Report No: AUS0000920 . Philippines Basic Education Public Expenditure Review October 1, 2020 . Macroeconomics, Trade and Investment . © 2019 The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved This work is a product of the staff of The World Bank. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this work is subject to copyright. 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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 MDG Millennium Development Goals Financing 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- Public Education Expenditure Tracking QSDS 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 SBM School-Based Management System 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. 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 i 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. ii 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 iii 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 automati c), 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). iv 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 v 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. vi 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. vii 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 4 More 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. viii 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 Attached Agencies: OFFICE OF THE SECRETARY • Philippine High School for the Arts Office of the Secretary Proper • National Book Development Board Office of the Undersecretaries • National Council for Children’s Television • National Museum Office of the Assistant Secretaries • Early Childhood Care and Development Council Coordinating Councils: TEACHER EDUCATION INTERNAL AUDIT • Teacher Education Council COUNCIL SECRETARIAT SERVICE • Literacy Coordinating Council • Adopt-a-School Program Coordinating Council CURRICULUM GOVERNANCE LEGAL AND FINANCE AND STRATEGIC AND AND LEGISLATIVE ADMINISTRATION MANAGEMENT INSTRUCTION OPERATIONS AFFAIRS Bureau of Bureau of Learner Finance Service Legal Service Planning Service Curriculum Support Services Development Bureau of Human Administrative Public Affairs Bureau of Learning Resource and Service Service Delivery Organizational Development Procurement Information and Bureau of Management Communications Education National Educators FIELD Service Technology Service Assessment Academy of the OPERATIONS Philippines Bureau of Learning External Partnerships Resources Project Management Regional Offices Service Service Disaster Risk Schools Division Offices Reduction and Management Service Schools and Learning Centers 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 nation al 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. ix 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. 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. x 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 NATIONAL Department of Budget and Management Department of Education LEVEL (DBM) (DepEd) Internal revenue Operations Operations In-kind GASTPE allotment budget budget transfers (Textbooks) REGIONAL LEVEL DBM Regional DepEd Regional Offices Offices PROVINCIAL/ City/municipality Local government unit DepEd Schools DIVISION own source Division Offices LEVEL revenue Province City/municipality SCHOOL Own source Private Schools Public Elementary Public Secondary LEVEL revenue 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 f rom the national budget, as well as the DepEd-approved multi-year school improvement plans. xi 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. xii 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. xiii 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. 1 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 30,000 26,162 25,000 22,147 4,066 2,894 20,000 In thousands 13,922 13,473 15,000 1,134 1,207 22,096 10,000 7,778 19,253 6,755 1,366 12,788 12,266 1,340 5,000 2,644 2,267 1,470 6,412 244 5,415 - 1,249 420 2,023 1,395 - 1,050 2009 2017 2009 2017 2009 2017 2009 2017 2009 2017 Kindergarten Elementary JHS SHS Total Public Private 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 12Itis 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 recen tly. 13PSA, Labor Force Survey 2009 and 2017. 2 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 120% 100% 80% 60% 40% 20% 0% 2010 2011 2012 2013 2014 2015 2016 2017 2009 2010 2011 2012 2013 2014 2015 2016 2017 2009 2010 2011 2012 2013 2014 2015 2016 2017 2016 2017 Kindergarten Elementary JHS SHS GER NER Source: DepEd EBEIS. 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. 3 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). 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). 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. 4 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 76,951 80,000 70,000 62,435 22,766 60,000 49,593 50,483 51,104 49,140 49,210 15,831 50,000 10,450 10,562 10,936 11,680 12,191 40,000 30,000 54,185 46,604 20,000 38,690 38,648 38,657 38,803 38,913 13,295 13,408 13,574 14,217 14,520 10,557 11,327 10,000 5,381 5,432 5,492 5,935 5,966 4,373 4,609 7,914 7,976 8,082 8,282 8,554 6,184 6,718 - 2013 2014 2015 2016 2017 2013 2014 2015 2016 2017 2016 2017 2013 2017 Elementary Public JHS SHS Total Source: DepEd EBEIS. Figure 6: Number of Teachers and Teacher Ratios, SY 2009-2010 to SY 2017-2018 500,000 45.00 40.00 Pupil-/Student-Teacher Ratio 400,000 35.00 30.00 300,000 Numberof Teachers 25.00 20.00 200,000 15.00 100,000 10.00 5.00 - - 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 Source: DepEd EBEIS. 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. 5 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 100% 92.4% 10% 7.6% 80% 73.5% 8% 84.3% 72.2% 60% 5.2% 6% 6.3% 40% 4% 20% 2% 1.6% 0% 0% 2009 2010 2011 2012 2013 2014 2015 2016 2017 Elementary Completion Secondary Completion Elementary Dropout Secondary Dropout Source: DepEd EBEIS. 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. 6 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 3,000,000 120% 100.0% 103.1% 96.4% 93.5% 90.4% 92.9% 2,500,000 88.7% 100% 83.8% 73.0% 2,000,000 66.5% 80% 1,500,000 60% 1,000,000 40% 500,000 20% - 0% (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 Source: PER Team’s computations using APIS data for various years 7 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 budg et 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). 8 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 100% 92.4% 80% 73.5% 84.3% 72.2% 60% 2009 2010 2011 2012 2013 2014 2015 2016 2017 Elementary Secondary (JHS) Source: DepEd EBEIS. 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. 20 Both 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. 21 PSA, APIS 2017. 22 Including 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). 9 Figure 10: Transition Rates by Level, SY 2011-2012 to SY 2017-2018 100% 99.7% 98.1% 96.6% 95% 93.1% 91.1% 90% 90.2% 85% 2011 2012 2013 2014 2015 2016 2017 Primary to Intermediate Elementary to JHS JHS to SHS Note: Transition from Primary to Intermediate corresponds to the transition from Grade 4 to Grade 5. Source: DepEd EBEIS. 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 th e 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. 10 Figure 11: Pre-Primary Enrollment Rates in East Asia, 2017 100% 80% 60% 40% 20% 0% GER NER 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 Elementary Secondary 100% 100% 80% 80% 60% 60% 40% 40% 20% 20% 0% 0% NER Completion Rate NER Completion Rate 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. 11 Figure 13: GER and Per Capita Income in East Asia, 2017 130% 120% Lao PDR Thailand Cambodia Philippines Malaysia 110% Indonesia 100% Vietnam Indonesia Thailand 90% Vietnam Philippines Malaysia 80% Lao PDR 70% Cambodia 60% 0 5,000 10,000 15,000 20,000 25,000 30,000 Elementary Secondary 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. 12 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 100 2008-2009 2009-2010 2010-2011 75 2011-2012 2012-2013 2013-2014 2014-2015 50 2015-2016 Superior (76-100%) Upper Average (51-75%) 25 Lower Average (26-50%) 0 Filipino Mathematics English Science HEKASI Overall Source: DepEd Bureau of Education Assessment. Figure 15: Grade 10 NAT Mean Percentage Scores, SY 2008-2009 to SY 2014-2015 100 2008-2009 2009-2010 2010-2011 75 2011-2012 2012-2013 50 2013-2014 2014-2015 Superior (76-100%) 25 Upper Average (51-75%) Lower Average (26-50%) 0 Filipino Araling Mathematics Science English Critical Thinking Overall Panlipunan Source: DepEd Bureau of Education Assessment. 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). 