FINAL REPORT

COMMISSION ON HIGHER EDUCATION

A Comprehensive Cost Analysis of Degree Programs for Selected Higher Educational Institutions (NCR Pilot Study – Phase 1)

De La Salle University Research Team DR ANDREA SANTIAGO * MR GERARDO LARGOZA * MS MITZIE PONCE DR PONCIANO S INTAL JR * DR MICHAEL M ALBA * DR CESAR RUFINO October 31, 2002

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ACKNOWLEDGMENTS

This Pilot Study would not have been completed without the inputs, time and patience provided by various individuals. The research team undertook focus group discussions, made presentations to end-users and other research teams, as well as requested data and other inputs from various universities For all this, the research team wishes to acknowledge the following for their invaluable contribution to the study, listed in alphabetical order:

Ms. Melba Abalete, Registrar, PUP Ms. Marilyn Aguinaldo, CHED Ms. Florence Allejos, Budget Officer, PNU Ms. Jocelyn Balistoy, URCO, DLSU Ms. Teresita Baterina, ADB Consultant Mr. Charlie Calimlim, CHED Dr. Ofelia Carage, President, PUP Ms. Virgie Cariaga, CHED Dr. Leticia Catris, Dean, PNU Ms. Lucinda Teresa David, Student Assistant, DLSU Bro. Roly Dizon, President, DLSU University System Ms. Wendy Duncan, ADB Ms. Teresita Farrell, VP Finance, DLSU Mr. Danilo Garcia, HRM Officer, PNU Dr. Ester Garcia, Chairman, CHED Ms. Lily Garcia, Head of Research, OPPRI, CHED Dr Lilia Garcia, President, PNU Dr Lydia Hilbero, Dean, PNU Ms. Harry Huliganga, Chief Accountant, PNU Ms. Florenita Imperial, Budget OIC, PUP Ms. Violeta Llaguna, HRM Officer I Ms. Marissa Legaspi, Director Accounting, PUP Mr. Arnualdo Macapagal, Chief Accountant, FEU Mr. Samuel Mallare, Director ITC, DLSU Dr. Rosemarie Montañano, DLSU, Director, CHED Zonal Regional Center Mr. Honesto Nuqui, UP, ADB Consultant Dr. Jesus Ochave, Dean, PNU Ms. Jessica Ong, Student Assistant DLSU Dr. Cristina Padolina, Commissioner, CHED Dr. Carmelo Perez, VP-Finance, PUP Ms. Cora Posadas, ADB Consultant Dr. Twila Punsalan, Dean, PNU Dr. Carmelita Quebengco, EVP, DLSU

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Dr. Samuel Salvador, VP-Academic Affairs, PUP Ms. Asuncion Santos, EVP Staff, DLSU Ms. Lourdes Santos, University Registrar, PNU Ma. Nelia Santos, VP Finance, PNU Ms. Chari Sevilla, Student Assistant, DLSU Ms. Ivy Sison, Student Assistant, DLSU Ms. Rhocelle Sosa, URCO, DLSU Ms. Dianne Sy, Student Assistant, DLSU Mr. James Sy, Database Administrator, DLSU Ms. Flor Tamonan, ITC, DLSU Dr. Editha Tan, ADB Consultant, UP Dr. Jean Tayag, Director of OPPRI, CHED Ms. Daisy Umali, Student Assistant, DLSU Ms. Sherryl Uy, Faculty, DLSU

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EXECUTIVE SUMMARY The first phase of this project assessing the viability of the normative financing framework involved an attempt to estimate the cost of producing degrees at a sample private and public HEI. Costs were broken down into 3 major categories: direct personnel expenses, departmental MOOE and indirect costs. Inasmuch as different universities accounted for costs in different ways, the researchers had to exert a considerable amount of effort to reconcile accounts and arrive at consistent ways of calculating figures. The full spreadsheet accounts with all relevant cost figures were then derived. To simplify analysis, we computed costs for 2 sample degrees per university, using the formula described in the methodology. The figures reveal significant differences between tuition fees charged and the cost figures computed. The cost figures are more reliable as they work on the premise that the university has internalized all relevant expenses. Our findings confirm the intuition that scale effects from the number of students enrolled work to drive down both personnel and MOOE costs. It is this sort of logic that has caused universities to enact internal controls on program expansion, class sizes, and other means to ensure efficiency. We have also uncovered the use of cross-subsidies from “high-volume” colleges (business, liberal arts) to “expensive/low-volume” colleges (sciences). If one compares expense figures to tuition rates, one will discover that universities transfer funds from high-revenue colleges to low-revenue ones in order to maintain relatively similar matriculation costs. We are careful to point out, however, that the data obtained from this method are essentially static – that is to say, they do not incorporate programmed increases in quality provision (which itself is costly), as well as very significant market distortions (such as “irrational” student preferences). As this is the first phase, we expect that as additional universities and HEIs are surveyed, we will be able to use the accumulated data to construct a cost function and compute the marginal cost of producing a graduate in a course from an HEI of a given quality level.

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TABLE OF CONTENTS PART I – RESEARCH FRAMEWORK 1 1.0 Introduction 2 1.1 Background of the Study 2 1.2 Statement of the Problem 2

1.3 Objective of the Study 3 1.4 Significance of the Study 4 1.5 Scope and Limitations 5 1.6 Acronyms and Operational Definitions 6

2.0 Review of Related Literature 7

2.1 State of Philippine Education 7 2.2 Normative Financing for Higher Education 8

3.0 Research Methodology 9

3.1 Conceptual Framework 9 3.2 Research Design 11 3.3 Research Tools 13 3.4 Research Criteria 13 3.5 Research Procedures 14

3.5.1 Development of Research Instrument 14 3.5.2 Selection of Cases 14 3.5.3 Preparation for Data Collection 15 3.5.4 Data Collection 15 3.5.5 Documentation 15 3.5.6 Analytic Procedures 16 3.5.7 Modification of Theory 19

PART II – CASE STUDY REPORTS, ANALYSIS AND CONCLUSION 21 4.0 Cost Analysis of Two Universities

4.1 Sample Costing for a Private Institution 22 4.2 Sample Costing for a State University/College 30

5.0 Recommendations and Insights 40

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PART III – REFERENCES, APPENDICES, TABLES AND FIGURES 46 References 47 Appendices

Appendix A Comparison of Different Methodologies 48 Appendix B Sample Survey 55 Appendix C Sample Sheets for Analysis 70 Appendix D Step-by-Step Procedure for Analysts 72 List of Tables Table 1.1 List of Acronyms and their Definitions 6 Table 5.1 Graduates per Subject 41 List of Figures Figure 2.1 Cumulative Number of State Universities and Colleges 8 Figure 3.1 Conceptual Framework: Cost Per Student Per Degree 10 Figure 3.2 Model Building Approach 14

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PART I – RESEARCH FRAMEWORK The research framework is composed of three chapters. The first chapter describes the study, enumerates the objectives, and provides the relevance of the study. The second chapter is dedicated to the review of related literature while the third chapter provides the details of the framework and the methodology adopted.

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CHAPTER 1 Introduction

1.1 Background of the Study The rationalization of the Philippine Educational System has been described extensively by the Presidential Commission on Educational Reform (PCER). In their April 2000 Report, they revealed three basic problems in the Philippine education system. These are inequity in opportunities and resource allocation, inefficiency in the use of resources, and low and declining levels of quality. In the bid to address these concerns, the Education Sector Development Program (ESDP) was formed. It is envisioned that this ADB-funded program would give rise to policy reforms in the following areas:

Sector Financing Normative Financing for Basic Education Scholarships and Loans Normative Financing in Higher Education Rationalization of State Universities and Colleges Allocations for Non-Salary Expenditures in Basic Education

The task is daunting and consequently each of the objectives had been broken up to manageable sizes. The concern of this research is for Normative Financing in Higher Education. 1.2 Statement of the Problem

In light of the importance of education to a nation’s development, it is vital that a thorough and in-depth understanding of the myriad issues involved in the financing of education be undertaken in order to develop a policy environment that will lead to its effective promotion. Of particular concern is the financing of higher education since it is widely seen as having diverted funds from the government’s commitment to basic education.

A review of the budgetary allocation for state universities and colleges (SUCs) has shown that they have been primarily subsidized by the National Government through input financing (PCER, 2000). About 75% of the budget allocation for SUCs goes towards personnel services, while about 18% finances operating expenses. Thus increments to yearly budgets are there only to cover mandated salary increases and the costs of inflation.

Introduction 2

Despite the steady 17-18% of the education budget going to the SUCs, the share of each university decreases not only because the total budget for the educational sector has decreased, but also because of the growing number of SUCs that have to be financed. While the number of SUCs has remained below 115, the number of satellite campuses has increased dramatically. With lower budgets, the quality of education has begun to deteriorate as teachers themselves are not able to obtain advanced degrees. Clearly there is high dependence on the National Government in the financing of higher education. Yet Government is financing the operations of 114 SUCs that serve only 28.3% of higher education institution (HEI) enrollees with expenditures ranging from as low as P6,000 to as high as P100,000 per student. Studies (PCER, 2000; Preddey and Nuqui, 2001) have shown that of total HEI enrollees, only 25 % belong to the poor income groups. The inequities and efficiencies cannot continue unabated if Government is to uplift the standard of education necessary for the nation’s development. This concern has led to the concept of normative financing, a budgetary allocation process used by countries such as Australia and the United Kingdom. In normative financing, educational institutions are given budget allocation according to a formula that considers the cost to educate a student taking a particular degree. In layman’s terms, government will be “buying” a particular number of students taking a particular degree, the degree of which is line with government priorities, thus transforming the system from being input based to being output based. It is targeted that by CY 2004, the normative financing formula shall be used to determine budget allocations per SUC. To determine the budget allocation however, it is imperative to arrive at a cost per student per degree so that such a “norm” can be imputed into the financing formula. This cost should not only include teaching costs but research and extension services costs as well. Such costs have not yet been determined although very rough estimates has been presented by Preddey and Nuqui (2001). 1.3 Objective of the Study

A comprehensive study on the costs of the different degree programs offered in higher educational institutions is a major component of the normative financing formula. However, before an extensive study can be done, it is essential to conduct a pilot research study to determine the best way to arrive at a cost for a particular degree. This is what the research study hopes to accomplish.

The output of this study is a research methodology that can be used across all HEIs, whether public or private, so that data are comparable. This methodology will be tested for a prototype degree, in order to arrive at useful estimates of student costs.

Introduction 3

1.4 Significance of the Study

An important step in trying to address the major issues involved in the financing of higher education is a comprehensive cost analysis of the major degree programs offered by higher educational institutions so as to have a positive view of how resources are spent and for what purposes. This will provide the stakeholders in higher education, relevant information so as to first of all answer normative questions regarding the uses of funds in higher education and then make the appropriate policy recommendations. Essentially an analysis of costs will provide a systematic accounting of the uses of funds in the degrees offered in higher education institutions.

This process will give us vital information such as: (a) the distribution pattern of the uses of the funds; (b) the allocation of funds across educational inputs (.i.e. salaries, equipment, research and development, etc); (c) the proportionate cost shares of inputs; (d) the overall structure of costs for each degree program and institution; and lastly (e) an estimate of the cost per student in the different degrees offered by higher education institutions in the country. In turn this will lead to insights on normative questions (of what ought to be) regarding these issues such as (a) is the allocation of funds across education inputs ideal?; (b) is the allocation of funds between research and teaching ideal? Or, (c) does teaching take precedence over research?

; The comparative cost data obtained will afford a better understanding of the costs of higher education degree programs; in particular the cost per student in each degree program considered in the study. Moreover, they will also afford a better understanding of other important issues in higher education financing as identified by the CHED. These include the following:

How much should the effective government subsidy amount to?

Will the option of selective subsidies based on programs and/or institutions lead to better allocative efficiency?

How much of the average cost of higher education should be borne by the

students and their families?

Are there possible options for alternative private sources of financing higher education?

Is there any possibility for government subsidies to private higher educational

institutions? If so, how much should the effective subsidy be and where should it be allocated (i.e. which private institutions, which programs)?

Introduction 4

Should the government increase its appropriations for higher education scholarships? Where should these scholarships be directed to (i.e. students, faculty, which programs and institutions)?

It is envisioned that as student placements begin to replace the traditional budgetary allocation process, then public HEIs will be forced to creatively source additional financing either through internally-generated income, local government support, or partnerships with donor institutions. In this way, there will be relief in the total education sector budget that would allow more funding for basic education and a re-channeled financing to HEIs through scholarship grants either direct to students or to institutions.

1.5 Scope and Limitations

There have been many constraints in the accomplishment of the objectives of this research. Since it is a pilot study that needed immediate output, the number of HEIs was considerably trimmed from 8 to 4, then later to just 2. The choice of these 2 HEIs was determined by the following: (1) easy access to data and (2) quality of education. Moreover, one HEI had to be a public institution, while the other a private institution both of high quality for benchmarking purposes. The choice of HEI for evaluation was limited to the National Capital Region. There was no attempt to try to identify HEIs from other regions since the study does not intend to arrive at a representative cost per student per degree but aims to test the research methodology

The research is thus limited to testing a research methodology. It is not meant to determine the cost per degree, per se. However, in testing the methodology, some cost estimates were derived. Nonetheless, the costs that were generated from this research are not representative of the cost to educate a student for a particular degree and cannot by itself be imputed directly into the normative financing formula. More comprehensive studies (phases 2 onwards) should be conducted to fulfill the requirements of the formula. These however should be coordinated with the research team to ensure uniformity in methodology.

