A spatial-econometric approach to modeling social capital of the Russian regions

Natalia A. Trofimova ()

Economics of Contemporary Russia, 2026, vol. 29, issue 2

Abstract: This study examines the social capital of the Russian regions in the context of their spatial interactions. Social capital is determined by the density of social network connections. The study’s methodological basis is spatial econometric methods, which allow for the analysis of spatial interactions between socioeconomic phenomena. To identify the possible existence of spatial effects in selected Russian regions, global Moran’s IQs were calculated. Spatial effects were estimated using an autoregressive SAR model. Panel data analysis methods were used to obtain a matrix of explanatory variables. Spatial effects were estimated with an autoregressive SAR model. Panel data analysis methods were used to obtain a matrix of explanatory variables. The best result was obtained using a fixed-effects model, which estimates the invariant variables while controlling for individual effects. All calculations were performed using the corresponding module in STATA 16. As a result, it was established that in the context of the proposed definition of social capital, there is a positive spatial autocorrelation of the social capital of neighboring regions of the Russian Federation, which makes possible to improve the quality of the obtained modeling results.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:ack:journl:y:2026:id:1176

DOI: 10.33293/1609-1442-2026-29(2)-21-32

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