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dc.contributor.authorMatovu, Richard Fulugensio
dc.date.accessioned2019-09-02T09:10:52Z
dc.date.available2019-09-02T09:10:52Z
dc.date.issued2019-08
dc.identifier.urihttp://hdl.handle.net/20.500.12281/6388
dc.descriptionA dissertation submitted to the school of statistics and planning in partial fulfillment of the requirements for the award of the degree of bachelor of Science in Quantitative Economics of Makerere Universityen_US
dc.description.abstractThe objective of this study was to analyse the fish exports of Uganda between 2010 and 2018. The assessment was made on the amount of fish and fish products that cross borders coming from Uganda. The software used in the analysis was Stata, R studio and Microsoft Excel. The analysis was done at four different stages. Stage one investigated the nature of the fish exports that is, stationarity and seasonality. Stage two looked at the statistical relationship (correlation) between the observations which was plotted on a correlogram. Stage three identified candidate ARIMA models from which the best candidate model ARIMA(1,1,9) was chosen basing on the principle of parsimony. Stage four involved checking the statistical significance of the model through the diagnostic tests. The test was based on the ACF and PACF for the residuals which showed that the model was a perfect fit for modelling. The results revealed that fish exports between 2010 and 2018 were trended. Between 2010 and mid-2014, they exhibited a downward trend and from mid-2014 to 2018, they exhibited an upward trend. This was proven by the Augmented Dickey Fuller unit root test and the line plots. However, fish exports were made stationary by first differencing. Fish exports were modeled using ARIMA(1,1,9) with the first term representing the Auto Regressive order, the second term representing the level of differencing, and the third term showing the Moving Average order. The forecasts for the period 2019 to 2020 also exhibited an upward trend. In addition, the fish exports also exhibited seasonality. This was evidenced in a line plot by the same variations throughout every year. It was identified that at the start and end of the year, that is during January, February, November and December, fish exportation was at its highest within each year and mid-way the year, the fish exports were averagely much lower. In conclusion, the two null hypotheses were rejected. The fish exports were found to be trended and had seasonality. Forecasts for the 2019 and 2020 were made. The study recommends that URA develops a friendlier tax policy on exporting fish and fish products, the government should adopt the price floor for fish exports, and the government should set up more associations responsible for looking for more international fish markets in order to widen the market for fish exports.en_US
dc.language.isoenen_US
dc.publisherMakerere Universityen_US
dc.subjectFish exports of Ugandaen_US
dc.titleA time series analysis of fish exportation in Ugandaen_US
dc.title.alternative(2010 – 2018)en_US
dc.typeThesisen_US


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