{"title":"Behaviour of Prices of Groundnut in Northern Hills of Chhattisgarh","authors":"Ankur Kumar Rathore","doi":"10.18782/2582-2845.8673","DOIUrl":null,"url":null,"abstract":"This study attempted to guide the farmers and planners for reliable and specific information concerning the prices of Groundnut in the Northern Hills agro-climatic zone of Chhattisgarh. The time series data of prices was taken monthly from January, 2010 to March, 2021 (135 months) and it was used to forecast the prices for upcoming 24 months i.e. April, 2021 to March, 2023. The time trend analysis of prices of groundnut were found sharpely increasing over the study period. The price remains almost similar over the year as indicated by seasonal indices. On the basis of lowest MAE, MAPE, RMSE and AIC, out of the seasonal ARIMA models we got, ARIMA (1,1,1) (0,0,2) [12] was best identified fitted model for predicting prices of Groundnut. The data analysis is done by using R ().","PeriodicalId":13334,"journal":{"name":"Indian Journal of Pure & Applied Biosciences","volume":"59 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indian Journal of Pure & Applied Biosciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18782/2582-2845.8673","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study attempted to guide the farmers and planners for reliable and specific information concerning the prices of Groundnut in the Northern Hills agro-climatic zone of Chhattisgarh. The time series data of prices was taken monthly from January, 2010 to March, 2021 (135 months) and it was used to forecast the prices for upcoming 24 months i.e. April, 2021 to March, 2023. The time trend analysis of prices of groundnut were found sharpely increasing over the study period. The price remains almost similar over the year as indicated by seasonal indices. On the basis of lowest MAE, MAPE, RMSE and AIC, out of the seasonal ARIMA models we got, ARIMA (1,1,1) (0,0,2) [12] was best identified fitted model for predicting prices of Groundnut. The data analysis is done by using R ().