The identity of the HEIs studied is to be kept confidential. This is especially important for private institutions. To further disguise these private HEIs, the more common programs were used to substitute the names of programs through which the university can readily be identified.

Finally, no inflationary factor was imputed in arriving at costs for each subsequent year of student education. However, costs are not stagnant and consequently a multiplier should be included when using the formula for normative financing.

Introduction 5

1.6 Acronyms and Operational Definitions

For uniformity, “degrees” shall refer to that conferred upon the students upon their graduation.

There are many terms that are referred to in their acronym form. These terms and their definitions are listed in the table next page:

Acronym Definition CHED Commission for Higher Education COD Center of Development COE Center of Excellence

CSI CHED Supervised Institutions GAA General Appropriations Act

HEI Higher Education Institution MOOE Maintenance and Other Operating Expenses

PAASCU Philippine Accrediting Association of Schools, Colleges, and Universities

PCER Presidential Commission on Educational Reform SUC State University and College

Table 1.1. List of Acronyms and their Definitions

Introduction 6

CHAPTER 2 Review of Related Literature

2.1 State of Philippine Education It is a constitutional mandate to provide basic education to the Filipino people. This is reflected in the large budgetary allocation the National Government provides for educational sector. Part of this budget however goes to financing higher education, except that the government is no longer obliged to provide free education at this level. What it must do is facilitate access of qualified students to advanced education perhaps through scholarships in state or private institutions. It should only be providing for higher education in priority programs and geographic areas, which other sectors cannot support (PCER, 2000).

Unfortunately, the proliferation of SUCs has placed a considerable strain on the scarce resources of the government. According to the PCER Report (2000), the average annual cost per student for basic education was about P5,000 in 1998 compared to that of higher education which ranged from P6,700 to close to P100,000. The cost per student at the University of the Philippines was P62,000 compared to its maximum tuition fee level of only P8,000. In the same report, it was relayed that the cost per student in SUCs is even much higher than those of private institutions. The balancing act has resulted in great deficiencies in basic education manifested by lack of classrooms, textbooks and teachers, and continued unsatisfactory ratings in achievements tests for math, science, and language (PCER).

The creation of additional SUCs over the years (see Figure 2.1), either through conversion of CHED-supervised institutions (CSIs) or legislative intervention, has meant that the 17-18% proportion of SUC budget to total education sector budget has resulted in smaller budget allocations per SUC. Thus the increase in SUCs as well as the increase in satellite campuses not only increases competition for scarce resources, but it also perpetuates poor quality of education as most of these SUCs have merely been converted from CSIs without regard to their capabilities (ADB and WB, 1998).

Figure 2.1 ulative Number of State Universities and Colleges 1 9

1 9 11 91 9 3

1 9 41 9 5 0

1 9 61 9

1 9 8 11 9

2 Cum0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

0 0 -0

2 1 -0

1 - 1 -7 0

-9 0

0 0 1 -2 0 1 0

N u m b e r o f S t a t e U n i v e r s i t i e s a n d C o l l e g e s

Table 2.1. Cumulative Number of State Universities and Colleges

Review of Related Literature 7

The Government would have to rely on private sector initiative to fill the gaps of the state. But the private institutions are under the impression that the additional SUCs are crowding them out (PCER, 2000). Ideally, SUCs should only be in regions not serviced by the private sector, offering programs that are not better served by the latter, and ensuring access to the poor. 2.1 Normative Financing in Higher Education According to Preddey and Nuqui (2001), government should support a budgetary allocation process that favors transparency and that becomes more predictable in the medium term. The current practice of input financing is fraught with ambiguity and uncertainty as budgets are negotiated rather than justified. With output financing these concerns may be addressed. Normative financing aims to provide financing of outputs: teaching, research and extension. There is a purchase of student places (outputs) in degrees that are priorities of the government. In this way, HEIs may be forced to either fund their other expenditures through alternative revenue sourcing and/or efficiently utilize their resources. It is possible that with normative financing, degrees that are no longer profitable and can be better served by other HEIs shall be eliminated from a SUCs original course offering. With normative financing the government hopes to achieve less dependence by the SUCs on the National Government for higher and advanced education financing. Consequently the rise of SUCs, should there be, will only in areas unserved by the private HEIs and thus deserving of National Government financial support.

Review of Related Literature 8

CHAPTER 3 Research Methodology

This chapter provides the framework used in this research. It justifies the methodology adapted by the research team and proceeds to describe in detail the tools, criteria, and procedures employed to arrive at the findings and conclusions. 3.1 Conceptual Framework

The objective of the study is to arrive at a cost per student per degree. To do this, it is necessary to properly allocate all costs to a particular degree. There are two components of costs: direct costs and indirect costs. Direct costs refer to the teaching expenses for personnel services and MOOE of the department offering the degree. Indirect costs refer to research, extension services, and administrative costs of running the entire HEI, the total of which is distributed to all departments.

The approach taken by the research team is to identify the following: an average cost per unit for each subject a student would have to take to attain a degree; an average share in the direct maintenance and operating expenses of departments by students who enroll in subjects offered by that department; and an average share in all other yearly costs to run a university by the total number of student enrolled in the university. There are different ways to compute the average cost per unit per subject per student, from the simplest to the most complex. Intuitively, the simplest formula that can arrive at cost estimates quicker makes many assumptions and consequently provides the roughest estimate of unit costs. On the other extreme is the complex methodology that entails more manpower efforts, minimizing assumptions, and thereby presenting more realistic estimates of unit costs. The different formulae and their effect on unit costs are described further in Appendix A. Notwithstanding, the framework calls for determining an average cost per student to take a course, for instance English. If the average cost is expressed in units, this cost is multiplied by the total number of units a student must take for English to complete a degree. If the average cost is expressed per subject, the average cost is then multiplied by the number of English courses a student must take to complete a degree. Therefore, if the above procedure is done for all major subject categories, then the direct teaching cost per degree per student can be readily attained. It can also be presented per year, thus fully disclosing how costs to educate may increase as a student progresses to higher years. To fully complete the cost per degree, the direct costs for operating expenses and the indirect costs per student are then added to determine the cost per student for each of the years in the university. The direct operating expense is determined by dividing total direct operating expense by the number of students taught; while the indirect cost per student is arrived at by dividing the total indirect costs, earlier described, by the total student population.

Research Methodology 9

Figure 3.1 below attempts to depict the conceptual framework that starts from the University budget.

TOTAL UNIVERSITY EXPENDITURES

University/College Level DIRECT ADMIN RESEARCH EXTENSION TEACHING Department Direct Cost Direct Cost Indirect Cost Personnel Svcs Operating Divide by Divide by Divide by Total Units/Year # of Enrolled Student & # Students Students Population

DIRECT UNIT COST PER STUDENT INDIRECT (by Subject or Department) COST/STUDENT

Add Products of all Direct Costs Per Subject/Department

COST PER STUDENT FOR YEAR

Add Direct Costs for Each Year in the Curriculum

COST PER STUDENT PER DEGREE

Figure 3-1. Conceptual Framework: Cost Per Student Per Degree

Research Methodology 10

3.2 Research Design

This research project is a pilot study that aims to test the usefulness and applicability of the methodology to determine the cost per degree. The model builds up as more information is gathered from the HEIs.

The initial concept of the research instrument was first discussed in a focus group discussion (FGD). During the FGD, representatives from the finance and information systems department of four universities were invited to discuss their accounting and information systems. This was necessary to determine the kind of data that can be retrieved and the time it would take to extract data. The FGD identified five sources of data: Finance department for financial statements, Human Resource department for plantilla, Office of the University Registrar for course offerings, number of enrollees, Office of the Vice President for Academics (or its equivalent) for faculty loading, and the different Department Heads for flowcharts.

3.2.1 Year of Analysis. In designing the research, it was important that the costs of the different HEIs could be made comparable. The year of study had to be as close to each other as possible. The initial review of the budgetary process of the universities revealed that the accounting cycle of public schools is different from that of the private sector. Public HEIs work on a calendar year while private HEIs use the school year. Given the difference in accounting cycles, a workable commonality had to be set. At the time this study was started, the complete set of data for a school year was SY 2000-2001. This was then used as the benchmark. Since this encompasses two budgetary periods of the public HEIs, a logical time frame to make data comparable would be to cover the same school year using two sets of financial data for public HEIs, one for 2000 and another for 2001. However, this approach requires more effort and discretion to correctly extract the information. For practical purposes, it would be easier to work on two separate school years, but only with one calendar year. Consequently, the data used for the SUCs is calendar year 2001. This encompasses data from 2nd semester, 2000-2001, summer of 2001, and first semester of 2001-2002. This is also better than getting the information for one term and multiplying it by 2.5. For the private institution, the data used came from school year 2000-2001.

3.2.2 Cost Centers. Another consideration in the design of the research was accountability centers. Initial feedback showed that the private HEIs are able to segregate expenditures according to cost centers that go down to the department level. For some, the portion of research and extension on the department level can be automatically charged to the research and extension services budget. Consequently, there was no need to extract data from the teaching component since all personnel expenses reflected per department in a computerized accounting system working on specific cost centers WERE direct teaching expenditures.

Research Methodology 11

For the SUC however, expenditures were treated as lump-sums and allocated to cost centers only on one level. Thus there would be a budget for “Higher Education” but this is not brought to the department level. If this would be the case for all SUCs, then more steps would have to be taken to arrive at the cost per department. These steps are discussed in data gathering procedures. 3.2.3 Service Courses. There are many departments that service the courses of other majors. For instance, a faculty member in the business management department may teach a course in liberal arts. Thus unless a portion of the personnel expenses were reported as part of the liberal arts expenditures, this would have to be transferred to reflect the true costs for both departments. Otherwise the expenditures of business management would be divided by less number of courses, while alternately, that of liberal arts would be divided by a bigger number of courses. The matter of service courses was resolved by determining the cost per course for each faculty member and correctly assigning that cost to the department that offers the subject. 3.2.4 Laboratory Costs. There are some courses that are more expensive to teach than others because of the laboratory costs. If a laboratory cost can be specifically identified as a department cost, then the costs are included in the MOOE of that department. If a laboratory cost is shared by a particular college, then the MOOE is assigned to the collage and allocated to the different departments under the college based on usage. In this case, the number of sections becomes relevant information. Finally, if the laboratory cost is shared by the entire University, then the costs are left at the University budget and shared by the total number of students. 3.2.5 Administrative Expenses. The basic premise used is that for as long as an expense can be identified as belonging to a college or department, then the expenditure is assigned to that college or department. Otherwise, it is treated as an indirect cost that is to be divided by the total student population.

3.2.6 Capital Outlay and Depreciation. Capital outlay is treated as an investment and not included in the expenditures of a department. However, capital outlay has the effect of improving the quality of education and consequently portions of this should be imputed into the expenditures. This is reflected in the depreciation. While depreciation is a non-cash item, it is reflected in the budgets of private HEIs. For public HEIs such is not so. Thus additional information is required so that a depreciation expense can be imputed. Nonetheless capital outlay itself is a non-recurring expense and can be treated separately in the normative financing formula. It also accounts for less than 10% in the budget of a typical SUC.

Research Methodology 12

3.2.7 Donated Property. For public HEIs in particular, there are properties donated by individuals or the local government units. The value of these properties are however not reflected in the financial statements. For the moment, this was not tackled. But the information is relevant in determining quality of education and efficiency of resource utilization.

3.3 Research Tools

The researchers used the interview method and survey form to gather data for the study.

3.3.1 Interview. The interview was necessary to ensure that proper clearances were given to gather data. The research analysts were basically tasked to gather the data. Research assistants were used only to follow-up submission of data or additional requirements. 3.3.2 Survey. A survey template was used to ensure that the same kind of data was being gathered. Raw data in hard copy were encoded using a template. Soft data were merely uploaded. The survey was further revised after the experience of the research exercise.

3.4 Research Criteria There were two basic requisites that had to be met for a university to be included in this study. The primary concern was accessibility of data while the secondary concern had to do with quality of education. Due to the confidential nature of the data, the names of the universities are not disclosed. Suffice that one is a public HEI and the other a private one.

3.4.1 Accessibility of Data. The expediency to complete the pilot study was a paramount concern. Because of this, the more cooperative Universities were tapped. Initially, 8 Universities were targeted. However the list was trimmed down to 4 and finally to only 2 since waiting for complete data from the other 2 would further delay the project.

3.4.2 Quality of Education. The cost per degree that would be derived from this study is supposed to be credible. Consequently, the search for Universities was limited to those who are either Centers of Excellence (COEs) or Centers of Development (CEDs). Other measures used to determine quality was the percentage passing rate in government licensure examinations.

