FOREACASTING OF COTTON PRICES IN MAJOR PRODUCING STATES USING ARIMA
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Abstract
Cotton is a very important commercial crop in Indian economy. India is one of the largest producer, consumer and exporter of cotton in the world. There is cotton price fluctuation from time to time due to which forecasting of cotton prices is an inevitable need which shall help the policy makers in addressing all concerns relating to its production and acreage under cultivation. Hence, the main objective of the research paper is to forecast cotton prices using secondary data pertaining to a period of 10 years from 2010-2020. The analysis of the data and thereon the prediction of cotton prices for the harvest months of 2021 (October’21 – January’22) has been done using Auto Regressive Integrated Moving Average (ARIMA) technique. The sample time series data pertains to four major cotton producing states of India, i.e. Gujarat, Maharashtra, Karnataka and Madhya Pradesh. The monthly price data relating to the states has been collected from the AGMARKNET website under the Ministry of Agriculture; Government of India. The estimation of model parameters has been done using the EViews software. The performance of the model was gauged by analysing and comparing various measures like Akaike Information Criteria (AIC), Adj R2,, volatility and significant coefficients. The results predict that the market prices of cotton in India would be ruling in the range of Rs 4869 – Rs 5973 per quintal in the kharif harvesting season, 2021-2022.
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References
- Anwar, D., Shabbir, D., Shahid, M. H., & Samreen, W. (2015). Determinants of potato prices and its forecasting: A case study of Punjab, Pakistan.
- Areef, M., Rajeswari, S., Vani, N., & Naidu, G. M. (2020). Price Behaviour and Forecasting of Onion Prices in Kurnool Market, Andhra Pradesh State. Economic Affairs, 65(1), 43-50.
- Celik, S., Karadas, K., & Eyduran, E. (2017). Forecasting the production of Groundnut in Turkey using Arima model. World, 17373490(150819), 25.
- Darekar, A. S., Pokharkar, V. G., & Datarkar, S. B. (2016). Onion price forecasting in Kolhapur market of Western Maharashtra using ARIMA technique. International Journal of Information Research and Review, 3(12), 3364-3368.
- Darekar, A., & Reddy, A. (2017). Price forecasting of maize in major states. Maize Journal, 6, 1-5.
- Darekar, A., & Reddy, A. A. (2017). Cotton price forecasting in major producing states. Economic Affairs, 62(3), 373-378.
- Kumar, R. R. (2020). Forecasting of Potato Prices in India: An Application of ARIMA Model. Economic Affairs, 65(4), 335190.
- Kumar, R. R., Gupta, A. K., & Patra, C. (2020). Jute price forecasting in Murshidabad market of west Bengal using ARIMA technique. Journal of Pharmacognosy and Phytochemistry, 9(1), 1802-1807.
- Mohapatra, S., Mohapatra, U., & Mishra, R. K. (2018). Price forecasting of groundnut in Odisha. The Pharma Innovation Journal, 7(3), 111-114.
- Nagaraja, Y. (2019). Behaviour of Arrivals and Prices of Cotton in Selected Markets of Karnataka-A Statistical Analysis (Doctoral dissertation, UNIVERSITY OF AGRICULTURAL SCIENCES GKVK, BENGALURU).
- Paul, R. K. (2014). Forecasting wholesale price of pigeon pea using long memory time-series models. Agricultural Economics Research Review, 27(347-2016-17130), 167-176.