Econometric analysis of price dynamics of high-value seed spices in India

In this paper, the volatile price series of spices namely black pepper, cardamom and cumin are modelled and forecast using the generalized autoregressive conditional heteroscedastic (GARCH) model. For the cumin series, due to the presence of kurtosis in its residual series, we fitted the GARCH model using the t-distributed error term. For the cardamom and black pepper series, owing to their asymmetric nature, the exponential GARCH model fit best. The forecasting efficiency of these models was compared with the basic autoregressive integrated moving average (ARIMA) model in terms of the root mean square error (RMSE) and the mean absolute percentage error (MAPE). We conclude by stating a few policy implications based on our findings.