Constructing a Mixed frequency Data Sampling Macro Econometric Model (MIDAS - EME) to assess the impact of sanctions imposed on the Iranian economy

Document Type : Original Article

Authors

1 Associate Professor of Economics, Shahid Beheshti University

2 PhD Student of Economics, Shahid Beheshti University

Abstract

In this article we constructed a Macro Econometric Model based on Mixed frequency Data to assess the impacts of sanctions that are imposed on the Iranian economy. In doing so, a monthly index is developed to reveal the toughness of imposed sanctions throughout the time. This sanction index is a time series high frequency data which encompasses various types of economic sanctions against Iran and is used as an explanatory variable in foreign sector’s behavioral equations. The constructed model is based on economic theory and stylized facts of the Iranian economy. It contains 27 behavioral equations, 7 connecting equations and 33 identities and definitional equations. The parameters of the model are estimated using time series data for the period of 1959 to 2017. Dynamic simulations are used to confirm the model validation.  To assess the impacts of sanctions, the model is simulated under the scenario of no sanctions and the results are compared with the actual case. According to the findings of this study, the complete lifting of sanctions will have effects such as increasing aggregate demand, increasing investment, increasing production, reducing imports of goods and increasing exports of goods.

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