Time Series Analysis of Value Added Tax Revenue Collection in Ghana
| dc.contributor.author | Edzie- Dadzie, Joseph | |
| dc.date.accessioned | 2014-03-19T17:50:43Z | |
| dc.date.accessioned | 2023-04-19T18:50:27Z | |
| dc.date.available | 2014-03-19T17:50:43Z | |
| dc.date.available | 2023-04-19T18:50:27Z | |
| dc.date.issued | 2013-05-19 | |
| dc.description | A thesis submitted to the Institute of Distance Learning, Kwame Nkrumah University of Science and Technology in partial fulfilment of the requirement for the award of Master of Science degree in Industrial Mathematics, May-2013 | en_US |
| dc.description.abstract | Economic growth is one of the major concerns of every government. In the quest to know how the Economy of Ghana is fairing through the various regimes of governance, increasing population and other factors that affects economic growth, this thesis has been purposed to study the behaviour pattern and trend in Ghana’s Domestic and Import Value Added Tax Revenue in Ghana and to choose the best model among various ARIMA models which pose’s high power of predictability for forecasting Ghana’s Real Domestic and Import VAT Revenue. Finally, the data of yearly Domestic and Import VAT revenue in Ghana from 1999 to 2009 was examined. The Box- Jenkins method of Time Series analysis was employed. The model; Y_t=〖2.0145Y_(t-1) –〖1.6275Y〗_(t-2 )+0.613Y_(t-3)+ 1.6053e〗_(t-1)-0.9999e_(t-2)+e_t+0.3402 An ARIMA (2, 1, 2) was deduced to be the best model to forecast Domestic VAT revenue in Ghana, Whilst the model; Y_t=〖0.1882Y_(t-1)+〖0.4917Y〗_(t-2 )+0.3201Y_(t-3)- 0.3196e〗_(t-1)+e_t+0.6093 An ARIMA (2, 1, 1) was deduced to be the best model to forecast Import VAT revenue in Ghana. | en_US |
| dc.description.sponsorship | KNUST | en_US |
| dc.identifier.uri | https://ir.knust.edu.gh/handle/123456789/5824 | |
| dc.language.iso | en | en_US |
| dc.title | Time Series Analysis of Value Added Tax Revenue Collection in Ghana | en_US |
| dc.type | Thesis | en_US |
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