Forecasting Black Tea Auction Prices by Capturing Common Seasonal Patterns

Tea industry plays a major role in economies of tea producing countries and therefore, it is important to study the behavior of tea auction prices and forecasting tea auction prices for several months. This study investigates whether the use of common seasonal patterns improve the forecasting accuracy of black tea auction prices with a special emphasis on forecasting prices of the Colombo tea auction. Monthly black tea auction prices of eight auction centers were used for the analysis. Seasonally unadjusted series were tested for seasonal unit roots using the procedure proposed by Beaulieu and Miron in 1992. Seasonal unit root tests provided evidence of presence of common seasonal cycles in monthly black tea auction prices of Colombo, Kolkata and Guwahati centers at six cycles per year. A seasonal cointegration relationship was identified in aforesaid three tea auction prices which made it possible to fit a Seasonal Error Correction Model (SECM). Similar analysis was carried out for seasonally adjusted data. It was found that all three seasonally adjusted series were I(1) and therefore, series were tested for cointegration relationships. A cointegration relationship among these series was evident and hence Vector Error Correction (VEC) model was fitted. Adequacy of the fitted SECM and VEC models were tested, and unit root tests and correlograms suggested that the error series were stationary. Using the fitted SECM and VEC models, prices for several months were forecasted. The accuracy of the forecasts was tested using Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE). Both measures confirmed that seasonally unadjusted model produces more accurate forecasts than those obtained from the other model, during the study period.