datu Blah T. Sinsuat 56.9 48.7 10.5 6.3 18.5 13.0 39.6 74.1 38.2 59.1

Datu Anggal Midtimbang 52.5 57.0 11.4 8.0 21.8 14.0 33.7 71.3 43.8 70.1

Mangudadatu 62.6 56.9 13.4 7.0 21.4 12.4 40.5 84.6 45.3 68.5

Pandag 61.6 66.8 11.1 7.7 17.9 11.5 43.4 79.8 54.1 79.4

Northern Kabuntalan 47.4 41.2 7.8 6.1 16.3 14.8 34.7 60.2 31.1 51.2

Datu Hoffer Ampatuan - 49.1 - 8.1 - 16.4 - - 35.8 62.4

Datu Salibo - 52.5 - 6.0 - 11.4 - - 42.6 62.3

Shariff Saydona Mustapha - 51.2 - 7.8 - 15.2 - - 38.4 64.0

Sulu Indanan 54.2 42.7 6.7 5.4 12.3 12.8 43.2 65.1 33.7 51.6

Jolo 43.3 46.1 12.2 7.8 28.1 17.0 23.3 63.3 33.3 59.0

Kalingalan Caluang 65.0 48.3 10.9 7.5 16.8 15.6 47.0 83.0 35.9 60.7

Luuk 70.2 47.9 8.0 6.9 11.4 14.5 57.0 83.4 36.5 59.4

Maimbung 57.2 51.9 9.5 5.6 16.5 10.8 41.6 72.7 42.7 61.2

Hadji Panglima Tahil (Marunggas) 60.9 53.2 14.8 10.5 24.4 19.7 36.5 85.3 36.0 70.4

Old Panamao 55.3 55.9 9.4 7.0 17.0 12.5 39.9 70.7 44.4 67.4

Pangutaran 50.9 49.3 10.1 5.9 19.9 12.0 34.2 67.6 39.5 59.0

Parang 54.7 53.2 7.4 5.1 13.5 9.5 42.6 66.8 44.8 61.5

Pata 52.8 52.6 10.2 7.4 19.4 14.1 35.9 69.6 40.4 64.7

Patikul 44.6 37.0 8.2 5.3 18.4 14.3 31.1 58.1 28.3 45.6

Siasi 59.7 46.1 8.9 4.6 14.9 9.9 45.1 74.3 38.6 53.6

Talipao 51.2 59.8 6.9 5.1 13.4 8.5 39.9 62.4 51.4 68.1

Tapul 57.7 52.4 9.7 5.9 16.9 11.4 41.7 73.7 42.6 62.2

Tongkil 69.8 51.2 8.5 6.4 12.2 12.5 55.8 83.8 40.6 61.8

Panglima Estino (New Panamao) 51.9 68.7 9.4 8.0 18.1 11.6 36.5 67.4 55.6 81.8

Lugus 54.4 50.1 10.7 6.4 19.7 12.7 36.8 72.0 39.6 60.6

Pandami 57.0 49.2 9.7 6.3 17.1 12.7 41.0 73.0 38.9 59.5

Omar - 50.8 - 9.9 - 19.4 - - 34.6 67.0


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Tawi-tawi Panglima Sugala (Balimbing) 52.8 44.9 9.5 6.6 18.0 14.6 37.1 68.5 34.1 55.7