13 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. Figure 16: Grade 6 and Grade 10 NAT Mean Percentage Scores, SY 2016-2017 100 Problem Solving Information Literacy 75 Critical Thinking 50 Highly Proficient (90-100%) 25 Proficient (75-89%) 0 Nearly Proficient (50-74%) Lowly Proficient (25- 49%) Grade 6 Grade 10 Source: DepEd Bureau of Education Assessment. 14 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. Source: DepEd Bureau of Education Assessment. 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. 15 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 1,200 No level Elementary level High school level Tertiary level 1,000 Daily pay (PhP) 800 600 400 200 0 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 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 19.2% 16.9% 16.4% 15.8% 8.0% 7.6% 7.2% 6.1% 3.2% 2.5% 2.3% 1.6% 2003 2008 2013 2018 2003 2008 2013 2018 2003 2008 2013 2018 Elementary level High school level Tertiary level 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. 16 Figure 19: Rate of Private Returns to Different Levels of Education, by Gender 17.9% 17.6% 15.0% 14.7% 11.6% 11.0% 6.8% 5.1% 3.3% 2.9% 1.7% 1.2% 2003 2018 2003 2018 2003 2018 Elementary level High school level Tertiary level Male Female 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 100 80 60 40 20 0 1998 2018 1998 2018 Male Female No level Elementary level High School level Tertiary level Source: LFS for various years. PER team calculations. 17 Figure 21: Socioemotional Skills and Labor Income Extraversion Openness Socio-emotional skills Decision-making Conscientiousness Grit Agreeableness Emotional stability Cognitive Numeracy skills Reading Education Years of education (with SE skills) Years of education (alone) 0 2 4 6 8 10 12 % return 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). 18 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 X VII III IV-A XII XI VI II V IX CARAGA VIII IV-B I CAR NCR ARMM 0% 20% 40% 60% 80% 100% 120% 2010-2011 NER 2010-2011 GER 2017-2018 NER 2017-2018 GER Source: DepEd EBEIS. 19 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 X VII III IV-A XII XI VI II V IX CARAGA VIII IV-B I CAR NCR ARMM 0% 20% 40% 60% 80% 100% 120% 2009-2010 NER 2009-2010 GER 2017-2018 NER 2017-2018 GER Source: DepEd EBEIS. 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. 20 Figure 24: JHS Enrollment Rates, by Region, Figure 25: SHS Enrollment Rates, by Region, SY 2009-2010 and SY 2017-2018 SY 2016-2017 and SY 2017-2018 NCR NCR VII I I IV-A IV-A III VI VII III VI V II CAR CAR XI V CARAGA IV-B VIII VIII II CARAGA IV-B X XII XI IX XII X IX ARMM ARMM 0% 20% 40% 60% 80% 100% 120% 0% 20% 40% 60% 80% 100% 120% 2009-2010 NER 2009-2010 GER 2017-2018 NER 2017-2018 GER 2016-2017 NER 2016-2017 GER 2017-2018 NER 2017-2018 GER Source: DepEd EBEIS. Source: DepEd EBEIS. 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. 21 Figure 26: Elementary Completion and Cohort Survival Figure 27: JHS Completion and Cohort Survival Rates, Rates, by Region, SY 2009-2010 and SY 2017-2018 by Region, SY 2009-2010 and SY 2017-2018 IV-A IV-A I NCR III I NCR III VI VI II II V VII VIII IV-B VII V IV-B CARAGA XII CAR X XII XII XII CAR VIII CARAGA X IX IX ARMM ARMM 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% 2009-2010 Completion Rate 2017-2018 Completion Rate 2009-2010 Completion Rate 2017-2018 Completion Rate 2009-2010 CSR 2017-2018 CSR 2009-2010 CSR 2017-2018 CSR Source: DepEd EBEIS. Source: DepEd EBEIS. 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. 22 Figure 28: Correlations Between Poverty Incidence and Various Education Indicators, by Region, 2015 Elementary JHS 120 120 r = -0.12 100 100 r = -0.72* r = -0.55* r = -0.90* 80 r = -0.66* 80 Percentage Percentage r = -0.60* 60 60 r = -0.72* r = -0.80* 40 40 20 20 0 0 0 10 20 30 40 50 60 0 10 20 30 40 50 60 Poverty Incidence Poverty Incidence GER NER Completion Rate Cohort Survival Rate GER NER Completion Rate Cohort Survival Rate 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 160% 140% 120% 100% 80% 60% 40% 20% 0% Quintile 1 (Poorest) Quintile 2 Quintile 3 Quintile 4 Quintile 5 (Richest) Kindergarten GER Elementary GER Kindergarten NER Elementary NER JHS GER SHS GER JHS NER SHS NER 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 23 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 120% 100% 80% 60% 40% 20% 0% 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 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. 24 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 141% 160% 129% 124% 128% 126% 1,000,000 120% 117% 100% 120% 800,000 600,000 100% 101% 80% 87% 84% 400,000 71% 74% 40% 200,000 47% 41% 0 0% 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 SHS Students in school (Quintile 1) Students in school (Quintile 5) CSR (Quintile 1) CSR (Quintile 5) 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. 25 Figure 32: Gross and Net Enrollment Rates, by Gender, SY 2000-2010 to SY 2017-2018 120% 100% 80% 60% 40% 20% 0% 2010 2011 2012 2013 2014 2015 2016 2017 2009 2010 2011 2012 2013 2014 2015 2016 2017 2009 2010 2011 2012 2013 2014 2015 2016 2017 2016 2017 Kindergarten Elementary JHS SHS Male GER Male NER Female GER Female NER Source: DepEd EBEIS. 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 100% 80% 60% 40% 20% 0% 2009 2010 2011 2012 2013 2014 2015 2016 2017 2009 2010 2011 2012 2013 2014 2015 2016 2017 Elementary JHS Male CSR Male Completion Rate Female CSR Female Completion Rate Source: DepEd EBEIS. 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 26 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 25% 9% 20% 5% 15% 5% 6% 10% 3% 16% 17% 4% 12% 5% 1% 10% 2% 7% 1% 7% 4% 3% 1% 4% 4% 1% 2% 0% 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 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Total (Poorest) (Richest) Males Females 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. 27 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. 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. 28 Figure 35: School Sizes, by Region, SY 2017-2018 NCR IV-A III XI XII V VII VI I X ARMM IV-B CARAGA IX II VIII CAR 0 500 1,000 1,500 2,000 2,500 3,000 3,500 4,000 Median School Size Average School Size Number of Schools Source: DepEd EBEIS. 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 l evel. 39 Across 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. 29 Figure 36: Pupil- and Student-Teacher Ratios, by Region, SY 2009-2010 and SY 2017-2018 Elementary JHS ARMM ARMM IV-A XI NCR IX III IV-A XII X XI V VII XII X VI IV-B IV-B V III VI VIII IX CARAGA CARAGA I I NCR II VII VIII II CAR CAR 0.00 10.00 20.00 30.00 40.00 50.00 60.00 0.00 10.00 20.00 30.00 40.00 50.00 60.00 2009-2010 PTR 2017-2018 PTR 2009-2010 STR 2017-2018 STR Source: DepEd EBEIS. 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. 30 Figure 37: Pupil- and Student-Classroom Ratios, by Region, SY 2011-2012 and SY 2016-2017 Elementary JHS NCR NCR IV-A IV-A ARMM ARMM XI XI X VII XII III III IX VII V CARAGA VIII IX X V IV-B IV-B VI VI CARAGA I XII VIII I II CAR II CAR 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 2011-2012 PCR 2016-2017 PCR 2011-2012 SCR 2016-2017 SCR Source: DepEd EBEIS. 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�. 31 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 II I CAR VIII III VII CARAGA VI NCR V IV-A IV-B X IX XII XI ARMM 0% 10% 20% 30% 40% 50% 60% 70% Elementary JHS SHS Source: DepEd EBEIS. 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, 42 ADB & World Bank, 1999, as cited in Maligalig et al., 2010. 43 NAT 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. 32 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 Grade 6 Grade 10 CARAGA CARAGA VIII IX XII VIII IV-B VI IX VII VI XII XI IV-B III XI II X X CAR VII II I NCR CAR III V V ARMM IV-A NCR I IV-A ARMM 0% 20% 40% 60% 80% 100% 0% 20% 40% 60% 80% 100% 2008-2009 NAT MPS 2014-2015 NAT MPS 2008-2009 NAT MPS 2014-2015 NAT MPS 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). 33 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). 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. 44 e.g., David & Albert, 2015; Albert & Raymundo, 2016. 34 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 15.6 350,000 14.7 16 14.2 14.2 14.2 327,200 13.9 13.4 13.2 13.3 LGU Spending 300,000 14 PHP million, in 2000 prices 12 NG Spending (DepEd 250,000 + DPWH BEFF) 10 Percentage 200,000 Total Education 8 Spending as % of 150,000 GDP 127,187 6 Basic Education 4.4 Spending (NG +LGU) 100,000 3.3 3.6 as % of GDP 2.7 2.7 3.0 2.8 4 2.4 2.3 NG + LGU Spending 3.8 as % of Total Govt 50,000 3.1 2 2.7 2.9 Spending 2.4 2.3 2.4 2.4 2.4 - 0 2009 2010 2011 2012 2013 2014 2015 2016 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. 