Predicting the Effects of New Sanctions and Evaluating Fiscal Policies in the Context of a Macroeconomic Model with Mixed-Frequency Data Sampling for the Iranian Economy Under Sanctions

In the Iranian economy, which has experienced various sanctions, it was necessary to anticipate macroeconomic variables when imposing new sanctions. On the other hand, in the context of sanctions, it is possible to make a more accurate assessment of economic policies in order to be able to respond in a timely manner to these shocks and the need for appropriate planning and security against them. Therefore, in the present study, a macroeconomic model with Mixed-frequency data sampling  has been used,While having a high accuracy in prediction, it is possible that when new information about multivariate variables is obtained, based on it, the previous prediction for the dependent variable of the pattern is revised. The model consists of 27 behavioral equations, 8 communication equations and 33 definitional and union relations and the parameters of the model are estimated using time series data in the period 1338 to 1396. Predictive results show that the use of new observations in high frequency variables in the model has led to improved accuracy in predicting the endogenous variables of the model.