24 Formula Funding in Ethiopian Higher Education1

Marc Robinson
Published Date:
October 2007
  • ShareShare
Show Summary Details
Kate Ashcroft

This chapter briefly describes a funding formula which has been developed for Ethiopia’s higher education institutions. It places this in the context of Ethiopia’s history and development stage and the particular requirements of its higher education context. It is argued that such a formula is an important element in the reform of Ethiopia’s civic society by providing:

  • protection for institutional autonomy and academic free speech, while requiring accountability

  • transparency of funding decisions and limiting the potential for government bias or control

  • support for the move towards a more flexible, responsive, outcome-oriented, customer-focused public service.

For 2,000 years Ethiopia was a feudal society ruled by a series of absolute monarchs, briefly interrupted from time to time by civil wars and from 1936 to 1941 by the occupation by Italian fascists. In 1974, a revolution deposed the monarchy and instituted a hard-line communist government (the Derg) committed to extreme centralization, the imposition of “scientific socialism,” and nationalization/collectivization. This regime was particularly brutal and caused the deaths and detention of many academics and other intellectuals. Eventually, in 1991 this oppressive dictatorship was overthrown by a coalition of liberation fronts, of which the Ethiopian People’s Revolutionary Democratic Front (EPRDF) has gradually developed into a grouping resembling a coherent political party. The EPRDF held its first elections in 1995 and received an overwhelming majority of the vote (Pankhurst, 1998). After three elections, each more open and democratic than the last, in 2005 the ruling political party once again won the most seats in parliament, albeit with a greatly reduced majority and amidst some controversy about the fairness of the election.

The liberation front took over a country that was in a parlous economic and social state with a tradition of extreme centralization and authoritarianism, poor leadership and management capability, deadening bureaucracy, widespread food insecurity, and periodic famine. There was little industry or private enterprise, a limited transport and communication infrastructure, poor health and education, many harmful traditional practices, and large increases in population and widespread illiteracy. In addition, the new government was confronted with a long-running border dispute with the newly independent Eritrea, which erupted into war between 1998 and 2000.

Ethiopia has an estimated total population of 72.4 million with diverse languages, culture, and topography. Out of the total population of the country, 15 percent is urban and 85 percent is rural. The population is growing at a rate of 2.7 percent so ever-more children and young people will require education, including higher education. About 85 percent of the population earn their living from rain-fed agriculture which constitutes 52 percent of GDP. The country is one of the poorest in the world with average income below $100 per year.

In 2003/04 there were 13.95 million primary school-age (7–14) children, of which 9.54 million are enrolled in formal primary schools (57 percent male and 43 percent female). Enrollments in grades 1–12 rose at about 9 percent a year between 1992–93 and 2001–02. In 2003/04, the gross enrollment of girls and boys in the first cycle secondary education (7–10) was 15.9 percent and 28.2 percent respectively, with a total gross enrollment rate of 22.1 percent. The gross enrollment in the 10–12 grade pre-HEI (higher education institution) program stands at about 2.3 percent. Less than 2 percent of the age cohort is currently enrolled in post-secondary education. Government plans a ten-fold increase in public technical and vocational education and training (TVET) over four years at a capital cost of $210 million for the construction of 71 new TVET facilities and five colleges.

There has been considerable development within Ethiopia’s higher education system. It has grown in the last decade, from two universities to eight in 2004, and will soon expand to 22 with the opening of 13 new higher education institutions and an open university. Higher education enrollment has expanded from 42,132 to 172,111 in 2004/05. However, Ethiopia’s gross enrollment figure remains low by world standards, at 1.5 percent.

There is a shortage of university educated leaders and staff in teaching positions at the secondary and university level. The percentage of qualified teachers at secondary level grades 9–12 was only 44.4 percent in 2003/04. Pressure to expand secondary education is building as a rising percentage of the age cohort completes primary education.

Despite these difficulties, over a 13-year period the ruling party has moved Ethiopia from a centralized dictatorship to a federated state with much power devolved to the regions, supported by elected regional government. At the same time the federal government has slowly liberalized the economy and society, allowing a somewhat freer press and some denationalizing of various state-owned enterprises, starting to free the financial system from over-regulation, reforming various aspects of the legal system, and, in 2003, initiating widespread reform of the higher education system.

In 2003 the federal government introduced a Higher Education Proclamation (Federal Democratic Republic of Ethiopia, 2003), establishing wide-ranging reforms to the higher education system and set up key agencies to guide and oversee the sector, including the Higher Education Strategy Center, the so-called “Brain Center” set up to advise government of higher education strategy and policy, and the Higher Education Relevance and Quality Assurance Agency (HERQA) to undertake quality assessment at subject level and institutional accreditation.

The reforms introduce elements of a quasi-market in higher education: learners are sharing the costs of higher education, and therefore are moving into a more customer-like relationship with higher education institutions; private higher education is expanding fast; and there is a gradual move away from state funding of public higher educational institutions through the encouragement of income-generation activity. The reforms also enable a move from extreme centralization towards institutional autonomy and internal devolution of budgets.

The Vice Minister for Higher Education emphasizes the higher education sector’s central role in increasing and diversifying knowledge and competitiveness in a global and knowledge-based market, as well as its role in the protection of democratic culture and society (Teshome, 2003). This role is facilitated by the rapid and substantial investment in higher education by the Ethiopian government, the World Bank, and other donors. Ethiopia requires a massification of its higher education system in order that its graduates might manage the processes of a civil society, oversee its economic and social development, and provide the professional class of teachers, business people, health workers, and so on.

Greater autonomy for HEIs has been achieved by various measures: a board no longer chaired by the Minister of Education; more powers given to HEI Boards and institutions to hire, reward, and manage of all categories of staff; HEIs given more independence to determine their internal organizational arrangements; the introduction of a funding formula and a block grant (Federal Democratic Republic of Ethiopia, 2002).

The World Bank (2004) notes that before the reforms the government routinely appointed university Presidents and Vice Presidents; all academic staff were civil servants managed by the Civil Service Commission rather than the HEI; line budgets were allocated centrally and increased incrementally irrespective of numbers of students or quality; additional income generated was deducted from budgets; and quality assurance was not an explicit concern.

