Philippines Basic Education Public Expenditure Review

Report No: AUS0000920

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Philippines Basic Education

Public Expenditure Review

October 1, 2020

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Macroeconomics, Trade and Investment

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© 2019 The World Bank

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Currency Equivalents

(Exchange Rate Effective September 3, 2020)

Currency Unit = Philippine Peso

USD 1 = PhP 48.59

Fiscal Year

January 1 – December 31

Abbreviations and Acronyms

4Ps Pantawid Pamilyang Pilipino Program IPIN Implicit Price Index

A&E Accreditation and Equivalency JHS Junior High School

APIS Annual Poverty Indicators Survey LFS Labor Force Survey

ALS Alternative Learning System LGU Local Government Unit

BESF Budget of Expenditures and Sources of

Financing

MDG Millennium Development Goals

BEFF Basic Education Facilities Fund MOOE Maintenance and Other Operating

Expenses

BEPER Basic Education Public Expenditure Review NAT National Achievement Test

BESRA Basic Education Sector Reform Agenda NER Net Enrollment Rate

BLGF Bureau of Local Government Finance NEP National Expenditure Program

CCT Conditional Cash Transfer PDP Philippine Development Plan

CHED Commission on Higher Education PETS-

QSDS

Public Education Expenditure Tracking

and Quantitative Service Delivery Survey

CSR Cohort Survival Rate PISA Programme for International Student

Assessment

DBM Department of Budget Management PTR Pupil-Teacher Ratio

DepEd Department of Education PSA Philippine Statistics Authority

DOF Department of Finance PST Process Skills Test

DOST Department of Science and Technology RA Republic Act

DPWH Department of Public Works and Highways SAAODB Statement of Appropriations, Allotments,

Obligations, Disbursements, and Balances

EBEIS Enhanced Basic Education Information

System

SBM School-Based Management

EFA Education For All SDG Sustainable Development Goals

ESC Education Service Contracting SEF Special Education Fund

FIES Family Income and Expenditure Survey SHS Senior High School

GAA General Appropriations Act STR Student-Teacher Ratio

GDP Gross Domestic Product SUC State Universities and Colleges

GNI Gross National Income TESDA Technical Education and Skills

Development Authority

GER Gross Enrollment Rate TIMSS Trends in International Mathematics and

Science Study

Table of Contents

Executive Summary ..................................................................................................................................... i

Introduction ............................................................................................................................................... vii

Chapter 1 – Performance of the Philippine Basic Education Sector 2009-18 ....................................... 1

Access to Schooling.................................................................................................................................. 1

Trends in Internal Efficiency .................................................................................................................... 5

Quality of Basic Education: Trends in Learning Achievement .............................................................. 12

Conclusion .............................................................................................................................................. 15

Chapter 2 – Equity in Basic Education ................................................................................................... 19

Equity in Access ..................................................................................................................................... 19

Equity in School Quality ........................................................................................................................ 28

Equity in Learning Achievement ............................................................................................................ 32

Conclusion .............................................................................................................................................. 34

Chapter 3 – Recent Trends in Public and Private Spending on Basic Education ............................... 35

Overall Trends in Government Spending ............................................................................................... 35

Factors in Government Spending Trends ............................................................................................... 38

Local Government Spending on Basic Education .................................................................................. 42

Private Spending on Basic Education ..................................................................................................... 44

Public Expenditure Efficiency ................................................................................................................ 47

Conclusion .............................................................................................................................................. 49

Chapter 4 –Main Findings and Policy Implications .............................................................................. 50

Annex 1 – Data and Methods ................................................................................................................... 54

Annex 2 – Reference Tables for Chapters 1 and 2 ................................................................................. 61

Annex 3 – Reference Tables for Chapter 3 ............................................................................................. 65

References .................................................................................................................................................. 89

List of Figures

Figure 1: DepEd Organizational Structure ................................................................................................... ix Figure 2: Flow of Public Funds from National Level to School Level ........................................................ xi Figure 3: Total Enrollment, SY 2009-2010 and SY 2017-2018 ................................................................... 2 Figure 4: Enrollment Rates in Private and Public Schools, SY 2009-2010 to SY 2017-2018 ..................... 3 Figure 5: Total Number of Schools by Level, SY 2010-2011 to SY 2017-2018 .......................................... 5 Figure 6: Number of Teachers and Teacher Ratios, SY 2009-2010 to SY 2017-2018 ................................. 5 Figure 7: Cohort Survival and Dropout Rates by Level, SY 2009-2010 to SY 2017-2018 .......................... 6 Figure 8: Grade-to-Grade Survival Rates, 2007-2017 .................................................................................. 7 Figure 9: Completion Rates by Level, SY 2009-2010 to SY 2017-2018 ..................................................... 9 Figure 10: Transition Rates by Level, SY 2011-2012 to SY 2017-2018 .................................................... 10 Figure 11: Pre-Primary Enrollment Rates in East Asia, 2017 .................................................................... 11 Figure 12: International Comparisons of Elementary and Secondary NER and Completion Rates, 2017 . 11 Figure 13: GER and Per Capita Income in East Asia, 2017 ....................................................................... 12 Figure 14: Grade 6 NAT Mean Percentage Scores, SY 2008-2009 to SY 2015-2016 ............................... 13 Figure 15: Grade 10 NAT Mean Percentage Scores, SY 2008-2009 to SY 2014-2015 ............................. 13 .................................................................................................................................................................... 14 Figure 16: Grade 6 and Grade 10 NAT Mean Percentage Scores, SY 2016-2017 ..................................... 14 Figure 17: Mean Nominal Pay for Wage Earners (in PhP), by Education Level and Age ......................... 16 Figure 18: Returns to Different Levels of Education .................................................................................. 16 Figure 19: Rate of Private Returns to Different Levels of Education, by Gender ...................................... 17 Figure 20: Educational Attainment Levels Among Wage Earners, by Gender .......................................... 17 Figure 21: Socioemotional Skills and Labor Income .................................................................................. 18 Figure 22: Kindergarten Enrollment Rates, by Region, SY 2010-2011 and SY 2017-2018 ...................... 19 Figure 23: Elementary Enrollment Rates, by Region, SY 2009-2010 and SY 2017-2018 ......................... 20 Figure 24: JHS Enrollment Rates, by Region, ............................................................................................ 21 SY 2009-2010 and SY 2017-2018 .............................................................................................................. 21 Figure 25: SHS Enrollment Rates, by Region, ........................................................................................... 21 SY 2016-2017 and SY 2017-2018 .............................................................................................................. 21 Figure 26: Elementary Completion and Cohort Survival Rates, by Region, SY 2009-2010 and SY 2017-

2018 ............................................................................................................................................................ 22 Figure 27: JHS Completion and Cohort Survival Rates, ............................................................................ 22 by Region, SY 2009-2010 and SY 2017-2018 ........................................................................................... 22 Figure 28: Correlations Between Poverty Incidence and Various Education Indicators, by Region, 2015 23 Figure 29: Gross and Net Enrollment Rates, by Income Quintile, 2017 .................................................... 23 Figure 30: Participation Rates in Public and Private Schools, by Income Quintile, 2017 .......................... 24 Figure 31: Grade-to-Grade Survival Rates for Poorest (Quintile 1) and Richest (Quintile 5) .................... 25 Households, 2007-2017 .............................................................................................................................. 25 Figure 32: Gross and Net Enrollment Rates, by Gender, SY 2000-2010 to SY 2017-2018 ....................... 26 Figure 33: Cohort Survival and Completion Rates, by Gender, SY 2000-2010 to SY 2017-2018 ............ 26 Figure 34: Percentage of Children of Junior High School Age (12-15 years) and ..................................... 27 Senior High School Age (16-17) Who Are Not in School, by Income Quintile and Gender, 2017 ........... 27 Figure 35: School Sizes, by Region, SY 2017-2018 ................................................................................... 29 Figure 36: Pupil- and Student-Teacher Ratios, by Region, SY 2009-2010 and SY 2017-2018 ................. 30 Figure 37: Pupil- and Student-Classroom Ratios, by Region, SY 2011-2012 and SY 2016-2017 ............. 31 Figure 38: Proportion of Teachers with Teacher III and Master Teacher Positions, .................................. 32 by Region, SY 2017-2018 ........................................................................................................................... 32 Figure 39: NAT Mean Percentage Scores by Region, SY 2008-2009 and SY 2014-2015 ......................... 33 Figure 40: Government Expenditure on Education as % of GDP, 2009-2017 ........................................... 35 Figure 41: Government Expenditure on Education as % of GDP in Selected Countries, 2017 ................. 36 Figure 42: Distribution of DepEd Spending by Level of Education, SY 2009-2010 to SY 2017-2018 ..... 37

Figure 43: Real Per Pupil Government Spending on Education and .......................................................... 38 Various Education Indicators, by Region, 2017 ......................................................................................... 38 Figure 44: DepEd Real Spending and Budget Utilization Rate, 2009-2017 ............................................... 40 Figure 45: Shares of Expense Classes in DepEd Appropriations and Obligations, 2009-2017 .................. 40 Figure 46: Nominal and Real Total Government Spending on Basic Education, 2009-2017 .................... 42 Figure 47: Nominal and Real Per Pupil Government Spending on Basic Education, 2009-2017 .............. 42 Figure 48: Share of Education Expenditure in Total Household Expenditure, ........................................... 45 by Income Quintile, 2012 and 2015 ............................................................................................................ 45

List of Tables

Table 1: Process Skills Test for Grades 1 to 10 Teachers, 2012-2017........................................................ 15 Table 2: Total Government Spending on Basic Education, 2009 to 2017 .................................................. 36 Table 3: Government Spending Per Pupil on Basic Education, 2009 to 2017............................................ 37 Table 4: Sectoral Distribution of National Government Spending, as %, .................................................. 39 Net of Net Lending and Interest Payments, 2009-2019 .............................................................................. 39 Table 5: Nominal and Real Per Pupil Government Spending on Basic Education, by Region, 2017 ........ 43 Table 6: Average of Household Expenditures on Education ...................................................................... 44 per School-Age Household Member (in 2006 NCR prices) ....................................................................... 44 Table 7: Average Number of School-Age Children per Household, by Income Quintile, 2012 and 2015 45 Table 8: Share of Education Expenditure in Total Household Expenditure, by Region, 2015 ................... 45 Table 9: Definitions of Key Public Expenditure Terms in the Philippines ................................................. 56 Table 10: Internal Efficiency Indicators, by Level, SY 2009-2010 to SY 2017-2018 ............................... 61 Table 11: Kindergarten GER and NER, by Gender, SY 2010-2011 to SY 2017-2018 .............................. 61 Table 12: Elementary GER and NER, by Gender, SY 2009-2010 to SY 2017-2018 ................................. 61 Table 13: JHS GER and NER, by Gender, SY 2009-2010 to SY 2017-2018 ............................................ 61 Table 14: SHS GER and NER, by Gender, SY 2016-2017 to SY 2017-2018 ............................................ 62 Table 15: Grade 6 NAT Overall Mean Percentage Scores, by Region, SY 2008-2009 to SY 2016-2017 . 62 Table 16: Grade 8/10 NAT Overall Mean Percentage Scores, by Region, SY 2008-2009 to SY 2016-2017

.................................................................................................................................................................... 62 Table 17: Achievement Score Analysis Results ......................................................................................... 63 Table 18: Summary Statistics (Achievement Score Analysis) ................................................................... 64 Table 19: Government Spending on Education, 2009-2017 ....................................................................... 65 Table 20: Government Spending on Education, in Constant Prices, 2009-2017 ........................................ 65 Table 21: Government Spending on Education as % of GDP, 2009-2017 ................................................. 66 Table 22: Government Spending on Education as % of National Government Spending,......................... 66 Net of Net Lending and Interest Payments, 2009-2017 .............................................................................. 66 Table 23: Sectoral Distribution of National Government Spending, Obligations Basis, ............................ 67 Net of Net Lending and Interest Payments, 2009-2017 .............................................................................. 67 Table 24: LGU Spending on Basic Education, 2009-2017 ......................................................................... 68 Table 25: Total Government Education Appropriations, Allotments, and Obligations, 2009-2017 .......... 68 Table 26: Per Pupil Nominal Spending, by Region, 2009-2017 ................................................................. 69 Table 27: Per Pupil Real Spending, by Region, 2009-2017 ....................................................................... 73 Table 28: Total Department of Education Spending, by Expense Class, 2009-2017 ................................. 77 Table 29: Per Pupil Department of Education Spending, by Expense Class, 2009-2017 ........................... 77 Table 30: Department of Education Regional Basic Education Spending (in Thousand PhP), .................. 78 by Expense Class, 2009-2017 ..................................................................................................................... 78 Table 31: Department of Education Regional Basic Education Spending (in Thousand PhP), .................. 81 by Level, by Expense Class, 2009-2017 ..................................................................................................... 81

List of Boxes

Box 1: Budget Execution Process ................................................................................................................. x Box 2: Findings from the Philippines Basic Education: Public Expenditure Review

(BEPER) in 2012 ........................................................................................................................... xii Box 3: Findings from the Philippines Public Education Expenditure Tracking and

Quantitative Service Delivery Study (PETS-QSDS) in 2016 ....................................................... xiii Box 4: Early Childhood Education and School Readiness ........................................................................... 4 Box 5: The Philippines Alternative Learning System: A Second Chance to Develop the

Human Capital of Out-of-School Youth and Adults ........................................................................ 8 Box 6: How to Interpret the Results of Grade 6 NAT in SY 2015-2016 .... Error! Bookmark not defined. Box 7: Returns to Education in the Last 15 Years ...................................................................................... 16 Box 8: Increasing Access to Education through Public-Private Partnerships ............................................. 28 Box 9: Three Strategies to Improve Learning Outcomes............................................................................ 34 Box 10: Case Studies of DepEd Program/Project Budget Execution ......................................................... 41 Box 11: Targeted Voucher Programs and Education Outcomes ................ Error! Bookmark not defined. Box 12: Determinants of Learning Outcomes ............................................................................................ 48 Box 13: Five Principles for Creating a Successful Teaching Force ............ Error! Bookmark not defined. Box 14: Institutional Arrangements in Education Systems ........................ Error! Bookmark not defined.

Philippines Basic Education: Public Expenditure Review was prepared by a World Bank team led by Rong Qian, and comprising of Sangeeta Goyal, Takiko Igarashi, Anna Alejo, and Catharine Adaro. The Team benefited from helpful comments and suggestions from Gabriel Demombynes (Program Leader) and Souleymane Coulibaly (Program Leader and Lead Economist). Samer Al-Samarrai and Yevgeniya Savchenko were the peer reviewers. The team benefited from guidance from Mara Warwick (Country Director), Ndiame Diop (Practice Manager), and Tobias Linden (Practice Manager). The team gratefully acknowledges the excellent collaboration of the Government of the Philippines, Department of Education, and Department of Budget and Management, in particular.

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Executive Summary

Countries with strong basic education systems encourage all children, irrespective of gender, household

income, and geographical location, from their early years onwards, to participate in the full cycle of

education. Good education systems have learning environments that lead to robust learning outcomes,

irrespective of abilities, level of household inputs, and socioeconomic characteristics of students. Since

education is the basis for human capital formation and improves individual productivity and earnings, good

education systems contribute to both economic growth and social equity.

The Government of the Philippines (GOP) has undertaken ambitious reforms in the basic education sector

in the last twenty years, and especially in the last eight years. The Governance of Basic Education Act of

2001 was succeeded in 2006 by the Basic Education Sector Reform Agenda (BESRA). A comprehensive

set of reforms were introduced with Republic Act No. 10533, also known as the Enhanced Basic Education

Act of 2013, through which one year of kindergarten and two years of senior high school (SHS) were

formally added to the previous 10-year basic education cycle. The universal kindergarten program was

introduced in 2011 and became institutionalized into the basic education system with the passing of

Republic Act No. 10157, also known as the Kindergarten Education Act, in 2013. Public investment in

basic education has also increased in the sector multifold in the last eight to ten years.

The cumulative effects of past reforms and spending in the basic education system have resulted in

considerable gains. Enrollment and completion rates are near universal in elementary education, and this is

true by gender, location, and household income. More than 80 percent of 5-year-old children attend

kindergarten classes. Enrollment in junior high school (JHS) grades is above 90 percent and enrollment in

SHS grades is expected to increase from its present rate of 64 percent, given that these grades were

introduced less than three years ago.

Higher public spending has been used to relieve two key constraints that have a bearing on education

quantity and quality – infrastructure and facilities in the form of availability of schools and classrooms, and

teacher numbers. The government has also effectively engaged with the private sector, whether in the form

of cash transfers to students to attend private schools or in the form of education service contracting, to fill

access gaps in basic education and to alleviate congestion in public junior and senior high schools. The

government has also expanded the Pantawid Pamilyang Pilipino Program (or known as Pantawid Pamilya,

4Ps, Conditional Cash Transfer, or CCT program) implemented by the Department of Social Welfare and

Development (DSWD), covering 4.4 million poor households with children in the age group 3-18 years by

2015, which led to improvement in school enrollment among children from the poorest families.

This public expenditure review is being undertaken to assess impact on the basic education sector in the

Philippines as a result of the reforms and investment, and as a follow-up to the last review carried out in

2012.

Trends in Education Quantity and Quality

Enrollment

The size of the basic education system grew by 18 percent, from 22 million students in 2009 to 26 million

students in 2017. Overall population falling within the basic education age range (i.e., 5-17 years old) grew

by around 3 percent between 2009 and 2017. Though the bulk of the increase came from new intake in

kindergarten and SHS enrollment, more children of elementary and JHS ages (i.e., 6-15 years old) attended

school in 2017 compared to 2009. Total kindergarten enrollment grew from 1.4 million in 2009 to 2.3

million in 2017, an increase of about 55 percent. With the introduction of SHS, total enrollment at the

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secondary level (i.e., junior high and senior high) expanded considerably by 21 percent in 2016, and by 17

percent in 2017.

Schools, Classrooms, and Teachers

The total number of public schools (elementary and secondary levels) has increased by 18.4 percent from

2010 to 2017, largely due to the doubling of public secondary schools. In addition, private schools make

up about 30 percent of elementary schools and 40 percent of the total number of junior and senior high

schools, and saw considerable growth in their numbers over this period, helped by public-private

partnerships that incentivize private school operators, such as the Education Service Contracting for JHS

and the SHS Voucher Program.

However, classroom ratios have shown variable improvement, depending on the education level –

substantial decline in the average number of students per class in secondary education, but largely

unchanged ratios for elementary education. Increase in the number of schools has also reduced the

percentage of schools operating multiple shifts. While average class sizes are within the generally accepted

norm of 30-40 students to a class across the basic education system, many schools, especially in urban

areas, continue to have very large number of students in a class.

Public elementary and secondary school teachers increased by 41 percent between 2009 and 2017, from

501,226 to 708,394. The increase was driven by the introduction of universal kindergarten and SHS, which

outpaced the growth in student enrollment. This reduced student-teacher ratios by more than 10 percentage

points between 2011 and 2017 to 31:1 at the elementary level, and by more than 11 percentage points to

26:1 at the secondary level, bringing them within generally accepted norms on average.

Internal Efficiency

Cohort survival rate (CSR) has improved at both the elementary and JHS levels in the decade between 2007

and 2017, and at rates faster than the previous decade. Higher CSR have been accompanied by reduction in

average dropout rates in elementary levels, though annual grade-to-grade dropout is still substantial in JHS.

Lack of personal interest and the financial cost of education are the most commonly cited reasons for not

attending school among boys and girls ages 12-15 years old.1

Philippines generally compares well with its regional neighbors and globally in participation and

completion rates in basic education. The mandatory kindergarten policy has contributed to rising pre-

primary enrollment in the Philippines. A Gross Enrollment Rate (GER) of over 100 percent and a Net

Enrollment Rate (NER) of 83 percent makes participation in kindergarten (i.e., pre-primary enrollment) in

the Philippines higher than these rates for many of its neighbors. Only Japan, Hong Kong, Korea, and

Macao in China do better.

Learning Outcomes

Despite improvements in access and output measures, learning outcomes measured by National

Achievement Test (NAT) scores have remained mostly stagnant over time or shown at best modest

improvements in some subjects. The NAT mean percentage scores (MPS) at the elementary level have

fluctuated across all subject areas from SY 2009-2010 to SY 2014-2015, showing little to no improvement.

For both elementary and secondary levels, critical thinking appears to be the skill needing most

improvement. Secondary level MPS generally remain between the upper average and lower average bands.

Among subject areas, Science and Math have the lowest MPS, reflecting a persistent problem. The

1Philippine Statistics Authority (PSA), Annual Poverty Indicators Survey (APIS) 2017.

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Philippines also ranked poorly in the Trends in International Mathematics and Science Study (TIMSS),

where it had ranked among the lowest in 2003. Most recently, after participating in the Programme for

International Student Assessment (PISA) for the first time in 2018, the Philippines ranked last among 79

participating countries and economies in Reading and second to last in Science and Math.

Equity in Basic Education

Equity in Access, Cohort Survival, and Completion

Despite the overall improvement in access to basic education between 2009 to 2017, not all regions gained

equally. Yet, kindergarten GERs and NERs across regions have become more equal over time. In 2010,

kindergarten enrollment rates varied from as low as 57.5 percent (Region II) to 101.4 percent (Region I)

for GERs, and 38.8 percent (NCR) to 78.9 percent (CARAGA) for NERs. In 2017, this had narrowed to a

range between 108.7 percent (Region X) and 89.7 percent (NCR) for GERs, and between 60.6 percent

(ARMM) to 91.4 percent (Region VII) for NERs. While ARMM had the lowest kindergarten NER and

GER among all regions, the gap between ARMM and the national average GER is around only 10

percentage points, indicating a reasonably high take-up of this program by households in that region.

Compared to the elementary level which shows improved equity in access across the country, access to JHS

and SHS continues to show greater regional variations, though overall participation rates have improved in

all regions. The greatest differences between regions is in SHS participation. GERs ranged from a low of

22.3 percent in ARMM to a high of 83.1 percent in NCR, and NERs from 8.7 percent in ARMM to 62.7

percent in NCR.

Elementary CSR and completion rates have continued to improve overall and have become moderately less

varied across regions from 2009 to 2017. JHS level CSR and completion rates have improved at a slower

pace than the elementary level but have become more equal across regions. However, overall regional

differences in CSR and completion rates were slightly larger in 2017 than in 2009 due to the starkly low

values for ARMM.

The poor persistently have the lowest NER, CSR, and completion rates, at the secondary level in particular.

NERs across all levels of basic education continue to be lowest for children from the poorest families,

although there is a generally upward trend in elementary and JHS enrollment between 2009 and 2017 for

all income groups. Over time, gains in participation have been the highest for the poorest quintile with

expansion of the CCT program over the last decade, albeit the lags are larger for secondary school

participation possibly due to the higher opportunity cost of time for the age group for poorer households.

Disparities between boys and girls in school access and completion continue to be a problem across almost

all levels of education. Even as early as kindergarten, boys’ NERs remain slightly lower than that of girls.

While the gender gap in NERs at the elementary level has virtually closed, gender disparities in the

secondary level have worsened since 2008. Gender disparities in CSR and completion rates too persist and

are more pronounced at the secondary level. More girls than boys reach and complete the final grade of

elementary and JHS schooling. Among out-of-school children from the poorest households, boys

outnumber girls twofold.

Equity in Learning Environment

Growth of number of schools varies across regions. From 2010 to 2017, while the national average annual

growth rate in the number of schools was 2.5 percent, growth of schools in ARMM was only 0.9 percent.

In contrast, the number of schools in urbanized areas such as NCR, Region VII, and Region XII increased

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at a faster pace than the national average, with average annual growth rates of 4.1 percent, 3.3 percent, and

4.2 percent, respectively.

Regional variations in pupil-teacher ratio (PTR) and student-teacher ratios (STR)2 have lessened

considerably over time, particularly at the secondary level. In 2009, secondary level STRs ranged from 29:1

to 53:1; in 2017, this narrowed substantially to a range between 21:1 to 28:1. From 2009 to 2017, PTRs and

STRs remained lowest in CAR. ARMM showed the greatest improvement from 2009 to 2017 but continued

to have the highest PTR and STR among all regions. In 2017, NCR and Region IV-A had the highest pupil-

and student-classroom ratios, suggesting that overcrowding remains a problem in highly urbanized regions

where school sizes are largest. In urban areas, land is limited and expensive, making school expansion

difficult; thus, shortage of classrooms becomes a problem.

At all education levels, however, teacher qualifications vary widely across regions. In 2017, the proportion

of teachers with Teacher III and Master Teacher positions at the elementary level ranged from 12 percent

(ARMM) to 66.2 percent (Region II). At the JHS level, the same ranged from 7.4 percent (ARMM) to 62.3

percent (Region II), while at the SHS level, this ranged from 3.2 percent (Region IX) to 58.2 percent (NCR).

Comparing teacher qualifications and teacher ratios across regions suggests a need for a more equitable

mechanism for deployment of better-qualified teachers and development of teachers who have lower

qualifications.

Equity in Learning Outcomes

Compared to the overall stagnant trend of learning outcomes between 2009 to 2015, both elementary and

secondary NAT MPS decreased for Regions IV-A and VIII. NCR saw a decline in the elementary level

performance, while NAT scores in Region I decreased at the secondary level. Learning outcomes seem

correlated with output measures. Regions with poorer NAT performances at the elementary level also have

higher pupil-classroom ratios. At the secondary level, regions with lower NAT scores have higher student-

classroom and student-teacher ratios, with the exception of Region I. The pattern between NAT scores and

school inputs reinforces the notion that highly congested schools which are usually in urban areas are less

conducive to effective teaching and better learning.

Trends in Public and Private Spending on Basic Education

Government spending on basic education has risen substantially by 2.6 times between 2009 and 2017 in

real terms. At the elementary level, government spending3 in 2017 rose to PhP 104 billion in real terms on

2000 prices, an increase of 72.8 percent from the year 2009. Per pupil real spending at the elementary level

grew by 80.1 percent over the same period, amounting to PhP 8,481 in 2017. At the secondary level,

government spending in 2017 amounted to PhP 58 billion in real terms on 2000 prices, about 133.2 percent

higher than in 2009. Per pupil real spending at the secondary level also increased from 2009 by 61.9 percent

to PhP 7,466 in 2017. The increasing share of secondary education expenditure by DepEd coincides with

not only growing total enrollment, but also declining student-teacher and student-classroom ratios at this

level. Pupil-teacher ratios at the elementary level have also continued to show improvement, though pupil-

classroom ratios have not changed much.

2In the Philippines, the ratio of students per teacher is referred to as pupil-teacher ratio in elementary education, and student-teacher

ratio in secondary education. 3In this report, government spending for each year reflects the total of obligations data from the current year budget/appropriations

and prior year’s budget/continuing appropriations (both regular and automatic), and are expressed in nominal and real terms with

implicit price index (IPIN) deflator with 2000 as the base year. Expenditure per education level reflects obligations data on

operations of schools as indicated in DepEd’s Statements of Appropriations, Allotments, Obligations, Disbursements, and Balances

(SAAODBs).

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Government spending is strongly correlated at the regional level to the number of teachers in the basic

education system. Correlation analysis at the regional level shows that per pupil government spending,

which includes both national and local government spending, is significantly correlated with lower teacher

ratios at the elementary and secondary levels. A large share of public basic education spending goes to

personnel services, such as salaries of teachers and non-teaching staff and their benefits.

Local government units’ (LGU) expenditure comprise a small and decreasing share of total basic education

spending. The LGU share of total basic education spending decreased from an average of 9.1 percent

between 2002 to 2008 to an average of 5.3 percent between 2009 to 2017. Regional disparities exist in LGU

spending, mainly due to differences in the Special Education Fund (SEF). The SEF, which makes up about

75 percent of LGU education spending, is accrued through an additional 1 percent tax on real property. As

such, larger and wealthier regions such as NCR and Region IV-A have considerably higher LGU funding

than other regions.

Private Spending on Basic Education

Between 2012 and 2015, average household expenditure per school-age child declined in real terms. Across

income groups, the decline in average education expenditures per school-age member is only observed for

the top two (i.e., richest) quintiles, with larger reductions for the fifth/richest quintile. In contrast, average

education spending per school-age member rose for the remaining income groups; moreover, this increase

in spending was significant for the lowest two (i.e., poorest) quintiles. The pattern of change across quintiles

is a reflection of the different demographic status of richer and poorer households (the latter have one more

child on average), the greater access of poorer households to education, and the complementarity between

public and private spending on education.

DepEd has continued to generate increased funding from partners in the private sector through its Adopt-

a-School Program, which allows private entities to assist public schools in particular aspects of educational

programs within an agreed period of time. In 2008, contributions amounted to about PhP 6 billion pesos;

in 2017, over PhP 10 billion pesos worth of support had been raised through the program, equivalent to

about 1.7 percent of total government spending on basic education.

Public Expenditure Efficiency

Due to lack of data availability, a cost-benefit or cost-effectiveness analysis for judging public expenditure

efficiency could not be carried out. Findings from a cross-section regression analysis using learning

outcomes for Grade 6 suggest that the higher availability of classrooms and teachers have led to learning

gains, indicating that reforms accompanied by a significant increase in public spending have relaxed

constraints with respect to inputs such as availability classrooms and teachers in elementary education

While the large number of teachers hired to fill the student-teacher ratio deficits has been an important step

in providing adequate resources to the basic education sector, teacher quality is deficient. The availability

of Master Teachers is low even where the overall availability of teachers is adequate with respect to norms.

Non-DepEd teachers are also less effective compared to teachers who belong to DepEd. While classroom

availability deficits in elementary education have reduced, as has the percentage of schools with multiple

shifts, school congestion remains a problem. Within some regions, teachers are less equally deployed,

leading to an imbalance in the availability of teachers across schools.

Policy Recommendations

While the substantial increase in investment has been successful in improving relative supply of key inputs

in the basic education, sustained coverage of early childhood education and senior high school will require

vi

continuous flow of funds into the sector. Teacher numbers have risen due to increase in hiring to reduce

student-teacher ratios and align them with national and international norms. Teacher deployment, across

and within regions, and teacher quality remain issues – especially the latter, as there is some evidence that

for schools where teachers with better credentials are present in larger shares, test scores are higher.

Governance and management of the education system, including budget and allocation of resources across

inputs in the Philippines have been centralized. Moving forward, policy-makers can determine whether the

division of responsibilities need to be reassigned to allow decision-making over inputs and processes among

the center, local government, and school to maximize learning outcomes. The Alternative Learning System

for dropouts and adults now covers more than three-quarters of a million individuals. This system needs to

be evaluated and based on findings appropriately scaled up. Effective planning and efficient use of funds

can be aided by strengthening data systems and ensuring that data is available at different levels of

administrative planning, namely, the nation, region, division, district, and school.

vii

Introduction

Countries invest in basic education to provide their citizens with the means to acquire the foundations

for building human capital. Countries with good school education systems provide equity of access, i.e.,

encourage all children, irrespective of gender, household income, and geographical location, from the early

years onwards, to participate in the full cycle of education. Good education systems have learning

environments that lead to strong learning outcomes. Since education is the basis for human capital

development and improves individual productivity and earnings, good education systems contribute both

to economic growth and social equity.

The Philippines has been on a reform trajectory of the basic education system in the last fifteen years.

Until 2011, school education in the country comprised of a total of 10 years, with 6 years of elementary

education and 4 years of junior high school. Since 2011, a year of kindergarten has been added to the school

cycle, and universal kindergarten was made mandatory in 2013. The Enhanced Basic Education Act of

2013 added two years of senior high school to the school system, which was implemented for the first time

in 2016, with the first cohort student graduated in 2018. The Philippines is also mindful of the need to assess

the outputs of its basic education system by conducting annual National Achievement Tests (NAT) for

elementary and secondary students. The country participated in the Programme for International Student

Assessment (PISA) for the first time in 2018 and in the Trends in International Mathematics and Science

Study (TIMSS) in 2019 after a break of 16 years.

These reforms have been accompanied by increased public spending, as a share of the Gross Domestic

Product (GDP), and in terms of per pupil expenditure. Total public spending in education was 4.4

percent in 2017, having risen steadily since 2010, and compared to less than 3 percent in the decade before.

The increase was mainly due to economic growth with education expenditure as share of government

budget averaging around 15 percent, which is below the benchmark for middle income countries of 20

percent.

