AN ECONOMIC ANALYSIS OF PRICE BEHAVIOUR OF ONION IN MAJOR MARKETS OF INDIA
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Date
2018
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Acharya N.G. Ranga Agricultural University
Abstract
The Present study entitled “An economic analysis of price behaviour
of onion in major markets of India” was undertaken to study the price
trends of onion, price forecasts and price volatility in selected markets of
India. Three markets viz., Lasalgaon, Bangalore and Kurnool were selected
based on maximum arrivals. The data pertained to the period from 2003 to
2017.
Time series analysis was employed for studying the price behavior of
onion for each market. ARIMA, trend analysis, moving average, single
exponential smoothing, double exponential smoothing, winter’s
multiplicative model, decomposition fit and Artificial Neural Network
(ANN) were used for forecasting of prices. Autoregressive Conditional
Heteroscedasticity (ARCH) and Generalized Autoregressive Conditional
Heteroscedasticity (GARCH) models are used for analyzing price
volatility.
The annual increase in prices of onion was found to be the highest in
Lasalgaon market (7.33 Rs/qtl) whereas it was the lowest in Kurnool
market (6.22 Rs/qtl). Bangalore and Kurnool were found to be statistically
significant at 1 per cent level of significance. In these three markets, the
contribution of time to change in prices was to the tune of 19 per cent to 26
per cent as indicated by adj-R2.
In Lasalgaon market the highest seasonal index was found in
October, followed by November and August and the indices stood at
149.01, 139.30 and 122.76 respectively. Lowest seasonal index was
recorded in May with 57.23. In Maharashtra harvesting of kharif season
onion crop started from October to December. Hence, kharif crop starts
arriving at the market in small quantities during the first fortnight of
October. The prices in October reach their highest of all the months. It is
mainly for the reason that stocks made from earlier rabi season dwindling
and there are still some time for main kharif onion crop to enter the market.
The limited arrivals fetch a good price and normally the prices during this
month are rewarding. Even in November and December months also have
highest prices, this is true because farmer respond to the higher prices and
bring more produce to sale at market. In Bangalore market the highest
seasonal index was found in November, followed by January and August as
the indices stood at 130.94, 115.90 and 115.66 respectively. Lowest
seasonal index was recorded in April with 70.91. In Kurnool market the
highest seasonal index was found in August, followed by November and
July as the indices stood at 140.80, 121.31 and 117.07 respectively. Lowest
seasonal index was recorded in May with 62.72. In Bangalore and Kurnool
markets the early kharif crop starts arriving the market in August month.
And the late kharif crop hits the market in October and November months.
These months where highest onion arrivals present also have the highest
prices. From the results it was found that no price cycles were identified in
the selected markets (Lasalgaon, Bangalore and Kurnool) of India for onion
crop. Irregular fluctuations did not exhibit any definite periodicity in their
occurrence in the Lasalgaon, Bangalore and Kurnool markets.
The ARIMA model (0,1,1) (2,1,1) was found to fit the series
suitably to forecast prices of onion in Lasalgaon market. According to the
forecasts the price of onion would be ranging from Rs. 2879 to Rs. 2748
per quintal for the months from January to June 2018. The ARIMA
model (1,1,0) (1,1,1) was found to fit for forecast prices in Bangalore
market. According to the forecasts the price of onion would be ranging
from Rs. 3495 to Rs. 3395 per quintal for the months from January to
June 2018. The ARIMA model (1,1,1) (1,1,1) was found to fit the series
suitably to forecast prices in Kurnool market. According to the forecasts
the price of onion would be ranging from Rs. 2956 to Rs. 1651 per quintal
for the months from January to June 2018.
Price volatility results revealed that there was high volatility in onion
prices in Lasalgaon market as the sum of alpha and beta values were 0.99
next followed by Bangalore (α+β = 0.94) and Kurnool (α+β = 0.93) during
the period from 2004 to 2017. These values were very closer to one,
indicated that the volatility shocks were quite persistent in these markets.
Description
D5684
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