Analysis of the Effects of Economic Variables on the Price of Cement and Forecasting its Price Trend

The present study aims to identify the variables affecting the price of cement and provide in- and out-of-sample forecasts using monthly data from 2019:03 to 2023:02 and a vector autoregression (VAR) model. In this regard, according to the results of the Johansen-Juselius cointegration test, the long-term relationship between the variables was confirmed. Then, the long-term and short-term models were estimated, and the error correction coefficient was -0.0858. In the next stage, based on the results of impulse response functions, exchange rate and construction input price index shocks (respectively with a positive effect of 8 and 6.8 percent in the standard form) have been more effective than other model variables on the fluctuations of cement price. The results of variance decomposition also showed that the construction input price index, energy cost, and exchange rate are important in explaining the price of cement. Finally, we estimated in-sample and out-of-sample forecasts. Based on the forecast evaluation criteria, our founding research model can accurately predict the price trend of cement.