The effects of past reforms and spending in the basic education system have resulted in considerable

gains. Higher public spending has been used to relieve two key constraints that have a bearing on education

quantity and quality – infrastructure and facilities in the form of availability of schools and classrooms, and

teacher numbers. The government has also effectively engaged with the private sector, whether in the form

of cash transfers to students to attend private schools or in the form of education service contracting, to fill

access gaps in basic education. As result, enrollment and completion rates are near universal in elementary

education in the Philippines, and this is true by gender, location, and household income. More than 80

percent of 5-year-old children attend kindergarten classes. Enrollment in junior high school grades is above

90 percent and enrollment in senior high school grades can be expected to increase from its present rate of

64 percent, given that these grades were introduced less than three years ago.

However, the challenges of equity in access and quality of basic education in the Philippines are far

from over. While universal kindergarten has been mandated, there is still a substantial share of young

children who are not covered by the program. Boys from poor households have a lower probability of

enrolling in and/or completing post-elementary education. Though the extent of age- and grade-mismatches

has declined, it is likely to continue for several years in the future as the country so far is not equipped to

provide a variety of pedagogical approaches for widely varying age groups in the same class, especially in

congested urban schools or in non-urban areas where schools have a higher share of teachers with lower

credentials. Availability of inputs such as student-teacher ratio and student-classroom ratio has become

more equal across regions; poor regions, however, still lag behind the richer and more advantaged regions.

Despite substantial increase in public spending and the gains in scope and coverage, changes in learning

outcomes at both the elementary and secondary levels have been modest at best, and most students’

competencies continue to measure below proficiency levels.

viii

This report looks at the role played by public expenditure in improving access, equity, quality, and

learning in basic education in the Philippines. It builds on work undertaken earlier, especially the Basic

Education Public Expenditure Review (BEPER, 2012; see Box 2 for summary of study) and the Philippines

Public Education Expenditure Tracking and Quantitative Service Delivery Survey (PETS-QSDS, 2016; see

Box 3 for summary of study). Specifically, this review provides a comparative picture of sector

performance, where possible, between the periods 2002 to 2008 and 2009 to 2017, the former being the

period studied by BEPER (2012). Chapter 1 looks at quantity and quality in basic education, Chapter 2

examines equity issues, and Chapter 3 looks at patterns of public expenditure in basic education. In the

remaining section of this introduction, a brief description of how basic education is managed and financed

in the Philippines is provided.

Department of Education

The Department of Education (DepEd) is mandated to develop and implement policies, programs,

and projects to improve access to, equity in, and quality of basic education as mandated under Republic

Act No. 9155, also known as the Governance of Basic Education Act of 2001. Basic education encompasses

kindergarten, elementary (Grades 1 through 6), junior high school (Grades 7 through 10), and senior high

school (Grades 11 and 12), as provided by Republic Act No. 10533, also known as the Enhanced Basic

Education Act of 2013. DepEd’s mandate covers both formal and non-formal areas of basic education,

including the Alternative Learning System (ALS) for out-of-school youth and adult learners, as well as

education for learners with special needs.

Management Structure

The DepEd management structure is composed of the central office and field offices. The central office

manages the education system at the national level, including the formulation of national educational

policies, plans, and standards, monitoring and assessing national learning outcomes, and developing

national programs and projects. The field offices, which consist of the regional, division, district, and school

levels, oversee the regional and local coordination and governance of basic education. The current

organizational structure of DepEd is presented in Figure 1.4

The DepEd central office oversees the administration of the basic education system at the national

level. The Secretary of Education, who exercises overall authority and supervision over DepEd, is assisted

by undersecretaries and assistant secretaries assigned to various areas of governance. The Office of the

Secretary, which includes attached agencies and coordinating councils, is supported by five organizational

strands: (a) Curriculum and Instruction, (b) Finance and Administration, (c) Governance and Operations,

(d) Legal and Legislative Affairs, and (e) Strategic Management. Each strand is made up of bureaus,

services, and divisions with functions and objectives to support DepEd’s mandate.

The field offices ensure that policies, programs, projects, and services are developed and adapted to

local and community needs and contexts. The field offices are composed of 17 regional offices, each

headed by a regional director or, in the case of the Autonomous Region in Muslim Mindanao5, a regional

4More detailed organizational charts, including those at the regional and schools division level, are found in DepEd Order No. 52,

s. 2015. The same also identifies counterpart offices across DepEd organizational levels. 5Republic Act No. 11054, also known as the Bangsamoro Organic Law, which provides the establishment of the autonomous

political entity Bangsamoro Autonomous Region in Muslim Mindanao (BARMM) to replace the Autonomous Region in Muslim

Mindanao (ARMM), was ratified after a plebiscite on January 21, 2019. BARMM was formally inaugurated on March 29, 2019.

Its territorial jurisdiction is the same as ARMM, with the addition of Cotabato City and a few barangays (i.e., villages, which are

the smallest administrative unit in local governance) in North Cotabato, which were originally under Region XII. As this report

analyzes data from 2009 to 2018, findings presented pertain to ARMM and its territorial jurisdiction. As such, ARMM, rather than

BARMM, is used throughout this report.

ix

secretary. Within the regions are division offices, which may be either provincial or city divisions. Each

division office is headed by a schools division superintendent. Within divisions, schools district offices are

led by a schools district supervisor who provides support to school heads and teachers in their respective

districts. Lastly, at the school level, school heads are responsible for the administrative and instructional

supervision of their respective schools.

Figure 1: DepEd Organizational Structure

Source: DepEd Order No. 52, s. 2015.

Basic Education Financing

The national budget for basic education is executed against the General Appropriations Act (GAA)

passed by the legislature for each fiscal year. The GAA serves as authorization for agencies to begin

incurring obligations. Box 1 summarizes the budget execution process. During the first phase of the budget

cycle, or the budget preparation stage, national government agencies undertake citizen engagement

activities such as consultations with local government units (LGUs) to ensure that regional and local needs

are addressed in the agencies’ respective budget proposals. To strengthen linkages between national and

local plans, Regional Development Councils evaluate the list of priority projects submitted by LGUs before

endorsing this to their respective Agency Central Office. Based on the evaluation conducted at the regional

level, the Agency Central Office then prioritizes the local programs and projects for inclusion in the budget

proposal.

Attached Agencies:

• Philippine High School for the Arts

• National Book Development Board

• National Council for Children’s Television

• National Museum

• Early Childhood Care and Development Council

Coordinating Councils:

• Teacher Education Council

• Literacy Coordinating Council

• Adopt-a-School Program Coordinating Council

OFFICE OF THE SECRETARY

Office of the Secretary Proper

Office of the Undersecretaries

Office of the Assistant Secretaries

CURRICULUM AND

INSTRUCTION

Bureau of Curriculum

Development

Bureau of Learning Delivery

Bureau of Education

Assessment

Bureau of Learning Resources

GOVERNANCE AND

OPERATIONS

Bureau of Learner Support Services

Bureau of Human Resource and

Organizational Development

National Educators Academy of the

Philippines

Project Management Service

LEGAL AND LEGISLATIVE

AFFAIRS

Legal Service

FINANCE AND ADMINISTRATION

Finance Service

Administrative Service

Procurement Management

Service

STRATEGIC MANAGEMENT

Planning Service

Public Affairs Service

Information and Communications

Technology Service

External Partnerships Service

Disaster Risk Reduction and

Management Service

TEACHER EDUCATION COUNCIL SECRETARIAT

INTERNAL AUDIT SERVICE

Schools and Learning Centers

Schools Division Offices

Regional Offices

FIELD

OPERATIONS

x

DepEd executes the national budget for basic education, except for school construction. A significant

portion of the basic education budget for school construction is managed and implemented by the

Department of Public Works and Highway (DPWH) through the School Building Program under the Basic

Education Facilities Fund (BEFF). Ninety percent of basic education in the Philippines is managed by the

national government which is responsible for education policy, standards, curricula, and teacher hiring.

Figure 2 presents the flow of education funds from the national level to the school level. Government funds

for the Autonomous Region in Muslim Mindanao (ARMM), however, are managed separately, and the

flow of funding to schools follow a different mechanism than the norm.6

Along with national government agencies, basic education is also supported by funding from LGUs,

which constitute a small and decreasing share of basic education expenditure. Local government

spending on education come from both the LGU’s General Fund and Special Education Fund (SEF). The

SEF, which account for majority of LGU education spending, is collected through a 1 percent surcharge on

property taxes. Some provisions such as the SEF allow shared governance of basic education between

central and local government units. Under Republic Act No. 7160,7 the SEF are automatically released to

the Local School Board (LSB) at the provincial, city, and municipal levels. The LSB is composed of the

local chief executive and the schools division superintendent/district supervisor as co-chairmen, and

representatives from various groups including the Sangguniang Kabataan (i.e., village youth council),

Parent-Teacher Association, teachers’ organization, and non-academic personnel of public schools in the

6ARMM is included in the national DepEd budget only for certain items, such as the creation of teaching and non-teaching

positions, funding for newly-legislated schools, the School Building Program, and various foreign-assisted and locally-funded

programs and projects. 7Also known as the Local Government Code of 1991.

Box 1: Budget Execution Process

The budget cycle of the national government, which begins in the prior fiscal year, involves four phases: (a)

Budget preparation, (b) budget authorization, (c) budget execution, and (d) budget accountability. The budget

execution phase begins with early procurement activities from August to December of the prior fiscal year.

Even before the General Appropriations Act (GAA) is enacted, agencies may bid their projects to allow the

immediate awarding of approved projects as soon as the GAA takes effect. Towards the last few months of

the prior year, agencies submit their Budget Execution Documents containing their financial plans and

performance targets for the fiscal year. These plans are consolidated by the Department of Budget and

Management (DBM) into the budget program, which breaks down the allotment and cash releases, including

automatic appropriations, for each month of the year.

The DBM then releases allotments authorizing agencies to incur obligations. Following the GAA-as-the-

Allotment Order policy, the enacted budget serves as the allotment release for agencies to incur obligations,

except for multi-use special purpose funds and items requiring special budget requests. As agencies

implement their programs, projects, and activities, obligations are incurred and are paid out from the Treasury.

The DBM issues cash and non-cash disbursement authorities, such as the Notice of Cash Allocation (NCA),

to authorize agencies to pay the obligations they incur.

Certain DepEd programs, such as the procurement of textbooks and school furniture, are appropriated by

lump-sum items. Once DBM has released allotments authorizing DepEd to incur obligations, DepEd then

transfers specific amounts to regional offices and other implementing units through the Sub-Allotment

Release Order (sub-ARO). The sub-ARO, in turn, authorizes the implementing units to incur obligations,

allowing them to implement programs and activities. Obligations are then paid by requesting a cash release

through the NCA.

xi

REGIONAL

LEVEL

City/municipality own source

revenue

Own source

revenue

NATIONAL

LEVEL

PROVINCIAL/DIVISION

LEVEL

SCHOOL

LEVEL

Department of Budget and Management

(DBM)

Department of Education

(DepEd)

Internal revenue

allotment

Operations

budget GASTPE

Operations

budget

In-kind

transfers (Textbooks)

DepEd Regional

Offices

DBM Regional

Offices

DepEd Schools Division Offices

City/municipality Province

Public Elementary Private Schools Public Secondary

Local government unit

LGU. The LSB is mandated to determine the allocation of the annual school board budget and authorize

the disbursements of funds from the SEF.8

Figure 2: Flow of Public Funds from National Level to School Level

Notes: GASTPE – Government Assistance for Students and Teachers in Private Education.

From the national level, broken black lines signify flow of funds from DBM to the school level, while solid

black lines represent flow of funds from DepEd to the school level. From the provincial/division level, broken

orange lines denote funds directed from LGUs to schools. Lastly, broken blue lines represent funds generated

by LGUs and schools’ own source revenues.

Source: “Assessing Basic Education Service Delivery in the Philippines: The Philippines Public Education

Expenditure Tracking and Quantitative Service Delivery Study”, World Bank, 2016.

In addition to national and local government levels, schools also manage their own budget to execute

their school improvement plans. Through initiatives such as the Basic Education Sector Reform Agenda

in 2006, the Philippines has introduced school-based management (SBM) reforms to the basic education

system. SBM decentralizes decision-making from the central office and field offices to individual schools

and local communities. The SBM strategy gives school heads, teachers, and parents greater autonomy and

accountability over the use of their respective school’s funds. The national government provides schools

with funds for maintenance and other operating expenses (MOOE), known as School MOOE, which are

disbursed to schools by division offices. To supplement the School MOOE they receive, certain schools

may be eligible to receive an SBM grant, depending on the school’s enrollment size and their municipality’s

income class.

8To guide budget formulation, DepEd regional offices provide LSBs with copies of individual schools’ allocation for the year from

the national budget, as well as the DepEd-approved multi-year school improvement plans.

xii

Box 2: Findings from the Philippines Basic Education:

Public Expenditure Review (BEPER) in 2012

In partnership with DepEd, the World Bank and AusAID (2012) conducted a study on public expenditures and outcomes in

the basic education sector, covering the years 2002 to 2008. The review analyzes trends in education performance in relation

to the 2015 Education for All (EFA) goals and the Basic Education Sector Reform Agenda (BESRA) objectives. The analysis

traces trends in government spending and their impact on basic education inputs and outcomes. The main findings are as

follows:

• Declining performance in basic education: Decreased enrollment rates, along with persistently high dropout and

repetition rates, were observed for both elementary and secondary levels. Mean percentage scores on the National

Achievement Test remained below 65 percent in the elementary level, and below 50 percent in the secondary level.

• Persistent inequalities: Divergent educational outcomes continued to persist across regions. Children from poor

families were the most likely to not complete school, not be in school at all, or drop out of school the earliest. Boys

consistently significantly lagged behind, and gender gaps were most striking at the secondary level.

• Quantity of public spending: Government spending on basic education declined from 2.9 percent of GDP in 2002

to 2.3 percent of GDP in 2008 due to a reduced public sector budget and to the decreasing priority given to the basic

education sector.

• Quality of government spending: Insufficient public spending on basic education and the inefficient allocation of

funds led to persistent under-provision of key inputs such as classrooms and inequitable teacher deployment. Analysis

of regional data showed higher government spending and better input ratios were associated with higher participation

and completion rates. At the municipal level, adequate school inputs, such as better-qualified teachers and single

shifts, were associated with better learning outcomes.

• Efficiency of government spending: Operational inefficiencies and instability in the sector's policy environment

hindered DepED’s ability to spend the allocated budget quickly and efficiently. Budget execution rates were

particularly low for maintenance and other operating expenses and capital outlay, which provide critical inputs for

access to and quality of education.

Policy suggestions from the study are as follows:

• Increase funding for basic education. Increase national and local government spending to a minimum of 3.2 percent

of GDP by 2015. Increase must be higher than 6 percent of GDP if there are improvements in pupil-teacher ratios,

prioritization of quality improvement measures such as teacher training, and elimination of shifts in classroom use.

• Improve budget execution and resource allocation. Review all relevant administrative actions to simplify and

streamline procedures. Strengthen DepEd’s ability to project and plan for future enrollments for provision of the

required level of inputs, including new teacher hires. Make increased and sufficient funds available at the school level.

• Introduce explicit mechanisms to ensure more effective coordination of expenditure assignments between

DepEd and LGUs. Tightly coordinate national and local government spending on basic education with DepEd to

provide increased resources, especially in poorer regions, strengthen school-based management, and improve equity

in resource allocation.

• Enhance cross-sectoral collaboration to ensure the link between demand- and supply-side interventions. Use

the Conditional Cash Transfer program (Pantawid Pamilyang Pilipino Program, or 4Ps) in a well-targeted manner to

boost parents’ incentives to keep children in school.

• Enhance public-private partnerships within a coherent policy and regulatory framework. Expand the Education

Service Contracting program to significantly alleviate pressure on the public school system to build additional

classrooms to accommodate current and future learners.

• Strengthen capacities for evidence-based decision-making and improve availability of accurate and consistent

data. Gradually invest in building capacities for making policy decisions based on objective analysis and evidence

from policy research. Invest in improving the coverage and quality of policy-relevant data.

• Track and monitor allocation and spending. Institutionalize annual reviews of public expenditures and key

programs, as well as regular (e.g., every other year) updating of the Multi-Year Spending Plan. Conduct periodic

public expenditure tracking surveys and school-level surveys.

xiii

Box 3: Findings from the Philippines Public Education Expenditure Tracking and

Quantitative Service Delivery Study (PETS-QSDS) in 2016

In partnership with DepEd, World Bank conducted a study (2016) that assessed the quality of basic education services and the

strength of existing systems used to allocate and manage public education resources. It tracked public education resources from

national and local governments to a nationally representative sample of elementary schools and high schools in the

Philippines. The key findings of the report are as follows:

• Teachers: While the availability of teachers in schools has improved, there are signs of growing inefficiency in

teacher deployment because of weaknesses in teacher allocation systems. Teacher absenteeism rates in elementary

and high schools are generally low in the Philippines compared to other countries. Teachers’ content knowledge

seems poor and professional development systems have been inadequate.

• School infrastructure: Despite progress in the availability of key inputs, classroom deficits remain a persistent

issue. Public infrastructure improvement systems suffer from many challenges leading to poor quality and incomplete

classrooms and water and sanitation facilities.

• School-based management and funding: Schools have limited discretionary funding to implement their own school

improvement plans, and a significant portion of the funding fails to reach schools compared to the

amount originally allocated at the national level. Schools also face difficulties in using public funds because

of complex management and reporting requirements. School level accountability through School Governing

Councils remains generally weak. Although parental awareness of the existence of School Governing Councils is

limited, parents are more aware and participate more actively in Parent-Teacher Associations.

• Local government funding for education: Local government funding for basic education is relatively low,

declining, and unequal. Poor record-keeping and reporting make it difficult to assess the distribution and effectiveness

of local government funding for education.

• Equity: Significant differences in levels of education spending and the quality of the learning environment exist

across regions and provinces. Even though urban schools tend to serve wealthier populations, they tend to perform

poorly compared to rural schools. Schools serving poorer communities tend to be more resource-constrained than

wealthier schools.

Policy suggestions from the study are as follows:

• Increase public spending on education. Despite significant improvements, infrastructure and teacher shortages

remain. More school level discretionary and professional development funding are needed.

• Improve allocation of education inputs through better planning. Introduce medium term planning (two to three

years) for key resource inputs. Increase role of division/district offices and schools in planning.

• Give schools greater authority in planning and resource management decisions and simplify reporting

requirements. Give greater authority to schools during implementation (e.g., infrastructure). Simplify reporting

requirements for MOOE through grant approach.

• Improve transparency of fund allocation and resource use across the system. Develop simple reporting formats

and bolster incentives (e.g., LGU seal). Introduce and widely disseminate a set of school standards.

• Strengthen the role of School Governing Councils and Parent Teacher Associations. Increase authority of School

Governing Councils in oversight of school planning and resource use. Raise awareness of School Governing Councils’

role and provide support/training.

• Address funding and quality inequalities through improved financing mechanisms and focused interventions

for schools serving disadvantaged groups. Focus on “schools under stress” to address poor learning

environments. Introduce equity component into division and school funding formulas

The main findings and policy suggestions of the PETS-QSDS (2016) are presented as a series of policy notes on specific issues

as well as a combined report.

1

Chapter 1 – Performance of the Philippine Basic Education Sector 2009-18

This chapter examines trends in school participation, cohort survival, completion, and learning achievement

in the basic education system in the Philippines from 2009 to 2018. Data presented are taken from the

DepEd Enhanced Basic Education Information System (EBEIS), several rounds of the National

Achievement Test (NAT), and the Annual Poverty Indicators Surveys (APIS) from 2007 to 2017. The

discussion in this chapter includes comparisons to the period 2002 to 2008, which correspond to the years

covered by the first Basic Education Public Expenditure Review (BEPER, 2012).

Over the last two decades, the Government of the Philippines (GOP) has established several critical

frameworks for education reform. Following the Governance of Basic Education Act of 2001, projects

such as the Basic Education Assistance for Mindanao (BEAM), the Third Elementary Education Project

(TEEP), and Strengthening the Implementation of Basic Education in Selected Regions in Visayas

(STRIVE) were implemented to improve education access and encourage decentralized governance. These

initiatives were succeeded by a comprehensive and sector-wide reform in 2006 with the Basic Education

Sector Reform Agenda (BESRA). The universal kindergarten program was also introduced in 2011 and

became institutionalized into the basic education system with the passing of the Kindergarten Education

Act, in 2013. In addition, under Enhanced Basic Education Act of 2013, one year of kindergarten and two

years of senior high school were formally added to the previous 10-year basic education cycle. Critical

basic education reforms supported the transition to the K to 12 system, accompanied by the introduction of

the new K to 12 Basic Education Curriculum and the Mother Tongue-Based Multilingual Education

program beginning in 20139. Senior high school education, covering Grades 11 and 12, began in 2016.

Access to Schooling

The Enhanced Basic Education Act (2013) built on the educational gains from earlier policies and

gave further impetus to the expansion of the basic education sector. Total enrollment in the basic

education system has increased since 2009, with an accelerated growth rate in recent years due to the

implementation of the K to 12 program in 2013. From 2009 to 2017, enrollment in public and private

schools grew at an average annual rate of 2.1 percent, over twice as fast compared to the period between

2002 to 2008. Strong household per capita income growth and decline in the incidence of poverty between

2006 to 2015, albeit weaker for the few years immediately following the 2009 crisis, have helped increase

household demand for education.10 Additionally, the formal launch in 2008 of the Pantawid Pamilyang

Pilipino Program (4Ps), the Philippines’ national conditional cash transfer (CCT) program, has

strengthened incentives for parents to send and keep their children in school.11 The CCT program has

expanded to cover total 4.4 million households with children ages 3-18 years in 2015, which contributed to

significant gains in school attendance among the poor.

Enrollment Rates

Between 2009 and 2017, number of students in the basic education increased from 22 million to 26

million (Figure 3). The bulk of the increase came from kindergarten and SHS enrollment. Total

kindergarten enrollment grew from around 1.5 million in 2009 to 2.3 million in 2017, an increase of about

55 percent. With the introduction of SHS, total enrollment at the secondary level (i.e., junior high and senior

high) expanded considerably by 21 percent in 2016, and by 17 percent in 2017 reaching 10.4 million

students. However, even as participation rates (discussed below) improved, the DepEd data shows that

9MTB-MLE covers kindergarten to Grade 3 students. 10World Bank, Making Growth Work for the Poor: A Poverty Assessment for the Philippines (Washington, D.C.: World Bank

Group, 2018). 11Studies on the impact of 4Ps (e.g., World Bank, 2013; Orbeta et al., 2014) have shown increases in school enrollment for

beneficiaries aged 12 years old and above, as well as improvements in school attendance for children ages 5 years old and below.

2

absolute number of elementary students registered a decline from 13.9 million in 2009 to 13.4 million in

2017.12 The national household survey shows that the school-age population (i.e., 5-17 years old) increased

by 3 percent between 2009 and 2017, and those in the age group 6-11 years. The same data shows the

number of school-age children who are in school also increased due to significant declines in the number

of school-age children who are not in school.13

Figure 3: Total Enrollment, SY 2009-2010 and SY 2017-2018

Source: DepEd EBEIS.

Private sector enrollment also increased between 2009 and 2017. The share of the private sector in all

enrollment increased between 2009 and 2017 from 13 percent to 15 percent. The increase was largely due

to private senior high school enrollment which was 47 percent of all senior high enrollment in 2017.

Meanwhile, the share of private enrollment in elementary education has changed marginally since 2009 and

private kindergarten enrollment decreased by 42 percent.

Overall, enrollment rates have grown across all levels of the basic education system (Figure 4).

Following the implementation of the universal kindergarten program in 2011, kindergarten gross (GER)

and net enrollment rates (NER) rose 20.1 and 16.6 percentage points, respectively, from 2010 to 2011.

Kindergarten GER decreased from its highest point of 106.7 percent in 2013 to a low 82.4 percent in 2016,

due to the strict implementation of the minimum entrance age qualification of 5 years. Through efforts such

as the early registration campaign, kindergarten GER and NER recovered to 102 and 83.7 percent,

respectively, in 2017.

Despite some fluctuations, the elementary participation rate has stayed steadily above 90 percent

from 2009 to 2017. Following a downward trend between 2002 to 2008, elementary level participation

rates began to increase in 2009 but then went through a period of decline. Between 2011 and 2015,

elementary NER declined from 97.1 percent to 91.1 percent. In 2015, the Philippines narrowly missed

meeting the Millennium Development Goals (MDGs) and Education For All (EFA) target of universal

12It is not totally assertive why the number of students enrolled in elementary schools declined in the DepEd data while the national

household survey data shows the opposite. While various factors should have contributed to this gap in the data, it may be partly

related to the introduction of the Enhanced Basic Education Information System, linked up with the Learner Information System.

The accuracy and reliability of DepEd’s official data has increased as the data is validated by multiple data sources recently. 13PSA, Labor Force Survey 2009 and 2017.

1,050 2,023

12,788 12,266

5,415 6,412

1,395

19,253 22,096

420 244

1,134 1,207

1,340 1,366

1,249

2,894

4,066

1,470 2,267

13,922 13,473

6,755 7,778

-

2,644

22,147

26,162

-

5,000

10,000

15,000

20,000

25,000

30,000

2009 2017 2009 2017 2009 2017 2009 2017 2009 2017

Kindergarten Elementary JHS SHS Total

In t

ho

usa

nd

s

Public Private

3

access to primary education.14 DepEd’s omnibus policy on kindergarten education, requiring completion of

DepEd-accredited kindergarten programs as a prerequisite for Grade 1 gave a new impetus to elementary

enrollment - elementary GER rose to 110.5 percent and NER rose to 96.2 percent in 2016 (see Box 4 for

further discussion on the benefits of early childhood education).

Figure 4: Enrollment Rates in Private and Public Schools, SY 2009-2010 to SY 2017-2018


Currently, almost eight out of ten students between the ages 12-15 years are enrolled in junior high

schools compared to fewer than six between 2002 to 2008. At the secondary level, JHS enrollment rates

declined slightly in 2014 before beginning a steady upward trend. The increase in JHS participation may

be due in part to the expansion of the coverage of the 4Ps/CCT program to include children in the ages 15-

18 years starting in 2014. A comparison of GERs and NERs, however, points to the persistent problem of

grade-age mismatch, revealing the continuing presence of under- and especially overage learners at the JHS

level.

The GOP introduced Grades 11 and 12 of SHS as part of the basic education system in 2016. This

change aims to ensure that students attain skills and competencies that will make them employable in good

jobs at home and abroad. The first cohort of Grade 12 completers graduated in 2018. In the first two years

of its implementation, the program has seen modest achievements with a GER of 66 percent and NER of

42 percent. SHS GER and NER are expected to grow in the coming years, as more senior secondary seats

become available, and with increasing demand from a larger number of students completing JHS. Currently,

elementary schools outnumber JHS in the ratio 4.5:1 and SHS in the ratio 3.5:1.

Input to Basic Education System: Numbers of Schools and Teachers

There has been a significant increase in the total number of schools and teachers in recent years. The

number of public schools has increased by 18.4 percent from 2010 to 2017.15 Although the number of public

elementary schools has grown only marginally by 1.2 percent from 2010 to 2017, the number of public

14Although the MDG and EFA goals use the term “primary”, the same refers to “elementary”. Elementary level NER was the

indicator used by the GOP to monitor this target (e.g., Philippine Development Plan 2011-2016; Progress Reports on the

Millennium Development Goals by the National Economic and Development Authority). To meet the MDG and EFA targets of

universal access to primary education, the Philippines should have reached 100 percent elementary level NER by the year 2015. 15Data on private schools is available only from 2013 onwards, whereas data on public schools is available from 2010.

0%

20%

40%

60%

80%

100%

120%

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

200

9

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

200

9

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

201

6

201

7

Kindergarten Elementary JHS SHS

GER NER

4

secondary schools more than doubled over the same period due to the opening of additional schools with

the introduction of the SHS program in 2016.

Number of private schools also expanded substantially. Private schools make up about 30 percent of

elementary schools and 40 percent of the total number of JHS and SHS. About 10.7 percent of children in

junior and senior high schools are in private schools, and the increase in the number of private schools has

continued to outpace the growth in public school numbers. In preparation for the introduction of SHS, the

total number of schools across both public and private sectors grew by 19 percent from 2015 to 2016, with

public schools expanding by nearly 14 percent and private schools by 33 percent.16 The rapid expansion of

private schools has been helped by public-private partnerships that incentivize private school operators,

such as the Education Service Contracting for JHS and the SHS Voucher Program (see Box 8).

Despite the increase in the total number of schools, classroom ratios have shown variable

improvement, depending on the education level. The secondary level student-classroom ratio has

decreased from 53:1 in 2011 to 39:1 in 2016, close to the ideal class size for Grades 7 to 10, by DepEd

standards.17 At the elementary level, classroom ratios have remained stagnant from 2011 to 2016 at nearly

35:1, which is just within the DepEd limits, despite the expansion in school numbers. To address classroom

shortages, schools often resort to double-, triple-, or even quadruple-shifts. According to the PETS-QSDS

(2016), the proportion of schools operating multiple shifts fell from 11 percent in 2011 to 6.5 percent in

2014. This suggests that the increase in the number of schools has reduced the proportion of schools

operating multiple shifts; however, some schools did not necessarily translate to better class sizes across

the basic education system equally.

The total number of teachers in public basic education grew by an average annual rate of 4.9 percent

from 2011 to 2017. With the introduction of universal kindergarten and SHS, public elementary and

16Public senior high schools are either standalone schools or situated within existing JHS or Integrated Schools (i.e., schools

offering both elementary and JHS levels). 17According to the DepEd Planning and Programming Division, the current standards for class sizes are as follows: ideal class size

of 30 learners to a maximum of 35 learners for Grades 1 to 3, ideal class size of 40 learners to a maximum of 45 learners for Grades

4 to 10, and a maximum class size of 40 learners for Grades 11 to 12.

Box 4: Early Childhood Education and School Readiness

Pre-school programs targeting children ages 3-6 years can foster foundational skills and boost children’s

ability to learn. Children who attend pre-school have higher attendance and better achievement in primary

school. Moreover, they are less likely to repeat, drop out, or need remedial or special education, all of

which benefit not only students but also education systems because efficiency is increased (Klees,

2017). Across countries at all income levels, the most disadvantaged children benefit most from quality

early child education programs (Britto et al., 2016). However, early child education programs are not

all equally effective; overly academic and structured programs for children under 5 years may undermine

their cognitive and socioemotional skills, as well as their motivation to learn, because young children learn

best through exploration, play, and interaction with others (Whitebread, Kuvalja, & O’Connor, 2015). Key

elements of programs that have led to strong pre-school outcomes include curriculums that foster crucial

pre-academic abilities (i.e., emotional security, curiosity, language, self-regulation) through play,

professional development plus coaching that enable teachers to effectively implement relevant

curriculums, and positive, engaging classrooms that promote children’s innate drive to learn (Phillips et

al., 2017). For early child education gains to be sustained, the content, budget, and capacity of providers of

pre-school programs should be integrated into formal education systems. In addition, the quality of

subsequent learning environments in primary school is an important determinant of the long-term effects

of pre-school programs.

Source: World Bank, World Development Report 2018: Learning to Realize Education’s Promise (2018).

5

2009 2010 2011 2012 2013 2014 2015 2016 2017

Elementary 358,078 361,564 363,955 377,831 401,913 417,848 448,966 450,134 462,299

Secondary 142,518 146,269 150,516 169,743 201,651 219,710 243,321 237,083 246,095

Elementary PTR 38.65 39.38 40.93 39.79 40.36 36.17 33.18 32.19 30.84

Secondary STR 38.00 37.81 37.05 33.24 34.06 26.98 24.71 26.06 25.64

-

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

-

100,000

200,000

300,000

400,000

500,000

Pu

pil-

/Stu

den

t-Te

ach

er R

atio

Nu

mb

ero

f Te

ach

ers

secondary school teachers increased 41 percent between 2009 and 2017 outpacing the growth in student

enrollment. This reduced student-teacher ratios from 39:1 in 2011 to 31:1 in 2017 at the elementary level,

and from 38:1 in 2011 to 26:1 in 2017 at the secondary level (Figure 6).

