Understanding the Impact of Regional Budgets on the Quality and Accessibility of Higher Education in the Philippines

Overview

P

Problem

Access to Collegiate Education is Growing, But Regional Inequalities Still Exist

In the Philippines, disadvantaged students are less likely to complete their degrees and are often concentrated in lower-tier institutions (Yee, 2023). This means that increased access to higher education alone is not enough to guarantee equitable learning conditions in the country.

Even with increased budgets for higher education, the quality and equity of education remain uneven across all regions. According to the Philippine Institute for Development Studies (2022), the Philippines still invests significantly less per student than neighboring countries. For instance, the Philippines spends only about 60–72% of Indonesia’s per-student spending despite having a comparable per capita income, which contributes to poor performance in international standardized assessments.

Q

Questions

Does the Commission on Higher Education (CHED) Allocate Its Budget Effectively?

Proper budget allocation significantly shapes both access to and quality of higher education. To ensure that public funds reach regions where they are truly needed, it is necessary to examine how resources translate into educational outcomes. Comparing regions reveals whether spending aligns with student demand, institutional capacity, and equity goals.

To further assess the relationship between funding and higher education outcomes, this study explores two main questions:

1. How does regional budget allocation influence education quality, particularly faculty–student ratios?
2. Which regions experience higher or lower access to higher education based on enrollment levels, and how do these differences relate to their budgets?

S

Solution

Using Data Science Techniques to Explore Relationships Between Budget Allocations and Higher Education Outcomes

By using data science techniques, this study analyzes data on regional education budgets, enrollment figures, and faculty-student ratios across higher education institution in the Philippines to determine the relationship between budget allocations and higher education outcomes. This study explores how regional budget allocations affect higher education quality as reflected by faculty-student ratios and accessibility to higher education as reflected by enrollment statistics.

H

Hypothesis

This Study Proposes the Following Hypotheses Based on The Current Data:

1. There is a significant relationship between changes in personnel budget allocation and changes in faculty-student ratios across Philippine regions from 2019 to 2024.
2. There is a significant relationship between enrollment growth patterns and personnel budget allocation changes across Philippine regions from 2019 to 2024.

Data

Data Collection

To address the main questions and test the hypotheses, the study utilizaed data obtained from official government datasets and statistical releases from the following sources:

1. Commission on Higher Education (CHED)
Regional enrollment data and faculty–student ratios for 2019 and 2024.
2. Department of Budget and Management (DBM)
Regional budget allocations for Personnel Services (PS), Maintenance and Other Operating Expenses (MOOE), and Capital Outlay (CO) for 2019 and 2024.

You may access our full Excel dataset through the interactive spreadsheet above, or view it directly through this link .

Methods

Data Preprocessing

To ensure consistency and comparabiltity across datasets, raw data was cleaned and transformed as follows:

Data Standardizing

The obtained raw data contained inconsistencies in formatting, structure, and naming conventions. To prepare the datasets for data visualization, the following steps were conducted:

Reformatting and standardizing region names and labels
Converting PDF tables into machine-readable Excel files
Merging institutional data (2019) into regional summaries
Aligning 2019 and 2024 datasets to ensure comparability

Feature Engineering

Key performance metrics were created to better capture relational patterns across regions.

Budget Change By Region (%)
Enrollment Growth By Region (%)
Faculty-Student Ratio Change

These variables allowed standardized comparisons between regions regardless of population sizes or budgets.

Data Visualization

Data was represented in graphs to visualize trends in budget, enrollment, and faculty-student ratios. This initial visual analysis revealed meaningful relationships between these metrics.

