Modeling and Forecasting GDP of India: ARIMA Model

The present study aims at estimating and forecasting of GDP in India. Quarterly time series data on GDP from Q1 of financial year 2004–05 to Q1 of financial year 2014–15 are used for estimation and forecasting. The study begins with Augmented Dickey Fuller unit root test and it is found that the time series data is stationary at second difference but not normally distributed. The series is integrated of order two. Later, GDP is estimated and forecasted by applying ARIMA model. In the present study fourauto regressive models are developed and it is found that ARIMA (5,2,4) is the best fit model in predicting the GDP when compared to ARIMA (5,2,5), ARIMA (5,2,6) and ARIMA (5,2,7). Forecasting GDP using the ARIMA model is carried out for In-sample (Dynamic Forecasting). The study shows that the forecasted values are close to the actual values thus minimising the forecasting error.