Beyond the Numbers

For welfare and development, Geography matters!

Certainly, statistics covering other dimensions of progress – whether economic, social, or environmental, are critical to give the relevant information to policy- and decision-makers to institute positive changes for the Philippine society.

Beyond the Numbers
For welfare and development, Geography matters!

by Jose Ramon G. Albert, Ph.D.1                                              Filipino Version


In several NSCB web articles, we have explained about traditional measures of economic performance, particularly the Gross Domestic Product (GDP), which in per capita terms was once viewed as a measure of progress of society.  However, in more recent times, the international community has recognized that conventional measures of (economic) progress do not necessarily capture welfare, especially since welfare has various dimensions.  The former King and current King of Bhutan espouse even the measurement of Gross National Happiness.  Other measures of welfare, including subjective measures, are being examined not just by non-government organizations in the Philippines, but also by other countries as well.   Countries in Europe are also beginning to measure quality of life and welfare either through various indicators, or a composite indicator.

The United Nations Development Programme (UNDP), in its first Human Development Report in 1990, introduced the Human Development Index (HDI),  “a composite measure of health, education and income … as an alternative to purely economic assessments of national progress, such as GDP growth.”2  The UNDP regarded the HDI as a breakthrough with “the creation of a single statistic which was to serve as a frame of reference for both social and economic development.”  It is more popularly referred to as a measure of the “quality of life.”

Last 29 July 2013, the Human Development Network (HDN)3 in cooperation with the NSCB released the 2012/2013 Philippine Human Development Report (PHDR), with funding support from the UNDP. 

The 2012/2013 Report contains the latest 2009 provincial HDI.  For trend analysis, it also presents back estimates for 1997, 2000, 2003 and 2006 using the updated methodology, showcasing the provinces’ progress in human development over time.

The HDI methodology and its components

The HDI, as mentioned earlier, measures the average achievement in three basic dimensions of human development:  longevity or a long and healthy life, access to knowledge, and a decent standard of living.  These dimensions are measured by a set of indicators that are aggregated into indices.  The HDI sets a minimum and a maximum for each dimension, expressed as a value between 0 (lowest) and 1 (highest). 

Since its inception in 1990, the global HDI estimation methodology has gone through a number of refinements – either a change in the indicator used to measure each dimension or a new functional form on how the index is computed.
 
The latest revision in the global methodology was undertaken in 2010.4  The current methodology measures the health component of the HDI using life expectancy at birth.  The knowledge component of the HDI is now measured by combining the expected years of schooling for a school-age child entering school today with the mean years of prior schooling for adults aged 25 and older.  The income measurement uses purchasing-power-adjusted per capita Gross National Income (GNI).  The GNI was used as it includes some remittances, providing a more accurate economic picture of many developing countries.

Another modification is the use of the geometric mean instead of the arithmetic mean in aggregating the indicators.5 The former was preferred over the latter as it assumes complementarity across dimensions; the latter, on the other hand, treats dimensions as perfect substitutes.  Hence, under the current methodology, the higher the level of achievement in one, the less it can compensate for the others.

Translating the global methodology to compile the Philippine HDI, in general, the same methodology was used except for a slight deviation in the computation of the income index. As the income component is per capita purchasing power comparable over time and space, in the Philippine context, real per capita income in NCR 2009 pesos was used as reference.6

Human Development in the Provinces

Top ten provinces in terms of HDI are all in Luzon

In 2009, Benguet recorded the highest HDI with 0.849. (Figure 1) In fact, Benguet is the only province in the country which is categorized as having a high level of human development, using the United Nations classification as basis. (Table 1)7

Also in the top 10 are Batanes (0.789), Rizal (0.734), Cavite (0.709), Bulacan (0.699), Bataan (0.698), Laguna (0.695), Nueva Vizcaya (0.678), Ilocos Norte (0.641), and Pampanga (0.634).  (Figure 1)

