Modelling and Forecasting of Meat Exports from India
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In the present study, seasonal autoregressive integrated moving average (SARIMA) methodology has
been applied for modelling and forecasting of monthly export of meat and meat products from India.
Augmented Dickey-Fuller test has been used for testing the stationarity of the series. Autocorrelation
(ACF) and partial autocorrelation (PACF) functions have been estimated, which have led to the
identification and construction of SARIMA models, suitable in explaining the time series and forecasting
the future export. The evaluation of forecasting of export of meat and meat preparations has been carried
out with root mean squares prediction error (RMSPE), mean absolute prediction error (MAPE) and
relative mean absolute prediction error (RMAPE). The residuals of the fitted models were used for the
diagnostic checking. The best identified model for the data under consideration was used for out-of-sample
forecasting along with the upper and lower 95 per cent confidence interval up to the year 2013.