Analysis of Trends and Forecast of Minimum Support Price (MSP) in India - Vaishnavi, Lokesha, H., Vedamurthy, K. B., Venkataramana, M. N., Jagannath Olekar.; Somashekar, Surendra, H. S. (Archives of Current Research International, 2024)
This present study was initiated with the objective of analysing the trends in MSP and its forecast to enhance production by providing fair price to the farmers there by ensuring food security and sustainable development of agriculture in the country in view of changing domestic and international market dynamics. The study revealed a significant growth in MSP and has steadily increased over the years for cereals, pulses and oilseeds which highlighted the growing importance of these crops in achieving food security in the country. The increase in MSP is mainly attributed to escalating factor prices in addition to global price factors which was observed during 2007-08, 2012-13 and during 2017-18 with the recommendation of M S Swaminathan Committee due to no parity between factor and product prices coupled with weather-related challenges contributed to rise in MSP across crops. The MSP in India is significantly rising for all the selected crops reflecting the Government's commitment to support and protect the income of farmers. To capture the fluctuations and trends in MSP for all the selected crops, the ARIMA model was employed from the year 1998 to 2023 and evaluated the model's goodness of fit, with R² values of 0.72 for paddy-C, 0.79 for paddy-A, 0.94 for maize, 0.82 for jowar, 0.85 for ragi, 0.90 for red gram, 0.78 for Bengal gram, 0.86 for groundnut, 0.88 for cotton medium staple, and 0.89 for cotton long staple indicated a strong ability to explain the variance in MSP. The accuracy and suitability of the ARIMA model for forecasting the MSP of selected crops were assessed, with potential for improvement in terms of RMSE and MAE for the year 2023-2030. This suggests that the ARIMA model is a suitable choice for forecasting MSP, given its accuracy and simplicity, thereby providing valuable insights for future agricultural policy planning.