Autoregressive Integrated Moving Average (ARIMA) is popularly known as Box-Jenkins method. The emphasis of this method is on analyzing the probabilistic or stochastic properties of a single time series. Unlike regression models where Y is explained by X1 X2….XN regressor (like the introductory case where GDP is explained by GFC and PFC), ARIMA allows Y (GDP) to be explained by its own past or lagged values.

The previous article based on the Dickey Fuller test established that GDP time series data is non-stationary. This prevented time series analysis from proceeding further. Therefore, in this article possible solution to non-stationarity is explained.

Time series analysis works on all structures of data. It comprises of methods to extract meaningful statistics and characteristics of data. Time series test is applicable on datasets arranged periodically (yearly, quarterly, weekly or daily).