35 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 6 5.7 5.3 4.8 5 4.5 4.3 4.3 4.3 4.1 4.1 4 3.6 2.9 3 Percentage 2.2 1.9 2 1 0 Cambodia Myanmar Lao PDR Indonesia Mongolia Thailand (i) Philippines Upper Lower Middle Malaysia High Vietnam (i) (ii) (iii) middle middle income (iv) income income income countries countries countries countries (ii) (iii) (iii) (ii) 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. Sources: DepEd SAAODBs; obligations data for various agencies from DBM Budget and Management Bureaus; DOF-BLGF LGU Fiscal Statement of Receipts and Expenditures 36 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. Sources: DepEd SAAODBs; obligations data for various agencies from DBM Budget and Management Bureaus; 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 100% 3.5% 0.7% 1.4% 1.3% 1.2% 80% 69.7% 69.9% 69.7% 69.1% 66.1% 64.5% 63.3% 68.2% 69.9% 60% 40% 20% 35.5% 30.2% 30.0% 30.2% 30.7% 29.4% 32.5% 34.2% 28.3% 0% 2009 2010 2011 2012 2013 2014 2015 2016 2017 Secondary Elementary Kindergarten 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 37 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 Elementary Secondary 100 r = -0.12 100 r = 0.21* r = -0.22 r = -0.22* r = 0.19* 80 80 r = 0.47* Percentage 60 Percentage 60 40 40 r = -0.71* 20 r = -0.95* 20 0 0 5,000 6,000 7,000 8,000 9,000 10,000 11,000 5,000 6,000 7,000 8,000 9,000 10,000 11,000 Real Per Pupil Spending by Region, in 2000 prices Real Per Student Spending by Region, in 2000 prices NER Completion Rate Cohort Survival Rate PTR NER Completion Rate Cohort Survival Rate STR 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. 38 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 Subsidy to Local Government Units 8.0 8.4 8.3 6.8 6.7 7.5 6.9 6.7 6.0 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 Subsidy to Local Government Units 6.1 6.4 6.3 5.1 5.1 5.7 5.2 5.1 4.5 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. 39 Figure 44: DepEd Real Spending and Budget Utilization Rate, 2009-2017 96.4% 94.3% 92.9% 91.8% 94.0% 97.1% 89.6% 87.7% 89.6% 100% 600,000 500,000 80% Appropriations 400,000 60% Allotments 300,000 40% Obligations 200,000 Utilization Rate 20% 100,000 - 0% 2009 2010 2011 2012 2013 2014 2015 2016 2017 Note: In 2000 prices, in million PhP. Data include current and continuing (regular and automatic) appropriations. Source: DepEd SAAODBs for various years. Figure 45: Shares of Expense Classes in DepEd Appropriations and Obligations, 2009-2017 Appropriations Obligations 2.2% 1.5% 3.7% 5.6% 6.2% 5.3% 4.8% 5.7% 7.1% 7.7% 9.8% 8.2% 8.2% 10.6% 9.5% 9.5% 17.3% 9.8% 10.3% 20.1% 9.7% 14.3% 22.8% 23.9% 13.4% 13.4% 12.7% 9.7% 13.3% 13.1% 12.6% 20.1% 11.6% 12.2% 13.7% 14.0% 88.3% 89.0% 85.3% 84.6% 86.0% 80.2% 80.4% 81.4% 82.1% 79.6% 79.6% 77.1% 76.8% 71.1% 71.6% 67.7% 63.5% 62.1% 2009 2010 2011 2012 2013 2014 2015 2016 2017 2009 2010 2011 2012 2013 2014 2015 2016 2017 Personnel Services MOOE Capital Outlay Personnel Services MOOE Capital Outlay 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. Source: DepEd SAAODBs for various years. 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 fun ds 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. 40 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. 41 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 600,000 577,924 500,000 400,000 NG Nominal NG Real 300,000 316,844 LGU Nominal 200,000 178,847 LGU Real 100,000 118,035 13,867 18,889 - 9,152 10,356 2009 2010 2011 2012 2013 2014 2015 2016 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 30,000.00 26,154.19 25,000.00 20,000.00 NG Nominal NG Real 15,000.00 LGU Nominal 9,288.97 14,375.13 10,000.00 LGU Real 5,000.00 6,361.48 720.24 854.82 475.34 - 468.65 2009 2010 2011 2012 2013 2014 2015 2016 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. Sources: DepEd SAAODBs; DPWH data from DBM Budget and Management Bureau – A; DOF-BLGF LGU Fiscal Data Statement of Receipts and Expenditures. 42 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 In current prices In constant 2000 prices Regions 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. Sources: DepEd SAAODBs; DPWH data from DBM Budget and Management Bureau – A; DOF-BLGF LGU Fiscal Data Statement of Receipts and Expenditures. 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. 43 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. 44 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. Source: PER team’s computations using FIES 2012 and 2015. 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 8% 6% 4% 2% 0% Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Overall (Poorest) (Richest) 2012 2015 Note: Figures only include households with school-age children (ages 5-17) and reporting education expenses. Source: PER team’s computations using FIES 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% 45 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% Note: Figures only include households with school-age children (ages 5-17) and reporting education expenses. Source: PER team’s computations using FIES 2012 and 2015. 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. 46 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). 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 progra m’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). 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, 47 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 48 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. 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. 49 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. 50 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. 51 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. 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. 52 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. 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. 53 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: 54 • 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 55 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. Definitions and Methods 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 The legislative authorization that contains the new appropriations authorized by Congress in terms of specific amounts for salaries, wages and other personnel benefits, General Appropriations Act 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. An authorization for incurring obligations during a specified budget year as listed in the New General Appropriations Act. An authorization to support obligations for a specific purpose or project, even when these Appropriations Continuing obligations are incurred beyond the budget year. One-time legislative authorization to provide funds for a specified purpose and is made Automatic automatically available and does not require periodic action by the Congress. 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 Allotments 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. 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 Obligations may only be incurred in the performance of activities authorized in appropriations acts within the limit of the allotment released by the DBM. The settlement/liquidation/payment of an obligation incurred in the current or prior Disbursements years, involving cash or non-cash transactions and covered by disbursement authorities. 56 The payment of salaries, wages and other compensation of permanent, temporary, Personnel Services contractual, and casual employees of the government. Maintenance and Support to the operations of government agencies such as expenses for supplies and Other Operating materials, transportation and travel, and utilities (e.g. water, electricity) and repairs. Expense Expenses Class The management supervision/trusteeship fees, interest expenses, guarantee fees, bank Financial Expenses charges, commitment fees and other financial charges incurred in owning or borrowing an asset property. The purchase of goods and services, the benefits of which extend beyond the fiscal year Capital Outlay 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 57 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. Definitions and Methods 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. 58 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. Definitions and Methods 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 59 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. 