Author(s): Dr. Arindam Banerjee
The monitoring of price level is important for keeping the economic condition of a country under control. This paper uses the monthly time series data on Indian Consumer Price Index (CPI) to create a forecasting model using the Box-Jenkins auto regressive integrated moving average (ARIMA) technique. This study finds the ARIMA (1,1,5) model for predicting CPI in India. The model may be used by policymakers to design the monetary and fiscal policy measures to regulate inflation in India. This paper is an attempt to create a model to forecast the price level at India. We validated the model using the monthly data from 1st January 2019 to 1st January 2020. Our model shows the forecasted Consumer Price Index has a CAGR of 6.67%, whereas the actual CAGR of CPI is 6.68% during the validation period. In the light of the deviation in target CPI and actual CPI, RBI has already decided to review the CPI-inflation targeting framework in February 2020.