Asian Journal of Agricultural Extension, Economics & Sociology

The way agricultural commodities' prices behave indicates how prices occasionally fluctuate between markets [1]. Comprehensive analysis provides valuable insights into the dynamics of paddy prices in Gujarat, emphasizing the importance of considering both short-term fluctuations and long-term trends. The findings contribute to a better understanding of market behaviour, aiding stakeholders in informed decision-making within the agricultural sector. In order to provide farmers with the knowledge of how much prices fluctuate over time in commodity markets and so increase their revenue, a ten-year study on the price behaviour of paddy was conducted inside the borders of the state of Gujarat (2009-2019). In order to gather statistics, three paddy markets in the state of Gujarat were specifically chosen based on the paddy arrivals that were highest. The trend diagram of the wholesale prices' yearly index number showed constant price fluctuations across the study period. Cuddy Dell Valle Index (CDI) was calculated to measure the instability in yearly and monthly prices.  Based on the investigation, it was determined that paddy displayed a poor stability index within their respective marketplaces. The trend in paddy prices was measured using the linear and quadratic models. For paddy markets, the coefficient of multiple determination (R2) was greater than 70%. Thus, it can be said that a significant portion of the changes in paddy prices over the chosen study period can be attributed to the linear model. In keeping with the quadratic trend, the markets for paddy, or Ahmedabad and Gandhinagar, also showed a positive coefficient of the quadratic term, or T2. Comparing the quadratic and linear model for the markets of paddy the quadratic model performed better in Gandhinagar than the linear model did in Ahmedabad and Surat. Compound rate of increase in annual prices were analysed by exponential model. The rates of growth in the prices of Paddy in Ahmedabad, Surat, and Gandhinagar were 5.80 percent, 5.84 percent, and 4.68 percent, respectively. To separate seasonal variation from the original composite data, a multiplicative model was applied. To arrive at the twelve-month total of 1200 points, these ratios were averaged for each of the twelve months for the whole period. The Ahmedabad market's paddy produced the highest coefficient of seasonal variation (25.84 percent).