60 Annex 2 – Reference Tables for Chapters 1 and 2 Table 10: Internal Efficiency Indicators, by Level, SY 2009-2010 to SY 2017-2018 Cohort Survival Rate (%) Completion Rate (%) Dropout Rate (%) School Year 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 Kindergarten GER (%) Kindergarten NER (%) School Year 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 Elementary GER (%) Elementary NER (%) School Year Male Female Total Male Female Total 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 JHS GER (%) JHS NER (%) School Year Male Female Total Male Female Total 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 61 Table 14: SHS GER and NER, by Gender, SY 2016-2017 to SY 2017-2018 SHS GER (%) SHS NER (%) School Year Male Female Total Male Female Total 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 2017 Region 2009 2010 2011 2012 2013 2014 2015 2016 Problem Information Critical Solving Literacy 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 2017 Region 2009 2010 2011 2012 2013 2014 2015 Problem Information Critical Solving Literacy 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. 62 Table 17: Achievement Score Analysis Results Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 With Region VARIABLES With With Division With Region With Division Dummies and Core Interaction Dummies and Dummies Dummies Interaction Terms Interaction Terms 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 8.214*** 7.783*** 5.651*** 8.544*** 8.094*** 6.138*** Teachers I-III (12.72) (12.85) (7.408) (12.43) (12.56) (7.270) Ratio: Non-DepEd Teachers -1.659*** -0.106 -0.801 -1.942*** -0.124 -0.791 to Total Teachers (-4.542) (-0.306) (-1.656) (-5.009) (-0.338) (-1.524) School Size: 154-248 3.599*** 3.656*** 3.270*** 3.602*** 3.620*** 3.208*** students (16.89) (18.21) (12.99) (15.99) (17.08) (12.06) School Size: 249-439 3.559*** 4.140*** 4.038*** 3.610*** 4.183*** 4.063*** students (16.11) (19.64) (12.41) (15.35) (18.70) (11.17) School Size: Above 439 1.909*** 2.739*** 3.345*** 2.375*** 3.190*** 3.371*** students (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 -0.0368** -0.0680*** 0.0468** Ratio (-2.013) (-3.938) (2.141) Urban School*Pupil- 0.0279* 0.0242* -0.00431 Classroom Ratio (1.839) (1.684) (-0.255) Urban School*Multiple -1.395 -2.433*** 1.779 Shifts (-1.411) (-2.623) (1.201) Urban School*Ratio: Master -2.741 -2.891 -4.155** Teachers to Teachers I-III (-1.376) (-1.557) (-2.151) Urban School*Ratio: Non- DepEd Teachers to Total 2.304** -0.344 0.0628 Teachers (1.984) (-0.318) (0.0485) Urban School & School Size: -0.217 0.107 0.478 154-248 students (-0.314) (0.166) (0.834) Urban School & School Size: -0.760 -0.586 -0.321 249-439 students (-1.101) (-0.911) (-0.566) 63 Urban School & School Size: -2.470*** -2.194*** -0.199 Above 439 students (-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 64 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 178,847 191,118 218,817 240,238 279,474 273,300 308,136 369,435 456,278 Education 1.2 DPWH Basic Education Facilities - - - - 11,556 11,306 57,066 60,613 121,646 Fund 2.0 State Universities and - - 27,827 26,920 32,177 38,648 47,172 53,089 63,380 Colleges 3.0 Commission on Higher - - 1,141 670 3,022 5,552 7,036 6,662 20,677 Education 4.0 Technical Education and Skills Development - 2,361 3,459 4,019 3,642 5,019 5,119 6,421 7,808 Authority 5.0 Department of Science and 1,496 1,148 1,272 2,089 2,321 2,653 3,394 4,178 6,798 Technology Local Government Units' 13,867 13,526 14,435 16,232 16,654 15,976 15,984 16,468 18,889 Spending 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 118,035 121,030 133,214 143,426 163,512 155,002 175,786 207,245 250,152 Education 1.2 DPWH Basic Education Facilities - - - - 6,761 6,412 32,555 34,003 66,692 Fund 2.0 State Universities and - - 16,941 16,072 18,826 21,919 26,911 29,782 34,748 Colleges 3.0 Commission on Higher - - 695 400 1,768 3,149 4,014 3,737 11,336 Education 4.0 Technical Education and Skills Development - 1,495 2,106 2,399 2,131 2,847 2,920 3,602 4,281 Authority 5.0 Department of Science and 987 727 774 1,247 1,358 1,505 1,936 2,344 3,727 Technology Local Government Units' 9,152 8,566 8,788 9,691 9,744 9,061 9,119 9,238 10,356 Spending 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 65 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 2.23 2.12 2.25 2.27 2.42 2.16 2.31 2.55 2.89 Education 1.2 DPWH Basic Education Facilities - - - - 0.10 0.09 0.43 0.42 0.77 Fund 2.0 State Universities and - - 0.29 0.25 0.28 0.31 0.35 0.37 0.40 Colleges 3.0 Commission on Higher - - 0.01 0.01 0.03 0.04 0.05 0.05 0.13 Education 4.0 Technical Education and Skills Development - 0.03 0.04 0.04 0.03 0.04 0.04 0.04 0.05 Authority 5.0 Department of Science and 0.02 0.01 0.01 0.02 0.02 0.02 0.03 0.03 0.04 Technology Local Government Units' 2.25 2.16 2.60 2.59 2.88 2.66 3.21 3.46 4.28 Spending 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, Net of Net Lending and Interest Payments, 2009-2017 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 15.55 16.34 17.06 16.14 16.85 16.22 14.70 15.63 15.19 Education 1.2 DPWH Basic Education Facilities - - - - 0.70 0.67 2.72 2.57 4.05 Fund 2.0 State Universities and - - 2.17 1.81 1.94 2.29 2.25 2.25 2.11 Colleges 3.0 Commission on Higher - - 0.09 0.05 0.18 0.33 0.34 0.28 0.69 Education 4.0 Technical Education and Skills Development - 0.20 0.27 0.27 0.22 0.30 0.24 0.27 0.26 Authority 5.0 Department of Science and 0.13 0.10 0.10 0.14 0.14 0.16 0.16 0.18 0.23 Technology Local Government Units' 1.21 1.16 1.13 1.09 1.00 0.95 0.76 0.70 0.63 Spending 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 66 Table 23: Sectoral Distribution of National Government Spending, Obligations Basis, Net of Net Lending and Interest Payments, 2009-2017 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 8.33 8.60 5.45 7.09 7.22 6.42 5.91 5.31 4.75 Natural Resources 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 1.97 1.58 1.24 1.52 1.63 1.52 2.24 2.42 2.77 Flood Control Communications, Roads, and Other 14.53 12.52 10.91 10.63 12.50 12.00 17.04 18.52 20.57 Transportation Other Economic Services 0.73 1.12 1.16 1.13 0.92 0.56 0.82 0.88 1.25 Subsidy to Local Government Units 7.61 7.95 7.83 6.43 6.38 7.10 6.51 6.35 5.67 SOCIAL SERVICES 35.80 35.56 42.47 39.78 42.94 45.39 42.31 41.16 40.32 Education, Culture, and Manpower 18.15 21.82 19.83 18.77 19.72 19.34 17.91 18.80 18.62 Development Health 2.04 2.65 3.16 3.52 3.43 5.05 5.01 5.30 5.34 Social Security, Welfare and 6.57 4.17 9.03 9.75 10.69 11.82 11.04 9.42 8.96 Employment Land Distribution (CARP) 0.11 0.34 0.31 0.00 0.30 - - - - Housing and Community 0.73 0.61 1.74 0.80 1.94 1.58 1.39 0.85 1.31 Development Other Social Services 0.16 0.12 0.12 0.14 0.11 0.10 0.09 0.08 0.09 Subsidy to Local Government Units 8.04 8.41 8.28 6.79 6.74 7.50 6.88 6.71 6.00 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 Subsidy to Local Government Units 6.09 6.36 6.26 5.14 5.10 5.68 5.21 5.08 4.54 67 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 In current prices, in million PhP 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 + 186,542 202,614 235,606 261,672 316,322 347,026 400,573 507,208 608,507 DPWH BEFF) 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 A. National Government 187,311 206,635 272,513 301,847 357,483 383,499 490,627 564,419 682,447 Basic Education (DepEd + 185,584 202,614 235,606 261,672 309,971 322,162 419,481 485,212 579,383 DPWH BEFF) B. LGU 13,867 13,526 14,435 16,232 16,654 15,976 15,984 16,468 18,889 C. Total Education Spending 201,178 220,161 286,948 318,079 374,137 399,475 506,611 580,887 701,336 III. Obligations A. National Government 180,343 194,627 252,516 273,936 332,192 336,478 427,923 500,398 676,587 Basic Education (DepEd + 178,847 191,118 218,817 240,238 291,030 284,606 365,202 430,048 577,924 DPWH BEFF) B. LGU 13,867 13,526 14,435 16,232 16,654 15,976 15,984 16,468 18,889 C. Total Education Spending 194,210 208,153 266,951 290,168 348,846 352,454 443,907 516,866 695,476 In 2000 prices, in million PhP I. Appropriations A. National Government 126,457 130,754 165,906 180,322 212,868 232,459 269,106 330,147 392,237 Basic Education (DepEd + 123,114 128,310 143,435 156,222 185,070 196,816 228,520 284,533 333,611 DPWH BEFF) B. LGU 9,152 8,566 8,788 9,691 9,744 9,061 9,119 9,238 10,356 68 C. Total Education Spending 135,609 139,319 174,694 190,013 222,612 241,520 278,225 339,385 402,593 II. Allotments A. National Government 123,621 130,856 165,903 180,207 209,152 217,502 279,894 316,627 374,149 Basic Education (DepEd + 122,482 128,310 143,435 156,222 181,354 182,714 239,307 272,193 317,644 DPWH BEFF) B. LGU 9,152 8,566 8,788 9,691 9,744 9,061 9,119 9,238 10,356 C. Total Education Spending 132,773 139,422 174,691 189,898 218,896 226,563 289,013 325,865 384,504 III. Obligations A. National Government 119,023 123,252 153,729 163,544 194,355 190,834 244,123 280,712 370,936 Basic Education (DepEd + 118,035 121,030 133,214 143,426 170,273 161,414 208,342 241,248 316,844 DPWH BEFF) B. LGU 9,152 8,566 8,788 9,691 9,744 9,061 9,119 9,238 10,356 C. Total Education Spending 128,174 131,817 162,517 173,235 204,099 199,895 253,241 289,951 381,292 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 