Predicting Iran's economic growth rate using meta-analysis method

One of the most important issues for governments to maintain and improve their position in the regional and global economy is the state of economic growth; one of the important issues in this situation is to predict the rate of economic growth. Proper forecasting of economic growth has very important effects on government policy and economic planning, and can help policymakers decide on future decisions in addition to creating opportunities for development. This study predicts Iran's economic growth rate using the Meta-analysis method and compares it with other methods. For this purpose, the results of ANFIS, ARIMA, Markov switching methods, future research and Gary Markov, ECM, fuzzy regression, accounting approach related to economic growth forecasting from 1383 to 1392 (except for forecasting values ​​with accounting approach that until 1395 Used). The fixed and random weights of each of the previous studies have been determined using fixed and random effects and have been used using the Meta-analysis method for forecasting. The results show that the accuracy of the Meta-analysis method is much higher than other methods and has the lowest difference with real data. Therefore, it is recommended to use the combined Meta method to increase the reliability coefficient of accurate forecasting.