Principal investigator: Viviane Pires Ribeiro
Article title: BRAZILIAN FEDERAL UNIVERSITIES: RELATIVE EFFICIENCY EVALUATION AND DATA ENVELOPMENT ANALYSIS
Article authors: Alexandre Marinho, Marcelo Resende and Luís Otávio Façanha
Location of the intervention: Brazil
Sample size: 52 federal institutions of higher education
Sector: Education
Type of Intervention: Measuring the relative efficiency of Brazilian Federal Universities
Primary variable of interest: Relative efficiency
Evaluation method: Other – Data Envelopment Analysis
Evaluation Context
The study of multi-product non-profit organizations is the subject of growing interest in the empirical literature. The main difficulty associated with evaluating these entities is related to a precise characterization of their technologies. Universities and professional hierarchies constitute a good example of this type of organization, since their technologies are characterized by multiple factors of production and products, and profit maximization is not the organization's main objective. Furthermore, their operations are guided by various missions and general objectives. Consequently, efficiency cannot be simply defined, and the question of efficiency measurement becomes a central challenge for research and management.
Intervention Details
Marinho et al. (1997) consider the efficiency measurement approach provided by Data Envelopment Analysis (DEA) in the context of the public sector. The application covered the main Brazilian federal universities for the year 1994, totaling 52 Federal Institutions of Higher Education (IFES), and each IFES was treated as an individual productive unit (DMU).
Some of the production input variables used in the analysis were: building area; hospital area; laboratory area; total number of students; faculty with doctorates; faculty with master's degrees; administrative staff with undergraduate or higher education degrees; budget for current expenses; students who started undergraduate courses. Some of the production variables were: number of undergraduate courses; number of postgraduate courses – master's and doctoral levels; certificates issued – undergraduate degree; number of approved master's dissertations; number of approved doctoral theses; weighted average or MEC evaluation of master's and doctoral courses.
Most of the data were obtained from the Ministry of Education (MEC) and the National Association of Directors of Federal Institutions of Higher Education (ANDIFES). Information on current expenses, obtained from a public report released by ANDIFES, was also considered. Thus, given the large number of factors of production and products, the authors raised the possibility of using factor analysis to explore common dimensions in the dataset.
Methodology Details
The methodology adopted by Marinho et al. (1997) is Data Envelopment Analysis, a flexible empirical technique for measuring comparative efficiency and a non-parametric method that employs mathematical programming to construct production boundaries of productive units, using similar technological processes to transform multiple inputs into multiple outputs. DEA evaluates the efficiency of non-profit organizations, with universities being good examples of complex management problems. Efficiency is measured against observed best practice. Furthermore, the methodology also addresses the difficulties arising from the unavailability of data on market prices, factors of production, and products.
DEA models allow for two orientations: increasing output (product orientation) or conserving production inputs (input orientation). In the first case, efficiency refers to achieving the maximum level of output given a fixed use of inputs. In the second case, efficiency refers to the minimum use of inputs given a level of output. When there are constant returns to scale, the hyperplane of the efficiency frontier is linear and passes through the origin; in this case, both orientations produce the same efficiency results. When there are variable returns to scale, this is no longer the case. However, empirical practice seems to show that the choice of inputs and outputs to be used in the analysis is the best choice, rather than the choice of orientation.
Results
Marinho et al. (1997) developed a data envelopment analysis application using information on Brazilian federal universities. The authors conducted an experiment using the DEA (Data Envelopment Analysis) of the Federal University of Rio de Janeiro, as part of their budgetary and institutional evaluation activities, with challenging and positive motivations. The ranking of production units was generated according to the efficiency score and suggested the importance of university management activities. Furthermore, a notable result is that most of the recognized Federal Institutions of Higher Education (IFES) in the academic community were evaluated as efficient production units.
The production units that presented 100% efficient results constituted the "efficient frontier". The authors emphasize that the exploration of common dimensions in the dataset, through factor analysis, was fundamental to allowing an adequate discrimination of the DMUs.
According to the authors, the objective of motivating the systematic application of data envelopment analysis as a subsidiary policy tool was not fully met. Therefore, new information and inventories will certainly improve the results of DEA applications.
Lessons in Public Policy
How to measure the relative efficiency of Brazilian Federal Universities? Given that data envelopment analysis evaluates the efficiency of non-profit organizations, this alternative technique can be used in the study of the efficiency of higher education institutions. In Marinho et al. (1997), the authors emphasize that DEA provides targets for each factor of production and output; in this sense, the menu can serve as an information support for the planning and monitoring of the activities of productive units. Thus, this type of analysis can be especially useful for measuring comparative efficiency and can therefore constitute an important management tool in the domain of complex organizational systems, characterized by multiple inputs and multiple outputs (even in cases where the technology is not well known) and where budgetary and financial support needs stronger coordination and monitoring instruments.
Reference
MARINHO, A., RESENDE, M., FAÇANHA, LO Brazilian Federal Universities: Relative Efficiency Evaluation and Data Envelopment Analysis. Brazilian Journal of Economics. v. 51, no. 4, p. 489-508, 1997.
