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Univariate Time Series Forecasting: A Study on Monthly Tax Revenue of Bangladesh

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dc.contributor.author Nandi, Biplob Kumar
dc.contributor.author Chaudhury, Muntasir
dc.contributor.author Hasan, Gazi Quamrul
dc.date.accessioned 2018-11-22T04:24:21Z
dc.date.available 2018-11-22T04:24:21Z
dc.date.issued 7/1/2015
dc.identifier.uri http://dspace.ewubd.edu/handle/2525/2886
dc.description.abstract In recent years, Bangladesh has taken various steps to modernize tax system in order to enhance tax effort. Due to subsequent increase in financial constraints globally, economy's reliance on domestic resource mobilization continues to intensify. As a result, tax revenue target for every forthcoming budget appears to be buoyant albeit the prevalence of domestic constraints, i.e. inefficiencies in tax system, narrower tax base along with numerous exemptions and political instability. To enhance tax effort to reduce fiscal vulnerability, a esoteric revenue forecasting procedure is necessary. But, in Bangladesh, during the budget preparation, the method to target tax revenue is based on the growth rate extended with discretionary adjustments for a number of updated assumptions and personal judgments, which can lead to huge forecast error. This exercise attempts to identify an appropriate model by scrutinizing three approaches - ARIMA SARIMA multiplicative approach, Holt-Winters seasonal multiplicative approach and Holt-Winters seasonal additive approach - to forecast monthly tax revenue of Bangladesh and finds that, Holt-Winter seasonal multiplicative approach is the most appropriate method with minimum forecast error. en_US
dc.language.iso en_US en_US
dc.publisher East West University en_US
dc.subject Tax revenue forecasting, Box-Jenkins Method, ARIMA, SARIMA. Holt-Winters seasonal multiplicative approach, Holt-Winters seasonal additive approach en_US
dc.title Univariate Time Series Forecasting: A Study on Monthly Tax Revenue of Bangladesh en_US
dc.type Article en_US


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