FORECASTING SUGARCANE PRODUCTION IN JAMAICA USING A VECTOR AUTOREGRESSION FRAMEWORK

This research paper provides a forecast for sugarcane production in Jamaica. The sugar industry contributes to the Jamaican economy through the direct and indirect effects of payments to households for labour services and payment of various government revenues, which amounts to just over 1% of the total Gross Domestic Product (GDP) of the country. The production of sugarcane in Jamaica has shown a historical decline by a geometric rate of 3.24% per year from the peak of 4.8 million tons in 1966. Given the past performance of the industry and renewed interest in using sugarcane for ethanol production, which will potentially be use as a substitute for methyl tertiary butyl ether (MTBE) in gasoline, it was necessary to forecast changes in producers’ supply response based on the acreage reaped and price offered. Jamaica produced 1.76 million tons of mill- able sugarcane in 2006, but given the renewed interest, hopes to increase output to 3.5 million tons from an available 46,411 hectares of land. The research addresses whether the Jamaican Sugarcane industry will be able to achieve the 3.5 million ton of sugarcane given the hectare available and the price paid to the growers. A vector autoregressive (VAR) framework was employed using time series data from 1956 to 2006 to estimate the equations. A lag length of two was chosen by the Akaike Information Criteria as the specification for the model. The regression indicated that 90.6% of the variation in yield was explained by lag lengths in yield, hectare reaped and deflated price of 2 periods, with an adjusted r-square of 0.854. The Akaike Information Criteria for the VAR was 57.75 which was the best model. The study focused on the dynamic relationship which existed between yield, hectare reaped and price paid to growers in the sugarcane industry. The result indicated that response was not instantaneous but took two (2) years to adjust as was indicated by the lag length. This information can be used by industry stakeholders in industry planning and trade negotiations and also have broad applicability to other industrie