Nine of the 10 provinces with the lowest HDI levels are all in Mindanao

Sulu posted the lowest HDI at 0.266 followed by Maguindanao (0.300), Tawi-Tawi (0.310), Zamboanga Sibugay (0.353), Agusan del Sur (0.354), Davao Oriental (0.356), Sarangani (0.371), Zambonga del Norte (0.384), Masbate (0.406), and Lanao del Sur (0.416).  All provinces in the Autonomous Region in Muslim Mindanao (ARMM) are in the bottom 10, except for Basilan.   (Figure 2)

Majority of the provinces with medium level of human development are in Luzon; those with low level of human development are mostly in Mindanao

Twenty-five out of 41 medium-HDI range provinces or 61.0% are in Luzon while 17 out of 37 low-HDI range provinces or 45.9% are in Mindanao.  (Table 1 and Figure 3)

Geography matters

The country’s physical space is certainly diverse, being an archipelago comprised of more than 7,000 islands.  As of 31 March 2013, the Philippines has 17 regions8… 80 provinces9… 143 cities… 1,491 municipalities… 42,028 barangays.10 

Based on the 2012/2013 PHDR, factors related to geography “explain” about 34.3% of the variation in provincial HDI.  It is considered a deep determinant of human development, intrinsically linked through human health, agricultural prospects, access between locations, and specific political institutions.  However, differences in location should not translate into differences in human opportunities.

The 2012/2013 Report also cited that geography can have its greatest impacts when traditional agriculture dominates a local economy.  In the Philippines, the incidence of income poverty among farmers is 36.7 percent – this is 10.2 percentage points higher than the general population (26.5 percent).  (Table 2)

Eight of the 15 provinces in the poorest cluster (or 53.3 percent) also belong to the bottom ten provinces with lowest HDI levels.  (Table 3)  On the other hand, all the 10 provinces in the least poor cluster, excluding Metro Manila, are included in the top ten with the highest HDI levels. (Table 4)  The relationship of poverty incidence with HDI may be expected with income being one of the components of HDI. 

Also to be noted is that while previous reports have examined various social aspects of welfare, such as education, the 2012/2013 Report for the first time also linked many health, particularly threats from worm infections and other neglected tropical diseases, to geography! 

Certainly, statistics covering other dimensions of progress – whether economic, social, or environmental, are critical to give the relevant information to policy- and decision-makers to institute positive changes for the Philippine society. 

Considering the findings in the 2012/2013 PHDR that geography matters – the important need for the generation of statistics with the relevant geographic disaggregation cannot be overemphasized.  This is to ensure that design of policies and programs, delivery of interventions are correctly geared towards achieving a better quality of life for the entire Philippine society.  While one can always point out that inequalities have persisted in society from time immemorial, and they will likely be there regardless of how developed we become, the recognition that geography matters should help us improve opportunities, especially in areas which need more attention, so that ultimately, no one will be left behind when the country grows.

Reactions and views are welcome thru email to the author at jrg.albert@nscb.gov.ph.

 

 

Filipino Version

 

Para sa kapakanan at kaunlaran, mahalaga ang Geograpiya (Geography)

by Jose Ramon G. Albert, Ph.D.1

Sa ilang NSCB web articles na lumabas, ipinaliwanag namin ang tungkol sa pangkaraniwang pagsukat sa takbo ng ekonomiya ng bansa, tulad ng Gross Domestic Product (GDP), kung saan ang ang pag-akyat ng “per capita” nito sa pagdaan ng panahon ay syang sinasabing sukatan ng pag-unlad ng lipunan. Subalit, sa panahon ngayon, hindi kasama sa pagkilala ng international community, sa tradisyunal na pagsukat ng kaunlaran ang kapakanan o kagalingan ng tao dahilan sa malawak nitong kahulugan. Kaya nga  maging ang dati at kasalukuyang hari ng bansang Bhutan ay nanguna sa promosyon ng Gross National Happiness bilang sukatan din ng kaunlaran. Pinag-aaralan ngayon di lamang ng mga NGO’s sa Pilipinas kundi maging sa ibang bansa ang iba pang sukatan ng kagalingan o kapakanan ng tao, kasama na dito ang ilang mga subjective na sukatan. May ilang bansa sa Europa ang nagsisimula nang sukatin ang kalidad ng pamumuhay at kagalingang pantao sa pamamagitan ng ibat-ibang indicators o composite indicators.

