Econometric Modeling for High Impact Sustainable Organic Tea Production: The Box-Jenkins Approach

Ram Prasad Chandra
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Abstract

India is world’s second leading tea producer, and biggest consumers in the worldwide. The main objective of this investigation is to identify the Box-Jenkins method an Autoregressive integrated moving average (ARIMA) models that can be used to make predictions the production and yield of tea in India. In this study considered the published yearly secondary data of tea production and yield in India period of 1970-71 to 2021-22. In accordance to the Sigma square, RMSE, MAPE, MAE, AIC and SIC the most appropriate models for prediction the tea production, and yield in India are ARIMA models (1, 1, 1) and (0, 1, 1). Acceptability of the selected models has been verified with the Ljung-Box test, ACF, PACF criterion, and white noise followed by residual diagnostics. Comparison between the original data series and the estimated data series in the similar manner indications that the fitted model performs good statistically and is suitable for forecasting 19 year (period of 2022-23 to 2040-41) the tea production and yield in India i.e., the models are good prediction during and beyond the forecasting period; and we have estimated that the annual amount of tea production and yield achieved in the year 2022-23 is 13500.17 lakh tonnes and 2119.73 kg/ha respectively, which will accelerate to reach 16728.34 lakh tonnes and 2444.34 kg/ha in the year 2041-41 respectively.
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高影响力可持续有机茶叶生产的计量经济学建模:方框-詹金斯方法
印度是世界第二大茶叶生产国,也是全球最大的茶叶消费国。这项调查的主要目的是确定 Box-Jenkins 方法和自回归综合移动平均(ARIMA)模型,用于预测印度茶叶的产量和收益率。本研究考虑了 1970-71 年至 2021-22 年期间公布的印度茶叶产量和收益率的年度二手数据。根据西格玛平方、RMSE、MAPE、MAE、AIC 和 SIC,最适合预测印度茶叶产量的模型是 ARIMA 模型(1,1,1)和(0,1,1)。所选模型的可接受性已通过 Ljung-Box 检验、ACF、PACF 准则以及白噪声和残差诊断进行了验证。原始数据序列与估算数据序列之间的比较表明,拟合模型的统计性能良好,适合预测印度 19 年(2022-23 年至 2040-41 年)的茶叶产量,即我们估计 2022-23 年的茶叶年产量和单产分别为 13500.17 千吨和 2119.73 千克/公顷,到 2041-41 年将分别达到 16728.34 千吨和 2444.34 千克/公顷。
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