Abstract

Improving the productivity of higher education in every nation's economy is one of the main challenges faced in the current environment of competition and shrinking public funds. The effective use of resources is a crucial issue in Chile's higher education reform. Data envelopment analysis (DEA) has been widely applied to measure efficiency in universities, sometimes focused on teaching or research. Universities function as a complex pro-duction process in which teaching and research are linked in the internal structure, share some inputs, and continue across multiple periods. To deal with this complexity, we developed a new DEA model that incorporates network structures, carryover activities, and shared inputs in a dynamic approach. We applied this model to a set of 33 Chilean universities and compared the results to their rankings and accreditation status. Our proposed DEA model has advantages: (a) there are no subjective criteria, and (b) the model considers the internal structure of the university production model, as well as the inputs and outputs over time. The objectivity of the model allows us to evaluate overall efficiency in terms of the quantity and quality of teaching and research, removing exog-enous criteria and judgments regarding the performance of higher education institutions. This new quantitative approach could generate disaggregated data to analyze efficiency improvement over time or serve as a bench-marking tool according to the universities' characteristics.