Abstract
Background/Objectives: The aim of this study is to choose the methods of economic analysis and develop economic and mathematic models for forecasting and economic growth to enhance the competitiveness of individual companies and the country\'s cotton-textile cluster. Methods: We used a variety of methods and techniques of economic analysis, including abstract thinking, economics and statistics, calculation and design, correlation regression analysis and trend model. Development of a mathematic model of the trend allows solving the problem-providing analysis of forecasting the dynamics of performance indicators. Findings: The factorial analysis findings indicate very high strength of result variation casualty by a variation of factors. According to the analysis, the performance of the industry can be monitored, and timely measures can be taken to eliminate shortcomings in the industrial and economic activities of the industry. The use of cluster model for the textile industry development in Kazakhstan is an important factor to increase the competitiveness of individual companies and the entire cotton-textile industry. Cluster approach allows mobilizing all economic factors in a certain direction. The main prerequisite for the creation of cotton-textile cluster is to restore an intermediate link in the chain of values added of cotton and textile sector for the dynamic development of yarn and fabrics production which today possesses the greatest competitive potential in the country. Further development of the agrarian and industrial complex of Kazakhstan should be guided by increase of competitiveness of agricultural products due to increase of efficiency of the state support and creation of equal favorable conditions for agribusiness development. Applications/Improvements: The obtained results can be used for further research on this issue and for increasing the competitiveness of the cotton and cotton-textile cluster enterprises in the country. Keywords: Competitiveness, Cotton, Cotton-Textile Cluster, Correlation and Regression Analysis, Factorial Analysis, The Republic of Kazakhstan