Figure 1: Correlation Between Budget & Faculty-Student Ratio

Figure 2: Faculty-Student Ratio

Figures 1 and 2 show clear changes between 2019 and 2024 in both personnel budgets and faculty–student ratios. Regions such as NCR and CALABARZON experienced steady increases in personnel budgets over this period, and they consistently maintained lower faculty–student ratios compared to other regions. This suggests that rising budgets may have helped sustain or improve instructional capacity by supporting additional faculty positions or reducing teaching loads. However, not all regions showed proportional improvements. Several regions increased their budgets from 2019 to 2024 but did not see meaningful changes in their faculty–student ratios. This indicates that higher funding does not always translate into better teaching conditions. Factors such as limited hiring pipelines, uneven distribution of qualified faculty, or administrative barriers may influence how budget increases affect educational quality.

Overall, the comparison of 2019 and 2024 trends reinforces that while funding growth is an important element in improving faculty availability, the effectiveness of funds depends heavily on regional implementation and institutional capacity. Budget increases alone are not a guarantee of better learning environments if structural challenges remain unaddressed.

Figure 3: Correlation Between Regional Budget & Enrollment Trends

Figure 3 presents the total regional budgets and enrollment trends in higher education between 2019 and 2024. The bar graphs represent total budget allocations in Philippine pesos, while the overlaid lines show the number of enrolled students per region. The figure reveals that regions with higher budget allocations, such as the National Capital Region, Central Luzon, and CALABARZON also tend to house higher student populations. This pattern suggests that there are pre-existing regional gaps in both funding and enrollment, highlighting the geographic inequity in resource distribution and access. On the other hand, regions with lower budgets, such as MIMAROPA, Caraga, and the Cordillera Administrative Region, observe lower enrollment rates and student populations. The comparison between 2019 and 2024 demonstrates that regional disparities in access are long-standing and remain largely unchanged over time. Funding patterns tend to follow existing enrollment strengths rather than compensate for regions with low access. This has important implications for equity, as regions with limited educational opportunities may not be receiving enough resources to expand access or support new institutions.

The visual data opens up an opportunity for even greater analysis, to uncover whether or not regional budget allocations are proportionate to enrollment growth and access to higher education.

Hypothesis Testing

To evaluate whether government budget allocation genuinely contributes to improving higher education outcomes in the Philippines, we conducted hypothesis testing to see if funding changes are linked to faculty–student ratios and regional enrollment growth. Rather than relying on descriptive patterns alone, the tests done allow us to assess whether increased budgets translate into measurable improvements in educational quality and accessibility.

Spearman's Rank Correlation

This correlation test evaluates whether two variables tend to rise or fall together, even if the pattern isn’t perfectly linear. We applied Spearman’s correlation to analyze:

Budget Change % vs. Ratio Change
Enrollment Change % vs. Total Budget Change %

Paired t-Test

To determine whether overall faculty capacity improved or worsened in each region, we used the paired t-test which is a method designed to compare the same regions measured at two different points in time. This test allows us to uncover whether or not faculty-student ratios improved over time

Hypothesis Testing Outcomes

Hypothesis 1

Hypotheses

H₀: No relationship between budget allocation and faculty–student ratios

H₁: A significant relationship exists

Spearman Correlation (Change in Budget & Faculty-Student Ratios)

r = -0.156, p = 0.5643
Fail to reject H₀ (not significant)

Paired t-test (2019 vs. 2024 Faculty-Student Ratios)

2019 Mean: 22.17 : 1
2024 Mean: 31.25 : 1
t = -5.556, p = 0.0001
Significant worsening of ratios

Interpretation

No significant relationship was found between personnel budget changes and faculty-student ratios. Despite an average personnel budget increase of 7.24%, the student-teacher ratio worsened significantly across all regions, rising from 22:1 to 31:1, which suggests that budgets did not keep pace with enrollment demand or were not directed toward faculty hiring. As a result, regions, most especially high-enrollment ones like Central Visayas, Bicol, Ilocos, and CALABARZON, struggled to maintain instructional quality. This misalignment slows progress toward SDG 4, which requires not just access, but adequate academic capacity.