Sa kanilang kauna-unahang Human Development Report noong 1990, ipinakilala ng United Nations Development Program (UNDP) ang Human Development Index (HDI), isang  pinagsanib na sukatan ng antas ng kalusugan, edukasyon at kita bilang alternatibong pamamaraan sa pagsusuri sa pambansang kaunlaran tulad ng pagtaas ng GDP. Itinuring ng UNDP ang HDI bilang malaking pangyayari sa paglikha ng nag-iisang estadistika na magsisilbing batayan sa pagkilala sa socio at ekonomikong kaunlaran. Mas lalo din itong nakilala bilang sukatan ng kalidad ng pamumuhay.

Noong July 29, 2013, inilabas ng Human Development Network (HDN) sa teknikal na tulong ng NSCB at suportang pinansyal ng UNDP, ang  2012/2013 Philippine Human Development Report (PHDR).  Ang ulat na ito ay naglalaman ng 2009  Provincial Human Development Index (PHDI).

Kabilang sa ulat na ito ang ginawang pagtaya sa HDI para sa mga taong 1997, 2000, 2003 at 2006 gamit ang bagong “methodology”.  Ginawa ito para sa mga taong ito upang mapag-aralan ang progreso o pagbabago ng human development ng mga lalawigan sa bansa sa mga nakalipas na taon.


Ang pamamaraan ng pagsukat sa HDI at iba pang bagay ukol rito

Ang HDI ay ang pinagsamang sukatan o batayan ng kaunlarang pang tao (human development).  Sinusukat nito ang performance ng isang lalawigan sa tatlong bahagi (dimension) ng human development: mahaba at malusog na buhay (longevity), pagkakaroon ng karunungan (access to knowledge), at maayos na uri ng pamumuhay (decent standard of living). Ang pagsukat ay ginagamitan ng mga piling indicators na pinagsama-sama upang maging “indices”. Sa bawat dimension ng HDI ay may nakatakdang pinakamaliit at pinakamalaking halaga sa pagitan ng bilang na 0  (pinakamababa) at 1 (pinakamataas). 

Simula nang ginawa ito noong 1990, ang global HDI estimation methodology ay sumailalim sa maraming pagbabago tulad ng pagpapalit sa mga ginamit na indicators sa bawat dimension o kaya naman ay pagbabago ng pamamaraan sa pagtaya ng HDI.

Ang pinakabagong pagpapalit sa global methodology ng HDI ay isinagawa noong 20104.  Sa ilalim ng kasalukuyang methodology, ang antas ng kalusugan ay sinusukat sa pamamagitan ng life expectancy at birth; ang antas ng edukasyon o karunungan ay sinusukat ng pinagsamang “expected years of schooling” para sa mga batang dapat nag-aaral sa ngayon, at sa “mean years of prior schooling” para sa mga matatandang may edad 25 pataas.   Sa kabilang dako, ang pagsukat sa kita ay ginagamitan ng   purchasing-power-adjusted per-capita Gross National Income (GNI). Ginamit ang GNI dahil kabilang rito ang ilang remittrances na syang nagpapamalas ng mas tamang larawan ng ekonomiya ng ilang umuunlad na bansa. 

Isa pang pagbabago ay ang paggamit sa “geometric mean” sa halip na “arithmetic mean” sa pagsasama-sama ng mga indicators. Pinili ang “geometric mean” dahilan sa pagtanggap nito ng pagkakaiba o pagkasalungat ng bawat dimensions. Sa kabilang dako, itinuturing ng “arithmetic mean” ang dimensions bilang perfect substitute.  Kaya, sa ilalim ng kasalukuyang methodology, ang mas mataas na antas ng “achievement o performance” ng isa, ay mangangahulugan ng mas mababang antas para sa iba.

