Spatial dependence across US counties: an integrated gravitational, Moran and entropy-based approach

Purpose The aim of this study is to investigate spatial economic dynamics in the United States by assimilating gravitational models, spatial analysis and entropy-based measures. Particularly, the paper examines how economic attractiveness and factors' mobility shape regional concentration patterns, extending the traditional notion of gravitational fields to a multidimensional framework including structural, performance and mobility-related variables across American counties. Design/methodology/approach The research combines an econophysical framework based on gravitational fields with spatial statistical techniques. A gravity model is employed to capture economic interactions and regional attractiveness, while Moran's I is used to detect spatial autocorrelation in the distribution of economic variables. Entropy provides a global measure of the distribution of economic and demographic activity. The study relies on county-level datasets and spatial weight matrices to model interactions. The analysis includes gross domestic product and population as structural variables, the financial performance index (FPI) as a performance indicator and net migration as a behavioral proxy. Findings The results highlight considerable spatial dependence in the US economic system, with clear clustering patterns. The gravitational approach identifies major poles of economic attraction, while Moran's I confirms the existence of spatial autocorrelation in the distribution of economic activity. Entropy reveals divergence between demographic and economic spatial distributions. The findings suggest that economic dynamics are not randomly distributed in space but are influenced by spatial interactions and structural heterogeneity. Originality/value This contribution combines econophysics and spatial econometrics within a unified framework. By linking gravitational models with Moran's I and entropy-based measures, it offers a comprehensive interpretation of spatial patterns, highlighting the importance of considering spatial structure in empirical analysis. The paper also underscores the relevance of methodological choices, such as spatial weights, in interpreting spatial economic dynamics.