Determining the Optimal Minimum Wage in the Framework of a Stochastic Dynamic General Equilibrium Model (Case Study of Iran)

In this paper, in order to determine the optimal minimum wage policy in Iran, in the framework of the new Keynesian theory, a Dynamic Stochastic General Equilibrium (DSGE) model was estimated for a small and open oil-exporting economy, according to the structure of Iran's economy in the time range of 1190 to 2019. In this model, the nominal rigidity and work habits in the supply and demand sectors are considered, and in order to simulation the economic conditions of the country, meanwhile classify the labor market in two parts; the skilled  (whose maximizes its wage based on its utility) and  unskilled labor, the model has  considered to four parts. The main purpose of this study is to answer the question of determining and adjusting the annual minimum wage based on which of the indicators of inflation, the growth of the total wage and a combination of inflation indicators and productivity of production factors, in a situation where the economy is exposed to markup of wages and prices shocks, supply and the demand of the economy and monetary and financial policies, was optimal and it causes the least negative fluctuation (deviation) on macroeconomic variables including inflation, employment, production, consumption and investment. Based on this study, three scenarios were designed and the effect of minimum wage on economic variables was analyzed. The results of the simulation and estimation of this model, which indicate the matching of the moments of the simulated data with the real world data and based on calibration in all three scenarios, it shows that the selection sum of inflation growth  and the productivity indexes to adjust the minimum wage policy, although it has cyclical effects on inflation, in comparison to other scenarios, it has the least negative deviation on economic variables and can be used as an optimal indicator for choosing the minimum wage in the Supreme Labor Council of the country.