International context

There are a variety of models for a funding formula across the world. These vary from the relatively simple to the highly complex. Funding through formulas is unusual in Africa. In most countries, separate negotiations take place for each public institution between the senior managers of the institution and the Ministry of Planning and Finance (Mozambique is an example). In others the system is so small (that is, only one HEI in Namibia or Malawi, for example) that a formula would make no sense.

The funding of public universities in Kenya is an example of a very simple method. Currently it is based on a unit cost. The current unit cost of $1,600 is comprised of tuition of $1,147 and catering, accommodation, and other costs that amount to $453. The method does not take into account differential costs of the various degree programs (INHEA, 2005).

Australia provides another example of a relatively simple system. The Australian government has recently moved from funding public higher education through block grants determined largely on a historical basis to a formula based on student places “delivered” each year within various discipline categories (ten in all). Each higher education provider receiving funds under the formula enters into a funding agreement with the government, specifying the number of places and the discipline mix that the Australian government will support. The agreement is negotiated annually in the context of each provider’s mission and strategic direction for course provision and labor market needs. Unfilled places from providers that consistently under-enroll will be redistributed to other higher education providers according to Australian Government priorities. Over-recruitment to programs will be funded provided that this does not exceed 5 percent. These new arrangements are accompanied by partial fee deregulation to allow higher education providers to charge fees to the student contribution level to a maximum determined by the Australian government. Students can fund their contribution through an income contingent loan supplied by a government agency (Department of Education, Science and Training, 2004).

In the UK, a much more complex system was introduced, though it is currently being reviewed. The Higher Education Funding Council for England (HEFCE) uses formulas to determine how most funding is allocated between institutions. Although subject categories are relatively crude (subjects are grouped into only four categories for funding purposes), complexity is created by the number of additional variables that are included as “premiums” in the formula. These include student-related factors, course characteristics, institutional characteristics, and the volume and quality of research. The money is provided in the form of a “block grant” which institutions are free to spend according to their own priorities within broad guidelines. The HEFCE is explicit in its expectation that institutions should not model their internal allocations on its own funding method. After an HEFCE grant, tuition fees are usually the other major source of funding for teaching. In the late 1980s and early 1990s, the UK government sought to use various performance indicators as a way to establish an accountability relationship with higher education (for example, access as indicated by numbers of students from state schools, deprived areas and low-participation areas, and disabled students; employment rates; year 1 student drop-out rates). The HEFCE derived a range of measures for these, but no consensus emerged on what should be the key indicators and how (or whether) they should relate to funding.

The HEFCE funding formula takes into account the number of students, subject-related factors (four categories are assumed), level of study, student-related factors, and institution-related factors. The HEFCE operates a plus or minus 5 percent tolerance band, restricting year-to-year changes in the unit of funding to that amount. In addition, the HEFCE makes separate allocations to recognize the additional costs of recruiting and supporting students from disadvantaged and non-traditional backgrounds, and students with disabilities. The formula takes into account additional costs associated with students on long courses, part-time students, and students on two-year foundation degrees. In addition, the formula takes account of additional costs associated with institutional factors. These result in the premiums for operating in London (weighting), small institutions, and those with old and historic buildings (HEFCE, 2004).

Along with various other countries, both Australia and the UK also have formulaic mechanisms to reward the volume and quality of research output. Since these are not relevant to Ethiopia at the present time, they are not described here.

Not all funding formulas for higher education are designed to reward performance. It is useful to distinguish those that are based on input (the costs of providing a service—in this case education—irrespective of whether that service produces desirable results); those that are based on outputs (for example, complete courses of study) and those based on outcomes (for example, the numbers of graduates provided to society). Using the term “outcomes” in this way is unconventional in higher education circles, where outcomes are usually used to refer to student learning (skills, knowledge, and understanding acquired) and tangible benefits of such learning (for example, graduates employed in professional capacities). Numbers of students graduating or successfully completing each year are seen in academe as indicative of, but by no means the same as, an outcome. They are therefore a “proximate” outcome (as opposed to a high-level outcome such as a more productive workforce and faster economic growth). The link between high-level outcomes and the effects of actions by a higher education institution is impossible to measure accurately. However, the level of student graduations is probably a good approximation that is sufficiently measurable to be used for funding purposes.

Funding formulas across the world may be based on inputs or outcomes. For example, the Australian model is based on output (those students educated each year), but not outcome (that is, those successfully graduating). The HEFCE model mixes measures of input (for example, the additional costs of certain forms of building) and of outputs (students being taught) and outcome (students successfully completing each year). Elsewhere in the world these are models based almost entirely on inputs. For example, in the US the Massachusetts model is based on prescribed student-faculty ratios by discipline, faculty workload, required direct support staff, and other non-salary costs in relation to credit hours. It estimates the level of need for support services based on assumed expenditures per student by service area and the estimated need for the physical plant level based space-facilities ratios, square feet of campus buildings, acreage occupied by the campus, historic rates of utility consumption, and the current replacement value of equipment used to maintain and operate the physical plant.

South Africa has introduced more goal-oriented public funding of higher education institutions through a revised and simplified funding formula accompanied by an increase the proportion of available funds for earmarked funding (that is, the proportion of funds outside of the formula). Its formula is based on the planned (full-time equivalent, or FTE) enrollments in different fields and levels of study at each HEI. Like the UK system, funding rates per FTE student place vary according to which of the broad fields the subject falls into and the level of study, and is standard for all institutions. Unlike the UK, initially the government rejected inclusion of student completions and research publications in the funding grid. It accepted the need to improve institutional efficiency and effectiveness, but the apartheid legacies of existing institutions meant that this would disproportionately benefit some HEIs and disadvantage others (Department of Education, 1997). However, more recently, 14 percent of the funding from the formula relates to graduation rates and 6 percent to institutional factors (Ministry of Education, 2004). This has added complexity to the formula.

Not all higher education systems are funded using formulas, but it does seem to be becoming more common across the world. There are a variety of reasons for this. First, a formula enables transparency and objectivity in funding decisions and so is a useful means of protecting institutional autonomy—individual HEIs are less subject to the whim of government. Second, a formula enables governments to fund larger and more complex systems where individual negotiations with HEIs to determine their “needs” would be impractical. Third, formulas, when based on outputs or outcomes, can be a useful means of ensuring greater focus on the core mission of HEIs and accountability for the allocation of taxpayers’ money (generally educating sufficient numbers of students, preferably to graduation).