Hypothesis 2

Hypotheses

H₀: No relationship between enrollment growth and budget changes

H₁: A significant relationship exists

Spearman Correlation (Change in Enrollmet Rates & Budget)

r = 0.179, p = 0.5061
Fail to reject H₀ (not significant)

Total Budget Equity Analysis

High-access growth regions: +5.42%
Low-access growth regions: -7.51%
Budget allocation favors regions with higher enrollment growth

Interpretation

The result revealed no strong statistical link between a region's enrollment growth and its change in total budget, showing that funding has not been systematically proportional to student population increases. However, a positive equity trend was identified, as the regions with the highest enrollment growth received a slight average budget increase of 5.42%, while those with the lowest growth saw their budgets cut by an average of 7.51%, suggesting a partial but weak policy response to access disparities.

Nutshell Plot

This nutshell plot provides a quick visual summary of how regional funding and academic conditions in the Philippines changed from 2019 to 2024. The top chart compares total higher-education budgets across regions, showing that most regions experienced increases by 2024, with particularly large jumps in areas such as CALABARZON and Central Luzon. The bottom chart pairs these changes with shifts in student–teacher ratios. While budgets generally grew, many regions also saw higher student–teacher ratios in 2024, indicating larger class sizes and increased pressure on faculty.

Taken together, the two charts highlight an important finding of the project: rising regional budgets did not consistently lead to improved student–teacher ratios, suggesting that increased funding alone may not be enough to enhance instructional conditions. The nutshell plot captures this core insight at a glance and sets the stage for deeper analysis in the full report.

Results

Summary

The study shows that higher regional budgets from 2019 to 2024 did not improve the quality or accessibility of higher education in the Philippines. Despite overall budget growth and rising enrollment, faculty–student ratios worsened from 22:1 to 31:1, indicating declining instructional capacity.

For Research Question 1, both the data visualizations and hypothesis testing show no significant relationship between personnel budget changes and faculty–student ratios (r = –0.156, p = 0.5643). Figures 1.1 and 1.2 illustrate that faculty hiring consistently failed to keep pace with enrollment increases. While regions like NCR and CALABARZON maintained relatively stable ratios, regions such as Eastern Visayas and Zamboanga Peninsula experienced severe mismatches between faculty supply and student demand. This confirms that budget increases have not translated into meaningful improvements in teaching capacity.

For Research Question 2, the analysis similarly found no significant correlation between budget changes and enrollment growth (r = 0.132, p = 0.6251). Figure 2 shows clear mismatches: regions with the largest enrollment surges—Bicol (133%) and Ilocos (112%)—did not receive proportional budget increases, with some regions even facing budget cuts up to 17%. Meanwhile, regions with stagnant or declining enrollment, such as CAR, received substantial budget gains. This reflects an inequitable funding model that does not respond to actual regional demand.

Overall, the study’s visual trends and statistical tests both point to the same conclusion: budget allocation in Philippine higher education is misaligned with quality needs and enrollment pressures. Funding increases over the five-year period did not improve faculty capacity, and faculty growth continued to lag behind rapid student expansion, resulting in overcrowded classrooms and declining educational quality.

Limitations & Future Research Recommendations

The study contains a few limitations, including the fact that the dataset included both SUCs and private HEIs, but only public institutions are directly affected by CHED/National Government budgets, making comparisons less precise. Although SUC-level data were available, the results were aggregated by region, which limited insights into specific institutions with the largest resource gaps. Additionally, student–faculty ratios and enrollment rates were the only proxies for educational quality used, and broader learning and outcome-based metrics were not included. Lastly, the study’s analysis covered only 2019 and 2024, restricting the evaluation of trends across longer periods.

To address these limitations, we recommend that future studies consider the following ideas. Firstly, there should be a separate analysis of SUCs compared to Private HEIs. Evaluating public and private institutions independently can avoid conflating resource conditions. Additionally, an institution-level evaluation can be done by using SUC-level data to identify specific universities that face the most severe funding or staffing mismatches. An expansion of quality indicators can also help with incorporating outcome-based metrics, such as graduation, licensure, and unemployment data, to measure education quality more effectively. Given the timeline limitations of the current study, analyzing more years can benefit future studies, especially in uncovering long-term patterns in budget shifts, enrollment growth, and faculty capacity. Lastly, placing more focus on the examination of SUC budget allocations and budget expenditures would also be a good point of interest, especially in determining whether resources translate into improved faculty and student support.