Figure 5: Total Number of Schools by Level, SY 2010-2011 to SY 2017-2018


Figure 6: Number of Teachers and Teacher Ratios, SY 2009-2010 to SY 2017-2018


Trends in Internal Efficiency

Measures such as cohort survival, repetition, and dropout rates, among others, estimate how efficiently

education systems combine inputs to produce education outputs. They indicate whether the education sector

works to maximize education outputs while minimizing wastage. Because internal efficiency is concerned

with inputs, processes, and outputs, greater internal efficiency contributes to improving the overall quality

of education. This section discusses trends in internal efficiency in basic education. Data presented refers

to public and private school performance together, as the DepEd EBEIS data are not disaggregated by

sector. Furthermore, figures for secondary level refer to JHS only, as SHS data on these indicators are not

available.

38,690 38,648 38,657 38,803 38,913

7,914 7,976 8,082 8,282 8,554 6,184 6,718

46,60454,185

10,450 10,562 10,936 11,680 12,191

5,381 5,432 5,492 5,935 5,9664,373 4,609

15,831

22,766

49,140 49,210 49,593 50,483 51,104

13,295 13,408 13,574 14,217 14,520 10,557 11,327

62,435

76,951

-

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

2013 2014 2015 2016 2017 2013 2014 2015 2016 2017 2016 2017 2013 2017

Elementary JHS SHS TotalPublic

6

Cohort Survival

Cohort Survival Rate (CSR) 18 has improved at the elementary level (Figure 7). From 2007 to 2017,

elementary CSR increased substantially by 20 percentage points. This is a marked improvement from the

modest increase of 5.3 percentage points in the 17-year period between the years 1990 and 2007. The

upward trend in elementary CSR noticeably started in SY 2012-2013 with the start of a stronger decline in

dropout rates. This period comes after the initial implementation of the universal kindergarten program in

SY 2011-2012 which appears to have helped prevent dropout and improve the likelihood of staying until

the final grade of elementary schooling. Currently, about nine out of every ten pupils entering Grade 1

successfully reach Grade 6, relative to about seven out of every ten pupils in 2009.

Figure 7: Cohort Survival and Dropout Rates by Level, SY 2009-2010 to SY 2017-2018


CSR has also steadily improved at the JHS level over the past six years.19 Although increasing at a

more modest pace than the elementary level, secondary CSR has risen 10 percentage points from the years

2007 to 2017, reaching 85.7 percent. The improvement in CSR has been accompanied by a steady decline

in the dropout rate from 8.1 percent in 2012 to 5.2 percent in 2017, but still three times higher than

elementary dropout rates. Yet, an annual grade-to-grade average dropout rate of 5.2 percent reported in

2017 is still relatively high, as it translates into nearly 15-16 of every 100 children entering JHS dropping

out before completing Grade 10. To help out-of-school youth and adults access and complete basic

education through non-formal education, DepEd has continued to implement its Alternative Learning

System (ALS), discussed in Box 5.

The need to address dropout and improve CSR at the secondary level is also apparent from household

survey data. CSR deteriorates as learners progress through secondary schooling. Using APIS data to track

the cohort of Grade 1 students in the year 2007, Figure 8 shows that grade-to-grade survival rate to

succeeding grades declined before recovering to 93 percent in the transition to Grade 8. Within the

18CSR measures the percentage of enrollees in the starting grade of a given school level (i.e. elementary, JHS, and SHS) who reach

the final grade of that level. Dropout rate refers to both students who leave during the school year and those who complete the

grade but fail to enroll in the next grade as a proportion students who enrolled in the previous grade. As defined here, the CSR

measures survival across an education level, whereas the dropout rate is an annual measure. Thus, even a low-seeming annual

dropout rate of 5 percent can correspond to a substantial deficit in cohort survival and completion. 19Secondary (JHS) CSR has been calculated as enrollees in Grade 7 who reached Grade 10. Prior to the implementation of JHS,

secondary CSR was calculated as enrollees in Year 1 who reached Year 4 of high school.

72.2%

92.4%

73.5% 84.3%

6.3%

1.6%

7.6%

5.2%

0%

2%

4%

6%

8%

10%

0%

20%

40%

60%

80%

100%

2009 2010 2011 2012 2013 2014 2015 2016 2017

Elementary Completion Secondary Completion Elementary Dropout Secondary Dropout

7

secondary level, however, CSR again began to decrease, reaching a low 67 percent as the cohort entered

Grade 10, the final grade of JHS, in 2016. Making school more attractive to students in the upper grades is

of great importance, as it is here that children are more likely to drop out of school to find work with the

rising opportunity costs of their time.

Figure 8: Grade-to-Grade Survival Rates, 2007-2017

Source: PER Team’s computations using APIS data for various years

100.0% 103.1%96.4% 93.5% 90.4% 88.7%

92.9%

83.8%

66.5%73.0%

0%

20%

40%

60%

80%

100%

120%

-

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

(2007) (2008) (2010) (2011) (2012) (2013) (2014) (2015) (2016) (2017)

Grade 1 Grade 2 Grade 4 Grade 5 Grade 6* Grade 7 Grade 8 Grade 9* Grade 10 Grade 11

Elementary JHS SHS

Students in school CSR

8

Box 5: The Philippines Alternative Learning System:

A Second Chance to Develop the Human Capital of Out-of-School Youth and Adults

Despite the remarkable progress in expanding access to basic education, education data in 2016 show that about

half of Filipino students are struggling to complete basic education on time. Estimates based on the recent

national household survey data indicate that a total of 6.5 million, comprised of 3.4 million youth (aged 16-24)

and 3.1 million young adults (aged 25-30), did not complete junior high school and are out-of-school. This figure

constitutes about 23 percent of individuals aged 15-30 (LFS, 2018).

DepEd leads in the delivery of a “second chance” program to build human capital of out-of-school youth and

adults through the implementation of the Alternative Learning System (ALS). ALS enrollees who pass the

accreditation and equivalency (A&E) exam, a DepEd-administered test assessing the competencies of those who

have neither attended nor completed elementary or secondary education in the formal school system, receive a

government credential that can facilitate access to higher education, vocational training, and overall better

employment prospects. The number of ALS learners being reached by the program has increased. According to

DepEd, the number of enrollers in ALS across the country have increased sevenfold, from 106,482 in 2005 to

833,161 in 2018.

ALS has been playing a key role in enabling school dropouts to develop their human capital and improve their

long-term educational outcomes and employment prospects. Upon the completion of ALS, 60 percent of the

enrollees who passed the A&E exam enrolled in tertiary education or vocational training. Furthermore, A&E

test passers were twice more likely to obtain full-time formal jobs compared to those who did not pass the A&E

exam. Between 2014 and 2016, about 60 percent of ALS enrollees attended learning sessions regularly and 30

percent passed the A&E exam. Female participants consistently outperformed their male counterparts, and urban

participants passed the A&E exam at a higher rate than rural participants.

There has been several challenges in the implementation of the ALS, which responds to out-of-school youth and

adults who have various motivations for learning and face diverse geographical and socioeconomic conditions.

National budget for implementation of ALS has been constrained. Though it has increased tenfold over the last

15 years, it has grown at a slower pace than that of public basic education spending. ALS has been one of the

ten big-ticket programs of DepEd, but its share in expenditure has been less than one percent. The share of ALS

in the total DepEd budget increased marginally from 2014 to 2016, but decreased to 0.14 percent in 2017 (DBM,

DepEd). In 2018, the share of the program’s appropriations in total DepEd budget further decreased to 0.01

percent. Although ALS had about 0.8 million learners in 2018, which represents 3 percent of the total students

in the K to 12 education system, the allocated budget for the program remained significantly at the lowest level.

Source: Igarashi, Tenazas, & Acosta, “Unlocking the Potential of the Bangsamoro People through the

Alternative Learning System” Philippines Education Notes (Forthcoming).

9

Completion

Over the last nine years, completion rates have generally improved (Figure 9). Completion rate refers

to the percentage of first grade entrants in a level of education who complete that level of education.20 It is

positively correlated to cohort survival and is a requirement for entering the next grade and/or level of

education. Both the CSR and the completion rate have improved considerably for both elementary and JHS,

especially since SY 2012-2013 for the latter. From 2009, elementary level completion rates grew by 20

percentage points, reaching 92.4 percent in 2017. Secondary completion rate fell as low as 57 percent in

2005 and stood at 72 percent in 2007. Currently, at least four out of every five students complete JHS.

Household data shows that nearly half a million children in the age group 12-15 years were not in school

in 2017.21 Lack of personal interest and the financial cost of education were the most commonly cited

reasons for not attending school by boys and girls in this age group.22

Figure 9: Completion Rates by Level, SY 2009-2010 to SY 2017-2018


Grade-Age Mismatch in Enrollment

Grade-age mismatch in enrollment remains high, particularly at the secondary level. At the

elementary level, the difference between GER and NER, which captures the grade and age mismatch, has

reduced from 17.4 percent in 2009 to 7.9 percent in 2017. Larger grade-age mismatch is found, however,

at the secondary level, where gaps between GER and NER are 18.7 percent in junior high schools and 20.9

percent in senior high schools. With DepEd policies indicating strict compliance to the minimum cut-off

age of 6 years old for entrance to Grade 1, it is likely that majority of learners who are not of the target

school age are overage rather than underage. The presence of overage learners may be a result of late entry

to Grade 1.23 The high proportion of overage learners may also be due to rising repetition rates, which show

small increases since 2014. While it is better to have children in school than not even if they are older for

the grade, where they receive educational and other social benefits, having a sizable population of overage

children in school has implications for pedagogy as well as for their grade-to-grade educational progress.

Teaching methods need to be different for very young children compared to older children, especially in

schools and classrooms that are already facing the problem of congestion. Finally, overage children may

also be pulled out by households before they complete different levels of schooling for domestic or labor

market work.

20Both CSR and completion rate are computed by cohort. According to DepEd’s definitions, the critical difference

between these indicators is that the CSR only measures learners who reach the final grade, not those who graduate. 21PSA, APIS 2017. 22Including the age group 6-11 years, nearly 0.7 million young children were not in school in 2017 in the Philippines

(APIS, 2017). 23World Bank, Philippines: Basic Education Public Expenditure Review (BEPER) (Washington, D.C.: World Bank Group, 2012).

72.2%

92.4%

73.5%84.3%

60%

80%

100%

2009 2010 2011 2012 2013 2014 2015 2016 2017

Elementary Secondary (JHS)

10

Figure 10: Transition Rates by Level, SY 2011-2012 to SY 2017-2018

Note: Transition from Primary to Intermediate corresponds to the transition from Grade 4 to Grade 5.


International Comparisons of Participation and Completion Rates in Basic Education

Philippines generally compares well with its regional neighbors and globally in pre-primary

education. The mandatory kindergarten policy has contributed to rising pre-primary enrollment in the

Philippines. A GER of over 100 percent and an NER of 83 percent makes participation in kindergarten (i.e.,

pre-primary enrollment) in the Philippines higher than these rates for many of its neighbors (Figure 11).

Only Japan, Hong Kong, Korea, and Macao in China do better.

Philippines’ elementary and secondary NER and completion rate comparable to regional peers. In

terms of participation rates, the Philippines compares well with an elementary NER of 94.2 percent and

secondary (JHS) NER of nearly 76 percent (Figure 12). Moreover, after falling behind neighboring

countries in 2008, the Philippines has managed to surpass Indonesia, Thailand, and Cambodia. The

Philippines also has higher secondary enrollment for its per capita income compared to some of its

neighbors, Lao, Cambodia, and Malaysia (Figure 13). The Philippines’ secondary completion rate of 84.3

percent is 5.5 percentage points above the average for the group, but its elementary completion rate of 92.4

lags 3.7 percentage points behind the average for the same group.24 The Philippines’ secondary completion

rate of 84.3 percent is 5.5 percentage points above the average for the comparison group (Figure 12), but

its elementary completion rate of 92.4 lags 3.7 percentage points behind the average for the same group.25

24The World Bank-Ed Stats defines completion rate as the number of new entrants in the last grade of a given level of education

expressed as a percentage of the total population of the theoretical entrance age to the last grade. This indicator is also known as

the “gross intake rate to the last grade of primary or secondary education”. In contrast, DepEd defines completion rate as the

percentage of a cohort of first grade entrants in a level of education who complete that level. The latest available data on the Philippines’ elementary and secondary completion rates in the UNESCO Institute for Statistics in the World Bank-

EdStats was 104 percent and 85.7 percent, respectively, in 2016. 25The World Bank-Ed Stats defines completion rate as the number of new entrants in the last grade of a given level of education

expressed as a percentage of the total population of the theoretical entrance age to the last grade. This indicator is also known as

the “gross intake rate to the last grade of primary or secondary education”. In contrast, DepEd defines completion rate as the

percentage of a cohort of first grade entrants in a level of education who complete that level. The latest available data on the

Philippines’ elementary and secondary completion rates in the UNESCO Institute for Statistics in the World Bank-EdStats was 104

percent and 85.7 percent, respectively, in 2016.

96.6%98.1%

99.7%

93.1%

91.1%90.2%

85%

90%

95%

100%

2011 2012 2013 2014 2015 2016 2017

Primary to Intermediate Elementary to JHS JHS to SHS

11

0%

20%

40%

60%

80%

100%

Elementary

NER Completion Rate

0%

20%

40%

60%

80%

100%

Secondary

NER Completion Rate

Figure 11: Pre-Primary Enrollment Rates in East Asia, 2017

Notes: Data for Philippines reflect kindergarten GER and NER as reported by DepEd.

(i) Latest available NER data for Lao PDR and GER and NER data for Japan and Korea as of 2016.

(ii) Latest available NER data for Malaysia as of 2015.

(iii) Latest available NER data for Indonesia as of 2014.

(iv) Latest available NER data for Vietnam as of 2012.

Sources: Data for Philippines taken from DepEd EBEIS; all others from UNESCO Institute for Statistics in World

Bank-EdStats, March 2018.

Figure 12: International Comparisons of Elementary and Secondary NER and Completion Rates, 2017

Notes: (i) Latest available NER data for Thailand and Indonesia as of 2015.

(ii) Latest available NER data for Vietnam as of 2013.

Sources: Data for Philippines from DepEd EBEIS; all others from UNESCO Institute for Statistics in World Bank-

EdStats, March 2018.

0%

20%

40%

60%

80%

100%

GER NER

12

Figure 13: GER and Per Capita Income in East Asia, 2017

Source: GER data for Philippines from DepEd EBEIS; all other GER data from UNESCO Institute for Statistics in

World Bank-EdStats, March 2018. GNI per capita data from World Bank-World Development Indicators, March

2018.

Quality of Basic Education: Trends in Learning Achievement

Despite increase in basic education spending and improvement in output, learning outcomes as

measured by NAT scores have remained mostly stagnant over time. The NAT Mean Percentage Score

(MPS) at the elementary level have fluctuated for all subject areas from SY 2009-2010 to SY 2014-2015,

showing little to no improvement (Figure 14). The MPS for subject areas has stayed below the maximum

of the upper average band, except for Filipino in some years. Science has the lowest MPS. Box 6

summarizes main points in interpreting the significant drop in Grade 6 NAT results in SY 2015-2016.26

For both elementary and secondary levels, critical thinking appears to be the skill needing most

improvement (Figure 16).27 Across all subject areas for both elementary and secondary, achievement

scores have failed to reach the 75 percent mark, equivalent to a level of “proficient” as set by DepEd. For

the secondary level there are few instances – information literacy and critical thinking for both Filipino and

Araling Panlipunan, and problem solving for English – where the average score crosses the 50 percent

mark. Among subject areas, Science and Math have the lowest MPS, reflecting a persistent problem. This

finding is consistent with international tests. When the Philippines participated in the Trends in International

Mathematics and Science Study (TIMSS), it had ranked 36th out of 38 for Grade 8 Math and Science in

1999, and 41st and 42nd out of 45 countries for Grade 8 Math and Science in 2003. The Philippines also

ranked poorly as 23rd out of 25 countries for Grade 4 Math and Science that same year. Similarly, in the

recent Programme for International Student Assessment (PISA) 2018, which assesses key knowledge and

26The NAT is an exit assessment administered by DepEd to Grades 6, 10, and 12 students. Although the NAT had previously also

been administered to Grade 3 learners, the assessment for this grade level was replaced by the Language Assessment for the Primary

Grades in 2014 and the Early Language, Literacy, and Numeracy Assessment in 2016. As the NAT has undergone several changes

over the past few years, the discussion in this section focuses mainly on NAT results from 2009 to 2015 for comparability. Prior to

the shift in test design in 2016, the NAT scores were reported as mean percentage scores (MPS) organized by core subject area. An

MPS of at least 51 percent was interpreted as above average, while an MPS of at least 76 percent was considered superior. 27Beginning SY 2016-2017, the NAT design shifted in alignment with the K to 12 curriculum, focusing on the 21st century skills

of problem solving, information literacy, and critical thinking. This NAT and the historical NAT are no longer comparable as they

are considered different assessments. Moreover, along with traditional academic knowledge, the development of such 21st century

abilities are essential, as emerging evidence suggests that non-cognitive skills, also known as socioemotional skills, are positively

correlated with employment status, higher earnings, and higher educational attainment.

Cambodia

Thailand

MalaysiaIndonesia

Lao PDR

Vietnam

Philippines

Cambodia

Thailand

Malaysia

Indonesia

Lao PDR

VietnamPhilippines

60%

70%

80%

90%

100%

110%

120%

130%

0 5,000 10,000 15,000 20,000 25,000 30,000

Elementary Secondary

13

skills of 15-year-old students, the country ranked second to last in Math and Science among 79 participating

countries and economies.

Low student achievement in Math and Science may be reflective of poor teacher preparation or

competency in these subject areas. The Process Skills Test (PST) in Science and Math has been

administered to teachers across two grade levels every year, beginning with Grades 1 and 2 in 2012.

Performance on the PST has been poor, averaging as high as only 54 percent for elementary school teachers

and 62 percent for secondary school teachers (Table 1). Similarly, Grades 6 and 10 teachers scored poorly

on content knowledge assessments in Math and Science, among other subject areas. 28

Figure 14: Grade 6 NAT Mean Percentage Scores, SY 2008-2009 to SY 2015-2016

Source: DepEd Bureau of Education Assessment.

Figure 15: Grade 10 NAT Mean Percentage Scores, SY 2008-2009 to SY 2014-2015


28Al-Samarrai, S., Assessing Basic Education Service Delivery in the Philippines: Public Education Expenditure Tracking and

Quantitative Service Delivery Study (PETS-QSDS) (Washington, D.C.: World Bank Group, 2016).

0

25

50

75

100

Filipino Mathematics English Science HEKASI Overall

2008-2009

2009-2010

2010-2011

2011-2012

2012-2013

2013-2014

2014-2015

2015-2016

Superior (76-100%)

Upper Average (51-75%)

Lower Average (26-50%)

0

25

50

75

100

Filipino AralingPanlipunan

Mathematics Science English Critical Thinking Overall

2008-2009

2009-2010

2010-2011

2011-2012

2012-2013

2013-2014

2014-2015

Superior (76-100%)

Upper Average (51-75%)

Lower Average (26-50%)

14

Figure 16: Grade 6 and Grade 10 NAT Mean Percentage Scores, SY 2016-2017


0

25

50

75

100 Problem Solving

Information Literacy

Critical Thinking

Highly Proficient(90-100%)

Proficient (75-89%)

Nearly Proficient(50-74%)

Lowly Proficient (25-49%)

Grade 10Grade 6

Box 6: How to Interpret the Results of Grade 6 NAT in SY 2015-2016

While historical data of the National Achievement Test (NAT) administered with Grade 6 and Grade 10 students has been

showing consistent patterns, scores from the SY 2015-2016 round with Grade 6 shows a sudden and big drop across all

subjects by 27 percentage points on average. Note that NAT for Grade 10 did not take place in the same year.

The drop seems related to the shift in the timing of undertaking NAT in that year. While NAT is normally administered at the

end of each school year, which is around February to March, delays in the implementation of NAT for SY 2015-2016 pushed

its administration between June and July 2017 (SY 2016-2017). As a result, the target of Grade 6 students had already moved

up to Grade 7, the first year of junior high school.

The substantial drop in the scores in 2015-16 can be explained by factors as follows:

• Students forgetting the tested content due to an increased amount of time between when they were taught (Grade 6) and

when they were tested (Grade 7).

• Lower student motivation due to the test being moved from Grade 6 to Grade 7 and possibly viewed as having less

relevance to their lives.

• A change in the population of students assessed. The same cohort was targeted, but with the shift in NAT

administration, there was a slight change in segments of the population. For example, enrollment ratio of public schools

to private schools decreases between elementary school and junior high school education levels, which potentially

affects the NAT sampling framework. NAT is administered on a census base with public schools but on a sample base

with private schools.

• Errors in data collection or analysis. The same protocol should have been used, but the current available data does not

allow to recalculate mean percentage scores.

With these limitations, the NAT data in SY 2015-2016 (with Grade 7 students) are not comparable to those from previous

years (with Grade 6 students) and should not be included on the same trend line. It is important that DepEd maintain the same

assessment framework, target sample, sample design, and so on in order to measure change over time.

15

Table 1: Process Skills Test for Grades 1 to 10 Teachers, 2012-2017

Grades Year of Administration Mean Percentage Score Std. Dev.

Grade 1 2012 47.0 12.4

Grade 2 2012 45.1 12.4

Grade 3 2013 49.6 14.0

Grade 4 2013 50.3 14.3

Grades 5 & 6 2015 54.1 5.2

Grades 7 & 8 2016 61.4 5.6

Grades 9 & 10 2017 62.4 5.6

Note: Separate results per grade level are only available for Grades 1 through 4.


To enhance student learning, DepEd has sought to improve teacher quality through a series of

programs and projects. These include the national adoption and implementation of the Philippine

Professional Standards for Teachers in 2017 and the partnership between DepEd and the Department of

Science and Technology the Capacity Building Program in Science and Mathematics Education in 2018.

In 2019, the plan to transform the National Educator Academy of the Philippines (NEAP), a unit responsible

for in-service training of teacher and non-teaching personnel in the public basic education system, has been

approved.29

Conclusion

In recent years, participation rates in the elementary and JHS levels have reached their highest points

since 2000. Participation in elementary education is near universal. With kindergarten being mandatory,

coverage of children who are 5 years old in pre-school programs can be expected to continue to rise.

However, participation in secondary education lags by nearly 25 percentage points in junior high schools

and over 55 percentage points in senior high schools for attainment of universal secondary education, which

is a Sustainable Development Goals (SDG) 4 indicator. Higher elementary NERs demonstrate the

Philippines’ advancement towards universal access to elementary education; however, reaching the “last

mile” learner remains a persistent obstacle. Cohort survival and completion rates have also improved

significantly. Despite this progress, challenges remain. Improvement in participation, cohort survival, and

completion rates at the secondary level have been at a slower pace than the elementary level.

Increasing enrollment has been accompanied by more schools and teachers in basic education. The

rate of growth in the teacher population has been faster than that of students, reducing student-teacher ratios.

Though student-teacher ratios have decreased at the national level, challenges persist in the allocation of

teachers across regions and within regions, as will be discussed in the next chapter.

Despite progress made in access and output indicators, education quality as measured by learning

achievement has shown little improvement over time. Due to many changes in the NAT, comparisons

across years are difficult to make; nonetheless, the latest mean percentage scores indicate that learning

achievement levels for both elementary and secondary have been stagnant below the level of proficiency

over time. Science continues to have the lowest MPS. Despite the stagnant performance in the NAT, a

return to participating in international assessments (PISA 2018) is an encouraging sign of the Philippines’

commitment to improve learning outcomes. Improving the quality of schooling, as with ensuring learners’

access to and completion of the education cycle, hold critical implications on future outcomes including

employment and earnings. Findings on the returns to education in the Philippines are summarized in Box

7.

29Additionally, DepEd has been working closely with the World Bank to develop a program to improve teachers’ effectiveness in

classroom, aiming to improve the teaching and learning of Math and Reading in kindergarten to Grade 6, as well as strengthen

instructional leadership at the field level.

16

Box 7: Returns to Education in the Last 15 Years

The rates of returns to education inform individuals in calculating the optimal amount of schooling, and

policymakers in strategizing how to invest in education for countries’ long-term development goals. Evidence

around the world suggests that educational attainment levels are closely associated with lifelong earning profiles.

Plotting nominal wages by education level over time shows that mean earnings vary by educational attainment for

each year of working life (Figure 17) and widens over time between those with tertiary education and below. Mean

wages for college graduates at age 20 are about 1.4 times than for high school (HS) graduates, 1.7 times than for

those with only an elementary level schooling, and 1.8 times than for those with no schooling. By age 64, mean

wages for college graduates are about 2.6 times than for HS graduates, 3.6 times than for those with only an

elementary level of education, and 4.1 times than for those with no schooling. Earning profiles for workers who

did not complete any level of education are homogeneous at very low levels across age.

Returns to schooling have declined between 2003 and 2018 for elementary and secondary education though both

remain positive. Returns to tertiary education are not only the highest but have remained above 16 percent over the

same time period. Near universal elementary education and increasing coverage of high school education have

depressed returns to these levels of schooling. Declining returns to elementary and secondary education may also

be an effect of increasing demand for higher skilled labor in the economy, which requires more advanced degrees.

Returns to education differ significantly and consistently between men and women except for elementary

education. This is in line with international evidence on returns to gender by level of education.

Figure 17: Mean Nominal Pay for Wage Earners (in PhP), by Education Level and Age

Note: Those engaged in the informal sector, self-employment, and household help are omitted

though they have sources of incomes for convenience in comparison.

Source: LFS January 2018.

Figure 18: Returns to Different Levels of Education

Note: Based on a standard Mincerean model using LFS data for 2003, 2008, 2013, and 2018. Dummy variables for

regions are also included to control variations across different localities.

Source: LFS for various years. PER team calculations.

0

200

400

600

800

1,000

1,200

15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63

Dai

ly p

ay (

Ph

P)

Age

No level Elementary level High school level Tertiary level

3.2% 2.5% 2.3% 1.6%

8.0% 7.6% 7.2%6.1%

16.9%15.8%

19.2%16.4%

2003 2008 2013 2018 2003 2008 2013 2018 2003 2008 2013 2018

Elementary level High school level Tertiary level

17

Figure 19: Rate of Private Returns to Different Levels of Education, by Gender

Note: Based on a standard Mincerean model using LFS data for 2003, 2008, 2013, and 2018. Dummy variables for

regions are also included to control variations across different localities. Source: LFS for various years. PER team calculations.

The level of education attainment of female workers has advanced rapidly in the last 20 years (Figure 20). In 2018,

40 percent of women who had formal sector jobs (compared to 20 percent in 1998) had at least a tertiary degree,

and only 16 percent had less than secondary education. In contrast, only about 14 percent of males with formal

sector jobs had tertiary education, and more than 40 percent had less than secondary education.

Emerging research shows that years of formal schooling and levels of educational attainment are proxy measures

and inadequate measures of workforce skills. Acosta et. al (2017) show that one-third of Filipino employers report

being unable to fill vacancies because of a lack of applicants with requisite skills, especially socioemotional skills,

also known as “noncognitive skills,” “soft skills,” or “behavioral skills.” Their finding confirmed that one standard

deviation in socioemotional skills is associated with a 9-percent increase in average daily earnings (approximately

USD 2), even after controlling for years of schooling and cognitive skills. Higher levels of socioemotional skills

are also correlated with a greater probability of being employed, having completed secondary education, and

pursuing tertiary education.

Figure 20: Educational Attainment Levels Among Wage Earners, by Gender

Source: LFS for various years. PER team calculations.

3.3%1.7%

6.8%5.1%

15.0% 14.7%

2.9%1.2%

11.6% 11.0%

17.9% 17.6%

2003 2018 2003 2018 2003 2018

Elementary level High school level Tertiary levelMale Female

0

20

40

60

80

100

1998 2018 1998 2018

Male FemaleNo level Elementary level High School level Tertiary level

18

Figure 21: Socioemotional Skills and Labor Income

Note: Bars filled with solid color are at a significance level of 0.05, and bars with lighter colors means that statistical

significance are not confirmed.

Source: Acosta, Igarashi, Olfindo, & Rutkowski, WB STEP Skills Measurement Survey for the Philippines (2017).

0 2 4 6 8 10 12

Years of education (alone)

Years of education (with SE skills)

Reading

Numeracy

Emotional stability

Agreeableness

Grit

Conscientiousness

Decision-making

Openness

Extraversion

Edu

cati

on

Co

gnit

ive

skill

sSo

cio

-em

oti

on

al s

kills

% return

19

0% 20% 40% 60% 80% 100% 120%

ARMM

NCR

CAR

I

IV-B

VIII

CARAGA

IX

V

II

VI

XI

XII

IV-A

III

VII

X

2017-2018 NER 2017-2018 GER2010-2011 NER 2010-2011 GER

Chapter 2 – Equity in Basic Education

While there has been overall progress at the national level, persistent inequalities remain for certain regions

and population groups. In this chapter, we examine equity in access to education, quality of schooling, and

learning achievement of different geographic areas, economic groups, and genders. Data used in this chapter

are taken from the DepEd EBEIS and several rounds of the APIS.

Equity in Access

Regional Access

Kindergarten participation rates have increased nationally and in all regions due to the mandatory

kindergarten policy. National level GER in kindergarten increased from 79.4 in 2010 to 102.0 in 2017,

and NER rose from 57.2 percent in 2010 to 83.7 percent in 2017. Regional kindergarten GERs and NERs

have also become more equal over time as the gap among regions narrowed. In 2010, kindergarten

enrollment rates varied from as low as 57.5 percent (Region II) to 101.4 percent (Region I) for GERs, and

38.8 percent (NCR) to 79 percent (CARAGA) for NERs. In 2017, this had narrowed to a range between

108.7 percent (Region X) and 89.7 percent (NCR) for GERs, and between 60.6 percent (ARMM) to 91.4

percent (Region VII) for NERs. While ARMM had the lowest kindergarten NER and GER among all

regions, gaps between ARMM and the national average GER is modest, indicating a reasonably high take-

up of this program by households. The large gap between GER and NER also indicates that prior to the

introduction of universal kindergarten, households in ARMM were the least likely to send their 5-year-old

children to pre-school programs.

Figure 22: Kindergarten Enrollment Rates, by Region, SY 2010-2011 and SY 2017-2018


20

0% 20% 40% 60% 80% 100% 120%

ARMM

NCR

CAR

I

IV-B

VIII

CARAGA

IX

V

II

VI

XI

XII

IV-A

III

VII

X

2017-2018 NER 2017-2018 GER2009-2010 NER 2009-2010 GER

While national elementary GER and NER have improved, some regions continue to lag considerably

behind (Figure 23). In 2017, elementary level GERs ranged from 89.2 percent (ARMM) to 111.1 percent

(Region X), and NERs ranged from 72.6 percent (ARMM) to 98.5 percent (Region II). Although NERs

improved for most regions during this period, some saw declines in enrollment rates. Most noticeably,

CAR, which had the highest NER in 2009 at 99.5 percent, fell five percentage points to 94.4 percent in

2017.

Figure 23: Elementary Enrollment Rates, by Region, SY 2009-2010 and SY 2017-2018


The JHS level shows greater regional variations compared to the elementary level (Figure 24). Overall

JHS participation rates, especially GERs, have improved in all regions. NERs have also improved due to

declining grade-age mismatch in all regions. Compared to a range of 10.1 percent (ARMM) to 76.7 percent

(NCR) in 2009, JHS NERs in 2017 were between 30.4 percent (ARMM) to 85.6 percent (Region I).

Additionally, the first two years of implementation of the SHS program has shown variable performance

across regions (Figure 25). GERs ranged from a low of 22.3 percent in ARMM to a high of 83.1 percent in

NCR, and NERs from 8.7 percent in ARMM to 62.7 percent in NCR in 2017.

ARMM consistently had the lowest participation rates among all regions across all levels of

education. In 2017, NERs in ARMM fell below the national average by about 23 percentage points in the

kindergarten level, 21 percentage points in the elementary level, 45.6 percentage points in the JHS level,

and 37.4 percentage points in the SHS level. When ARMM is removed from the computation, NERs

become more equal across regions, with standard deviations reduce by nearly half for all education levels.

21

Elementary CSR and completion rates have become moderately less varied across regions from 2009

to 2017 (Figure 26). In 2009, elementary CSRs and completion rates ranged from about 38 percent

(ARMM) to about 86 percent (Region IV-A); in 2017, all regional CSRs and completion rates were above

90 percent, with the exception of ARMM which fell considerably behind at 54 percent.

