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- W3039916178 abstract "For every country in over the world, tax revenues appear to be the main engines contributing to the growth momentum. The prediction of tax revenues is one of the main challenges of the Myanmar Internal Revenue Department. It is not easy to get an accurate prediction of the tax revenues of the coming financial year. This is an important issue because the obtained results are used in the decision making of the target budget for the coming year's revenues. In this paper, a model of time series analysis based on Autoregressive Moving-Average (ARMA) for the forecast of the tax revenue collection is introduced. The results were more accurate in comparison to the outcome of the IRD that is estimated with the traditional estimation method. ARMA models are constructed for the prediction of each of four different tax revenues, income tax, commercial tax, lottery tax, and stamp duties. Although the proposed method is applied to four main types of tax revenues, only forecasting of commercial tax revenues is found out in the experiments of this paper. The results show that the error rate reduces to one-third of the traditional forecasting method of the Internal Revenue Department." @default.
- W3039916178 created "2020-07-10" @default.
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- W3039916178 date "2020-07-01" @default.
- W3039916178 modified "2023-09-24" @default.
- W3039916178 title "ARMA Model for Revenue Prediction" @default.
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- W3039916178 doi "https://doi.org/10.1145/3406601.3406617" @default.
- W3039916178 hasPublicationYear "2020" @default.
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