The objective of this article is to propose a new methodological approach to determine the level of competitiveness of subnational territories (regions). To this end, the relationship between regions’ economic performance and the determinant of regional competitiveness is studied. The regions’ level of competitiveness can be considered an unobserved effect and, to determine it, a model is proposed that takes into account unobserved heterogeneity, which is postulated to be a simplification of regional competitiveness within a country, that is, the element that can explain the differences in the region’s economic performance. An econometric panel data model with fixed effects using the dummy variables technique is proposed. The dependent variable represents a model region and is constructed by averaging all of the regions’ GDPs in real terms, as an approximation of a model region. For the independent variables, five dimensions are proposed to explain regional competitiveness. The data used are based on 91 variables for each one of the 25 regions of Peru from 2012 to 2018. The main finding is proof that the model is significant and correlates with the theoretical model. In this sense, the proposed model adequately explains the economic performance of the model region, and the estimations for each of the regions of Peru are relevant when it comes to measuring the differences between them in order to have a new way to measure regional competitiveness.
Carpio, L. D., Marquina, P., & Avolio, B. (2023). Measuring Regional Competitiveness. Global Business Review, 0(0). https://doi.org/10.1177/09721509221145445