Cotton price behaviour and forecasting in major producing states of India
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Date
2020
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Publisher
Punjab Agricultural University, Ludhiana
Abstract
The present study has been undertaken to work out the trends in the area, production and
productivity of cotton in India, to examine the behaviour of prices, volatility and their
forecasting in major cotton markets. The study is based on secondary data. To meet the
objectives of the study, major cotton-producing states of India were selected based on their
percentage share in total cotton production. From each of the selected state, one important
market was taken for the study. Time series data regarding monthly wholesale cotton prices
and arrivals in the major markets were collected from various secondary sources. Various
statistical/econometric tools like CAGR, trend, seasonal indices, Auto-Regressive Integrated
Moving Average (ARIMA), and Auto-Regressive Conditional Heteroscedasticity and
Generalised Auto-Regressive Conditional Heteroscedasticity (ARCH-GARCH) models were
employed to analyze the data. The analysis revealed that the production and productivity of
cotton were consistently increasing significantly over the years. India was leading among all
the cotton-growing countries in the world both in area and production. The variability, both in
area and productivity of cotton contributed towards variability of cotton output in the country.
In all the study markets, a strong positive trend was observed in the prices of cotton during
the given study period (2008 – 2018). The peak period for arrivals of cotton consisted the
months of November, December, January and February and the lean period of the `arrivals
were observed in June, July, August and September. The prices during the lean period
remained relatively higher with few exceptions. The Augmented Dickey-Fuller for unit root
test showed that cotton price series were stationary on first order integration. SAS 9.3
software is used in identifying parameter estimates of the model. The adequacy of the fitted
model was tested by various measures of goodness of fit viz., AIC, BIC, Standard error and
MAPE. The best model was selected based on the relatively lower value of AIC and MAPE.
The forecast results revealed that market prices of cotton, possibly ruling in the range of Rs.
4939– 5611 per quintal in Adoni, Rs. 5238 – 5395 per quintal in Adilabad, Rs. 5527 – 5517
per quintal in Akot and Rs. 4827 – 4876 per quintal during November to March in 2019-20.
The sum of alpha and beta is 0.34 for both Adoni and Adilabad market while it is 0.36, 0.37
for Akot and Rajkot markets respectively. Hence farmers and traders can use the price
forecasting information to minimize speculation and can take advantage of the same for
additional net returns.