Analysis of Coffee Exports of Uganda Using An Arima Model from 1990 To 2018
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This study was to investigate the general trend of coffee export in Uganda from 1990 to 2017 and to construct an autoregressive model of a suitable order for the process. The test statistics used in this research were autocorrelation function, autoregressive model and partial autocorrelation function. It was also discovered that among the test statistic used in this research, the forecast for the series was best obtained using the autoregressive of order one AR (1). The goal of this study was to develop a methodology for the investigation of the trend and to forecast the fish exports using an ARIMA (autoregressive integrated moving average) model. A final model, based on the coffee export, was constructed from a number of tentative models identified by examining the ACF (autocorrelation function) plots and the PACF (partial autocorrelation function) plots. This underpins the development of a time series model for forecasting Coffee Exports in Uganda. Several time series models including AR, MA, ARMA, ARIMA and SARIMA were fitted to the data, and it emerged that the most adequate model for the data was ARIMA (1, 1, 0). There will be increase in the receipts from coffee export in the next ten years The government has put-up a policy of increasing Uganda export of coffee with the target of 20 million bags by 2020, to achieve this target Uganda governments should Increase and sustainable production and yield at the farm level. Encourage coffee production in new areas and expand acreage in traditional coffee areas. Improve the use of agro inputs in coffee production. Promote the availability of water for production at farm level. Promote coffee farming as a business among small holder farmers. Service delivery shall be guided by the needs of all actors in the value chain and Government of Uganda should subsides the local farmer to be able to meet their running cost, so they would be competitive in terms price in international market.