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 136.24 177.62 251.70 565.56 11,761.04 12,326.59 Region 2 - Cagayan Valley 149.82 29.38 86.78 265.98 11,794.55 12,060.52 Region 3 - Central Luzon 236.42 142.38 189.72 568.52 9,188.50 9,757.01 Region 4A - CALABARZON 310.10 344.74 184.67 839.51 8,233.30 9,072.81 Region 4B - MIMAROPA 111.36 76.71 138.95 327.02 9,554.88 9,881.90 Region 5 - Bicol Region 66.01 78.20 175.19 319.41 9,449.99 9,769.39 Region 6 - Western Visayas 87.82 251.53 100.59 439.94 10,807.83 11,247.77 69 Region 7 - Central Visayas 134.09 277.26 56.34 467.69 8,893.54 9,361.23 Region 8 - Eastern Visayas 55.94 61.66 39.42 157.02 9,928.77 10,085.80 Region 9 - Zamboanga Peninsula 43.51 83.91 34.93 162.36 9,685.13 9,847.49 Region 10 - Northern Mindanao 88.27 255.84 51.25 395.36 9,645.16 10,040.52 Region 11 - Davao Region 75.76 305.10 54.45 435.31 9,001.69 9,437.00 Region 12 - Central Mindanao 117.38 148.07 90.12 355.56 8,884.46 9,240.02 CARAGA 77.58 80.17 53.70 211.45 10,008.76 10,220.20 Cordillera Administrative Region 114.42 182.17 91.06 387.65 13,826.37 14,214.02 National Capital Region 4.37 2,994.37 - 2,998.73 8,771.47 11,770.20 Total 121.51 459.79 102.90 684.20 9,108.59 9,792.79 2011 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 147.44 166.05 352.96 666.46 13,315.70 13,982.17 Region 2 - Cagayan Valley 177.45 88.28 119.56 385.29 12,639.64 13,024.93 Region 3 - Central Luzon 265.06 163.19 243.11 671.36 10,577.03 11,248.39 Region 4A - CALABARZON 315.13 309.68 219.05 843.85 9,005.15 9,849.00 Region 4B - MIMAROPA 106.14 64.02 122.64 292.79 10,541.59 10,834.38 Region 5 - Bicol Region 67.78 95.28 194.38 357.43 10,486.22 10,843.65 Region 6 - Western Visayas 99.35 258.32 91.60 449.27 11,775.64 12,224.91 Region 7 - Central Visayas 133.28 296.14 71.36 500.79 9,916.53 10,417.32 Region 8 - Eastern Visayas 55.68 65.87 56.58 178.13 11,480.73 11,658.87 Region 9 - Zamboanga Peninsula 47.79 94.12 63.44 205.35 10,875.62 11,080.97 Region 10 - Northern Mindanao 89.16 178.23 70.58 337.96 10,380.68 10,718.64 Region 11 - Davao Region 81.56 331.47 103.34 516.37 9,909.96 10,426.32 Region 12 - Central Mindanao 131.81 124.92 71.86 328.59 10,058.55 10,387.14 CARAGA 97.33 88.91 49.95 236.19 11,376.57 11,612.76 Cordillera Administrative Region 120.17 228.24 85.42 433.83 15,653.74 16,087.57 National Capital Region 5.01 2,919.34 - 2,924.35 9,851.38 12,775.73 Total 129.30 451.73 124.01 705.04 10,171.52 10,876.56 2012 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 215.77 148.84 357.45 722.05 14,002.06 14,724.11 Region 2 - Cagayan Valley 119.78 47.08 122.84 289.70 14,734.21 15,023.90 Region 3 - Central Luzon 277.51 205.60 214.15 697.27 11,399.83 12,097.10 Region 4A - CALABARZON 337.29 374.85 234.69 946.83 9,826.33 10,773.16 Region 4B - MIMAROPA 140.23 64.61 128.53 333.37 11,800.58 12,133.95 Region 5 - Bicol Region 80.14 128.33 101.20 309.67 11,801.97 12,111.64 Region 6 - Western Visayas 102.69 263.85 116.14 482.67 12,842.86 13,325.53 Region 7 - Central Visayas 154.58 339.81 87.10 581.49 10,520.30 11,101.79 Region 8 - Eastern Visayas 54.87 79.65 56.66 191.18 12,566.05 12,757.22 Region 9 - Zamboanga Peninsula 59.58 100.88 57.87 218.34 11,968.77 12,187.10 Region 10 - Northern Mindanao 114.47 292.63 82.29 489.39 11,719.27 12,208.66 Region 11 - Davao Region 83.17 343.62 81.67 508.46 10,771.97 11,280.42 70 Region 12 - Central Mindanao 133.65 159.39 109.27 402.30 10,597.45 10,999.75 CARAGA 81.59 115.87 53.66 251.12 12,580.63 12,831.75 Cordillera Administrative Region 129.72 267.10 94.31 491.13 16,937.90 17,429.03 National Capital Region 4.39 3,346.81 - 3,351.20 10,789.03 14,140.23 Total 141.42 521.68 122.01 785.11 11,153.64 11,938.75 2013 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 185.01 128.34 422.28 735.63 15,554.47 16,290.10 Region 2 - Cagayan Valley 142.58 46.36 118.63 307.58 16,142.69 16,450.26 Region 3 - Central Luzon 255.81 234.97 217.75 708.52 12,220.25 12,928.77 Region 4A - CALABARZON 277.38 491.31 183.80 952.49 10,853.75 11,806.24 Region 4B - MIMAROPA 107.74 62.62 108.56 278.92 14,078.91 14,357.82 Region 5 - Bicol Region 80.74 151.01 83.59 315.34 12,644.12 12,959.46 Region 6 - Western Visayas 109.98 280.48 106.04 496.50 14,462.57 14,959.07 Region 7 - Central Visayas 93.11 297.93 70.58 461.61 12,060.69 12,522.30 Region 8 - Eastern Visayas 38.87 74.78 38.82 152.47 14,002.33 14,154.80 Region 9 - Zamboanga Peninsula 52.52 85.35 56.50 194.37 14,200.73 14,395.10 Region 10 - Northern Mindanao 118.47 352.02 60.61 531.10 12,878.54 13,409.64 Region 11 - Davao Region 66.74 331.76 78.34 476.84 12,290.39 12,767.24 Region 12 - Central Mindanao 130.44 142.83 94.98 368.25 12,724.61 13,092.86 CARAGA 84.18 116.04 67.19 267.42 14,045.48 14,312.90 Cordillera Administrative Region 136.32 317.55 118.09 571.96 18,371.47 18,943.43 National Capital Region 4.14 3,535.06 - 3,539.20 11,411.09 14,950.29 Total 124.54 559.45 113.45 797.45 12,419.70 13,217.15 2014 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 171.32 65.79 359.80 596.91 15,732.71 16,329.61 Region 2 - Cagayan Valley 142.60 59.71 89.22 291.53 16,149.40 16,440.93 Region 3 - Central Luzon 245.18 226.74 182.97 654.89 12,728.22 13,383.11 Region 4A - CALABARZON 241.47 447.70 143.23 832.40 10,992.62 11,825.02 Region 4B - MIMAROPA 116.25 83.66 126.10 326.02 13,714.38 14,040.40 Region 5 - Bicol Region 81.69 113.54 61.59 256.83 12,681.45 12,938.27 Region 6 - Western Visayas 113.88 237.01 87.52 438.42 14,452.93 14,891.36 Region 7 - Central Visayas 99.17 250.84 66.54 416.55 12,597.25 13,013.80 Region 8 - Eastern Visayas 46.50 48.62 29.72 124.84 13,869.79 13,994.63 Region 9 - Zamboanga Peninsula 59.40 94.21 58.41 212.02 13,702.82 13,914.84 Region 10 - Northern Mindanao 111.40 192.42 79.85 383.66 13,141.60 13,525.26 Region 11 - Davao Region 79.01 287.05 86.42 452.48 11,690.21 12,142.69 Region 12 - Central Mindanao 160.04 126.35 57.38 343.77 10,647.86 10,991.63 CARAGA 106.22 92.26 70.03 268.51 14,342.90 14,611.40 Cordillera Administrative Region 146.89 177.02 133.55 457.46 18,687.91 19,145.37 National Capital Region 1.31 3,691.01 - 3,692.32 11,426.54 15,118.86 Total 123.40 537.81 98.02 759.23 12,444.23 13,203.46 71 2015 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 183.75 89.41 354.94 628.10 16,693.29 17,321.38 Region 2 - Cagayan Valley 175.09 70.41 86.69 332.20 16,993.30 17,325.50 Region 3 - Central Luzon 294.52 203.80 211.55 709.87 13,253.05 13,962.92 Region 4A - CALABARZON 245.97 484.56 142.03 872.56 11,620.50 12,493.07 Region 4B - MIMAROPA 120.20 95.11 77.08 292.40 14,056.69 14,349.09 Region 5 - Bicol Region 88.89 124.11 72.84 285.84 12,972.95 13,258.79 Region 6 - Western Visayas 136.45 266.80 79.23 482.48 14,601.55 15,084.03 Region 7 - Central Visayas 110.60 245.11 75.41 431.12 13,138.19 13,569.31 Region 8 - Eastern Visayas 59.57 92.52 98.48 250.56 16,077.51 16,328.07 Region 9 - Zamboanga Peninsula 97.26 97.93 81.62 276.81 14,771.67 15,048.48 Region 10 - Northern Mindanao 117.40 243.98 46.74 408.12 13,338.37 13,746.49 Region 11 - Davao Region 89.60 254.86 128.66 473.12 12,033.42 12,506.53 Region 12 - Central Mindanao 173.69 128.48 87.47 389.64 12,858.39 13,248.04 CARAGA 138.16 106.94 73.53 318.63 14,776.63 15,095.26 Cordillera Administrative Region 154.48 211.32 107.69 473.49 19,663.69 20,137.18 National Capital Region 3.26 3,415.71 - 3,418.97 12,096.71 15,515.68 Total 139.97 518.24 106.30 764.52 13,154.37 13,918.89 2016 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 199.30 83.83 377.97 661.10 19,609.88 20,270.98 Region 2 - Cagayan Valley 138.68 115.56 75.78 330.02 19,023.09 19,353.11 Region 3 - Central Luzon 269.00 196.06 180.19 645.24 15,761.82 16,407.06 Region 4A - CALABARZON 196.25 508.31 147.11 851.67 13,899.32 14,750.99 Region 4B - MIMAROPA 130.99 69.50 44.84 245.34 16,536.69 16,782.03 Region 5 - Bicol Region 96.94 123.31 92.85 313.10 16,684.44 16,997.54 Region 6 - Western Visayas 124.34 213.06 102.63 440.03 17,718.06 18,158.09 Region 7 - Central Visayas 150.88 207.67 64.40 422.95 15,169.08 15,592.03 Region 8 - Eastern Visayas 48.90 76.68 59.97 185.55 19,148.94 19,334.49 Region 9 - Zamboanga Peninsula 96.15 145.99 111.16 353.30 17,107.28 17,460.59 Region 10 - Northern Mindanao 101.01 236.45 43.34 380.80 15,977.68 16,358.48 Region 11 - Davao Region 83.58 265.54 87.54 436.66 14,620.27 15,056.93 Region 12 - Central Mindanao 156.29 135.59 93.59 385.46 14,265.80 14,651.26 CARAGA 131.06 94.56 55.02 280.64 18,172.24 18,452.88 Cordillera Administrative Region 123.73 284.48 91.71 499.92 23,302.14 23,802.07 National Capital Region 4.91 3,693.58 - 3,698.49 14,062.33 17,760.82 Total 130.79 536.43 102.38 769.60 15,620.24 16,389.84 2017 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 203.18 91.52 511.23 805.93 21,313.17 22,119.10 Region 2 - Cagayan Valley 129.87 100.33 73.40 303.60 22,055.02 22,358.62 