Optimization of Cropping Pattern in Madhya Pradesh for Risk Minimization

Abstract

Cropping-pattern decisions involve trade-offs among returns, risk, resource use, and diversification. This study evaluated a risk-minimising cropping pattern for Madhya Pradesh using the Markowitz mean-variance quadratic programming framework. The study was undertaken to identify an optimised cropping pattern for Madhya Pradesh using the Markowitz mean-variance quadratic programming formulation. The study used 15 years of data from 2005-06 to 2019-20. The suggested Kharif-season cropping pattern involved reducing the areas under paddy and soybean while increasing the areas under cotton, maize, black gram (Urd), and red gram (Arhar). Similarly, for the Rabi season, the suggested cropping pattern allocated a lower area to wheat than the existing cropping pattern. The area under gram was maintained at approximately its existing level, whereas the areas under rapeseed and mustard and lentil increased substantially in the suggested cropping pattern. The suggested cropping pattern reduced risk while increasing returns and also had greater diversity than the existing cropping pattern. The policy recommendations include improved labour management and reduced labour requirements for labour-intensive crops such as wheat, paddy, and cotton. The Government should focus on stabilising the production and prices of soybean and black gram (Urd) to reduce risk.