Sa paggamit ng global methodology sa pagbuo ng HDI para sa Pilipinas, kaparehong methodology ang ginamit maliban sa maliit na pagbabago sa pagtaya ng “income index”. Ang income component ay gumagamit ng per capita puchasing power na pwedeng maikukumpara sa ibat ibang panahon at lugar.  Sa Pilipinas, ang ginamit na “reference6” ay ang real per capita income sa NCR 2009 pesos.


Human Development sa mga lalawigan

Sa Luzon makikita ang 10 pangunahing lalawigan na may mataas na HDI level

Noong 2009, ang lalawigan ng Benguet ang nagtala ng pinakamataas na HDI sa antas na 0.849. (Figure 1). Sa katunayan, ang Benguet ang tanging lalawigan sa bansa na sinasabing mayroong pinakamataas na antas ng human development ayon sa classification ng United Nations. Kabilang din sa top 10 ay ang mga lalawigan ng Batanes (0.789), Rizal (0.734), Cavite (0.709), Bulacan (0.699), Bataan (0.698), Laguna (0.695), Nueva Vizcaya (0.678), Ilocos Norte (0.641), atPampanga (0.634).  (Figure 1)

Siyam sa 10 lalawigan na may mababang HDI lahat ay nasa Mindanao

Ang lalawigan ng Sulo ang nagtala ng pinakamababang HDI sa bilang na 0.266. Sumunod dito ang Maguindanao(0.300), Tawi-Tawi (0.310), Zamboanga Sibugay (0.353), Agusan del Sur (0.354), Davao Oriental (0.356), Sarangani (0.371), Zambonga del Norte (0.384), Masbate (0.406), at Lanao del Sur (0.416).  Maliban sa Basilan, lahat ng lalawigan sa Autonomous Region of Muslim Mindanao (ARMM) ay nasa pinakamababang sampu. (Figure 2)

Karamihan sa mga nasa “medium level” ng human development ay nasa Luzon, samantalang yong nasa low level naman ay nasa Mindanao.

Dalawamput lima sa 41 medium HDI range provinces o 61% ay nasa Luzon samantalang 17 sa 37 low HDI range  provinces ay nasa Mindanao. (Table 1 and Figure 3)

Mahalaga ang Geograpiya

Bilang isang archipelago, tunay na malawak ang kalupaan ng bansa na binubo ng mahigit sa 7 libong isla.  Ayon sa pinakabagong tala noong March 2013, ang Pilipinas ay may 17 rehiyon… 80 lalawigan… 143 lungsod  1,491 munisipyo… 42,028 barangays

Ayon sa 2012/2013 PHDR, ang mga bagay na may kaugnayan sa geograpiya ang nagbibigay paliwanang sa 34.3% na di pagkakapareho sa HDI ng mga lalawigan. Ang geograpiya ay itinuturing na may kinalaman sa human development lalo na ukol sa kalusugan ng tao, kayamanang pang agrikultura, kalsada at political institutions. Subalit, ang pagkakaiba sa lokasyon ay hindi nangangahulugan ng pagkakaiba rin sa pagkakataong umunlad ang tao.

Binanggit din ng ulat na ito na ang geograpiya  ay may malaking impluwensya kung ang tradisyunal na agrikultura ang nagdodomina sa isang lokal na ekonomiya. Sa Pilipinas, ang incidence ng poverty sa panig ng mga magsasaka ay 36.7% - mas mataas ito ng 10.2% sa general population na 26.5%. (Table 2)

Walo sa labinglimang lalawigan (53.3 percent) na nasa poorest cluster ang kasama rin sa 10 lalawigan na may pinakamababang HDI levels. (Table 3)  Sa kabilang dako, lahat ng 10 lalawigan sa least poor cluster, maliban sa Metro Manila, ay kasama rin sa 10 na may pinakamataas na HDI levels. (Table 4)  Ang pagkakaroon ng ugnayan ng poverty incidence sa HDI ay inaasahan dahil sa ang kita ay isang bahagi ng HDI.    

Bukod pag-aaral ukol sa ibat ibang aspetong sosyal ng kapakananan o kagalingan ng tao tulad ng edukasyon, dapat ding malaman, na sa 2012/2012 Report, iniuugnay din sa geograpiya ang mga banta sa kalusugan tulad impeksyong dulot ng bulati sa katawan at iba pang tropical diseases.  

