Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Introduction. The modern Russian economy is facing serious problems in the field of labor resources, which leads to high unemployment and low wages. The development of effective solutions requires conducting evidence-based programs, including actions at the enterprise level, the regional labor market and the national level. The options offered to date by various researchers for assessing the employment and income of the rural population are characterized by an aspect and a lack of an integrated approach. Insufficient attention is paid to the integration of estimates, as well as the development of forecast values based on the expected dynamics of stochastic factors. The purpose of the study is to develop a methodology for assessing the employment of the rural population in the production of beekeeping products. Methods. The state and dynamics of the beekeeping industry development was analyzed on the example of the Perm Region. The study of indicators for assessing the employment level of the rural population included the effect of stochastic factors. The uncertainty influence was accounted by the use of correlation and regression analysis and a multidimensional model. The development of a population assessment methodology was based on the method of mathematical modeling. Results. The influence percentage of stochastic factors on changes in the employment level of the economically active population and the complex impact indicator of factors on the of employment level and incomes of the rural population of the Perm Territory were calculated with a forecast for 5 years. Conclusions. The proposed approach will make it possible to more effectively monitor the trends and dynamics of beekeeping development, which will further help to develop effective support measures for this industry.
Introduction. The modern Russian economy is facing serious problems in the field of labor resources, which leads to high unemployment and low wages. The development of effective solutions requires conducting evidence-based programs, including actions at the enterprise level, the regional labor market and the national level. The options offered to date by various researchers for assessing the employment and income of the rural population are characterized by an aspect and a lack of an integrated approach. Insufficient attention is paid to the integration of estimates, as well as the development of forecast values based on the expected dynamics of stochastic factors. The purpose of the study is to develop a methodology for assessing the employment of the rural population in the production of beekeeping products. Methods. The state and dynamics of the beekeeping industry development was analyzed on the example of the Perm Region. The study of indicators for assessing the employment level of the rural population included the effect of stochastic factors. The uncertainty influence was accounted by the use of correlation and regression analysis and a multidimensional model. The development of a population assessment methodology was based on the method of mathematical modeling. Results. The influence percentage of stochastic factors on changes in the employment level of the economically active population and the complex impact indicator of factors on the of employment level and incomes of the rural population of the Perm Territory were calculated with a forecast for 5 years. Conclusions. The proposed approach will make it possible to more effectively monitor the trends and dynamics of beekeeping development, which will further help to develop effective support measures for this industry.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.