Region 3 - Central Luzon 269.60 196.90 165.22 631.73 17,001.33 17,633.05 72 Region 4A - CALABARZON 225.24 432.35 130.32 787.92 14,997.51 15,785.43 Region 4B - MIMAROPA 144.65 69.58 145.55 359.77 18,624.81 18,984.59 Region 5 - Bicol Region 101.63 111.73 74.07 287.43 17,851.31 18,138.74 Region 6 - Western Visayas 122.14 270.51 138.95 531.60 18,474.33 19,005.94 Region 7 - Central Visayas 117.62 205.65 79.20 402.47 17,694.97 18,097.44 Region 8 - Eastern Visayas 57.22 75.85 49.80 182.87 20,655.93 20,838.80 Region 9 - Zamboanga Peninsula 79.83 150.51 103.01 333.35 18,295.75 18,629.11 Region 10 - Northern Mindanao 145.90 200.25 35.11 381.27 17,328.95 17,710.22 Region 11 - Davao Region 1,104.23 201.14 97.64 1,403.01 15,785.69 17,188.70 Region 12 - Central Mindanao 135.77 104.99 52.84 293.60 17,203.41 17,497.01 CARAGA 149.75 91.09 68.46 309.31 20,209.29 20,518.60 Cordillera Administrative Region 157.67 87.87 94.11 339.64 26,276.00 26,615.65 National Capital Region 3.57 4,088.51 - 4,092.08 15,115.60 19,207.68 Total 63.37 1.45 187.67 252.49 - 252.49 Table 27: Per Pupil Real Spending, by Region, 2009-2017 2009 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 72.55 104.26 163.91 340.71 7,426.58 7,767.29 Region 2 - Cagayan Valley 97.70 62.18 76.86 236.73 6,727.23 6,963.96 Region 3 - Central Luzon 144.54 102.22 132.47 379.23 5,769.12 6,148.35 Region 4A - CALABARZON 220.19 244.97 125.84 591.00 5,035.40 5,626.40 Region 4B - MIMAROPA 77.22 63.57 106.06 246.86 6,034.75 6,281.61 Region 5 - Bicol Region 50.73 75.47 59.86 186.07 5,887.84 6,073.90 Region 6 - Western Visayas 71.26 154.92 54.64 280.82 6,616.09 6,896.92 Region 7 - Central Visayas 61.58 168.04 45.88 275.50 5,440.32 5,715.82 Region 8 - Eastern Visayas 29.09 46.48 43.29 118.85 6,718.62 6,837.47 Region 9 - Zamboanga Peninsula 27.37 444.66 35.97 508.00 6,163.32 6,671.33 Region 10 - Northern Mindanao 47.64 206.80 51.98 306.43 6,164.09 6,470.52 Region 11 - Davao Region 43.58 171.17 48.97 263.72 5,744.07 6,007.79 Region 12 - Central Mindanao 72.98 85.65 46.92 205.54 5,519.34 5,724.89 CARAGA 45.97 68.26 39.52 153.75 6,452.44 6,606.20 Cordillera Administrative Region 56.08 156.55 69.97 282.59 9,014.24 9,296.83 National Capital Region 3.12 1,994.54 - 1,997.66 5,142.88 7,140.54 Total 77.57 329.30 68.48 475.34 5,670.13 6,145.47 2010 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 86.28 112.48 159.39 358.15 7,447.94 7,806.09 Region 2 - Cagayan Valley 94.87 18.61 54.95 168.44 7,469.16 7,637.59 Region 3 - Central Luzon 149.72 90.17 120.14 360.03 5,818.82 6,178.84 Region 4A - CALABARZON 196.38 218.31 116.94 531.64 5,213.92 5,745.56 Region 4B - MIMAROPA 70.52 48.58 87.99 207.09 6,050.84 6,257.93 Region 5 - Bicol Region 41.80 49.52 110.95 202.27 5,984.41 6,186.68 73 Region 6 - Western Visayas 55.62 159.29 63.70 278.60 6,844.29 7,122.90 Region 7 - Central Visayas 84.91 175.58 35.68 296.18 5,632.03 5,928.21 Region 8 - Eastern Visayas 35.43 39.05 24.96 99.44 6,287.62 6,387.05 Region 9 - Zamboanga Peninsula 27.56 53.14 22.12 102.82 6,133.32 6,236.14 Region 10 - Northern Mindanao 55.90 162.02 32.46 250.37 6,108.01 6,358.38 Region 11 - Davao Region 47.98 193.21 34.48 275.67 5,700.52 5,976.19 Region 12 - Central Mindanao 74.33 93.77 57.07 225.17 5,626.28 5,851.45 CARAGA 49.13 50.77 34.01 133.90 6,338.27 6,472.17 Cordillera Administrative Region 72.46 115.36 57.66 245.48 8,755.86 9,001.34 National Capital Region 2.77 1,896.25 - 1,899.01 5,554.73 7,453.74 Total 76.95 291.17 65.16 433.29 5,768.22 6,201.50 2011 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 89.76 101.09 214.88 405.74 8,106.48 8,512.22 Region 2 - Cagayan Valley 108.03 53.75 72.79 234.56 7,694.90 7,929.46 Region 3 - Central Luzon 161.36 99.35 148.01 408.72 6,439.20 6,847.92 Region 4A - CALABARZON 191.85 188.53 133.35 513.73 5,482.26 5,995.98 Region 4B - MIMAROPA 64.62 38.97 74.66 178.25 6,417.62 6,595.87 Region 5 - Bicol Region 41.26 58.00 118.34 217.60 6,383.91 6,601.52 Region 6 - Western Visayas 60.48 157.27 55.76 273.51 7,168.90 7,442.41 Region 7 - Central Visayas 81.14 180.29 43.45 304.88 6,037.09 6,341.97 Region 8 - Eastern Visayas 33.90 40.10 34.45 108.45 6,989.37 7,097.81 Region 9 - Zamboanga Peninsula 29.09 57.30 38.62 125.02 6,620.98 6,745.99 Region 10 - Northern Mindanao 54.28 108.50 42.97 205.75 6,319.66 6,525.41 Region 11 - Davao Region 49.65 201.80 62.91 314.36 6,033.09 6,347.45 Region 12 - Central Mindanao 80.24 76.05 43.75 200.04 6,123.56 6,323.60 CARAGA 59.25 54.13 30.41 143.79 6,925.95 7,069.74 Cordillera Administrative Region 73.16 138.95 52.00 264.11 9,529.85 9,793.96 National Capital Region 3.05 1,777.27 - 1,780.32 5,997.43 7,777.75 Total 78.71 275.01 75.50 429.22 6,192.33 6,621.55 2012 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 128.82 88.86 213.40 431.07 8,359.44 8,790.51 Region 2 - Cagayan Valley 71.51 28.11 73.34 172.95 8,796.54 8,969.49 Region 3 - Central Luzon 165.68 122.75 127.85 416.28 6,805.87 7,222.15 Region 4A - CALABARZON 201.37 223.79 140.11 565.27 5,866.47 6,431.74 Region 4B - MIMAROPA 83.72 38.57 76.74 199.03 7,045.12 7,244.15 Region 5 - Bicol Region 47.85 76.61 60.42 184.88 7,045.95 7,230.83 Region 6 - Western Visayas 61.30 157.52 69.34 288.16 7,667.38 7,955.54 Region 7 - Central Visayas 92.28 202.87 52.00 347.16 6,280.78 6,627.94 Region 8 - Eastern Visayas 32.76 47.55 33.83 114.13 7,502.12 7,616.25 Region 9 - Zamboanga Peninsula 35.57 60.23 34.55 130.35 7,145.53 7,275.88 Region 10 - Northern Mindanao 68.34 174.70 49.13 292.17 6,996.58 7,288.75 74 Region 11 - Davao Region 49.65 205.15 48.76 303.56 6,431.02 6,734.58 Region 12 - Central Mindanao 79.79 95.16 65.23 240.18 6,326.83 6,567.01 CARAGA 48.71 69.18 32.04 149.92 7,510.83 7,660.75 Cordillera Administrative Region 77.45 159.46 56.30 293.21 10,112.18 10,405.39 National Capital Region 2.62 1,998.10 - 2,000.72 6,441.21 8,441.93 Total 84.43 311.45 72.84 468.72 6,658.89 7,127.61 2013 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 108.24 75.09 247.06 430.39 9,100.44 9,530.83 Region 2 - Cagayan Valley 83.42 27.13 69.41 179.95 9,444.59 9,624.54 Region 3 - Central Luzon 149.66 137.47 127.40 414.53 7,149.69 7,564.22 Region 4A - CALABARZON 162.28 287.45 107.54 557.27 6,350.19 6,907.47 Region 4B - MIMAROPA 63.03 36.63 63.52 163.19 8,237.13 8,400.32 Region 5 - Bicol Region 47.24 88.35 48.91 184.50 7,397.68 7,582.18 Region 6 - Western Visayas 64.35 164.10 62.04 290.49 8,461.60 8,752.09 Region 7 - Central Visayas 54.47 174.31 41.30 270.08 7,056.34 7,326.41 Region 8 - Eastern Visayas 22.74 43.75 22.71 89.21 8,192.33 8,281.53 Region 9 - Zamboanga Peninsula 30.73 49.93 33.06 113.72 8,308.41 8,422.13 Region 10 - Northern Mindanao 69.31 205.96 35.46 310.73 7,534.84 7,845.56 Region 11 - Davao Region 39.05 194.11 45.84 278.99 7,190.73 7,469.72 Region 12 - Central Mindanao 76.32 83.57 55.57 215.45 7,444.77 7,660.23 CARAGA 49.25 67.89 39.31 156.46 8,217.57 8,374.03 Cordillera Administrative Region 79.76 185.79 69.09 334.64 10,748.58 11,083.21 National Capital Region 2.42 2,068.26 - 2,070.68 6,676.27 8,746.95 Total 72.87 327.32 66.38 466.56 7,266.38 7,732.95 2014 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 97.16 37.32 204.06 338.54 8,922.82 9,261.35 Region 2 - Cagayan Valley 80.87 33.87 50.60 165.34 9,159.14 9,324.48 Region 3 - Central Luzon 139.05 128.60 103.77 371.42 7,218.82 7,590.24 Region 4A - CALABARZON 136.95 253.91 81.23 472.09 6,234.47 6,706.57 Region 4B - MIMAROPA 65.93 47.45 71.52 184.90 7,778.12 7,963.02 Region 5 - Bicol Region 46.33 64.40 34.93 145.66 7,192.29 7,337.95 Region 6 - Western Visayas 64.59 134.42 49.64 248.65 8,196.99 8,445.64 Region 7 - Central Visayas 56.24 142.26 37.74 236.25 7,144.54 7,380.79 Region 8 - Eastern Visayas 26.37 27.58 16.86 70.80 7,866.26 7,937.06 Region 9 - Zamboanga Peninsula 33.69 53.43 33.13 120.25 7,771.57 7,891.81 Region 10 - Northern Mindanao 63.18 109.13 45.28 217.60 7,453.26 7,670.86 Region 11 - Davao Region 44.81 162.80 49.01 256.62 6,630.11 6,886.73 Region 12 - Central Mindanao 90.77 71.66 32.54 194.97 6,038.94 6,233.91 CARAGA 60.24 52.32 39.72 152.28 8,134.58 8,286.87 Cordillera Administrative Region 83.31 100.40 75.74 259.45 10,598.86 10,858.31 National Capital Region 0.75 2,093.36 - 2,094.10 6,480.57 8,574.67 75 Total 69.99 305.02 55.59 430.60 7,057.75 7,488.35 2015 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 104.83 51.00 202.49 358.32 9,523.24 9,881.56 Region 2 - Cagayan Valley 99.89 40.17 49.46 189.51 9,694.39 9,883.90 Region 3 - Central Luzon 168.02 116.26 120.69 404.97 7,560.64 7,965.61 Region 4A - CALABARZON 140.32 276.43 81.03 497.78 6,629.30 7,127.09 Region 4B - MIMAROPA 68.57 54.26 43.97 166.81 8,019.11 8,185.91 Region 5 - Bicol Region 50.71 70.80 41.55 163.07 7,400.85 7,563.91 Region 6 - Western Visayas 77.84 152.20 45.20 275.24 8,329.94 8,605.18 Region 7 - Central Visayas 