Abstract

The article is devoted to assessing the relationship between productivity as the most important source of sustainable economic development, and various factors that can explain this productivity. The method of productivity estimation used in the paper takes into account that income is created using not only living labour, but also capital stock. In contrast to previous studies, the paper uses the productivity index that meets the transitivity criterion, which allows for geographical comparisons. To assess the benefits of economic-geographical location (EGL), a new centrality measure is presented that reflects the network nature of territorial connections and allows us to switch to accounting for not only points but also areal objects, particularly the subjects of the Russian Federation. Using the new centrality measure, it is shown that EGL explains the differences in productivity between the regions – the subjects of the Russian Federation in 2010–2016 better than other factors. At the same time, it follows from the estimated model that various properties of the labour force described by the concepts of human capital, and the institutional environment are significantly less related to the observed productivity of regions. To demonstrate the superiority of economic-geographical approaches to explaining productivity, we used relatively new for economic geography methods of machine learning.

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