3.5 Research Procedure The researcher used the illustration, labeled as figure 3-2, as a guide in the research design, data collection, and data analysis. Essentially, it was a model-building approach as the research formula was constantly being evaluated. This was adapted from the case study method espoused by Yin (1994).

Research Methodology 13

ANALYZE &

DEFINE & DESIGN PREPARE, COLLECT, & ANALYZE CONCLUDE conduct write draw

first individual cross-case case study case report conclusions

select cases modify instrument

develop conduct write instrument second individual

case study case report develop implications design data collection protocol write conduct write cross-case remaining individual report case studies case reports

Figure 3-2. Model Building Approach (Adapted from Case Study Method used by the Cosmos Corporation)

Source: Yin (1994, p. 49) “Case Study Research: Design and Methods” 3.5.1 Development of Research Instrument. The research team met on several occasions to draft and critique a research instrument. The initial bases for the drafts were research instruments used for other projects on HEIs, here and abroad. Sample instruments were also downloaded from the web. The research instrument was then presented to the participants of the focus group discussion. Based on the comments, the instrument for data gathering was again revised. This final instrument takes into account the possibility that not all HEIs have cost centers and consequently is lengthier. Since the direct department costs would have to be derived, the amount and detail of information required is necessarily more. A copy of the research instrument as used for data gathering purposes is found in Appendix B.

3.5.2 Selection of Cases. The process of identifying and confirming the participation of HEIs took place over a period of close to four months. Initially 8 HEIs were identified but this was reduced to 4 HEIs due among others to budgetary constraints. Out of the original 4 HEIs identified, one did not participate so the HEI had to be replaced. Eventually, 2 HEIs failed to submit all the required data on time so these were likewise eliminated.

Research Methodology 14

3.5.3 Preparation for Data Collection. The data required by the research was confidential and voluminous. Consequently, two critical steps were undertaken prior to data gathering.

The first step was to get the clearance from the University administrators to disclose confidential information. This was done with the help of the CHED, who prepared an endorsement letter. Once the CHED letter was received and acknowledged, the research team set an appointment with the key personnel identified in section 3.5.4.

The second step was to send an advance copy of the research instrument that specifically lists the information required of the HEIs. With this in place, the HEI were given more lead to prepare their data. Unfortunately, this did not work for the 2 HEIs eliminated from the study.

3.5.4 Data Collection. As soon as the clearance from the University registrars was given and the survey guide sent out, the members of the research analysts including research assistants went to the University to gather the data. The following offices were visited for the required information: Finance Department Financial Data University Registrar Enrollment Headcount, Course Offerings Human Resource Dept Plantilla Office of the VP Academics Faculty Loading Department Heads Flowcharts Despite the prior clearances however it was the experience that the release of information was still staggered and spread over several months. Some data, especially from the SUC, was in hard copy and the team had to photocopy this and encode it into the system template. In trying to make sense of the data collected, it became imperative to arrive at the following: total cost per department, total number of units taught in the whole year by the department, average class size, while making sure that the expenditures balanced at the aggregate level. To ensure this, the financial statements were divided into three major categories: (1) direct (teaching) personnel services; (2) direct MOOE; and (3) indirect costs. If the HEI did not have specific cost centers, the costs were further broken down to the department level (i.e. economics, business management, math, etc.) of each college.

3.5.5 Documentation Process. All hard and soft copies submitted by the HEIs were properly labeled and stored. These reached about 2 feet high for the SUC and a foot high for the private HEI. A lesser amount of hard copy was submitted by the private HEI because submission of data was in a soft copy.

Research Methodology 15

For the SUC, data were encoded into the system template and were regularly backed up to ensure that data would remain intact should a virus hit the system. The system template is simply the survey form in excel file.

3.5.6 Analytical Procedures. The research team made no attempts to force the data gathered into an existing conceptual framework. Only when the data were analyzed and the conclusions drawn, did the researcher review the existing conceptual frameworks. Thus, much of the analysis relied on dissecting each individual case and comparing them to the other cases so that a pattern could be established. The analytical process is a 3-step approach. The first step is to arrange the information needed into a form that could be analyzed. The sample sheets as basis for analyses is found in Appendix C. The second step is analyze the individual cases by comparing average results with individual results and making sense of the costs by considering efficiency and quality indicators. The final step is to compare the results with other HEIs. For this study, the final step was limited and focused more on determining the differences in research methodology.

3.5.6.1 Analytical Sheets. There were 6 basic worksheets that were used as bases of further analysis. Data for these worksheets were extracted from the encoded data in the templates. A step-by-step procedure on how to accomplish the analytical sheets is found in Appendix D. • Distribution of Direct Personnel Cost per Faculty Member. First, it

is important to get the plantilla per department including total annual compensation. Second, the total annual compensation is proportionately spread over the faculty loading for the entire year to arrive at the direct teaching cost.

To costs were allocated based on the time spent each week on the following: Undergraduate Teaching Graduate Teaching Administration Research Extension Services All Others

• Direct Cost per Student per Department for Personnel Services.

Information needed to accomplish this worksheet was the subjects and units taught by the faculty member for the entire year, the number of sections taught, and the class size per section taught. A subject classification was also included for sorting purposes.

Research Methodology 16

To arrive at a cost per student per faculty member for personnel services, the total teaching expense (direct personnel costs) per faculty member is divided first by the number of sections taught to arrive at a cost per subject per faculty member. This quotient is then divided by number of students enrolled in the class to get the cost per course per student. This second quotient is further divided by the number of units the course is equivalent to. The steps were repeated for each of the faculty members in the department.

Since there could be more than one faculty member teaching a subject, for instance English, the unit costs of all faculty members teaching English are added then divided by the total number of faculty members teaching English. The resulting figure is the average cost to a student to enroll in one unit of English. So, if one were to compute the direct personnel costs to a student to take a total of 12 units of English as pre-requisite to graduating with a particular degree, simply multiply the average unit cost per student for English by 12 units. Therefore, if the above procedure is done for all major subject categories1, then the direct teaching cost per degree per student can be readily attained. It can also be presented per year, thus fully disclosing how costs to educate may increase as a student progresses to higher years. The flowchart or curriculum is necessary to accomplish this latter task.

• Direct Cost per Student for MOOE. For the computation of the MOOE per department, the direct operating cost of the department was derived. This included any college or university expense directly related to running the department like laboratory expenses. If this was not readily available, the figures were extracted from the financial statements. The direct MOOE was simply divided by the total number of students who took enrolled in subjects offered by the department.

• Indirect Cost per Student. The indirect cost refers to all costs not

directly shouldered by a particular department. For the purpose of this study, this indirect cost was broken down ultimately per student. If the cost could be assigned to specific departments (as per usage or size), the amount was segregated, included in the direct MOOE and divided by the number of students who contributed to the cost. Other costs, such as library services, cafeteria services, registrar’s office, accounting office, etc. were divided by the total student population to arrive at an indirect cost

1 It is advisable to group similar subjects instead of computing a unit cost for all possible subjects. There could be for instance a unit cost for basic Mathematics and advanced Mathematics. This is where the subject classification becomes useful. The research team suggests three categories: (B) basic, (C) cognate, (M) major, and (E) elective.

Research Methodology 17

per student. The personnel costs related to administration, research and extension services that were removed from the personnel services expenditures formed part of indirect costs. These personnel cost were added to costs that could be directly assigned either to research or extension services. The sum was then divided by the total student population.

To recap, total indirect cost is the sum of: (1) costs of running the university that cannot be directly allocated to each department such as library services, IT services, medical services, etc. (2) portion of personnel services, earlier removed, of teaching faculty members who rendered administrative work, research, and/or extension services.

• Cost per Student per Year. The cost per student per year is simply an addition exercise. The figures derived from direct personnel costs, direct MOOE, and indirect costs were added.

• Cost Per Student per Degree. The costs a student would incur per

year, dictated by the subjects taken, were added to arrive at a cost per student per degree. The research team however recognizes that the costs are not stagnant each year and thus a multiplier has to be factored in. This step was not performed for the pilot study.

3.5.6.2 Individual Case Analysis. Each of the individual cases had to be analyzed. Again for the pilot study, this was limited due to the confidentiality of the information gathered. The results however are expected to be presented in the report of subsequent phases.

Basically, the research team recommends the following analytical process to make sense of the information generated:

• Compare the different unit cost per faculty member within a

department. Explain variance possibly due to faculty rank, allocation of faculty hours, classification of subjects (basic or major), and class size.

• Compare the different unit costs per department within a college. Explain variance possibly due to composition of faculty members, number of course offerings, and class size.

• Compare the different unit costs per college for the entire university. Explain variance possibly due to composition of faculty members, nature of major, etc.

• Compare the different unit costs per department with other departments. Explain variance possibly due to composition of faculty members, number of enrolled students, additional MOOE expense for laboratory, etc.

Research Methodology 18

• Evaluate efficiencies and standards of quality. For instance look into class sizes, utilization of space, investment in facilities.

• To evaluate quality of university consider acceptance/rejection rate into the university, percentage passing rate as compared to national passing rate of government licensure examinations, and accreditation levels by CHED. Consider research output of the university. Review student: faculty ratio.

• Consider additional expenses that would be incurred to upgrade the standard of quality for each department, college, or for the university in general.

• Other factors that may affect efficiency and quality are access to donor grants.

3.5.6.3 Comparative Case Analysis. For the pilot study, the comparative analysis was largely focused on discussion differences in research experience for the SUC and non-SUC. However, for subsequent phases of study on normative financing, the research team recommends the following analytical framework.

• Compare unit costs per department with similarly situated

departments in other universities. Explain variance possibly attributed to faculty qualification, compensation levels, allocation of faculty loading, class sizes, etc.

• Compare loading policies between universities. • Evaluate efficiencies and standards of quality as compared with

other HEIs using the factors used in the individual case analyses. Look into cost per student for library services, etc.

3.5.7 Modification of Formula. As the HEIs were being analyzed, it became evident that some information was harder to get than others. The level of detail of information from the original design of the research was tedious for universities not operating with a computerized accounting system and specific cost centers. Since the algorithms could get pretty complicated, the research instrument and cost analytic framework was revised to be more accommodating to the lack of detail. Initially, it was envisioned that costs would be pro-rated on different measures. For instance expenditures can be allocated based on student population or floor area used. However, this was too tedious and had relatively little value added. Moreover, the initial research design called for allocating the different non-teaching expenditures on different bases. This was not followed. Instead a uniform cost per student was computed by lumping together administrative costs, research costs and extensive services expenditures and dividing simply by total student population.

Research Methodology 19

Moreover, the initial formula presented by the research made aggressive use of averages. It was initially thought that the costs per subject could be lumped and simply divided by the average class size. Given the arguments presented in Appendix A, it was decided that the analytical method be modified to take into account differences not only within the department but among the different classes themselves. Thus, a faculty member teaching 4 different sections of the same class can effectively produce 4 different cost per student since the class composition could be different.

To illustrate, faculty A with direct teaching salary of P29,572.85 teaches 4

sections, its cost per course is P7,393.21. By treating each class as individual case with class sizes of 58, 30, 10 and 43, cost per student of P127.47, P246.44, P739.92, and P171.94. This will yield an average cost per student of P321.29. However, if the cost per course is simply divided by average class size of 35.25, the average cost would only be P209.73.

Given the discrepancy, the research team presents the different formula that could

be used and leaves the judgment to the decision-makers.

Research Methodology 20

PART II – CASE STUDY REPORTS, ANALYSIS AND CONCLUSION The second part is composed of three chapters. The first chapter describes the results of the study on an individual basis. It presents sample figures for identified departments/degrees and a simple analysis of these figures. As mentioned earlier, the full analysis, especially of the private HEI, was not discussed but shall be included as part of the research output of subsequent researches. This is so because of the highly confidential nature of the actual costs. The next chapter compares the results of the two cases. Since little was done in terms on analysis on the individual cases, this chapter covers more the comparison in data gathering between a SUC and a non-SUC. Finally, the last chapter presents conclusion and recommendations for subsequent research on normative financing, in particular, and future studies, in general.

Cost Analysis 21

CHAPTER 4 Cost Analysis

4.1 Sample Costing for a Private University The private university test case falls under the “high quality/high cost” category. It offers a variety of courses through its colleges, although its unique and evolving financial structure means that those colleges that have become financially autonomous under its set-up (i.e. are called “professional schools”) were not considered in this study. After all, the rationale for the granting of financial autonomy is the ability of such a college to pay market-or-better-than-market rates for its faculty members and thus does not require an “umbrella” organization such as a university with which to share costs. Based on the methodology, there are now three sets of data: (a) a cost per student per subject taken; this appears as a large spreadsheet containing

said information for every subject offered by the private university during the year in question; the research team has taken a typical student’s flowchart and matched each subject that needs to be taken to the appropriate cost of that subject;

(b) an MOOE per department figure, which is to be added as an annual cost for each

subject taken; (c) an annual indirect cost, which rounds out the total. Case 1: The Cost of a BS Economics Degree2 Subject (3 units, except when specified) Cost Per Student (Php) Algebra 1 726.72 Accounting 1 798.17 English 1 1328.79 History 1 879.45 Religion 13 1172.85 Philippine Government 970.95 PE 1 (2 units) 418.25 Algebra 2 781.75 Economics 1 1087.02 Accounting 2 910.84 2 Total academic units: 175 3 It is interesting to speculate as to whether any “Establishment Clause” provisions would be violated if public funding were channeled toward religious education.