Countries (or states) express their objectives with respect to the operation of a funding formula differently. For example, the South African aims include the achievement of:

  • an appropriate balance between institutional autonomy and public accountability

  • procedures that are simple, transparent, flexible, and fair, and which are capable of being managed within the available and foreseeable capability of the Department of Education and the institutional councils, managements, and academic leadership.

The HEFCE’s aims are to:

  • increase opportunities for students from all types of backgrounds to benefit from higher education

  • maintain and enhance the quality of teaching and research

  • encourage universities and colleges to work with business and the community

  • support diversity

  • encourage efficiency in the use of public funding

  • provide stability in funding from year to year.

However, when one looks in detail at the expressed principles, certain themes emerge: a commitment to institutional responsibility, efficiency, transparency, and fairness, student access to higher education, and so on.

There have been some undesirable consequences of funding higher education through formulas that have emerged across the world. Since certain outcome measures are used as “proxies” of quality as well as quantity (for example, student graduation rates), and because these measures are imprecise in these terms, institutional behavior may be distorted. Examples of this include a tolerance of “grade inflation” as a means of ensuring high undergraduate pass rates in UK HEIs and “salami publishing” (publishing several papers from the same data) in those countries where the volume of research output is rewarded (for example, some states in the US). Most countries have instituted agencies responsible for checking quality as well as quantity to ensure that standards do not slip: for instance, in the UK the Quality Assurance Agency checks the quality of taught programs and the research assessment exercise uses peer review panels to check the volume and national and international standing claimed for research output.

In addition, governments often put in place regulatory and other mechanisms to ensure that institutional behavior conforms to certain standards and practices: for example, student learning outcomes that must be included in programs in each subject; codes of conduct; student appeals processes and systems; published performance indicators, and league tables, as well as intake targets to particular programs. They often earmark funds in addition to those within the formula to incentivize HEIs to pursue particular government objectives such as increased access for disadvantaged groups or industry linkages.

Origins of the funding formula

Until 2005, HEIs were funded through a line budget, negotiated annually with the government. This meant that each HEI had to make a case based on need for an enlarged budget (an input model of funding), and this case might be accepted in whole or part by the government. HEIs were not free to vire between budget heads, even within the revenue account, and neither were they allowed a contingency fund. Therefore it was in their interests to overstate their needs in order to ensure that unexpected costs in any line would be covered.

Prior to 2003 the situation was even more constrained, with HEI staff being technically civil servants, employed by the state: the decision to employ a new member of staff or to replace an existing one, along with their terms and conditions, had to be approved by the Ministry of Education and fit within the Civil Service Commission structure. This ensured a very close relationship with the Ministry of Education, amounting to control and surveillance. In effect, HEIs were financed much as if they were core government departments.

It was also the case that different HEIs appeared to achieve very different rates of productivity, with some seemingly very much more expensive in terms of costs per student than others. However, there was no way of knowing whether these apparent inefficiencies were the result of the subject mix or levels of study within the various HEIs, or whether some were indeed delivering comparatively poor value for money.

There was a lack of focus on efficiency—it was not in any HEI’s interest to seek economies: any end-of-year surplus could not be rolled over to the next year, and any apparent efficiencies would be assumed in the next year’s budget. It was in the HETs interests to spend up to the limit of every line in the budget and so to make the case for a larger allocation in the following year. Often there was a scramble to spend any remaining funds just before the end of the financial year. There was also a lack of focus on effectiveness—for example, there existed no penalty for high drop-out rates of students from programs. Indeed, a cynical HEI manager might welcome a high level of drop-out early in the year, since this would reduce the total costs of teaching.

A funding formula was seen as desirable by government as a means of encouraging greater efficiency and a greater focus on outcomes. It was welcomed by HEI managers as a means of enabling more rational decision-making and preventing unnecessary interference by government in institutional affairs. In addition, it was seen as essential for the block grant and a means to enable HEIs to reflect institutional performance objectives in the objectives and rewards for their staff. HEI managers, perhaps rightly, have been slow to introduce financial incentives for better-performing staff: such incentives can, and often do, have unintended consequences, especially for the morale and performance of the majority of (perfectly satisfactory staff) who do not receive the incentives. Rather, HEI leaders see the funding formula and the associated block grant as enabling better management and providing greater rewards for staff through devolved decision-making and the satisfactions of greater autonomy and reduced bureaucracy.

The Higher Education Proclamation (No. 351/2003) determined that there would be a funding formula for higher education and created the obligation to:

  • decide on its form

  • devise rules for its operation

  • devise the transitional arrangements for its introduction.

At the time that the government chose the author to lead this development, she was Acting Director of the Higher Education Strategy Center (the leading strategy and policy development body for higher education in Ethiopia) and had just completed chairing the National Committee of Enquiry that had resulted in the Report of the Higher Education Strategy Overhaul Committee of Inquiry into Governance, Leadership and Management in Ethiopia’s Higher Education System (Ashcroft, 2004).

During the early part of 2004, the author (with others) visited 13 higher education institutions: all six of the Ethiopian public universities funded through the Ministry of Education; one of the institutions that became a university during 2004; one that was upgraded in 2005; four of the private institutions that aspired to university status; and one higher education institution funded by a ministry other than the Ministry of Education. During the visits to public sector institutions under the Ministry of Education, a series of meetings was conducted with groups of senior managers, academic staff, and students. In all but one of the visits meetings were held with a group of administrative managers, and in all but two a tour of the site, which included the library, IT facilities, student facilities, a typical classroom, a typical laboratory, and other facilities, was organized. Where the institution was a multi-campus operation, these tours generally included visits to more than one site. In all institutions except two, individual meetings with the librarian, a science instructor, and the IT center manager took place.

In the visits to the institutions not funded by the Ministry of Education, a scheduled meeting took place with senior managers in three of the institutions and with middle managers in two of them. A tour of the site was given in three of them.

The author’s knowledge and experience of the UK higher education system was used in developing the funding formula: she had worked as a senior executive and middle manager in four public sector higher education institutions, chaired a national university forum, and been a member of a variety of government working parties. In addition, she drew on her work as a member of the senior management team of the Higher Education Funding Council for England.

This combination of fairly extensive and in-depth knowledge of the Ethiopian higher education context and direct experience of the operation of a higher education funding system from the point of view of both the finder and of the recipient of funding (albeit in a northern context) proved essential to developing a workable funding formula for Ethiopia.