Bongao 39.4 27.7 6.2 4.1 15.8 15.0 29.2 49.7 20.8 34.5

Mapun (Cagayan De Tawi-Tawi) 46.2 35.2 8.1 5.7 17.5 16.2 32.9 59.6 25.8 44.6

Simunul 32.4 30.4 8.2 5.7 25.3 18.6 18.9 45.9 21.1 39.7

Sitangkai 36.6 31.7 9.1 7.5 24.8 23.8 21.7 51.6 19.3 44.1

South Ubian 43.7 36.4 7.8 4.7 17.8 12.8 30.9 56.5 28.7 44.0

Tandubas 45.2 35.3 8.4 6.1 18.6 17.4 31.3 59.0 25.2 45.4

Turtle Islands 43.4 28.6 18.9 13.0 43.6 45.4 12.3 74.5 7.2 49.9

Languyan 40.0 38.0 7.0 6.5 17.4 17.1 28.5 51.4 27.3 48.7

Sapa-Sapa 45.7 37.2 8.7 5.3 19.1 14.2 31.4 60.0 28.6 45.9

Sibutu 34.7 38.9 7.8 6.9 22.6 17.6 21.8 47.6 27.6 50.2

Caraga Agusan del Norte Buenavista 34.1 38.0 3.3 3.2 9.7 8.5 28.6 39.5 32.7 43.2

Butuan City 24.6 27.6 2.2 1.8 8.9 6.3 21.0 28.2 24.7 30.4

Cabadbaran 28.0 28.4 3.4 2.7 12.1 9.6 22.5 33.6 23.9 32.9

Carmen 37.1 40.6 5.1 5.2 13.8 12.7 28.7 45.6 32.1 49.1

Jabonga 48.6 45.7 5.0 3.7 10.3 8.1 40.3 56.8 39.6 51.8

Kitcharao 39.0 39.9 6.9 4.0 17.7 10.0 27.7 50.3 33.3 46.4

Las Nieves 52.3 53.0 5.3 3.5 10.1 6.6 43.6 60.9 47.3 58.8

Magallanes 34.2 28.6 4.6 4.3 13.3 15.1 26.7 41.7 21.5 35.7

Nasipit 23.0 28.3 2.9 3.1 12.7 10.9 18.2 27.8 23.2 33.3

Santiago 55.5 47.7 7.0 4.9 12.5 10.2 44.0 66.9 39.7 55.7

Tubay 39.6 39.2 5.0 4.1 12.6 10.5 31.4 47.8 32.4 46.0

Remedios T. Romualdez 38.3 41.0 5.0 4.7 13.1 11.5 30.0 46.6 33.3 48.7

Agusan del Sur Bayugan 46.1 48.4 3.1 3.1 6.7 6.3 41.0 51.2 43.4 53.4

Bunawan 60.8 54.2 5.4 3.8 8.9 7.1 51.9 69.8 47.9 60.5

Esperanza 66.9 61.9 3.6 2.7 5.4 4.4 61.0 72.7 57.4 66.4

La Paz 74.2 66.7 4.7 3.9 6.3 5.9 66.5 81.9 60.2 73.2

Loreto 70.3 56.9 4.0 3.9 5.7 6.9 63.7 76.8 50.5 63.3

Prosperidad 53.5 52.8 3.6 3.1 6.7 5.8 47.6 59.4 47.8 57.8

Rosario 56.0 48.2 5.3 4.8 9.5 10.0 47.3 64.7 40.3 56.1

San Francisco 41.9 39.7 2.9 2.6 6.8 6.4 37.2 46.6 35.5 43.9

San Luis 69.7 62.0 3.7 2.8 5.3 4.5 63.6 75.7 57.4 66.6

Santa Josefa 54.0 53.3 4.4 3.7 8.1 6.9 46.9 61.2 47.3 59.4

Talacogon 56.1 58.0 4.9 4.0 8.8 6.8 48.0 64.2 51.5 64.4

Trento 42.6 49.1 5.0 5.0 11.7 10.1 34.3 50.8 40.9 57.2

Veruela 63.0 58.5 4.5 3.4 7.1 5.8 55.6 70.4 52.9 64.0

Sibagat 63.3 59.4 3.8 3.7 6.0 6.2 57.1 69.5 53.3 65.5

Surigao del Norte Alegria 47.6 57.2 4.9 4.9 10.4 8.5 39.4 55.7 49.1 65.2

Bacuag 35.3 50.6 5.3 5.4 15.0 10.7 26.6 44.1 41.7 59.5

Basilisa (Rizal) 65.1 55.7 4.3 4.1 6.5 7.3 58.1 72.1 49.0 62.4

Burgos 46.9 53.2 6.3 6.0 13.5 11.2 36.5 57.3 43.4 63.0

Cagdiano 60.6 55.6 4.8 5.1 7.8 9.2 52.8 68.5 47.2 64.0

Claver 38.8 49.8 4.2 4.7 10.9 9.5 31.8 45.7 42.0 57.6

Dapa 44.0 52.2 3.7 3.7 8.3 7.1 38.0 50.1 46.1 58.4

