| Issue |
SHS Web Conf.
Volume 106, 2021
III International Scientific and Practical Conference “Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth” (MTDE 2021)
|
|
|---|---|---|
| Article Number | 01003 | |
| Number of page(s) | 9 | |
| Section | Digital Technologies in Socio-Economic Systems Management | |
| DOI | https://doi.org/10.1051/shsconf/202110601003 | |
| Published online | 18 May 2021 | |
Economic complexity and inclusion of regional economies
Central Economics and Mathematics Institute of the Russian Academy of Sciences, Moscow, Russia
* Corresponding author: mi.afan@yandex.ru
The paper presents a probabilistic interpretation of the elements of the matrix, which is used to assess the economic complexity in accordance with the traditional approach. Their properties are given, on the basis of which aggregate indicators are introduced that characterize the nesting of the structures of strong sectors of regional economies. It is shown that aggregate nesting indicators are statistically significant explanatory variables for economic complexity. It is proved that the used procedure for calculating the economic complexity is correct in the sense of the existence and uniqueness of the solution. It is shown that the data that are used to assess the economic complexity in accordance with the author’s approach allow to reflect the formation of value chains and groups of related sectors focused on both the external and internal markets. For this economic complexity, calculated on regional data, its high values correspond to large values of the aggregated nesting indicators. Low values of economic complexity correspond to low values of nesting indicators.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.