Cost Analysis 22

English 2 1410.69 Computer 1 907.81 Sociology 1094.45 PE 2 (2 units) 364.41 Calculus 1 797.28 Economics 2 1165.67 Accounting 3 830.80 Filipino 1 951.78 Computer 2 1278.40 Science 1 1584.06 PE 3 (2 units) 426.27 Total Direct Costs Per Student 19886.41 Add Indirect Costs Per Student 29,390.09 Cost for First Year: 49,276.50 In the student’s second year, the costs are as follows: Subject (3 units, except when specified) Cost Per Student (Php) Calculus 2 1284.29 Literature 1 1003.86 Filipino 2 946.42 Religion 2 1271.25 Philosophy 1 1097.08 Science 2 1614.35 Microeconomics 1360.66 Macroeconomics 1513.35 Economic Statistics 1797.48 Literature 2 1037.33 Science 3 1031.50 General Psychology 841.25 International Economics 1235.99 Economic Development 1674.22 Econometrics 1378.13 English 3 1648.22 Religion 3 1245.89 Science 4 919.15

Cost Analysis 23

Total Direct Costs Per Student 22,900.42 Add Indirect Costs Per Student 29,390.09 Cost for Second Year: 52,290.51 Finally, in the third year, the following costs obtain: Subject (3 units, except when specified) Cost Per Student (Php) Mathematical Economics 1522.33 Public Finance 3365.39 Economics Research 1640.99 English Elective 1013.18 Foundations of Logic 1145.42 Operations Research 2691.56 Economics Elective 1 1241.06 Thesis Writing 1420.49 Rizal 877.66 Religion 4 1207.44 Economics Elective 2 1540.67 Economics Elective 3 959.78 Total Direct Costs Per Student 18,625.97 Add Indirect Costs Per Student 29,390.09 Cost for Final Year: 48,016.06 Total Cost of Producing 149,583.07 a BS Economics Graduate To make the analysis of cost structures more meaningful, we first present the data for Case 2 below, as this should make comparisons easier:

Cost Analysis 24

Case 2: The Cost of a BS Chemistry Degree4 A BS Chemistry degree takes 3 years and 1 term to complete. It is probably worth noting for future studies that flowcharts may change quite frequently as departments decide to add subject requirements to the program. Our sample university, in particular, has reached a PAASCU accreditation level that allows it to do this. As such, the flowchart that was used as a basis for this work has 6 additional units from the previous year’s version. Subject (3 units, except when specified) Cost Per Student (Php) Inorganic Chemistry 1 3346.22 Chemistry Lab 1 (2 units) 2355.11 Computer 1 1390.84 Math 1 1233.57 Religion 1 1222.85 Filipino 1 951.78 PE 1 (2 units) 364.41 Subject (3 units, except when specified) Cost Per Student (Php) Inorganic Chemistry 2 2061.44 Chemistry Lab 2 2355.11 Chemistry Math 4479.85 Math 2 1440.74 Religion 2 1271.25 Philosophy 1 1097.08 English 1 1282.27 PE 2 (2 units) 426.27 Analytical Chemistry 1594.25 Analytical Chemistry Lab (2 units) 2129.74 Computer 2 1684.45 Math 3 1585.63 Filipino 2 946.37 Literature 1 1004.73

4 Total academic units: 175

Cost Analysis 25

PE 3 (2 units) 418.25 Total Direct Personnel Costs 34,642.22 Add Indirect Costs Per Student 29,390.09 Cost for First Year: 64,032.31 For the second year, the following data obtain: Subject (3 units, except when specified) Cost Per Student (Php) Organic Chemistry 1 2355.19 Organic Chemistry Lab 1 2677.95 Physics 1 2206.77 Math 4 1675.10 History 879.45 English 2 1394.90 Organic Chemistry 2 1574.62 Organic Chemistry Lab 1941.58 Physics 2 1221.46 Physics Lab 1 1586.03 Math 5 3185.45 Religion 3 1245.89 Rizal 877.66 Subject (3 units, except when specified) Cost Per Student (Php) Instrumental Methods 1 1408.13 Instrumental Methods Lab 2224.59 Physics 3 1477.21 Physics Lab 2 1496.77 Differential Equations 1214.11 Sociology 1094.45 English 3 1743.70 Total Direct Costs Per Student 33,481.01 Add Indirect Costs Per Student 29,390.09 Cost for Second Year: 62,871.10

Cost Analysis 26

For the student’s third year, we have: Subject (3 units, except when specified) Cost Per Student (Php) Biochemistry 1 2428.52 Biochemistry Lab 1 2094.82 Physics 4 1400.18 Physics Lab 3 2151.15 Chemistry Seminar 1 2287.34 Chemistry Research 1 2287.34 General Psychology 841.25 Literature 2 1037.33 Biochemistry 2 1594.25 Biochemistry Lab 2 2508.32 Organic Chemistry 3 1448.46 Physics 5 1440.08 Chemistry Research 2 7934.72 Religion 4 1207.44 Analytical Chemistry 2 1969.68 Physics 6 4369.22 Biology 2565.74 Biology Lab 3561.92 Chemistry Research 3 8852.42 Statistics 2229.1 Economics 1087.02 Total Direct Costs Per Student 55,023.30 Add Indirect Costs Per Student 29,390.09 Cost for Third Year: 84,413.39 For the final term (with MOOE and indirect costs adjusted accordingly): Subject (3 units, except when specified) Cost Per Student (Php) Analytical Chemistry Lab 2 2355.11 Chemistry Elective 1 1260.55 Chemistry Elective 2 2287.34 Inorganic Chemistry 3 3346.22 Bioethics 1641.18

Cost Analysis 27

Total Direct Costs Per Student 10,890.40 Add Indirect Costs Per Student 9,796.69 Cost for Final Year: 20,687.09 Cost to Produce 232,003.89 a BS Chemistry Graduate We must begin by stressing that the data obtained from this pilot study are intended to eventually become sample observations in a cost-function regression. The larger project is to estimate the cost of producing a degree after controlling for quality levels. The following sections are in order as we examine the properties of the individual cost structures of our two sample degrees, as well as survey related issues:

4.1.1 Patterns in Personnel Costs. The average personnel cost per subject that an Economics major incurs is P854.60 – for a Chemistry major, it is P1769.40. Nothing about this is unusual as it is merely reflective of the higher proportion of Phd-holders in the Chemistry Department. One must also note that since benefits are pro-rated according to tenure, departments with more long-staying staff are also going to experience higher wage bills.

We may look closer at the individual accounts and see that the 3 most expensive subjects an Economics major takes are Public Finance (P3108.78 per student), Operations Research (P2134.95) and Economic Development (P1417.61). Again, this is to be expected as all 3 are “major” subjects and are generally given to more senior faculty members. The classes are also smaller, averaging 25 students or so each time they are offered, as a number of majors fail pre-requisites to the subjects above and are thus unable to proceed.

The 3 least expensive subjects in the Economics program, on the other hand, are expectedly “general” or “basic” courses – Science 4 (P326.05), Science 3 (P438.32) and Algebra 1 (P471.62). This is so, again, because relatively junior instructors are usually assigned to handle these courses, apart from the fact that it is common for these subjects to feature near-maximum student counts.

For Chemistry, the 3 most expensive subjects are Research 3 (P8259.29), Research 2 (P7341.59) and Physics 6 (P3896.73). These, in fact, rank among the 10 most expensive taught for the entire university. However startling the figures may seem at first, they are simply the result of highly-paid senior professors handling very small classes. Research subjects are taken toward the

Cost Analysis 28

end of the program when, presumably, most of the original “block” have been screened out.

Chemistry’s 3 least expensive subjects are likewise basic ones – General Psychology (P497.79), Filipino 1 (P659.83) and Chemistry Elective (P667.42).

4.1.2 Patterns in Departmental MOOE. We begin by explaining that three variables clearly determine the size of department MOOE: firstly, the existence (and number) of in-house research and publication institutes, as their costs are considered part of MOOE. Secondly, the number of programs offered by the department, as the administration of each program entails its own costs. Finally, there is the number of majors (or, in the case of first-years, prospective majors) registered with the department. In a very real sense, departments have to walk a tightrope. On the one hand, additional programs and extension services help increase the departmental profile, and this in turn may have a salutary effect on enrollment, especially if the programs are considered innovative. If one examines the figures across departments in the university, for instance, one will notice that the 3 out of the 4 highest MOOE figures belong to the Biology Department (P946.95), Chemistry Department (P593.13) and Physics (P482.49) – which have more “traditional” courses, while those departments that offer new degree programs more often have lower MOOE – see Business Management (P230.63), Marketing Management (P263.87). Yet new programs are a challenge to sustain, especially given a very unpredictable (some have said distorted) set of student preferences. Many departments in recent years have had financially painful experiences with “donor-driven” programs. A typical story would involve an international donor giving seed money to establish a program, new course offerings been advertised, student counts rising in the first few years, then tapering off as student preferences change. The department then suffers from very high MOOE until the last major of the defunct program graduates. This being a private university, where all costs are internalized, there are numerous in-house mechanisms designed to maintain levels of efficiency and control costs. Some of these include rules on the dissolution of classes (the minimum number is 14 for undergraduate subjects and 6 for graduate subjects), and the offering of subjects (the fully computerized enrollment process allows each dean’s office to track student enlistment; subjects are opened only when demand reaches a threshold level). Other policies spell out penalties (such as

Cost Analysis 29

phasing out or the reduction of departmental budgets) for keeping unsustainable programs. At the university level, there exist directives for maintaining optimal full-time/part-time faculty ratios as well as “salary caps” designed to guide hiring practices. Departments are also classified according to size – “large” or “very large” departments (based on the number of faculty and course offerings) are given proportionately higher operating budgets each year.

4.1.3 Behavior of Costs over the Program and the Need for Cross-Subsidies. In this section, we trace the movement of costs as a student proceeds through a given program and note the implications for both university and normative financing authorities.

First, we calculate that a Chemistry degree costs 1.55 times an Economics degree. In future studies, the fact that the Chemistry Department is a CHED Center of Excellence, while the Economics Department is not should be noted, as estimates should control for quality. Returning to the data above, we see that our composite Economics student costs P49,276.41 to educate during the first year, then P52,290.51 and P48,016.06 for the second and third years respectively. The figures are quite stable and reflect the impact of higher personnel costs as a student takes major subjects. The pattern for Chemistry is slightly different – P64,032.32 for the first year, P62,871.10 for the second, P84,413.39 for the third, and P20,687.09 for the final term. The markedly higher cost of the third year reflects the impact of extremely expensive research subjects taken by the student. What is interesting to note at this point is the phenomenon of cross-subsidies that operates quite extensively within this private university. We see this in the fact that the average tuition for an Economics student is about P90,000 a year – almost twice the actual cost of the program! On the other hand, a Chemistry student pays roughly P100,000 a year in fees – not enough to cover actual costs, if we adjust for the fact that the Chemistry Department has very few majors (as opposed to those who merely take chemistry subjects). In order to keep fees manageable and stable, it is clear that this private university uses revenues from low-cost, high enrollment colleges like Business and Liberal Arts to augment those of high-cost low-enrollment ones like Science. Although not within the scope of this pilot study, we suggest that these cross-subsidy mechanisms should be studied more closely as they hint at the existence of, say, an optimal number of colleges for a university. The private

Cost Analysis 30

university in question has, in recent years, experimented with the granting of financial autonomy to a number of its colleges. This was supposed to allow said colleges to offer better-than-market rates to its instructors, paid for by proportionately higher tuition fees charged. All in all, however, the undertaking has produced disappointing results – and a large part of the explanation lies in the autonomous colleges being less able to take advantage of the common pool of university resources (under the arrangement, they would have to “pay” for their use), while leaving the under-subscribed colleges to fend for themselves in the absence of a source of subsidies. The result is that further “professionalization” of colleges has been put off until more modifications can be made to the experiment.

