the uncertainty evaluation of tax revenue forecast in iran using a fan chart

The present study aimed to analyze the forecast error of the tax revenue forecasting in iran using the fan chart method. to this end, the tax revenue of iran was forecasted utilizing the data obtained during 1974-2016, as well as bayesian linear regression model. then, the uncertainty of such a tax revenue was derived from the uncertainty in correlated macroeconomic variables. in addition, the tax revenue forecast skewness was obtained by internalizing the subjective assessments of macro variables. in most cases, the uncertainty of macro variables is based on their historical standard deviation. however, in the present study, the uncertainty of macro variables was subjectively adjusted in order to find the reason for less or more uncertainty compared to their historical standard deviations. a subjective balance of risk assessment was applied to identify whether the distributions were symmetric or non-symmetric. the results revealed that the fan chart method has high efficiency in depicting the forecast uncertainty of tax revenue and thus can be used in the budget preparation and formulation in iran.