Patunay ito na ang estadistika na bumubuo sa iba pang bahagi ng kaunlaran- ekonomikal, sosyal o environmental man, ay kritikal sa pagbibigay ng mahalagang impormasyon sa mga policy at decision makers upang makapagdulot ng positibong pagbabago sa lipunang Pilipino.

Dahil sa resulta ng 2012/2013 PHDR, lumalabas na walang pasubali, na mahalaga ang geograpiya at ang paglikom sa estadistika na may kasamang geographic disaggregation o mga datos  mula sa iba-ibang lugar. Ito ay para maseguro na ang mga gagawing programa at  kaukulang solusyon ng gobyerno ay naaayon tungo sa pagkamit ng mas mahusay na uri ng buhay para sa buong lipunang Pilipino. Bagamat, masasabing nanatili pa rin ang hindi pagkakapantay pantay sa lipunan mula pa noong panahon, at ito ay mananatili, gaano mang pag unlad ang mangyari  sa atin, ang katotohanan ay nagsasabi na mahalaga ang geograpiya upang malaman natin kung paano natin magagamit ang magandang mga pagkakataon, lalo na sa mga lugar na dapat pagtuunan ng higit na pansin upang sa ganoon walang sinumang maiwan sa pag-unlad ng bansa.

Kung kayo ay may reaksyon o ibang pananaw ukol sa artikulong ito, mangyari lamang na sumulat sa may akda sa email address na: jrg.albert@nscb.gov.ph.

________________________________

1 Secretary General of the National Statistical Coordination Board (NSCB). The NSCB, a statistical agency functionally attached to the National Economic and Development Authority (NEDA), is the highest policy making and coordinating body on statistical matters in the Philippines. Immediately prior to his appointment at NSCB, Dr. Albert was a Senior Research Fellow at the Philippine Institute for Development Studies, a policy think tank attached to NEDA. Dr. Albert finished summa cum laude with a Bachelor of Science degree in Applied Mathematics from the De La Salle University in 1988. He completed a Master of Science in Statistics from the State University of New York at Stony Brook in 1989 and a Ph.D. in Statistics from the same university in 1993. He is also a past President of the Philippine Statistical Association, a Fellow of the Social Weather Stations, and an Elected Regular Member of the National Research Council of the Philippines.

This article was co-written by Ms. Evangeline M. Paran, Ms. Herlita G. Caraan, Ms. Ma. Eileen A. Berdeprado, and Ms. Jane G. Balondo, Regional Statistical Coordination Unit (RSCU) VIII Head, RSCU XII Head, Statistical Coordination Officer (SCO) III, and Information Officer I, respectively of the NSCB. This article was translated in Filipino by Mr. Ruben V. Litan of the NSCB. The authors thank Dir. Candido J. Astrologo, Jr., Dir. Jessamyn O. Encarnacion, and Mr. Sonny U. Gutierrez of the NSCB for the assistance in the preparation of the article. The views expressed in the article are those of the authors and do not necessarily reflect those of the NSCB and its Technical Staff.

2 http://hdr.undp.org/en/statistics/hdi/

3 The National Statistical Coordination Board (NSCB) Technical Staff (TS) provided assistance to the HDN in the launching of the Report.

4 Under the previous HDI formula, health was measured by life expectancy at birth; education or “knowledge” by a combination of the adult literacy rate and school enrolment rates (for primary through university years); and income or standard of living by GDP per capita adjusted for purchasing-power parity (PPP US$).

5 This new functional form addresses the flaw of the previous linear aggregation formula. The arithmetic mean treats dimensions as perfect substitutes. That is, the rate at which one dimension can offset another is constant, so that regardless of the level of achievement, the level of priority to be given to a dimension does not change. In contrast, the geometric mean assumes complementarity across dimensions.

6 A more detailed presentation on the refined global methodology as well as its translation for the estimation in the Philippines is available at the NSCB website: http://www.nscb.gov.ph/hdi/2009/Dr.%20Monsod's%20Presentation% 20on%20the%20Refined%20HDI%20Methodology.pdf

7 Using the UN classification on the level of human development:  HDI ranging from 0.8 to 1.0 is considered high, medium if its value ranges from 0.5 to 0.799 and low if below 0.5.