JHS level CSR and completion rates have become more equal across regions, excluding ARMM

(Figure 27). In 2017, regional JHS CSRs were between 80 to 91 percent, except for ARMM, which reported

a CSR of 63.2 percent. Similarly, regional JHS completion rates ranged between 78 to 91 percent, except

for ARMM, which had a completion rate of 62.1 percent. Moreover, while CSR and completion rates

increased from 2009 to 2017 for almost all regions, ARMM showed declines in these indicators over the

same period. JHS level dropout rate in ARMM also increased from 11.2 percent in 2010 to 14.1 percent in

2017. When ARMM is removed from the analysis, inequalities in CSR and completion rates across regions

are decreased, as indicated by standard deviations cut by over half at the JHS level and by about 75 percent

at the elementary level.

Figure 25: SHS Enrollment Rates, by Region,

SY 2016-2017 and SY 2017-2018

Figure 24: JHS Enrollment Rates, by Region,

SY 2009-2010 and SY 2017-2018

0% 20% 40% 60% 80% 100% 120%

ARMM

X

IX

XII

IV-B

II

VIII

CARAGA

XI

CAR

V

III

VI

IV-A

I

VII

NCR

2017-2018 NER 2017-2018 GER2009-2010 NER 2009-2010 GER

Source: DepEd EBEIS. Source: DepEd EBEIS.

0% 20% 40% 60% 80% 100% 120%

ARMM

IX

XII

XI

X

CARAGA

VIII

IV-B

V

CAR

II

VI

VII

III

IV-A

I

NCR

2017-2018 NER 2017-2018 GER2016-2017 NER 2016-2017 GER

22

Economic Disparities

Across regions, poverty incidence (measured by PSA) is significantly negatively correlated with NER,

CSR, and completion rate at the elementary level. At the JHS level, poverty incidence is even more

strongly negatively correlated with the same indicators, as well as with GER (Figure 28). Overlaps exist

between poverty and geographic locations. Highly urbanized regions such as NCR and Region IV-A have

lower poverty incidences compared to regions that are predominantly rural, such as ARMM, CARAGA,

and Region VIII. Although improvements are seen at the national level, access to and completion of

education continue to be a problem among poorer regions.


0% 20% 40% 60% 80% 100%

ARMM

IX

CARAGA

CAR

XII

X

XII

IV-B

VII

VIII

V

II

VI

NCR

III

I

IV-A

2017-2018 Completion Rate2017-2018 CSR


Figure 26: Elementary Completion and Cohort Survival

Rates, by Region, SY 2009-2010 and SY 2017-2018

Figure 27: JHS Completion and Cohort Survival Rates,

by Region, SY 2009-2010 and SY 2017-2018

0% 20% 40% 60% 80% 100%

ARMM

IX

X

VIII

XII

XII

CAR

CARAGA

V

IV-B

VII

II

VI

III

I

NCR

IV-A




23

0%

20%

40%

60%

80%

100%

120%

140%

160%

Quintile 1 (Poorest) Quintile 2 Quintile 3 Quintile 4 Quintile 5 (Richest)

Kindergarten GER Elementary GER

JHS GER SHS GER

Kindergarten NER Elementary NER

JHS NER SHS NER

Figure 28: Correlations Between Poverty Incidence and Various Education Indicators, by Region, 2015

Sources: Poverty incidence data from Official Poverty Statistics of the Philippines Full Year 2015, PSA; education

indicators data for SY 2014-2015 from DepEd EBEIS.

Across income quintiles, disparities in access to education also persist. Household survey data from

APIS 2017 show that NERs across all levels of basic education continue to be lowest for children from the

poorest families (Figure 29), similar to the findings in BEPER (2012).

Figure 29: Gross and Net Enrollment Rates, by Income Quintile, 2017

Source: Basic data from APIS 2017.

Elementary and JHS school participation increases with income quintiles. Compared to other levels,

disparities in elementary GERs and NERs across income quintiles are relatively small. The largest gap in GERs is 4.6 percentage points between the third and fourth quintile, while the largest gap in NERs is 3.8

percentage points between the first and second quintile. Although elementary NERs increased from 2004

to 2017 across all income quintiles, gains are largest for poorest households, where participation rates

increased by 7.5 percentage points.

Inequalities in GERs and NERs across income quintiles are starker at the JHS level, where financial

cost of schooling is cited by children ages 12-15 years as one of the main deterrents to attending school. At

the JHS level, GERs among children from the poorest households is 9 percentage points lower than that of

0

20

40

60

80

100

120

0 10 20 30 40 50 60

Per

cen

tage

Poverty Incidence

Elementary

GER NER Completion Rate Cohort Survival Rate

r = -0.60*

r = -0.12

r = -0.55*

r = -0.66*

0

20

40

60

80

100

120

0 10 20 30 40 50 60

Per

cen

tage

Poverty Incidence

JHS

GER NER Completion Rate Cohort Survival Rate

r = -0.72*

r = -0.72*

r = -0.80*

r = -0.90*

24

0%

20%

40%

60%

80%

100%

120%

Public Private Public Private Public Private Public Private Public Private

Quintile 1 (Poorest) Quintile 2 Quintile 3 Quintile 4 Quintile 5 (Richest)Elementary GER JHS GER SHS GER Elementary NER JHS NER SHS NER

the richest households. The gap in NERs is even larger at 21 percentage points, revealing that low income

remains a hindrance to school enrollment. Disparities across income groups are most striking at the SHS

level, where both GERs and NERs clearly rise as income increases. SHS participation among children from

the fifth (i.e., richest) quintile was noticeably stronger compared to other quintiles. This suggests that

majority of families are unable to afford the costs associated with attending SHS or the opportunity cost is

much higher at that level. Across all income groups, however, SHS GERs and NERs were lowest among

all levels of basic education. Even among the richest households, SHS GER and NER remained 10

percentage points behind that of JHS and over 15 percentage points behind that of elementary. For children

in the age group 16-17 years, corresponding to the official school ages for SHS, lack of personal interest

and high cost of education are cited as the main hindrances for not attending school. It is also in this age

group that employment-seeking becomes a common reason for not attending school, pointing to the high

opportunity cost of schooling as a key impediment to SHS participation.

Gaps between GER and NER, pointing to the presence of overage learners, especially in

kindergarten. With many overage learners at the kindergarten level, the problem of grade-age mismatch

will persist as learners proceed through each level of schooling. Mandatory kindergarten, however, appears

to have resulted in the largest gains for the poorest households. In 2010, kindergarten NERs among the

poorest families trailed behind upper middle income households by 29.1 percentage points; by 2017, this

gap had reduced to 1.7 percentage points.

Richer households are more likely to send their children to private schools (Figure 30). This is true

for all levels of schooling, but particularly the case for JHS and SHS. Children from the richest quintiles

are as or more likely to attend private schools for all levels of schooling, whereas households in the first

three quintiles overwhelmingly send their children to public schools. Another interesting highlight from

Figure 30 is the smaller gap between GER and NER for richer households and for poorer households that

send their children to private schools, for all school levels.30

Figure 30: Participation Rates in Public and Private Schools, by Income Quintile, 2017

Source: Basic data from APIS 2017.

30The data does not allow us to delve deeper into what makes the poorer households with children in private schools and lower

gaps between GER and NER systematically different from other households in the same quintiles and should be an area for future

research.

25

Children from richer households are considerably more likely to transition through all the grades of

elementary and secondary schools than those of poorer households. The gap between the two groups

of children begins to open in Grade 4 and becomes larger with each additional grade, especially from Grade

7. There is more than 30 points difference between the survival of children from the first quintile from

Grade 5 on, compared to children from the richest quintile (Figure 31).

Figure 31: Grade-to-Grade Survival Rates for Poorest (Quintile 1) and Richest (Quintile 5)

Households, 2007-2017

Source: PER Team’s computations using APIS data for various years.

Gender Disparities

Lower school participation among boys than girls continues to be a problem across almost all levels

of education. Even as early as kindergarten, boys’ NERs remain slightly lower than that of girls. While the

gender gap at the elementary level has virtually closed, gender disparities in the JHS and SHS level have

worsened since 2008. Girls’ NERs are now about 10 percentage points higher than boys’ in the JHS level

and about 14 percentage points higher in the SHS level (Figure 32). One contributing factor to the gender

disparity in NERs may be the higher opportunity cost of sending boys to school as perceived by households.

This may additionally be due to the presence of larger proportions of overage, and possibly under-age, male

students, as indicated by wider gaps in GERs and NERs for boys than girls. Within regions, the largest

gender disparities in NER are found in ARMM at the kindergarten and elementary level, Region VII at the

JHS level, and Regions VII and CAR at the SHS level.

100% 101%

87% 84%

71% 74%

47%41%

100%

120%129%

117%124%

141%

128% 126%

0%

40%

80%

120%

160%

0

200,000

400,000

600,000

800,000

1,000,000

2007 2008 2010 2011 2013 2014 2016 2017

Grade 1 Grade 2 Grade 4 Grade 5 Grade 7 Grade 8 Grade 10 Grade 11

Elementary JHS SHSStudents in school (Quintile 1) Students in school (Quintile 5)CSR (Quintile 1) CSR (Quintile 5)

26

Figure 32: Gross and Net Enrollment Rates, by Gender, SY 2000-2010 to SY 2017-2018


Gender disparities in CSR and completion rates too persist and are more pronounced at the JHS

level. More girls than boys reach and complete the final grade of elementary and JHS schooling. In 2009,

girls’ elementary and JHS completion rates were about 10 percentage points higher than boys’ (Figure 33).

In 2017, the gender gap decreased to 4 percentage points in the elementary level but remained high at 7

percentage points at the secondary level.

Figure 33: Cohort Survival and Completion Rates, by Gender, SY 2000-2010 to SY 2017-2018


Low completion and cohort survival rates of males may be due to repetition or school dropout, which

are more pronounced at the secondary level. In 2017, secondary level dropout rates for males and females

were 6.7 percent and 3.7 percent, respectively. Across all regions, males were more likely than females to

leave school in regions that are predominantly agricultural, with high production of major crops such as

0%

20%

40%

60%

80%

100%

120%

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

09

20

10

20

11

20

12

20

13

20

14

20

15

20

16

20

17

20

16

20

17

Kindergarten Elementary JHS SHSMale GER Male NER Female GER Female NER

0%

20%

40%

60%

80%

100%

200

9

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

200

9

201

0

201

1

201

2

201

3

201

4

201

5

201

6

201

7

Elementary JHS

Male CSR Male Completion Rate Female CSR Female Completion Rate

27

corn, coconut, and sugarcane.31 A major demand-side barrier to school completion is absenteeism from

school due to work, particularly among rural farming communities.32 This is especially common among

boys, who leave school to work during harvest season. As they get older, these boys are less likely to return

to school altogether and eventually drop out of the education system.33

Gender disparities are also reflected by household survey data. The APIS 2017 reveals that there are

over twice as many boys than girls in the age group 6-15 years old who are currently not attending school.

(Figure 34) Furthermore, the number of out-of-school children ages 12-15 are nearly double those in the

6- to 11-year-old age group. For both boys and girls ages 12-15, financial concerns are cited as one of the

most common reasons for not attending school. In secondary schools, school participation is lowest among

children from the poorest households. Moreover, large gaps in SHS enrollment between the top 20 percent

and of the remaining income groups reflect the struggle to cover the costs of two added years of education.

This suggests that programs alleviating financial burden such as the 4Ps/CCT program could potentially

help encourage school participation and prevent poor children, especially boys and older students, from

dropping out to pursue work, but the 4Ps/CCT program covers children who are 18 years old and below. In

addition, equity in access to education is also addressed through public-private partnerships, as discussed

in Box 8.34

Figure 34: Percentage of Children of Junior High School Age (12-15 years) and

Senior High School Age (16-17) Who Are Not in School, by Income Quintile and Gender, 2017

Source: PER Team’s computations using APIS 2017.

31PSA, Selected Statistics on Agriculture 2018. 32David and Albert (2012; 2015) 33David and Albert (2012) make a special note about urban poor regions. In urban areas, as well as for some cases of dropout among

younger children in rural areas, the decision to leave school precedes the choice of putting children to work. In other words, parents

do not choose to take boys out of school to work, but put boys to work because they have already dropped out of school. For these

cases, the main reason for leaving school is the inability to cover the financial costs of education. Such distinctions in the causes

of dropout, the authors note, are important considerations in designing appropriate interventions. 34In the selection of grantees for the programs discussed in Box 8, preference is given to graduates of public schools. Grant amounts

depend on the income class of the locality of the school, where grants are highest in NCR, followed by highly urbanized cities

outside of NCR, then by all other cities outside of NCR. For the SHS Voucher Program, all Grade 10 graduates of public JHS are

automatically eligible to receive the full amount of SHS vouchers. Grade 10 completers from private JHS who are ESC grantees

are automatically eligible to receive 80 percent of the full voucher value, as DepEd recognizes such students have some capacity

to pay for SHS tuition as they are paying students in private schools.

7%

16%

4%

17%

3%

10%

1%

7%

2%4% 4%

12%

3%

9%

1%

5%

1%

6%

4%

1%

2%

5%

0%

5%

10%

15%

20%

25%

JHS Age SHS Age JHS Age SHS Age JHS Age SHS Age JHS Age SHS Age JHS Age SHS Age JHS Age SHS Age

Quintile 1(Poorest)

Quintile 2 Quintile 3 Quintile 4 Quintile 5(Richest)

Total

Males Females

28

Equity in School Quality

Overcrowding in schools is generally considered unconducive to teaching and learning processes. Larger

enrollment sizes would require more school inputs like teachers and classrooms; as such, student-teacher

and student-classroom ratios are often used as proxies for school quality.35 Adequate school inputs are

critical to education access and learning achievement. Multivariate analysis by Maligalig et al. (2010), for

instance, found that each unit increase in student-teacher ratios reduces the likelihood of school attendance

among 6- to 12-year-old children by 2 percent. This section discusses equity in school quality in terms of

school sizes, teacher and classroom ratios, and teacher qualifications.

School Numbers and Sizes

Growth in number of schools have been slowest for poor and rural regions while school sizes vary

substantially. Between 2010 to 2017, among all regions, annual average rate of growth in the number of

schools was slowest for ARMM (0.9 percent), followed by other rural areas such as Region VIII and CAR

(both at 1.8 percent), compared to the national rate (2.5 percent). In contrast, the number of schools in NCR,

Region VII, and Region XII increased at a faster pace than the national average, with average annual growth

rates of 4.1 percent, 3.3 percent, and 4.2 percent, respectively. However, school sizes vary across regions.

NCR had the least number of schools (792 schools) but the largest median school size (2,107 enrollees per

school) in 2017 (Figure 35). CAR had the least number of schools (1,828 schools) but also the smallest

median school size (114 enrollees per school). Even with the larger school sizes in urban and populated

cities than other areas within the same region, school congestion issues are pronounced in urban centers

across countries with the severest problems in in NCR and Region IV-A.

35e.g., Albert & Raymundo, Trends in out-of-school children and other basic education statistics, Discussion Paper Series No.

2016-39; Maligalig, Caoli-Rodriguez, Martinez, & Cuevas, Education outcomes in the Philippines, ADB Economics Working

Paper Series No. 199, May 2010.

Box 8: Increasing Access to Education through Public-Private Partnerships

With the implementation of K to 12, Government Assistance to Students and Teachers in Private Education

(GASTPE) has expanded its programs of assistance to provide financial support for students to attend JHS and SHS

in certified private and non-DepEd public schools. These programs not only support students in enrolling and

completing their education, but also help address the problem of overcrowding in public schools.

Through the Educational Service Contracting (ESC) Program for JHS, qualified elementary school graduates are

extended financial assistance to attend JHS, or Grades 7 to 10, in private schools. The number of ESC grantees has

grown from nearly 600,000 beneficiaries in 2010 to over a million students in 2018. In 2015, 79 percent of grantees

completed JHS.

The SHS Voucher Program provides financial aid for students to enroll in private and non-DepEd public schools.

In 2017, over 1.2 million qualified voucher recipients were enrolled in Grades 11 and 12 (which is 47.3 percent of

total enrollment in Grades 11 and 12; and 93.8 percent of all enrollment in private schools in these grades). In 2018,

86 percent of voucher program grantees successfully completed SHS. Additionally, the Joint Delivery Program for

SHS offers financial assistance to students in DepEd public senior high schools, allowing them to pursue Technical-

Vocational-Livelihood (TVL) specializations in partner TVL institutions.

29

0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000

CAR

VIII

II

IX

CARAGA

IV-B

ARMM

X

I

VI

VII

V

XII

XI

III

IV-A

NCR

Median School Size Average School Size Number of Schools

Figure 35: School Sizes, by Region, SY 2017-2018


Both very large and very small schools pose problems of access and quality. Larger school sizes may

imply higher school congestion, which presents a hindrance to accessing available education services.

Parents often perceive overcrowding as an indication of lower school quality and thus feel discouraged to

send their children to such schools.36 However, smaller school sizes may likewise pose problems to

education equity. Areas of sparse population often have “incomplete schools” that do not offer all grade

levels, receive lower funding, and have an insufficient number of teachers.37 The nearest “complete

schools” are often a far distance away from students’ homes, creating challenges in the access to and

completion of education. CAR and Region VIII, which had the smallest median school sizes in 2017, also

had among the highest number of “incomplete schools” as classified by DepEd in 2013.

Teacher and Classroom Ratios

Regional variations in pupil- (PTR) and student-teacher ratios (STR)38 have lessened considerably

over time, particularly at the secondary level (Figure 36). In 2009, STRs ranged from 29:1 (CAR) to

53:1 (ARMM) in 2017, this narrowed substantially to a range between 21:1 (CAR) to 28:1 (ARMM). From

2009 to 2017, PTRs and STRs remained lowest in CAR. ARMM showed the greatest improvement from

2009 to 2017, but continued to have the highest PTR and STR among all regions.39

36Maligalig et al., 2010. 37David & Albert, Primary education: Barriers to entry and bottlenecks to completion, Discussion Paper Series No. 2012-07. 38In the Philippines, “pupils” refer to learners at the elementary level, while “students” refer to learners at the secondary level. 39Across all performance indicators, ARMM remains a constant outlier. The accuracy of data on ARMM is unclear, as

school-level data in the region reveal missing values for basic school information such as total enrollment and number of teachers,

which affect the computation for indicators like pupil- and student-teacher ratio.

30

0.00 10.00 20.00 30.00 40.00 50.00 60.00

CAR

VIII

II

I

CARAGA

IX

VI

V

IV-B

X

VII

XI

XII

III

NCR

IV-A

ARMM

Elementary

2009-2010 PTR 2017-2018 PTR

0.00 10.00 20.00 30.00 40.00 50.00 60.00

CAR

II

VII

NCR

I

CARAGA

VIII

III

IV-B

VI

XII

V

X

IV-A

IX

XI

ARMM

JHS

2009-2010 STR 2017-2018 STR

Figure 36: Pupil- and Student-Teacher Ratios, by Region, SY 2009-2010 and SY 2017-2018


Greater regional variation exists in classroom ratios compared to teacher ratios. Regional differences

in student-classroom ratios at the JHS level have slightly diminished over time (Figure 37). In 2011, JHS

level student-classroom ratios varied from 38:1(CAR) to 82:1 (ARMM); in 2016, variation in classroom

ratios reduced to a range between 26:1 (Region II) to 59:1 (NCR). In contrast, regional variation in

elementary level pupil-classroom ratios have remained unchanged over time and show greater variation

than their JHS level counterparts. In 2011, regional pupil-classroom ratios ranged from 25:1 (CAR) to 66:1

(NCR); in 2016, the same ranged from 24:1 (CAR) to 69:1 (NCR).

In 2017, NCR and Region IV-A had the highest pupil- and student-classroom ratios, suggesting that

overcrowding remains a problem in highly urbanized regions where school sizes are largest. In urban

areas, land is limited and expensive, making school expansion difficult and thus shortage of classrooms

becomes a problem. Even though DepEd may have the funds to build schools, DepEd cannot purchase land;

rather, lots are either provided by local governments or donated by private individuals. Moreover, urban

areas often have sudden influxes of students due to relocation, contributing further to congestion.40

40David & Albert, Recent trends in out-of-school children in the Philippines, Discussion Paper Series No. 2015-51 (Revised);

David, Albert, & Vizmanos, Out-of-school children: Changing landscape of school attendance and barriers to completion,

Discussion Paper Series No. 2018-25.

31

Figure 37: Pupil- and Student-Classroom Ratios, by Region, SY 2011-2012 and SY 2016-2017


Teacher quality is another key factor in overall school quality. In the Philippine system, teacher

positions are based on such qualifications as educational attainment, years of experience, and specialized

skills and training. Teacher III and Master Teacher positions are the highest-ranked teaching positions, and

presumably reflect better teacher quality. In 2017, the elementary level had a higher proportion of better

qualified teachers than both JHS and SHS levels. Across all education levels, teacher quality varies widely

across regions (Figure 38). In 2017, the proportion of teachers with Teacher III and Master Teacher

positions at the elementary level ranged from 12 percent (ARMM) to 66.2 percent (Region II). At the JHS

level, the same ranged from 7.4 percent (ARMM) to 62.3 percent (Region II), while at the SHS level, this

ranged from 3.2 percent (Region IX) to 58.2 percent (NCR).

Comparing the distribution of teacher qualifications and teacher ratios across regions suggests a need

for a more equitable deployment of better-quality teachers. ARMM has not only the highest PTR and

STR, but also the lowest supply of better qualified elementary and JHS teachers. In contrast, Region II,

which has the lowest PTR and STR next to CAR, also has the highest proportion of better qualified teachers.

The need for teacher redeployment to effectively address local requirements is constrained by such laws as

Republic Act No. 4670, also known as the Magna Carta for Public School Teachers, which provides that

teachers cannot be reassigned to another station without their consent.41 The limitations posed by the Magna

41Attempts to amend the Magna Carta have generally focused on expanding benefits to teachers such as scholarship grants for their

dependents and free medical treatment, rather than on issues in teacher redeployment. Although the Magna Carta prohibits the

reassignment of teachers without their consent, there are few special conditions that do not require teachers’ consent to be

reassigned. Such cases include transferring teachers out of schools where PTRs are below 35:1 in the elementary level, STRs are

below 27:1 in the secondary level, or enrollment has decreased considerably due to emergencies such as armed conflict and natural

disasters. Details are outlined in DepEd Order No. 22, s. 2013, entitled “Revised Guidelines on the Transfer of Teachers from One

Station to Another”.

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00

CAR

II

VIII

I

VI

IV-B

V

IX

CARAGA

VII

III

XII

X

XI

ARMM

IV-A

NCR

Elementary

2011-2012 PCR 2016-2017 PCR

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00

II

CAR

I

XII

CARAGA

VI

IV-B

X

VIII

V

IX

III

VII

XI

ARMM

IV-A

NCR

JHS

2011-2012 SCR 2016-2017 SCR

32

0% 10% 20% 30% 40% 50% 60% 70%

ARMM

XI

XII

IX

X

IV-B

IV-A

V

NCR

VI

CARAGA

VII

III

VIII

CAR

I

II

Elementary JHS SHS

Carta on teacher redeployment has long been recognized by studies as early as 199942 and appear to remain

a challenge, as indicated by regional inequalities in teacher ratios and teacher qualifications.

Figure 38: Proportion of Teachers with Teacher III and Master Teacher Positions,

by Region, SY 2017-2018


School quality show correlation with geography and poverty. Regions with higher poverty incidences

tend to have poorer teacher quality, while highly urbanized regions such as NCR, Region IV-A, and Region

III have worse teacher and classroom ratios. Teacher quality, teacher ratio, and classroom ratio affect the

attainment of learning outcomes, discussed below.

Equity in Learning Achievement

While NAT scores have improved across all regions at elementary level and most at secondary level

from 2002 to 2008, it was not the case from 2009 to 2015. From 2009 to 201543, both elementary and

secondary NAT mean percentage scores (MPS) decreased for Regions IV-A and VIII. NCR saw a decline

in the elementary level performance, while NAT scores in Region I decreased at the secondary level.

For some regions, NAT MPS climbed up competency bands as set by DepEd from SY 2008-2009 to

SY 2014-2015. At the elementary level, Regions IV-B and XII moved from the level of upper average,

corresponding to an MPS of 51 to 75 percent, to the level of superior, equivalent to an MPS of 76 to 100

percent. In 2009, ARMM had an MPS of 48.2 percent, corresponding to the lower average band; in 2015,

42ADB & World Bank, 1999, as cited in Maligalig et al., 2010. 43NAT data for SY 2014-2015 was used as the latest comparator for regional NAT performances over time due to

several changes that happened in the succeeding years, as noted in Chapter 1.

33

0% 20% 40% 60% 80% 100%

IV-A

NCR

ARMM

V

CAR

I

VII

X

II

III

XI

VI

IX

IV-B

XII

VIII

CARAGA

Grade 6

2008-2009 NAT MPS 2014-2015 NAT MPS

0% 20% 40% 60% 80% 100%

ARMM

I

IV-A

V

III

NCR

II

CAR

X

XI

IV-B

XII

VII

VI

VIII

IX

CARAGA

Grade 10

2008-2009 NAT MPS 2014-2015 NAT MPS

the region moved up to the upper average level, with a NAT MPS of 59.6 percent. At the secondary level,

many regions that were previously at the lower average level in 2009 moved up to the upper average band

in 2015. Most notably, NAT scores in Regions IX and XII increased by about 8.5 percentage points, putting

their regional MPS within the upper average competency band.

Figure 39: NAT Mean Percentage Scores by Region, SY 2008-2009 and SY 2014-2015

Source: DepEd-Bureau of Education Assessment.

Regions with poorer NAT performances at the elementary level, such as Regions IV-A, NCR, and

ARMM, also have higher pupil-classroom ratios. In the secondary level, regions with lower NAT scores

have higher student-classroom and student-teacher ratios, with the exception of Region I, which has

relatively lower ratios but scored poorly on the NAT. The pattern between NAT scores and school inputs

reinforces the notion that highly congested schools which are usually in urban areas are less conducive to

learning, an observation noted in previous studies. Maligalig et al. (2010), for instance, found that PTR was

a significant determinant of NAT scores at the elementary level. The authors observed that for every unit

increase in PTR, there is a corresponding 1.18 score decrease in NAT. For regions that are at a disadvantage

in terms of school quality, the challenge of increasing learning achievement will be compounded. Both the

national as well as regional performances in the NAT have remained low over time and improving learning

outcomes may require a menu of strategies adapted to learner characteristics (Box 9).

34

Conclusion

Although much improvement has been made in enrollment and completion at the national level,

access and completion persistently lag among males and children from the poorest households, and

regional disparities remain substantial. For these groups, poverty and the high opportunity cost of

schooling remain major constraints to enrollment and completion. Both DepEd EBEIS and household

survey data reinforce previous findings of differing opportunity costs of schooling between boys and girls,

between older and younger children, as well as between rural and urban areas.44 The 4Ps/CCT program

have helped children from the poorest background to attend schools, and the financial assistance program

for private education such as Education Service Contracting for JHS and the SHS Voucher Program have

helped to widen choices for schools among the poor; however, more targeted provisions that take into

account the differing opportunity costs among various disadvantaged groups should be considered further.

Also, the overall progress in the basic education system may mask important disparities in school quality

and learning outcomes across regions and within regions. Particularly ARMM continues to show serious

deficiencies in various aspect of school quality and access, and lowest student achievement across the

country. Targeted programs to improve conditions are expected for ARMM and other areas exhibiting

persistent challenges.

44e.g., David & Albert, 2015; Albert & Raymundo, 2016.

Box 9: Three Strategies to Improve Learning Outcomes

Recognizing that “schooling is not the same as learning” (p. 3), the World Development Report 2018 discusses

three complementary strategies countries can implement to go beyond providing access to education to achieving

learning. First, it is imperative to assess learning through well-designed assessments, and to apply the results

appropriately. Measures of learning should not only track students’ progress, but must also monitor whether

programs, policies, and critical factors like teacher quality and school management are supporting learning.

Second, countries must act on the abundance of evidence on learning. Interventions that have been found to

make a difference in learning include (a) addressing learner preparation through early childhood programs,

demand-side programs to increase access and capacity to learn, and remediation programs; (b) increasing teacher

effectiveness by providing teachers with follow-up coaching, targeting teaching to the student’s level, and using

incentives to improve teachers’ motivation; and (c) improving school management by providing school inputs

that support rather than substitute teachers, ensuring technology can be feasibly implemented in schools, and

focusing on improving teacher-learner interactions.

Lastly, greater alignment is needed within the education system and among all education stakeholders to better

support learning. In doing so, countries must address political and technical constraints to more strongly align

all actors toward learning.

Source: World Bank, World Development Report 2018: Learning to Realize Education’s Promise (2018).

35

Chapter 3 – Recent Trends in Public and Private Spending on Basic Education

This chapter reviews government spending on basic education, and government budget allocation and

utilization of basic education funds from 2009 to 2017. In this chapter, we further explore the impacts of

recent policy and reform measures on public and private spending on basic education, and the efficiency of

public expenditure on basic education.

Overall Trends in Government Spending

Government education spending has steadily increased from 2008 to 2017. Education spending has

shown recovery from the 2002 to 2008 period, when public expenditure on education decreased from 3.4

to 2.6 percent of GDP. Since then, apart from a slight decline in 2014, government spending on education

has steadily increased to 4.4 percent of GDP in 2017 (Figure 40). Basic education spending, which has

consistently comprised at least 85 percent of total education spending, generally follows the same pattern.

Figure 40: Government Expenditure on Education as % of GDP, 2009-2017

Note: Figures for national government (NG) include DepEd (current and continuing, regular and automatic) and

DPWH Basic Education Facilities Fund (BEFF) obligations data. Data for certain years are not available (i.e., SUC

and CHED data for 2009 to 2010; TESDA data for 2009).

Sources: DepEd SAAODBs; obligations data for various agencies from DBM Budget and Management Bureaus;

DOF-BLGF LGU Fiscal Statement of Receipts and Expenditures.

Government spending on education in the Philippines as share of GDP came close to the average for

upper middle-income countries and to the richer countries in the region (Figure 41).45 Data as far back

as 1998 show that the Philippines has persistently lagged behind neighboring countries such as Malaysia,

Vietnam, and Thailand, in terms of public expenditure on education. Since 2009, however, the Philippines

has moved closer to the average for countries within the region. The distance between the Philippines and

other countries has partly closed due to the decrease in education spending as percent of GDP within the

region, while the same increased for the Philippines over this period. Table 2 shows how total public

spending on basic education (i.e., national and local government spending) has increased between 2009 and

2017 at an average annual rate of 13.1 percent in real terms.46 In 2017, total real government spending was

45As international spending data on basic education are not available, figures represent government expenditure on total education,

including tertiary level. 46National government spending includes obligations data from DepEd Office of the Secretary and data from the Basic Education

Facilities Fund (BEFF), a significant portion of which has been managed and implemented directly by DPWH beginning in 2013.

127,187

327,200

2.4 2.32.7 2.7 3.0 2.8

3.3 3.6

4.4

2.4 2.3 2.4 2.4 2.7 2.42.9 3.1

3.8

13.413.9 14.2

13.2

14.2

13.3

14.214.7

15.6

0

2

4

6

8

10

12

14

16

-

50,000

100,000

150,000

200,000

250,000

300,000

350,000

2009 2010 2011 2012 2013 2014 2015 2016 2017

Per

cen

tage

PH

P m

illio

n, i

n 2

00

0 p

rice

s

LGU Spending

NG Spending (DepEd+ DPWH BEFF)

Total EducationSpending as % ofGDP

Basic EducationSpending (NG +LGU)as % of GDP

NG + LGU Spendingas % of Total GovtSpending

36

PhP 327.2 billion, 1.6 times higher than 2009. As noted earlier, trends in spending have coincided with

major reforms in the basic education sector.

Real per pupil spending more than doubled between 2009 and 2017. Although there was a 6 percent

decline in 2014, real per pupil spending recovered by over 28 percent the following year and has continued

to rise since (Table 3). This upward trend in per pupil spending has been accompanied by greater enrollment

in kindergarten, rising NERs, particularly at the secondary level, as well as increasing cohort survival and

completion rates at both elementary and secondary levels.

Figure 41: Government Expenditure on Education as % of GDP in Selected Countries, 2017

Note: Data for comparator countries are for 2017, or latest available: (i) 2013, (ii) 2014, (iii) 2015, and (iv) 2016.

Sources: DepEd SAAODB, UNESCO Institute for Statistics in World Bank-EdStats (March 2018).