4.2 Sample Costing for a State University: Teacher Training and Related

Disciplines Our analysis of the sample state-university will, unfortunately, be limited to examining cost structures. Unlike the private university described earlier, we are not privy to the policies and mechanisms of the various departments within this institution – only to external indicators of cost and quality. Nevertheless, in the tables below, we find a similar computation of the cost of various degree offerings from this university. We examine two cases: a bachelor’s degree in secondary education, and a degree in dietetics. Case 1: The Cost of a Bachelor of Secondary Education Major in Physics and Technology Degree5 Subject Cost Per Student (Php) Math 4 4199.70 Science 2 2123.78 Filipino 1 1957.59 AGP 1 2152.15 Eng 1 1957.59 PE 1 1957.59 Euth 1 1528.87 Physics 1 3035.28 Chemistry 1 3035.28 Math 7 2099.85 Eng 2 1957.58 Fil 2 2194.82 VE 1 1528.88

5 Total academic units: 190

Cost Analysis 31

PE 2 1528.88 Total Direct Personnel Costs 29,728.99 Add MOOE for Chemistry Department 4,110.06 Add Indirect Costs Per Student 21,543.00 Cost for First Year: 55,382.05 For the second year, we have the following figures: Subject Cost Per Student (Php) Ed 1C 2835.52 Math 13 3499.75 Chem 2 3035.28 Phys 2 3035.28 Phys 3 3035.28 Tech 1A 4628.35 Lenf 1 3471.26 Per Ed 645.62 Ed 2C 2935.52 Ed 3C 2935.52 Math 14 3499.75 AGP 2 2152.15 Litt 1A 1957.59 Tech 1E 4628.35 Phys 4 3035.27 Per Ed 645.62 Per Ed 645.62 Total Direct Personnel Costs 46,271.75 Add MOOE for Chemistry Department 5,374.69 Add Indirect Costs Per Student 21,543.00 Cost for Second Year: 73,639.44 Then for the third year, we have Subject Cost Per Student (Php) Ed 4C 2935.52

Cost Analysis 32

IT 1 3380.09 AGP 4 2152.15 Sci 3 2276.46 Phys 5 3035.28 Phys 6 3035.28 Tech 2A 4628.35 KAS 1 2152.15 Per Ed 645.62 Ed 6C 2935.52 Ed 7C 2935.52 Eng 3 1957.59 IT 2 3380.10 AGP 5 2152.15 Com SC 3380.10 Phys 9 2276.46 Tech 2E 2869.53 Per Ed 465.62 Total Direct Personnel Costs 46,773.51 Add MOOE for Chemistry Department 5,690.85 Add Indirect Costs Per Student 21,543.00 Cost for Third Year: 74,007.36 And finally, the fourth year figures come to Subject Cost Per Student (Php) Ed 8C 2935.52 AGP 6 2152.15 Litt 2 1957.59 Com Sc 3380.10 Sci 10 2276.46 Phys 12 2276.46 Phys 13 2276.46 Psych 2194.82 Hum 1 2697.06 Ed 9C 11742.09 Total Direct Personnel Costs 33,878.71

Cost Analysis 33

Add MOOE for Chemistry Department 3,161,58 Add Indirect Costs Per Student 21,543.00 Cost for Final Year: 58,583.29 Cost to Produce 261,612.12 a BS Ed Graduate We then proceed to Case 2, which features a non-education undergraduate degree Case 2: Cost of a Bachelor of Science in Nutrition & Dietetics Degree6 Subject Cost Per Student (Php) Fil 1 1957.59 Eng 1 1957.59 Reading 2116.80 Math 1 2099.85 AGP 1 2152.15 Sci 1 2770.91 PE 1 1528.88 Eng 2 1957.59 Music 1 2687.06 Psych 2194.82 Math 2 2099.85 VE 1 2194.82 Math 15 2099.85 PE 2 1528.87 Total Direct Personnel Costs 29,346.66 Add MOOE for Chemistry Department 4,426.22 Add Indirect Costs Per Student 21,543.00 Cost for First Year: 55,315.87 For the second year, we have the following figures: Subject Cost Per Student (Php) Chem 1 3035.28 Eng 3 1957.59

6 Total academic units: 156

Cost Analysis 34

Bio 4 2770.92 Math 16 2099.85 ND 1 2123.78 ND 2 2123.78 PE 3 1528.87 Fil 2 1957.59 Chem 3 3035.28 ND 3 2123.78 ND 9 2123.78 Bio 11 2770.91 Psych 3 2194.82 PE 4 1528.88 Total Direct Personnel Costs 31,375.11 Add MOOE for Chemistry Department 4,426.22 Add Indirect Costs Per Student 21,543.00 Cost for Second Year: 57,344.32 Then for the third year, we have Subject Cost Per Student (Php) AGP 3 2152.15 Eng 9 1957.59 ND 10 2123.78 ND 15 2123.78 ND 4 2123.78 ND 5 2123.78 AGP 4 2152.15 Eng 13 1957.59 Chem 6 2276.46 ND 14 2123.78 ND 7 2123.78 ND 12 2123.78 ND 6 2123.78 Total Direct Personnel Costs 27,486.19 Add MOOE for Chemistry Department 4,110.06 Add Indirect Costs Per Student 21,543.00 Cost for Third Year: 53,139.24

Cost Analysis 35

And finally, the fourth year figures come to Subject Cost Per Student (Php) AGP 2 2152.15 AGP 6 2152.15 Eng 12 1957.59 ND 8 2831.71 ND 10 2123.78 ND 11 2123.78 ND 16 2831.71 Practi 11742.09 Total Direct Personnel Costs 27,914.97 Add MOOE for Chemistry Department 3,477.74 Add Indirect Costs Per Student 21,543.00 Cost for Final Year: 52,935.70 Cost of a Bs Nutrition Graduate 218,735.14

4.2.1 Composition of Program Costs. Given that the average tuition fee per term at this state university is about P225, it is interesting to look at the actual costs incurred running a COE-quality teacher training program. It must be noted immediately that scale appears to be the primary determinant of per unit costs. Large differences in the number of sections carried by each department as well as total enrollment within the college account for the discrepancies in per unit personnel costs. With more time-series data, it would be possible to construct a cost function using these figures, but at the moment, we are limited to analyzing the spread of the cost values. The foregoing tables indicate three important characteristics of the cost structure: first, the relative stability of most accounts. Unlike our sample private university, both departmental MOOE and personnel costs do not fluctuate by more than a few hundred pesos in either direction. The most frequently recurring per unit costs, for instance, are P1957.59 for, say, English courses, P2152.15 for AGP and P2123.78 for Science subjects. It seems that there is little or no variation in the costs of the subjects taught, regardless of whether they are basic or advanced courses.

Cost Analysis 36

We surmise that this flatness of costs is due to the relative lack of market incentives for performance within the institution. The salary scales in SUCs tend to be flatter than those in private universities as a result of budget constraints and this allows those with tenure to “catch up” with those who may have come in with higher academic ranks. The result would be a departmental wage bill that is evenly distributed across lecturers. Second, we must look at the efficiency implications of this situation. It seems clear that when future phases are carried out, the data will indicate that this state university incurs much lower personnel costs than a comparable private institution. If we accept the idea that quality is costly, then we can only conclude that a significant part of the university’s “efficiency burden” is borne by faculty members who are paid less than the median wage for the program. A final pattern that may be recognized has to do with the relatively high personnel costs for math subjects in all program. Math subjects cost twice as much as non-math courses across the board (for some education courses, they cost 8 times as much as non-math courses!). There are two possible explanations for this. First would be the higher academic qualifications of those handling math and related subjects; the other reason could be the increased number of units given to math subjects – a quick examination, after all, would show that the per unit costs do not differ substantially from the other offerings. 4.2.2 Relatively Large Indirect Costs. The figures also indicate per student indirect costs that amount to roughly 3 times the level of personnel costs (P21,346 as compared to about P5000 for MOOE expenses). This suggests that if all costs of this state university were to be internalized, the bulk of the expenses would be on the maintenance of facilities and services. In a sense, this can be expected as it is less likely that savings can be obtained from property, plant and equipment than it can from, say, a fixed but low salary scale, especially when this sort of capital has historically been maintained at a relatively small expense. Overall, the costs of these high-quality degrees (as certified by CHED) indicate that the market (i.e. private-institution) price of education hovers around P20,000 to P25,000 a semester for essentially non-lab program, even as we stress that these are static figures and do not reflect either generally increasing prices nor future quality targets. 4.2.3 Public Provision. Another important question that must be addressed is the level of government provision of education that has strong public goods

Cost Analysis 37

characteristics – such as teaching. A well-established economic principle says that individuals should pay for courses whose returns are primarily private. The primary examples of this are business degrees. On the other, there are degree programs that manifest strong externalities or spillovers (i.e. benefits to society and not just to the individual). Science and technology courses are good examples of this for the research they create, but one can make the argument that teaching also falls under this category, as there is a pressing social need not just for instructors, but instructors of high caliber.

Having said this, we must determine whether the normative financing framework takes the narrower view of efficiency – that is to say, the balancing of private costs and benefits. For if this is so, then there probably exist good reasons to scale down funding for many state universities, given the slackness with which they manage resources. But if the social welfare principle is followed instead, one can then make the argument in favor of much larger endowments to courses taught at normal universities, since in effect, the institution is “underpaid” for the services it provides. In this case, the monetized value of the social benefit should be used to balance off the cost of maintaining facilities, paying personnel, and all other activities related to operating the university. A computation such as this raises more questions than provides answers, given the number of obvious qualifications. Firstly, it must be noted that neither research nor extension services are considered in the formula and as such, the final figure is to be treated as the sum of purely instructional and maintenance activities – with no room for improvements in the quality of services. To the extent that the government sets its own research agenda and targets for accreditation, the appropriate cost adjustments must be made. Secondly, personnel costs are entirely dependent upon the willingness of faculty members to accept present wage scales. Preliminary comparisons with the ADB paper on normative financing (Table A9 p115) suggest that our formula produces a cost per student figure that is several thousand pesos less than the ADB cost for an education student (there computed as P18,507/full-time entry). The ADB figure is an average taken over a number of private and public universities throughout the country and is evidence that our sample university probably pays its personnel lower than the median rate – a situation that is hardly sustainable. Thirdly, we point out that, again, market distortions on the demand side are likely to affect cost computations as well. Take the well-documented preference for law degrees, which may, in part, explain the overwhelming

Cost Analysis 38

number of students enrolled in CASS. On the one hand, the college benefits from this large population, as costs per unit tend to be quite low. It does not follow, however, that this figure should be interpreted as a sign of the college’s “efficiency”. Rather, the low cost can itself be viewed as a reason for the course being over-subscribed.

Cost Analysis 39

CHAPTER 5 Recommendations, Insights and Conclusion

5.1 Recommendations on Research Methodology There were several constraints on the analysis of information since the number of HEIs reviewed was brought down to only 2. For subsequent studies however, we recommend that the following be undertaken.

• Encoding of data using the analytical worksheets. However caution should be exercised since the totals would have to tally on the aggregate level.

• Data generated should be in soft copy for easy manipulation of data. • Subjects should be classified into general education/basic, cognates, major

courses and electives. This additional step allows a richer evaluation of the costs to service a student and the costs associated for a student to get a degree.

• In the analysis of direct MOOE, it is recommended that the analysis include not only a cost per student but a cost per faculty member. It is possible that a department cost is higher than normal because there are more faculty members. Dividing the direct MOOE first by the total number of faculty members within a department may allow analysis on the appropriate size of the faculty complement with respect to number of students enrolled.

• A multiplier shall have to be imputed for each of the years it takes to attain a degree to determine a more realistic cost per degree.

• Finally, the research team further recommends that the period of analysis be the latest financial statements, SY 2001-2002 for private HEIs and CY 2002 for SUCs.

5.2 Insights

5.2.1 Market Failures7 in Philippine Higher Education. We come now move to a discussion of market failures in higher education, and how these market failures ought to inform our cost estimates.

7 A market failure is commonly defined as a situation in which the free operation of demand and supply forces still does not result in a socially desirable outcome.

Recommendations, Insights, and Conclusions 40

The table below shows changes in the composition of higher education graduates over a 10-year span. Together with findings similar to the ones given in chapter 4, it is a commonly used indicator of the “relevance” of the country’s labor training to its industrialization needs. On the one hand, the figures confirm many widely held perceptions about the most common example of a market failure in higher education: the mismatch that exists between the needs of a developing country and the output of its universities. Perhaps the best way of describing the situation is one of continuity and change, with different types of market failures. For one, it is significant that Philippine higher education still continues to be dominated by an urban professional orientation, with no sign of developing a requisite preference for hard sciences and research. Business, commerce and accountancy still make up about a quarter of all graduates. Education continues to account for 15% of the pool, with the arts & sciences taking about 10%. The main changes are said to be in engineering and health, which doubled their share in 10 years. Of course, this increase is almost entirely explained by the rapid increase in enrollments in the more popular specialist IT and computer science colleges.

