Open AccessFACTOR ANALYSIS OF PRODUCTION ECONOMIC INDICATORS IN AGRICULTURAL SECTOR
Author(s) -
B. D. Sharipova,
A. T. Baktgereyeva
Publication year - 2020
Publication title -
problemy agrorynka
Language(s) - English
Resource type - Journals
eISSN - 2708-9991
pISSN - 1817-728X
DOI - 10.46666/2020.2708-9991.15
Subject(s) - interdependence , agriculture , production (economics) , agricultural productivity , econometrics , factor (programming language) , computer science , order (exchange) , operations research , risk analysis (engineering) , mathematics , economics , business , geography , microeconomics , programming language , archaeology , finance , political science , law
The task of the research is to display modern method of applied mathematics - factor analysis, which allows to determine the interdependent and interdependent phenomena and processes of agricultural activity. Some of them are directly related to each other, others are indirectly. Hence it follows that important methodological aspect is the study of factors and their influence on the value of economic indicators under study. The factor analysis method is illustrated by the example of agro-industrial complex of Zhambyl region of Kazakhstan. Its performance indicators in the conditions of irrigated agriculture are presented. The results of forecasting the yield of agricultural crops are given, economic and mathematical models of the development of agricultural production are developed. A system for managing the marketing activities of agricultural enterprise and schemes of information interaction, principles and methods of modeling are proposed. The relationship between the numbers obtained as a result of processing the investigated mathematical phenomena is determined, some of them are fundamental and underlie all procedures of factor analysis. Significant elements are shown that create correlation matrix model between variables. Averaging was performed in order to smooth out fluctuations in production factors in dynamics. As a result, multivariate statistical methods are promising. The authors state that the use of factor analysis objectively and comprehensively reflects the current situation in agriculture of the region under study.