Table 2: Total Government Spending on Basic Education, 2009 to 2017

2009 2010 2011 2012 2013 2014 2015 2016 2017

In current prices (in million PhP)

National Government 178,847 191,118 218,817 240,238 291,030 284,606 365,202 430,048 577,924

Local Government 13,867 13,526 14,435 16,232 16,654 15,976 15,984 16,468 18,889

Total Government 192,714 204,644 233,252 256,470 307,684 300,582 381,186 446,516 596,813

In 2000 prices (in million PhP)

National Government 118,035 121,030 133,214 143,426 170,273 161,414 208,342 241,248 316,844

Local Government 9,152 8,566 8,788 9,691 9,744 9,061 9,119 9,238 10,356

Total Government 127,187 129,595 142,002 153,116 180,016 170,475 217,460 250,486 327,200

Note: National government includes DepEd (current and continuing, regular and automatic) and DPWH Basic

Education Facilities Fund (BEFF) obligations data.


DOF-BLGF LGU Fiscal Statement of Receipts and Expenditures

1.92.2

2.9

3.6

4.1 4.1 4.3 4.3 4.3 4.54.8

5.35.7

0

1

2

3

4

5

6

Cambodia(ii)

Myanmar Lao PDR Indonesia(iii)

Mongolia Thailand (i) Philippines Uppermiddleincome

countries(iii)

Lowermiddleincome

countries(ii)

Middleincome

countries(ii)

Malaysia(iv)

Highincome

countries(iii)

Vietnam (i)

Per

cen

tage

37

Table 3: Government Spending Per Pupil on Basic Education, 2009 to 2017

2009 2010 2011 2012 2013 2014 2015 2016 2017

In current prices (PhP)

National Government 9,289.0 9,667.5 10,687.4 11,619.8 13,935.4 13,525.5 17,467.6 20,097.5 26,154.2

Local Government 720.2 684.2 705.0 785.1 797.5 759.2 764.5 769.6 854.9

Total Government 10,009.2 10,351.7 11,392.5 12,404.9 14,732.8 14,284.7 18,232.1 20,867.1 27,009.0

In 2000 prices (PhP)

National Government 6,130.5 6,122.2 6,506.4 6,937.2 8,153.2 7,671.0 9,965.0 11,274.3 14,338.9

Local Government 475.3 433.3 429.2 468.7 466.6 430.6 436.2 431.7 468.7

Total Government 6,605.9 6,555.4 6,935.6 7,405.9 8,619.7 8,101.6 10,401.1 11,706.0 14,807.6

Note: National government includes DepEd (current and continuing, regular and automatic) and DPWH Basic

Education Facilities Fund (BEFF) obligations data.


DOF-BLGF LGU Fiscal Data Statement of Receipts and Expenditures.

Distribution of Government Spending by Level of Education

The share of government expenditure allocated to elementary education is the highest among all

levels of education. Although government expenditure by level of education is not available from local

government data, which constituted 3.2 percent of total government expenditure on education in 2017,

DepEd SAAODBs include obligations data on operations of schools that distinguish among the

kindergarten, elementary, and secondary levels (Figure 42). While the bulk of spending goes to the

elementary level, its share has declined continuously over the 2009 to 2017 period. In parallel, spending on

kindergarten and secondary levels have increased, reflecting the rising expenditures associated with the

additional years brought about by the K to 12 implementations in 2012.

Figure 42: Distribution of DepEd Spending by Level of Education, SY 2009-2010 to SY 2017-2018

Note: Figures represent obligations data on operations of schools as indicated in DepEd SAAODBs.

Source: DepEd SAAODBs for various years.

Actual government spending has risen substantially at both the elementary and secondary levels. As

reflected by obligations data on operations of schools, government spending at the elementary level

increased by 72.8 percent in real terms between 2009 and 2017. Per pupil real spending at the elementary

level grew by 80.1 percent over the same period, amounting to PhP 8,481 on 2000 prices in 2017. At the

secondary level, government spending in 2017 amounted to PhP 58 billion in real terms on 2000 prices,

about 133.2 percent higher than in 2009. Per pupil real spending at the secondary level also increased from

2009 by 61.9 percent to PhP 7,466 in 2017. The increasing share of secondary education expenditure by

DepEd coincides with not only growing total enrollment (also due to the introduction of SHS), but also

28.3% 30.2% 30.0% 30.2% 30.7% 29.4% 32.5% 34.2% 35.5%

68.2% 69.7% 69.9% 69.7% 69.1% 69.9% 66.1% 64.5% 63.3%

3.5% 0.7% 1.4% 1.3% 1.2%

0%

20%

40%

60%

80%

100%

2009 2010 2011 2012 2013 2014 2015 2016 2017

Secondary Elementary Kindergarten

38

0

20

40

60

80

100

5,000 6,000 7,000 8,000 9,000 10,000 11,000

Per

cen

tage

Real Per Pupil Spending by Region, in 2000 prices

Elementary

NER Completion Rate Cohort Survival Rate PTR

r = -0.22*

r = -0.95*

r = -0.12

r = -0.22

0

20

40

60

80

100

5,000 6,000 7,000 8,000 9,000 10,000 11,000

Per

cen

tage

Real Per Student Spending by Region, in 2000 prices

Secondary

NER Completion Rate Cohort Survival Rate STR

r = 0.47*

r = 0.21*

r = 0.19*

declining student-teacher and student-classroom ratios at this level. Pupil-teacher ratios at the elementary

level have also continued to show improvement, though pupil-classroom ratios have not changed much.

Government spending is strongly correlated at the regional level to the number of teachers.

Correlation analysis at the regional level shows that per pupil government spending, which includes both

national and local government spending, is significantly correlated with lower teacher ratios at the

elementary and secondary levels (Figure 43). Per pupil spending is only weakly associated with other

education indicators such as completion rates and CSRs for both elementary and secondary levels but has

a moderate positive correlation with secondary level NERs.

Figure 43: Real Per Pupil Government Spending on Education and

Various Education Indicators, by Region, 2017

Notes: * - correlation is significant at the 0.05 level. No available spending data for ARMM.

Sources: DepEd SAAODBs by region; DepEd EBEIS.

Factors in Government Spending Trends

The steady increase in public spending on basic education reflects the government’s commitment to

implementing the K to 12 program, DepEd’s largest education reform. The full commitment to K to

12 has been identified as a priority under the current DepEd administration’s 10-point agenda, as well as

the Philippine Development Plan (PDP) 2017-2022. The strengthened fiscal position of the country has led

to an increased public budget, resulting in education spending growth. However, a closer look at the sectoral

distribution of the national government (NG) expenditures reveals that while the absolute level of the budget

remains highest for basic education as a sector, this has not necessarily translated into an increased share

for the sector. Moreover, while DepEd’s budget has continued to increase, its budget execution rate declined

over majority of the period 2009 to 2017.

Although improved education has consistently been cited as a key agenda point in both PDP 2011-

2016 and PDP 2017-2022, the share of basic education in NG spending has actually declined (Table

4). The average annual share of basic education in total government expenditure between 2002 to 2008 was

17.1 percent; it decreased to 15.8 percent between 2009 to 2017. Moreover, the share of basic education in

total spending declined beginning 2013, just after the initial K to 12 implementation. During this period,

the government’s focus shifted towards infrastructure development, as the share of communications, roads,

and other transportation increased from an annual average of 12.2 percent between 2009 to 2012 to an

average of 16.1 percent from 2013 to 2017.

r = -0.71*

39

Table 4: Sectoral Distribution of National Government Spending, as %,

Net of Net Lending and Interest Payments, 2009-2019

2009 2010 2011 2012 2013 2014 2015 2016 2017

ECONOMIC SERVICES 35.0 32.6 28.5 32.9 31.2 29.2 33.8 34.7 35.9

Agriculture, Agrarian Reform, and Natural Resources 8.3 8.6 5.5 7.1 7.2 6.4 5.9 5.3 4.8

Trade and Industry 0.5 0.5 0.4 0.4 0.4 0.3 0.4 0.5 0.4

Tourism 0.2 0.1 0.2 0.3 0.3 0.2 0.3 0.3 0.2

Power and Energy 1.1 0.2 1.4 5.4 1.8 1.1 0.6 0.5 0.3

Water Resource Development and Flood Control 2.0 1.6 1.2 1.5 1.6 1.5 2.2 2.4 2.8

Communications, Roads, and Other Transportation 14.5 12.5 10.9 10.7 12.5 12.0 17.0 18.5 20.6

Other Economic Services 0.7 1.1 1.1 1.1 0.9 0.6 0.8 0.9 1.3

Subsidy to Local Government Units 7.6 8.0 7.8 6.4 6.4 7.1 6.5 6.4 5.7

SOCIAL SERVICES 35.8 35.6 42.5 39.8 42.9 45.4 42.3 41.2 40.3

Education, Culture, and Manpower Development 18.2 21.8 19.8 18.8 19.7 19.3 17.9 18.8 18.6

Basic Education 14.9 16.3 17.0 16.0 16.7 16.1 14.7 15.6 15.1

Health 2.0 2.7 3.2 3.5 3.4 5.1 5.0 5.3 5.3

Social Security, Welfare and Employment 6.6 4.2 9.0 9.8 10.7 11.8 11.0 9.4 9.0

Land Distribution (CARP) 0.1 0.3 0.3 0.0 0.3 - - - -

Housing and Community Development 0.7 0.6 1.7 0.8 1.9 1.6 1.4 0.9 1.3

Other Social Services 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1


DEFENSE 5.5 7.8 5.5 5.0 5.3 5.2 4.6 4.8 5.2

Domestic Security 5.5 7.8 5.5 5.0 5.3 5.2 4.6 4.8 5.2

GENERAL PUBLIC SERVICES 23.7 24.0 23.5 22.3 20.6 20.2 19.3 19.3 18.6

General Administration 8.4 7.6 7.7 8.6 8.0 7.1 7.0 6.4 5.8

Public Order and Safety 8.1 9.2 8.0 7.7 6.9 7.2 6.8 6.9 6.6

Other General Public Services 1.2 0.9 0.2 0.9 0.6 0.2 0.3 0.9 1.7


Note: Figures for basic education are shares in total national government spending.

Source: DBM Budget of Expenditures and Sources of Financing.

Budget Execution by DepEd

DepEd’s budget utilization rate47 has increased since 2015. (Figure 44) Except for a slight growth in

2013, DepEd’s budget execution displayed a downward trend from 2009 to 2015, reaching a low 87.7

percent in 2015. Large gaps between DepEd’s total allotments and obligations reflect its inability to fully

execute its budget. This has particularly been the case in the early years of preparation for a critical new

education program, senior higher school education (see Box 10 for findings on case studies of five DepEd

program/project budget execution). Since 2015, DepEd’s budget utilization has improved, reaching 97

percent in 2017, a result of financial reforms implemented by DepEd in preparation for the possible shift to

the Annual Cash-Based Appropriations System in FY 2019.48

47Computed as obligations over allotments. 48Government agencies are typically allowed to spend appropriations over two succeeding fiscal years. Under the Annual Cash-

Based Budgeting Appropriations System, agencies are limited to complete contractual obligations within the fiscal year. As of

writing, the shift to this new system has not been officially written into law. However, in preparation for the possible transition to

the cash-based system, DepEd has implemented financial reforms, including the performance of pre-procurement activities, early

downloading of funds to implementing units, and the application of multi-year implementing guidelines for big-ticket items.

40

80.2% 80.4% 79.6% 77.1% 76.8%71.1%

67.7%63.5% 62.1%

14.3% 13.4% 12.7%13.1% 12.6%

11.6%12.2%

13.7% 14.0%

5.6% 6.2% 7.7% 9.8% 10.6%

17.3%20.1%

22.8% 23.9%

2009 2010 2011 2012 2013 2014 2015 2016 2017

Appropriations

Personnel Services MOOE Capital Outlay

81.4%

88.3%85.3% 84.6% 82.1%

89.0%86.0%

79.6%

71.6%

13.4%

9.5%9.8% 9.7%

9.7%

9.5%10.3%

13.3%

20.1%

5.3%2.2%

4.8% 5.7% 8.2%

1.5% 3.7%7.1% 8.2%

2009 2010 2011 2012 2013 2014 2015 2016 2017

Obligations

Personnel Services MOOE Capital Outlay

96.4% 94.3% 92.9% 91.8% 94.0%89.6% 87.7% 89.6%

97.1%

0%

20%

40%

60%

80%

100%

-

100,000

200,000

300,000

400,000

500,000

600,000

2009 2010 2011 2012 2013 2014 2015 2016 2017

Appropriations

Allotments

Obligations

Utilization Rate

Figure 44: DepEd Real Spending and Budget Utilization Rate, 2009-2017

Note: In 2000 prices, in million PhP. Data include current and continuing (regular and automatic) appropriations.


Figure 45: Shares of Expense Classes in DepEd Appropriations and Obligations, 2009-2017

Note: Includes current and continuing (regular and automatic) appropriations and obligations. Financial expenses are

not represented in the figures as they constitute less than 1 percent of DepEd’s appropriations and obligations.


With the introduction of K to 12 in 2013, the patterns of spending across expense classes have shifted.

The share of personnel services, which covers spending on salaries and wages, have reduced from its

average of 85 percent prior to 2013 to 71.6 percent in 2017. Maintenance and other operating expenses

(MOOE), which are funds allocated for schools to spend on activities and necessities, constitute one-fifth

of DepEd’s expenditure, its highest share in the period 2002 to 2017. Capital outlay pertain to funds

allocated for the repair and rehabilitation of school buildings, the purchase of school furniture, and the

electrification of schools. The share of capital outlay in total DepEd expenditure declined in 2014 but

increased in 2016 and 2017 with the introduction of senior high school.

41

Box 10: Case Studies of DepEd Program/Project Budget Execution

To better understand constraints in the budget execution process, case studies were developed to examine five DepEd

programs and projects, namely, the (a) School-Based Feeding Program, (b) School Building Program, (c) School

Furniture Program, (d) Procurement of Textbooks and Other Instructional Materials, and (e) New Teacher Deployment.

In developing the case studies, data from DepEd’s SAOODBs, as well as existing reports and studies conducted on these

programs, were analyzed. To obtain a clearer understanding of the bottlenecks in program and budget execution,

interviews were conducted with key DepEd central office personnel.

The main findings and recommendations of the case studies were as follows:

• School-Based Feeding Program (SBFP): In terms of attaining the objective of improving beneficiaries’

nutritional status, the case study recommends that the SBFP give importance to other health-related activities, such

as those focusing on good hygiene and sanitation practices, to complement the feeding program. To improve the

accuracy of targeting beneficiaries, uniform and standard measurement equipment, as well as regular reorientations

on the conduct of baseline and end line nutritional status assessment, are needed. Although the SBFP has reached its

objective of rehabilitating at least 70 percent of severely wasted beneficiaries to normal nutritional status at the end

of the 100 to 120 feeding days, the case study noted that its budget execution has been inconsistent, as reflected by

the presence of unutilized funds over the years.

• School Building Program (SBP) and School Furniture Program (SFP): The SBP, under the Basic Education

Facilities Fund, covers the improvement and maintenance of school facilities. The SBP is jointly managed and

implemented by DepEd and DPWH. The SFP, which is managed by DepEd, prioritizes newly constructed schools

through the SBP. Delays in the completion of school building construction and provision of school furniture, as well

as underutilization of their respective budgets, may be attributed to issues in coordination between DPWH and

DepEd. The synchronization of timelines of the two agencies must be improved to avoid deficiencies and lapses in

the provision of these inputs. The case study further recommends that DepEd take advantage of the National

Inventory of DepEd Public School Buildings and hire more engineers to effectively monitor its infrastructure

projects.

• Procurement of Textbooks and Other Instructional Materials: Delays in procurement resulted in budget

underutilization and failure to meet program targets. Despite the introduction of procurement reforms, issues such

as failure of bidding, supply limitations to meet DepEd’s demands, and late downloading of funds contributed to

persistent delays in the delivery of textbooks and other instructional materials. As the procurement process is

complex and involves multiple stages, the case study recommends that DepEd identify key time-consuming activities

that should be included in specific budgeting periods to avoid non-utilization and lapsing of funds. Furthermore,

proper inspection, monitoring, and accounting of textbooks and other instructional materials, as well as the

warehouses in which they are stored, must be ensured to avoid wastage of these learning materials.

• New Teacher Deployment: Due to the complexity of the hiring and deployment processes, setbacks

can trickle down from various stages, causing a domino effect of delays. The late submission of

prerequisite deployment reports by DepEd regional offices, for instance, results in the delayed release of the Notice

of Organization, Staffing, and Compensation Action by DBM regional offices; this delay, in turn, pushes back the

filling up of new teacher items. As such, improving the coordination between the calendars of activities of both

DepEd and DBM is needed to address this trickle-down effect in delays. Furthermore, the case

study recommends the inclusion of locally-funded teachers and the exclusion of mobile teachers and teachers on

leave in DepEd’s computations for pupil-teacher ratios to more accurately identify areas with teacher shortages and

surpluses.

42

Local Government Spending on Basic Education

Local government units’ (LGU) expenditure comprise a small and decreasing share of total basic

education spending. LGU spending has fluctuated over the last nine years but has generally risen and

fallen in the same pattern as NG spending (Figure 46). The LGU share of total basic education spending

decreased from an average of 9.1 percent between 2002 to 2008 to an average of 5.3 percent between 2009

to 2017. As NG spending increased over the period 2009 to 2017, the share of LGU spending in total public

basic education funding declined from 7.2 percent in 2009 to 3.2 percent in 2017.

Figure 46: Nominal and Real Total Government Spending on Basic Education, 2009-2017

Note: Real spending in 2000 prices, in million PhP. National government spending reflects obligations data (current

and continuing) from DepEd Office of the Secretary and DPWH BEFF from 2013 to 2017.

Sources: DepEd SAAODBs; DPWH data from DBM Budget and Management Bureau – A; DOF-BLGF LGU Fiscal

Data Statement of Receipts and Expenditures.

Per pupil real LGU spending has remained stagnant even as per pupil real NG spending rose steadily

and substantially in the period 2009 to 2017. By 2017, per pupil NG spending had reached about 126

percent higher than in 2009. In contrast, real per pupil LGU spending was stagnant over the same period.

In 2017, real per pupil LGU spending was about 1.4 percent lower than in 2009 (Figure 47).

Figure 47: Nominal and Real Per Pupil Government Spending on Basic Education, 2009-2017

Note: Real spending in 2000 prices. National government spending reflects obligations data (current and continuing)

from DepEd Office of the Secretary and DPWH Basic Education Facilities Fund from 2013 to 2017.



178,847

577,924

118,035

316,844

13,867 18,889 9,152 10,356 -

100,000

200,000

300,000

400,000

500,000

600,000

2009 2010 2011 2012 2013 2014 2015 2016 2017

NG Nominal

NG Real

LGU Nominal

LGU Real

9,288.97

26,154.19

6,361.48

14,375.13

720.24 854.82 475.34 468.65 -

5,000.00

10,000.00

15,000.00

20,000.00

25,000.00

30,000.00

2009 2010 2011 2012 2013 2014 2015 2016 2017

NG Nominal

NG Real

LGU Nominal

LGU Real

43

Regional disparities exist in LGU spending, mainly due to differences in the Special Education Fund

(SEF). The SEF, which makes up about 75 percent of LGU education spending, is accrued through an

additional 1 percent tax on real property. As such, larger and wealthier regions such as NCR and Region

IV-A have considerably higher LGU funding than other regions. In 2017, for instance, NCR accounted for

44 percent of the total LGU education spending, despite the region having less than 10 percent of total basic

education enrollment. LGU per pupil spending in NCR was thus boosted to almost eight times higher than

the average LGU per pupil spending in all other regions. Table 5 presents nominal and real per pupil NG

and LGU spending across regions.

Reported LGU spending does not necessarily translate to LGU direct school funding. The PETS-

QSDS (2016) found that fewer than 50 percent of schools receive any kind of LGU funding, which suggests

that funds are not completely being utilized on activities that directly benefit schools. There has been a

sharp decline in the absolute numbers and relative ratios of locally-funded and nationally-funded teachers.

In 2009, there were more than 25,000 locally funded elementary teachers (7 percent of all teachers). This

number had declined to less than 9,000 in 2017 (less than 2 percent of all teachers). Similarly, there were

more than 17,000 junior high locally funded teachers in 2009 (12 percent of all teachers), which had

declined to a little over 5,000 teachers in 2017 (2 percent of all teachers). Inconsistencies between LGU

direct school funding and LGU spending reported at the national level make it difficult to examine where

remaining funds have been spent or how they have affected education outcomes and quality.49

Table 5: Nominal and Real Per Pupil Government Spending on Basic Education, by Region, 2017

Regions In current prices In constant 2000 prices

LGU NG Total LGU NG Total

Region 1 - Ilocos Region 805.9 21,313.2 22,119.1 441.9 11,684.9 12,126.7

Region 2 - Cagayan Valley 303.6 22,055.0 22,358.6 166.5 12,091.6 12,258.0

Region 3 - Central Luzon 631.7 17,001.3 17,633.1 346.3 9,320.9 9,667.2

Region 4A - CALABARZON 787.9 14,997.5 15,785.4 432.0 8,222.3 8,654.3

Region 4B - MIMAROPA 359.8 18,624.8 18,984.6 197.2 10,211.0 10,408.2

Region 5 - Bicol Region 287.4 17,851.3 18,138.7 157.6 9,786.9 9,944.5

Region 6 - Western Visayas 531.6 18,474.3 19,005.9 291.5 10,128.5 10,419.9

Region 7 - Central Visayas 402.5 17,695.0 18,097.4 220.7 9,701.2 9,921.8

Region 8 - Eastern Visayas 182.9 20,655.9 20,838.8 100.3 11,324.5 11,424.8

Region 9 - Zamboanga Peninsula 333.4 18,295.8 18,629.1 182.8 10,030.6 10,213.3

Region 10 - Northern Mindanao 381.3 17,329.0 17,710.2 209.0 9,500.5 9,709.6

Region 11 - Davao Region 1,403.0 15,785.7 17,188.7 769.2 8,654.4 9,423.6

Region 12 - Central Mindanao 293.6 17,203.4 17,497.0 161.0 9,431.7 9,592.7

CARAGA 309.3 20,209.3 20,518.6 169.6 11,079.7 11,249.2

Cordillera Administrative Region 339.6 26,276.0 26,615.7 186.2 14,405.7 14,591.9

National Capital Region 4,092.1 15,115.6 19,207.7 2,243.5 8,287.1 10,530.5

ARMM 252.5 - 252.5 138.4 - 138.4

Total 854.8 17,135.7 17,990.5 468.7 9,394.6 9,863.2

Note: Real spending in 2000 prices. National government spending reflects obligations data (current and continuing)

from DepEd Office of the Secretary and DPWH Basic Education Facilities Fund from 2013 to 2017. NG spending

data is not available for ARMM.



49The PETS-QSDS also noted weaknesses in the system that managed and allocated local level funds. Local School Boards (LSBs)

who have the mandate to make decisions and approve the budget met much less frequently than required by the local government

board. Many heads of schools were not aware of the meetings taking place or their outcomes. Schools also did not seem to have

opportunities to provide their response or feedback to the LSBs on decisions made on their behalf.

44

Private Spending on Basic Education

To examine private expenditure on basic education, education spending data from households are analyzed

using the Family Income and Expenditures Survey rounds. Private corporate spending through DepEd

programs and partnerships with the private sector are also discussed.

Household Expenditure on Basic Education

Between 2012 and 2015, average household expenditure per school-going child declined in real

terms.50 Average total expenditures on education per school-age member declined significantly from 2012

to 2015 in real terms, although less drastically than the 20 percent-change observed in the first BEPER

(2012) for the period 2003 to 2006, largely driven by decline in such expenditure by the richest 40 percent

of households

Table 6: Average of Household Expenditures on Education

per School-Age Household Member (in 2006 NCR prices)

Education Expenditures and Components 2012 2015 Percent Change

Total education expenditures 3,568.7 3,213.1 -10.0% ***

Tuition fees 2,672.6 2,364.5 -11.5% ***

Education not definable by level 30.4 18.8 -38.2% ***

Allowance 509.0 483.9 -4.9% *

Other educational expenses 356.8 343.1 -3.8% ***

Number of households 12,643,804 13,664,435 8.1%

Note: *** - the difference between 2012 and 2015 estimates are significant at 0.01 (two-tailed) level of significance

** - the difference between 2012 and 2015 estimates are significant at 0.05 (two-tailed) level of significance

*- the difference between 2012 and 2015 estimates are significant at 0.1 (two-tailed) level of significance

Source: PER team’s computations using FIES 2012 and 2015.

Household expenditures declined most for the richest households. Across income groups, the decline

in average education expenditures per school-age member is only observed for the top two (i.e., richest)

quintiles, with larger reductions for the fifth/richest quintile. In contrast, average education spending per

school-age member rose for the remaining income groups; moreover, this increase in spending was

significant for the lowest two (i.e., poorest) quintiles. This pattern in household spending is unlike the period

2003 to 2006, where all income groups, except for the fourth quintile, showed significant declines in

average education spending per school-age member. Moreover, poorer quintiles showed larger decreases,

reflecting the inability to compensate for declining government spending on education in this earlier time.

The years 2012 to 2015, on the other hand, saw an overall increase in government spending on education,

albeit with a slight fluctuation in 2014. Despite higher public spending, lower-income households showed

an increase in out-of-pocket education expenses per school-age member, implying that government and

household expenditures on education are complements rather than substitutes.

Reasons for increased gap in education spending among poorer and rich households include a larger

number of children in poorer households and their greater access to education. First, this reflects the

50Data in Table 6 presents the average expenditures on education per school-age household member for 2012 and 2015. The

estimates are expressed in 2006 NCR prices to adjust for overall inflation and spatial price differences and are conditional on

households reporting education expenditures and the presence of school-age members. Household expenditure data are taken from

the Family Income and Expenditures Survey (FIES) 2012 and 2015, which include information on education expenditures such as

tuition fees, allowance, and education-related expenses like school uniforms, printing services, and computer training. It should be

noted, however, that the data from the FIES do not distinguish between public and private education. Furthermore, household

education expenditure data are not disaggregated by level of education but are lumped together. As such, the FIES include education

expenses encompassing pre-kindergarten to tertiary levels of education.

45

difference in population growth of school-age children between the top two and bottom three quintiles.

There were fewer school-age children in the top two quintiles in 2015 compared to 2012, while numbers

for the bottom three quintiles increased. This seems to be consistent with enrollment data; while enrollment

in public schools, which most children from low-income households attend, increased from 2012 to 2015,

enrollment in private schools, where most high-income children go, decreased by 6 percent over the same

period. Second, the increase in spending among poorer households may be illustrative of increased access

to education, particularly due to efforts like the expansion of the 4Ps. Between 2003 and 2015, the 4Ps had

grown from 3.8 million to 4.4 million beneficiary households; moreover, in 2014, the program coverage

expanded to cover children ages 15-18 years old, beyond the original eligibility of 0- to 14-year-old

children. As the cash transfer is conditional on attendance to school, this created more incentives for parents

from poorer households to spend on their children’s education.

Table 7: Average Number of School-Age Children per Household, by Income Quintile, 2012 and 2015

Income Quintile 2012 2015

Quintile 1 (Poorest) 2.9 2.8

Quintile 2 2.3 2.2

Quintile 3 2.0 1.9

Quintile 4 1.8 1.7

Quintile 5 (Richest) 1.6 1.5

Overall 2.2 2.1

Note: Figures only include households with school-age children (ages 5-17) and reporting education expenses.


Richer households continue to spend more on education than poorer households as a share of total

household expenditure (Figure 48). This translates to higher expenditure per school-age child for richer

households – on average, these households have one less child than poorer households. Though the

relationship is not entirely straightforward, households in urban regions also spend a higher share of their

total household expenditure on education. This could partly be due to the higher cost of living and higher

cost of education in these areas.

Figure 48: Share of Education Expenditure in Total Household Expenditure,

by Income Quintile, 2012 and 2015



Table 8: Share of Education Expenditure in Total Household Expenditure, by Region, 2015

Region Share of Education Expenditure

Cordillera Administrative Region 6.1%

Region X – Northern Mindanao 5.3%

National Capital Region 4.9%

Region IV-A - CALABARZON 4.9%

0%

2%

4%

6%

8%

Quintile 1(Poorest)

Quintile 2 Quintile 3 Quintile 4 Quintile 5(Richest)

Overall

2012 2015

46

Region XI – Davao Region 4.7%

Region VII – Central Visayas 4.6%

Region III – Central Luzon 4.6%

Region XII – Central Mindanao 4.5%

Region V – Bicol Region 4.5%

Region IV-B - MIMAROPA 4.5%

ARMM 4.4%

CARAGA 4.3%

Region VI – Western Visayas 4.0%

Region II – Cagayan Valley 4.0%

Region VIII – Eastern Visayas 4.0%

Region I – Ilocos Region 3.9%

Region IX – Zamboanga Peninsula 3.7%



Private Corporate Spending

DepEd has continued to generate increased funding from partners in the private sector through its

Adopt-a-School Program.51 In 2008, contributions amounted to about PhP 6 billion pesos; in 2017, over

PhP 10 billion pesos worth of support had been raised through the program, equivalent to about 1.7 percent

of total government spending on basic education. More than 90 percent of projects funded through the

program are focused on school facilities improvement and information technology support, while the

remainder are used on interventions targeting learners and teachers, such as school supplies, health and

nutrition projects, and teaching and learning aids. With the launch of SHS in 2016, funds from the Adopt-

a-School program have also been utilized for SHS-related efforts. In 2017, about PhP 26 million were

allotted for the SHS Work Immersion program, a key feature of the SHS curriculum.52

Partnerships with the Private Sector

Financial assistance were available to some students enrolled in private schools. The Educational

Service Contracting (ESC) Program for JHS provides financial assistance for students to enroll in private

schools. In 2017, there were about 975,010 ESC grantees, representing almost 13 percent of total junior

high school enrollment that year. Through the program, grantees receive a fixed annual tuition subsidy

throughout the four years of JHS. The value of the grant varies depending on the location of the school

attended, with NCR schools receiving the highest subsidy. A World Bank study (2011) on the Philippines’

ESC found that the annual cost per grantee was only about 58 percent of the direct per student cost of public

secondary education, thus presenting a lower-cost alternative to the direct provision of secondary schooling

by the government. Moreover, the study suggested further potential cost savings through the ESC, as a

simulation showed that the cost of accommodating excess students (i.e., “aisle students”) through the ESC

program was lower than the cost of expanding the capacity of public schools.

DepEd has begun implementing the SHS Voucher Program since the introduction of SHS in SY 2016-

2017. As with the ESC, the SHS Voucher Program is tiered depending on the income class of the locality

of the school, with NCR schools receiving the highest voucher value. In the Philippines, all Grade 10

51Under Republic Act No. 8528, also known as the “Adopt-a-School Act of 1998”, the Adopt-a-School Program allows private

entities to assist a public school, whether elementary, secondary, or tertiary, by providing support to school infrastructure, facilities,

health and nutrition, reading programs, training and development, and technology support, among others. 52Under the Senior High School curriculum, students are required to undergo at least 80 hours of work immersion in an industry

related to the learners’ post-secondary goals. The work immersion course aims to provide students opportunities to become familiar

with and apply skills learned in school to actual work environments. Work immersion options are provided by SHS partner

institutions.

47

students from public junior high schools are automatically eligible to receive the full amount of the voucher,

while students from private schools who are JHS ESC grantees are eligible to receive 80 percent of the

voucher value. The program does not prioritize children for support on the basis of household income. As

the opportunity cost for older poorer children is higher, the richer households may be receiving more

benefits from the program, making it regressive. In comparison, other countries implement targeted voucher

systems to reduce constraints to access across population groups (Box 11).

Public Expenditure Efficiency

Government spending affects the quantity and quality of school and teacher characteristics that make up

the learning environment, which in turn impacts learning outcomes. The efficiency of public expenditure

can be directly measured by doing a cost-benefit or a cost-effective analysis if the required amount and

level of information are available. It, however, has been hard to find a direct relationship between spending

and learning outcomes in the case of the Philippines – these relationships appear to be flat – possibly due

to the complexity of the education production function, and the lack of availability of appropriately

disaggregated cost data. Increased public expenditure in the basic education sector in the last eight years

has been used for a larger number of schools and teachers. For government schools, we correlate school-

and teacher-related factors that contribute to learning outcomes to identify those that are constrained.