63.09 139.83 43.02 245.94 7,495.12 7,741.06 Region 8 - Eastern Visayas 33.98 52.78 56.18 142.94 9,171.95 9,314.89 Region 9 - Zamboanga Peninsula 55.49 55.87 46.56 157.92 8,426.99 8,584.91 Region 10 - Northern Mindanao 66.97 139.19 26.67 232.83 7,609.31 7,842.14 Region 11 - Davao Region 51.12 145.39 73.40 269.91 6,864.86 7,134.77 Region 12 - Central Mindanao 99.08 73.30 49.90 222.28 7,335.50 7,557.78 CARAGA 78.82 61.01 41.95 181.77 8,429.82 8,611.59 Cordillera Administrative Region 88.13 120.56 61.44 270.12 11,217.80 11,487.92 National Capital Region 1.86 1,948.60 - 1,950.46 6,900.97 8,851.43 Total 79.85 295.65 60.64 436.15 7,504.35 7,940.49 2016 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 111.80 47.03 212.04 370.86 11,000.72 11,371.58 Region 2 - Cagayan Valley 77.80 64.82 42.51 185.13 10,671.54 10,856.68 Region 3 - Central Luzon 150.90 109.98 101.08 361.97 8,842.04 9,204.01 Region 4A - CALABARZON 110.09 285.15 82.52 477.77 7,797.22 8,274.99 Region 4B - MIMAROPA 73.48 38.99 25.16 137.63 9,276.72 9,414.35 Region 5 - Bicol Region 54.38 69.17 52.09 175.64 9,359.61 9,535.25 Region 6 - Western Visayas 69.75 119.52 57.57 246.85 9,939.45 10,186.29 Region 7 - Central Visayas 84.64 116.50 36.13 237.26 8,509.53 8,746.79 Region 8 - Eastern Visayas 27.43 43.02 33.64 104.09 10,742.14 10,846.23 Region 9 - Zamboanga Peninsula 53.94 81.90 62.36 198.20 9,596.82 9,795.01 Region 10 - Northern Mindanao 56.67 132.64 24.31 213.62 8,963.13 9,176.75 Region 11 - Davao Region 46.88 148.96 49.11 244.96 8,201.65 8,446.61 Region 12 - Central Mindanao 87.67 76.06 52.50 216.24 8,002.81 8,219.04 CARAGA 73.52 53.05 30.87 157.43 10,194.23 10,351.67 Cordillera Administrative Region 69.41 159.59 51.45 280.45 13,072.00 13,352.44 National Capital Region 2.75 2,072.02 - 2,074.77 7,888.66 9,963.44 Total 73.37 300.93 57.43 431.73 8,762.62 9,194.35 2017 Regions Municipalities Cities Provinces Total LGU NG Total Spending Region 1 - Ilocos Region 111.40 50.17 280.28 441.85 11,684.85 12,126.70 Region 2 - Cagayan Valley 71.20 55.01 40.24 166.45 12,091.57 12,258.02 76 Region 3 - Central Luzon 147.81 107.95 90.58 346.34 9,320.90 9,667.24 Region 4A - CALABARZON 123.49 237.04 71.45 431.97 8,222.32 8,654.29 Region 4B - MIMAROPA 79.30 38.14 79.80 197.24 10,210.97 10,408.22 Region 5 - Bicol Region 55.72 61.25 40.61 157.58 9,786.90 9,944.49 Region 6 - Western Visayas 66.96 148.31 76.18 291.45 10,128.47 10,419.92 Region 7 - Central Visayas 64.49 112.75 43.42 220.65 9,701.19 9,921.84 Region 8 - Eastern Visayas 31.37 41.58 27.30 100.26 11,324.52 11,424.78 Region 9 - Zamboanga Peninsula 43.77 82.52 56.48 182.76 10,030.57 10,213.33 Region 10 - Northern Mindanao 79.99 109.79 19.25 209.03 9,500.52 9,709.55 Region 11 - Davao Region 605.39 110.27 53.53 769.20 8,654.44 9,423.63 Region 12 - Central Mindanao 74.43 57.56 28.97 160.96 9,431.70 9,592.66 CARAGA 82.10 49.94 37.53 169.58 11,079.66 11,249.23 Cordillera Administrative Region 86.44 48.17 51.60 186.21 14,405.70 14,591.91 National Capital Region 1.96 2,241.51 - 2,243.47 8,287.06 10,530.53 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 In current prices, in million PhP 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 In 2000 prices, in million PhP 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 77 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 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 Region Personnel 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 Services 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 589,766 247,419 388,092 469,955 0 0 0 0 0 Expenses Capital Outlay 0 0 0 0 420,033 29,123 224,339 1,020,396 607,195 Region 2 - 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 Cagayan Valley Personnel 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 Services MOOE 607,176 527,858 512,649 662,824 794,981 758,710 932,175 1,151,058 1,683,964 Financial 176,019 186,460 364,310 321,745 23 0 0 0 0 Expenses Capital Outlay 0 8 0 0 350,418 23,470 191,360 538,076 514,159 Region 3 - 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 Central Luzon Personnel 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 Services 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 608,467 505,794 817,768 1,076,410 234 72 0 0 0 Expenses Capital Outlay 94 1,429 2,373 300 627,800 112,825 449,850 1,244,504 888,269 Region 4A - 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 CALABARZON Personnel 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 Services 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 694,034 503,701 963,309 1,545,544 0 0 0 0 0 Expenses Capital Outlay 0 0 0 0 774,234 17,990 330,456 1,079,006 1,442,895 Region 4B - 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 MIMAROPA Personnel 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 Services MOOE 533,726 504,675 512,498 626,107 766,844 668,148 869,902 1,254,182 1,608,812 Financial 200,416 129,994 279,035 376,832 0 0 0 0 0 Expenses Capital Outlay 28 0 0 0 1,025,821 54,884 160,832 371,022 451,906 Region 5 - Bicol 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 Region Personnel 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 Services 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 78 Financial 502,453 203,154 546,124 884,741 4 0 0 0 0 Expenses Capital Outlay 8 8 12 13 1,261,657 59,661 388,044 1,109,600 774,582 Region 6 - Western 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 Visayas Personnel 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 Services 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 436,660 231,823 380,998 667,346 0 0 0 0 0 Expenses Capital Outlay 0 103 0 0 1,117,400 539,835 594,921 616,772 1,134,935 Region 7 - 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 Central Visayas Personnel 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 Services 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 401,250 427,011 743,178 967,422 0 0 0 0 0 Expenses Capital Outlay 0 0 0 0 1,304,559 436,405 168,404 462,738 829,338 Region 8 - 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 Eastern Visayas Personnel 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 Services 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 491,559 158,365 522,629 700,847 0 1 0 0 0 Expenses Capital Outlay 0 0 4 0 378,064 333,420 641,728 1,472,412 844,037 Region 9 - Zamboanga 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 Peninsula Personnel 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 Services MOOE 557,499 566,671 620,865 797,542 981,577 847,218 1,124,103 1,369,440 1,817,713 Financial 297,937 158,875 363,334 463,834 0 0 0 0 0 Expenses Capital Outlay 0 0 0 0 658,977 15,703 286,934 291,074 415,014 Region 10 - Northern 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 Mindanao Personnel 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 Services MOOE 674,486 680,873 658,774 917,080 1,017,132 897,934 1,080,334 1,515,023 2,241,065 Financial 418,887 123,795 409,194 645,248 30 17 0 0 0 Expenses Capital Outlay 219 31 19 92 415,554 37,722 73,867 520,185 583,789 Region 11 - 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 Davao Region 79 Personnel 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 Services MOOE 690,344 633,721 609,100 823,223 911,917 824,646 1,009,570 1,444,314 1,863,792 Financial 252,344 156,392 427,587 593,066 0 0 0 0 0 Expenses Capital Outlay 0 0 0 0 837,711 210,684 132,768 471,216 589,392 Region 12 - Central 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 Mindanao Personnel 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 Services MOOE 797,359 607,450 712,008 779,499 917,200 761,061 1,053,138 1,484,870 2,118,066 Financial 250,044 171,417 510,864 376,032 0 0 0 0 0 Expenses 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 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 Services MOOE 514,487 411,043 451,840 546,528 671,306 664,916 860,924 1,042,655 1,547,745 Financial 254,304 178,494 279,296 356,350 4 0 0 0 0 Expenses Capital Outlay 0 0 10 0 332,801 18,882 82,241 485,757 486,839 Cordillera Administrative 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 Region Personnel 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 Services MOOE 453,807 360,291 334,116 403,221 533,091 463,721 663,500 659,842 986,000 Financial 308,474 114,758 315,303 232,672 0 0 1 0 0 Expenses Capital Outlay 0 0 0 0 173,545 8,852 57,498 253,044 353,299 National Capital 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 Region Personnel 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 Services 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 606,452 523,821 1,462,101 2,028,205 0 0 0 0 0 Expenses 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 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 Services 