Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 20, Pages: 1-8
Ainur Yergazievna Yesbolova1*, Saltanat Saparbaevna Ibraimova2 , Aziza Toymahanbetovna Mergenbaeva2 , Gulnara Zharasovna Urazbayva2 , Shahlo Amankulovna Narkulova2 and Aizhan Urinbasarovna Abishova2
1A. Yassawi International Kazakh-Turkish University, Turkistan, Kazakhstan; [email protected] 2M. Auezov South Kazakhstan State University, Shymkent, Kazakhstan
*Author for correspondence
Ainur Yergazievna Yesbolova
A. Yassawi International Kazakh-Turkish University, Turkistan, Kazakhstan; [email protected]
Background/Objectives: The article is aimed to assess the relationship between factors and determine predictive values of growth of the main indicators characterizing the development of the poultry industry in Kazakhstan. Methods/Statistical Analysis: We used such research methods in the study as analysis and synthesis, calculation and design methods, factor analysis, correlation and regression analysis and econometric methods and models for substantiation of poultry sector development in the country; identifying the link between performance indicator and factors determining it. Findings: The value of this article consists in developing proposals formulated as a result of calculations by statistical and econometric methods and models. According to the results of the study we identified and assessed factors influencing the efficiency of the poultry industry indicators. The econometric and correlation-regression models of forecasting and development of the poultry industry economy have been worked out, the impact of the selected factors on the production of poultry meat in the country has been identified and quantified and the extent of their impact on the industry growth and development has been revealed. Improvements/Applications: The research results can be used to develop strategic plans for the future and to enhance the competitiveness of the poultry industry in the country.
Keywords: Econometric Models, Factor Analysis, Forecast, Poultry Industry, Productivity, Regression Analysis
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