In developing the funding formula, it was decided that it would be undesirable to “import” a model from abroad wholesale, and, equally, it would be important to inform the development by direct experience of operating within a context that uses such a formula. Direct experience and knowledge of the higher education context, its mission, and the type of people and systems that it employs proved to be indispensable. The maintenance of particular values and principles are essential to higher education. It would be inappropriate to adapt a formula for the funding of (say) the police service to the higher education context—higher education by its very nature is staffed by professionals who value their autonomy highly and who must work in a context of high trust if they are to undertake the necessary research and curriculum innovation. This requires a “light touch” formula with the minimum of policy drivers if it is to create the environment necessary for innovative thinking and action.

The team developing Ethiopia’s funding formula was very small: one administrator, one statistician, and the author. The first two members of the team had no higher education management experience: one had operated within a funding formula context abroad as a senior manager in a police force, and the other worked as an instructor within an Ethiopian university.

For this reason, the team relied heavily on appropriate models developed by others. The most useful were found to be a study undertaken by the Ministry of Education in Ethiopia and the World Bank (Merisotis, 2003) and experience in other parts of the world of introducing similar funding formulas, particularly the HEFCE.

As the model developed it was subjected to statistical modeling and refinement and presented for further comment to the Minister and Vice Minister responsible for higher education. Ministry of Education and Ministry of Finance and Economic Development staff, and senior managers of HEIs across Ethiopia. Their feedback was incorporated as appropriate.

Values informing the funding formula

There were three overriding values that informed all of the work on the funding formula.

Value 1: The formula should support institutional autonomy while providing appropriate accountability.

The introduction of a block grant based on a formula taking account of the output of graduates in various subjects is supportive of autonomy and accountability: it enables HEIs to make their own financial decisions, provides a public, objective, and transparent basis for funding, and therefore eliminates the fear of government penalties if HEI staff do not toe the party line, while providing accountability by making funding dependent on the achievement of outcomes.

In democratic countries, universities are one of the pillars that support freedom, alongside an elected government, a free press, and an impartial judiciary. It is no coincidence that academics are among the first to suffer in a dictatorship. Universities are one of the more important sources of new ideas, of new ways of conceptualizing work and society, and of the articulation of dissident opinions. Many of the notions stemming from the universities will be unacceptable to government (at least initially), but they are essential to providing the checks and balances on government power. Universities can only fulfill their democratic functions if there will be no penalty for expressing unpopular or novel ideas. A funding formula, by providing a public and objective measure of the funding for each HEI based on outcomes, takes away the fear of financial penalty for anything but underperformance. In an emerging and fragile democracy such as Ethiopia, this protection is critical.

Value 2: The formula should reward performance and outcome in a fair and consistent way.

The funding formula is also a tool for rewarding performance. Until the funding formula and its associated block grant are introduced, HEIs must negotiate line budgets with government. A line budget has the disadvantage that it focuses on activities, input, and processes, rather than outcomes and outputs. A formula based on (say) student graduation rewards those HEIs that positively respond to the call for expansion and that teach students well so that they do not drop out. Any funding formula may have unintended consequences. It is important to anticipate these as far as possible. One consequence of a formula that rewards throughput (student graduations) is that HEIs might be tempted to pass students who have not achieved the necessary standard. Another is that the student experience may be eroded in the pursuit of quantity. In other words, there is a danger that the quality and standards of the education provided may be compromised. Most governments that have used targets or performance-related funding have also put in place a mechanism to check quality. Such a formula was not a realistic proposition in Ethiopia until the establishment of the HERQA, which could provide assurance that each HETs outcome standards were appropriate. The HERQA is presently developing methods and criteria to check that institutional processes are adequate to ensure standards and that the quality of teaching and learning practices and facilities are appropriate. If it fails to bring sufficient rigor to its task, there is a real danger that slackness rather than real performance may (at least in some instances) be rewarded.

Funding formulas like all other methods of funding can encourage undesirable behavioral consequences. They must use data that are relatively simple to measure. These cannot represent the full range of desirable institutional behavior. This may lead to a focus only on these factors and not on others (such as the qualitative elements of instructional behavior and student learning) that are equally desirable. In addition, no matter how sophisticated the formula, the values within it cannot be precise in all circumstances. Even if it is possible to measure exactly the average cost of (say) educating an undergraduate student in psychology to graduation, there will be some courses that contain more laboratory work than others and so are expensive, but nonetheless useful in that they turn out the kind of graduate that will be needed to fill (say) research posts. This means that the reward of all desirable outcomes is an unobtainable goal, but it should not be taken to imply that the reward of some important aspects of performance is not worthwhile.

It was decided that the education and graduation of students is the main job of HEIs in the Ethiopian context. Research and other outputs are less important to the country’s development than the supply of trained personnel. For this reason it was decided to base the funding formula on the number of students successfully completing each year of study. At this stage, taking account of quality indicators (for example, graduate employment) would depend upon data that were completely unavailable. It was therefore decided to leave quality issues out of the funding equation and to rely on the newly established HERQA to ensure that desirable qualitative outcomes are achieved.

The funding formula does not need to include a process by which the government can control enrollments. At present students are centrally assigned to HEIs by the Ministry of Education, and therefore HEIs have no control over their intakes. At a later stage, it is likely that the assignment of students to programs will be devolved to HEIs, and so rules governing the formula will need to be adjusted to take account of intake targets as well student completions.

Value 3: The funding formula should encourage efficiency and effectiveness in the system.

The funding formula is a tool to create a more efficient and effective higher education system. Until 2005, HEIs bid for their funds on the basis of “need” and historic funding. They could not keep any element of funding that was unspent at the end of the financial year. This provided incentives for HEI managers to emphasize short-term financial planning, to neglect maintenance, to bid for the maximum number of staff they felt would be acceptable rather than seeking staff economies, to bid for large capital goods such as cars without examining the intensity of the use of assets already owned, and so on.

The current allocation funds HEIs in the form of a line budget. This creates the incentive to overstate funding needs in each line in order to provide a margin of safety should there be unplanned demands on the budget. It is also difficult to obtain additional money during the financial year so again HEIs are encouraged to bid for as much as possible at the start of the year. All of this contributes to inflexible financial management.

Income generation is formally encouraged, but any income generated tends to be assumed for the following year and subtracted from the amount allocated to the HEI. This is a strong disincentive to entrepreneurial activity: the HEI carries all the risks with few of the benefits.