Significance of The Study

Education plays a critical role in shaping the future of the Filipino people, making it essential to understand whether current resources truly support quality learning. Hence, this project underscores the importance of data-driven analysis in identifying structural inefficiencies within higher education. By integrating statistical results with visual analyses, the study reveals that current funding mechanisms are reactive rather than proactive, leading to misaligned resources and declining educational quality.

By examining regional patterns in funding, faculty–student ratios, and enrollment growth, the study highlights that sustainable improvement requires aligning budget allocations with measurable indicators of need and performance. The widening mismatch between funding levels, enrollment pressures, and faculty capacity shows that existing allocation practices are no longer adequate to ensure quality, accessibility, and equity across regions. These insights are essential for guiding evidence-based reforms in Philippine higher education.

Call to Action

The results of this study make it clear that higher budgets alone are not improving Philippine higher education. Despite increased funding, faculty–student ratios have worsened, enrollment has outpaced capacity, and resource distribution remains disconnected from actual regional needs.

To reverse this decline, policy decisions must become truly data-driven. Budget allocation should be aligned with measurable indicators such as enrollment growth and faculty shortages rather than applied uniformly nationwide.

Equally important is greater transparency and accountability in how funds are allocated and used. Public institutions must clearly report how personnel budgets impact hiring, instructional capacity, and student outcomes. Without transparent spending and performance monitoring, even increased funding will continue to fall short.

Improving the quality and accessibility of higher education is essential to shaping the future of the Filipino people. This requires smart funding, responsible use of resources, and continuous evaluation. The system must move beyond reactive budgeting and shift toward a proactive, evidence-based approach that ensures every peso contributes to better learning conditions.

Now is the time to commit to fairer allocation, stronger oversight, and a more responsive education system so regional budgets finally translate into meaningful improvements for students nationwide.

Team

Arian Balicusto

rlbalicusto1@up.edu.ph

2023-01223

Dash Ceñido

ddcenido@up.edu.ph

2023-06831

Trish Obzunar

tbobzunar@up.edu.ph

2023-13237

Chloe Santos

cpsantos5@up.edu.ph

ID: 2023-16995

References

Commission on Higher Education. (2019). 2019 PHEIs faculty-student ratio. https://ched.gov.ph/wp-content/uploads/2019-PHEIs-Faculty-Student-Ratio.pdf
Commission on Higher Education. (2019). 2019 SUCs faculty-student ratio. https://ched.gov.ph/wp-content/uploads/2019-SUCs-Faculty-Student-Ratio.pdf
Commission on Higher Education. (2019). CHED regional expenditure program, FY 2019. Department of Budget and Management. https://www.dbm.gov.ph/wp-content/uploads/NEP%202019/OEO/D.pdf
Commission on Higher Education. (2024). 2024 higher education facts and figures. https://ched.gov.ph/2024-higher-education-facts-and-figures/
Commission on Higher Education. (2024). CHED regional expenditure program, FY 2024. Department of Budget and Management. https://www.dbm.gov.ph/wp-content/uploads/NEP2024/OEO/E.pdf
Easdown, N., et al. (2024, June 4). Harmonizing work and higher education: Analysis of the circular flow of income in the Philippine setting. http://dx.doi.org/10.2139/ssrn.4853693
Philippine Institute for Development Studies. (2022, January 22). PH lags behind regional peers in basic education spending—PIDS study. https://www.pids.gov.ph/details/ph-lags-behind-regional-peers-in-basic-education-spending-pids-study
Yee, K. M. R. (2023). At all costs: Educational expansion and persistent inequality in the Philippines. Higher Education, 87(6), 1809–1827. https://doi.org/10.1007/s10734-023-01092-y

Understanding the Impact of Regional Budgets on Quality and Accessibility of Higher Education in the Philippines