Optimization and Simulation (Monte Carlo) of the Impact of Productivity Shocks on GDP of Iran using the Advanced Algorithms Approach

• Main Authors: Ramin Jamshidi Dehnavi, Mohsen Zayandeh Roodi, Sayed AbdolMajid Jalaee, Ali Raees Poor
• Format: Article
• Language: fas
• Published: University of Tehran 2017-07-01
• Series: مدیریت صنعتی
• Subjects: Advanced algorithm; GDP; Monte Carlo simulation; Optimization; Productivity shocks
• Online Access: https://imj.ut.ac.ir/article_64585_77f7903ec7e2251b2ccd75c6a1740c1b.pdf
• ISSN: 2008-5885; 2423-5369

In this paper, the impact of productivity shocks on GDP using advanced algorithm approach and the Monte Carlo simulation in the Iranian economy has been surveyed. After reviewing the theoretical and experimental studies, the variables of inflation, unemployment, potential production and productivity shocks are selected as the variables explaining the variable of gross domestic product. Using three algorithms of fireflies, cuckoo, and particle swarms optimization, the coefficients of each of the independent variables were estimated. After estimating the coefficients and given the uncertainty of the estimated coefficients by the advanced algorithms, Monte Carlo method was used to simulate the equations. Comparing the findings obtained from the simulation and findings of the estimation indicate the high accuracy of the findings obtained from estimates. Given the obtained findings, productivity shocks had very little impact on GDP and the potential production was introduced as the most influential variable.