8 By regional clustering, Luzon is composed of NCR, CAR, Regions I, II, III, IV-A, IV-B  and V. On the other hand, Visayas is composed of Regions VI, VII, and VIII. Mindanao, the second largest island group next to Luzon, is composed of Regions IX, X,  XI,  XII,  Caraga and  ARMM.

9 A total of 39 provinces are in Luzon, 16 provinces in the Visayas and 25 provinces in Mindanao.

10 http://www.nscb.gov.ph/activestats/psgc/NSCB_PSGC_SUMMARY_March_2013.pdf


1

Source:  2012/2013 Philippine Human Development Report, Human Development Network

 

1

Source:  2012/2013 Philippine Human Development Report, Human Development Network



Source:  2012/2013 Philippine Human Development Report, Human Development Network

Table 1. Provinces Categorized According to HDI Range, 2009

High Region HDI Rank Medium Region HDI Rank Low Region HDI Rank
Benguet CAR 0.849 1 Batanes Region II 0.789 2 Albay Region V 0.498 43
        Rizal Region IV-A 0.734 3 North Cotabato Region XII 0.498 44
        Cavite Region IV-A 0.709 4 Palawan Region IV-B 0.498 45
        Bulacan Region III 0.699 5 Bukidnon Region X 0.494 46
        Bataan Region III 0.698 6 Antique Region VI 0.493 47
        Laguna Region IV-A 0.695 7 Sorsogon Region V 0.492 48
        Nueva Vizcaya Region II 0.678 8 Camarines Sur Region V 0.491 49
        Ilocos Norte Region I 0.641 9 Southern Leyte Region VIII 0.489 50
        Pampanga Region III 0.634 10 Abra CAR 0.488 51
        Batangas Region IV-A 0.632 11 Quezon Region IV-A 0.482 52
        Cagayan Region II 0.632 12 Bohol Region VII 0.482 53
        Biliran Region VIII 0.630 13 Oriental Mindoro Region IV-B 0.478 54
        Aurora Region III 0.630 14 Misamis Occidental Region X 0.477 55
        Misamis Oriental Region X 0.626 15 Siquijor Region VII 0.471 56
        Iloilo Region VI 0.619 16 Camarines Norte Region V 0.469 57
        Quirino Region II 0.616 17 Ifugao CAR 0.465 58
        La Union Region I 0.615 18 Surigao del Sur Caraga 0.463 59
        South Cotabato Region XII 0.612 19 Western Samar Region VIII 0.461 60
        Catanduanes Region V 0.606 20 Compostela Valley Region XI 0.461 61
        Isabela Region II 0.603 21 Basilan ARMM 0.460 62
        Davao del Sur Region XI 0.602 22 Aklan Region VI 0.460 63
        Zambales Region III 0.600 23 Eastern Samar Region VIII 0.450 64
        Zamboanga del Sur Region IX 0.590 24 Sultan Kudarat Region XII 0.448 65
        Ilocos Sur Region I 0.582 25 Surigao del Norte Caraga 0.442 66
        Cebu Region VII 0.582 26 Mt. Province CAR 0.432 67
        Tarlac Region III 0.573 27 Northern Samar Region VIII 0.432 68
        Leyte Region VIII 0.566 28 Romblon Region IV-B 0.428 69
        Pangasinan Region I 0.556 29 Lanao del Sur ARMM 0.416 70
        Marinduque Region IV-B 0.544 30 Masbate Region V 0.406 71
        Agusan del Norte Caraga 0.541 31 Zamboanga del Norte Region IX 0.384 72
        Kalinga CAR 0.540 32 Sarangani Region XII 0.371 73
        Negros Occidental Region VI 0.537 33 Davao Oriental Region XI 0.356 74
        Lanao del Norte Region X 0.537 34 Agusan del Sur Caraga 0.354 75
        Occidental Mindoro Region IV-B 0.529 35 Zamboanga Sibugay Region IX 0.353 76
        Capiz Region VI 0.522 36 Tawi-Tawi ARMM 0.310 77
        Guimaras Region VI 0.512 37 Maguindanao ARMM 0.300 78
        Nueva Ecija Region III 0.511 38 Sulu ARMM 0.266 79
        Camiguin Region X 0.510 39        
        Apayao CAR 0.509 40        
        Davao del Norte Region XI 0.506 41        
        Negros Oriental Region VII 0.504 42        

