Abstract:

Governments provide support to Higher Education Institutes (HEI) due to the benefits for both individuals who ear a professional degree and the society in general. Therefore, Governments are particularly interested in funding the public HEI (P-HEI) activities of research, teaching, and knowledge dissemination. However, one issue is to evaluate the P-HEIs’ efficiency because many variables are involved. The process evaluation is necessary because funds are public (taxes), and their allocation depends on P-HEIs’ efficiency.

In this work, a framework based on a linear programming model called Data Envelopment Analysis (DEA) is proposed to evaluate the relative effectiveness of P-HEIs. DEA, a non-parametric method, aims to compute how a decision-making unit (in our case P-HEI) utilises the available resources to generate some outputs. The changes in efficiency over time are calculated using the Malmquist index.

In our framework, the resources of every P-HEI are the public funding, the number of researchers, and lecturers; meanwhile, the outputs are accredited under- and post-graduate programmes, journal papers, number of cites, alumni, granted patents, and edited journals.

To test our framework, a dataset of Mexican P-HEIs is downloaded from http://www.execum.unam.mx, and an R script is programmed to allow the reader to reproduce the results.

The proposed framework computes efficiency with different assumptions such as constant and variable returns of scale. Our results classified the P-HEIs as relative efficient and inefficient; more important for relative inefficient P-HHEI, our framework reports the set of P-HEIs than an inefficient one can be compared with to increase its efficiency. Finally, the framework computes the changes in the levels of the inputs and outputs to reach 100% efficiency of inefficient P-HEI.

Keywords:

Efficiency HEI, Data Envelopment Analysis, Malmquist index.