Institute of Sociology
of the Federal Center of Theoretical and Applied Sociology
of the Russian Academy of Sciences

Manshin, R.V., & Xu, Siqi. (2023). Development of border regions economic interaction: Mechanisms and models. RUDN Journal of Economics, 31(2), 268–281. https: ...



Manshin, R.V., & Xu, Siqi. (2023). Development of border regions economic interaction: Mechanisms and models. RUDN Journal of Economics, 31(2), 268–281. https://doi.org/10.22363/2313-2329-2023-31-2-268-281
ISSN 2313-2329
DOI 10.22363/2313-2329-2023-31-2-268-281
ÐÈÍÖ: https://elibrary.ru/contents.asp?id=54157732

Posted on site: 26.09.23

 


Abstract

In order to develop cross-border circulation of goods and people, the authorities of a country or region can take various measures aimed at creating favorable conditions for cross-border exchange and reducing barriers and restrictions that impede its development. The article explores the mechanisms of cross-border cooperation and proposes a new grouping of them. The author made an attempt to develop a new methodological approach to modeling the development of commodity exchange in the border regions, based on the development of two complementary models — descriptive and prescriptive type. The peculiarity of the author’s approach is to distinguish between target impacts on the result and the “natural” trend in the development of commodity flows and assess the impact of the consequences of target impacts. The proposed descriptive model makes it possible to identify and explain the determinants of the advance or lag in the growth rates of the region’s import-export operations in comparison with the growth rates of the gross regional product. In the descriptive model, there are no estimated indicators that would reflect the level of administrative, logistical, and other barriers in the trade and economic relations of the border regions. To overcome this shortcoming, in combination with the first model, the author proposes to use another model — a normative one, in which the same estimated indicator is chosen as two factor indicators — an aggregated indicator of barriers to cross-border turnover. The idea is that the “height of the barriers” should be measured separately — on each side of the common border of the two border regions. The use of two models in combination allows a better understanding of the reasons for the change in indicators of cross-border transactions in the region. On this basis, decision makers can develop and implement a “road map” to reduce administrative, bureaucratic barriers at border checkpoints.

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