Methodology for the latent indicators formation

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The food industry is the most important link in the food realm of the country, determining the possibility of its autonomous existence in critical situations. This type of industry plays a leading role in solving the issue of providing the population with food products in a sufficient range and quantity. The food industry is in demand all over the world, since the need for food is the basic need of every person. The uniqueness of the Russian food industry is determined by its close connection to regional peculiarities and, as a result, the uneven distribution of food industry enterprises across the country. The study is devoted to the analysis of interrelationships of the food industry indicators with the indicators of the socio-economic sphere and the formation of latent indicators of the economy according to the indicators of de- velopment of the food industry on the example of the Volga Federal District. The paper presents a multidimensional study of the closeness of relationship between the indicators of the food industry and the indicators of the socio- economic sphere using canonical analysis. The indicators of the food industry have the greatest connection with the indicators of public health, since the significant coefficient of canonical correlation in 2019 was more than 0.6. In this group of indicators, the analysis of canonical correlation revealed that such indicators as the production of livestock and poultry for slaughter, as well as the gross harvest of vegetables, have the most significant influence. The coefficients for the indicators of total fertility and mortality rates are dramatically high in the studied groups. This indicates that the de- terioration in the quality and quantity of products will lead to a decrease in the birth rate and an increase in the mortality rate. In this paper, based on canonical variables, the visualization of multidimensional data is carried out and a method for classifying regions in according to their resources and potential is proposed. The results of clustering focusing on the plant resources and trade potential show which territorial authorities situated close can exchange technological experi- ence and provide support to each other. The paper also ranks the entities of the Volga Federal District, according the degree of impact of the food sector indicators with the use of latent indicators.

About the authors

Alla Yu. Trusova

Samara National Research University

Author for correspondence.
ORCID iD: 0000-0001-7679-9902

Candidate of Physical and Mathematical Sciences, associate professor of the Department of Mathematics and Business Informatics

Russian Federation, 34, Moskovskoye shosse, Samara

Alla I. Ilina

Samara National Research University

ORCID iD: 0000-0002-7624-5771

senior lecturer of the Department of Mathematics and Business Informatics

Russian Federation, 34, Moskovskoye shosse, Samara


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