These problems with the centralized funding system make it likely that a funding formula will encourage HEI managers to become more outcome-oriented, to act with prudence, to increase efficiency and effectiveness, to plan investment, and to assess the relative costs and benefits of various forms of action and give HEIs the flexibility to respond to changes in demand and to opportunities.

The funding formula is also essential to enable the ministry to manage the expansion of the system. The government could negotiate detailed line budgets with the management of each HEI, monitor line by line the HETs spending, and approve each staff appointment against the budget when there was only a handful of HEIs to deal with. Once the number of HEIs increased, this process became unmanageable. A formulaic system of funding allocation became essential to allow freedom to HEIs to determine their own spending within the funds allocated, with accountability through financial and quality audit systems.

Principles underpinning the funding formula

These overriding values are reflected in the ways that the principles below are actualized. Some of these principles proved more difficult than others to operate in practice. Each of them is discussed in some detail below.

Principle 1: The formula should be based on a unit (base) price which reflects the costs of teaching within the subjects and includes weightings to reflect subjects that are more expensive to deliver and other additional expenses.

Since it is important that HEIs graduate students in a variety of subjects and not just in those that are cheaper to teach, the model has to reward graduation in different subjects at different levels. It is not possible to assess accurately the actual costs of subject teaching within Ethiopia. There was a limited amount of research done by the World Bank and the Ministry of Education in 2003, but the data provided by HEIs suffer from problems of validity and incompleteness, and few HEIs took advantage of the opportunity to comment upon the provisional results.

The author therefore requested each public sector HEI to provide detailed data on the costs per student of teaching in various undergraduate and postgraduate subjects and the level of funding for research. A one-day workshop was held for the Administrative Vice Presidents and Heads of Finance of the HEIs to outline why the data were needed, to present the format for recording the data, and to answer questions and queries with respect to the data collection instrument and any other matters. Representatives from all but one of the HEIs attended. Despite this good attendance, only four HEIs responded by sending data and of these only one presented complete data. The problem is that HEIs allocate their funding according to categories of spending (that is, according to the “lines” within the budget determined by government), and not to cost centers. There is little devolution to departments, and so budgets and all but minor spending tends to be approved centrally. They know what was spent on (say) stationery across the institution, but have few records of what was spent in total by any particular department.

The approach has to be one where funding is allocated in a fair and transparent way, with no institutional “favorites.” This implies that benchmarking of costs must be undertaken. In a small system such as Ethiopia all the HEIs could be “benchmarking partners,” but the benchmarking data remain chronically weak. Given this weakness of the data, a decision had to be made as to whether to delay the development of the formula for one year to allow HEIs to collect better data. However, although HEIs had been asked to provide similar data in 2003, that provided in 2004 showed no improvement. HEI managers had known for a year that the funding formula was to be introduced and the data that would be needed to support it. HEIs had not managed to create systems to collect necessary data in the intervening period. After consultation it was felt that the HEIs will only start to collect data department by department when the funding formula is introduced and they need to know and control such costs. While a line budget is in existence, they will continue to collect and analyze data line by line. Therefore it was agreed with the HEI Presidents and the Vice Minister for Higher Education not to delay the development of the formula.

Data for the relative costs for masters and doctoral programs were particularly weak: these courses had been subsidized from the undergraduate program to an unknowable extent. In developing advice to the government about the weightings for Masters and doctoral programs, the author therefore took experience from elsewhere in the world and the anecdotal accounts of the higher costs of Masters programs in Ethiopia (the need to concentrate expatriate staff in these programs, the need for small class size, and so on) to come up with a recommended weighting.

Ethiopian higher education institutions declared remarkably low levels of spending on research and consultancy. If these data are a true reflection of the actual level of spending, they represent an undesirably small proportion of institutional budgets. Little attempt has been made by HEIs to separate costs for research and consultancy from those for teaching and learning and it is likely that some costs (especially overheads) have been grossly underestimated. In addition, the level of research activity as revealed by the rate of publication is startlingly low. This is evidence that Ethiopian HEIs are not undertaking the scale of research either to inform policy and practice, or to develop as the economic engines and income generators that the country needs. A level of funding for research and consultancy was therefore recommended higher than that suggested by the data, to allow HEIs to start in a small way to undertake research that could be the basis for consultancy and knowledge transfer of the kind that generates substantial economic activity in most modern HEI systems.

The estimated costs were a less than ideal model on which to base the formula; however, they represented the best information available at the time. The data will need to be tested and improved by empirical tracking of costs over time. HEIs and the Ministry of Education will need to develop systems to routinely collect actual delivery costs, including indirect costs such as maintenance and equipment costs, HEI management and administration, student services, and so on. Even so, the pattern of costs might reflect resource availability rather than desirable levels of spending.

Principle 2: The funding formula should be as simple as possible, with relatively few variables.

There have been difficulties found with complex funding formulas in other countries from the point of view of rewarding performance: the opportunities for game playing by HEIs are great and some factors that may be rewarded relate to increased input costs not desirable outcomes. In addition, increased complexity increases the accountability burden and requires increasingly sophisticated management information systems of the kind that do not exist even in embryo form in Ethiopia.

Reviews of the operation of funding formulas tend to increase complexity. For example, in its recent review of the funding formula in England, the HEFCE (2005) describes the current formula funding method as an attempt to resolve tensions, and sometimes conflicting objectives: seeking to reflect government priorities and giving institutions scope for discretionary actions. Many of the issues which HEIs identified during the review could only be resolved by a much more finely grained formula funding method, which would increase the burden on both the sector and the funding council. In addition, the HEFCE has concluded that more detail in the formula funding method would provide less flexibility for institutions to manage their allocations and changes in the numerous premiums and price groups reduce predictability and created difficulties for some HEIs.

In seeking to develop a funding formula for Ethiopia, it was decided that simplicity should be a guiding principle, first as a matter of pragmatics (there are simply no data to support a more complex formula) and second, those systems with simpler formulas do not seem to be less efficient than those with complex ones. There is no doubt that complex formulae create an accountability burden on institutions, and in the Ethiopian context, HEI managers have insufficient systems and management capacity to manage such complexity. In addition, the complexity of some systems (such as in the UK) undoubtedly favors certain HEIs (while disadvantaging others), but it is uncertain that the inclusion of many of the variables benefits the country as a whole: it is not clear why the taxpayer should pay more for students in specialist colleges or those educated in London, since there is no evidence that the graduates disproportionately benefit the economy or society.

