Applied Mathematical Studies in Risk Management Strategies and Crop Insurance in Agriculture
Journal: International Journal of Science and Research (IJSR) (Vol.4, No. 2)Publication Date: 2015-02-05
Authors : Dhananjaya Reddy;
Page : 935-938
Keywords : crop insurance; agricultural productivity; risk; mathematical formulation;
Abstract
Rural population depends on agriculture that is major source of income for livelihood. The agricultural work is sensitive to variation of external uncontrollable environmental parameters as well as some controllable parameters that are vulnerable to risk on return on investment. The Indian business cycle is influenced by the crop pattern that mainly depends on the vagaries of nature, every flood or drought has its own impact on the Indian economy. Agri-business encompasses whole lot of activities of agriculture sector under one umbrella, like integration of production, processing and marketing. The process starts at the product level and reaches out to the final consumers through vertical integration. Agribusiness favors Indian farmers in every possible way be it policy, climate and several other advantages points that India inherently possess in production. Agricultural insurance is seen as one of the best strategies to address farm risks and encourage farmers to embrace modern production practices with greater potential for better and quality yields. Crop insurance serves as an effective institutional mechanism to cope with production risks. Crop insurance is an important measure/instrument used by farmers for mitigating the financial losses due to various types of natural calamities/risks which damage and destruct the production. The Analysis is based on identifying linkage of agricultural productivity with energy intensity, rainfall and consumption of fertilizer by statistics and mathematical formulation of the system dynamics. In modeling farm systems it is widely accepted that risk plays a central role. Furthermore, farmers risk aversion determines their decisions in both the short and the long run. This paper presents a methodology based on multiple criteria mathematical programming to obtain relative and absolute risk aversion coefficients.
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