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Modeling the Spatial Effects of Digital Data Economy on Regional Economic Growth: SAR, SEM and SAC Models

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  • Julia Varlamova

    (Institute of Management, Economics and Finance, Department of Economic Theory and Econometrics, Kazan Federal University, 420008 Kazan, Russia)

  • Ekaterina Kadochnikova

    (Institute of Management, Economics and Finance, Department of Economic Theory and Econometrics, Kazan Federal University, 420008 Kazan, Russia)

Abstract

The potential for the development of digital data and their infrastructure creates new opportunities for economic growth. The purpose of this study was to develop an approach to identify a set of indicators to quantify the data economy and model its impact on economic growth. The cumulative index and Gini coefficient indicated differentiation and disparity in the digital data infrastructure of 85 regions for 2016–2021. In the presence of a positive spatial correlation, digital development does not indicate clear spatial clubs. Selected according to the calculation of Lagrange multipliers and likelihood ratios, panel econometric models with spatial lags, using SAR, SEM and SAC, showed a short-term negative effect and a long-term positive effect of the digital data economy on economic growth, confirmed by the calculation of marginal effects. During the pandemic, the data economy had a positive impact on regional economic growth. The positive spatial effect of interactions between regions detected by the models in the framework of economic growth indicates the synergistic nature of digitalization. The main conclusions of this study provide evidence-based support for the digital transformation of regions and can help create information infrastructure and accumulate human capital to eliminate disparities in the digital development of regions.

Suggested Citation

  • Julia Varlamova & Ekaterina Kadochnikova, 2023. "Modeling the Spatial Effects of Digital Data Economy on Regional Economic Growth: SAR, SEM and SAC Models," Mathematics, MDPI, vol. 11(16), pages 1-31, August.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:16:p:3516-:d:1217206
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    Cited by:

    1. Julia A. Varlamova, Ekaterina I. Kadochnikova, 2024. "Determinants of the Use of Big Data Technologies by Organizations in Russian Regions," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 23(2), pages 422-451.

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