1987-1988 1997-1998 Subject Graduates % Subject Graduates % 1 Business 73.3 26.4 Business 76.5 25.2 2 Med/Health 52.2 18.8 Engineering 72.7 23.9 3 Teacher Ed 45.4 16.4 Education 40.0 13.2 4 Maritime 32.7 11.8 Health 34.7 11.4 5 Engineering 32.0 11.6 Arts/Sciences 16.7 5.5 6 Arts/Sciences 27.8 10.0 General 13.6 4.5 7 Agriculture 8.3 3.0 Agriculture 11.0 3.6 8 Law 2.4 0.9 Law 3.3 1.0 9 Criminology 2.1 0.8 Mass Comm 3.3 1.0 10 Religion 1.1 0.4 Other 31.9 10.5

Table 5.1 Graduates by Subject, 1987-88 and 1997-1998 (in thousands)

Source: PCER Report (2000)

Recommendations, Insights, and Conclusions 41

On the other hand, the table also does indicate how quickly the education market responds to changes in employment prospects. For instance, there is the noticeable drop in graduates from health-related professions, from 18.8 to 11.4 percent – no doubt attributable to the less sanguine job prospects both here and abroad. The same may be said of maritime education, which dropped out of the “Top 10” list. Furthermore, the demand for post-graduate courses has not increased from its historically low figure (in a recent survey, only 1.5% of newspaper advertisements carried postgraduate requirements for entry), except of course in the teaching profession. But even this has been interpreted as evidence of a “demand spiral” in education in which graduates would rather pursue additional degrees rather than settle for entry-level work – yet another socially inefficient allocation of resources. The coupling of mismatch problems along with the high sensitivity of student choices to job market signals is what has led experts to characterize the education sector as “unplanned”. Perhaps the most telling statistic showing the extent of the labor-education mismatch is the figure for the number of graduates taking jobs outside their field of training. The CHED Graduate Tracer Study of 1998 reveals an alarming decline in the number of graduates finding work in the areas they prepared for. The only exception was nautical science, which increased by 9%. In computer science, the percentages went from 76 to 39 (!), in fisheries from 67 to 21, in law from 62 to 40, in nursing from 85 to 41, in physical sciences from 64 to 20 and in teacher education from 77 to 42. In a calculation whose result can only be described as scandalous, it was determined that the actual unemployment rate may be discounted by about 40% by removing those graduates with high search criteria (say, those that would only accept employment in white-collar jobs in the urban sector) and those no longer in the labor market (say, those simply not interested in finding a job after repeated rejection). The mismatches themselves are explainable in terms of market failures. On the demand side, there is the well-known “fetish for diplomas” that causes students to enroll in heavily subscribed courses without being able to properly read job market signals. On the supply side, there is the failure of capital markets to provide incentives to undertake the most efficient courses. The lack of well-functioning loan programs, subsidies to socially preferred but expensive courses etc serve as structural obstacles to a more rational system of higher education.

Recommendations, Insights, and Conclusions 42

Quite apart from the standard economic explanations for the state of the education sector are comments that these low entry rates are themselves indicative of a need for broader preparation involving generic or problem-solving skills. It has even been suggested in both the ADB and World Bank technical reports on the sector that a “bridging year” may be necessary to prepare students for proper specialization – the sort that will increase their mobility and competitiveness internationally in the absence of domestic opportunities. In the meantime, we strongly suggest that the normative finance framework develop the means to account for the effects of these significant market distortions present in Philippine higher education – especially since the PCER Report makes recommendations for rationalizing student degree choices. 5.2.2 The Worrisome Case of the Literatura at Wikang Filipino Department. It takes a case like the Literature at Wikang Filipino (LWF) Department to drive home the point about how the pre-occupation with “cost efficiency” can result in harmful social outcomes. We include this section in order to encourage normative financing authorities to take a wider view of financing issues and to balance cost considerations against other important social objectives. The Literatura at Wikang Filipino Department is a troubling example of a well-performing department suffering from serious distortions in the education market. The first thing that must be said about it is that it is an exceptionally performing department by academic considerations – indeed, it has been named a Center of Excellence by CHED. In its faculty are some of the country’s most established and most promising writers. By all non-economic accounts, it should be a flagship department. The trouble, however, lies precisely in its economic circumstances. The LWF Department has the 5th highest MOOE bill in the private university. Its personnel costs are driven up by the fact that most of its staff is made up of Phd holders and promotion can be quite rapid within this department8. And then there is enrollment. By the department’s own count, there are 81 students registered with it – an extremely shallow student base, not helped by the fact that the College of Education has siphoned off those who would wish to do translation studies or related work.

8 Some faculty members have raised concerns about this publicly, pointing out that “anthologies” and “creative works” are put in the same class as “original research” of social scientists, to the relative disadvantage of the latter. Since promotion is based almost solely on publication, it is claimed that a discipline that allows creative work to be credited as research will result in faster promotion for some.

Recommendations, Insights, and Conclusions 43

The department, already working under difficult conditions, is now suffering from an extra squeeze – the reduction of general studies subjects across the board within the university. As departments participate in a movement to increase specialization and prepare students to practice a trade, they find themselves increasing the number of technical subjects at the expense of the humanities, arts, and other courses not “directly related” to the major program. And while clearly this has wide-ranging pedagogical implications, we wish to stress here that departments like LWF have historically survived low enrollment rates by “servicing” colleges with their required literature and language courses. It appears that even this escape hatch looks to be shut soon. This looks to be fate of every department not fancied by a growing yet ill-informed student market. For clearly, it is in our social interest to preserve and encourage literature and language studies – the PCER Report itself gives as a major recommendation the expansion of vernacular programs as a means of improving overall literacy. But the private demand for such courses has not responded accordingly – as the table above shows, students continue to flock to courses that are not just over-subscribed, but also lead to redundancy. A similar argument can be made for, say, a China Studies program. In our sample private university, the China Studies program has just been phased out. From the point of view of private demand, this can perhaps be explained by the preference of students for European studies (a largely “donor-driven”) program. But from a social standpoint, it is hard to explain how the demand for this major can be so low given the increasing importance of China as a trading partner and regional player, as well as the complete dearth of any “China experts” in both academic and policy circles. In a technical workshop, CHED Commissioner Dr Cristina Padolina raised concerns about policymakers using the results of this study to slash the budgets of “inefficient” state universities at a time when what they need is precisely an infusion of funds to improve quality. These concerns can now be supported by evidence that even efficiently-run departments may suffer from what William Baumol called a “cost disease” – the inherent tendency of some industries (in this case, university departments) to experience continued cost increases over time, despite the best efforts at achieving productive efficiency.

Recommendations, Insights, and Conclusions 44

5.3 Conclusion. We take the results if this study as evidence that the following steps must eventually be taken in order to arrive at true economic cost inputs to the normative financing framework: (1) the construction of a cost function, using enough time series data. This is important

for determining the factors which most greatly affect the marginal cost of an additional “place” at a university;

(2) the normative financing framework itself must incorporate dynamic changes such as

the government’s own programs for rationalizing higher education, improving faculty qualifications and standards of living, producing better research etc;

(3) finally, the extent and role of market distortions in higher education must be

incorporated more explicitly. College courses that are over-subscribed necessarily become cheaper – and in such instances, cheapness is not an indicator of efficiency. Therefore, in order for cost figures to be more meaningful, they have to be adjusted to take into account market trends, individual preferences, and the true economic cost of selecting a given degree program.

Recommendations, Insights, and Conclusions 45

PART III – REFERENCES, APPENDICES, LIST OF TABLES AND FIGURES

The third part provides a listing of the various research documents utilized in this research project as well as a list of the tables and figures. The information contained in the following appendices is useful and should dispel ideas on variations to the model. Appendix A provides the arguments using different formulae in arriving at a cost per degree. Appendix B is a sample survey format used to gather data needed for analysis. Appendix C shows the worksheets used for cost analysis while Appendix D describes in detail the steps an analyst should take to accomplish the worksheets.

Part III 46

REFERENCES Asian Development Bank and World Bank. (1999). Philippine Education for the 21st

Century. The 1998 Philippines Education Sector Study. Manila. Johanson, R. (2001). Education Sector Development Program: Synthesis Report.

Manila. Preddey, G. and Nuqui, H. (2001). Normative Financing in Higher Education. Manila. Presidential Commission on Educational Reform (2000). Philippine Agenda for

Educational Reform: The PCER Report. Manila. Yin, R.K. (1994). Case Study Research: Design and Methods (2nd Ed.). Thousand Oaks,

California: Sage Publications.

References 47

APPENDIX A Comparison on Different Formulae to Compute Unit Direct Personnel Costs Per Student

Emphasis is made on the computation of the estimated unit cost for direct personnel expenditures because personnel services readily account for 80-90% of the total university budget. Consequently in arriving at the cost per degree for each student enrollee, the impact of this variable is significant. The decision as to which formula to use has to do with the degrees of confidence. From the perspective of a generalist, a simple average would suffice. After all, it is the costs of several universities averaged out that will eventually be the determinant of the true cost to educate. From the perspective of a numerically oriented individual, the closest estimate to the average cost to complete a degree is highly appreciated. However arriving at the closest estimate requires more time and energy. Understandably the output of cost studies serve as inputs to the normative financing formula. This formula has a significant impact on the budgetary allocations of state universities and colleges. Consequently, the formula must be as credible as possible to convince lawmakers and university officials that it is the better budgetary allocation mechanism. Essentially, we are looking at a model that is defensible. It is the decision makers that have to be convinced, not the analysts. This chapter shows the different formulae discussed by the research team, using the civil engineering third year of an SUC as an example. Essentially, the first formula differs in approach as the denominator for the computation considers only students who are majoring in a particular degree while the second method looks at total figures and averages this out. The next formulae are similar in components but the degree of estimation moves closer to arriving at closer to actual costs under study at a considerable amount of effort. In essence the formulae is similar in approach in the sense that the personnel expenditures are considered are divided by number of sections taught and then by number of students enrolled in the course. The course costs are then added for a one-year period. There are admittedly other ways of computing average costs per degree, true to the adage there are many ways to skin a cat. However, these were no longer presented but analysts can readily derive the computations from the data presented in the examples. The research team is open to discuss any methodology with future researchers and analysts, to address concerns of interested third parties. A. Computing Unit Cost using Student Majors as Basis

This method calls for using the actual college personnel services expenditures and dividing this by the number of students majoring in degrees offered by the department.

Appendix A 48

For instance, the cost to complete an engineering degree is computed as follows: Total College Expenditures for Personnel Services P10,026,748 Number of Engineering Majors 834 Cost of Direct Personnel Services for One Year P12,022.48 Points of Concern: 1. The method did not take into account the costs that have to be removed

from faculty members who spent time doing administrative work, research work or extension services.

2. To major in engineering, it is necessary to take general education courses. This method only takes into the account the costs of engineering. It implies that the costs for teaching mathematics, for instance, should be shouldered solely by the mathematics department. This would mean that the cost per student majoring in mathematics would be artificially higher, which is incorrect since it is known that the mathematics department services the requirements of the entire student population.

B. Computing Unit Cost from Total University Expenditures

This method calls for simply dividing total personnel services expenditures for higher education by the number of sections offered by the university and dividing this quotient by the average class size. Total University Expenditures for Personnel Services (Teaching) P101,683,280 Total Number of Sections Taught (University) 2656 Cost per Course P38,284.36 Average Class Size (No. of Students Enrolled/No. of Sections) 34.89 Cost per Student for a Course P1,097.25 Multiply cost per student for a course by the number of courses in a year. For example, 16 subjects of courses are needed by civil engineer students in the third year, thus arriving at a yearly cost of P17,556.60 Points of Concern: 1. The method is obviously simplistic. 2. The numerator does not remove the personnel services expenditure

unrelated to direct teaching. 3. It also does not consider many of the peculiarities of each department like

the faculty composition, number of sections offered, number of units offered, number of students enrolled, and nature of the subjects.

4. It assumes that all departments are equally efficient (or inefficient) in the utilization of resources.

Appendix A 49

5. However, experience from reviewing SUC financial statements show that this method is convenient as personnel expenditures are presented as a lump-sum figure. For instance there is a total personnel cost for Advanced Education and total personnel cost for Higher Education. These are not normally presented as personnel costs for the different colleges and departments. This being the case, the method provides great ease in computing cost estimates.

6. At this point, it is noteworthy to state that many of the succeeding methods assume that the proportion of students to sections is the same and that the unit equivalents for a course are likewise the same. This is a critical assumption since the teaching expenditures are divided by total number of sections regardless if the course weight is 2, 3, 5, or 7 units. This in effect should not be the case since it is total units that play a more significant role in allocation of teaching expenditures and not number of section.

C. Computing Unit Cost from Total University Expenditures (Direct Teaching)

This method is similar to Method B except that the personnel services expenditures used are that of direct teaching only. Thus, it eliminates the share of costs for doing administrative or research work. Total Direct University Expenditures for Personnel Services P66,944,200 Total Number of Sections Taught (University) 2656 Cost per Course P25,190.58 Average Class Size (No. of Students Enrolled/No. of Sections) 34.89 Cost per Student for a Course P722 Given the same example of a civil engineering student, the annual direct personnel cost per student is P11,552. Points of Concern: 1. This is an improvement of Method B since the matter of the numerator

was resolved. Instead of total personnel expenditures, only the direct teaching expenditure was used.

2. However, like in Method B, this method fails to address all other concerns that are peculiar to the different departments.

D. Computing Unit Cost from College Expenditures

This method calls for getting the direct teaching costs of faculty members in a college and dividing it by the number of students enrolled in the course to arrive at a cost per course. This is done for all departments.