Determinants of Learning Outcomes

The learning environment – the availability of teachers, classrooms, teaching time, and school

resources, among other factors – has a bearing on learning outcomes. To estimate the effects of school

and teacher characteristics on learning outcomes, a cross-section regression analysis was done using school-

level Grade 6 NAT mean percentage scores in SY 2014-2015 as the dependent variable. The 2015 NAT

data was chosen for this analysis as more recent versions of the assessment underwent many changes that

have rendered them non-comparable. Six models were used to examine the determinants of learning

achievement scores among schools (see Annex 1 for details). Region and division dummies were included,

Box 11: Targeted Voucher Programs and Education Outcomes

While universal voucher systems increase access and school choice, targeted voucher systems help to reduce

inequity frequently experienced by girls, children from far-flung areas, children in poverty, and minorities. The

targeted system implemented by Bangladesh, for instance, provided stipends to girls who had high attendance

rates, high test scores, and remained unmarried until they turned 18 years old. This program resulted in significant

increases in enrollment among girls. In Pakistan, a voucher system focused on poor areas in Punjab demonstrated

increased enrollment among children from low-income families. In addition to increasing enrollment, the voucher

system also aimed to improve school quality through accountability measures such as a cut-off in test scores for

eligibility to receive the voucher, and performance-related incentives for schools and teachers.

Aside from influencing enrollment rates, there is also evidence that suggests the impact of voucher programs on

other education indicators. A targeted voucher system focused on economic characteristics was implemented in

Colombia, where vouchers were eligible to the poorest third of the population. Because demand exceeded supply,

a lottery was used to determine eligibility, providing a natural experiment to examine the program’s impact on

education outcomes. Three years after the lottery, voucher recipients were about 6 percentage points less likely

to repeat a grade, were about 10 percentage points more likely to have finished Grade 8, and had scored 0.2

standard deviations higher on achievement tests compared to their non-voucher counterparts.

Sources: Patrinos, Barrero-Osorio, & Guaqueta, The Role and Impact of Public-Private Partnerships in Education

(2009); Angrist, Bettinger, Bloom, King, & Kremer, Vouchers for Private Schooling in Colombia: Evidence from

a Randomized Natural Experiment (2002).

48

as well as interactions between urban-rural classification and other school characteristics. Box 12 presents

the results of the regression analysis.

The analysis found that school characteristics such as better student-teacher ratios, smaller school

sizes, and better-qualified teachers had a positive impact on learning outcomes, while operating on

multiple shifts had a negative effect on test scores. Pupil-teacher ratio and pupil-classroom ratio continue

to have small positive effects on test scores, but they are lower than those found in the public expenditure

analysis done in 2012. The negative effects of lower teacher quality and the shift system on test scores are

quite large. Schools have higher test scores when they have a higher proportion of Master Teachers, who

are more experienced and more highly skilled, and a lower proportion of non-DepEd teachers, whose

qualifications and compensation differ from nationally-funded teachers.

The above cross-section regression analysis, though limited in scope, indicates the following: (a) greater

public spending on classrooms and teachers in elementary education has been successful in increasing test

scores, though there is scope for further improvement, (b) larger school sizes in the case of the Philippines

are indicative of school level congestion and not necessarily economies of scale, and (c) it is not only teacher

quantity, which has been increased in the last decade, but also teacher quality that matters.

Box 12: Determinants of Learning Outcomes

School Congestion

Schools with multiple shifts and urban schools with large enrollment sizes (of 440 or more students in the data

used), have lower NAT scores. For the analysis, schools were grouped into quartiles according to size. School

size is significant and positive in all six models, including the full model which controls for divisions and urban

location. The MPS rises with school size until the third quartile and then declines but remains positive for all

school sizes. While larger school sizes especially in urban areas is associated with congestion (as will be seen

below), the positive association between test scores and school size, after controlling for shift status as well as

urban location, indicates that there are returns to scale in school education. Larger schools may be better equipped

with facilities and ancillary resources that are beneficial for students either directly or in improving the learning

environment. Such facilities may be costlier for the government, national or local, to provide for smaller schools.

About 1,159 of the 33,566 schools in the analysis reported using multiple shifts. Of these schools, about 93 percent

were operating double shifts, while the remainder used triple or quadruple shifts. Analysis shows that the shift

system has a large negative effect on test scores, by more than 4 points in the full model. Students in schools with

multiple shifts are at a disadvantage as they have less contact hours with their teachers, limiting instructional time

and reducing learning achievement. In addition to teachers, in multiple-shift schools’ available resources such as

textbooks and equipment may also be limited as they are meant to be used by students belonging to only one shift.

School Inputs

Schools with better pupil-teacher and pupil-classroom ratios have higher NAT scores, even after controlling for

region and division, and under the assumption that the indicator has a differential effect in urban versus non-urban

schools. In the full model, teacher and classroom ratios are significant - an increase of one student in the number

of pupils per teacher is correlated with a 0.06-percentage point decrease in test scores, while an increase of one

student in the number of pupils per classroom would lead to a 0.03-percentage point decrease in NAT

performance. This result is consistent with previous findings (e.g., Maligalig et al., 2010; BEPER, 2012).

Urban Location

There is a large significant difference in the average NAT scores between urban and rural scores – urban schools

have 10 points less on the average on the NAT compared to rural schools. In the full model, the coefficients on

pupil-teacher ratio and shifts are positive – this may be due to overlap between schools with higher teacher ratios

49

Conclusion

Overall, public spending on education has increased in the last eight years. NG spending on basic

education has generally seen an upward trend over the period 2009 to 2017, with increases in spending to

meet various reforms related to the K to 12 program. LGU spending which constitutes a very small share

of all public spending has been declining. Private spending on education has risen especially for lower

income households, indicating an improved access to education as a result of increased incentives to send

children to school. Access to education is also supported by partnerships with the private sector, which help

decongest public schools and provide a lower-cost alternative to direct provision of schooling by the

government.

and schools with shifts and schools in urban areas. Students in urban areas may also have socioeconomic

advantages compared to students in rural areas.

Teacher Quality

Data on positions of teaching personnel were used as proxy measures for teacher quality. As noted in Chapter 2,

DepEd’s teacher ranking system is based on qualifications such as years of teaching experience, educational

attainment, and specialized skills and training. Higher rankings such as Master Teacher positions, which progress

from Master Teacher I to III positions, presumably reflect better teacher quality than Teacher positions, which

also progress from Teacher I to III positions. The current analysis looked at the proportion of total Master Teacher

positions to total Teacher positions in the school.

Schools with better teacher quality, as reflected in having a larger proportion of Master Teachers, have

significantly higher NAT scores. Students’ learning achievement thus benefits from having more experienced and

more highly skilled teachers. Better learning outcomes may be a result of students’ direct instruction under these

more highly-ranked teachers, or through better overall teaching quality in the school due to the guidance provided

by Master Teachers to fellow teachers in lower-ranked positions.

Source of Teacher Funding

Teachers from funding sources other than the national budget are often hired to compensate for shortages in

nationally-funded DepEd teachers. The current analysis looked at the proportion of non-DepEd teachers to the

total number of teachers in each school. Non-DepEd teachers were teachers funded by the LGU’s main budget,

LGU’s SEF municipality, LGU’s SEF province/city, Parent-Teacher Association, and other sources of funding.

Having a higher proportion of non-DepEd, locally-funded teachers has a negative impact on achievement scores,

though its impact is non-significant in the full model. Although locally-hired teachers may help improve teacher

ratios, LGUs often pay lower salaries and sometimes hire teachers with lower qualifications.

50

Chapter 4 –Main Findings and Policy Implications

The findings from this study show both substantial gains in the basic education system in the Philippines

in the last eight years, as well as limitations and challenges going forward. Reforms accompanied by public

spending have been relatively successful in expanding the scope and scale of the basic education system

and relaxing constraints relating to inputs such as availability of senior high schools and classrooms, and

teachers in both junior and senior high schools.

Public Expenditure on Inputs into Basic Education

National education spending has increased over time, rising to more than 4 percent of the GDP in recent

years. This is close to the average for upper middle countries. The share of basic education in the

government education budget is high at around 85 percent. Increased government spending has largely been

absorbed by increase in the number of elementary and secondary teachers, and senior high school

infrastructure. As a result, pupil-/student-teacher ratios have improved at all school levels. Classroom ratios

have also improved, but mainly for secondary education. The government’s focus on expanding access to

kindergarten, junior high, and especially the newly-introduced senior high grades is likely to continue. In

such a scenario, the government will have to continue spending public funds on expanding school places

directly or through subsidies to students to attend private sector institutions.

Greater kindergarten coverage will improve equity and efficiency and concomitant savings later in the

system. With the introduction of three new grades – a mandatory year of kindergarten and two years of

senior high school – the Philippine basic education system has moved closer to the typical model of school

education. Coverage of 5-year-old children by pre-school still lags by 20 percent as can be seen in the large

difference between GER and NER in kindergarten. Parents consider the age of 5 years too young for

children to be attending school. With kindergarten being mandatory prior to enrollment in Grade 1, and age

5 being made the cut-off for enrolling in kindergarten, both coverage and enrollment at the right age can be

expected to improve in the next few years. However, cultural norms take time to change, and the

government should pursue outreach among parents and communities to help close the gaps in parental

perceptions.

Lower enrollment in senior high grades is likely due to the higher opportunity cost of time of children in

the relevant age group, especially boys. Providing parents and youth with information on returns to

schooling has shown to change the choices young people make in developing countries between education

and work.53 Lower enrollment and completion rates of boys is also seen in lower grades among the poorest

households, an issue which requires further investigation. Constraints faced by these households may be

systematically different and may require additional or different kinds of support.

The problem of multiple-shift schools has reduced over the period considered in this study, but such schools

still exist in considerable numbers. These schools tend to be among the larger ones (and urban-located)54,

and a significant number of children are affected by the negative impact on the quality of education due to

congestion. This problem needs to be responded to by either expanding the number of classes in the school

and equipping them adequately, and/or by opening more schools, either by the government on its own or

through partnerships with the private sector. The latter may be an effective option as multiple-shift schools

are most often found in urban areas.

53World Bank (2017). 54Large schools by themselves do not confer disadvantages but may be beneficial for educational quality due to greater variety of

resources becoming available. This was seen in the (regression) analysis in Box 12.

51

While public spending on education has relaxed access constraints in the form of more schools and subsidies

for poor students, learning outcomes have not shown concomitant gains. Education quality gains have been

modest at best, and students’ learning outcomes have shown only small improvements. By the system’s

own reckoning, small percentages of students both in elementary and secondary grades show proficiency

level competencies. Furthermore, results from the PISA 2018 reveal that majority of 15-year-old students

in the Philippines have not reached minimum proficiency levels in key learning areas, ranking last among

79 participating countries and economies in Reading and second to last in Science and Mathematics.

Better Teacher Preparation

Although the problem of teacher numbers has become less important, teacher quality remains at the heart

of the quality of education. The large number of teachers hired to fill the student-teacher ratio deficits has

been an important step forward in reducing teacher-related constraints. The fact that this has not translated

into improved learning outcomes is related to teacher preparedness and teaching-learning methods followed

in classrooms as teachers score low on tests measuring teacher content knowledge.

More Equal Distribution of Teachers by Quality

As noted, overall student-teacher ratios have declined – nationally and across regions, and across levels of

education. Within some regions, teachers are less equally deployed leading to an imbalance in the

availability of teachers across schools, with a percentage of schools with student-teacher ratios higher than

average and DepEd norms.

There are also significant variations in teacher quality among regions as measured by the distribution of

teacher positions. The percentages of teachers who are lower than Master Teacher level are higher in the

poorer regions. Learning outcomes are poorer in regions that have a lower share of teachers with higher

credentials, and in regions where the share of non-DepEd-funded teachers, who have lower eligibility

credentials and lower salaries, is higher. Teacher preparedness and teacher training are key areas that require

review and reform in the Philippines.

Subject Teachers Availability

This study has not looked at the availability of teachers by subject areas, which may be another dimension

of imbalance. Given the lower levels of proficiency among students in acquiring Science- and Math-related

skills (as measured by NAT scores), there is scope for further research on whether the education system,

including tertiary education, produces enough Math and Science graduates who enter the teaching

profession and incentivizes their production.

52

Greater Role for Local Governments

In 2017, the Philippines had a population of 100.3 million, making it the 11th most populous country in the

world, with 26 million Filipino children and young students constituting more than a quarter of the

population attending a largely centralized basic education system. The education system in the Philippines

is administered largely by the national government. The role of the LGU, financially and otherwise. is small

and seems to be declining over time. While the share of MOOE in the government education budget has

increased, the share of the MOOE allocated towards school discretionary expenditure has remained

constant. This may constrain schools from putting together education strategies that suit their mix of

students optimally. As can be seen from the data presented earlier, regions tend to use LGU funding to hire

teachers. On the one hand, LGU expenditures have been used to make up teacher numbers and contribute

to a more even spread of a critical input; on the other, differences in the abilities of LGUs to spend

(especially between primarily urban and primarily rural LGUs) also exacerbate inequalities between

regions. Additionally, locally-funded teachers tend to have lower credentials and inferior contracts

compared to teachers hired by the center. Different compensation packages for nationally- and locally-

funded teachers may create problems in teacher management, as well as have implications on teacher

motivation.

Alternative Education and Financial Support

The Alternative Learning System (ALS) provides second chance education in a structured manner and

reaches nearly 800,000 youth and others, but is unable to achieve its full potential due to inadequate

allocation of funds. Studies of the ALS, though limited, indicate that participants find the ALS effective,

but also note the existence of mismatch between program offerings and learner capacities and

characteristics. There is therefore an opportunity for the GOP to conduct an comprehensive evaluation of

the ALS program and using the findings for strengthening and scaling up the program. Children from better-

off households seem to be benefitting more from funding systems such as the ESC and SHS voucher

program. As has been recommended by the Department, there is scope for the program to be targeted

towards children with social disadvantages.

Box 13: Five Principles for Creating a Successful Teaching Force

A World Bank study, based on an extensive review of what works, has identified five principles for creating a

successful teaching force:

• Make teaching an attractive profession by improving its status, compensation policies and career

progression structures;

• Include a strong practicum component in pre-service education to ensure teachers are well-equipped to

transition and perform effectively in the classroom;

• Promote meritocratic selection of teachers, followed by a probationary period to improve the quality of

the teaching force;

• Provide continuous support and motivation in the form of high-quality in-service professional

development and strong school leadership to allow teachers to continually improve; and

• Use technology wisely to enhance the ability of teachers to reach every student factoring their areas of

strength and development.

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Building Comprehensive Data Systems

For efficient and effective planning at the system level for use of public funds, scaling up innovations and

interventions, and for continuous improvement at the school level, there is need for more and complete data

to be available at the national, region, division, district, and school levels:

• Expenditure on different levels of education (kindergarten, elementary, junior high, senior high,

tertiary, etc.) and the different items of expenditure for any given level of education (new

infrastructure, maintenance, salaries, textbooks, etc.).

• Impact assessments of initiatives such as ALS, vouchers, and others prior to scaling up. The impact

assessment should ideally be part of the initial design of the intervention.

• School-level data that combines information processes, demographics, teaching-learning methods,

assessments, and expenditures (whether from public, private, or community sources) for feedback

on the production of learning at the school level.

Box 14: Institutional Arrangements in Education Systems

Centralized or decentralized system?

Tiebout (1956) had highlighted economies and diseconomies of scale in governance and management associated

with population size. Tiebout, in fact, had assumed an optimal (city) size given economies of scale in the provision

of public goods. Functions need to be allocated at different levels of aggregation for maximizing social welfare.

In education, this would mean establishment of standards and curricula be a central government responsibility;

conversely, relevance of decision-making and accountability could improve if local governments and schools

have a greater role in the allocation of resources as they may be better judges of where they are needed the most.

How do institutional arrangements affect learning outcomes?

Research on this question is uncommon as the data requirement for answering it is large. Wossman (2003), using

1995 TIMSS data for 39 countries, found the following institutional features of education systems to be associated

with better test scores: central examinations, centralized control mechanisms on curricula and budget, school

autonomy in process and personnel decisions, incentives and powers for teachers to select their teaching methods,

administrative tasks and educational funding handled by intermediate administrative levels, among others. Fuchs

and Wossman (2005), using 2000 PISA data for 31 countries, found positive association between test scores and

external exit examinations, school autonomy over textbook purchase decisions, school autonomy over budget

allocations, central authority over budget size, school autonomy over teacher hiring decisions, and private

schooling.

54

Annex 1 – Data and Methods

This annex discusses data sources used in the report. Methods and definitions of key technical terms are

provided. Lastly, limitations of the available data used in the report are noted.

Basic Education Inputs and Outcomes Data Analysis

Data Sources

Data on basic education performance indicators for the years 2009 to 2018 were taken from the Enhanced

Basic Education Information System (EBEIS) through the DepEd Planning Service – Education

Management Information Systems Division. Learning achievement data were based on the National

Achievement Test (NAT) scores obtained from the DepEd Bureau of Education Assessment – Education

Research Division. Data on international comparisons for various education performance indicators were

taken from the World Bank’s Education database.

Definitions and Methods

Data on participation and internal efficiency indicators include both public and private schools, while data

on input indicators such as teacher and classroom ratios represent only public schools. The report follows

DepEd’s definitions for each performance indicator.

In addition to total enrollment, the report used data on enrollment rates. Gross and net enrollment rates are

defined as follows:

• Gross enrollment rate (GER) is the total enrollment in a given level of education as a percentage of

the population which should be enrolled at that level (i.e., school-age ranges per level, which are

age 5 for kindergarten, 6-11 for elementary, 12-15 for JHS, and 16-17 for SHS).

• Net enrollment rate (NER) is the enrollment of learners in the school-age range in a given level of

education as a percentage of the school-age population for that level.

Internal efficiency indicates whether education funds are being allocated to maximize education outputs

while minimizing wastage. The internal efficiency indicators used in this report are defined as follows:

• Cohort survival rate is the proportion of enrollees at the beginning of the grade of a level of

education who reach the final grade of that level.

• Completion rate is the percentage of first year entrants in a level of education who finish that level

of education.

• Transition rate is the percentage of learners who graduate from one level of education and move on

to the next higher level. Three transition rates are included: transition from primary level to

intermediate level (i.e., Grade 4 to Grade 5), from elementary to junior high school (i.e., Grade 6

to Grade 7), from junior high school to senior high school (i.e., Grade 10 to Grade 11).

• Repetition rate is the percentage of learners enrolled in a given grade in a given school year who

repeat the same grade the following school year.

• Dropout rate is the proportion of learners who leave school during the year, as well as those who

complete the grade but fail to enroll in the next grade the following year, to the total number of

learners enrolled during the previous year.

Data on education inputs such as number of teachers and classrooms, as provided by EBEIS, refer only to

public schools. The input indicators are defined as follows:

55

• Pupil-/student-teacher ratio is the proportion of enrollment at a given level of education in a given

school year to the total number of authorized nationally-paid positions for teachers at the same level

in the same school year.

• Pupil-/student-classroom ratio is the proportion of enrollment at a given level of education in a

given school year to the total number of classrooms at the same level in the same school year.

• Teacher ranking refers to the official position of teaching personnel (i.e., Teacher I to III, Master

Teacher I to IV) based on DepEd’s teacher ranking system. Because teacher ranking is based on

qualifications such as educational attainment and years of experience, the report used data on

teacher ranking as a proxy measure for teacher quality.

To examine trends in learning achievement, the report used data on NAT scores. National assessments are

administered to Grades 3, 6, 10, and 12. Due to limitations described below, the report focused on Grades

6 and 10 NAT results for the years 2009 to 2015.

Data Limitations

The available EBEIS data limits comparisons between public and private sectors, with the exception of data

on total enrollment and total number of schools. The EBEIS data on participation and internal efficiency

indicators cannot be disaggregated by sector. Data on input indicators, however, are only available for

public schools; the same are not available for the private sector. Additionally, some inconsistencies were

found in the data reported for ARMM. School-level data in the region reveal missing values for basic

information such as total enrollment and number of teachers, which then affect the computation of

performance indicators.

The Grade 3 assessment has undergone several changes, including the replacement of the previously-

administered NAT by the Early Language, Literacy, and Numeracy Assessment in 2016. Because Grade

12 was only introduced in SY 2017-2018, data on the Grade 12 NAT are not yet available. Due to these

limitations, the report focused on NAT data for Grades 6 and 10 to examine learning achievement in

elementary and secondary levels, respectively. Changes in test administration and composition, as discussed

in Chapter 1, have made certain years of NAT results non-comparable over time. As such, analysis of trends

in Grades 6 and 10 NAT performance are only limited to SY 2008-2009 to SY 2014-2015.

Government Spending Data Analysis

Data Sources

As provided by Republic Act No. 9155, or the “Governance of Basic Education Act of 2001”, DepEd is the

agency responsible for ensuring access to quality and equitable basic education. In addition to DepEd,

agencies such as the Department of Public Works and Highways (DPWH) and local government units

(LGUs) also contribute to the provision of basic education. Under the Basic Education Facilities Fund

(BEFF), the School Building Program funds are transferred from the DepEd budget to that of DPWH. The

School Building Program, which covers new classroom construction and comprises majority of the BEFF,

is managed and implemented directly by the DPWH. LGUs also spend on basic education through both

their main budget and their Special Education Fund (SEF).

Budget data for DepEd was obtained from the Statements of Appropriations, Allotments, Obligations,

Disbursements, and Balances (SAAODB) from the DepEd Finance Service – Budget Division. Budget data

for the School Building Program under the BEFF was taken from the DPWH SAAODB provided by the

Department of Budget and Management (DBM). LGU spending data was obtained from the LGU Fiscal

Statement of Receipts and Expenditures from the Department of Finance – Bureau of Local Government

56

Finance. Additionally, budget data on other education-related agencies, to reflect total education spending,

were obtained from SAAODBs for the Department of Science and Technology (DOST), State Universities

and Colleges (SUC), the Technical Education and Skills Development Authority (TESDA), and the

Commission on Higher Education (CHED), which were provided by the DBM. All budget data covered the

years 2009 to 2017, with the exception of certain years for agencies listed in the section on data limitations

below.

Other data obtained from DBM include the Implicit Price Index (IPIN), which was used by the DBM as the

deflator with 2000 as the base year, data on the Gross Domestic Product (GDP), and national total

government spending. Data on the sectoral allocation of the national government budget were taken from

the Budget of Expenditures and Sources of Financing (BESF), also provided by DBM.


Table 9 presents the definitions of the key terms in budget data. Appropriations refer to the funds the

government is allowed to spend through the national budget under the General Appropriations Act in each

fiscal year. Allotments are the authorizations issued by DBM allowing an agency to incur obligations.

Obligations are the incurred liabilities that the government is committed to pay immediately or in the future,

while disbursements refer to the settlement of obligations. Although disbursements or actual payments are

ideal to use in budget data analysis, data on disbursements are limited in the availability of details by actual

service rendered, allotment class, and program or project. As such, the report used data on obligations,

which reflect the amount the government has promised to pay, to approximate actual government spending.

In this report, national government spending on basic education is defined as the total of DepEd and DPWH

BEFF obligations, unless otherwise specified.

Table 9: Definitions of Key Public Expenditure Terms in the Philippines

Public Expenditure Term Definition

General Appropriations Act

The legislative authorization that contains the new appropriations authorized by Congress in terms of specific amounts for salaries, wages and other personnel benefits, maintenance and other operating expenses, and capital outlay authorized to be spent for the implementation of programs, activities and projects of all departments, bureaus and offices of government for a given year.

Appropriations

New An authorization for incurring obligations during a specified budget year as listed in the General Appropriations Act.

Continuing An authorization to support obligations for a specific purpose or project, even when these obligations are incurred beyond the budget year.

Automatic One-time legislative authorization to provide funds for a specified purpose and is made automatically available and does not require periodic action by the Congress.

Allotments

Authorization issued by the DBM to an agency, permitting the agency to commit/incur obligation and/or pay out funds within the amount specified through the:

1. General Appropriations Act as an Allotment Order (starting FY 2017), for specific appropriation items deemed released upon effectivity of the General Appropriations Act;

2. General Allotment Release Order for the full year requirement for the automatically appropriated Retirement and Life Insurance Premium contributions; and

3. Special Allotment Release Order for budget items requiring compliance with certain conditionalities.

Obligations

A commitment by a government agency arising from an act of a duly authorized official which binds the government to the immediate or eventual payment of a sum of money. Obligations may only be incurred in the performance of activities authorized in appropriations acts within the limit of the allotment released by the DBM.

Disbursements The settlement/liquidation/payment of an obligation incurred in the current or prior years, involving cash or non-cash transactions and covered by disbursement authorities.

57

Expense Class

Personnel Services The payment of salaries, wages and other compensation of permanent, temporary, contractual, and casual employees of the government.

Maintenance and Other Operating Expenses

Support to the operations of government agencies such as expenses for supplies and materials, transportation and travel, and utilities (e.g. water, electricity) and repairs.

Financial Expenses The management supervision/trusteeship fees, interest expenses, guarantee fees, bank charges, commitment fees and other financial charges incurred in owning or borrowing an asset property.

Capital Outlay The purchase of goods and services, the benefits of which extend beyond the fiscal year and which add to the assets of the government (e.g., school buildings, furniture).

Source: DBM Glossary of Terms, BESF 2017 and 2018.

Using these definitions, various indicators were calculated to examine the trends in public spending on

basic education. These include:

• National government (NG) basic education spending, which is the amount of spending (i.e.,

obligations) by DepEd plus DPWH BEFF;

• LGU basic education spending, which is the amount of spending on basic education by LGUs;

• Total government basic education spending, which is the sum of NG and LGU basic education

spending; and

• NG basic education spending by expense class, which is the NG basic education spending reported

for personnel services, maintenance and other operating expenses, financial expenses, and capital

outlay.

These indicators were also expressed in real terms with 2000 as the base year. Per pupil spending was

computed by dividing the obligations in each indicator by total enrollment. Per pupil real spending was

then also expressed in real 2000 prices. To compute for these indicators in real terms, the obligations amount

was multiplied by the factor 1 , where IPIN is the Implicit Price Index (i.e., GDP deflator).

IPINdeflator2000

Data Limitations

The available data have several limitations. First, as earlier noted, data for the other agencies contributing

to total education spending are incomplete for certain years. Budget data for TESDA are only available

from FY 2010, while budget data for SUC and CHED are only available from FY 2011. Second, LGU

spending data are not available by level of education. As such, LGU per pupil spending by level of education

is not possible to compute. Also, because LGU data are not available by expense class, it is not possible to

track where LGU funds are actually spent. Next, NG obligations data on specific programs, projects, and

activities, such as spending on textbooks and furniture, are not disaggregated by level of education. Lastly,

NG spending data on ARMM are not available.

Household Data Analysis

Data Sources

The report used two national surveys to obtain household data, namely, the Annual Poverty Indicators

Survey (APIS) and the Family Income and Expenditure Survey (FIES) by the Philippine Statistics Authority

(PSA). The FIES is conducted every three years, while the APIS is conducted annually in the years between

the FIES surveys.

Several rounds of the APIS were used to examine various education outcome indicators. In comparing

school participation by income quintile and by gender, the report used APIS 2017, which was the most

58

recently available data. To estimate grade-to-grade cohort survival rate, APIS data from 2007 to 2017 were

used.

The report used the FIES 2012 and 2015, which were the two most recently available data from the survey.

The survey covered a total of 40,171 households in 2012 and 41,544 households in 2015. The FIES tags

households with members aged 5-17 years old, which correspond to the official age group for K to 12

learners. This report used data on household expenditure on education for households with school-age

members, which is defined in this report as children aged 5-17 years. Household education expenditure was

examined by income quintile and by region.


Using the household member-level APIS data, the following education outcome indicators were derived:

• GER, which is the total enrollment in a given level of education as a percentage of the population

which should be enrolled at that level (i.e., school-age ranges per level, which are age 5 for

kindergarten, 6-11 for elementary, 12-15 for JHS, and 16-17 for SHS);

• NER, which is the enrollment of learners in the school-age range in a given level of education as a

percentage of the school-age population for that level; and

• Cohort survival rate, which is the proportion of individuals enrolled in a certain grade (e.g., Grade

1) who transition to the next grade (e.g., Grade 2). For this, APIS 2007 to 2017 data were used to

track the Grade 1 cohort in 2007 until they had reached Grade 11 in 2017.

The number of out-of-school children, which are reflected in the number of children reported as currently

not in school, were also examined by gender and by income quintile. In addition to the prevalence of out-

of-school children, the reasons cited for not attending school were also examined. All statistics were

weighted using the appropriate raising factor provided in the APIS datasets.

The FIES disaggregates household spending on education into the following categories:

• Tuition fees, which encompass pre-primary to tertiary education;

• Education not definable by level, which are expenses on education activities such as review centers

and computer training;

• Allowance for family members studying away from home; and

• Other educational expenses; which include miscellaneous expenses such as school uniform and

footwear, computer rental services, and printing services.

The sum of all these categories is equal to total household education spending. Using the regional Consumer

Price Index (CPI) obtained from the PSA, the data were expressed in 2006 prices to adjust for overall price

inflation and were further adjusted to NCR levels to account for spatial price differences. Only households

with school-age members, defined as children aged 5-17 years old, and reporting education expenditures

were included in the analysis.

To approximate per capita spending on education, household spending on education was divided by the

total number of school-age household members. Per capita education spending was examined by income

quintile and by region. Total education spending as a share of total household spending was also examined

by income quintile. All statistics were weighted using the appropriate raising factor provided in the FIES

datasets.

59

Data Limitations

Although the APIS data provide information on whether children are currently attending school or not,

there may be discrepancies between APIS school attendance data and EBEIS enrollment data, as noted in

BEPER (2012). The reference period for enrollment in the APIS is the first six months of the survey year;

in contrast, DepEd’s reference period for enrollment is an entire school year, and its definition for

enrollment is being properly registered by August 31. Also, because the survey is not conducted every year,

complete K to 12 grade-to-grade cohort survival cannot be computed using the APIS datasets.

Although the FIES provides information on the number of school-age household members, which are

defined as children aged 5-17 years old, data on enrollment status are not given. Furthermore, the FIES data

do not identify whether children are attending private or public schools. This makes it difficult to interpret

household expenditure data, as households sending children to private schools would likely be spending

much more than those sending their children to public schools. Lastly, the FIES education expenditure data

do not segregate by level of education, except for the category of tuition fees. Although households with

only 5- to 17-year-old children were kept in the analysis, it is possible that some pre-primary and tertiary

education expenses were still included.

Determinants of Learning Outcomes

Data Sources

School-level data on the Grade 6 National Achievement Test (NAT) scores were obtained from the DepEd

Bureau of Education Assessment – Education Research Division. Due to changes in the administration and

structure of the assessment over the last few years, the NAT SY 2014-2015 was chosen for the analysis.

The Grade 6 NAT measured students’ competencies in English, Science, Math, Filipino, and HEKASI (i.e.,

social studies). The analysis used the overall NAT mean percentage scores for each school.

School characteristics were obtained from the EBEIS database through the DepEd Planning Service –

Education Management Information Systems Division. School characteristics used in the analysis included

total enrollment, pupil-teacher ratios, pupil-classroom ratios, number of shifts, number of teachers by

teaching position, and number of locally-funded teachers. The NAT and EBEIS datasets were merged using

unique school IDs assigned by DepEd for each school. A total of 33,567 schools were merged.


Although school-level data such as number of CCT recipients, school MOOE utilization, and number of

non-teaching positions are available for more recent years, data for the earlier school year used in the

analysis were more limited. Available EBEIS data on school characteristics were included in the analysis

as regressors.

The school inputs used in the analysis were pupil-teacher ratios and pupil-classroom ratios, which reflect

the number of teachers and classrooms available to students in the school. Data on total enrollment was

divided into quartiles and entered into the regression as dummy variables. As schools with large enrollment

sizes often resort to the shift system, its effect on learning achievement was also examined. Schools with

two, three, or four shifts were counted as multiple-shift schools.

As proxy measures for teacher quality, data on the number of teachers by teaching positions were used in

the analysis. Teachers who occupy Master Teacher positions have higher rankings and are presumed to

reflect better teacher quality. To examine whether teacher quality has an effect on achievement scores, the

60

analysis used data on the proportion of total Master Teachers I to III positions to total Teacher I to III

positions.