On the other hand, there are some variables that are unavoidable in any formula that rewards performance. Some allowance must be made for the different costs of teaching students in different subjects to graduation. This can be approached in two ways:

  • looking at the actual costs of different subjects and developing a formula that reflects each of these

  • looking at the average costs associated with different forms of delivery (for instance, classroom-based courses, laboratory-based courses, courses that include significant clinical elements) and developing a formula that reflects each of these.

The problem with the first of these approaches is that the formula would end up with a large number of individual categories (one for each subject or broad group of subjects) and that new weightings will need to be devised for any new subject introduced into the curriculum. The advantage is that the cost of teaching each individual subject is likely to be reflected more accurately in the formula than with the second approach. In Ethiopia, the data are insufficient to support this model and therefore this model was not recommended.

The problem with the second approach is that the weighting for each category would reflect only very approximately the actual costs of teaching any particular subject. The advantage is that it requires relatively fewer categories (subjects can be arranged into a few academic discipline clusters according to the features of their delivery) and therefore would be much simpler to administer and new subjects could be easily allocated to a particular weighting band according to the main teaching approaches within the subject. Allowance could also be made for the higher costs associated with Masters and PhD programs compared with undergraduate programs. Despite its problems, this was the approach that was recommended in the Ethiopian context. However, it must be recognized that, since prices will be at best approximate, some HEIs will be tempted to shift the mix of the programs they offer towards those where they make a “profit.” The protection against this in the Ethiopian system is the central allocation of student intakes that makes such “game playing” difficult. If (as expected) in the near future the government devolves student admissions to HEIs, this system will need to be replaced by a contractual relationship whereby each HEI agrees to achieve student targets within different subject programs.

Principle 3: The formula should be based on rough costings and will not be accurate with respect to the actual costs of teaching any or all subjects with any or all HEIs.

The reward for student outcome is intended to operate at institutional level. This means that the reward has to be commensurate to the outcome of an HEI as a whole, and not necessarily fair in terms of any particular subject department (it is up to the HEI to distribute its resources between departments fairly). This means that the costing on which rewards are to be based can be quite rough and ready, provided they are broadly appropriate. In the proposal, each student within each of the subjects within an HEI will be funded according to one of seven “price groups,” as shown in Table 24.1.

Table 24.1Funding formula price groups
Group 1, least expensive subjects (classroom-based subjects)Group 2, intermediate subjects (those requiring more than 30% supported placement or laboratory work)Group 3, more expensive subjects (dentistry, veterinary science, and clinical medicine)
UndergraduatePrice Group A Least expensive, anchored at 1Price Group B IntermediatePrice Group C Intermediate
MastersPrice Group D IntermediatePrice Group E IntermediateNot applicable
PhD, MD, etc.Price Group F IntermediatePrice Group G Most expensiveNot applicable

The choice of only three subject groupings for funding purposes is rather more crude than is common in the rest of the world (the UK and South Africa use four and Australia uses ten), but the use of three “levels” (undergraduate. Masters, and PhD/MD) is fairly conventional. However, all formulas group subjects into categories and therefore in all systems the actual costs of teaching any student may be lower or higher than the average for that weighting band. The assumption was that an individual HEI will find that the formula benefits it with respect to the teaching costs associated with graduating students for some subjects but disadvantages it with respect to the costs within other subjects. Thus, it is likely, though not certain, that the overall effect will be broadly neutral. As stated above, such approximation may encourage profit-maximizing and loss-minimizing behavior unless government either allocates student intakes or sets intake targets at program level. If it is found that the advantages of such a crude categorization of subjects are outweighed by the disadvantages (though this is by no means certain), Ethiopia may decide to develop more precise categories as data become available.

The approximate nature of weightings within the formula compared with actual costs for any particular subject implies that HEIs should not slavishly follow the formula funding when allocating funding to subject departments internally, but rather use it as a rough guide. It also requires that the funds should be allocated in the form of a block grant and HEI managers and boards should be free to allocate them as they see fit, provided that such allocations are transparent and conform to principles of probity and sound financial management.

Principle 4: The formula should be designed to cover all institutional costs except for a limited number of specific items, which should be funded separately.

The reward to an institution from the funding formula is intended to cover a range of indirect costs. Thus the HEI could allocate the budget derived from the funding formula to cover matters such as administrative costs, heating, lighting and utilities, student services, maintenance, repairs, equipment, library, ICT, and other overheads, as well as faculty expenses. This creates an incentive to reduce the subsidy for items unrelated to the academic mission of the HEI such as students’ food and lodging, since the HEI will then be able to allocate more resources to its core business.

The proposal for a funding formula therefore is not dependent on activity-based costing, except so far as teaching students to graduation could be seen as “activity.” It places the responsibility for activity-based costing with institutions themselves: they will have to develop their own budgetary allocations to departments with very different functions, including assumptions about indirect costs. In doing this they will determine not only what the costs are, but also what they should be. This will encourage targeted action on aspects such as the ratio of administrative staff to academic staff: at the moment this ratio (2:1) is very high.

It is important that the values within the formula should not be adjusted to take account of the income generation activity of an institution (that is they would not be adjusted downwards as HEIs develop alternative forms of income). Such additional income could be used to add value or quality to the basic provision by government or to invest in areas of excellence for the future. Thus income generation (except for income from the national system of cost sharing with students) would not affect the funds provided to an HEI by government. This requires that HEIs can hold over any unspent budget to the following year.

In addition, if the formula is to be simple and manageable, a separate system remains necessary for the allocation of funding to run university hospitals, for research and consultancy, for major capital works, for incentives to achieve various government policy objectives, and for funds to support the establishment and initial support for new higher education institutions. In the medium term, a fair and competitive system will be needed to reward relevant and high-quality research and income generation through consultancy. This would provide the incentive to ensure that HEIs develop the kind of research culture and profile that is necessary for income generation through knowledge transfer.

In the short term, one option is for the funding for research and consultancy to come from a premium on the base price of a research student. This has the advantage of simplicity, but it was not recommended as a model, since it relies on the assumption that the number of research students has a linear relationship to the volume and quality of research and consultancy occurring in an HEI. This is highly doubtful: as the numbers of Masters and PhD students increase in a particular university, it might receive additional funding that was not justified by the levels of research produced. Such a system might also encourage an HEI to recruit more research students than it could realistically resource or accommodate.

