The Uncertainty Evaluation of Tax Revenue Forecast in Iran, Using Fan Chart

Abstract

In this research, we tried to analyze the forecast error of the tax revenue forecasting in Iran using the Fan chart method. In this regard, using data during the period of 1974-2016 and Bayesian linear regression model, Iran's tax revenue be forecasted and its uncertainty is derived from uncertainty in correlated macroeconomic variables. Internalizing subjective assessments of the macro variables, the tax revenue forecast skewness be obtained. In most cases, the uncertainty of macro variables' are based on their historical standard deviation. However, in the present study, we allow the uncertainty of macro variables to be adjusted subjectively, if there is a reason to be less or more uncertain than their historical standard deviations. A subjective balance of risk assessment, that whether the distributions are symmetric or non symmetric, is also used. The results show that the fan chart method has high efficiency in depicting the forecast uncertainty of tax revenue and can be used in the budget preparation and Formulation in Iran.