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Forecasting cotton (Gossypium spp.) prices in major Haryana markets: A time series and ARIMA approach

Indian Agricultural Research Journals

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Title Forecasting cotton (Gossypium spp.) prices in major Haryana markets: A time series and ARIMA approach
 
Creator KUMAR, AJAY
KUMAR, VINAY
CHETNA
GHALAWAT, SUMAN
KAUR, JASPREET
KUMARI, KHUSHBU
SAHARAN, HIMANSHU
CHHABRA, SHUBHI
RAI, BASANT
 
Subject Autocorrelation, Coefficient of determination, Differencing, Partial autocorrelation function, Price forecast
 
Description Economic outputs are an attractive prospect in any field and hence agriculture also relies heavily on economic stability. The costs associated with cotton farming are increasing and profitability is taking a hit in cotton cultivation. Timely and accurate forecast of the price helps the farmers switch between the alternative nearby markets to sale their produce and getting good prices. Present study was carried out during 2022 to 2023 in Haryana to provide some insights into the possible future prices of cotton (Gossypium spp.) with the help of data collected from AGMARKNET and various major cotton markets (Adampur, Sirsa and Fatehabad) of Haryana. The Autoregressive Integrated Moving Average (ARIMA) models have been employed in order to forecast the prices of cotton crops for the years 2022–23 to 2027–28. Through a meticulous exploration of various combinations of lagged moving average and autoregressive components, the ARIMA (1,1,1) model was selected as the most suitable for the price forecasting in these districts. The results of this analysis demonstrate that the coefficient of determination (R2) for the forecasted cotton crop prices in comparison to the real-time prices falls within acceptable ranges. This finding underscores the efficacy of the ARIMA (1,1,1) model as a reliable tool for generating short-term price estimates. This model offers valuable insights and predictive accuracy, aiding decision-makers and stakeholders in the cotton industry of Adampur, Sirsa and Fatehabad markets to make informed choices and plan effectively for the coming years. Cotton prices vary according to the season and the region, hence a valuable insight on future price assumptions will help the agriculture community.
 
Publisher Indian Council of Agricultural Research
 
Date 2024-09-11
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier https://epubs.icar.org.in/index.php/IJAgS/article/view/150524
10.56093/ijas.v94i9.150524
 
Source The Indian Journal of Agricultural Sciences; Vol. 94 No. 9 (2024); 1013–1018
2394-3319
0019-5022
 
Language eng
 
Relation https://epubs.icar.org.in/index.php/IJAgS/article/view/150524/55819
 
Rights Copyright (c) 2024 The Indian Journal of Agricultural Sciences
https://creativecommons.org/licenses/by-nc-sa/4.0