Del Carmen 40.7 58.9 3.8 4.2 9.3 7.1 34.5 47.0 52.0 65.7

Dinagat 55.1 57.6 5.1 5.1 9.2 8.9 46.7 63.4 49.2 66.1

General Luna 50.6 55.4 4.8 4.3 9.5 7.8 42.7 58.5 48.3 62.5

Gigaquit 45.2 59.6 5.1 4.8 11.4 8.0 36.7 53.6 51.8 67.5

Libjo (Albor) 59.8 54.1 5.0 4.7 8.3 8.7 51.6 68.0 46.4 61.8

Loreto 29.9 54.2 4.0 5.1 13.2 9.4 23.4 36.4 45.8 62.6

Mainit 42.5 57.0 4.5 4.1 10.7 7.2 35.0 49.9 50.3 63.8

Malimono 51.2 50.3 4.9 5.1 9.6 10.2 43.1 59.3 41.8 58.7

Pilar 54.4 62.8 5.3 4.4 9.7 6.9 45.7 63.0 55.6 69.9

Placer 30.6 47.7 3.5 4.2 11.5 8.9 24.8 36.4 40.7 54.7

San Benito 48.2 62.6 7.1 5.1 14.8 8.2 36.4 59.9 54.2 71.1

San Francisco (Anao-Aon) 44.6 48.8 4.3 4.4 9.6 8.9 37.5 51.6 41.7 56.0

San Isidro 49.6 51.7 6.0 5.6 12.2 10.8 39.7 59.6 42.5 60.9

Santa Monica (Sapao) 45.4 52.4 5.0 4.2 11.0 8.1 37.2 53.7 45.5 59.4

Sison 41.1 52.1 5.2 4.9 12.6 9.5 32.6 49.6 44.0 60.2

Socorro 54.0 52.1 5.7 5.9 10.6 11.4 44.6 63.4 42.3 61.8

Surigao City 32.4 40.1 2.9 3.0 8.9 7.4 27.7 37.2 35.2 44.9

Tagana-an 49.6 50.4 4.3 5.1 8.7 10.1 42.5 56.6 42.0 58.7

Tubajon 47.6 56.3 5.3 5.4 11.1 9.6 38.9 56.3 47.4 65.2

Tubod 30.6 47.8 4.4 4.5 14.4 9.4 23.3 37.8 40.4 55.2

San Jose 49.2 46.7 4.9 4.4 9.9 9.4 41.1 57.2 39.5 54.0


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009



Lower

Limit

Upper

Limit

Lower

Limit

Upper

Limit

Surigao del Sur Barobo 42.5 45.7 4.7 4.4 11.1 9.6 34.7 50.2 38.4 52.9

Bayabas 44.3 39.4 5.5 5.2 12.5 13.2 35.2 53.4 30.9 48.0

Bislig 26.6 34.2 4.3 4.9 16.0 14.3 19.6 33.6 26.1 42.2

Cagwait 40.5 39.4 5.9 4.9 14.7 12.3 30.7 50.2 31.4 47.4

Cantilan 20.0 25.7 3.7 2.8 18.3 10.9 14.0 26.1 21.1 30.3

Carmen 30.6 34.6 4.7 5.2 15.2 14.9 22.9 38.3 26.1 43.1

Carrascal 32.0 32.7 3.6 3.9 11.3 11.9 26.1 37.9 26.3 39.1

Cortes 42.0 36.4 6.3 4.9 14.9 13.5 31.7 52.2 28.3 44.4

Hinatuan 43.3 43.6 3.7 3.1 8.6 7.1 37.2 49.4 38.5 48.6

Lanuza 41.2 35.1 4.4 4.4 10.7 12.4 33.9 48.4 27.9 42.3

Lianga 29.2 37.0 4.1 4.2 13.9 11.3 22.5 35.8 30.1 43.9

Lingig 45.2 48.9 4.7 4.3 10.4 8.8 37.5 52.9 41.8 56.0

Madrid 25.0 33.0 3.1 3.7 12.4 11.1 19.9 30.1 27.0 39.0

Marihatag 48.3 50.3 5.5 4.4 11.3 8.8 39.3 57.2 43.0 57.5

San Agustin 44.7 49.9 5.3 4.0 11.7 8.0 36.1 53.4 43.3 56.5

San Miguel 50.1 50.5 4.7 3.7 9.4 7.3 42.4 57.8 44.4 56.5

Tagbina 47.1 48.0 4.6 3.7 9.7 7.8 39.6 54.6 41.9 54.2

Tago 41.5 37.5 4.4 3.2 10.7 8.5 34.2 48.8 32.2 42.7

Tandag 24.3 26.3 3.1 2.7 12.7 10.3 19.2 29.4 21.8 30.7

Source: NSCB/World Bank/AusAID Project on the Generation of the 2006 and 2009 Small Area Estimates of Poverty