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 6,489,067 4,021,271 8,773,121 11,706,248 295 90 1 0 0 Expenses Capital Outlay 349 1,580 2,417 405 11,589,002 1,987,214 4,052,447 10,863,604 10,943,819 80 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 0 0 0 0 0 8,839 97,995 58,217 88,416 Services MOOE 0 0 0 0 0 43,901 13,700 89 0 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 163,669 170,797 166,044 177,528 401,975 431,424 432,564 575,879 604,551 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 212,442 204,679 201,261 214,058 290,152 323,205 331,521 474,281 750,312 Financial 160 0 0 0 0 0 0 0 0 Expenses Capital Outlay 0 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 0 0 0 4,579 5,774 22,694 59,815 123,989 142,001 Services MOOE 0 0 0 0 0 40,112 33,146 0 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 150,606 164,906 144,258 171,553 327,315 320,642 311,742 392,615 466,635 Financial 7,159 0 0 0 14 0 0 0 0 Expenses 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 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 Services MOOE 126,974 139,471 147,910 162,161 197,018 199,710 220,311 287,738 486,547 Financial 6,491 0 0 0 9 0 0 0 0 Expenses Capital Outlay 0 8 0 0 0 0 0 0 0 Region 3 – Central Luzon 81 Kindergarten 10,766 10,800 12,345 13,488 16,822 176,312 262,573 391,805 440,497 Personnel 10,766 10,800 12,345 13,488 16,822 91,729 233,680 389,450 440,497 Services MOOE 0 0 0 0 0 84,582 28,893 2,355 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 397,349 388,934 386,899 418,820 645,051 731,906 769,820 986,294 1,063,279 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 377,216 383,916 385,546 412,512 483,238 586,216 622,304 841,825 1,270,612 Financial 0 0 0 0 215 70 0 0 0 Expenses 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 0 0 0 0 0 61,030 303,906 349,473 387,123 Services MOOE 0 0 0 0 0 88,277 34,702 0 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 448,036 476,940 441,340 470,282 735,510 802,435 843,429 1,108,813 1,191,147 Financial 1,950 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 429,233 430,068 433,386 455,545 583,421 667,733 713,116 977,039 1,402,138 Financial 2,438 0 0 0 0 0 0 0 0 Expenses Capital Outlay 0 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 23,140 6,188 23,774 28,906 34,727 35,074 168,481 177,203 207,101 Services MOOE 0 0 0 0 0 33,370 5,893 7,014 0 82 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 139,641 331,143 136,821 145,890 281,394 274,850 309,617 376,414 447,833 Financial 0 1,250 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 102,552 256,402 118,133 121,201 165,190 179,397 196,461 280,725 434,186 Financial 0 5,518 0 0 0 0 0 0 0 Expenses Capital Outlay 0 8 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 6,182 52,580 8,824 9,592 1,102 113,436 298,313 304,002 333,985 Services MOOE 0 0 0 0 0 65,408 22,524 25,430 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 268,339 279,755 254,562 319,299 527,133 543,890 473,764 719,383 903,195 Financial 4,360 0 2,370 1,029 4 0 0 0 0 Expenses 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 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 Services MOOE 237,505 325,685 208,256 309,752 326,970 368,768 291,413 570,876 964,312 Financial 6,598 0 2,276 774 0 0 0 0 0 Expenses 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 52,177 52,580 75,481 83,688 113,977 173,073 447,305 452,619 505,501 Services MOOE 0 0 0 0 0 77,754 36,612 0 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 83 Personnel 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 Services MOOE 290,913 279,755 309,100 333,959 616,223 645,702 479,692 956,211 995,486 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 316,395 325,685 337,089 321,246 463,365 420,934 340,791 834,455 1,079,088 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 0 0 0 0 0 0 330,721 337,840 376,914 Services MOOE 0 0 0 0 0 72,895 15,202 5,848 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 274,031 293,433 283,770 305,050 500,357 365,192 619,901 759,859 825,144 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 259,331 265,233 269,706 270,033 352,979 398,582 434,158 660,024 967,919 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 11,081 13,019 14,784 16,211 21,825 27,822 43,491 65,034 76,761 Services MOOE 0 0 0 0 0 24,900 18,055 0 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 228,313 228,116 221,120 255,989 445,446 484,981 485,901 627,580 705,513 Financial 0 0 0 0 0 0 0 0 0 Expenses 84 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 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 Services MOOE 177,237 186,384 187,678 200,935 245,622 289,407 313,157 429,580 710,936 Financial 0 0 0 0 0 1 0 0 0 Expenses Capital Outlay 0 0 0 0 0 0 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 4,302,866 0 19,196 20,797 31,595 74,509 225,044 78,925 254,146 Services MOOE 167,449 0 0 0 0 41,267 11,359 0 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 134,658 168,393 168,063 189,936 330,334 353,349 362,336 627,580 539,372 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 21,581 135,294 137,988 144,307 185,555 229,800 231,188 429,580 474,374 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 0 0 0 0 0 0 220,548 246,587 291,120 Services MOOE 0 0 0 0 0 0 6,390 1,944 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 205,434 188,795 174,478 210,646 371,862 0 396,534 518,685 582,858 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 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 Services 85 MOOE 166,435 155,495 143,041 156,683 210,327 0 232,257 340,020 563,773 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 0 0 0 0 0 10,974 151,560 198,530 222,506 Services MOOE 0 0 0 0 0 38,686 14,093 7,214 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 194,365 187,782 176,915 212,430 317,858 352,596 368,600 495,290 537,188 Financial 17,395 305 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 152,790 163,916 165,455 183,209 215,428 241,161 252,547 345,862 522,530 Financial 0 292 0 0 0 0 0 0 0 Expenses Capital Outlay 0 0 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 0 0 0 0 0 0 0 0 0 Services MOOE 0 0 0 0 0 28,052 13,291 3,950 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 174,218 174,153 173,980 193,093 319,900 312,187 439,449 457,206 527,138 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 150,196 150,914 154,138 164,755 209,238 206,471 249,286 350,887 592,034 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 0 0 0 0 0 0 0 0 0 86 CARAGA Kindergarten 29,388 22,736 26,089 28,234 36,611 90,077 172,562 166,740 184,779 Personnel 29,388 22,736 26,089 28,234 36,611 56,873 159,959 166,740 184,779 Services MOOE 0 0 0 0 0 33,205 12,603 0 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 110,023 118,417 112,671 115,830 245,460 252,879 284,366 348,515 370,619 Financial 931 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 104,252 103,016 107,387 122,725 151,885 178,790 190,370 265,321 401,251 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 13,276 17,676 20,285 23,165 34,179 47,845 78,082 79,017 94,821 Services MOOE 0 0 0 0 0 17,815 12,408 0 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 78,326 68,831 68,507 82,983 166,291 179,204 184,637 229,225 259,580 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 66,910 66,284 64,031 76,381 100,038 110,522 116,351 159,207 225,651 Financial 0 0 0 0 0 0 1 0 0 Expenses Capital Outlay 0 0 0 0 0 0 0 0 0 National Capital Region Kindergarten 0 0 0 0 0 41,190 14,823 0 0 87 Personnel 0 0 0 0 0 0 0 0 0 Services MOOE 0 0 0 0 0 41,190 14,823 0 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services MOOE 310,951 297,920 300,982 324,758 462,354 528,900 546,151 697,801 739,755 Financial 0 0 0 0 0 0 0 0 0 Expenses 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 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 Services MOOE 406,646 486,586 491,476 497,920 546,771 625,505 652,989 808,756 1,018,982 Financial 100 0 0 0 0 0 0 0 0 Expenses Capital Outlay 0 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 4,448,877 175,579 200,779 228,660 296,612 723,899 2,818,899 3,027,626 3,605,671 Services MOOE 167,449 0 0 0 0 731,415 293,694 53,843 0 Financial 0 0 0 0 0 0 0 0 0 Expenses Capital Outlay 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 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 Services 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 31,795 1,555 2,370 1,029 18 0 0 0 0 Expenses 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 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 Services 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 15,787 5,810 2,276 774 224 72 1 0 0 Expenses Capital Outlay 101 1,527 26 288 670 0 0 239 81 88 References Acosta, P. 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