Economic Viability of Rice Cultivation in Punjab and Uttar Pradesh, India: A Cost and Profit Analysis
Padigapati Venkata Naga Sindhuja, Popavath Bhargav Naik, Perka Shiva Kumar, Selvaprakash Ramalingam, Konda Ramanjaneya Reddy, Hemanth D B, Alka Singh
Journal of Scientific Research and Reports · pp. 9–19 · Published 10 Feb 2025
10.9734/jsrr/2025/v31i22821Abstract
Aims: The main objective of this study is to analyse the profitability of rice crop in Punjab and Uttar Pradesh and investigate the factors influencing the cost structure of rice farming. Study Design: This study utilized secondary data from the Directorate of Economics & Statistics, the Department of Agriculture & Farmers' Welfare (DA&FW), and the Commission for Agricultural Costs and Prices (CACP). Place and Duration of Study: The study primarily focused on Punjab and Uttar Pradesh. Starting from 2001-02, every fourth year was selected up to the most recent available data. Finally, the selected points of years were 2001-02, 2005-06, 2009-10, 2013-14, 2017-19, and 2020-21. Methodology: This study employed various cost concepts to assess the profitability. A Panel Instrumental Variable (IV) regression analysis was conducted to assess the cost structure and the Hausman test was done to select appropriate model between fixed and random effects. Results: In Punjab, the profitability ratio remained above one for all the selected years, whereas in Uttar Pradesh, it was either close to or slightly below one at Cost C3. Additionally, in Punjab, the profitability ratio consistently exceeded two, while in Uttar Pradesh, it was just above one at Cost A2+FL. This indicates that rice cultivation was significantly more profitable in Punjab compared to Uttar Pradesh. The cost structure was primarily influenced by yield and price fluctuations, both of which were statistically significant. Conclusion: The results indicate a significant disparity observed in profitability between Punjab and Uttar Pradesh states and highlight that total costs significantly impact technology adoption and price movements, with last year's market conditions influencing current production costs.
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