In this paper, we propose a method to measure competitiveness performance at the subnational level, with an application to Peruvian regions. For this, we propose a benefit-of-the-doubt composite index that summarizes the information of several indicators that characterize competitiveness. It is based on an optimization approach, using data enveloping analysis (DEA) techniques, so that each indicator is weighted in an endogenous way, and each unit is evaluated in the most favourable light. Our proposed index is a non-radial variant of the typical DEA scores, which avoids the traditional pitfalls of DEA-based composite indices, such as unreasonable weights. Additionally, we propose a meta-frontier approach in order to compare the competitiveness performances across different periods of evaluation. Our assessments of the Peruvian regions’ competitiveness performance improve on the results of traditional DEA methods, which award high marks to regions with very heterogeneous performance (i.e., regions with very high scores in some indicators, and very poor in others). Additionally, the comparison of the performance across time shows a general decrease in the average competitiveness between 2008 and 2014 of the Peruvian regions.

In this paper, we propose a method to measure competitiveness performance at the subnational level, with an application to Peruvian regions. For this, we propose a benefit-of-the-doubt composite index that summarizes the information of several indicators that characterize competitiveness. It is based on an optimization approach, using data enveloping analysis (DEA) techniques, so that each indicator is weighted in an endogenous way, and each unit is evaluated in the most favourable light. Our proposed index is a non-radial variant of the typical DEA scores, which avoids the traditional pitfalls of DEA-based composite indices, such as unreasonable weights. Additionally, we propose a meta-frontier approach in order to compare the competitiveness performances across different periods of evaluation. Our assessments of the Peruvian regions’ competitiveness performance improve on the results of traditional DEA methods, which award high marks to regions with very heterogeneous performance (i.e., regions with very high scores in some indicators, and very poor in others). Additionally, the comparison of the performance across time shows a general decrease in the average competitiveness between 2008 and 2014 of the Peruvian regions.