An Economic Analysis of Changes in Cropping Pattern in Parbhani District of Maharashtra, India: A Markov Chain Approach

The present investigation examines structural changes in the cropping pattern in Parbhani district of Maharashtra, utilizing secondary time-series data on crop areas from 2013-14 to 2022-23. By applying Markov Chain analysis, the study evaluates shifts in cropping pattern by analysing transitions in the area allocated to different crops over time to reveal significant trends through Transitional probability matrix (TPM). Soybean and jowar retained largest area shares. Hence, area under these crops were stable, while sugarcane and soybean emerged as major area gainers, often at the expense of wheat, maize, mung, and safflower. The findings highlight soybean and sugarcane's economic viability and adaptability to local conditions. This analysis underscores the importance of crop selection for economic resilience and sustainable agricultural practices in the region.