A Critical and Comprehensive Study on Paddy Market Trends, Predictive Models, and Stability for Agricultural Revenue Enhancement

Damor Joyal Rupsinh, Tripti Verma, Krishna
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Abstract

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).
关于水稻市场趋势、预测模型和稳定性的关键性综合研究,以增加农业收入
农产品价格的行为方式表明了价格在市场间的偶尔波动[1]。综合分析为了解古吉拉特邦稻米价格的动态提供了有价值的见解,强调了考虑短期波动和长期趋势的重要性。研究结果有助于更好地了解市场行为,帮助利益相关者在农业领域做出明智决策。为了让农民了解商品市场价格随时间波动的程度,从而增加他们的收入,我们在古吉拉特邦境内开展了一项为期十年(2009-2019 年)的稻谷价格行为研究。为了收集统计数据,根据稻谷到货量最高的情况,特别选择了古吉拉特邦的三个稻谷市场。批发价格的年度指数趋势图显示,在整个研究期间,价格持续波动。通过计算卡迪-德尔-瓦莱指数(CDI)来衡量年度和月度价格的不稳定性。 根据调查结果显示,稻谷在各自市场上的稳定指数较低。使用线性和二次模型测量了稻谷价格的趋势。水稻市场的多重判定系数(R2)大于 70%。因此可以说,在所选研究期间,稻谷价格变化的很大一部分可归因于线性模型。与二次方趋势一致,稻谷市场,即艾哈迈达巴德和甘地纳加尔,也显示出二次方项,即 T2 的正系数。比较稻谷市场的二次模型和线性模型,甘地纳加尔的二次模型比艾哈迈达巴德和苏拉特的线性模型表现更好。年价格复合增长率通过指数模型进行分析。艾哈迈达巴德、苏拉特和甘地纳加尔的稻谷价格增长率分别为 5.80%、5.84% 和 4.68%。为了将季节性变化从原始综合数据中分离出来,采用了乘法模型。为了得出 12 个月的总计 1200 点,对整个时期 12 个月中每个月的这些比率进行了平均。艾哈迈达巴德市场稻谷的季节变化系数最高(25.84%)。
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