Data on the number of teachers by source of funding were also included in the analysis. In particular, the

analysis looked at whether the proportion of locally-funded teachers to the total number of teachers would

have an impact on learning outcomes. As listed in the EBEIS database, locally-hired teachers are funded

by the LGU’s main budget, the LGU’s SEF municipality, the LGU’s SEF province/city, the Parent-Teacher

Association, and other sources of funding.

Patterned after the models in BEPER (2012), in the absence of data on national government expenditure

per school, region level dummies were included in the models. To control for the effects of student,

household, and community characteristics that presumably contribute to learning outcomes, division level

dummies were also used in the analysis. To see whether the effects of the variables differ for schools in

urban areas, interaction terms were included in the models. Schools were counted as urban or rural based

on their DepEd classification as a city schools division or non-city schools division.

Six models were used to examine the determinants of learning outcomes among schools. The regressors

are:

a) Model 1 (Core): pupil-teacher ratio, pupil-classroom ratio, use of multiple shifts, Master Teacher

to Teacher ratios, Non-DepEd to total teacher ratio, dummies for school size, dummies for urban-

rural classification.

b) Model 2: core plus region dummies.

c) Model 3: core plus division dummies.

d) Model 4: core plus interactions between urban-rural classification and each variable in the core

model.

e) Model 5: core plus region dummies and interactions between urban-rural classification and each

variable in the core model.

f) Model 6: core plus division dummies and interactions between urban-rural classification and each

variable in the core model.

The R2 value was 0.077 for Model 1 and 0.437 for Model 6. Annex 2 provides detailed tables of the results

using these different models. Despite the inclusion of region and division dummies in four of the models,

all six models failed the test for omitted variables. This implies that other relevant variables, such as student

and household characteristics, were not captured in the models. As such, the regression results should be

viewed with caution.

Data Limitations

First, although learning achievement data at the individual student level are ideal, data on the NAT scores

are limited to the school level. Second, although the NAT data are available for public and private schools,

the school-level EBEIS data only capture public schools. As such, it is not possible to make comparisons

between the two sectors. Furthermore, as earlier noted, the models used in the regression do not capture

other substantial components of education production, such as individual student, household, and

community characteristics, as the data are limited to those available in the EBEIS. Lastly, it is noted that

other school-level data which are typically collected by DepEd, such as the number of non-teaching

personnel, positions of school heads, and MOOE utilization, were not available for the school year used in

the analysis.

61

Annex 2 – Reference Tables for Chapters 1 and 2

Table 10: Internal Efficiency Indicators, by Level, SY 2009-2010 to SY 2017-2018

School Year Cohort Survival Rate (%) Completion Rate (%) Dropout Rate (%)

Elementary JHS Elementary JHS Elementary JHS

SY 2009-2010 74.38 78.44 72.18 73.55 - -

SY 2010-2011 74.23 79.43 72.11 75.06 6.29 7.59

SY 2011-2012 73.82 78.88 71.01 74.40 6.36 7.79

SY 2012-2013 74.24 78.05 72.66 74.64 6.24 8.10

SY 2013-2014 78.97 79.30 77.67 76.25 4.85 7.58

SY 2014-2015 85.08 80.73 83.74 77.77 3.26 6.90

SY 2015-2016 87.52 81.56 84.02 74.03 2.69 6.62

SY 2016-2017 93.81 83.06 93.06 80.91 1.50 6.17

SY 2017-2018 93.67 85.65 92.41 84.32 1.56 5.22

Note: SHS data are not available for these internal efficiency indicators.

Table 11: Kindergarten GER and NER, by Gender, SY 2010-2011 to SY 2017-2018

School Year Kindergarten GER (%) Kindergarten NER (%)

Male Female Total Male Female Total

SY 2010-2011 77.92 80.97 79.39 55.88 58.63 57.20

SY 2011-2012 98.22 100.78 99.45 72.53 75.11 73.77

SY 2012-2013 101.45 104.02 102.69 75.83 78.31 77.03

SY 2013-2014 106.39 107.09 106.73 74.99 76.95 75.93

SY 2014-2015 102.52 102.19 102.36 77.85 80.85 79.30

SY 2015-2016 97.83 96.82 97.33 72.44 75.94 74.13

SY 2016-2017 84.09 80.77 82.47 66.36 65.53 65.95

SY 2017-2018 103.61 100.40 102.04 82.98 84.46 83.70

Table 12: Elementary GER and NER, by Gender, SY 2009-2010 to SY 2017-2018

School Year Elementary GER (%) Elementary NER (%)


SY 2009-2010 107.75 106.76 107.27 88.26 90.77 89.48

SY 2010-2011 114.93 114.41 114.68 94.46 97.47 95.92

SY 2011-2012 115.42 114.41 114.93 95.82 98.47 97.10

SY 2012-2013 114.35 112.62 113.51 94.16 96.16 95.13

SY 2013-2014 112.26 110.08 111.20 93.00 94.65 93.80

SY 2014-2015 110.56 107.93 109.29 91.76 93.42 92.57

SY 2015-2016 107.43 105.11 106.31 90.20 91.96 91.05

SY 2016-2017 112.35 108.47 110.46 96.17 96.12 96.15

SY 2017-2018 103.61 100.40 102.04 94.12 94.27 94.19

Table 13: JHS GER and NER, by Gender, SY 2009-2010 to SY 2017-2018

School Year JHS GER (%) JHS NER (%)


SY 2009-2010 78.94 84.23 81.53 55.16 64.82 59.89

SY 2010-2011 83.51 89.48 86.42 59.54 70.21 64.74

SY 2011-2012 82.45 88.52 85.41 59.04 69.62 64.20

SY 2012-2013 81.82 87.95 84.81 59.15 69.60 64.24

SY 2013-2014 81.23 87.52 84.29 59.95 70.10 64.90

SY 2014-2015 81.37 86.90 84.07 58.42 68.30 63.23

SY 2015-2016 80.75 86.74 83.67 63.59 72.95 68.15

SY 2016-2017 88.25 95.95 91.98 68.79 79.94 74.19

SY 2017-2018 91.44 98.22 94.73 70.88 81.42 75.99

62

Table 14: SHS GER and NER, by Gender, SY 2016-2017 to SY 2017-2018

School Year SHS GER (%) SHS NER (%)


SY 2016-2017 65.24 76.67 70.78 31.03 44.14 37.38

SY 2017-2018 61.17 73.16 66.98 39.20 53.48 46.12

Table 15: Grade 6 NAT Overall Mean Percentage Scores, by Region, SY 2008-2009 to SY 2016-2017

Region 2009 2010 2011 2012 2013 2014 2015 2016 2017

Problem Solving


Critical Thinking

Region 1 69.02 69.09 69.35 64.98 66.61 70.66 70.12 39.71 42.97 37.88 34.58

Region 2 60.58 64.68 67.94 68.17 68.14 73.67 72.70 42.96 44.86 39.45 35.64

Region 3 67.69 70.03 70.27 69.96 74.04 74.87 73.39 40.76 44.69 39.38 35.97

Region 4A 66.83 69.02 68.43 64.54 65.96 59.82 57.89 42.55 47.16 42.16 37.86

Region 4B 70.67 67.31 72.87 73.63 74.52 76.17 75.93 41.49 43.56 39.05 35.24

Region 5 62.28 66.17 66.21 66.62 69.03 68.88 67.95 38.68 41.93 37.10 34.09

Region 6 64.58 67.65 66.71 66.96 68.99 73.38 73.80 43.38 43.25 38.44 34.90

Region 7 62.41 66.04 66.13 65.99 67.90 71.45 72.15 46.27 44.77 40.10 36.04

Region 8 77.22 80.89 80.36 76.95 77.71 78.87 77.06 41.93 42.40 37.20 34.59

Region 9 66.22 70.68 71.90 69.47 71.64 74.95 74.84 38.24 39.34 34.65 31.91

Region 10 64.23 69.16 70.39 69.52 70.64 73.14 72.23 39.88 42.10 37.22 33.94

Region 11 63.91 67.02 67.18 67.90 71.36 74.51 73.73 41.40 42.70 37.38 33.91

Region 13 66.38 71.73 72.60 71.51 73.42 76.32 76.12 39.78 41.96 37.06 34.70

CARAGA 75.50 79.12 79.48 79.85 79.49 80.42 79.58 39.40 41.03 36.12 33.55

CAR 60.22 63.75 63.85 65.63 66.33 70.27 69.79 47.90 50.64 45.09 40.44

NCR 63.09 62.41 59.87 57.08 60.09 61.31 58.05 45.32 50.09 45.27 40.59

ARMM 48.22 50.60 54.88 54.09 56.46 62.29 59.64 44.94 41.99 36.70 36.08

National 65.55 68.01 68.15 66.79 68.88 69.97 69.10 41.45 44.45 39.48 35.92

Table 16: Grade 8/10 NAT Overall Mean Percentage Scores, by Region, SY 2008-2009 to SY 2016-2017

Region 2009 2010 2011 2012 2013 2014 2015 2017

Problem Solving


Critical Thinking

Region 1 46.70 43.25 45.10 42.60 43.59 47.39 43.31 41.29 42.60 39.84

Region 2 44.12 42.26 45.55 47.75 49.49 52.96 49.36 43.11 44.26 41.52

Region 3 45.71 44.81 47.22 50.20 51.85 53.45 48.89 42.26 43.33 40.93

Region 4A 45.28 44.22 46.51 47.17 49.01 49.08 44.45 44.52 45.76 43.36

Region 4B 46.83 41.94 48.20 50.46 54.23 56.76 52.10 42.78 44.36 41.81

Region 5 43.32 42.13 45.13 46.36 49.66 51.29 46.90 42.41 43.76 41.41

Region 6 49.08 47.82 48.38 49.75 52.93 56.35 52.98 44.48 45.41 43.26

Region 7 47.65 47.37 49.26 51.98 53.94 58.40 52.80 45.50 46.13 44.32

Region 8 59.93 59.40 59.71 55.38 55.62 59.58 53.07 45.15 46.27 43.53

Region 9 45.78 45.97 48.47 48.44 49.38 57.40 54.28 41.05 41.71 39.06

Region 10 45.14 45.24 49.18 48.92 50.83 55.00 51.52 43.46 44.25 41.61

Region 11 44.82 44.44 47.21 48.11 52.88 55.84 51.57 43.88 44.59 42.41

Region 13 43.91 46.28 48.07 47.98 50.56 54.02 52.44 41.91 42.61 40.06

CARAGA 55.70 59.59 61.20 62.42 64.62 64.52 61.40 43.79 44.70 42.05

CAR 46.35 44.41 47.38 49.10 51.88 54.38 49.73 46.88 48.25 45.62

NCR 47.38 44.67 47.50 49.32 54.21 55.11 49.28 48.14 49.29 46.99

ARMM 36.53 33.68 37.06 37.11 37.94 44.49 41.07 37.65 38.38 35.35

National 46.70 43.25 45.10 42.60 43.59 47.39 43.31 41.29 42.60 39.84

Note: Prior to SY 2011-2012, the NAT was administered to students in Year 2, or the K to 12 equivalent of Grade 8.

Grade 10 NAT data for SY 2016-2017 are not available.

63

Table 17: Achievement Score Analysis Results

VARIABLES

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6

Core With Region

Dummies With Division

Dummies

With Interaction

Terms

With Region Dummies and

Interaction Terms

With Division Dummies and

Interaction Terms

Pupil-Teacher Ratio -0.0947*** -0.0893*** -0.0609*** -0.0904*** -0.0828*** -0.0638***

(-17.53) (-17.38) (-3.224) (-15.83) (-15.30) (-2.970)

Pupil-Classroom Ratio -0.0806*** -0.0421*** -0.0328*** -0.0836*** -0.0439*** -0.0325***

(-14.85) (-8.144) (-4.329) (-14.17) (-7.854) (-3.552)

Multiple Shifts -8.610*** -6.449*** -3.650*** -7.588*** -4.779*** -4.590***

(-18.94) (-13.45) (-4.579) (-11.00) (-7.204) (-4.218)

Ratio: Master Teachers to Teachers I-III

8.214*** 7.783*** 5.651*** 8.544*** 8.094*** 6.138***

(12.72) (12.85) (7.408) (12.43) (12.56) (7.270)

Ratio: Non-DepEd Teachers to Total Teachers

-1.659*** -0.106 -0.801 -1.942*** -0.124 -0.791

(-4.542) (-0.306) (-1.656) (-5.009) (-0.338) (-1.524)

School Size: 154-248 students

3.599*** 3.656*** 3.270*** 3.602*** 3.620*** 3.208***

(16.89) (18.21) (12.99) (15.99) (17.08) (12.06)

School Size: 249-439 students

3.559*** 4.140*** 4.038*** 3.610*** 4.183*** 4.063***

(16.11) (19.64) (12.41) (15.35) (18.70) (11.17)

School Size: Above 439 students

1.909*** 2.739*** 3.345*** 2.375*** 3.190*** 3.371***

(7.907) (11.78) (7.662) (9.011) (12.62) (7.151)

Urban School -1.164*** -2.304*** -10.10*** 0.738 0.987 -10.89***

(-5.585) (-11.64) (-26.34) (0.957) (1.366) (-14.72)

Urban School*Pupil-Teacher Ratio

-0.0368** -0.0680*** 0.0468**

(-2.013) (-3.938) (2.141)

Urban School*Pupil-Classroom Ratio

0.0279* 0.0242* -0.00431

(1.839) (1.684) (-0.255)

Urban School*Multiple Shifts

-1.395 -2.433*** 1.779

(-1.411) (-2.623) (1.201)

Urban School*Ratio: Master Teachers to Teachers I-III

-2.741 -2.891 -4.155**

(-1.376) (-1.557) (-2.151)

Urban School*Ratio: Non-DepEd Teachers to Total Teachers

2.304** -0.344 0.0628

(1.984) (-0.318) (0.0485)

Urban School & School Size: 154-248 students

-0.217 0.107 0.478

(-0.314) (0.166) (0.834)

Urban School & School Size: 249-439 students

-0.760 -0.586 -0.321

(-1.101) (-0.911) (-0.566)

64

Urban School & School Size: Above 439 students

-2.470*** -2.194*** -0.199

(-3.570) (-3.395) (-0.407)

Constant 78.06*** 73.90*** 72.98*** 77.85*** 73.57*** 73.01***

(341.6) (224.2) (173.3) (325.1) (218.8) (155.6)

Observations 33,393 33,393 33,393 33,393 33,393 33,393

R-squared 0.077 0.201 0.437 0.078 0.203 0.437

Note: *** p<0.01, ** p<0.05, * p<0.1; t-statistics in parentheses.

Table 18: Summary Statistics (Achievement Score Analysis)

Variable Mean Std. Dev. Min. Max.

Overall Mean Percentage Score 73.93 14.08 21.50 98.71

Pupil-Teacher Ratio 39.90 17.77 5.50 584.00

Pupil-Classroom Ratio 31.98 16.98 3.50 448.00

Multiple Shifts 0.03 0.18 0.00 1.00

Ratio of Master Teacher Positions to Teacher Positions 0.07 0.12 0.00 2.50

Ratio of Non-DepEd Teachers to Total Teachers 0.07 0.24 0.00 9.00

Total Enrollment 424.29 608.97 8.00 10,622.00

School Size 73.93 14.08 21.50 98.71

65

Annex 3 – Reference Tables for Chapter 3

Table 19: Government Spending on Education, 2009-2017

In current prices, in million PhP 2009 2010 2011 2012 2013 2014 2015 2016 2017

National Government Spending 180,343 194,627 252,516 273,936 332,192 336,478 427,923 500,398 676,587

1.0 Basic Education 178,847 191,118 218,817 240,238 291,030 284,606 365,202 430,048 577,924

1.1 Department of

Education 178,847 191,118 218,817 240,238 279,474 273,300 308,136 369,435 456,278

1.2 DPWH Basic

Education Facilities

Fund

- - - - 11,556 11,306 57,066 60,613 121,646

2.0 State Universities and

Colleges - - 27,827 26,920 32,177 38,648 47,172 53,089 63,380

3.0 Commission on Higher

Education - - 1,141 670 3,022 5,552 7,036 6,662 20,677

4.0 Technical Education and

Skills Development

Authority

- 2,361 3,459 4,019 3,642 5,019 5,119 6,421 7,808

5.0 Department of Science and

Technology 1,496 1,148 1,272 2,089 2,321 2,653 3,394 4,178 6,798

Local Government Units'

Spending 13,867 13,526 14,435 16,232 16,654 15,976 15,984 16,468 18,889

Basic Education Spending 192,714 204,644 233,252 256,470 307,684 300,582 381,186 446,516 596,813

Total Education Spending 194,210 208,153 266,951 290,168 348,846 352,454 443,907 516,866 695,476

Table 20: Government Spending on Education, in Constant Prices, 2009-2017

In 2000 prices, in million PhP 2009 2010 2011 2012 2013 2014 2015 2016 2017

National Government Spending 119,023 123,252 153,729 163,544 194,355 190,834 244,123 280,712 370,936

1.0 Basic Education 118,035 121,030 133,214 143,426 170,273 161,414 208,342 241,248 316,844

1.1 Department of

Education 118,035 121,030 133,214 143,426 163,512 155,002 175,786 207,245 250,152

1.2 DPWH Basic


Fund

- - - - 6,761 6,412 32,555 34,003 66,692


Colleges - - 16,941 16,072 18,826 21,919 26,911 29,782 34,748


Education - - 695 400 1,768 3,149 4,014 3,737 11,336


Skills Development

Authority

- 1,495 2,106 2,399 2,131 2,847 2,920 3,602 4,281


Technology 987 727 774 1,247 1,358 1,505 1,936 2,344 3,727


Spending 9,152 8,566 8,788 9,691 9,744 9,061 9,119 9,238 10,356

Basic Education Spending 127,187 129,595 142,002 153,116 180,016 170,475 217,460 250,486 327,200

Total Education Spending 128,174 131,817 162,517 173,235 204,099 199,895 253,241 289,951 381,292

Deflator (IPIN = 2000) 151.52 157.91 164.26 167.50 170.92 176.32 175.29 178.26 182.40

66

Table 21: Government Spending on Education as % of GDP, 2009-2017

2009 2010 2011 2012 2013 2014 2015 2016 2017

National Government Spending 2.25 2.16 2.60 2.59 2.88 2.66 3.21 3.46 4.28

1.0 Basic Education 2.23 2.12 2.25 2.27 2.52 2.25 2.74 2.97 3.66

1.1 Department of

Education 2.23 2.12 2.25 2.27 2.42 2.16 2.31 2.55 2.89

1.2 DPWH Basic


Fund

- - - - 0.10 0.09 0.43 0.42 0.77


Colleges - - 0.29 0.25 0.28 0.31 0.35 0.37 0.40


Education - - 0.01 0.01 0.03 0.04 0.05 0.05 0.13


Skills Development

Authority

- 0.03 0.04 0.04 0.03 0.04 0.04 0.04 0.05


Technology 0.02 0.01 0.01 0.02 0.02 0.02 0.03 0.03 0.04


Spending 2.25 2.16 2.60 2.59 2.88 2.66 3.21 3.46 4.28

Basic Education Spending 2.40 2.27 2.40 2.43 2.67 2.38 2.86 3.08 3.78

Total Education Spending 2.42 2.31 2.75 2.75 3.02 2.79 3.33 3.57 4.40

Table 22: Government Spending on Education as % of National Government Spending,


2009 2010 2011 2012 2013 2014 2015 2016 2017

National Government Spending 15.68 16.64 19.68 18.40 20.03 19.98 20.42 21.18 22.52

1.0 Basic Education 15.55 16.34 17.06 16.14 17.55 16.90 17.43 18.20 19.23

1.1 Department of

Education 15.55 16.34 17.06 16.14 16.85 16.22 14.70 15.63 15.19

1.2 DPWH Basic


Fund

- - - - 0.70 0.67 2.72 2.57 4.05


Colleges - - 2.17 1.81 1.94 2.29 2.25 2.25 2.11


Education - - 0.09 0.05 0.18 0.33 0.34 0.28 0.69


Skills Development

Authority

- 0.20 0.27 0.27 0.22 0.30 0.24 0.27 0.26


Technology 0.13 0.10 0.10 0.14 0.14 0.16 0.16 0.18 0.23


Spending 1.21 1.16 1.13 1.09 1.00 0.95 0.76 0.70 0.63

Basic Education Spending 16.75 17.50 18.18 17.23 18.55 17.84 18.19 18.90 19.86

Total Education Spending 16.88 17.80 20.81 19.49 21.04 20.92 21.18 21.87 23.15

67

Table 23: Sectoral Distribution of National Government Spending, Obligations Basis,


PARTICULARS 2009 2010 2011 2012 2013 2014 2015 2016 2017

ECONOMIC SERVICES 34.99 32.60 28.54 32.93 31.16 29.24 33.79 34.71 35.86

Agriculture, Agrarian Reform, and

Natural Resources 8.33 8.60 5.45 7.09 7.22 6.42 5.91 5.31 4.75

Trade and Industry 0.53 0.48 0.42 0.44 0.39 0.34 0.39 0.46 0.39

Tourism 0.19 0.14 0.17 0.33 0.31 0.22 0.25 0.25 0.17

Power and Energy 1.12 0.21 1.36 5.38 1.80 1.09 0.62 0.51 0.28

Water Resource Development and

Flood Control 1.97 1.58 1.24 1.52 1.63 1.52 2.24 2.42 2.77

Communications, Roads, and Other

Transportation 14.53 12.52 10.91 10.63 12.50 12.00 17.04 18.52 20.57

Other Economic Services 0.73 1.12 1.16 1.13 0.92 0.56 0.82 0.88 1.25


SOCIAL SERVICES 35.80 35.56 42.47 39.78 42.94 45.39 42.31 41.16 40.32

Education, Culture, and Manpower

Development 18.15 21.82 19.83 18.77 19.72 19.34 17.91 18.80 18.62

Health 2.04 2.65 3.16 3.52 3.43 5.05 5.01 5.30 5.34

Social Security, Welfare and

Employment 6.57 4.17 9.03 9.75 10.69 11.82 11.04 9.42 8.96

Land Distribution (CARP) 0.11 0.34 0.31 0.00 0.30 - - - -

Housing and Community

Development 0.73 0.61 1.74 0.80 1.94 1.58 1.39 0.85 1.31

Other Social Services 0.16 0.12 0.12 0.14 0.11 0.10 0.09 0.08 0.09


DEFENSE 5.47 7.83 5.54 5.00 5.30 5.18 4.64 4.82 5.20

Domestic Security 5.47 7.83 5.54 5.00 5.30 5.18 4.64 4.82 5.20

GENERAL PUBLIC SERVICES 23.73 24.01 23.46 22.30 20.60 20.20 19.26 19.31 18.62

General Administration 8.37 7.61 7.70 8.60 7.99 7.07 6.99 6.43 5.82

Public Order and Safety 8.12 9.15 7.95 7.65 6.94 7.24 6.77 6.90 6.57

Other General Public Services 1.15 0.89 0.16 0.91 0.57 0.20 0.29 0.91 1.70


68

Table 24: LGU Spending on Basic Education, 2009-2017

PARTICULARS 2009 2010 2011 2012 2013 2014 2015 2016 2017

In current prices, in million PhP

Total LGU Education Spending 13,867 13,526 14,435 16,232 16,654 15,976 15,984 16,468 18,889

General Fund 3,562 3,129 3,434 3,235 3,450 4,086 4,642 5,359 5,716

Special Education Fund 10,305 10,397 11,001 12,997 13,204 11,890 11,342 11,109 13,172

In 2000 prices, in million PhP

Total LGU Education Spending 9,152 8,566 8,788 9,691 9,744 9,061 9,119 9,238 10,356

General Fund 2,351 1,981 2,091 1,932 2,018 2,318 2,648 3,006 3,134

Special Education Fund 6,801 6,584 6,697 7,759 7,726 6,743 6,470 6,232 7,222

As shares of total education spending

General Fund 25.7% 23.1% 23.8% 19.9% 20.7% 25.6% 29.0% 32.5% 30.3%

Special Education Fund 74.3% 76.9% 76.2% 80.1% 79.3% 74.4% 71.0% 67.5% 69.7%

As shares of total LGU spending

Total LGU Education Spending 5.9% 5.3% 5.4% 5.7% 5.6% 5.2% 4.9% 4.6% 5.0%

General Fund 1.5% 1.2% 1.3% 1.1% 1.1% 1.3% 1.4% 1.5% 1.5%

Special Education Fund 4.4% 4.1% 4.1% 4.6% 4.4% 3.9% 3.4% 3.1% 3.5%

Table 25: Total Government Education Appropriations, Allotments, and Obligations, 2009-2017 2009 2010 2011 2012 2013 2014 2015 2016 2017


I. Appropriations

A. National Government 191,608 206,473 272,517 302,039 363,834 409,872 471,716 588,520 715,440

Basic Education (DepEd +

DPWH BEFF) 186,542 202,614 235,606 261,672 316,322 347,026 400,573 507,208 608,507

B. LGU 13,867 13,526 14,435 16,232 16,654 15,976 15,984 16,468 18,889

C. Total Education Spending 205,475 219,999 286,952 318,271 380,488 425,848 487,700 604,988 734,329

II. Allotments



DPWH BEFF) 185,584 202,614 235,606 261,672 309,971 322,162 419,481 485,212 579,383

B. LGU 13,867 13,526 14,435 16,232 16,654 15,976 15,984 16,468 18,889


III. Obligations



DPWH BEFF) 178,847 191,118 218,817 240,238 291,030 284,606 365,202 430,048 577,924

B. LGU 13,867 13,526 14,435 16,232 16,654 15,976 15,984 16,468 18,889



I. Appropriations



DPWH BEFF) 123,114 128,310 143,435 156,222 185,070 196,816 228,520 284,533 333,611

B. LGU 9,152 8,566 8,788 9,691 9,744 9,061 9,119 9,238 10,356

69


II. Allotments



DPWH BEFF) 122,482 128,310 143,435 156,222 181,354 182,714 239,307 272,193 317,644

B. LGU 9,152 8,566 8,788 9,691 9,744 9,061 9,119 9,238 10,356


III. Obligations



DPWH BEFF) 118,035 121,030 133,214 143,426 170,273 161,414 208,342 241,248 316,844

B. LGU 9,152 8,566 8,788 9,691 9,744 9,061 9,119 9,238 10,356


Table 26: Per Pupil Nominal Spending, by Region, 2009-2017

2009

Regions Municipalities Cities Provinces Total LGU NG Total Spending

Region 1 - Ilocos Region 109.93 157.97 248.35 516.25 11,252.75 11,769.00

Region 2 - Cagayan Valley 148.03 94.22 116.46 358.70 10,193.09 10,551.79

Region 3 - Central Luzon 219.01 154.89 200.72 574.62 8,741.36 9,315.98

Region 4A - CALABARZON 333.63 371.18 190.67 895.48 7,629.64 8,525.12

Region 4B - MIMAROPA 117.01 96.33 160.71 374.04 9,143.86 9,517.90

Region 5 - Bicol Region 76.87 114.35 90.71 281.93 8,921.25 9,203.18

Region 6 - Western Visayas 107.97 234.74 82.79 425.50 10,024.70 10,450.21

Region 7 - Central Visayas 93.30 254.62 69.52 417.44 8,243.17 8,660.61

Region 8 - Eastern Visayas 44.07 70.42 65.59 180.08 10,180.05 10,360.14

Region 9 - Zamboanga Peninsula 41.47 673.75 54.50 769.73 9,338.67 10,108.39

Region 10 - Northern Mindanao 72.19 313.35 78.77 464.30 9,339.82 9,804.12

Region 11 - Davao Region 66.03 259.36 74.19 399.59 8,703.42 9,103.01

Region 12 - Central Mindanao 110.58 129.77 71.09 311.44 8,362.91 8,674.35

CARAGA 69.66 103.43 59.88 232.97 9,776.74 10,009.71

Cordillera Administrative Region 84.97 237.20 106.01 428.19 13,658.37 14,086.56

National Capital Region 4.72 3,022.13 - 3,026.85 7,792.49 10,819.34

Total 117.53 498.95 103.76 720.24 8,591.38 9,311.61

2010









70







CARAGA 77.58 80.17 53.70 211.45 10,008.76 10,220.20



Total 121.51 459.79 102.90 684.20 9,108.59 9,792.79

2011















CARAGA 97.33 88.91 49.95 236.19 11,376.57 11,612.76



Total 129.30 451.73 124.01 705.04 10,171.52 10,876.56

2012














71


CARAGA 81.59 115.87 53.66 251.12 12,580.63 12,831.75



Total 141.42 521.68 122.01 785.11 11,153.64 11,938.75

2013















CARAGA 84.18 116.04 67.19 267.42 14,045.48 14,312.90



Total 124.54 559.45 113.45 797.45 12,419.70 13,217.15

2014















CARAGA 106.22 92.26 70.03 268.51 14,342.90 14,611.40



Total 123.40 537.81 98.02 759.23 12,444.23 13,203.46

72

2015















CARAGA 138.16 106.94 73.53 318.63 14,776.63 15,095.26



Total 139.97 518.24 106.30 764.52 13,154.37 13,918.89

2016















CARAGA 131.06 94.56 55.02 280.64 18,172.24 18,452.88



Total 130.79 536.43 102.38 769.60 15,620.24 16,389.84

2017





73









Region 11 - Davao Region 1,104.23 201.14 97.64 1,403.01 15,785.69 17,188.70


CARAGA 149.75 91.09 68.46 309.31 20,209.29 20,518.60



Total 63.37 1.45 187.67 252.49 - 252.49

Table 27: Per Pupil Real Spending, by Region, 2009-2017

2009















CARAGA 45.97 68.26 39.52 153.75 6,452.44 6,606.20



Total 77.57 329.30 68.48 475.34 5,670.13 6,145.47

2010








74








CARAGA 49.13 50.77 34.01 133.90 6,338.27 6,472.17



Total 76.95 291.17 65.16 433.29 5,768.22 6,201.50

2011















CARAGA 59.25 54.13 30.41 143.79 6,925.95 7,069.74



Total 78.71 275.01 75.50 429.22 6,192.33 6,621.55

2012













75



CARAGA 48.71 69.18 32.04 149.92 7,510.83 7,660.75



Total 84.43 311.45 72.84 468.72 6,658.89 7,127.61

2013















CARAGA 49.25 67.89 39.31 156.46 8,217.57 8,374.03



Total 72.87 327.32 66.38 466.56 7,266.38 7,732.95

2014















CARAGA 60.24 52.32 39.72 152.28 8,134.58 8,286.87



76

Total 69.99 305.02 55.59 430.60 7,057.75 7,488.35

2015















CARAGA 78.82 61.01 41.95 181.77 8,429.82 8,611.59



Total 79.85 295.65 60.64 436.15 7,504.35 7,940.49

2016















CARAGA 73.52 53.05 30.87 157.43 10,194.23 10,351.67



Total 73.37 300.93 57.43 431.73 8,762.62 9,194.35

2017




77












CARAGA 82.10 49.94 37.53 169.58 11,079.66 11,249.23



Total 34.74 0.80 102.89 138.43 - 138.43

Table 28: Total Department of Education Spending, by Expense Class, 2009-2017

PARTICULARS 2009 2010 2011 2012 2013 2014 2015 2016 2017


Personnel Services 145,495 168,802 186,705 203,273 229,442 243,256 264,956 294,249 326,785

MOOE 23,897 18,151 21,515 23,342 27,123 25,849 31,714 48,975 91,876

Capital Outlay 9,454 4,163 10,595 13,623 22,908 4,195 11,466 26,211 37,617

Total 178,847 191,118 218,817 240,238 279,474 273,300 308,136 369,435 456,278


Personnel Services 96,023 106,898 118,235 121,357 134,240 137,963 151,153 165,067 179,158

MOOE 15,772 11,495 13,625 13,935 15,869 14,660 18,092 27,474 50,371

Capital Outlay 6,239 2,636 6,710 8,133 13,403 2,379 6,541 14,704 20,623

Total 118,035 121,030 138,571 143,426 163,512 155,003 175,786 207,245 250,152

Table 29: Per Pupil Department of Education Spending, by Expense Class, 2009-2017

PARTICULARS 2009 2010 2011 2012 2013 2014 2015 2016 2017

In current prices

Personnel Services 7,556.74 8,538.67 9,119.02 9,831.88 10,986.39 11,560.38 12,672.85 13,751.18 14,788.76

MOOE 1,241.19 918.15 1,050.81 1,128.99 1,298.75 1,228.44 1,516.87 2,288.75 4,157.89

Capital Outlay 491.02 210.57 517.48 658.90 1,096.90 199.36 548.41 1,224.94 1,702.38