Appendix A 50

Direct Teaching Cost in the Engineering College P4,012,406 Number of Students Enrolled in College 3,066 Cost per Student for an Engineering Course P1,308.68 English P159 x 2 subjects P 318 Mathematics P159 x 2 subjects 318 Accounting P709 x 1 subject 709 Rizal P159 x 1 subject 159 Engineering P1,308 x 10 subjects 13,080 Total for Junior Year in Civil Engineering P14,584

Points of Concern: 1. This method uses direct teaching expenditures only of faculty members in

the department. It does not consider the portion of salaries of faculty members who taught subjects in the department but whose salaries are really lodged with their mother department. Nor does it remove from its costs the share of faculty members who teach in other departments. Thus, there is a question on the accuracy of the numerator.

2. This model also assumes that within colleges, the efficiency rates are the same. Note that the cost of English, Mathematics and Rizal are the same because they belong to the same college. It does not take into account that some departments may offer more sections or have a lesser number of students in a class. Neither does it consider the faculty composition, meaning one department may have more or less doctors or masters graduates.

E. Computing Unit Cost from College Expenditures

This method calls for getting the direct teaching costs of faculty members who taught subjects offered in a department (regardless of their mother department) and dividing it by the number of students enrolled in the course. This is done for all departments. Direct Teaching Cost in the Engineering College P2,297,999 Number of Students Enrolled in College 3,066 Cost per Student for an Engineering Course P749.08 English P383.63 x 2 subjects P 767 Mathematics P383.63 x 2 subjects 767 Accounting P493.75 x 1 subject 494 Rizal P383.63 x 1 subject 384 Engineering P749.08 x 10 subjects 7,491 Total for Junior Year in Civil Engineering P 9,907

Appendix A 51

Points of Concern: 1. This method addresses the concerns of Method E on the use of the

appropriate numerator. However, it still does not address the concerns of finding correct efficiency rates per department.

2. It fails again to consider the other aspects that make-up the department such as faculty composition.

F. Computing Unit Cost from Total College Expenditures

This method calls for getting the direct teaching costs of the university and dividing the costs by the number of sections offered by the department over the total number of sections offered by the entire university. The resulting quotient is then divided by the number of students enrolled in the courses offered by the department. Total Direct University Expenditures for Personnel Services P66,944,200 Number of Sections Taught (College) 144 Total Number of Sections Taught (University) 1328 Total Cost for an Engineering Course P7,259,009 Number of Students Enrolled in College 6,1329 Cost per Student for an Engineering Course P2,367 English P625 x 2 subjects P 1,250 Mathematics P835 x 2 subjects 1,670 Accounting P691 x 1 subject 691 Rizal P582 x 1 subject 582 Engineering P1,183 x 10 subjects 11,830 Total for Junior Year in Civil Engineering P16,023 Points of Concern: 1. This method artificially bloats the teaching expenditure attributable to the

engineering college. In other words, the personnel services budget allocated to the department is much more than the actual expenditures by the department.

2. In this method, the inefficiency of the college of engineering is greatly apparent as average class sizes are only at 20 compared to university average of 34.

3. However this method again assumes that efficiency rates within the college and faculty composition are the same.

9 Figure is annualized because the personnel services is also on an annual basis. For other methods, there is no adjustment if the numerator and denominator have the same period of coverage.

Appendix A 52

G. Computing Unit Cost from Total Departmental Expenditures

This method goes down to the department level and uses the direct teaching costs of the college and dividing the costs by the number of sections offered by the department over the total number of sections offered by the entire college. The resulting quotient is then divided by the number of students enrolled in the courses offered by the department.

Total Direct College Expenditures for Personnel Services P2,297,999 Number of Sections Taught (Department) 106 Total Number of Sections Taught (College) 144 Total Cost for an Engineering Course P1,691,582 Number of Students Enrolled in Civil Engineering 2332 Cost per Student for an Engineering Course P725.37 English P369.12 x 2 subjects P 778 Mathematics P470.84 x 2 subjects 941 Accounting P572.23 x 1 subject 572 Rizal P328.13 x 1 subject 328 Engineering P725.37 x 10 subjects 7,254 Total for Junior Year in Civil Engineering P 9,872

Points of Concern: 1. This method underestimates the direct cost of personnel services that form

part of the cost per degree per student. 2. It fails to account for different unit weights of subjects within a

department as well as the different qualifications of the faculty member. 3. However, if the profile of the subjects and teachers is uniform, this method

would approximate direct teaching cost for one student.

H. Computing Unit Cost from by Grouping Similar Subjects

This method computes the direct teaching costs of each course in a department and divides it by the number of students taught. It does this by grouping together the personnel costs of all faculty members who teach a particular subject.

Total direct teaching of a civil engineering course P1,626,351 Number of Students Taught 2,332 Cost per student taking a civil engineering course P697.40 English P370.67 x 2 subjects P 741

Mathematics P483.78 x 2 subjects 968 Accounting P551.77 x 1 subject 552 Rizal P284.21 x 1 subject 284 Engineering P697.40 x 10 subjects 6,974 Total for Junior Year in Civil Engineering P9,519

Appendix A 53

Points of Concern: 1. This method already is a good indicator of average costs per student 2. However, it still fails to account for differences in units and class sizes per

faculty member. It assumes that all civil engineering courses for instance are 3 unit courses and all class sizes are 20 students. It is possible that some civil engineering courses are more than 3 units or that some sections will have larger or smaller class sizes.

I. Computing Unit Cost from Individual Faculty Expenditures

This method brings Method H one-step forward. Since the data to get the costing is already presented and in an analytical form, this method merely computes the direct teaching costs per student per faculty member and only then averages it out. This is the method discussed in Chapter 3 of this paper. The cost per student is directly lifted from the worksheet and consequently the computations are no longer shown here. English P408.22 x 2 subjects P 816 Mathematics P683.19 x 2 subjects 1,366 Accounting P621.09 x 1 subject 621 Rizal P363.20 x 1 subject 363 Engineering P892.08 x 10 subjects 8,921 Total for Junior Year in Civil Engineering P12,087

Appendix A 54

APPENDIX B RESEARCH INSTRUMENT

PURPOSE OF THE SURVEY The primary purpose of this survey to collect basic revenue and cost data of your University as broken down per degree. The ultimate objective is to arrive at a unit cost per degree per student. The survey is being conducted for the Commission on Higher Education in support of an ADB Project on Normative Financing of Higher Education. FORM A1 CONTACT INFORMATION Institution Name Classification: Private Public Address City Province Region Respondent name Contact Phone Contact E-mail

Appendix B 55

FORM A2 Revenue Stream

National Government Local Government Tuition Fees Basic fees laboratory miscellaneous Private Grants Other Revenue Investment income and investment gains (losses) Sales and services of educational activities Sales and services of auxiliary enterprises Other revenue

I. Expenditures

Appendix B 56

FORM A3 ALLOTMENTS (Period) BY COLLEGE, DEPARTMENT, OR OFFICE Name of SUC: Campus: College/Dept/Office Allotment Fund 101 Allotment Fund 164 Total Allotment PS MOOE CO PS MOOE CO PS MOOE CO Graduate School College of Arts and Sciences Languages Department Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture College of Business Economics, & Accountancy College of Education Office of the President Office of the Registrar Main Library Information Technology Center Student Services Division Auxiliary Medical & Dental Clinic Research Services Extension Services Others Total Allotments xx xx xx xx xx xx xx xx xx

Appendix B 57

FORM A4 EXPENDITURES (Period) BY COLLEGE, DEPARTMENT, OR OFFICE Name of SUC: Campus: College/Dept/Office Expenditure Fund 101 Expenditures Fund 164 Total Allotment PS MOOE CO PS MOOE CO PS MOOE CO College of Arts and Sciences Languages Department Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture College of Business Economics, & Accountancy College of Education Graduate School Office of the President Office of the Registrar Main Library Information Technology Center Student Services Division Auxiliary Medical & Dental Clinic Research Services Extension Services Others Total Expenditures xx xx xx xx xx xx xx xx xx

Appendix B 58

FORM B1 ENROLLMENT COLLEGE/DEPARTMENT/DEGREE Second Term10 Freshmen Sophomore Junior Senior Terminal Total College of Arts and Sciences Languages Department AB English AB Literature AB Filipino Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture College of Business Economics, & Accountancy College of Education Graduate School Total xx xx xx xx xx xx Summer Term Freshmen Sophomore Junior Senior Terminal Total College of Arts and Sciences Languages Department Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture Graduate School Total xx xx xx xx xx xx First Term Freshmen Sophomore Junior Senior Terminal Total College of Arts and Sciences Languages Department Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture College of Education Graduate School 10 If the financial data is for calendar year 2002, enrollment data should be second term 2001-2002, summer 2002, first term 2002-2003.

Appendix B 59

Total xx xx xx xx xx xx FORM B2 GRADUATES COLLEGE/DEPARTMENT/DEGREE School Year 97-98 98-99 99-00 00-01 01-02 Total College of Arts and Sciences Languages Department AB English AB Literature AB Filipino Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture College of Business Economics, & Accountancy College of Education Graduate School Total xx xx xx xx xx xx

Appendix B 60

FORM B3 LICENSURE EXAMINATIONS School Year 97-98 98-99 99-00 00-01 01-02 Total Architecture Examination Civil Engineering Etc. Total xx xx xx xx xx xx

Appendix B 61

FORM C1 FACULTY INFORMATION COLLEGE/DEPARTMENT Rank Grade Highest Years of Remarks Educ. Service Attain. College of Arts and Sciences Languages Department Faculty Name (Family Name first) Faculty Name Prof VI 29 Ph.D 10 Dean Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture College of Business Economics, & Accountancy College of Education Graduate School Office of the President Office of the Registrar Main Library Information Technology Center Student Services Division Auxiliary Medical & Dental Clinic Research Services Extension Services Others

Appendix B 62

FORM C2 FACULTY COMPENSATION INFORMATION COLLEGE/DEPARTMENT Basic Lump SUC Salary Benefits Allowances Others Total Sum Income College of Arts and Sciences Languages Department Faculty Name (Family Name first) 230 230 Faculty Name 100 100 Department Sub-Total xx xx xx xx xx Mathematics Department Sciences Department College Sub-Total xx xx xx xx xx College of Agricultures and Forestry College of Agriculture College of Business Economics, & Accountancy College of Education Graduate School Office of the President Office of the Registrar Main Library Information Technology Center Student Services Division Auxiliary Medical & Dental Clinic Research Services Extension Services Others GRAND TOTAL xx xx xx xx xx xx xx

Appendix B 63

FORM C3 FACULTY ACTUAL DISTRIBUTION OF FACULTY TIME (in units per week) COLLEGE/DEPARTMENT Teaching Teaching Admin Research Extn Others Total Undergrad Grad Svcs Second Term College of Arts and Sciences Languages Department Faculty Name (Family Name first) Faculty Name Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture College of Business Economics, & Accountancy College of Education Graduate School Teaching Teaching Admin Research Extn Others Total Undergrad Grad Svcs Summer College of Arts and Sciences Languages Department Faculty Name (Family Name first) Faculty Name Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture College of Business Economics, & Accountancy College of Education Graduate School

Appendix B 64

Teaching Teaching Admin Research Extn Others Total Undergrad Grad Svcs First Term College of Arts and Sciences Languages Department Faculty Name (Family Name first) Faculty Name Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture College of Business Economics, & Accountancy College of Education Graduate School Teaching Teaching Admin Research Extn Others Total Undergrad Grad Svcs Total All Terms College of Arts and Sciences Languages Department Faculty Name (Family Name first) Faculty Name Mathematics Department Sciences Department College of Agricultures and Forestry College of Agriculture College of Business Economics, & Accountancy College of Education Graduate School

Appendix B 65

FORM D1 LIST OF CLASSES TAUGHT PER FACULTY COLLEGE/DEPARTMENT Faculty Name Department Course Cat.11 Number of Number of (family name, Code Student Units first name) Artates, Rodrigo Biology BIO1 B 20 3 Artates, Rodrigo Biology BIO101 C 25 3 11 Indicate whether subject is basic (B), cognate (C), major (M), or elective (E)

Appendix B 66

FORM E1 PHYSICAL INFRASTRUCTURE INFORMATION Land Area

What is the total land area upon which the University sits in? When was the property acquired? How did the University acquire the property? What was the valuation of the property at the time of acquisition? What is the valuation of the property as of December 31, 2001?

What is the usage of the property in terms of square area? Total Area Building Parking Sports Field Roads, Streets Easements Total How many buildings are there and what is its size? Land Area # Floors Flr Ar Matl Used Acq. Date Acq Price Condition Building For the spaces in each building, specify its usage in terms of floor area. Admin Classroom Lab Aisles Gym Cmft Room Others Building

Appendix B 67

FORM E2 EQUIPMENT and CAPITAL OUTLAY INFORMATION What is the current inventory of equipment? Major Eqpt Acq Date Acq Price Depr condition Office Capital Outlay Expenditures Acquisition of Land within the Next 5 years Do you expect to acquire land for expansion within the next 5 years? If yes, for what purpose would this be? What would be the expected budget? What funding source to do you expect to use to finance the acquisition of land? Construction Do you expect to construct additional building/s within the next 5 years? If yes, for what purpose would this be? What would be the expected budget? What funding source to do you expect to use to finance this? How is the cost of building depreciated? Major Repairs Do you expect to undertake any major repairs on existing building/s within the next 5 years?

