Regional convergence in Russia: Estimating an augmented Solow model

This paper studies convergence in per capita gross regional products across Russian regions in the period from 1996 to 2017. By applying the system GMM technique we estimate growth equations that are directly derived from the classic Solow model, augmented with human capital and migration and considering possible spatial effects. Our main estimates establish a convergence rate of around 2% per year. While interregional migration and interdependencies of the growth of Russian regions contribute to the convergence process, the role of human capital is ambiguous: when we employ system GMM we do not find any significant impact of human capital on regional growth no matter how we measure human capital, while pooled OLS estimates establish a positive contribution. •We study convergence in per capita gross regional products across Russian regions in the period from 1996 to 2017.•Our empirical growth equations are directly derived from the classic Solow model, augmented with human capital and migration.•We find that Russian regions converge with a rate equal to 2.2% per year, remarkably close to the ‘iron law’ of convergence.•This suggests that the long-run economic development of Russian regions is subject to certain universal mechanisms.•We find that interregional migration and the interdependencies of the regional economic growth contribute to convergence.