Spatial correlation across multiple economic sectors through the North American Industry Classification System: a multivariate Moran’s I approach

Purpose This paper investigates spatial interdependencies among economic sectors in the USA using Multivariate Moran’s I applied to county-level employment data classified according to the North American Industry Classification System (NAICS). The study aims to identify patterns of sectoral co-location, spatial clustering and regional economic interdependence, providing an exploratory framework for understanding the spatial organization of the US economy. Design/methodology/approach The study uses a spatial econometric framework based on queen contiguity matrices and Multivariate Moran’s I. County-level employment data across 14 major NAICS sectors are analysed to detect spatial autocorrelation and intersectoral relationships. The analysis is complemented by a network-based interpretation in which sectors are represented as interconnected nodes linked through significant spatial correlations. Findings The results reveal distinct spatial economic clusters, including industrial agglomerations, consumer-oriented urban economies and financial and managerial hubs. The analysis also identifies negative spatial relationships between metropolitan knowledge-intensive sectors and territorially dispersed population-serving activities. Furthermore, some sectors occupy structurally central or bridging positions within the spatial network, suggesting differentiated roles in regional integration and specialization across the US economy. Originality/value This paper contributes to the literature by integrating Multivariate Moran’s I with a network-based interpretation of sectoral spatial relationships. Unlike traditional spatial autocorrelation studies focused on single sectors or variables, the analysis examines interdependencies across multiple economic sectors simultaneously. The study provides an exploratory perspective on how sectoral co-location, divergence and structural centrality shape regional economic organization in the USA. By combining multivariate spatial econometrics with network analysis, the paper offers a novel framework for interpreting spatial economic structures and intersectoral connectivity.