Another model is to estimate the desirable level of funding for research infrastructure that could “kick-start” the level of research activity and publication for HEIs to develop as significant producers of income from knowledge generation and transfer, and as sources of policy advice and evaluation, and to allocate this to HEIs as a lump sum. This has the advantage of simplicity, but it has the disadvantage that there is no guarantee that it would be used appropriately. The way chosen to ameliorate this disadvantage was to require each HEI to develop a satisfactory strategic plan to develop research capacity and an action plan to spend the funds allocated.

Principle 5: In the initial stages, the formula should be based on those data that are presently available.

The formula might have been driven by rewarding or penalizing all sorts of variables: those students who enter; those who fail to complete each year successfully and those who graduate; the type of student (for example, sex, regional origin, disability, entry qualifications) and the additional costs of teaching them; and institutional characteristics such as size and location. Experience elsewhere suggests that the advantages of a complex funding formula are not great and that such complexity encourages “game playing” by institutions to maximize their funding by reclassifying activity to profitable categories. A more complex formula might lead to a more accurate allocation of the funds for teaching with respect to actual costs, but it is likely that each premium is an inaccurate refection of costs in the case of any one HEI. Where there are many variables in the formula, most institutions will benefit from some premiums but not others. Since the total “pot” of funding for higher education is unlikely to increase with the number of premiums, the effect on the funding of most HEIs is probably broadly neutral.

In Ethiopia, many of these data were not easily available. The number of students enrolled was easily obtained from HEI registries and checked by the Ministry of Education against those allocated to HEIs by subject. However, it is intended that the formula should reward performance and so the allocation is to be based on the numbers of students graduating and successfully completing each year, rather than on those entering. These data can also be easily obtainable from registries and can be audited by the HERQA during accreditation visits. This should eliminate any incentive for HEIs to pass students not reaching required standards.

Non-completion rates could have been dealt with either by funding “drop-out” students for half of any year, or by not funding them at all. Since funding students for half of any year they fail to complete successfully would be paid for by reducing the funding for other students (the total “funding pot” being finite), the effect on the total funding for the average HEI would be broadly neutral whichever system was used. Eliminating all funding for students who fail to successfully complete the year has the advantage of simplicity and fits with the notion of rewarding outcomes. This was chosen as the method of calculation.

Principle 6: Incentives for different activities should be funded through a top-slicing of the funds available for learning and teaching, rather than through the formula itself

All governments wish to influence the direction of higher education, and indeed, as representatives of the society at large, government has the right to do so, provided this right does not conflict with other rights such as academic freedom. It was decided that government should exercise this right through the operation of a top-slice of 10 percent of the overall higher education allocated to HEIs on the basis of their contribution to government priorities. At the present time these priorities include access for disadvantaged students and improving graduation rates. It was decided that the top slice will become an incentive fund outside the formula.

The World Bank’s analysis of the proposed funding formula supported the idea that incentives for various forms of activity should not be included in the funding formula:

Non-base funding comes in addition to the funding provided through the base formula. This type of funding is usually a pool or pools of resources directed to specific purposes, and is therefore somewhat better suited to steering. It also offers more flexibility than base formula funding and can be adapted to address new needs and goals. There are several different types of non-base funding approaches. These include earmarked funding, which is funding dedicated or earmarked for a specific program, mini-formulas, which use an algorithm separate from the base formula to determine how funding is allocated to institutions, and other approaches that are on top of the base formula. In the compass analogy, these non-base funding approaches can often be more precise in targeting coordinates. (Merisotis, 2003)

A system of top-slicing has the additional advantage that incentives can reflect changing national and government priorities (for instance, the support of disadvantaged students and the maintenance of community-based programs) without disrupting the main formula.

The World Bank suggests that HEIs should be rewarded for surpassing previous performance:

Such steering mechanisms tend to work best when they use the baseline performance of an individual institution as the starting point for determining the amount of funding provided. In other words, the pool of resources does not reward those who are already advantaged—it rewards attainment of policy goals in relation to where that individual institution was previously. (Merisotis, 2003)

The problem with this approach in the Ethiopian context is that HEIs are not responsible for the allocation of students and therefore have very limited control over the admission of students from disadvantaged groups, whilst carrying the additional costs that their proper support necessitates. In addition, HEIs have made markedly different amounts of targeted effort to support disadvantaged students. A system which requires HEIs to surpass their previous best would disadvantage those who have good systems already in place.

Another method of allocating incentive funding—used, for example, in the UK—is to set aside funds to be allocated by a competitive bidding process in which each HEI bases its bid on a strategic plan for the utilization of funds and/or past performance in that area. Such a system would require expert staff and expensive and sophisticated assessment systems that do not yet exist in the Ministry of Education. Given the relatively small amount to be devoted to incentive funding, and given that the intention of the new system is to reward performance and outcome, it is not clear that it would have substantial advantages over a simpler system.

It was therefore proposed that 10 percent of the funding available for higher education should be top-sliced to create an “incentive fund” and allocated formulaically (per head) to compensate HEIs for the additional costs of teaching and supporting disadvantaged students, and to reward better-than-average graduation rates for disadvantaged students and students in each price group. This top-slice arrangement allows the government some leeway and to change the criteria in the future if it wishes.

Principle 7: As far as possible, individual HEIs should not be destabilized by the way the formula funding is introduced.

A key issue raised by outcome funding is the funding risk created for the HEIs, since they are not entirely in control of their outcomes: in this case, students’ successful completions of each year and final-year graduations. In part these depend upon factors such as the quality of intake that are determined by government rather than by the institution itself. For example, the Ministry of Education is planning to open 13 new HEIs in the country at the same time as incentives are planned for the expansion of the private sector. If, at the same time, more disadvantaged students are admitted, there is a strong possibility that factors outside of the control of the HEIs will lead to lower graduation rates and more failure at the end of each year of study. Provided that there are not systematic differences between the intakes of different universities, and all are affected to the same extent, and provided that none decides to compensate by lowering examination standards, the net effect on each may not be great, but these provisos do create risk. This risk implies that there must be measures put in place to protect HEIs from the effects of the funding formula and to allow them time to adjust to different levels of funding.