What would be the expected budget? What funding source to do you expect to use to finance this? Instructional Equipment

Do you expect to acquire any instructional equipment within the next 5 years? What are these? What would be the expected budget? What funding source to do you expect to use to finance this? How is the cost of equipment depreciated?

Appendix B 68

All Other Equipment Do you expect to acquire any other equipment within the next 5 years? What are these?

What would be the expected budget? What funding source to do you expect to use to finance this? How is the cost of equipment depreciated?

Appendix B 69

APPENDIX C SAMPLE ANALYTICAL SHEETS

WORKSHEET PART 1 Distribution of Direct Personnel Cost Per Faculty Member

LOADING HOURS Faculty Name

College/ Dept

Total Salaries Teaching Admin Res. Extn Others Total

Under- graduate Grad Svcs

(Col A) (Col B) (Col C) (Col D) (Col E) (Col F) (Col G) (Col H) (Col I) (Col J)

SHARE OF TOTAL SALARIES Faculty Name

College/ Dept

Total Salaries Teaching Admin Res. Extn Others Total

Under- graduate Grad Svcs

(Col A) (Col B) (Col C) (Cok K) (Col L) (Col M) (Col N) (Col O) (Col P) (Col Q) PART 2 Direct Personnel Cost Per Student

Faculty Name College/Dept

Course Code

Cate-gory

Num Stud

Num Units

Cost/ Course

Cost/ Stud

Cost/Unit

(Col A) (Col B) (Col C) (Col D) (Col E) (Col F) (Col G) (Col H) (Col I)

PART 3 Cost Per Student by Subject

Subject

# Faculty

who taught

Total Teaching

Cost

Total Sections

Cost/ Course

Total Student

Cost/ Student/Course

Total Units

Cost/ Unit/

Student

(Col A) (Col B) (Col C) (Col D) (Col E) (Col F) (Col G) (Col H) (Col I)

Appendix C 70

PART 4 Direct MOOE per Student Department/

College MOOE Total

Enrolled Students

MOOE/ Student

(Col A) (Col B) (Col C) (Col D)

PART 5 Indirect Cost per Student

Office Personnel Services MOOE

Personnel Services Removed

from Part 1

Total Total

Student Population

Indirect Cost per Student

(Col A) (Col B) (Col C) (Col D) (Col E) (Col F) (Col G)

PART 6 Cost per Degree

First Term Second Term Year Total

Subject Unit Cost/Unit Total Cost Subject Unit Cost/Unit Total

Cost Direct Teach

Direct MOOE

Indirect Cost

Total Cost

(Col A) (Col B) (Col C) (Col D) (Col F) (Col G) (Col H) (Col I) (Col K) (Col L) (Col M) (Col N)

Appendix C 71

APPENDIX D STEP-BY-STEP INSTRUCTIONS FOR THE ANALYST

These are instructions for Microsoft Excel Users. The term encode is used for universities that can provide only hard copies of the data. For some universities, a soft copy of the data can be given. In this case, the analyst merely picks up the data from the other files already existing. Sheet 1 – Used to Extract Direct Teaching Costs 1.1 This Sheet is used to allocate the total personnel services of each faculty member

to the different major responsibilities. 1.2 Encode the faculty name in column A, using the format family name, then first

name. 1.3 Indicate the department the faculty is assigned to in column B. 1.4 Encode the total personnel services per faculty member in column C. Get data

from survey form C2. 1.5 From survey form C3, indicate the distribution of faculty time for each faculty

member. Get the total of first term, second term, and summer of the year in study. For instance, a faculty members spent 12 hours for teaching in the undergraduate program in term 1, 16 hours in term 2 and 3 hours in summer, the total teaching load is 31 hours. Do this for research and extension as well. All other hours in a week unaccounted for can be placed in the column marked “Others”.

1.6 Columns D to I are numeric fields. The total of these fields is shown in Column J. Use the @sum (d6:i6) formula.

1.7 Apportion the total personnel salaries by the main categories of Undergraduate teaching, Graduate teaching, Research, Administration, Extension, and Others. This is computed by getting the ratio of hours spent to total hours multiplied by the total personnel services. For instance, a faculty member spent a total of 36 hours teaching and total work week for the year is 80 hours. Multiply the total personnel salaries by 36 over 80.

1.8 For Column L, use the formula as follows (+d6/$k6 x c6). Copy this formula to Column M, N, O, and P.

1.9 The last column is merely to check that all costs have been accounted for. Add the Columns L to P using the formula @sum (l6:p6) . The total amount should be equal to total personnel services. If not, something went wrong.

1.10 After doing this procedure for all faculty members in the department, add the columns so that there is a total figure for each of the columns. This is the department total.

1.11 Do this for all subsequent departments. 1.12 After the last row of entries, add all department totals to get the university total.

The figure for total personnel services should match the total expenditures for the year under survey form A4. If it does not, data could be missing.

Appendix D 72

1.13 Note that the listing on Sheet 1 is unique. A faculty member cannot be listed twice. This may explain any discrepancy between the total personnel services on sheet with actual expenditure.

1.14 Move onto Sheet 2. 2.1 Sheet 2 is the more complicated portion of the worksheets for cost analysis. This

sheet contains information on the actual subjects taught by all faculty members in the year. Sometimes, it is better to create sub-sheets so the file is manageable. If there are 100 faculty members who teach 10 subjects in a year, the total rows would be 1000.

2.2 Sheet 2 starts with the faculty name in column A and department in Column B. Ensure that each row has the name of faculty and the department for sorting purposes.

2.3 Proceed to encode all the subjects taught by a faculty member for the entire year in Column C. Data should be encoded the same way again for sorting purposes. So if capital letters were used for the faculty name, all faculty names should be in capital letters. If not, the data will not be properly sorted.

2.4 Classify each subject into basic (B), cognate (C), major (M), or elective (E). Indicate the capital letters in Column D.

2.5 For each subject, encode the number of students enrolled in the class (Column E) and the number of student units (Column F).

2.6 Create an exact copy of Sheet 2. Under the Edit button of Excel, choose the option Move/Create Copy. Then click on create a copy. This new copy is now sheet 2 (2).

2.7 On sheet 2(2), sort the data by faculty name so that you can get all the subjects taught by a faculty member. Sometimes a faculty member services other department and even graduate studies. To sort, mark all the fields to be sorted, click the Data button, press sort, choose No Header, and sort by field A, ascending.

Tamayo, Delia Q Soc. Sci. B PHILO 1 21 3 13,755 Tamayo, Delia Q Soc. Sci. B Pol Sci 1 15 3 13,755 BALDONADO, ESMERALDA A. Soc. Sci. C Philo 11 37 3 19,714 BALDONADO, ESMERALDA A. Soc. Sci. C Philo 11 51 3 19,714 BALDONADO, ESMERALDA A. Soc. Sci. B Pol Sci 1 56 3 19,714 BALDONADO, ESMERALDA A. Soc. Sci. B 47 3 19,714 BALDONADO, ESMERALDA A. Soc. Sci. B Pol Sci 1 31 3 19,714 NAJORDA, IMELDA L. Soc. Sci. C Philo 11 58 3 11,751

Pol Sci 1

Appendix D 73

2.8 Once all the information is encoded and the names have been sorted, compute the

teaching cost per course (Column G). This is done by dividing the total teaching salary (from Sheet 1) by the number of subjects taught. Each row will now have a cost per subject.

2.9 To copy the personnel services amount, press (+) then press Sheet 1, then bring cursor to the correct field. When you press enter, the amount will automatically transfer. Do this for all rows. Then using the edit key, divide the amounts by total number of subjects taught by faculty member.

2.10 After doing the same thing for all faculty members, total Column G. The total amount should equal Column K of Sheet 1.

2.11 When you are certain the sheet balances, create a copy of sheet 2(2). This is now sheet 2(3).

2.12 On sheet 2(3) sort the data again this time by the course code (Column C). For each of the courses/subjects taught, compute the cost per student (Column H) and the cost per student per unit (Column I).

Tamayo, Delia Q Soc. Sci. B PHILO 1 21 3 13,755 BALDONADO, ESMERALDA A. Soc. Sci. C Philo 11 37 3 6,877 BALDONADO, ESMERALDA A. Soc. Sci. C Philo 11 51 3 6,877 NAJORDA, IMELDA L. Soc. Sci. C Philo 11 58 3 19,714 Tamayo, Delia Q Soc. Sci. B Pol Sci 1 15 3 19,714 BALDONADO, ESMERALDA A. Soc. Sci. B Pol Sci 1 56 3 6,571 BALDONADO, ESMERALDA A. Soc. Sci. B Pol Sci 1 47 3 6,571 BALDONADO, ESMERALDA A. Soc. Sci. B Pol Sci 1 31 3 6,571

2.13 To compute for cost per student, divide Column G by Column E. 2.14 To compute for cost per student per unit, divide Column H by Column F. 2.15 Move to Sheet 3. 3.1 Sheet 3 is the summary of all computations derived from Sheet 2(3). 3.2 List all the major subject categories in Column A. 3.3 In Column B, just add the total number of faculty members who taught the

subject. Use the command @sum(then enclose the relevant rows) 3.4 In Column C, add the total cost/course for all similar subjects, taken from Column

G of Sheet 2(3). (Note that data is already sorted by subject so it is easy to get the sum).

3.5 In Column D, add the total number of sections for the course. Use the formula @count (then enclose relevant rows). Count Column F of Sheet 2(3).

3.6 In Column E, get the average teaching cost. To compute for the average teaching cost use @average (then enclose the relevant rows). This is taken from Column G of Sheet 2(3). This step is different from 3.4 since it is the average as against the @sum in 3.4.

3.7 For Column F, add the total number of students who enrolled in that subject, taken from Column E of Sheet 2(3).

Appendix D 74

3.8 For Column G, get the average cost per student, taken from Column H of Sheet 2(3).

3.9 For Column H, add the total number of units taught, taken from Column F of Sheet 2(3).

3.10 For Column I, get the average cost per student per unit, taken from Column I of Sheet 2(3).

3.11 Proceed to sheet 4. 4.1 Sheet 4 computes the direct MOOE cost per student. 4.2 Encode the different non-teaching departments in Column A. 4.3 Get the MOOE cost per department from Survey Form A4 and encode this in

Column B. 4.4 Get the number of students taught by the department by adding the total number

of students (per subject) from Sheet 3. Place this in Column C. 4.5 In Column D, divide the department cost by the total number of students serviced

by the department. 4.6 Proceed to sheet 5 5.1 Sheet 5 computes the total indirect cost per student. 5.2 From Survey Form A4, get the different non-teaching cost centers. For example,

Administration Office, Library Services, research, extension services etc. Encode the list in Column A.

5.3 Then pick up the personnel services expenditure and place in Column B. 5.4 To the same for MOOE in column C. 5.5 Column D is for costs previously removed from the personnel services costs of

teaching faculty. 5.6 Go back to Sheet 1 and pick up the sum of research costs, extension services

costs, and other costs. Encode this in the proper rows on Sheet 5 on Column D. 5.7 Column E is the total of columns B, C, and D. 5.8 Column F is the total student population for the year. Note: this refers to number

of students officially enrolled in the program for the entire year. Ensure that students are not double counted. Get the information from Survey Form B1.

5.9 Divide column E by column F to get the cost per student in column G. 5.10 Add the rows in column G to get the total indirect cost per student. 6.1 Shows the computation of the cost per degree. 6.2 Encode the curriculum for a degree. List all subjects for all the terms 6.3 In Column A, indicate the subject. In Column B, the number of units for the

subject. Pick up unit cost for the subject from Sheet 3 and place in Column C. Multiply Column B and C to get Column D.

6.4 For the second term in the year, use Columns F, G, H, and I. 6.5 Column K is the sum of Column D and Column I.

Appendix D 75

Appendix D 76

6.6 Encode in Column L, the direct MOOE per student for each subject taken. So if there were 2 subjects on English taken in the first year, the direct MOOE is multiplied by 2. The Direct MOOE was computed in Sheet 4.

6.7 Encode the indirect cost per student taken from Sheet 5. Note that this is a yearly expense and should only be included in the bottom of the year.

6.8 After adding Columns K, L and M, you will get the total cost for that year. Do this for all the years and add each year to get the cost per degree.

Subj Unit

Cost/Unit

Total Cost Subj Units

Cost Per Unit

Total Cost

Dir. PS

Dir MOOE

Ind. Cost Total/Year

ENG 101 3 137 411 ENG 102 3 137 411 822 300 FIL 101 3 137 411 FIL 102 3 137 411 822 300 MATH 102a 3 205 614 MATH 113 3 205 614 1228 300 ECON 101 3 134 402 HUM 101 3 196 588 990 300 MU 101 3 144 432 PHILO 101 3 162 487 920 300 SOCIO 101 3 123 369 MU 102 3 144 432 801 300 RIZAL 3 123 369 PSYCHO 101 3 175 525 894 300 PE 101 2 167 335 EDP 1 3 165 495 830 300 PE 102 2 167 335 335 300 TOTAL 23 1170 3344 TOTAL 261489 4299 7643 27004098 14441