Modeling Factors Influencing Inflation Rate in Iran's Economy Using Firefly and Cuckoo Algorithm

Inflation, as one of the economic phenomena, causes many negative social and cultural consequences such as poverty, disproportionate distribution of income and the spread of financial distress, which in turn imposes significant costs on the economy. For this reason, price stability is considered as the main goal of economic planning and policy in all countries. Therefore, it is important to study and predict this macroeconomic variable. In this regard, various predictive models have been developed in competition with each other. One of these methods is evolutionary algorithms, which is a new method for modeling and predicting various phenomena. In the present study, using the Firefly and Cuckoo algorithm, and employing variables that affect inflation, including liquidity, exchange rate, real interest rate, expected inflation and industrial output during the period of 1975-2015, we attempt to model inflation linearly and non-linearly. The results show that the nonlinear model is more suitable for inflation modeling, and the Firefly algorithm is better than Cuckoo algorithm. According to the precision of the non-linear model developed by Firefly algorithm, it can be used to forecast inflation in the future.