Source: National Statistical Coordination Board

 

Table 2. Poverty Incidence for Farmers, by Region: 2009

Region 2009
Poverty Incidence Coefficient of Variation 90% Confidence Interval
Lower Limit Upper Limit
Philippines  36.7 2.2 35.4 38.1
NCR        
CAR 30.0 9.2 25.4 34.5
Region I 21.3 10.7 17.6 25.1
Region II 13.0 10.4 10.8 15.3
Region III 12.0 13.0 9.5 14.6
Region IVA 24.5 10.3 20.4 28.7
Region IVB 33.8 8.3 29.2 38.3
Region V 41.3 5.5 37.5 45.0
Region VI 28.8 11.2 23.5 34.1
Region VII 53.8 5.4 49.0 58.6
Region VIII 46.7 5.7 42.3 51.1
Region IX 54.0 5.6 49.0 59.0
Region X 52.3 5.1 47.9 56.6
Region XI 44.3 9.9 37.1 51.5
Region XII 38.0 8.3 32.8 43.2
ARMM 46.4 6.4 41.5 51.3
Caraga 49.7 6.2 44.6 54.9

          Source: National Statistical Coordination Board

 

Table 3. HDI Levels of Provinces in the Poorest Cluster: 2009

Province 2009
Clustera/ Poverty Incidence  90% Confidence Interval HDI Rank
Lower Limit Upper Limit
Zamboanga del Norte 1 46.0 52.9 59.8 0.384 72
Agusan del Sur 1 43.5 51.2 58.9 0.354 75
Surigao Del Norte 1 43.1 47.9 52.8 0.442 66
Eastern Samar 1 37.6 45.8 54.1 0.450 64
Maguindanao 1 37.7 44.6 51.6 0.300 78
Zamboanga Sibugay 1 35.4 43.2 50.9 0.353 76
Romblon 1 36.3 43.0 49.8 0.428 69
Masbate 1 36.6 42.5 48.3 0.406 71
Davao Oriental 1 36.4 42.5 48.6 0.356 74
Northern Samar 1 32.4 41.7 51.0 0.432 68
Bohol 1 33.6 41.0 48.4 0.482 53
Saranggani 1 34.0 40.7 47.3 0.371 73
Sulu 1 33.0 39.3 45.5 0.266 79
Lanao del Norte 1 31.9 39.0 46.1 0.537 33
Camarines Sur 1 33.8 38.7 43.6 0.491 49

a/ Where cluster 1 indicates the bottom (poor) cluster of provinces
Source: National Statistical Coordination Board

 

Table 4. HDI Levels of Provinces in the Least Poor Cluster: 2009

Province 2009
Clustera/ Poverty Incidence  90% Confidence Interval HDI Rank
Lower Limit Upper Limit
Ilocos Norte 5 6.1 9.2 12.3 0.641 9
Bataan 5 4.8 7.4 10.0 0.698 6
Nueva Vizcaya 5 2.9 6.7 10.5 0.678 8
Pampanga 5 4.9 6.7 8.4 0.634 10
Rizal 5 4.2 6.5 8.7 0.734 3
Laguna 5 4.1 5.9 7.6 0.695 7
Bulacan 5 3.7 4.8 5.9 0.699 5
Cavite 5 3.1 4.5 5.9 0.709 4
Benguet 5 2.0 4.0 6.1 0.849 1
Batanes 5 0.0 0.0 0.0 0.789 2

a/ Where cluster 5 indicates the least poor cluster of provinces
Source: National Statistical Coordination Board

 

 


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Posted: 13 September 2013

 


 

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