Total 9,288.97 9,667.48 10,687.44 11,619.80 13,382.06 12,988.18 14,738.12 17,264.87 20,649.03

In 2000 prices

Personnel Services 4,987.29 5,407.30 5,551.58 5,869.78 6,427.80 6,556.48 7,229.65 7,714.11 8,107.87

MOOE 819.16 581.44 639.72 674.02 759.86 696.71 865.35 1,283.94 2,279.54

Capital Outlay 324.06 133.35 315.04 393.37 641.76 113.07 312.86 687.16 933.32

Total 6,130.52 6,122.15 6,506.42 6,937.19 7,829.43 7,366.25 8,407.85 9,685.22 11,320.74

78

Table 30: Department of Education Regional Basic Education Spending (in Thousand PhP),

by Expense Class, 2009-2017

Regions 2009 2010 2011 2012 2013 2014 2015 2016 2017

Region 1 - Ilocos

Region 11,242,691 11,855,431 13,552,590 14,413,044 16,181,410 16,383,916 17,151,019 20,769,879 23,611,750

Personnel

Services 9,808,821 10,890,984 12,388,397 13,105,502 14,643,554 15,298,296 15,619,397 18,005,296 20,592,729

MOOE 844,103 717,029 776,101 837,588 1,117,823 1,056,497 1,307,282 1,744,187 2,411,826

Financial

Expenses 589,766 247,419 388,092 469,955 0 0 0 0 0

Capital Outlay 0 0 0 0 420,033 29,123 224,339 1,020,396 607,195

Region 2 -

Cagayan Valley 6,521,164 7,618,132 8,604,285 10,233,274 11,372,362 11,413,685 12,034,756 13,907,936 16,869,888

Personnel

Services 5,737,969 6,903,807 7,727,326 9,248,705 10,226,940 10,631,505 10,911,221 12,218,802 14,671,765

MOOE 607,176 527,858 512,649 662,824 794,981 758,710 932,175 1,151,058 1,683,964

Financial

Expenses 176,019 186,460 364,310 321,745 23 0 0 0 0

Capital Outlay 0 8 0 0 350,418 23,470 191,360 538,076 514,159

Region 3 -

Central Luzon 17,207,226 18,496,341 21,708,663 23,814,875 26,317,373 27,613,949 28,843,812 35,034,003 38,999,937

Personnel

Services 14,767,323 16,590,875 19,566,223 21,140,198 23,941,902 25,695,747 26,354,687 31,001,887 34,038,731

MOOE 1,831,341 1,398,243 1,322,298 1,597,967 1,747,437 1,805,305 2,039,276 2,787,612 4,072,938

Financial

Expenses 608,467 505,794 817,768 1,076,410 234 72 0 0 0

Capital Outlay 94 1,429 2,373 300 627,800 112,825 449,850 1,244,504 888,269

Region 4A -

CALABARZON 17,363,727 19,414,877 22,134,585 24,951,961 27,816,452 29,054,256 30,908,010 38,026,249 42,614,120

Personnel

Services 15,118,343 17,496,375 19,782,135 21,713,598 25,013,791 27,131,451 28,215,894 33,432,139 35,906,191

MOOE 1,551,350 1,414,801 1,389,141 1,692,819 2,028,427 1,904,815 2,361,660 3,515,104 5,265,035

Financial

Expenses 694,034 503,701 963,309 1,545,544 0 0 0 0 0

Capital Outlay 0 0 0 0 774,234 17,990 330,456 1,079,006 1,442,895

Region 4B -

MIMAROPA 6,167,266 6,635,369 7,654,048 8,676,706 10,403,046 10,217,256 10,462,591 12,619,793 14,739,958

Personnel

Services 5,433,096 6,000,699 6,862,515 7,673,767 8,610,380 9,494,225 9,431,857 10,994,589 12,679,239

MOOE 533,726 504,675 512,498 626,107 766,844 668,148 869,902 1,254,182 1,608,812

Financial

Expenses 200,416 129,994 279,035 376,832 0 0 0 0 0

Capital Outlay 28 0 0 0 1,025,821 54,884 160,832 371,022 451,906

Region 5 - Bicol

Region 12,690,355 13,751,978 15,822,420 17,908,943 19,392,400 19,383,947 19,594,873 25,813,736 28,698,266

Personnel

Services 11,044,594 12,477,415 14,364,743 15,636,031 16,698,521 18,084,803 17,919,935 22,483,045 24,499,521

MOOE 1,143,300 1,071,401 911,542 1,388,157 1,432,218 1,239,483 1,286,895 2,221,090 3,424,163

79

Financial

Expenses 502,453 203,154 546,124 884,741 4 0 0 0 0

Capital Outlay 8 8 12 13 1,261,657 59,661 388,044 1,109,600 774,582

Region 6 -

Western

Visayas

15,580,654 16,889,757 19,190,865 21,206,741 24,189,790 24,358,774 24,347,224 30,412,837 33,035,598

Personnel

Services 14,052,232 15,616,999 17,778,151 19,108,162 21,297,734 22,364,723 22,342,791 26,621,337 28,324,289

MOOE 1,091,762 1,040,832 1,031,716 1,431,233 1,774,656 1,454,216 1,409,512 3,174,727 3,576,374

Financial

Expenses 436,660 231,823 380,998 667,346 0 0 0 0 0

Capital Outlay 0 103 0 0 1,117,400 539,835 594,921 616,772 1,134,935

Region 7 -

Central Visayas 12,030,559 13,430,647 15,527,575 16,785,809 19,558,904 20,623,679 21,411,018 25,248,420 30,540,094

Personnel

Services 10,469,580 11,905,946 13,573,706 14,652,077 16,829,921 19,026,511 19,662,249 22,333,959 26,504,608

MOOE 1,159,729 1,097,690 1,210,692 1,166,310 1,424,424 1,160,763 1,580,364 2,451,723 3,206,148

Financial

Expenses 401,250 427,011 743,178 967,422 0 0 0 0 0

Capital Outlay 0 0 0 0 1,304,559 436,405 168,404 462,738 829,338

Region 8 -

Eastern Visayas 10,430,339 10,586,435 12,604,628 13,876,510 15,491,123 15,284,672 17,586,656 21,537,082 24,045,342

Personnel

Services 8,789,492 9,748,463 11,253,921 12,173,892 13,911,593 13,913,385 15,429,620 18,178,709 20,702,750

MOOE 1,149,288 679,607 828,075 1,001,771 1,201,466 1,037,866 1,515,307 1,885,962 2,498,555

Financial

Expenses 491,559 158,365 522,629 700,847 0 1 0 0 0

Capital Outlay 0 0 4 0 378,064 333,420 641,728 1,472,412 844,037

Region 9 -

Zamboanga

Peninsula

7,489,358 8,109,419 9,488,031 10,433,701 12,062,895 12,032,601 12,825,654 15,147,320 16,670,853

Personnel

Services 6,633,922 7,383,873 8,503,832 9,172,325 10,422,340 11,169,680 11,414,617 13,486,806 14,438,126

MOOE 557,499 566,671 620,865 797,542 981,577 847,218 1,124,103 1,369,440 1,817,713

Financial

Expenses 297,937 158,875 363,334 463,834 0 0 0 0 0

Capital Outlay 0 0 0 0 658,977 15,703 286,934 291,074 415,014

Region 10 -

Northern

Mindanao

8,271,834 8,961,952 10,288,407 11,596,026 12,807,375 13,262,131 13,512,524 16,725,054 18,792,398

Personnel

Services 7,178,241 8,157,253 9,220,421 10,033,607 11,374,659 12,326,458 12,358,323 14,689,846 15,967,544

MOOE 674,486 680,873 658,774 917,080 1,017,132 897,934 1,080,334 1,515,023 2,241,065

Financial

Expenses 418,887 123,795 409,194 645,248 30 17 0 0 0

Capital Outlay 219 31 19 92 415,554 37,722 73,867 520,185 583,789

Region 11 -

Davao Region 7,858,032 8,492,989 9,834,461 10,960,787 12,764,091 12,505,068 12,965,020 15,950,261 17,824,112

80

Personnel

Services 6,915,344 7,702,876 8,797,774 9,544,498 11,014,463 11,469,739 11,822,681 14,034,731 15,370,928

MOOE 690,344 633,721 609,100 823,223 911,917 824,646 1,009,570 1,444,314 1,863,792

Financial

Expenses 252,344 156,392 427,587 593,066 0 0 0 0 0

Capital Outlay 0 0 0 0 837,711 210,684 132,768 471,216 589,392

Region 12 -

Central

Mindanao

7,357,678 8,024,815 9,584,080 10,180,830 12,268,037 10,720,608 12,958,752 14,758,943 18,514,932

Personnel

Services 6,310,275 7,245,949 8,361,207 9,025,298 10,543,953 9,938,137 11,826,591 12,931,193 15,644,328

MOOE 797,359 607,450 712,008 779,499 917,200 761,061 1,053,138 1,484,870 2,118,066

Financial

Expenses 250,044 171,417 510,864 376,032 0 0 0 0 0

Capital Outlay 0 0 0 0 806,885 21,410 79,023 342,880 752,539

CARAGA 5,628,273 6,011,590 6,987,217 7,753,846 8,793,704 9,158,614 9,471,673 11,950,338 13,828,371

Personnel

Services 4,859,482 5,422,053 6,256,072 6,850,969 7,789,593 8,474,817 8,528,508 10,421,926 11,793,786

MOOE 514,487 411,043 451,840 546,528 671,306 664,916 860,924 1,042,655 1,547,745

Financial

Expenses 254,304 178,494 279,296 356,350 4 0 0 0 0

Capital Outlay 0 0 10 0 332,801 18,882 82,241 485,757 486,839

Cordillera

Administrative

Region

4,360,188 4,474,671 5,231,605 5,662,476 6,216,612 6,309,076 6,578,427 7,893,065 9,063,881

Personnel

Services 3,597,908 3,999,621 4,582,186 5,026,583 5,509,977 5,836,503 5,857,429 6,980,180 7,724,582

MOOE 453,807 360,291 334,116 403,221 533,091 463,721 663,500 659,842 986,000

Financial

Expenses 308,474 114,758 315,303 232,672 0 0 1 0 0

Capital Outlay 0 0 0 0 173,545 8,852 57,498 253,044 353,299

National Capital

Region 15,215,966 17,314,582 20,040,338 22,144,729 23,740,414 23,532,356 24,371,761 28,448,396 30,795,365

Personnel

Services 13,253,863 15,734,822 17,295,990 18,765,517 21,181,843 21,925,314 22,389,411 25,738,270 27,154,194

MOOE 1,355,651 1,055,939 1,282,247 1,351,008 1,455,026 1,540,694 1,792,167 2,125,204 3,365,540

Financial

Expenses 606,452 523,821 1,462,101 2,028,205 0 0 0 0 0

Capital Outlay 0 0 0 0 1,103,545 66,348 190,183 584,923 275,631

Total Regional 165,415,310 180,068,986 208,253,797 230,600,257 259,375,987 261,854,590 275,023,769 334,243,311 378,644,865

Personnel

Services 143,970,485 163,278,011 186,314,598 202,870,727 229,011,166 242,781,292 250,085,211 293,552,715 326,013,311

MOOE 14,955,409 12,768,124 13,163,660 16,022,876 18,775,524 17,085,993 20,886,109 29,826,993 41,687,735

Financial

Expenses 6,489,067 4,021,271 8,773,121 11,706,248 295 90 1 0 0

Capital Outlay 349 1,580 2,417 405 11,589,002 1,987,214 4,052,447 10,863,604 10,943,819

81

Table 31: Department of Education Regional Basic Education Spending (in Thousand PhP),

by Level, by Expense Class, 2009-2017 2009 2010 2011 2012 2013 2014 2015 2016 2017

Region 1 – Ilocos Region

Kindergarten 0 0 0 0 0 52,740 111,696 58,306 88,416

Personnel

Services 0 0 0 0 0 8,839 97,995 58,217 88,416

MOOE 0 0 0 0 0 43,901 13,700 89 0

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 0 0

Elementary 6,090,564 6,212,764 7,213,863 7,813,565 9,602,096 9,276,594 9,406,948 9,829,525 11,779,638

Personnel

Services 5,926,895 6,041,967 7,047,819 7,636,037 9,200,120 8,845,170 8,974,384 9,252,045 11,162,753

MOOE 163,669 170,797 166,044 177,528 401,975 431,424 432,564 575,879 604,551

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 1,602 12,333

Secondary 2,873,835 2,919,843 3,356,299 3,638,768 4,451,136 4,366,496 5,580,957 5,169,061 7,669,228

Personnel

Services 2,661,233 2,715,165 3,155,039 3,424,710 4,160,984 4,043,291 5,249,436 4,694,779 6,918,916

MOOE 212,442 204,679 201,261 214,058 290,152 323,205 331,521 474,281 750,312

Financial

Expenses 160 0 0 0 0 0 0 0 0


Region 2 – Cagayan Valley

Kindergarten 0 0 0 4,579 5,774 62,806 92,961 123,989 142,001

Personnel

Services 0 0 0 4,579 5,774 22,694 59,815 123,989 142,001

MOOE 0 0 0 0 0 40,112 33,146 0 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 3,813,251 4,281,680 4,680,275 5,654,672 6,777,961 6,483,372 6,617,120 7,048,461 8,727,796

Personnel

Services 3,655,486 4,116,774 4,536,017 5,483,119 6,450,632 6,162,730 6,305,378 6,655,846 8,251,486

MOOE 150,606 164,906 144,258 171,553 327,315 320,642 311,742 392,615 466,635

Financial

Expenses 7,159 0 0 0 14 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 0 9,674

Secondary 1,586,305 1,764,292 2,070,063 2,471,037 2,977,376 2,912,326 3,144,781 3,623,375 5,136,628

Personnel

Services 1,452,841 1,624,813 1,922,153 2,308,876 2,780,349 2,712,616 2,924,470 3,335,637 4,650,081

MOOE 126,974 139,471 147,910 162,161 197,018 199,710 220,311 287,738 486,547

Financial

Expenses 6,491 0 0 0 9 0 0 0 0


Region 3 – Central Luzon

82

Kindergarten 10,766 10,800 12,345 13,488 16,822 176,312 262,573 391,805 440,497

Personnel

Services 10,766 10,800 12,345 13,488 16,822 91,729 233,680 389,450 440,497

MOOE 0 0 0 0 0 84,582 28,893 2,355 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 9,682,567 9,830,747 11,525,369 12,495,532 15,013,869 14,699,811 14,930,415 15,832,122 19,020,686

Personnel

Services 9,285,218 9,441,814 11,136,101 12,076,712 14,368,818 13,967,905 14,160,595 14,842,964 17,941,380

MOOE 397,349 388,934 386,899 418,820 645,051 731,906 769,820 986,294 1,063,279

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 0 2,369 0 0 0 0 2,864 16,027

Secondary 4,005,465 4,139,055 4,910,028 5,420,729 6,761,847 6,816,686 7,489,526 9,142,635 11,386,832

Personnel

Services 3,628,184 3,753,710 4,524,478 5,007,942 6,278,394 6,230,400 6,867,222 8,300,810 10,116,219

MOOE 377,216 383,916 385,546 412,512 483,238 586,216 622,304 841,825 1,270,612

Financial

Expenses 0 0 0 0 215 70 0 0 0

Capital Outlay 65 1,429 4 275 0 0 0 0 0

Region 4A – CALABARZON

Kindergarten 0 0 0 0 0 149,307 338,608 349,473 387,123

Personnel

Services 0 0 0 0 0 61,030 303,906 349,473 387,123

MOOE 0 0 0 0 0 88,277 34,702 0 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 9,967,130 10,235,664 11,881,660 12,840,980 15,487,372 15,458,625 16,542,880 17,537,314 20,697,914

Personnel

Services 9,517,143 9,758,725 11,440,319 12,370,698 14,751,863 14,656,191 15,699,451 16,426,002 19,490,832

MOOE 448,036 476,940 441,340 470,282 735,510 802,435 843,429 1,108,813 1,191,147

Financial

Expenses 1,950 0 0 0 0 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 2,500 15,935

Secondary 4,425,198 4,602,046 5,282,876 5,835,525 7,390,235 7,626,931 9,677,152 10,514,950 12,680,633

Personnel

Services 3,993,527 4,171,978 4,849,490 5,379,980 6,806,814 6,959,198 8,964,036 9,537,911 11,278,494

MOOE 429,233 430,068 433,386 455,545 583,421 667,733 713,116 977,039 1,402,138

Financial

Expenses 2,438 0 0 0 0 0 0 0 0


Region 4B - MIMAROPA

Kindergarten 23,140 6,188 23,774 28,906 34,727 68,444 174,374 184,217 207,101

Personnel

Services 23,140 6,188 23,774 28,906 34,727 35,074 168,481 177,203 207,101

MOOE 0 0 0 0 0 33,370 5,893 7,014 0

83

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 3,814,527 7,712,190 4,226,902 4,648,585 5,699,861 5,570,679 5,971,630 6,324,359 7,365,385

Personnel

Services 3,674,858 7,379,797 4,090,081 4,502,695 5,418,467 5,295,829 5,662,013 5,947,076 6,911,538

MOOE 139,641 331,143 136,821 145,890 281,394 274,850 309,617 376,414 447,833

Financial

Expenses 0 1,250 0 0 0 0 0 0 0

Capital Outlay 28 0 0 0 0 0 0 870 6,014

Secondary 1,202,471 3,076,802 1,707,609 1,908,248 2,398,581 2,403,697 2,599,539 3,200,291 3,782,610

Personnel

Services 1,099,919 2,814,873 1,589,476 1,787,047 2,233,391 2,224,300 2,403,079 2,919,566 3,348,425

MOOE 102,552 256,402 118,133 121,201 165,190 179,397 196,461 280,725 434,186

Financial

Expenses 0 5,518 0 0 0 0 0 0 0


Region 5 – Bicol Region

Kindergarten 6,182 52,580 8,824 9,592 1,102 178,843 320,836 329,432 333,985

Personnel

Services 6,182 52,580 8,824 9,592 1,102 113,436 298,313 304,002 333,985

MOOE 0 0 0 0 0 65,408 22,524 25,430 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 7,371,230 9,087,854 8,932,271 9,628,899 11,175,617 11,285,149 11,531,202 12,342,319 14,961,465

Personnel

Services 7,098,531 8,808,066 8,675,339 9,308,572 10,648,481 10,741,259 11,057,438 11,621,436 14,046,340

MOOE 268,339 279,755 254,562 319,299 527,133 543,890 473,764 719,383 903,195

Financial

Expenses 4,360 0 2,370 1,029 4 0 0 0 0

Capital Outlay 0 33 0 0 0 0 0 1,500 11,930

Secondary 2,935,868 4,195,818 3,550,706 3,856,663 4,423,667 4,813,617 4,831,045 6,069,184 7,535,138

Personnel

Services 2,691,756 3,870,092 3,340,163 3,546,123 4,096,027 4,444,849 4,539,632 5,498,308 6,570,825

MOOE 237,505 325,685 208,256 309,752 326,970 368,768 291,413 570,876 964,312

Financial

Expenses 6,598 0 2,276 774 0 0 0 0 0

Capital Outlay 8 41 12 13 670 0 0 0 0

Region 6 – Western Visayas

Kindergarten 52,177 52,580 75,481 83,688 113,977 250,827 483,917 452,619 505,501

Personnel

Services 52,177 52,580 75,481 83,688 113,977 173,073 447,305 452,619 505,501

MOOE 0 0 0 0 0 77,754 36,612 0 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 8,856,500 9,087,854 10,553,022 11,457,258 13,496,346 13,414,606 13,527,878 14,229,071 16,886,093

84

Personnel

Services 8,565,587 8,808,066 10,243,922 11,123,298 12,880,123 12,768,904 13,048,186 13,265,889 15,879,487

MOOE 290,913 279,755 309,100 333,959 616,223 645,702 479,692 956,211 995,486

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 33 0 0 0 0 0 6,971 11,120

Secondary 4,088,672 4,195,818 4,853,630 5,226,033 6,348,442 6,207,949 6,888,364 7,668,426 9,129,271

Personnel

Services 3,772,277 3,870,092 4,516,541 4,904,787 5,885,077 5,787,015 6,547,573 6,833,971 8,050,183

MOOE 316,395 325,685 337,089 321,246 463,365 420,934 340,791 834,455 1,079,088

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 41 0 0 0 0 0 0 0

Region 7 – Central Visayas

Kindergarten 0 0 0 0 0 72,895 345,923 343,688 376,914

Personnel

Services 0 0 0 0 0 0 330,721 337,840 376,914

MOOE 0 0 0 0 0 72,895 15,202 5,848 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 7,150,179 7,552,093 8,848,540 9,426,253 11,223,471 11,025,652 11,789,023 12,714,130 14,862,465

Personnel

Services 6,876,148 7,258,660 8,564,770 9,121,203 10,723,114 10,660,460 11,169,122 11,946,822 14,025,809

MOOE 274,031 293,433 283,770 305,050 500,357 365,192 619,901 759,859 825,144

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 7,450 11,513

Secondary 2,532,874 2,744,026 3,198,541 3,522,205 4,308,816 4,609,983 5,519,853 6,456,683 7,953,118

Personnel

Services 2,273,544 2,478,793 2,928,835 3,252,172 3,955,837 4,211,401 5,085,695 5,796,658 6,985,199

MOOE 259,331 265,233 269,706 270,033 352,979 398,582 434,158 660,024 967,919

Financial

Expenses 0 0 0 0 0 0 0 0 0


Region 8 – Eastern Visayas

Kindergarten 11,081 13,019 14,784 16,211 21,825 52,723 61,546 65,034 76,761

Personnel

Services 11,081 13,019 14,784 16,211 21,825 27,822 43,491 65,034 76,761

MOOE 0 0 0 0 0 24,900 18,055 0 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 5,851,602 6,135,600 7,198,823 7,741,955 9,481,012 8,829,459 9,467,781 9,920,696 12,074,221

Personnel

Services 5,623,289 5,907,484 6,977,699 7,485,965 9,035,566 8,344,478 8,981,880 9,291,310 11,359,545

MOOE 228,313 228,116 221,120 255,989 445,446 484,981 485,901 627,580 705,513

Financial

Expenses 0 0 0 0 0 0 0 0 0

85

Capital Outlay 0 0 4 0 0 0 0 1,805 9,164

Secondary 2,074,192 2,150,312 2,607,066 2,803,329 3,476,204 3,498,885 3,859,084 4,446,588 5,914,568

Personnel

Services 1,896,955 1,963,928 2,419,388 2,602,394 3,230,582 3,209,477 3,545,928 4,017,008 5,203,632

MOOE 177,237 186,384 187,678 200,935 245,622 289,407 313,157 429,580 710,936

Financial

Expenses 0 0 0 0 0 1 0 0 0


Region 9 – Zamboanga Peninsula

Kindergarten 4,470,316 0 19,196 20,797 31,595 115,776 236,403 78,925 254,146

Personnel

Services 4,302,866 0 19,196 20,797 31,595 74,509 225,044 78,925 254,146

MOOE 167,449 0 0 0 0 41,267 11,359 0 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 1,549,230 4,653,145 5,422,528 5,854,618 7,126,580 7,003,935 7,240,985 9,734,894 8,974,022

Personnel

Services 1,414,572 4,484,751 5,254,465 5,664,682 6,796,246 6,650,586 6,878,649 9,105,508 8,427,532

MOOE 134,658 168,393 168,063 189,936 330,334 353,349 362,336 627,580 539,372

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 1,805 7,118

Secondary 21,581 1,608,193 1,889,183 2,073,434 2,589,609 2,648,273 3,021,621 4,364,243 4,158,749

Personnel

Services 0 1,472,899 1,751,196 1,929,127 2,404,054 2,418,473 2,790,433 3,934,663 3,684,375

MOOE 21,581 135,294 137,988 144,307 185,555 229,800 231,188 429,580 474,374

Financial

Expenses 0 0 0 0 0 0 0 0 0


Region 10 – Northern Mindanao

Kindergarten 0 0 0 0 0 0 226,938 248,531 291,120

Personnel

Services 0 0 0 0 0 0 220,548 246,587 291,120

MOOE 0 0 0 0 0 0 6,390 1,944 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 4,953,695 5,125,021 5,924,854 6,482,543 7,842,052 630,532 7,874,478 8,084,562 9,787,130

Personnel

Services 4,748,120 4,936,226 5,750,376 6,271,897 7,470,190 630,532 7,477,944 7,565,377 9,191,138

MOOE 205,434 188,795 174,478 210,646 371,862 0 396,534 518,685 582,858

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 141 0 0 0 0 0 0 500 13,133

Secondary 1,696,167 1,751,387 1,995,886 2,219,391 2,760,212 217,488 3,209,143 3,552,471 4,378,814

Personnel

Services 1,529,704 1,595,891 1,852,845 2,062,708 2,549,885 217,488 2,976,886 3,212,451 3,815,041

86

MOOE 166,435 155,495 143,041 156,683 210,327 0 232,257 340,020 563,773

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 28 0 0 0 0 0 0 0 0

Region 11 – Davao Region

Kindergarten 0 0 0 0 0 49,660 165,653 205,744 222,506

Personnel

Services 0 0 0 0 0 10,974 151,560 198,530 222,506

MOOE 0 0 0 0 0 38,686 14,093 7,214 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 4,634,912 4,753,555 5,523,208 5,962,455 7,189,088 7,017,919 7,105,901 7,764,771 9,478,899

Personnel

Services 4,423,153 4,565,469 5,346,293 5,750,024 6,871,230 6,665,323 6,737,302 7,268,072 8,934,536

MOOE 194,365 187,782 176,915 212,430 317,858 352,596 368,600 495,290 537,188

Financial

Expenses 17,395 305 0 0 0 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 1,409 7,175

Secondary 1,815,283 1,875,842 2,181,418 2,374,300 2,988,931 2,982,502 3,088,876 3,470,524 4,577,255

Personnel

Services 1,662,492 1,711,633 2,015,963 2,191,090 2,773,503 2,741,341 2,836,330 3,124,662 4,054,725

MOOE 152,790 163,916 165,455 183,209 215,428 241,161 252,547 345,862 522,530

Financial

Expenses 0 292 0 0 0 0 0 0 0


Region 12 – Central Mindanao

Kindergarten 0 0 0 0 0 28,052 13,291 3,950 0

Personnel

Services 0 0 0 0 0 0 0 0 0

MOOE 0 0 0 0 0 28,052 13,291 3,950 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 4,178,701 4,353,410 5,176,516 5,576,691 6,800,677 5,806,304 7,731,746 7,788,892 9,422,833

Personnel

Services 4,004,483 4,179,257 5,002,536 5,383,598 6,480,776 5,494,117 7,292,296 7,329,692 8,889,759

MOOE 174,218 174,153 173,980 193,093 319,900 312,187 439,449 457,206 527,138

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 1,994 5,936

Secondary 1,718,089 1,741,122 2,064,139 2,252,241 2,804,428 2,423,186 3,324,335 3,659,023 4,767,312

Personnel

Services 1,567,893 1,590,209 1,910,001 2,087,486 2,595,190 2,216,715 3,075,049 3,308,137 4,175,278

MOOE 150,196 150,914 154,138 164,755 209,238 206,471 249,286 350,887 592,034

Financial

Expenses 0 0 0 0 0 0 0 0 0


87

CARAGA

Kindergarten 29,388 22,736 26,089 28,234 36,611 90,077 172,562 166,740 184,779

Personnel

Services 29,388 22,736 26,089 28,234 36,611 56,873 159,959 166,740 184,779

MOOE 0 0 0 0 0 33,205 12,603 0 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 3,231,758 3,358,047 3,917,157 4,299,673 5,251,964 4,882,004 5,230,832 5,600,748 6,804,557

Personnel

Services 3,120,804 3,239,630 3,804,487 4,183,842 5,006,504 4,629,125 4,946,466 5,247,355 6,426,840

MOOE 110,023 118,417 112,671 115,830 245,460 252,879 284,366 348,515 370,619

Financial

Expenses 931 0 0 0 0 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 4,879 7,098

Secondary 1,164,537 1,216,770 1,413,825 1,584,469 1,982,515 2,000,016 2,002,536 2,597,643 3,322,361

Personnel

Services 1,060,285 1,113,754 1,306,429 1,461,744 1,830,630 1,821,226 1,812,166 2,332,082 2,921,029

MOOE 104,252 103,016 107,387 122,725 151,885 178,790 190,370 265,321 401,251

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 0 10 0 0 0 0 239 81

Cordillera Administrative Region

Kindergarten 13,276 17,676 20,285 23,165 34,179 65,660 90,490 79,017 94,821

Personnel

Services 13,276 17,676 20,285 23,165 34,179 47,845 78,082 79,017 94,821

MOOE 0 0 0 0 0 17,815 12,408 0 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 2,284,370 2,357,256 2,755,354 2,995,627 3,649,463 3,486,043 3,629,137 3,745,863 4,318,320

Personnel

Services 2,206,045 2,288,425 2,686,847 2,912,644 3,483,172 3,306,839 3,444,500 3,514,903 4,052,820

MOOE 78,326 68,831 68,507 82,983 166,291 179,204 184,637 229,225 259,580

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 1,736 5,920

Secondary 942,872 978,492 1,132,679 1,238,997 1,528,910 1,440,873 1,602,541 1,732,334 2,033,739

Personnel

Services 875,962 912,207 1,068,648 1,162,616 1,428,872 1,330,352 1,486,189 1,573,126 1,808,088

MOOE 66,910 66,284 64,031 76,381 100,038 110,522 116,351 159,207 225,651

Financial

Expenses 0 0 0 0 0 0 1 0 0


National Capital Region

Kindergarten 0 0 0 0 0 41,190 14,823 0 0

88

Personnel

Services 0 0 0 0 0 0 0 0 0

MOOE 0 0 0 0 0 41,190 14,823 0 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 7,818,313 8,130,863 8,995,026 9,810,339 11,617,231 11,574,986 12,267,283 12,916,812 14,593,799

Personnel

Services 7,507,362 7,832,944 8,694,044 9,485,581 11,154,877 11,046,086 11,721,131 12,217,932 13,841,585

MOOE 310,951 297,920 300,982 324,758 462,354 528,900 546,151 697,801 739,755

Financial

Expenses 0 0 0 0 0 0 0 0 0

Capital Outlay 0 0 0 0 0 0 0 1,079 12,460

Secondary 4,762,396 5,606,038 6,227,825 6,772,510 8,339,386 8,254,900 9,221,671 9,873,038 11,802,829

Personnel

Services 4,355,650 5,119,451 5,736,349 6,274,591 7,792,615 7,629,396 8,568,683 9,064,281 10,783,848

MOOE 406,646 486,586 491,476 497,920 546,771 625,505 652,989 808,756 1,018,982

Financial

Expenses 100 0 0 0 0 0 0 0 0


Total Regional

Kindergarten 4,616,327 175,579 200,779 228,660 296,612 1,455,313 3,112,594 3,081,469 3,605,671

Personnel

Services 4,448,877 175,579 200,779 228,660 296,612 723,899 2,818,899 3,027,626 3,605,671

MOOE 167,449 0 0 0 0 731,415 293,694 53,843 0

Financial

Expenses 0 0 0 0 0 0 0 0 0


Elementary 91,248,530 102,867,745 112,775,369 122,689,643 147,434,660 136,445,671 150,865,242 161,414,539 189,755,223

Personnel

Services 87,647,696 99,048,053 109,251,116 118,760,567 140,740,179 129,865,533 143,556,736 151,498,228 178,833,380

MOOE 3,568,871 3,818,072 3,519,510 3,928,047 6,694,462 6,580,137 7,308,505 9,877,348 10,759,292

Financial

Expenses 31,795 1,555 2,370 1,029 18 0 0 0 0

Capital Outlay 169 65 2,373 0 0 0 0 38,963 162,550

Secondary 37,845,804 44,565,856 48,441,772 53,197,878 65,530,294 63,223,809 75,061,025 85,540,468 106,229,086

Personnel

Services 34,522,223 40,779,489 44,886,992 49,383,394 60,802,205 58,197,537 69,672,806 77,484,052 94,364,359

MOOE 3,307,693 3,779,029 3,552,478 3,813,422 4,727,195 5,026,200 5,388,218 8,056,177 11,864,646

Financial

Expenses 15,787 5,810 2,276 774 224 72 1 0 0

Capital Outlay 101 1,527 26 288 670 0 0 239 81

89

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