ProvinceRegion


Municipality/City


200920062009200620092006

2006 2009


NSCB TECHNICAL STAFF*

JOSE RAMON G. ALBERT Secretary General

LINA V. CASTRO

Assistant Secretary General

REGINA S. REYES JESSAMYN O. ENCARNACION

Acting Director III Director III

MARIA FE M. TALENTO ESTRELLA R. TURINGAN Chief, Statistical Programs, Policies, and Advocacy Division

SEVERA B. DE COSTO BERNADETTE B. BALAMBAN Chief, Statistical Standards Chief, Poverty, Labor, Human Development, and Classifications Division

and Gender Statistics Division

Director IV

VIVIAN R. ILARINA EDWARD EUGENIO P. LOPEZ-DEE

Chief (concurrent), Production Chief, Integrated Accounts Division

VIVIAN R. ILARINA CYNTHIA S. REGALADO

Chief, Expenditure Accounts Division Chief, Economic Indicators and Satellite

Accounts Division

CANDIDO J. ASTROLOGO, JR. AGNES V. CAPULE

Director IV OIC, Financial Services Division

RAYMUNDO J. TALENTO

Chief (concurrent), Population, Health

and Nutrition, and Nutrition, Housing and

MANAGEMENT SERVICES

SOCIAL STATISTICS OFFICE STATISTICAL PROGRAMS, POLICIES

AND STANDARDS OFFICE

INFORMATION CENTER NATIONAL STATISTICAL

ECONOMIC STATISTICS OFFICE

Human Resource and International

CANDIDO J. ASTROLOGO, JR.

EMALYN P. PINEDA

SUBNATIONAL STATISTICS OFFICE

Affairs Division

Director IV (concurrent)

Education Statistics Division

RUBEN V. LITAN

Head, Information Management Services Unit

EDWIN U. ARAGON

Head, Information Technology Unit

as of December 2013

Accounts Division


GENERATION OF THE 2006 AND 2009 MUNICIPAL AND CITY LEVEL POVERTY ESTIMATES PROJECT STAFF

NSCB Project Management Committee

Chair

ROMULO A. VIROLA (November 2011 - June 2013) JOSE RAMON G. ALBERT (September 2012 – December 2013)

Members

LINA V. CASTRO JESSAMYN O. ENCARNACION RAYMUNDO J. TALENTO REGINA S. REYES

CANDIDO J. ASTROLOGO, JR.

Lead Technical Staff BERNADETTE B. BALAMBAN

MILDRED B. ADDAWE

Technical Staff

Administrative Staff

AGNES V. CAPULE TERESITA M. ALMARINES

RUFINA P. DAYOT FELY V. COLLADO EDWIN U. ARAGON

DENNIS E. SAN DIEGO

SONNY U. GUITTIEREZ NOEL S. NEPOMUCENO

ANDREA S. BAYLON VIRGINA M. BATHAN ALBERT A. GARCIA

EDILBERTO M. SURIAGA

MANUEL POQUIZ EDGARD E. ENRADO

EDGARDO A. GUEVARRA JOSE A. DAYOT

Project Manager JESSAMYN O. ENCARNACION

MECHELLE M. VIERNES

ANNA JEAN G. CASAÑAS ANDREA JANE B. BIBARES

JOSEPH ALBERT NIÑO M. BULAN

LEI ISABEL S. DOMINGO


The World Bank

Australian Government

Project Technical Adviser DR. ROMULO A. VIROLA

Project Consultant

DR. ZITA VJ. ALBACEA

The NSCB thanks Mr. Gino Regalado, Mr. Joseph Addawe, Ms. Eva Paran, Ms. Gloria Guarin, Ms. Riza Moraleta, Mr. Rosendo Aya-ay, and Ms. Marina Araneta for their assistance in this Project.

Documents

in cooperation with Australian Government