scholarly journals Modified localization coefficients for cluster processes identification: a comparative analysis (case study: the Russian rye sector)

2020 ◽  
Vol 161 ◽  
pp. 01008
Author(s):  
O V Kostenko
Keyword(s):  
Comparative Analysis ◽  
Winter Rye ◽  
Gross Regional Product ◽  
Regional Product ◽  
Cluster Processes

The paper presents the results of the identification of agrarian clusters. Research is done in connection with the rye sector of Russia taken as a case study. The localization coefficients were calculated from the gross yield of winter rye grain. Two variants of calculating coefficients were compared – in proportion to the indicators of the gross regional product and employment statistics. Studies have shown that the coefficients in proportion to the gross regional product are more sensitive and allow a more subtle diagnosis of cluster processes. Localization coefficients in proportion to employment statistics are a more stringent method for identifying clusters.

Forecast estimates of the gross regional product of the Republic of Sakha (Yakutia) for 2020–2025, taking into account the coronavirus pandemic impact

2021 ◽  
Vol 19 (2) ◽  
pp. 339-359
Author(s):  
Gavril N. OKHLOPKOV
Keyword(s):  
Mathematical Modeling ◽  
Comparative Analysis ◽  
Methodological Approach ◽  
Gross Regional Product ◽  
The Republic ◽  
Regional Product

Subject. This article deals with the system of indicators of forecasting gross regional product and their relationship. Objectives. The article aims to obtain projections of the gross regional product of the Republic of Sakha (Yakutia) for 2020–2025. Methods. For the study, I used the methods of mathematical modeling in economics. Results. The article calculates and conducts a comparative analysis of the scenario forecast estimates of the gross regional product of the Republic of Sakha (Yakutia) for 2020–2025. Conclusions. The developed methodological approach, based on a phased prediction of gross regional product, provides forecasting for various variants of the coronavirus pandemic impact on the region's economy.

scholarly journals Modeling of the relationship between gross regional product, labor force, and employment: The Lipetsk Oblast case study

2020 ◽  
Vol 18 (5) ◽  
pp. 870-890 ◽  
Author(s):  
E.I. Kozlova ◽  
M.A. Novak ◽  
M.Yu. Karlova
Keyword(s):  
Multiple Regression ◽  
Linear Models ◽  
Linear Equations ◽  
Gross Regional Product ◽  
Labor Costs ◽  
Correlation And Regression Analysis ◽  
Forecast Models ◽  
Regional Product ◽  
The Relationship

Subject. This article discusses the prospects for growth of Russia and its regions' economies. Objectives. The article aims to identify causal relationships between gross regional product as the main economic growth indicator of a particular region and labor costs. Methods. For the study, we used a correlation and regression analysis. Results. The article presents trend forecast models and linear equations of multiple regression. It finds that all capital factors have a stronger impact on public product of the Lipetsk Oblast than the labor ones. Regarding labor factors, only the average per capita income of the population has a direct impact on the formation of the Lipetsk Oblast's GRP. Conclusions. The identified relationships between the Lipetsk Oblast's GRP and exogenous variables help define the hierarchy of linear models that provide extensive analytical information on the formation of the Lipetsk Oblast's GRP. In linear models, there is no significant relationship between the changes in the working population of the Oblast and the regional product. To adequately describe the dynamics of the Lipetsk Oblast's GRP, it makes sense to apply a set of linear models of multiple regression.

Sign in / Sign up

Export Citation Format

Share Document