A preliminary analysis of the data produced by the World Bank and Ministry of Education indicates a large variation in the levels of funding per student received by different HEIs within Ethiopia. HEIs could be destabilized or experience unearned windfall profits by the precipitous introduction of a formula. The draft formula was tested and adjusted in the light of historical funding allocations to HEIs in Ethiopia, but it is clear that it should be further reviewed as data became more accurate. Thus, a precipitous introduction of the formula with no safety net could unfairly penalize certain HEIs. In addition, HEIs need time to adapt their costs to any changes in income caused by the introduction of the funding formula. Therefore, it is desirable that, where the historical funding for an HEI implies a unit price markedly different from that which it would receive through the formula, the funding the HEI actually receives should gradually be adjusted over a number of years until it conforms to the formula.

The World Bank analysis suggests that one way of ensuring that HEIs are not destabilized is to use a three-year rolling average of their student numbers within the formula.

To ensure that there is not a “drop off the cliff” phenomenon that results from annual fluctuations, the formula instead could use a simple three-year actual rolling average. The three-year rolling average would be based on an average of each of the three factors for the three years prior to the current year. For example, to calculate the number of diploma and degree program graduates for 2004, the numbers from 2002, 2001, and 2000 would be averaged. This would help to promote system stability as it continues to transition and transform. (Merisotis, 2003)

The problem with this approach is that, in a context of extremely rapidly expanding student numbers, those institutions that had responded positively to the call for rapid expansion would be disadvantaged.

It was therefore proposed that there should be a transitional period to enable HEIs to adjust to the effects of the formula on their funding. In each year the average unit funding an HEI receives for each student through the funding formula will not vary by more than plus or minus 5 percent over that in the previous year, plus an adjustment (determined each year by the government) for inflation and other factors.

Next steps

It is recognized that as Ethiopia’s system becomes more sophisticated and allows additional different modes of study, and as more data become readily available, a more sophisticated formula may be needed. In the introduction of any new system there will be teething problems and adjustments will the needed. In addition, HEIs will need considerable guidance and training in its operation.

It is therefore proposed that a full review and evaluation of the operation of the formula should be undertaken after the first and second year of operation and necessary adjustments should be made to the weightings and some of the rules governing the formula’s operation. This review should take particular account of the fact that the data for the costs of postgraduate courses were especially weak and therefore the weightings were in large part based on anecdotal evidence.


As the development of the formula progressed and discussion occurred it became clear that its introduction offered very real advantages over the previous system. HEI managers supported its introduction and saw it as a prerequisite for the block grant, which in turn offered them a number of efficiencies. In particular they saw the formula as an important protection for HEI autonomy.

The Ministry of Education supported the introduction for various pragmatic reasons (for example, it was a prerequisite for World Bank support and the fact that as the sector expands the ministry can no longer monitor all the various line budgets and so has to delegate this responsibility to the HEIs themselves) but also for other more idealistic reasons such as enabling transparency of funding decisions and encouraging the delegation of budgets which is seen as an essential element of HEI good management. The government is committed to developing more customer centered and outcome-oriented public services, to HEIs being funded for outcome not on the basis of history, and to develop a more responsible approach to students, who should be seen as income earning rather than as expenses.

Historical funding allocation provides an incentive to maximize expenditure and gives no incentive for generating income—it is agreed that this should cease and HEIs become more cost conscious and make more rational choices as to priorities as they exercise the freedom to allocate internal budgets. In turn it seems likely that this will result in better forward planning and the ability to respond more quickly to changing priorities and to offer more attractive salaries for instructors in “hard to recruit” subjects such as ICT. In short, the formula funding and the associated block grant provides incentives for cost saving and income generation by HEIs (underspending and income are not clawed back). On the other hand, HEIs must act responsibly and develop financial systems: they cannot turn to government to bail out unexpected expenses, and therefore must generate surpluses and carry these over from year to year.

It will be found that some HEIs generate higher than average teaching costs. They will have to instigate efficiencies, some of which may be painful and may affect quality in the short term: for example, increasing class size and closing courses that recruit too few students. Others may be more desirable, such as changing teaching and learning methods to reduce class contact time, and a more intensive use of resources and targeting administrative costs, so that a higher proportion of spending goes on the academic mission.

In any case, HEIs will need to rapidly develop systems and processes that are largely absent at the moment. These include mechanisms for making rational decisions about matters such as the amounts to be spent on different activities, staff incentive schemes, and investment in the future. They will be able to target reductions in certain expenditures and increase others. Some may start to undertake asset audits. Importantly, they will need the Management Information System to monitor cost commitments and outgoings, accurately track students, and record the costs of each kind of activity. Preparation for the change should include budget monitoring training for all budget holders so that all managers can read and monitor accounts and marketing systems to attract fee-paying students and consultancy. Each of these requirements is a step change from the present position. In total, the formula forces a modernization of the entire system that could move it in the direction of better governance and management.

The most important benefit of the funding formula may be that it directs institutional attention to the achievement of outcomes that the country needs (more trained personnel). In the longer term the formula may take account of outcomes such as graduate employment, HERQA quality assessments and research volume, quality, and relevance.

In summary, the benefits to HEIs are potentially great, but so are the risks. If managers do not rise to the challenge of devolved budgets, good budget planning and monitoring and more strategic planning for the future, HEIs may end up with resources badly utilized, unmanageable bureaucracy, and crisis management. HEIs may be tempted to “game play” and undesirable institutional behavior may be encouraged.

The government too must develop its infrastructure to allocate its funding according to the formula. So far it has failed to do so. The introduction of the formula was planned for July 2005 but has been delayed for more than a year.

It seems likely that the potential benefits of a funding formula depend upon it being designed to suit the context (the country and the sector) and being informed by best practice from across the world. This implies that consultants from abroad working on such a design will need experience of the sector and knowledge of funding formulas and how they work, but they will also need to spend time in the country, not just enquiring into the financial context, but developing an in-depth understanding of the management; values; and historical, sociopolitical, and cultural contexts in which the formula will operate. Even with such knowledge, they will need to consult often and widely so that unintended consequences of different approaches can be understood and so that the benefits of the change can be maximized.


The full document, The Introduction of a Funding Formula for Teaching and Learning in Higher Education Institutions in Ethiopia, can be found on <>.


    Other Resources Citing This Publication