Integrating investor risk attitudes into the Index of Economic Freedom with linguistic models and clustering techniques

Abstract

Evaluating economic freedom is essential because it is correlated with economic development and prosperity. The Index of Economic Freedom (IoEF), developed by the Heritage Foundation and The Wall Street Journal, assesses economic freedom via 12 criteria, providing a crucial composite indicator for governments and investors. However, all 12 IoEF criteria are equally weighted and do not account for investors' risk attitudes when measuring economic freedom, limiting their applicability to personalized investment decisions. For instance, cautious investors focus more on the less favorable criteria in the calculation of the IoEF, whereas the opposite is true for adventurous investors. Therefore, this paper introduces a model that incorporates investor risk attitudes into the measurement of economic freedom. This paper is the first to use linguistic quantifiers of the Ordered Weighted Averaging aggregation operator, along with the 2-tuple linguistic model, to generate a more personalized IoEF. Fuzzy C-Means clustering is also employed in this paper to classify 173 countries based on the newly generated IoEF, allowing for membership in multiple clusters and identifying those with high membership degrees in specific clusters. The effectiveness of the proposed model is assessed via a dataset from the Heritage Foundation’s 2022 IoEF. The results show that our model provides more flexible and understandable personalized versions of the IoEF that better reflect investor risk preferences. To further support practical application, we present an interactive web application to visualize the results, demonstrating the model’s reproducibility and helping investors identify suitable investment destinations based on risk preferences.